New Materials, Intelligent Systems, and Innovative Companies

@article{dornaika_3401,

title = {Semi-supervised learning for multi-view and non-graph data using Graph Convolutional Networks},

author = {Fadi Dornaika and Jinan Charafeddine and Huaiyuan Xiao and Jingjun Bi},

url = {https://www.sciencedirect.com/science/article/abs/pii/S0893608025000978?via%3Dihub},

year  = {2025},

date = {2025-05-01},

journal = {Neural Networks},

volume = {185},

pages = {107218},

abstract = {Semi-supervised learning with a graph-based approach has become increasingly popular in machine learning, particularly when dealing with situations where labeling data is a costly process. Graph Convolution Networks (GCNs) have been widely employed in semi-supervised learning, primarily on graph-structured data like citations and social networks. However, there exists a significant gap in applying these methods to non-graph multi-view data, such as collections of images. To bridge this gap, we introduce a novel deep semi-supervised multi-view classification model tailored specifically for non-graph data. This model independently reconstructs individual graphs using a powerful semi-supervised approach and subsequently merges them adaptively into a unified consensus graph. The consensus graph feeds into a unified GCN framework incorporating a label smoothing constraint.

To assess the efficacy of the proposed model, experiments were conducted across seven multi-view image datasets. Results demonstrate that this model excels in both the graph generation and semi-supervised classification phases, consistently outperforming classical GCNs and other existing semi-supervised multi-view classification approaches. 1},

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}

@article{zhu_3394,

title = {CarNet: A generative convolutional neural network-based line-of-sight/non-line-of-sight classifier for global navigation satellite systems by transforming multivariate time-series data into images},

author = {Ni ZHU and Ruiwen He and Zhiqiang Wang},

url = {https://www.sciencedirect.com/science/article/pii/S0952197625001605?via%3Dihub},

year  = {2025},

date = {2025-04-01},

journal = {Engineering Applications Of Artificial Intelligence},

volume = {145},

pages = {110160},

abstract = {Urban environments present significant challenges to commercial Global Navigation Satellite Systems (GNSS) receivers due to degraded satellite visibility and Non-line-of-sight (NLOS) receptions. Mitigating NLOS receptions for GNSS is essential, especially for safety-critical and reliability-critical location-based applications. Traditional physical error channel propagation modeling encountered bottlenecks since the NLOS and multipath errors cannot be modeled accurately in complex urban environments. Data-driven methods show significant potential for effectively classifying GNSS Line-of-sight (LOS) and NLOS. This paper proposes the CarNet - a generative Convolutional Neural Network (CNN)-based GNSS LOS/NLOS classifier by transforming multivariate time-series data into images. CarNet comprises two modules: an image generator and an image classifier. The image generator enriches and augments the original 1-dimension feature vector into 2-dimension feature maps and the image classifier uses an inception-based CNN to realize multi-scale feature extraction and classification. The proposed architecture is trained and tested on more than 6 h of real vehicle data collected in different challenging environments (about 1.6 million samples). A thorough benchmark is conducted, comparing CarNet against the existing mainstream Artificial Intelligence (AI) methods. The results with cross-validation on unseen data indicate that CarNet achieves the highest accuracy, i.e., 81.47% while maintaining the optimal balance between precision for both classes: 83.3% for LOS and 70.99% for NLOS. Finally, positioning accuracy is assessed using a reweighting strategy based on the LOS/NLOS information predicted by CarNet. The assessment of total datasets shows that CarNet weighting can achieve the best accuracy compared to the traditional weighting schemes based on signal-to-noise ratio or satellite elevation. CarNet shows strong potential for embedding into GNSS receivers to enhance positioning accuracy in complex urban environments, benefiting a wide range of location-based applications such as autonomous driving, emergency response, and urban logistics.},

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}

@article{sebban_3242,

title = {SeeAround: an offline mobile live support system for the visually impaired},

author = {Othmane Sebban and Ahmed Azough and Mohamed Lamrini},

url = {https://www.beei.org/index.php/EEI/article/view/7904},

year  = {2025},

date = {2025-02-01},

journal = {Bulletin of Electrical Engineering and Informatics},

volume = {14},

number = {1},

pages = {485-504},

abstract = {The inability of blind or partially-sighted people to understand visual content and real-life situations reduces their standard of living, especially in a world mainly tailored for sighted individuals. Despite the progress made by certain devices to assist them in using touch, sound, or other senses, these solutions often fall short of bridging the comprehension gap. Our work proposes an intuitive, user-friendly mobile-based framework named "SeeAround" that is capable of automatically providing real-time audio descriptions of the user's immediate visual surroundings. Our solution addresses this challenge by leveraging key point detection, image captioning, text-to-speech (TTS), optical character recognition (OCR), and translation algorithms to offer comprehensive support for visually impaired individuals. Our system architecture relies on convolutional neural networks (CNNs) such as Inception-V3, Inception-V4, and ResNet152-V2 to extract detailed features from images and employs a multi-gated recurrent unit (GRU) decoder to generate word-by-word natural language descriptions. Our framework was integrated into mobile applications and optimized with TensorFlow lite pre-trained models for easy integration on the Android platform.},

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}

@article{wang_3132,

title = {Determining the equilibrium efficient frontier by proportional frontier shifting for data envelopment analysis with fixed-sum outputs},

author = {Weijiao Wang and Fei Xu and Junfei Chu and Yanhua Dong and Zhe Yuan},

url = {https://www.sciencedirect.com/science/article/pii/S0305048324001397?via%3Dihub},

year  = {2025},

date = {2025-01-01},

journal = {Omega-International Journal Of Management Science},

volume = {130},

pages = {103174},

abstract = {The equilibrium efficient frontier data envelopment analysis (EEFDEA) has been extensively used to evaluate efficiencies of the decision-making units (DMUs) with fixed-sum outputs. This study develops a new EEFDEA approach based on a proportional frontier-shifting strategy. Our approach applies an iterative procedure to find the equilibrium efficient frontier (EEF). Each iteration uses a proportional frontier-shifting model to improve an inefficient DMU to the efficient frontier by increasing its fixed-sum outputs. Meanwhile, the DMUs on the efficient frontier decrease fixed-sum outputs proportionally to ensure the total fixed-sum outputs are unchanged. Our theoretical developments show that the proportional frontier-shifting strategy is feasible and can finally obtain a unique EEF. The new approach allows DMUs to use their preferred input and output weights when determining the EEF. This generates an EEF that better aligns with real-world practices and avoids the need to construct it as a single hyperplane, as required by conventional EEFDEA methods. It also avoids unfair adjustments in fixed-sum outputs among the DMUs and eliminates the problem of peculiar efficiency evaluation results (i.e., some DMUs obtain extremely high, or infinity, efficiencies). Finally, we apply our approach to a case study of Chinese vehicle industry companies to demonstrate its usefulness and compare it with the previous representative approach.},

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tppubtype = {article}

}

@article{can_3151,

title = {Institutional pressures and greenwashing in social responsibility: reversing the link with hybridization capability},

author = {Ozge Can and Duygu Türker},

url = {https://www.emerald.com/insight/content/doi/10.1108/MD-10-2023-1790/full/html},

year  = {2025},

date = {2025-01-01},

journal = {Management Decision},

volume = {63},

number = {1},

pages = {187-216.},

abstract = {Purpose



Despite the ongoing scholarly interest in greenwashing, it is not well known the impact of multiple institutional pressures on greenwashing in corporate social responsibility (CSR). Following the institutional logics perspective, this study investigates how three distinct logics - commercial, public, and social welfare - drive greenwashing and whether organizational capability for blending diverse CSR expectations reverses this link.

Design/methodology/approach



The current study conceptualized and tested an original model on how three institutional logics influence greenwashing in CSR, with the mediation effect of hybridization capability as a response to logic plurality. Partial least squares structural equation modeling was performed on a survey data, which was collected from 150 middle managers in Turkey.

Findings



The results show that while commercial logic has no direct or indirect impact on greenwashing, public and social welfare logics drive greenwashing in CSR. However, these effects are reversed when the CSR hybridization capability increases.

Practical implications



This study contributes to the understanding of what predicts CSR greenwashing by integrating a comprehensive theoretical framework involving multiple institutional logics, conflicting stakeholder demands, and organizational hybridity.

Originality/value



To the best of our knowledge, this is the first study that theoretically and empirically analyzed how the exposure of multiple external pressures affects the CSR greenwashing and how it can be reversed by CSR hybridization capability. This capability mitigates the threats and challenges of multiple logics and turns them into an opportunity to gain legitimacy in the eyes of stakeholders by preventing greenwashing.},

keywords = {},

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}

@article{dornaika_3269,

title = {Unified Multi-view Data Clustering: Simultaneous Learning of Consensus Coefficient Matrix and Similarity Graph},

author = {Fadi Dornaika and Sally El Hajjar and Jinan Charafeddine and Nagore Barrena},

url = {https://link.springer.com/article/10.1007/s12559-024-10392-z},

year  = {2025},

date = {2025-01-01},

journal = {Cognitive Computation},

volume = {17},

number = {38},

abstract = {Integrating data from multiple sources or views has become increasingly common in data analysis, particularly in fields

like healthcare, finance, and social sciences. However, clustering such multi-view data poses unique challenges due to the

heterogeneity and complexity of the data sources. Traditional clustering methods are often unable to effectively leverage the

information from different views, leading to suboptimal clustering results. To address this challenge, multi-view clustering

techniques have been developed, aiming to integrate information from multiple views to improve clustering performance.

