Article
Multidisciplinary Sciences
Juan Carlos Castro-Palacio, Pedro Fernandez-de-Cordoba, J. M. Isidro, Sarira Sahu, Esperanza Navarro-Pardo
Summary: This study introduces a Physics-inspired model to represent individual reaction time data as a Maxwell-Boltzmann distribution within a coetaneous group, providing a new framework for understanding collective responses. Additionally, a simple entropy-based methodology for classifying individuals within a collective without the need for external reference is proposed, which can be applied across various social science fields.
Article
Construction & Building Technology
Michael Kim, Athanasios Tzempelikos
Summary: This paper proposes a framework for non-intrusive luminance monitoring based on re-projected luminance maps, which can accurately predict and monitor the luminance distributions in the occupant field of view. The study highlights the importance of such monitoring for human-centered daylighting control.
BUILDING AND ENVIRONMENT
(2022)
Article
Business
Karin Sanders, Phong T. Nguyen, Dave Bouckenooghe, Alannah E. Rafferty, Gavin Schwarz
Summary: During times of crisis, employees look to their managers for information and guidance. Sharing distinctive, consistent, and consensual information, also known as human resource management (HRM) system strength, makes it easier for employees to understand their roles. This study explores the factors that influence managers when sharing information with employees, and suggests that the interaction between managers' motivation and their cultural values can explain HRM system strength in times of crisis. The findings indicate that crisis severity and organization reputation have stronger effects on HRM system strength in countries with high uncertainty avoidance, but weaker effects in countries with high power distance. Implications for theory and practice are discussed.
JOURNAL OF BUSINESS RESEARCH
(2024)
Article
Environmental Sciences
Yixin Zhang, Zhijie Wu
Summary: The Human Development Index (HDI) and Environmental Performance Index (EPI) are important indicators for measuring sustainable development. Combining these indicators can assess socio-ecological sustainability. A study on China's development showed significant progress in human development, but weak environmental performance. Analysis indicated that urbanization and economic growth put pressure on the environment.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Chemistry, Multidisciplinary
Md Mehedi Hasan, Md Ariful Islam, Sejuti Rahman, Michael R. Frater, John F. Arnold
Summary: Provisioning high-quality stereoscopic 3D video transmission services in a wireless environment is a significant challenge. This paper proposes a no-reference quality assessment method based on the human visual system to evaluate the quality of stereoscopic 3D videos. By evaluating perceptual aspects and correlations of visual binocular impacts, the proposed method can objectively measure impairments and has shown good performance in experiments.
APPLIED SCIENCES-BASEL
(2022)
Article
Medicine, General & Internal
Gijs Thepass, Hans G. Lemij, Koenraad A. Vermeer, Johannes van der Steen, Johan J. M. Pel
Summary: The study found that the saccadic reaction time was significantly prolonged in patients with mild, moderate, and advanced glaucoma, regardless of whether sensitivity loss was detected in SAP. This suggests that altered sensory processing in glaucoma may occur before changes in visual field sensitivity are detected, potentially enabling earlier diagnosis of the condition.
FRONTIERS IN MEDICINE
(2021)
Article
Biology
Abhijit Dutta, Himadri Chattopadhyay
Summary: The study developed a comprehensive thermodynamic model for the human respiratory system, finding that respiratory efficiency increases with inspiratory air temperature and relative humidity but decreases with O2 percentage. The efficiency of the respiratory system decreases from rest to moderate and extreme levels of activity under different physiological conditions.
JOURNAL OF THERMAL BIOLOGY
(2021)
Article
Electrochemistry
Sivaprakasam Radhakrishnan, Selva Chandrasekaran Selvaraj, Tae Hoon Ko, Jayaraman Mathiyarasu, Byoung-Suhk Kim
Summary: The fabrication of metal phosphonate (MP) products with desired morphologies is challenging due to uncontrolled precipitation reactions. However, the fabrication of MP nanomaterial with controlled morphologies is important for potential applications. We report the synthesis of uniform one-dimensional (1D) nickel phenylphosphonate (NiPP) nanorods without templates. The formation mechanism of NiPP with 1-D nanostructure is systematically investigated for the first time. The prepared NiPP nanorods are further used as electrocatalysts.
