Top Tweets for #NewPublishedPaper

2 days ago

📢 #NewPublishedPaper 📚 Power-Law Degradation and Lifetime Interpretation in Microelectronics Reliability 🔗 https://t.co/Obp0AP1h7Y 👨‍🔬 by Joseph B. Bernstein, Ariel University, Israel #microelectronics reliability #power-law degradation #bias temperature instability #thermally activated kinetics #diffusion #reliability physics #time-to-failure analysis Reliability degradation in semiconductor devices originates from microscopic stochastic processes such as defect motion, diffusion, bond rearrangement, and charge trapping occurring under electrical and thermal stress. Experimental degradation measurements, however, often exhibit smooth empirical scaling behavior, particularly power-law time dependences extending across many orders of magnitude in time. This tutorial reviews the thermodynamic and kinetic foundations underlying these observations and explains how empirical power-law degradation behavior can emerge from the collective interaction of many microscopic stochastic processes. The discussion begins with irreversible thermodynamics, random walk transport, diffusion, and Arrhenius kinetics and then connects these microscopic concepts to the macroscopic degradation trends commonly observed in semiconductor reliability experiments. Attention is given to the interpretation of stress-dependent power-law degradation kinetics and their implications for accelerated lifetime extrapolation. Practical limitations associated with conventional logarithmic degradation analysis are examined, including baseline sensitivity, logarithmic instability near the measurement floor, and systematic curvature that may remain hidden despite high goodness-of-fit metrics. Methods based on transformed-coordinate linearization and curvature-sensitive extraction are discussed together with their implications for time-to-failure extrapolation and activation-energy interpretation. Experimental studies of phenomena such as bias temperature instability frequently show degradation behavior in which the time exponent depends systematically on voltage and temperature stress conditions. Under such conditions, the reciprocal exponent 𝑚=1/𝑛 can significantly amplify stress acceleration during lifetime extrapolation. This work provides a conceptual framework connecting microscopic stochastic degradation physics with the empirical methods commonly used in practical semiconductor reliability analysis and long-term lifetime prediction.

Applsci's tweet photo. 📢 #NewPublishedPaper
📚 Power-Law Degradation and Lifetime Interpretation in Microelectronics Reliability
🔗 https://t.co/Obp0AP1h7Y
👨‍🔬 by Joseph B. Bernstein, Ariel University, Israel
#microelectronics reliability #power-law degradation #bias temperature instability #thermally activated kinetics #diffusion #reliability physics #time-to-failure analysis

Reliability degradation in semiconductor devices originates from microscopic stochastic processes such as defect motion, diffusion, bond rearrangement, and charge trapping occurring under electrical and thermal stress. Experimental degradation measurements, however, often exhibit smooth empirical scaling behavior, particularly power-law time dependences extending across many orders of magnitude in time. This tutorial reviews the thermodynamic and kinetic foundations underlying these observations and explains how empirical power-law degradation behavior can emerge from the collective interaction of many microscopic stochastic processes. The discussion begins with irreversible thermodynamics, random walk transport, diffusion, and Arrhenius kinetics and then connects these microscopic concepts to the macroscopic degradation trends commonly observed in semiconductor reliability experiments. Attention is given to the interpretation of stress-dependent power-law degradation kinetics and their implications for accelerated lifetime extrapolation. Practical limitations associated with conventional logarithmic degradation analysis are examined, including baseline sensitivity, logarithmic instability near the measurement floor, and systematic curvature that may remain hidden despite high goodness-of-fit metrics. Methods based on transformed-coordinate linearization and curvature-sensitive extraction are discussed together with their implications for time-to-failure extrapolation and activation-energy interpretation. Experimental studies of phenomena such as bias temperature instability frequently show degradation behavior in which the time exponent depends systematically on voltage and temperature stress conditions. Under such conditions, the reciprocal exponent 𝑚=1/𝑛 can significantly amplify stress acceleration during lifetime extrapolation. This work provides a conceptual framework connecting microscopic stochastic degradation physics with the empirical methods commonly used in practical semiconductor reliability analysis and long-term lifetime prediction.