These techniques typically involve learning a similarity matrix for each view and then combining these matrices to form

a consensus similarity matrix, which is subsequently used for clustering. However, existing approaches often suffer from

limitations such as the need for manual tuning of parameters and the inability to effectively capture the underlying structure

of the data. In this paper, we propose a novel approach for multi-view clustering that addresses these limitations by jointly

learning the consensus coefficient matrix and similarity graph. Unlike existing methods that follow a sequential approach

of first learning the coefficient matrix and then constructing the similarity graph, our approach simultaneously learns both

matrices, ensuring a more regularized consensus graph. Additionally, our method automatically adjusts the weight of each

view, eliminating the need for manual parameter tuning. Our approach involves several key steps. First, we formulate an

optimization problem that jointly optimizes the consensus coefficient matrix, unified spectral projection matrix, coefficient

matrix, and soft cluster assignment matrix. We then propose an efficient algorithm to solve this optimization problem, which

involves iteratively updating the matrices until convergence. To learn the consensus coefficient matrix and similarity graph, we

leverage techniques from matrix factorization and graph-based learning. Specifically, we use a self-representation technique

to learn the coefficient matrix (regularization graPh) and a graph regularization technique to learn the similarity graph. By

jointly optimizing these matrices, we ensure that the resulting consensus graph is more regularized and better captures the

underlying structure of the data. We evaluate our approach on several public image datasets, comparing it against state-of-the-

art multi-view clustering methods. Our experimental results demonstrate that our approach consistently outperforms existing

methods in terms of clustering accuracy and robustness. Additionally, we conduct sensitivity analysis to evaluate the impact

of different hyperparameters on the clustering performance. We present a novel approach for multi-view data clustering

that jointly learns the consensus coefficient matrix and similarity graph. By simultaneously optimizing these matrices, our

approach achieves better clustering performance compared to existing methods. Our results demonstrate the effectiveness and

robustness of our approach across different datasets, highlighting its potential for real-world applications in various domain.},

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}

@article{abou_ali_3271,

title = {Enhancing Generalization and Mitigating Overfitting in Deep Learning for Brain Cancer Diagnosis from MRI},

author = {Mohamad Abou Ali and Jinan Charafeddine and Fadi Dornaika and Ignacio Arganda?Carreras},

url = {https://link.springer.com/article/10.1007/s00723-024-01743-y},

year  = {2025},

date = {2025-01-01},

journal = {Applied Magnetic Resonance},

abstract = {Brain cancer represents a significant global health challenge with increasing inci-

dence and mortality rates. Magnetic Resonance Imaging (MRI) plays a pivotal role

in early detection and treatment planning. This study adopts a systematic approach

across four phases: (1) Optimal Model Selection using the Adam optimizer, empha-

sizing accuracy metrics, weight computation, early stopping, and ReduceLROn-

Plateau techniques. (2) Real-world Scenario Simulation through synthetic per-

turbed datasets created by applying noise, blur (to simulate various magnetic field

strengths: 1T, 1.5T, 3T), and patient motion artifacts (mimicking MRI scanning

motion effects) to the testing data from the BT-MRI dataset, an online published

brain tumor MRI dataset. (3) Optimization involving a range of optimizers (Adam,

Adagrad, Nadam, RMSprop, SGD) and online augmentation techniques (AutoMix,

CutMix, LGCOAMix, PatchUp). (4) Solution Exploration integrating Gaussian

Noise and Blur as augmentation strategies during training to enhance model gener-

alization under diverse conditions. Initial evaluations achieved strong performance,

consistently reaching 99.45% accuracy on the BT-MRI dataset. However, testing

against synthetic perturbed datasets mimicking real-world conditions revealed chal-

lenges in maintaining robust model performance. Despite employing diverse opti-

mization methods and advanced augmentation techniques, this study identifies per-

sistent challenges in ensuring model robustness with synthetic perturbed datasets.

Notably, the integration of Gaussian Noise and Blur during training significantly

improved model resilience. This research underscores the critical role of method-

ological rigor and innovative augmentation strategies in advancing deep learning

applications for precise brain cancer diagnosis using MRI.},

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}

@article{hentati_3277,

title = {Experimental study on the temperature effect and constitutive modeling of the tensile response of PC/ABS blend},

author = {FATMA HENTATI and RIDHA MNIF and Naila Hfaiedh and Johann Petit},

url = {http://dx.doi.org/10.1007/s00289-024-05631-0},

year  = {2025},

date = {2025-01-01},

journal = {Polymer Bulletin},

abstract = {This study investigates the tensile properties of the PC/ABS blend under both small

and large strains using experimental analysis and predictive analytical models. The

influence of temperature and strain rate on the tensile response were evaluated, with

strain rates reaching from 1.25 × 10?

4 to 1.25 × 10?

1 s?

1 and temperatures ranging

from 20 to 150 °C. The experimental results indicate that the tensile behavior of

the material blend exhibits sensitivity to both strain rate and temperature. As the

temperature rises, the yield strength and strain at failure decrease significantly;

while, the young's modulus only slightly decreases. Among several constitutive

models studied, including the G'sell and Jonas and Duan-Saigal-Greif-Zimmerman

(DSGZ) models, a modified version of the DSGZ model, referred to as the

?Zhu et al.? model. However, this model struggled to accurately represent material

behavior at elevated temperatures. To address this limitation, a new model named

Hentati-Mnif-Hfaiedh-Petit (HMHP) was developed by introducing a temperature

dependence into two key parameters of the ?Zhu et al.? model. This improvement

enabled the HMHP model to more accurately predict tensile behavior across a wide

temperature range. The results confirm that the new developed model, HMHP provides

a reliable prediction of tensile properties at different temperatures.},

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}

@article{chu_3285,

title = {Balancing contributions and rewards: a DEA approach for fair carbon emission abatement allocation},

author = {Junfei Chu and Yanhua Dong and Zhe Yuan and Fangqing Wei},

url = {http://dx.doi.org/10.1080/01605682.2024.2449470},

year  = {2025},

date = {2025-01-01},

journal = {Journal Of The Operational Research Society},

pages = {1-16},

abstract = {Fairness is imperative in implementing carbon emission abatement (CEA) allocation schemes. This study introduces a new data envelopment analysis (DEA) methodology for the fair distribution of CEA among decision-making units (DMUs), taking into account their individual fairness. First, we establish a model to determine the maximum CEA potential for each DMU. Subsequently, an environmental efficiency evaluation model is presented to estimate a DMU's maximum potential desirable output increment (referred to as individual reward) based on its CEA level (defined as individual contribution). The individual fairness index is then defined as the ratio of individual reward to individual contribution. A convergence of individual fairness indexes among DMUs indicates higher perceived fairness in the CEA allocation. To promote fairness, we propose a centralized CEA allocation model that maximizes the minimum individual fairness index among DMUs, aiming to minimize disparities. Our contribution lies in formulating the concept of individual fairness within the DEA-based CEA allocation paradigm and introducing an approach to generate a CEA allocation result that embodies fairness. Lastly, the proposed approach is applied to a case study involving 38 OECD countries, demonstrating its superiority in achieving equitable CEA allocation results.},

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}

@article{abdolmaleki_3315,

title = {On Quantum Simulation-Soundness},

author = {Behzad Abdolmaleki and Céline Chevalier and Ehsan Ebrahimi and Giulio Malavolta and Quoc Huy VU},

url = {http://dx.doi.org/10.62056/a66ce0iuc},

year  = {2025},

date = {2025-01-01},

journal = {IACR Communications in Cryptology},

volume = {1},

number = {4},

abstract = {Non-interactive zero-knowledge (NIZK) proof systems are a cornerstone of modern cryptography, but their security has received little attention in the quantum settings. Motivated by improving our understanding of this fundamental primitive against quantum adversaries, we propose a new definition of security against quantum adversary. Specifically, we define the notion of quantum simulation soundness (SS-NIZK), that allows the adversary to access the simulator in superposition.