ELECTROCHIMICA ACTA
(2023)
Article
Neurosciences
Olga Lukashova-Sanz, Siegfried Wahl
Summary: The study investigated the potential of improving visual search performance through subtle saliency-aware modulation of the scene. Results showed that blurring salient regions can help participants find the target faster, which has potential implications for enhancing user performance in everyday visual search tasks.
Article
Neurosciences
Edmund T. Rolls, Gustavo Deco, Chu-Chung Huang, Jianfeng Feng
Summary: This study investigates the effective connectivity in the human hippocampal memory system, revealing the directionality and strength of the connections between different brain regions. By connecting different information streams with the hippocampus, the hippocampal function is optimized.
Article
Neurosciences
Areej A. Alhamdan, Melanie J. Murphy, Sheila G. Crewther
Summary: The contribution of motor development to measures of multisensory and visuomotor processing tasks in young school age children was investigated, showing age-related differences. The results suggest that motor development plays a more significant role in multisensory facilitation compared to visual sensory system development. Additionally, multisensory integration may continue into late childhood/early adolescence.
FRONTIERS IN HUMAN NEUROSCIENCE
(2022)
Article
Construction & Building Technology
Andisheh Zahedi, Leandro F. M. Sanchez, Martin Noel
Summary: Conventional visual inspection techniques are unable to accurately assess the extent of alkali-silica reaction-induced damage in concrete. This study aims to evaluate the development of ASR-induced damage on different surfaces of concrete blocks using visual and microscopic techniques. Results show that higher confinement leads to increased surface damage in affected members.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Chemistry, Physical
Yue Shi, Dan Zhang, Hongfu Miao, Wen Zhang, Xueke Wu, Zuochao Wang, Hongdong Li, Tianrong Zhan, Xilei Chen, Jianping Lai, Lei Wang
Summary: Transition metal-based selenides synthesized using a simple, rapid, and scalable microwave method exhibit excellent catalytic properties for the oxygen evolution reaction. Optimized composition of the material shows outstanding water oxidation performance.
JOURNAL OF MATERIALS CHEMISTRY A
(2021)
Article
Multidisciplinary Sciences
Asmaa M. Elsotohy, Ahmed Mohammed Attiya Soliman, Ahmed S. Adail, Ayman A. Eisa, El-said A. Othman
Summary: Studying and evaluating the power quality (PQ) is crucial for the safe and accurate operation of sensitive equipment, especially in nuclear installations. This study aims to assess the PQ performance of the electrical power system at a Nuclear Research Reactor (NRR) using multiple measures for various PQ phenomena. The results are analyzed and discussed to evaluate the performance of the NRR electrical system from the PQ perspective. The findings show that the compromise solution obtained through the CRITIC-VIKOR method can serve as a guide for PQ evaluation in nuclear installations and provide benefits for benchmarking and monitoring.