Applied Sciences MDPI

@Applsci

3 days ago

📢 #NewPublishedPaper 📚 Hybrid Intrusion Detection System for Software-Defined Networks 🔗 https://t.co/tGIzAVYlHl 👨‍🔬 by Aleksandra Łapczuk, Jerzy Domżał, Edyta Biernacka and Robert Wójcik AGH University of Krakow, Poland #anomalydetection #deeplearning #IDS #SDNcontroller Software-Defined Networking, as a relatively recent networking paradigm, offers centralized infrastructure management, flexibility and high programmability. However, it also creates particular security risks due to being exposed to external threats. To address these challenges, numerous methods have been developed and applied over the past few years. This study proposes a hybrid Intrusion Detection System that combines signature-based analysis with deep learning-based anomaly detection. In this architecture, a signature module quickly filters known attack patterns, while remaining traffic is analyzed by an autoencoder and a supervised deep neural network classifier. The final decision is based on rule-based prioritization of the outputs from both models, improving the reliability and robustness of detection.

Applsci's tweet photo. 📢 #NewPublishedPaper
📚 Hybrid Intrusion Detection System for Software-Defined Networks
🔗 https://t.co/tGIzAVYlHl
👨‍🔬 by Aleksandra Łapczuk, Jerzy Domżał, Edyta Biernacka and Robert Wójcik
AGH University of Krakow, Poland
#anomalydetection #deeplearning #IDS #SDNcontroller
Software-Defined Networking, as a relatively recent networking paradigm, offers centralized infrastructure management, flexibility and high programmability. However, it also creates particular security risks due to being exposed to external threats. To address these challenges, numerous methods have been developed and applied over the past few years. This study proposes a hybrid Intrusion Detection System that combines signature-based analysis with deep learning-based anomaly detection. In this architecture, a signature module quickly filters known attack patterns, while remaining traffic is analyzed by an autoencoder and a supervised deep neural network classifier. The final decision is based on rule-based prioritization of the outputs from both models, improving the reliability and robustness of detection.

Applied Sciences MDPI

@Applsci

4 days ago

📢 #NewPublishedPaper 📚 Liquid Biopsy in Precision Oncology: Clinical Applications and Emerging Roles of Circulating Tumor DNA, Cell-Free DNA, and Extracellular Vesicles 🔗 https://t.co/UjPlf9TbFj 👨‍🔬 by by Zsolt Kovács et al. #liquidbiopsy #circulatingtumorDNA #cellfreeDNA #exosomes

Applsci's tweet photo. 📢 #NewPublishedPaper
📚 Liquid Biopsy in Precision Oncology: Clinical Applications and Emerging Roles of Circulating Tumor DNA, Cell-Free DNA, and Extracellular Vesicles
🔗 https://t.co/UjPlf9TbFj
👨‍🔬 by by Zsolt Kovács et al.

#liquidbiopsy #circulatingtumorDNA #cellfreeDNA #exosomes

Applied Sciences MDPI

@Applsci

4 days ago

📢 #NewPublishedPaper 📚 Characterization of Tenderness-Related SNPs in Culled Holstein Cows: CAPN1 and CAST Genotypes Show Neutral Effects on Postmortem Meat Quality Parameters—A Pilot Study 🔗 https://t.co/pATzrzjJip 👨‍🔬 by Maria de los Angeles Robles-Mota, Manuel Andrés González Toimil, María Salud Rubio-Lozano, Henry Alberto Grajales-Lombana, Jorge Alfredo Cuéllar-Ordaz, José Francisco Montiel-Sosa, Jonathan Josué Balderas Correa, Crisóforo Mercado-Márquez, Rosa Isabel Higuera-Piedrahita, Daniel Hernandez-Patlan and Ana Elvia Sánchez-Mendoza. 🏫National Autonomous University of Mexico, Universidad Nacional Autónoma de México, Universidad Nacional de Colombia and Polytechnic University of the Valley of Mexico #SNP #tenderness #calpain #calpastatin #Holsteinmeat