We show a separation between post-quantum and quantum security of SS-NIZK, and prove that Sahai's construction for SS-NIZK (in the CRS model) can be made quantumly-simulation-sound. As an immediate application of our new notion, we prove the security of the Naor-Yung paradigm in the quantum settings, with respect to a strong quantum IND-CCA security notion. This provides the quantum analogue of the classical dual key approach to prove the security of encryption schemes. Along the way, we introduce a new notion of quantum-query advantage functions, which may be used as a general framework to show classical/quantum separation for other cryptographic primitives, and it may be of independent interest.},

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pubstate = {published},

tppubtype = {article}

}

@article{aloosh_2899,

title = {Direct Evidence of Bitcoin Wash Trading},

author = {Arash Aloosh and Jiasun Li},

url = {https://pubsonline.informs.org/doi/abs/10.1287/mnsc.2021.01448?af=R},

year  = {2024},

date = {2024-12-01},

journal = {Management Science},

volume = {70},

number = {12},

pages = {8875-8921},

abstract = {We use the internal trading records of a major Bitcoin exchange leaked by hackers to detect

and characterize wash trading ? a type of market manipulation in which a single trader clears

her own limit orders to ?cook? transaction records. Our finding provides direct evidence for

the widely-suspected ?fake volume? allegation against cryptocurrency exchanges, which has

so far only been backed by indirect estimation. We then use our direct evidence to evaluate

various indirect techniques for detecting the presence of wash trades and find measures based on

Benford's law, trade size clustering, lognormal distributions, and structural breaks to be useful,

while ones based on power law tail distributions to give opposite conclusions. We also provide

suggestions to effectively apply various indirect estimation techniques.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ben_eleuchi_2941,

title = {Effect of friction coefficients and extrapolation laws on springback prediction of HSLA420 Steel},

author = {Slim Ben Eleuchi and Seddik Shiri and Mohamed Guerich},

url = {http://www.jomac.it/index.php?id=2024b_05},

year  = {2024},

date = {2024-12-01},

journal = {International Journal of Mechanics and Control},

volume = {25},

number = {2},

pages = {39-45},

abstract = {The high strength steels are widely used especially for the metal stamping. This process could have important differences with the desired geometry due to the springback phenomenon. The numerical simulation of the stamping and springback is widely adopted in automotive industry. The accurateness is highly dependent on numerical techniques as well as process parameters. Among the parameters that affect the precision, we can mention: the bending radius-thickness ratio, the friction coeffcients, the yield loci, the finite element formulation, the damage ... In this work, the effects of friction coefficients and the extrapolation laws on springback numerical prediction are investigated. The accuracy of this work is demonstrated through the industrial stamping process of an automotive part with High-Strength low-alloy steel HSLA420. The numerical results are obtained with the Pam-stamp 2G. It was shown that the extrapolations of the laws have the same order of influence as the friction coefficients},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ahmed_3081,

title = {Digital leadership and innovative work behavior: impact of LMX, learning orientation and innovation capabilities},

author = {Farooq Ahmed and M. Muzamil Naqshbandi and Mehwish Waheed and Noor Ul-Ain},

url = {https://www.emerald.com/insight/content/doi/10.1108/MD-04-2023-0654/full/html},

year  = {2024},

date = {2024-12-01},

journal = {Management Decision},

volume = {62},

number = {11},

pages = {3607-3632},

abstract = {Purpose - Grounded in the Social Exchange theory, this study focuses on the perception of digital leadership

and innovative work behaviors. It also examines the complex effects of leader-member exchange, learning

orientation, and innovation capabilities.

Design/methodology/approach - We undertake a quantitative approach using a two-wave longitudinal

field survey of 440 employees and managers from various backgrounds working in the automobile industry in

France.

Findings - The findings based on Structural Equation Modeling reveal that the perception of digital

leadership leads to innovative work behavior while leader-member exchange moderates between the

perception of digital leadership and learning orientation. The findings also support the mediating roles of

learning orientation and innovation capabilities.

Originality/value - The study contributes important policy suggestions, raises queries for additional

investigation, and suggests theoretical and practical implications for leadership and organizational

environmental factors to foster innovative work behaviors in organizations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{zhang_3170,

title = {Robotic warehouse systems considering dynamic priority},

author = {Zhengmin Zhang and Yeming Gong and Zhe Yuan and Wanying Chen},

url = {https://www.sciencedirect.com/science/article/pii/S1366554524003703?via%3Dihub},

year  = {2024},

date = {2024-12-01},

journal = {Transportation Research Part E-Logistics And Transportation Review},

volume = {192},

pages = {103779},

abstract = {The research proposes a new methodological framework based on dynamic priority to handle different order classes in robotic warehouse systems. Traditional static priority methods in facility logistics may cause low-priority orders to experience excessive delays and fail to ensure fairness. Our dynamic priority approach addresses this fairness issue by adjusting priorities over time to fulfill orders within promised times, ensuring both high-priority orders and long-waiting low-priority orders receive timely attention. We present stochastic models of dynamic priority queueing networks to describe warehouse systems and estimate throughput times. Experiments validate the analytical stochastic models, and experimental results indicate that the dynamic priority model achieves shorter delay times than the static priority model and the FCFS model. We propose design insights based on experimental results and provide an approach to select the optimal robot number. Furthermore, by employing a fairness index, we develop a new decision support tool for determining warehouse configurations with requested performance objectives. Experimental results demonstrate that dynamic priority can ensure fairness across a wider range of scenarios. Additionally, with insufficient pickers, the system performs better with the put wall than without it.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{chaabene_3194,

title = {Experimental Investigation of the Influence of Process Parameters on the Mechanical Properties of Maraging Steel Produced by Electron Beam Melting},

author = {Ameni Chaabene and Slim Ben Elechi and Sami Chatti and Mohamed Guerich and Ated Ben Khalifa},

url = {https://link.springer.com/article/10.1007/s00170-024-14731-0#citeas},

year  = {2024},

date = {2024-12-01},

journal = {International Journal Of Advanced Manufacturing Technology},

volume = {135},

pages = {3865-3882},

abstract = {Maraging steels are used in industries that require high precision due to their exceptional mechanical properties. This paper

presents the impact of ten process parameters on the mechanical properties of maraging steel produced via electron beam

melting (EBM). The parameters studied here include printing orientation, scanning speed, beam power, beam diameter,

line offset, layer thickness, scan strategy, number of contours, preheating temperature, and post-processing. The mechanical

properties evaluated are tensile strength, strain at fracture, elongation at failure, energy density, material hardness, porosity,

and surface morphology. The results showed a significant correlation between these mechanical properties and the EBM

parameters. The highest ultimate tensile stress, determined from the tensile test, was recorded at 1491.51 MPa, corresponding

to an energy density of 64.28 J/mm3. The optimal parameters were identified as a line offset of 0.1 mm, a layer thickness

of 50 ?m, a scanning speed of 2800 mm/s, and a beam power of 15 mA. The energy density during EBM in turn affected

microstructure, porosity, and mechanical properties. Furthermore, the study revealed that aging heat treatment had a considerable

impact on the mechanical properties, with the highest tensile strength observed for a sample that had undergone

aging at 460 °C for 8 h. The results show the critical role of process parameters and aging heat treatment in achieving optimal

mechanical properties in EBM-produced maraging steel M789. These findings contribute to the optimization of this

manufacturing technique for industrial applications.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kadri_3203,

title = {Virtual reality in medical education: Effectiveness of Immersive Virtual Anatomy Laboratory (IVAL) Compared to traditional learning approaches},

author = {Mohammed Kadri and Fatima Ezzahra Boubakri and Timothy Teo and Fatima Zahra Kaghat and Ahmed Azough and Khalid Alaoui Zidani},

url = {https://www.sciencedirect.com/science/article/pii/S0141938224002348?via%3Dihub},

year  = {2024},

date = {2024-12-01},

journal = {Displays},

volume = {85},

pages = {102870},

abstract = {Immersive Virtual Anatomy Laboratory (IVAL) is an innovative learning tool that combines virtual reality and serious games elements to enhance anatomy education. This experimental study compares IVAL with traditional learning methods in terms of educational effectiveness and user acceptance. An experimental design was implemented with 120 undergraduate health-science students, randomly assigned to two groups: an experimental group using IVAL, and a control group following traditional learning methods. Data collection focused on quantitative measures such as pretest and posttest vocabulary assessment scores and task completion times, alongside qualitative measures obtained through a user experience questionnaire. This study utilizes the Technology Acceptance Model (TAM), incorporating variables such as Perceived Usefulness and Perceived Ease of Use. Results revealed significant improvements in the experimental group, with a 55.95% increase in vocabulary scores and an 18.75% reduction in task completion times compared to the control group. Qualitative data indicated that IVAL users reported greater Perceived Usefulness of the technology, improved Perceived Ease of Use, a more positive Attitude Toward Using IVAL, and stronger Behavioral Intention to continue using IVAL for anatomy learning. This study demonstrates that the integration of immersive virtual reality in the IVAL approach offers a promising method to enhance anatomy education. The findings provide insights into the effectiveness of immersive learning environments in improving learning outcomes and user acceptance. While further research is needed to explore long-term effects, this innovative approach not only enhances the effectiveness and enjoyment of anatomy learning but also provides valuable data on optimizing educational technology for improved learning outcomes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kadri_3276,

title = {C-IVAL: A Longitudinal Study of Knowledge Retention and Technology Acceptance in Collaborative Virtual Reality-Based Medical Education},

author = {Mohammed Kadri and Fatima Ezzahra Boubakri and GWO-JEN HWANG and Fatima Zahra Kaghat and Ahmed Azough and Khalid Alaoui Zidani},