SCIENTIFIC REPORTS
(2023)
Article
Multidisciplinary Sciences
Pralay Gayen, Sulay Saha, Xinquan Liu, Kritika Sharma, Vijay K. Ramani
Summary: The study focuses on the bifunctional oxygen electrocatalyst for fixed-gas unitized regenerative fuel cells (FG-URFCs), synthesizing Pt-Pb2Ru2O7-x which shows superior ORR and OER activity compared to benchmark electrocatalysts. It demonstrates potential for applications in AEM URFC or metal-air battery.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Energy & Fuels
Oracio Barbosa-Ayala, Jhon A. Montanez-Barrera, Cesar E. Damian-Ascencio, Adriana Saldana-Robles, J. Arturo Alfaro-Ayala, Jose Alfredo Padilla-Medina, Sergio Cano-Andrade
Article
Chemistry, Multidisciplinary
Victor Samano-Ortega, Alfredo Padilla-Medina, Micael Bravo-Sanchez, Elias Rodriguez-Segura, Alonso Jimenez-Garibay, Juan Martinez-Nolasco
APPLIED SCIENCES-BASEL
(2020)
Article
Chemistry, Analytical
Celia Francisco-Martinez, Juan Prado-Olivarez, Jose A. Padilla-Medina, Javier Diaz-Carmona, Francisco J. Perez-Pinal, Alejandro I. Barranco-Gutierrez, Juan J. Martinez-Nolasco
Summary: This paper focuses on identifying techniques for the quantitative assessment of upper limb movements in children with cerebral palsy, utilizing optoelectronic devices, wearable sensors, and low-cost Kinect sensors. Results showed an improvement in motor function and daily tasks in the study population, with optoelectronic devices being the most commonly used. The potential of wearable sensors and Kinect sensors as complementary devices for quantitative evaluation of upper limb movements was evident.
Article
Chemistry, Multidisciplinary
Daniel Alberto Garcia-Espinosa, Miguel Leon-Rodriguez, Pedro Yanez-Contreras, Israel Miguel-Andres, Jose Alfredo Padilla-Medina, Alejandra Cruz-Bernal, Patricia Ibarra-Torres
Summary: This study explores the behavior and distribution of nanoparticles generated from commonly used printable materials in fused deposition modeling (FDM) using digital holographic microscopy (DHM). The experimental results validate the feasibility of using DHM to determine the presence of nanoparticles in the FDM process, providing extensive knowledge about the implications of FDM on health.
APPLIED SCIENCES-BASEL
(2022)
Article
Chemistry, Analytical
Celia Francisco-Martinez, Jose A. Padilla-Medina, Juan Prado-Olivarez, Francisco J. Perez-Pinal, Alejandro Barranco-Gutierrez, Juan J. Martinez-Nolasco
Summary: The interruption of rehabilitation activities due to the COVID-19 lockdown has negatively affected the health of people with physical disabilities. This paper describes a Kinect v2-based active range of motion (AROM) measuring system for upper limb motion analysis. The system was tested on two groups of children and compared with a universal goniometer, showing no significant differences in the measured angles and FMA assessments. The developed system is a good alternative for assessing AROM and motor performance of upper limbs in both healthy children and children with spastic hemiparesis.
Article
Chemistry, Analytical
Marcos Gutierrez-Lopez, Juan Prado-Olivarez, Carolina Matheus-Troconis, Alfredo Padilla-Medina, Alejandro Barranco-Gutierrez, Alejandro Espinosa-Calderon, Carlos A. Herrera-Ramirez, Javier Diaz-Carmona
Summary: The study explores a bioimpedance-based method, ATC, to analyze breast density and potentially serve as an objective tool to evaluate breast cancer risk. The results indicate a correlation between ATC variation and breast density, highlighting the potential of this approach as a complementary tool to mammography for precise and objective breast density evaluation.
Article
Chemistry, Analytical
Hugo A. Mendez-Guzman, Jose A. Padilla-Medina, Coral Martinez-Nolasco, Juan J. Martinez-Nolasco, Alejandro Barranco-Gutierrez, Luis M. Contreras-Medina, Miguel Leon-Rodriguez
Summary: The article discusses the use of an IoT monitoring system in greenhouses to provide information on climatic variables and crop status, enabling optimal decision-making for irrigation and inspections. This innovative system has the potential to enhance aeroponic farming practices through IoT-assisted monitoring.
Article
Chemistry, Multidisciplinary
Coral Martinez-Nolasco, Jose A. Padilla-Medina, Juan J. Martinez Nolasco, Ramon Gerardo Guevara-Gonzalez, Alejandro Barranco-Gutierrez, Jose J. Diaz-Carmona
Summary: This study evaluated the growth of lettuce plants in an aeroponic environment using multispectral image processing and temperature analysis methods. The results showed that the morphometric parameters of the root and leaf growth can be effectively characterized using the implemented imaging system. Additionally, a strong correlation was found between the plant temperature and the ambient temperature in aeroponic crops.