Applsci's tweet photo. 📢 #NewPublishedPaper
📚 Characterization of Tenderness-Related SNPs in Culled Holstein Cows: CAPN1 and CAST Genotypes Show Neutral Effects on Postmortem Meat Quality Parameters—A Pilot Study
🔗 https://t.co/pATzrzjJip
👨‍🔬 by Maria de los Angeles Robles-Mota, Manuel Andrés González Toimil, María Salud Rubio-Lozano, Henry Alberto Grajales-Lombana, Jorge Alfredo Cuéllar-Ordaz, José Francisco Montiel-Sosa, Jonathan Josué Balderas Correa, Crisóforo Mercado-Márquez, Rosa Isabel Higuera-Piedrahita, Daniel Hernandez-Patlan and Ana Elvia Sánchez-Mendoza.
🏫National Autonomous University of Mexico, Universidad Nacional Autónoma de México, Universidad Nacional de Colombia and Polytechnic University of the Valley of Mexico

#SNP #tenderness #calpain #calpastatin #Holsteinmeat

Applied Sciences MDPI

@Applsci

5 days ago

📢 #NewPublishedPaper 📚 Predictors of Functional Responsiveness to Exercise in Postmenopausal Women 🔗https://t.co/l9YoqXlY0C 👨‍🔬 by António M. Monteiro et al. Osteoporosis and functional decline are major health concerns among postmenopausal women. Identifying factors associated with exercise responsiveness may improve understanding of interindividual variability in exercise adaptations and support the development of more individualized intervention strategies. This study investigated whether baseline body composition, bone health, and functional fitness characteristics were associated with exercise responsiveness in postmenopausal women. Eighty women participated in a 30-week supervised multicomponent exercise program and were classified as responders or non-responders according to changes in functional performance following the intervention. Body composition and bone health were assessed by dual-energy X-ray absorptiometry (DXA), and functional fitness was evaluated using the Senior Fitness Test battery. Unadjusted analyses suggested small differences in baseline Z-score (p = 0.038) and upper-body flexibility assessed by the Back Scratch test (p = 0.030), while total bone mineral content showed a trend toward significance (p = 0.056). However, none of these differences remained statistically significant after Benjamini–Hochberg false discovery rate correction. As a complementary analysis, multiple linear regression adjusted for baseline performance identified baseline body mass (p = 0.007), total bone mineral content (p = 0.018), and upper-body flexibility (p = 0.020) as factors independently associated with post-intervention functional performance. Exploratory machine learning analyses demonstrated limited ability to discriminate responders from non-responders using baseline characteristics alone, although Random Forest variable importance highlighted similar variables to those identified in the regression analysis. Overall, these findings suggest that baseline musculoskeletal characteristics alone are insufficient to accurately classify exercise responsiveness and that larger studies incorporating additional clinical, behavioural, physiological, and biological variables are needed to improve individualized exercise prescription.

Applsci's tweet photo. 📢 #NewPublishedPaper
📚 Predictors of Functional Responsiveness to Exercise in Postmenopausal Women
🔗https://t.co/l9YoqXlY0C
👨‍🔬 by António M. Monteiro et al.
Osteoporosis and functional decline are major health concerns among postmenopausal women. Identifying factors associated with exercise responsiveness may improve understanding of interindividual variability in exercise adaptations and support the development of more individualized intervention strategies. This study investigated whether baseline body composition, bone health, and functional fitness characteristics were associated with exercise responsiveness in postmenopausal women. Eighty women participated in a 30-week supervised multicomponent exercise program and were classified as responders or non-responders according to changes in functional performance following the intervention. Body composition and bone health were assessed by dual-energy X-ray absorptiometry (DXA), and functional fitness was evaluated using the Senior Fitness Test battery. Unadjusted analyses suggested small differences in baseline Z-score (p = 0.038) and upper-body flexibility assessed by the Back Scratch test (p = 0.030), while total bone mineral content showed a trend toward significance (p = 0.056). However, none of these differences remained statistically significant after Benjamini–Hochberg false discovery rate correction. As a complementary analysis, multiple linear regression adjusted for baseline performance identified baseline body mass (p = 0.007), total bone mineral content (p = 0.018), and upper-body flexibility (p = 0.020) as factors independently associated with post-intervention functional performance. Exploratory machine learning analyses demonstrated limited ability to discriminate responders from non-responders using baseline characteristics alone, although Random Forest variable importance highlighted similar variables to those identified in the regression analysis. Overall, these findings suggest that baseline musculoskeletal characteristics alone are insufficient to accurately classify exercise responsiveness and that larger studies incorporating additional clinical, behavioural, physiological, and biological variables are needed to improve individualized exercise prescription.