url = {https://ieeexplore.ieee.org/document/10817604},

year  = {2024},

date = {2024-12-01},

journal = {Ieee Access},

abstract = {Anatomy education faces challenges in providing engaging, interactive, and collaborative learning experiences, particularly in understanding complex three-dimensional structures and maintaining long-term knowledge retention. Although virtual reality (VR) has shown promise in addressing spatial comprehension challenges, questions remain regarding its effectiveness in supporting collaborative learning and sustained knowledge retention. This longitudinal study examined Collaborative Immersive Virtual Anatomy Laboratory (C-IVAL), an innovative VR platform designed to enhance traditional anatomy learning through integrated collaborative features, immersive technology, and serious game elements. We conducted an experimental study with 65 medical students to evaluate their knowledge acquisition and technology acceptance compared to its non-collaborative predecessor, the Immersive Virtual Anatomy Laboratory (IVAL). Our evaluation framework combined quantitative assessments (knowledge tests, comprising pre-test, immediate post-test, and delayed post-test) with Technology Acceptance Model (TAM) analysis. Knowledge assessment revealed significant cognitive improvements, with mean knowledge scores increasing from 2.48 to 3.94 in the immediate post-tests, while long-term retention of anatomy knowledge showed sustained engagement for over two months. Importantly, C-IVAL demonstrated significantly higher scores across all TAM dimensions than the non-collaborative IVAL system, particularly for perceived usefulness and intention to use. Post-session feedback analysis showed 73.8% positive responses, highlighting enhanced social presence, immersive engagement, and effective collaboration, with 26.2% of constructive feedback focusing on system refinement and feature enhancement. This study contributes to the understanding of the effectiveness of collaborative features in virtual reality education by offering insights into designing and implementing virtual learning environments that e...},

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}

@article{navazhylava_3216,

title = {The Impact of Legal Uncertainties on Innovating HR Practices in Developing Countries: A Case Study of Remote Work in Kazakhstan's Technical Gas Industry during the healthcare crisis},

author = {Kseniya Navazhylava and Meruyert Ibraimova},

url = {https://www.tandfonline.com/doi/abs/10.1080/09585192.2024.2428356},

year  = {2024},

date = {2024-11-01},

journal = {International Journal Of Human Resource Management},

volume = {35},

number = {21},

pages = {3715-3743},

abstract = {This study explores the influence of legal uncertainties on the process of innovating human resources (HR) practices in developing countries. Through a case study focused on introducing remote work within Kazakhstan's Technical Gas Industry during a healthcare crisis, we examine the multifaceted challenges and opportunities that emerge when navigating a complex legal landscape. Our findings reveal that legal uncertainties, stemming from inadequacies in legislation and the tightness of norms, significantly impede the ability to adapt and modernize HR practices during crises. Furthermore, the criticality of the company's position within the industry, combined with a low degree of legal enforcement, underscores the concept of "responsibilization" among HR professionals. This phenomenon compels HR practitioners to assume greater responsibility and make strategic decisions that occasionally push the boundaries of existing laws and regulations. In this context, we propose a novel conceptualization of responsibilization, distinct from empowerment, as it involves embracing negative legal consequences associated with proactive decision-making during crises. This study contributes significantly to our understanding of how legal uncertainties influence the process of HR innovation in developing countries, highlighting the intricate interplay between regulatory frameworks, crisis management, and organizational transformation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{peticca-harris_3217,

title = {Neoliberal healthism and women's entrepreneurial subjectivities in yoga},

author = {Amanda Peticca-Harris and Sara R.S.T.A Elias and Kseniya Navazhylava and M.N. Ravishankar},

url = {https://journals.sagepub.com/doi/abs/10.1177/13505084241295736},

year  = {2024},

date = {2024-11-01},

journal = {Organization},

abstract = {Women entrepreneurs have long encountered the neoliberal expectation to perform as ideal subjects by exhibiting an enterprising femininity. However, existing literature on critical women's entrepreneurship has largely overlooked how health and wellbeing discourses permeate enterprising ideals and impact one's subjectivity. This qualitative study explores how 41 women entrepreneurs construct an enterprising subjectivity through neoliberal healthism, and by doing so, provides a deeper understanding of alternative logics within and beyond the neoliberal logic of the enterprise. Our findings detail who they understand themselves to be by internalizing and at times challenging neoliberal ideals through themes of self-responsibilization, self-optimization, and reflective health.  Our main contribution to critical women's entrepreneurship is that we conceptualize how an enterprising subjectivity is constructed through the personal optimization of health and wellbeing, fueled by shared-self-care rather than only the logic of market enterprise.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{josserand_3255,

title = {Australia's right to disconnect from work: Beyond rhetoric and towards implementation},

author = {Emmanuel Josserand and Martijn Boersma},

url = {https://journals.sagepub.com/doi/epub/10.1177/00221856241290625},

year  = {2024},

date = {2024-11-01},

journal = {Journal Of Industrial Relations},

volume = {66},

number = {5},

pages = {703-720},

abstract = {Amendments to the Fair Work Act now allow workers in Australia a right to disconnect. The implementation of this right precipitated a polarised public debate that was not consistently evidence-based, encompassing the often-contradictory perspectives of unions, employers, business lobbies and politicians. This study offers a more nuanced and evidence-based understanding of the right to disconnect, its benefits and challenges and the possible impact on Australian employment practices and relations. It provides an international comparative analysis; it explores the literature on related topics such as work-life balance, occupational stress, management practices and productivity; and it proposes a model of the consequences of technology-enabled flexible work. The comparative analysis and literature review are supplemented with themes identified in Australian media coverage through a Leximancer analysis. The findings discuss the advantages and limitations of diverse top-down legislative or self-regulatory pathways experienced overseas by early adopters. While the right to disconnect can improve work-life balance, health and well-being and productivity, its implementation requires careful consideration of industry-specific contexts, clear policies and cultural shifts in workplaces to mitigate the risks associated with hyperconnectivity. These insights are useful for Australia as it enters the implementation phase of the right to disconnect.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{aggarwal_3278,

title = {Inside story of impact investing in emerging market: A systematic review to measure the responsible and sustainable investing pattern using the ADO framework},

author = {Shalini AGGARWAL and Prerna RATHEE and Vikas ARYA and Hiran ROY},

year  = {2024},

date = {2024-11-01},

journal = {Journal of Economic Surveys},

abstract = {Impact investing has emerged as a significant global phenomenon as it provides a valuable avenue for investors to shape their cognitive decision-making ability to have a societal impact. The present study aims to review the existing literature on impact investing systematically. It tries to understand the major motivational factors that impact the investor in impact investing using the ADO framework by linking it with McClelland's Theory of Motivation, geographical areas, journal of publication, and type of research articles for impact investing, significant research gaps in impact investing, theoretical and managerial implications and future research of impact investing. PRISMA framework has been used to finalize the articles from the Scopus database. As a result, 154 articles have been identified from the year 2011 to 2024. The result identifies three motivational factors that drive the investor to invest in impact investing. It includes financial, social, and self-actualization. The study will guide the policymaker in introducing comprehensive regulatory policies in the area of impact investing. Accordingly, tax incentives and subsidies should be granted for promoting investment in impact investing. The development of proper infrastructure for trading in impact investing needs attention.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{arya_3279,

title = {Using Augmented Reality to Strengthen Consumer/Brand Relationships: The Case of Luxury Brands},

author = {Vikas ARYA and Deepa SETHI and Linda D. HOLLEBEEK},

url = {https://onlinelibrary.wiley.com/doi/10.1002/cb.2419},

year  = {2024},

date = {2024-11-01},

journal = {Journal Of Consumer Behaviour},

abstract = {Though augmented reality (AR) is increasingly adopted in marketing, its capacity to foster consumers' engagement and attachment remain tenuous, exposing an important literature-based gap. Addressing this gap, we deploy social presence theory and luxury consumption theory to develop and test a model that proposes that consumers' engagement with AR-deploying luxury brands drives the development of their perceived brand warmth, social value, and brand competence, in turn impacting their brand attachment. To explore these issues, we draw on survey data from a sample of 537 luxury apparel and automotive consumers. The results using structural equation modelling (SEM) show that first, luxury consumers who exhibit high engagement with the AR-deploying brand perceive higher levels of brand warmth, -competence, and social value, in turn raising their attachment to the AR-deploying luxury brand. Overall, the findings highlight AR's strategic capacity to engage consumers and raise the brand's perceived brand warmth, competence, and social value, in turn boosting individuals' attachment to the AR-deploying brand.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{meng_3010,

title = {Consensus adjustment for multi-attribute group decision making based on cross-allocation},

author = {Fan-Yong Meng and Deng-Yu Zhao and Zai-Wu Gong and Jun-Fei Chu and Witold Pedrycz and Zhe Yuan},