APPLIED SCIENCES-BASEL
(2022)
Article
Mathematics
Marcos J. Villasenor-Aguilar, Jose E. Peralta-Lopez, David Lazaro-Mata, Carlos E. Garcia-Alcala, Jose A. Padilla-Medina, Francisco J. Perez-Pinal, Jose A. Vazquez-Lopez, Alejandro Barranco-Gutierrez
Summary: The incorporation of high precision vehicle positioning systems is demanded by the AEV industry. Research on VO and AI to reduce positioning errors automatically is essential. This work presents a new method using FL to reduce AEV's absolute location error and performs data fusion to improve localization estimation. The proposed model using all sensors (stereo camera, odometer, and GPS) reduces positioning MAE up to 25% compared to the state of the art.
Article
Neurosciences
Mauro Santoyo-Mora, Carlos Villasenor-Mora, Luz M. Cardona-Torres, Juan J. Martinez-Nolasco, Alejandro Barranco-Gutierrez, Jose A. Padilla-Medina, Micael Gerardo Bravo-Sanchez
Summary: This study evaluated cognitive damage in post-COVID-19 patients. The results showed that patients who recovered from severe-critical cases performed poorly in various cognitive tests, indicating significant reduction in cognitive processes capabilities due to damage caused by the coronavirus on the central nervous and visual systems.
Article
Computer Science, Information Systems
V Samano-Ortega, H. Mendez-Guzman, J. Martinez-Nolasco, J. Padilla-Medina, M. Santoyo-Mora, J. Zavala-Villalpando
Summary: In Latin America and the Caribbean, the use of fossil resources for energy consumption has led to increased air pollution. The residential sector, particularly in electricity generation and consumption, contributes significantly to this problem. However, recent research has shown that smart energy meters can reduce electricity consumption in developed countries by providing continuous feedback to consumers. This study presents the development and implementation of an electrical energy consumption monitoring system using IoT technology. The system calculates instant power, electrical efficiency, energy consumption, and cost. The data is processed and transmitted to a cloud database using a WIFI ESP8266 module. An Android mobile application is also developed for users to visualize the variables. The accuracy of the smart sensors is validated by comparing their measurements with those of an oscilloscope and a multimeter, with relative errors ranging from -2.34% to 1.92%.
IEEE LATIN AMERICA TRANSACTIONS
(2023)
Article
Chemistry, Multidisciplinary
Moises Arredondo-Velazquez, Paulo Aaron Aguirre-Alvarez, Alfredo Padilla-Medina, Alejandro Espinosa-Calderon, Juan Prado-Olivarez, Javier Diaz-Carmona
Summary: This paper presents a flexible convolver that can adapt to different convolution layer configurations of state-of-the-art CNNs. The adaptability is achieved by using two proposed programmable components. A Programmable Line Buffer based on Programmable Shift Registers generates the required convolution masks for each processed CNN layer. The convolution layer computing is performed through a proposed programmable systolic array. The experimental results show that the proposed computing method allows for the processing of any CNN without requiring special adaptation for a specific application.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Multidisciplinary
Juan Aguilera-Alvarez, Juan Martinez-Nolasco, Sergio Olmos-Temois, Jose Padilla-Medina, Victor Samano-Ortega, Micael Bravo-Sanchez
Summary: This paper presents a web application that semi-automatically quantifies the amount of coronary artery calcium using the Agatston technique. The application's functionality was verified and compared to commercial software, showing potential clinical application.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Information Systems
Celia Francisco-Martinez, Karla S. Morales-Soto, Juan Prado-Olivarez, Javier Diaz-Carmona, Jose A. Padilla-Medina, Alejandro I. Barranco-Gutierrez, Carlos A. Herrera-Ramirez, Alejandro Espinosa-Calderon
Summary: This paper describes a study on the quantitatively assessment of upper limb motor performance using the NUI Kinect v2 sensor for children with spastic hemiparesis. The results show that the applied Modified Constrained-Induced Movement Therapy (mCIMT) effectively improved upper extremity motor performance, and also identified post-rehabilitation movement limitations. The described NUI assessment method has the potential to be used as a quantitative measurement tool for objective diagnosis and defining appropriate rehabilitation therapy.