102

Applied Sciences MDPI

@Applsci

10 days ago

📢 #NewPublishedPaper 📚 A Joint Numerical Simulation Method for Mine Seismic–Electric Coupling 🔗https://t.co/qzL6uEIdJc 👨‍🔬 by Guochuan Zhang, Guoyou Zhou, Hui Fu, Maolin Huang and Benyu Su 🏫China University of Mining and Technology #DC resistivity method #seismic exploration #joint inversion #numerical simulation #cross-gradient This study aims to enhance the detection accuracy of concealed structures by implementing a joint seismic–electric inversion that exploits the complementary strengths of both methods. For the DC resistivity component, a forward model was established using the finite element method with unstructured meshes, and inversion was performed via Occam regularization. For seismic exploration, forward modeling employed curved-ray tracing, and inversion was conducted via the LSQR algorithm. Cross-gradient constraints were incorporated into the joint inversion to establish a structurally coupled framework. The novelty of this study lies in the integration of unstructured mesh discretization, curved-ray seismic tomography, and cross-gradient-constrained joint inversion for mine water detection. Numerical simulation results demonstrate that joint inversion effectively constrains the spatial extent of anomalies, accurately characterizes the morphology of multiple anomalous bodies and water-conducting fault channels, and substantially reduces solution non-uniqueness compared to single-method inversions. This research provides a reliable methodology for the refined detection of concealed hazard-inducing structures, offering considerable practical value for safeguarding coal mine safety.

Applsci's tweet photo. 📢 #NewPublishedPaper
📚 A Joint Numerical Simulation Method for Mine Seismic–Electric Coupling
🔗https://t.co/qzL6uEIdJc
👨‍🔬 by Guochuan Zhang, Guoyou Zhou, Hui Fu, Maolin Huang and Benyu Su
🏫China University of Mining and Technology
#DC resistivity method #seismic exploration #joint inversion #numerical simulation #cross-gradient

This study aims to enhance the detection accuracy of concealed structures by implementing a joint seismic–electric inversion that exploits the complementary strengths of both methods. For the DC resistivity component, a forward model was established using the finite element method with unstructured meshes, and inversion was performed via Occam regularization. For seismic exploration, forward modeling employed curved-ray tracing, and inversion was conducted via the LSQR algorithm. Cross-gradient constraints were incorporated into the joint inversion to establish a structurally coupled framework. The novelty of this study lies in the integration of unstructured mesh discretization, curved-ray seismic tomography, and cross-gradient-constrained joint inversion for mine water detection. Numerical simulation results demonstrate that joint inversion effectively constrains the spatial extent of anomalies, accurately characterizes the morphology of multiple anomalous bodies and water-conducting fault channels, and substantially reduces solution non-uniqueness compared to single-method inversions. This research provides a reliable methodology for the refined detection of concealed hazard-inducing structures, offering considerable practical value for safeguarding coal mine safety.