url = {https://www.sciencedirect.com/science/article/pii/S0377221724003400},

year  = {2024},

date = {2024-10-01},

journal = {European Journal Of Operational Research},

volume = {318},

number = {1},

pages = {200-216},

abstract = {Consensus adjustment is crucial in group decision making (GDM), aiming to reduce discrepancies in decision makers' (DMs') judgments for final decision results. The consensus adjustments made by DMs are interactive rather than independent. However, few studies investigate the consensus adjustment problem from the perspective of interactions among DMs. This study first constructs a model to determine the total minimum consensus adjustment under the requirements of consensus threshold and individual-collective judgment bias. Then, a consensus adjustment approach based on cross-allocation scheme is proposed to address the inconsistency between individual and collective minimum adjustments, which concerns all DMs' individual favorable allocation results under the total minimum consensus adjustment. The cross-allocation scheme ensures unanimous support for the same allocation result among all rational DMs, thereby eliminating the discrepancies among them. Subsequently, the optimization model-based minimum consensus judgment penalty is formulated to handle the non-cooperative behaviors of DMs. Furthermore, we show how to determine the unique consensus adjustment result for the non-cooperative DMs using the cross-allocation scheme. Therefore, our study contributes by developing a new GDM method that conducts consensus adjustment allocation by considering interactions among DMs. Finally, a case study is employed to demonstrate the specific application of the new method and discuss its efficiency. Meanwhile, comparison analysis and simulation experiments are provided.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{sun_3024,

title = {LCAMix: Local-and-contour aware grid mixing based data augmentation for medical image segmentation},

author = {Danyang Sun and Fadi Dornaika and Jinan Charafeddine},

url = {https://pdf.sciencedirectassets.com/272144/1-s2.0-S1566253524X00068/1-s2.0-S1566253524002628/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEBcaCXVzLWVhc3QtMSJHMEUCIB%2Bm2yVgKP%2BTa1w1tSg%2FydrF%2Fvb0NtGUi2OtE0dCfm5ZAiEAvS5zznXIlJGGqU0uDk6urwemR%2FjBXI8flOEVsv%2Bqi7MqvAUIj%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FARAFGgwwNTkwMDM1NDY4NjUiDGlNeMR%2BKpLBIx%2FJkiqQBUxi37rUay01aPHdPyUjlEmZScIOm09oNOKMm2j4kAJ%2BBXu4xZ6ts%2FYVWeKloZ9bKO688mVLpZYW96XCoW8DS9E%2FGvhCoLNFgFEV35VB1ai8O7M21%2BlU%2Br8%2FcPbj77ypLNC%2BKDWJV0NPrB1DKOvao6ZpbspbrdK4kPspEAzZ%2FVkFT%2FKiopgMXf6iniq2tANtPaizXkk%2BZaNSAGIFt9OmCXMk6H7VYJALKEF4ZJm9kBslRj5nE5Y6edtx2JSSptvlujKMXhJbwjIiUiX7Ui1B4pUWDVtzmLpVcElBM78VwS0H8TKlHXBl5pyVDCym%2Fp2r%2BZbZdJWW6ZWgrqb26Dqc%2F22RSCtts8Lm%2Fs8vSHEc2cfI2mYpPSj5gL51yaDqoZyA9JcEBsQRAecvv%2F8RkbvtzMzuNBRjn4V8HoQR137Q2pYM%2FJgAly5tkgk5KS8JB2jb%2BaTA88ZJLx6YSDeqJdX2PXwyB1XvrrRy8oUgMmff8s2zVgT1f1dX5iPmZ1jtYEVu40cdvJ88ac8j4zAfWQPmBb%2FvfXWd%2BDVOp7h8ftVwQnI7bLDlFBXbhH3oVb%2FFpJ3Bw3DFakM7j%2FSOVug7DP8dC9h8Dj2oIOW8C4QAgdCeHaDRMfh2F7VZjw3FZf3i631%2BAdBp8r4d4XkYeREmbmiovEoVWBBHoYD6RTIK9lp37AmDnhFSAMr2LEmzG2NypUQ3Hwb7zLu4thOxdGz5MBApBAh44ukY8YuN1ufa38eyKRtCUO%2Fxd2kuIIJ2LVXa3bQYug5Lx%2B9KIKhgqxCrwptvf8OaxtQ5FoYhuqNU0pL1Chohou2d1vld8RViOconvLl0VWMsZ5YyP9ZxaM0xtzdz9jZQUUyYOV92u8ehS7ie1qwrMNDAwrIGOrEBxpUgPvpVhdMKearFfabKLjWh5dtniMHIFTE5cSfjDp3cUuAHaEMlV2m22S1E7%2B%2BqLhJRHUxrx0Ahj9AgijOS6Ej7rGG3xGTKGOnhYGjvrjhMzhpYH7bBR2UDVY%2Ff5JnU3IqbM8%2BmzPkwAtPDE4f74N3zJ3CUErPd4nF0UOXyQABK0JE3XGOZmeqIIDshevKKQuAQWWCmCYyGaPWgjtPkrFNgDEqhkhXN4QWxs%2FJfC2Tb&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240524T152432Z&X-Amz-SignedHeaders=host&X-Amz-Expires=299&X-Amz-Credential=ASIAQ3PHCVTY4RJ4ZEGT%2F20240524%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=49fff6e8e4aa2160d63ba58a605230103a570a99a899c33049a2447724567bf6&hash=cf866cff1fcd93c461170f4149fdcc586b3e8c5bd13fbef0361db16227b04cc0&host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&pii=S1566253524002628&tid=spdf-53f47d50-21b1-4fa1-a93b-92addbddb736&sid=5b8e3010830f534aec5849b2797ace9af2f9gxrqb&type=client&tsoh=d3d3LnNjaWVuY2VkaXJlY3QuY29t&ua=001156565a0352015207&rr=888e4b0cfc530203&cc=fr},

year  = {2024},

date = {2024-10-01},

journal = {Information Fusion},

volume = {110},

pages = {102484},

abstract = {Medical image segmentation often faces challenges related to overfitting, primarily due to the limited and complex training samples. This challenge often prompts the use of self-supervised learning and data augmentation. However, self-supervised learning requires well-defined hand-crafted tasks and multiple training stages. On the other hand, basic image augmentation techniques like cropping, rotation, and flipping, effective for natural scene images, have limited efficacy for medical images due to their isotropic nature.



While regional dropout regularization data augmentation methods have proven effective in image recognition tasks, their application in image segmentation is not as extensively studied. Additionally, existing augmentation methods often operate on square regions, leading to the loss of crucial contour information. This is particularly problematic for medical image segmentation tasks dealing with regions of interest characterized by intricate shapes. In this work, we introduce LCAMix, a novel data augmentation approach designed for medical image segmentation. LCAMix operates by blending two images and their segmentation masks based on their superpixels, incorporating a local-and-contour-aware strategy. The training process on augmented images adopts two auxiliary pretext tasks: firstly, classifying local superpixels in augmented images using an adaptive focal margin, leveraging segmentation ground truth masks as prior knowledge; secondly, reconstructing the two source images using mixed superpixels as mutual masks, emphasizing spatial sensitivity. Our method stands out as a simple, one-stage, model-agnostic, and plug-and-play data augmentation solution applicable to various segmentation tasks. Notably, it requires no external data or additional models. Extensive experiments validate its superior performance across diverse medical segmentation datasets and tasks. The source codes are available at https://github.com/DanielaPlusPlus/DataAug4Medical.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{chu_3041,

title = {An improved equilibrium efficient frontier data envelopment analysis approach for evaluating decision-making units with fixed-sum outputs},

author = {Junfei Chu and Yanhua Dong and Zhe Yuan},

url = {https://www.sciencedirect.com/science/article/pii/S0377221724004314},

year  = {2024},

date = {2024-10-01},

journal = {European Journal Of Operational Research},

volume = {318},

number = {2},

pages = {592-604},

abstract = {In recent years, significant development has been made in efficiency evaluation for Decision-Making Units (DMUs) with fixed-sum outputs. The Generalized Equilibrium Efficient Frontier Data Envelopment Analysis (GEEFDEA) approach introduced by Yang et al. (2015) is one of the most representative methods. In the GEEFDEA approach, all DMUs are adjusted to become efficient under the same set of weights, indicating that the Equilibrium Efficient Frontier (EEF) constructed consists of only one hyperplane. However, in practical scenarios under the Variable Return to Scale (VRS) assumption, the production frontier always consists of multiple hyperplanes, presenting a more complex shape. To fill this research gap, we propose an improved Equilibrium Efficient Frontier Data Envelopment Analysis approach. Our approach allows DMUs to have different weights for inputs, variable-sum outputs, and fixed-sum outputs, resulting in an EEF with multiple hyperplanes. It is noted that our new approach uses a non-linear model to obtain the EEF. We show that the model can be linearized in the case of a single fixed-sum output. In situations involving multiple fixed-sum outputs, we propose an algorithm based on the Expectation Maximization (EM) mechanism to solve the model to obtain an EEF. Finally, we illustrate the advantages of our new approach through a numerical example and a case study in the global motor vehicle industry.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{latukha_3185,

title = {Adaptive Leadership for Multilevel Resilience in the Context of Disruptions},