Article
Computer Science, Information Systems
Victor Samano-Ortega, Hugo Mendez-Guzman, Jose Padilla-Medina, Juan Aguilera-Alvarez, Coral Martinez-Nolasco, Juan Martinez-Nolasco
Summary: This article presents the development of a platform for validating controllers applied to photovoltaic systems using real-time hardware in the loop simulation and Internet of Things. The platform consists of a control emulator, a cloud database, a smart sensor, a residential photovoltaic system, and an Android application. It successfully replicates the behavior of the photovoltaic system and AC loads, with low errors and good data transfer performance.
Article
Biology
Seyyed Bahram Borgheai, Alyssa Hillary Zisk, John McLinden, James Mcintyre, Reza Sadjadi, Yalda Shahriari
Summary: This study proposed a novel personalized scheme using fNIRS and EEG as the main tools to predict and compensate for the variability in BCI systems, especially for individuals with severe motor deficits. By establishing predictive models, it was found that there were significant associations between the predicted performances and the actual performances.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Hongliang Guo, Hanbo Liu, Ahong Zhu, Mingyang Li, Helong Yu, Yun Zhu, Xiaoxiao Chen, Yujia Xu, Lianxing Gao, Qiongying Zhang, Yangping Shentu
Summary: In this paper, a BDSMA-based image segmentation method is proposed, which improves the limitations of the original algorithm by combining SMA with DE and introducing a cooperative mixing model. The experimental results demonstrate the superiority of this method in terms of convergence speed and precision compared to other methods, and its successful application to brain tumor medical images.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jingfei Hu, Linwei Qiu, Hua Wang, Jicong Zhang
Summary: This study proposes a novel semi-supervised point consistency network (SPC-Net) for retinal artery/vein (A/V) classification, addressing the challenges of specific tubular structures and limited well-labeled data in CNN-based approaches. The SPC-Net combines an AVC module and an MPC module, and introduces point set representations and consistency regularization to improve the accuracy of A/V classification.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Omair Ali, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis, Christian Klaes
Summary: This study introduces a novel hybrid model called ConTraNet, which combines the strengths of CNN and Transformer neural networks, and achieves significant improvement in classification performance with limited training data.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Juan Antonio Valera-Calero, Dario Lopez-Zanoni, Sandra Sanchez-Jorge, Cesar Fernandez-de-las-Penas, Marcos Jose Navarro-Santana, Sofia Olivia Calvo-Moreno, Gustavo Plaza-Manzano
Summary: This study developed an easy-to-use application for assessing the diagnostic accuracy of digital pain drawings (PDs) compared to the classic paper-and-pencil method. The results demonstrated that digital PDs have higher reliability and accuracy compared to paper-and-pencil PDs, and there were no significant differences in assessing pain extent between the two methods. The PAIN EXTENT app showed good convergent validity.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Biao Qu, Jialue Zhang, Taishan Kang, Jianzhong Lin, Meijin Lin, Huajun She, Qingxia Wu, Meiyun Wang, Gaofeng Zheng
Summary: This study proposes a deep unrolled neural network, pFISTA-DR, for radial MRI image reconstruction, which successfully preserves image details using a preprocessing module, learnable convolution filters, and adaptive threshold.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Alireza Rafiei, Milad Ghiasi Rad, Andrea Sikora, Rishikesan Kamaleswaran
Summary: This study aimed to improve machine learning model prediction of fluid overload by integrating synthetic data, which could be translated to other clinical outcomes.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jinlian Ma, Dexing Kong, Fa Wu, Lingyun Bao, Jing Yuan, Yusheng Liu
Summary: In this study, a new method based on MDenseNet is proposed for automatic segmentation of nodular lesions from ultrasound images. Experimental results demonstrate that the proposed method can accurately extract multiple nodules from thyroid and breast ultrasound images, with good accuracy and reproducibility, and it shows great potential in other clinical segmentation tasks.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jiabao Sheng, SaiKit Lam, Jiang Zhang, Yuanpeng Zhang, Jing Cai