137

Applied Sciences MDPI

@Applsci

13 days ago

📢#NewPublishedPaper 📚 Seismic Soil Amplification in a Thick Alluvial Basin: One-Dimensional Site Response Analysis for Afyonkarahisar, Türkiye 🔗 https://t.co/oCjyFQDAui 👨‍🔬 Süleyman Gücek and İsmail Zorluer, Afyon Kocatepe University, Turkey Kamil Bekir Afacan, Osmangazi University, Turkey Evren Seyrek, Dumlupınar University, Turkey "How much can local soil conditions amplify earthquakes? Afyonkarahisar's first GIS-based seismic microzonation study reveals local site effects and supports earthquake-resistant design."

Applsci's tweet photo. 📢#NewPublishedPaper
📚 Seismic Soil Amplification in a Thick Alluvial Basin: One-Dimensional Site Response Analysis for Afyonkarahisar, Türkiye
🔗 https://t.co/oCjyFQDAui
👨‍🔬 Süleyman Gücek and İsmail Zorluer, Afyon Kocatepe University, Turkey
Kamil Bekir Afacan, Osmangazi University, Turkey
Evren Seyrek, Dumlupınar University, Turkey

"How much can local soil conditions amplify earthquakes? Afyonkarahisar's first GIS-based seismic microzonation study reveals local site effects and supports earthquake-resistant design."

121

Applied Sciences MDPI

@Applsci

19 days ago

📢 #NewPublishedPaper 📚 Network Coding Enhanced Semantic Communications in Internet of Vehicles 🔗 https://t.co/nC1bg8UPrO 👨‍🔬 by Yanzhou Wang, Jiahang Zhong and Congduan Li. 🏫Beijing University of Posts and Telecommunications and Sun Yat-sen University #vehicularviewsharing #semanticcommunication #networkcoding #jointsource-channelcoding #roadsideunit #cooperative perception

Applsci's tweet photo. 📢 #NewPublishedPaper
📚 Network Coding Enhanced Semantic Communications in Internet of Vehicles
🔗 https://t.co/nC1bg8UPrO
👨‍🔬 by Yanzhou Wang, Jiahang Zhong and Congduan Li.
🏫Beijing University of Posts and Telecommunications and Sun Yat-sen University

#vehicularviewsharing #semanticcommunication #networkcoding #jointsource-channelcoding #roadsideunit #cooperative perception

Applied Sciences MDPI

@Applsci

20 days ago

📢 #NewPublishedPaper 📚 A Robotic Coordination Framework for Human-Robot Teams in Matrix Manufacturing 🔗https://t.co/4gfIBg4erX 👨‍🔬 by Gabriel de Moura Costa, Gonçalo Figueira, António Paulo Moreira and Marcelo R. Petry 🏫Universidade do Porto #human–robot collaboration #flexible manufacturing #industrial robotics #Industry 5.0 #cyber-physical systems #task allocation #ROS This paper presents a cyber-physical robotic coordination framework for human-robot teams deployed in an industrial matrix manufacturing system, integrating a collaborative workstation, a fleet of mobile programmable cobots, and an automatic battery changer through ROS/OPC UA communication. The framework coordinates task execution, intra-logistics, and energy management through a decision layer that assigns operations to human and robotic agents, relocates idle mobile robots, and triggers battery swaps. Three coordination modules—a Battery Management Module, a Task Allocation Module, and a Robot Relocation Module—implement this pipeline by computing feasible execution plans at each scheduling cycle, accounting for human and robot capabilities, workstation availability, transport times, and battery state. The approach is validated on a deployed industrial matrix manufacturing platform through a disassembly task comprising human-only, robot-only, and human–robot collaborative operations, demonstrating the feasibility of coordinating heterogeneous robotic and human resources in a physical reconfigurable manufacturing environment.