author = {Marina Latukha and Polina Yakovleva and Kaifeng Yan},

url = {https://onlinelibrary.wiley.com/doi/10.1002/tie.22416},

year  = {2024},

date = {2024-10-01},

journal = {Thunderbird International Business Review},

abstract = {This paper examines the relationship between adaptive leadership and three levels of resilience: individual, team, and organizational. Developing multilevel resilience enables organizations to better anticipate conflicts and respond to environmental disruptions. Through correlation and regression analysis based on 148 respondents from companies in Russia, we build the relationship between adaptive leadership and three levels of resilience, unpacking the new role of leadership in shaping managerial responses to contextual change. The results suggest that adaptive leadership can positively influence all three levels of resilience, with adaptive leadership having the most significant impact on team resilience, then organizational resilience, leaving employee resilience behind. Such findings contribute to a deeper understanding of how exactly managerial mechanisms should be redesigned to overcome disruptions and develop leadership capabilities.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{alirezazadeh_3188,

title = {Mises-Fisher similarity-based boosted additive angular margin loss for breast cancer classification},

author = {Pandar Alirezazadeh and Fadi Dornaika and Jinan Charafeddine},

url = {https://link.springer.com/article/10.1007/s10462-024-10963-4#citeas},

year  = {2024},

date = {2024-10-01},

journal = {Artificial Intelligence Review},

volume = {57},

pages = {326},

abstract = {To enhance the accuracy of breast cancer diagnosis, current practices rely on biopsies and microscopic examinations. However, this approach is known for being time-consuming, tedious, and costly. While convolutional neural networks (CNNs) have shown promise for their efficiency and high accuracy, training them effectively becomes challenging in real-world learning scenarios such as class imbalance, small-scale datasets, and label noises. Angular margin-based softmax losses, which concentrate on the angle between features and classifiers embedded in cosine similarity at the classification layer, aim to regulate feature representation learning. Nevertheless, the cosine similarity's lack of a heavy tail impedes its ability to compactly regulate intra-class feature distribution, limiting generalization performance. Moreover, these losses are constrained to target classes when margin penalties are applied, which may not always optimize effectiveness. Addressing these hurdles, we introduce an innovative approach termed MF-BAM (Mises-Fisher Similarity-based Boosted Additive Angular Margin Loss), which extends beyond traditional cosine similarity and is anchored in the von Mises-Fisher distribution. MF-BAM not only penalizes the angle between deep features and their corresponding target class weights but also considers angles between deep features and weights associated with non-target classes. Through extensive experimentation on the BreaKHis dataset, MF-BAM achieves outstanding accuracies of 99.92%, 99.96%, 100.00%, and 98.05% for magnification levels of ×40, ×100, ×200, and ×400, respectively. Furthermore, additional experiments conducted on the BACH dataset for breast cancer classification, as well as on the LFW and YTF datasets for face recognition, affirm the generalization capability of our proposed loss function.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nguyen_3192,

title = {Size-dependency and lattice-discreetness effect on fracture toughness in 2D crystals under antiplanar loading},

author = {Thuy Nguyen and Daniel Bonamy},

url = {https://link.springer.com/article/10.1007/s10704-024-00812-4?utm_source=rct_congratemailt&utm_medium=email&utm_campaign=oa_20241017&utm_content=10.1007%2Fs10704-024-00812-4},

year  = {2024},

date = {2024-10-01},

journal = {International Journal Of Fracture},

volume = {248},

pages = {257-273},

abstract = {Fracture toughness is the material property

characterizing resistance to failure. Predicting its value from the solid structure at the atomistic scale remains elusive, even in the simplest situations of brittle fracture. We report here numerical simulations of crack propagation in two-dimensional fuse networks of different periodic geometries, which are electrical analogs of bidimensional brittle crystals under antiplanar loading. Fracture energy is determined from Griffith's analysis of energy balance during crack propagation, and fracture toughness is determined from fits of the displacement fields with Williams' asymptotic solutions. Significant size dependencies are evidenced in small lattices, with fracture energy and fracture toughness both converging algebraically with system size toward well-defined material-constant values in the limit of infinite system size. The convergence speed depends on the loading conditions and is faster when the symmetry of the considered lattice increases. The material

constants at infinity obey Irwin's relation and properly define the material resistance to failure. Their values are approached up to ? 15% using the recent analytical method proposed in Nguyen and Bonamy (Phys

Rev Lett 123:205503, 2019). Nevertheless, the deviation remains finite and does not vanish when the system size goes to infinity. We finally show that this deviation is a consequence of the lattice discreetness and

decreases when the super-singular terms of Williams' solutions (absent in a continuum medium but present here due to lattice discreetness) are taken into account.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{huang_3211,

title = {Catch-up in Complex Products and Systems: A Fuzzy-Set Qualitative Comparative Analysis of China's Equipment Manufacturing Industry},

author = {Han Huang and Jie Xiong and Lu XU and Zhe Yuan and Chun Liu},

url = {https://ieeexplore.ieee.org/document/10738479},

year  = {2024},

date = {2024-10-01},

journal = {Ieee Transactions On Engineering Management},

volume = {71},

pages = {15375 - 15389},

abstract = {The rapid advancement of Chinese Complex Products and Systems (CoPS) enterprises marks their transition into a post-catch-up phase, challenging conventional theories of catch-up. This study employs a configurational approach to explore the intricate relationships between catch-up environments and strategies, specifically focusing on the distinct paths of State-Owned Enterprises (SOEs) and non-State-Owned Enterprises (non-SOEs) within the CoPS sector. Utilizing Fuzzy-Set Qualitative Comparative Analysis (fsQCA) with data sourced from the EU Industrial R&D Investment Scoreboard (2017-2020) and corresponding Chinese-listed companies, our research identifies diverse catch-up configurations for SOEs, characterized by ?complexity adoption? and ?complexity decipher? models. In contrast, non-SOEs encounter challenges in strategically adapting to environmental shifts, which affects their catch-up strategies. Our findings emphasize the critical role of strategic alignment with external conditions, technological learning, and resource utilization in achieving successful catch-up in CoPS. These configurations enable SOEs to effectively align internal resources with external opportunities, resulting in superior catch-up performance. In contrast, non-SOEs encounter significant obstacles in adapting to environmental changes and optimizing resource utilization, which hinders their ability to attain similar successes. Moreover, our study sheds light on specific challenges faced by non-SOEs in responding to environmental shifts. This enriched understanding provides valuable theoretical insights into the catch-up of latecomer CoPS enterprises and has practical implications for both policymakers and business practitioners.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{scuotto_1758,

title = {Responsible I(m)ovation in Asia Pacific regions},

author = {Veronica Scuotto and Alexeis Garcia-Perez and David Kalisz and Amandeep Dhir},

url = {https://link.springer.com/article/10.1007/s10490-022-09803-2},

year  = {2024},

date = {2024-09-01},

journal = {Asia Pacific Journal Of Management},

volume = {41},

pages = {1005-1029},

abstract = {Over the past 20 years, a debate has developed on the differences between innovation and imitation strategies as mechanisms by which businesses operating in the Asia Pacific region may gain a competitive advantage. The current research contributes to this debate from a different perspective by exploring some of the challenges and opportunities associated with the combination of both strategies into what has been defined as imovation. Imovators and imovations do not stand alone in business ecosystems. Rather, they should be embraced in the context of sustainability-related virtues and emerging capabilities, such as ethical behaviour, co-responsibility and positive social impact. Taking dynamic capabilities as a theoretical lens, this paper conducts an empirical investigation of responsible imovation in a sample of 180 enterprises operating in the Asia Pacific market. In particular, this research evaluates the relationship between dynamic capabilities and imovation capabilities using a logistic regression analysis whereby we correlate the three main features of imovation strategies: strategic alliances, strategic decision-making and product innovations. To the best of our knowledge, ours is the first study to focus on responsible imovation in the Asia Pacific market from an empirical perspective. The research highlights the key organisational and individual actions with the potential both to preserve existing capabilities and to create and integrate new ones. Our findings highlight the importance of technology adoption for responsible imovation to become more effective and accessible to imovators in the Asia Pacific business ecosystem. We conclude that responsible imovations combined with product-level innovations and core dynamic capabilities pave the way towards more rapid growth and a more sustainable competitive advantage.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{de_grazia_3030,

title = {Procrastination or incomplete data? An analysis of USPTO examiner search activity},

author = {Charles de Grazia and Alexander Giczy and Nicholas Pairolero},

url = {https://doi.org/10.1016/j.respol.2024.105033},

year  = {2024},

date = {2024-09-01},

journal = {Research Policy},

volume = {53},

number = {7},

pages = {105033},

abstract = {Frakes and Wasserman (2020) finds evidence that United States Patent and Trademark Office (USPTO) patent examiners disproportionately receive credit for examination activities at the end of production periods and interprets this behavior as systemic examiner procrastination. Using newly assembled micro data on the

timing of USPTO examiner activities, our results show examiner work effort more closely resembles a uniform distribution over the production period, indicating consistent workflow and not procrastination. The assembled

data better track the precise timing of examiner work activities than the data used in Frakes and Wasserman

(2020), explaining the differences in our results. While Frakes and Wasserman (2020) conduct a thorough analysis of the markers and consequences of ??end-loading'', its use of an inadequate proxy for examination activity (i.e., Office action count dates) leads to incorrect conclusions about the examination process (i.e., widespread examiner procrastination)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{hemsley_3213,

title = {Views on the usability, design, and future possibilities of a 3D food printer for people with dysphagia: outcomes of an immersive experience},

author = {Bronwyn Hemsley and Stephen Dann and Courtney Reddacliff and Rebecca Smith and Fiona Given and Valerie Gay and Tuck Wah Leong and Emmanuel Josserand and Katrina Skellernd and Chriss Bull and Stuart Palmer and Susan Balandin},

url = {https://www.tandfonline.com/doi/full/10.1080/17483107.2022.2131914},

year  = {2024},

date = {2024-09-01},

journal = {Disability And Rehabilitation},

volume = {19},

number = {3},

pages = {527-536},

abstract = {Purpose



Although 3D food printing is expected to enable the creation of visually appealing pureed food for people with disability and dysphagia, little is known about the user experience in engaging with 3D food printing or the feasibility of use with populations who need texture-modified foods. The aim of this study was to explore the feasibility and usability of using domestic-scale 3D food printer as an assistive technology to print pureed food into attractive food shapes for people with dysphagia.