Summary: Omics fusion is an important preprocessing approach in medical image processing that assists in various studies. This study aims to develop a fusion methodology for predicting distant metastasis in nasopharyngeal carcinoma by mitigating the disparities in omics data and utilizing a label-softening technique and a multi-kernel-based neural network.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Zhenxiang Xiao, Liang He, Boyu Zhao, Mingxin Jiang, Wei Mao, Yuzhong Chen, Tuo Zhang, Xintao Hu, Tianming Liu, Xi Jiang
Summary: This study systematically investigates the functional connectivity characteristics between gyri and sulci in the human brain under naturalistic stimulus, and identifies unique features in these connections. This research provides novel insights into the functional brain mechanism under naturalistic stimulus and lays a solid foundation for accurately mapping the brain anatomy-function relationship.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Qianqian Wang, Mingyu Zhang, Aohan Li, Xiaojun Yao, Yingqing Chen
Summary: The development of PARP-1 inhibitors is crucial for the treatment of various cancers. This study investigates the structural regulation of PARP-1 by different allosteric inhibitors, revealing the basis of allosteric inhibition and providing guidance for the discovery of more innovative PARP-1 inhibitors.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Qing Xu, Wenting Duan
Summary: In this paper, a dual attention supervised module, named DualAttNet, is proposed for multi-label lesion detection in chest radiographs. By efficiently fusing global and local lesion classification information, the module is able to recognize targets with different sizes. Experimental results show that DualAttNet outperforms baselines in terms of mAP and AP50 with different detection architectures.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Kaja Gutowska, Piotr Formanowicz
Summary: The primary aim of this research is to propose algorithms for identifying significant reactions and subprocesses within biological system models constructed using classical Petri nets. These solutions enable two analysis methods: importance analysis for identifying critical individual reactions to the model's functionality and occurrence analysis for finding essential subprocesses. The utility of these methods has been demonstrated through analyses of an example model related to the DNA damage response mechanism. It should be noted that these proposed analyses can be applied to any biological phenomenon represented using the Petri net formalism. The presented analysis methods extend classical Petri net-based analyses, enhancing our comprehension of the investigated biological phenomena and aiding in the identification of potential molecular targets for drugs.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Hansle Gwon, Imjin Ahn, Yunha Kim, Hee Jun Kang, Hyeram Seo, Heejung Choi, Ha Na Cho, Minkyoung Kim, Jiye Han, Gaeun Kee, Seohyun Park, Kye Hwa Lee, Tae Joon Jun, Young-Hak Kim
Summary: Electronic medical records have potential in advancing healthcare technologies, but privacy issues hinder their full utilization. Deep learning-based generative models can mitigate this problem by creating synthetic data similar to real patient data. However, the risk of data leakage due to malicious attacks poses a challenge to traditional generative models. To address this, we propose a method that employs local differential privacy (LDP) to protect the model from attacks and preserve the privacy of training data, while generating medical data with reasonable performance.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Siwei Tao, Zonghan Tian, Ling Bai, Yueshu Xu, Cuifang Kuang, Xu Liu
Summary: This study proposes a transfer learning-based method to address the phase retrieval problem in grating-based X-ray phase contrast imaging. By generating a training dataset and using deep learning techniques, this method improves image quality and can be applied to X-ray 2D and 3D imaging.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