Applsci's tweet photo. 📢 #NewPublishedPaper
📚 A Robotic Coordination Framework for Human-Robot Teams in Matrix Manufacturing
🔗https://t.co/4gfIBg4erX
👨‍🔬 by Gabriel de Moura Costa, Gonçalo Figueira, António Paulo Moreira and Marcelo R. Petry
🏫Universidade do Porto
#human–robot collaboration #flexible manufacturing #industrial robotics #Industry 5.0 #cyber-physical systems #task allocation #ROS

This paper presents a cyber-physical robotic coordination framework for human-robot teams deployed in an industrial matrix manufacturing system, integrating a collaborative workstation, a fleet of mobile programmable cobots, and an automatic battery changer through ROS/OPC UA communication. The framework coordinates task execution, intra-logistics, and energy management through a decision layer that assigns operations to human and robotic agents, relocates idle mobile robots, and triggers battery swaps. Three coordination modules—a Battery Management Module, a Task Allocation Module, and a Robot Relocation Module—implement this pipeline by computing feasible execution plans at each scheduling cycle, accounting for human and robot capabilities, workstation availability, transport times, and battery state. The approach is validated on a deployed industrial matrix manufacturing platform through a disassembly task comprising human-only, robot-only, and human–robot collaborative operations, demonstrating the feasibility of coordinating heterogeneous robotic and human resources in a physical reconfigurable manufacturing environment.

181

Applied Sciences MDPI

@Applsci

2 months ago

📢 #NewPublishedPaper 📚 From Bioactivity to Functionality: Bridging Marine Chemical Diversity and Performance in Food Systems 🔗 https://t.co/8QryTABBLE 👨‍🔬 by Marco F. L. Lemos, Susana F. J. Silva, and Ana Augusto 🏫 Polytechnic of Leiria, Portugal #marine biotechnology #marine bioactives #food systems

Applsci's tweet photo. 📢 #NewPublishedPaper
📚 From Bioactivity to Functionality: Bridging Marine Chemical Diversity and Performance in Food Systems
🔗 https://t.co/8QryTABBLE
👨‍🔬 by Marco F. L. Lemos, Susana F. J. Silva, and Ana Augusto
🏫 Polytechnic of Leiria, Portugal
#marine biotechnology #marine bioactives #food systems

152

Nutrients MDPI @Nutrients_MDPI

6 months ago

#NewPublishedPaper Tiny Tummies, Big Questions: Unpacking Ultra-Processed Ingredients and Additives in Complementary Foods in the United States by Elizabeth K. Dunford et al. @MediPharma_MDPI Welcome to read: https://t.co/a2KP8obMkm

129

IJNS MDPI @IJNS_MDPI

about 1 year ago

#NewPublishedPaper Read "Evaluation of the Performance of Newborn Screening for Tyrosinemia Type 1 in The Netherlands: Suggestions for Improvements Using Additional Biomarkers in Addition to Succinylacetone" by Bouva, M. J. et al. 🔗 https://t.co/DVQvWvXoNG #NewbornScreening

IJNS_MDPI's tweet photo. #NewPublishedPaper

Read "Evaluation of the Performance of Newborn Screening for Tyrosinemia Type 1 in The Netherlands: Suggestions for Improvements Using Additional Biomarkers in Addition to Succinylacetone" by Bouva, M. J. et al.

🔗 https://t.co/DVQvWvXoNG

#NewbornScreening https://t.co/KfNeFISGnK

172

Energies MDPI @energies_mdpi

over 2 years ago

#mdpienergies #newpublishedpaper Levelized Cost of Biohydrogen from Steam Reforming of Biomethane with Carbon Capture and Storage (Golden Hydrogen)—Application to Spain 👉https://t.co/PseI3Oz6wX #greyhydrogen #bluehydrogen #goldenhydrogen #CCS #SMR #LCOH

energies_mdpi's tweet photo. #mdpienergies #newpublishedpaper

Levelized Cost of Biohydrogen from Steam Reforming of Biomethane with Carbon Capture and Storage (Golden Hydrogen)—Application to Spain

👉https://t.co/PseI3Oz6wX

#greyhydrogen #bluehydrogen #goldenhydrogen #CCS #SMR #LCOH https://t.co/FAnq55TAGG

250

Enzo Peruffo @EnzoPeruffo

almost 8 years ago

#familybusiness #greeninnovation #newpublishedpaper with antonio Petruzzelli e lorenzo ardito https://t.co/R1wm8W2yD7

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