Materials and Methods



In total, 16 participants engaged in the unfamiliar, novel process of using a domestic-scale 3D food printer (choosing, printing, tasting), designed for printing pureed food, and discussed their impressions in focus group or individual interviews.

Results and Conclusions



Overall, results demonstrated that informed experts who were novice users perceived the 3D food printing process to be fun but time consuming, and that 3D food printers might not yet be suitable for people with dysphagia or their supporters. Slow response time, lack of user feedback, scant detail on the appropriate recipes for the pureed food to create a successful print, and small font on the user panel interface were perceived as barriers to accessibility for people with disability and older people. Participants expected more interactive elements and feedback from the device, particularly in relation to resolving printer or user errors. This study will inform future usability trials and food safety research into 3D printed foods for people with disability and dysphagia.



    IMPLICATIONS FOR REHABILITATION



    3D food printers potentially have a role as an assistive technology in the preparation of texture-modified foods for people with disability and dysphagia.



    To increase feasibility, 3D food printers should be co-designed with people with disability and their supporters and health professionals working in the field of dysphagia and rehabilitation.



    Experts struggled to be able to print 3D pureed shapes owing to relatively low usability of the 3D food printer tested with problems using the interface and resolving problems in the print.



    3D food printing is a fun and novel activity and may help to engage people with disability and dysphagia in making choices around the shape of the food to be printed.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{tao_3056,

title = {Artificial intelligence-driven transformations in low-carbon energy structure: Evidence from China},

author = {Weiliang Tao and Shimei Weng and Xueli Chen and Fawaz Baddar Al Hussan and Malin Song},

url = {https://www.sciencedirect.com/science/article/abs/pii/S0140988324004274},

year  = {2024},

date = {2024-08-01},

journal = {Energy Economics},

volume = {136},

pages = {107719},

abstract = {The widespread integration of artificial intelligence (AI) technology in the realms of energy and the environment has emerged as a catalyst for transformative shifts toward low-carbon energy structures. However, existing literature and practical applications have yet to delve into the intricate ways in which intelligent technology influences energy structures. Consequently, this study addresses this gap by constructing a comprehensive theoretical model that encompasses robots and differentiated energy inputs. By drawing on the Chinese case, this research investigates the impact of AI on low-carbon energy structure transformation, both theoretically and empirically. The study's results reveal that AI technology significantly advances the cause of low-carbon energy transformation. Notably, this effect is manifested in the post-Industry 4.0 era and regions endowed with abundant renewable energy resources and strong governmental support for innovation. Rigorous robustness tests substantiate the existence of this relationship. Furthermore, adopting smart technology fosters energy structure transformation through industrial restructuring, and introduces the energy rebound effect, thereby partially offsetting its positive impact. Importantly, the study underscores that the efficacy of AI is further heightened when the influx of innovation factors surpasses a certain threshold. These findings furnish crucial evidence and policy insights for China and other developing nations, offering guidance on accelerating energy transitions and attaining carbon neutrality.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{shakir_3063,

title = {Novel Approximate Distribution of the Generalized Turbulence Channels for MIMO FSO Communications},

author = {Wafaa Shakir and Ali Mahdi and Hani Hamdan and Jinan Charafeddine and Haitham Satai and Radouane Akrache and Samir Hadad and Jinane Sayah},

url = {https://ieeexplore.ieee.org/document/10568928},

year  = {2024},

date = {2024-08-01},

journal = {Ieee Photonics Journal},

volume = {16},

number = {4},

pages = {1 - 15},

abstract = {In this paper, we develop an innovative series representation for the sum of Rician non-zero boresight pointing error random variates based on the k - ? distribution, which is suitable for multiple-input multiple-output (MIMO) transmission for the first time. Then, using this new representation, we introduce a novel closed-form probability density function (PDF) approximation for the sum of Gamma-Gamma random variates with generalized pointing errors and atmospheric attenuation of MIMO free-space optical (FSO) communications. Statistical Kolmogorov-Smirnov tests confirm the accuracy of this approximation over a wide range of channel conditions. The significance of this approximation is emphasized by deriving closed-form expressions for the ergodic capacity, outage probability, and average bit error rate (BER) using Meijer's G-function. This paper provides a comprehensive analysis of the performance of MIMO FSO systems utilizing the equal gain combining (EGC) diversity technique under various conditions, such as different numbers of transmitter and receiver, turbulence intensities, the effects of non-zero boresight pointing errors, and path attenuation. The results show that using MIMO technology with more transmitters and receivers significantly improves the performance of FSO communication compared to other diversity techniques, including single input single output (SISO), and multiple input single output (MISO) systems. Detailed evaluations of the ergodic capacity, outage probability, and average BER performance at high signal-to-noise ratios provide additional insights. Monte-Carlo simulation results demonstrate the accuracy of the proposed approach.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ketata_3136,

title = {Impact of fractured tibia implant fixation devices on bone stiffness during bending test},

author = {HAJER KETATA and Naila Hfaiedh and Michèle Kanhonou and Houssem Badreddine},

url = {https://www.sciencedirect.com/science/article/pii/S1350453324001292?via%3Dihub},

year  = {2024},

date = {2024-08-01},

journal = {Medical Engineering & Physics},

volume = {131},

pages = {104228},

abstract = {This study focuses on evaluating the failure resistance of a previously reduced tibia with internal fixation implants as PLate (PL) or InterMedullary Nail (IMN), subjected later to a tibial lateral trauma. To replicate this type of trauma, which can be caused by a road accident, a three-point bending test is considered using experimental tests and numerical simulations.



The withstand evaluation of the tibia-PL and tibia-IMN structures was conducted by following the load transfer through, the bone and the used implants. The analysis, up to tibia failure, required the use of an elasto-plastic behaviour law coupled to damage. The model parameters were identified using experimental tests.



Il was shown that the tibia-IMN structure provided a bending resistant load up to three-times higher than the tibia-PL. In fact, the used screws for plate fixation induced a high level of stress in the vicinity of threaded region, leading to a crack initiation and a damage propagation. However, in tibia-IMN structure the highest stress was generated in the trapped zone between the loader and the nail, promoting crack formation.



From a biomechanical point of view, the structure with IMN is safer than the structure with PL, whose fixation induces earlier damage in bone.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{latukha_3150,

title = {The effect of sanctions on macro talent management: The case of Russia},

author = {Marina Latukha and Ilan Alon and Nikita Kuleshov and Vlad Vaiman},

url = {https://doi.org/10.1016/j.jwb.2024.101570},

year  = {2024},

date = {2024-08-01},

journal = {Journal Of World Business},

volume = {59},

number = {5},

pages = {101570},

abstract = {The purpose of our study is to examine how the sanctions imposed on Russia influence talent management. To do

so, we review the macro talent management (MTM) framework alongside the literature on sanctions. In addition,

we have collected data from 419 media publications discussing the effects of sanctions and analyzed them using

critical discourse analysis (CDA). Our findings highlight the predominantly negative nature of the sanctions'

impact on MTM ecosystems, theoretically yielding closer links between the sanctions and the MTM framework,

and human capital more specifically.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{farronato_1909,

title = {The Green Frontier of Mobile Applications in Improving Recycling Consumers' Behavior},

author = {Nicola Farronato and Veronica Scuotto and Marco Pironti and Manlio Del Giudice},

url = {https://ieeexplore.ieee.org/abstract/document/9884976},

year  = {2024},

date = {2024-07-01},

journal = {Ieee Transactions On Engineering Management},

volume = {71},

pages = {13191-13200},

abstract = {In this article, we provide a new insight into overcoming resistance to emerging green technologies through mobile app users' environmental engagement. The use of a mobile recycling application is evaluated with regard to its media richness with a sample of 12 539 users in Italy. The research is developed during the COVID-19 pandemic, at a time when users have become more environmentally conscious and aware of plastic pollution. This time period has also seen an increase in the use of mobile applications, which provide social engagement and other benefits. Although it has encouraged new research on recycling behavior and how environmental messages are spread, as far as we know, no research has included a specific technology, such as mobile applications. Through the lens of consumer social media engagement behavior, it has emerged that media richness has a positive correlation with user engagement and recycling behavior. Theoretically, the research offers a novel technological tool worthy of further exploration in the fields of management and engineering. New practical insights are offered in terms of best practices for strengthening the relationships between companies and their clients. As users become more accustomed to social technologies, those technologies may help to establish responsible consumption patterns.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{bouzbib_2109,

title = {PalmEx: Adding Palmar Force-Feedback for 3D Manipulation with Haptic Exoskeleton Gloves},

author = {Elodie Bouzbib and Marc Teyssier and Thomas Howard and Claudio Pacchierotti and Anatole Lécuyer},

url = {https://ieeexplore.ieee.org/document/10041940/},

year  = {2024},

date = {2024-07-01},

journal = {Ieee Transactions On Visualization And Computer Graphics},

volume = {30},

number = {7},

pages = {3973-3980},

abstract = {Haptic exoskeleton gloves are a widespread solution for providing force-feedback in Virtual Reality (VR), especially for 3D object manipulations. However, they are still lacking an important feature regarding in-hand haptic sensations: the palmar contact.

In this paper, we present PalmEx, a novel approach which incorporates palmar force-feedback into exoskeleton gloves to improve the overall grasping sensations and manual haptic interactions in VR. PalmEx's concept is demonstrated through a self-contained hardware system augmenting a hand exoskeleton with an encountered palmar contact interface -- physically encountering the users' palm.

We build upon current taxonomies to elicit PalmEx's capabilities for both the exploration and manipulation of virtual objects. 

We first conduct a technical evaluation optimising the delay between the virtual interactions and their physical counterparts.

We then empirically evaluate PalmEx's proposed design space in a user study (n=12) to assess the potential of a palmar contact for augmenting an exoskeleton. Results show that PalmEx offers the best rendering capabilities to perform believable grasps in VR.

PalmEx highlights the importance of the palmar stimulation, and provides a low-cost solution to augment existing high-end consumer hand exoskeletons.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{gangi_2329,

title = {Uncovering Backers' Intention to Participate in Reward-Based Crowdfunding: The Role of Value Cocreation},

author = {Francesco Gangi and Lucia Michela Daniele and Veronica Scuotto and Tani Mario},

url = {https://ieeexplore.ieee.org/document/10114066},

year  = {2024},

date = {2024-07-01},

journal = {Ieee Transactions On Engineering Management},

pages = {1 - 13},

abstract = {The ongoing dynamic market evolution has reshaped the way companies can create value, thanks to new funding models and new market opportunities, especially in the early business stages. In particular, with the growing development of crowdfunding models, scholars and practitioners are questioning how backers can cocreate value by funding new entrepreneurial initiatives through digital platforms dedicated to this new form of financial support. Therefore, positioning this article in the knowledge and engineering management literature, the current research explores whether two subdimensions of value cocreation (VCC), knowledge sharing and interaction, may help to understand backers' intention to participate in a reward-based crowdfunding (RBCF) campaign. In particular, using the partial least square structural equation modeling approach on an original sample of 3574 backers, in this article, we find that knowledge sharing, understood as backers' expertise as well as the preparedness of the proponent team, and the interaction between the campaign actors contribute to explaining backers' participation in an RBCF initiative. The research supports the relevance of backers' engagement in terms of VCC as an experiential benefit for the success of an RBCF initiative. From this perspective, our study suggests that both entrepreneurs and platforms should consider VCC in the design and setting of RBCF campaigns.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dornaika_2943,

title = {Towards unsupervised radiograph clustering for COVID-19: The use of graph-based multi-view clustering},

author = {Fadi Dornaika and Sally El Hajjar and Jinan Charafeddine},

url = {https://www.sciencedirect.com/science/article/pii/S0952197624004949?via%3Dihub},

year  = {2024},

date = {2024-07-01},

journal = {Engineering Applications Of Artificial Intelligence},

volume = {133},

number = {Part D},

pages = {108336},

abstract = {Automatic classification methods widely used for diagnosing and analyzing COVID-19 cases. These methods assume known labels and rely on a single view of the dataset. Given the prevalence of COVID-19 cases and the extensive volume of patient records lacking labels, this communication underscores our unique approach?conducting the first study on COVID-19 case diagnosis in an unsupervised manner. Our work operates under the assumption of prior knowledge regarding the number of classes, such as COVID-19, pneumonia, and normal, in a case study.



By adopting an unsupervised learning paradigm, we leverage the wealth of unlabeled data, reducing dependence on human experts for annotating numerous images. This paper introduces an enhanced version of a recent direct method where non-negative cluster indices and spectral embeddings are jointly estimated. Beyond the inherent advantages of this method, our proposed model introduces improvements through two additional types of constraints: (i) ensuring consistent smoothing of cluster labels across all views and (ii) imposing an orthogonality constraint on the matrix of cluster assignments. The efficacy of the proposed method is demonstrated using the public COVIDx dataset with three classes, showcasing promising results in categorizing radiographs. The proposed approach is tested on other public image datasets to assess its effectiveness.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{waheed_3109,

title = {Satisfaction as a function of user justice: a social exchange theory perspective},

author = {Mehwish Waheed and Noor Ul-Ain and Jan Riezebos and Patrick Mikalef},

url = {https://www.tandfonline.com/doi/full/10.1080/09537325.2024.2369934},

year  = {2024},

date = {2024-07-01},

journal = {Technology Analysis & Strategic Management},

abstract = {This study investigates complaint behaviour as a function of post-satisfaction behaviour stemming from perceptions of justice and security. Grounded in social exchange theory, we propose an integrated framework in which

security, expectation confirmation, and dimensions of justice (distributive, procedural, and interactional) influence satisfaction, affecting complaint behaviour towards the eCommerce Digital Supply Chain (DSC) process.

Data were collected through a quantitative online survey involving 316 Amazon eShoppers of tech products from the European region. The confirmatory factor analysis results validated the second-order reflective justice construct, encompassing distributive, procedural, and interactional

dimensions. Furthermore, the structural relationship results revealed (i) justice and security have a significant impact on eShoppers' satisfaction; (ii) a significant relationship exists between word of mouth, satisfaction, and eShoppers' complaint intention. This framework contributes to the existing knowledge base and offers valuable insights for stakeholders in the eCommerce DSC.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{vazquez-ferrel_3163,

title = {Political survival and legislative reselection in Mexico's chamber of deputies},

author = {Carlos Vazquez-Ferrel and Erik Ernesto Vazquez Hernandez},

url = {https://doi.org/10.1080/13572334.2024.2372953},

year  = {2024},

date = {2024-07-01},

journal = {The Journal of Legislative Studies},

abstract = {This article presents an empirical investigation into the factors influencing the renomination of legislators by party leaders for their continued presence in Congress. We argue that legislators who have previously held influential positions within Congress, such as Committee President, have a successful track record of (co)sponsoring bills, and have built distinguished political careers, are more likely to be renominated in Congress. To test this theory, we employ an original dataset sourced from the Mexican 2018-2021 Chamber of Deputies, which comprises the inaugural group of Congress members allowed to seek reelection after a 90-year prohibition within the context of a transforming party system marked by the diminishing electoral attractiveness of traditional parties. Our findings carry significant implications for comprehending how party leaders recognise and reward legislators who effectively safeguard the party's interests and uphold its reputation inside the halls of Congress.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{ogorodnikov_3297,

title = {Fault-Tolerant Families of Production Plans: Mathematical Model, Computational Complexity, and Branch-and-Bound Algorithms},

author = {Yuri Ogorodnikov and Roman Rudakov and Daniil KHACHAI and M. Yu. KHACHAI},

url = {https://link.springer.com/article/10.1134/S0965542524700441#citeas},

year  = {2024},

date = {2024-07-01},

journal = {Computational Mathematics And Mathematical Physics},

volume = {64},

pages = {1193-1210},

abstract = {The design of fault-tolerant production and delivery systems is one of the priority areas in modern operations research. The traditional approach to modeling such systems is based on the use of stochastic models that describe the choice of a possible scenario of actions in the event of problems in a production or transportation network. Along with a number of advantages, this approach has a known drawback. The occurrence of problems of an unknown nature that can jeopardize the performance of the entire simulated system significantly complicates its use. This paper introduces the minimax problem of constructing fault-tolerant production plans (reliable production process design problem, RPPDP), the purpose of which is to ensure the uninterrupted operation of a distributed production system with minimal guaranteed cost. It is shown that the RPPDP is NP-hard in the strong sense and remains intractable under quite specific conditions. To find exact and approximate solutions with accuracy guarantees for this problem, branch-and-bound methods are developed based on the proposed compact model of the mixed integer linear program (MILP) and novel heuristic of adaptive search in large neighborhoods (adaptive large neighborhood search, ALNS) as part of extensions of the well-known Gurobi MIP solver. The high performance and complementarity of the proposed algorithms is confirmed by the results of numerical experiments carried out on a public library of benchmarking instances developed by the authors based on instances from the PCGTSPLIB library.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}