bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling the impact of genetically modified humans on the transmission dynamics of COVID-19: Case study of Nigeria
Authors: Idisi Oke Isaiah , Onifade Akindele Akano , Kareem Lateef
Published: February 2024

The emergence of a coronavirus disease (COVID-19) pandemic caused by severe acute respiratorysyndrome coronavirus 2 (SARS-COV 2) has caused an unprecedented global societal andpublic health crisis. A novel variable (genetically resistant humans, which they serve as reservoirhost) that could influence the prevalence of COVID-19 pandemic have been incorporatedand analyzed rigorously. Detection and testing for COVID-19 (in humans that are geneticallyresistant to COVID-19), proper preventive measures, and timely medical care are essential inmanaging and controlling COVID-19 outbreak. First, we analyze the disease-free state of theCOVID-19 model, calculate the baseline control reproduction number, and obtain the localstability of disease-free equilibrium. The model is calibrated using data obtained from NigeriaCentre for Disease Control and key parameters of the model are estimated. Sensitivity analysisis carried out to investigate the influence of the parameters in curtailing the disease. Numericalsimulations are then used to explore the behaviour of the model solutions involving the novelvariable (genetically resistant humans) and control measures. Our results suggest that strictintervention effort (early detection of genetically resistant individuals, testing and isolation ofthe infected individuals) is required for quick suppression of the disease.
Ultra-selective and Stable Ethylene Detection via Exsolution of Catalytic Ni Nanoparticles in Chemiresistive Gas Sensors
Authors: Jeong Youngkyu , Lee Jieon , Kwon Yong Jung , Choi Hyeunseok , Kim Soo Young , Lee Jung-Hoon
Published: February 2024

Ethylene, a gaseous indicator that provides critical information about plant aging, is biologically active in plants, even at trace levels. Therefore, it must be precisely monitored and controlled at sub-ppm levels. However, the accurate detection and clear identification of ethylene has been a major challenge, owing to its low chemical reactivity and severe interference with other gases, including water vapor. In this study, we devised a novel sensor capable of detecting even trace amounts of ethylene using ZnO nanoflowers embedded with exsolved Ni nanocatalysts. It completely removed interferents via catalytic oxidation and exhibited remarkable gas selectivity (approximately 60 and 32 to 1 and 0.2 ppm ethylene, respectively) and an excellent stability against humidity variations. Furthermore, owing to robust metal-support interactions in the nanocatalysts, the sensor exhibited excellent thermal stability and reliable long-term sensing performance at elevated temperatures. This study provides an approach for facilitating the successful commercialization of ethylene detectors.
Integrating Numerical Techniques and Predictive Diagnosis for Precision Enhancement in Roller Cam Rotary Table
Authors: Chan Tzu-Chi , Wu Shao Chi , Ullah Aman , Farooq Umar , Wang I-Hung , Chang Shinn-Laing
Published: February 2024

Currently, various industries are increasingly trending towards multi-axis machining and Industry 4.0. As a result, the demand for machining flexibility, speed, and precision in machine tools is also rising. Different manufacturers provide many components of machine tools, and the alignment precision, main structure, component rigidity, and dynamic performance of these components all impact the machining precision of multi-axis machine tools. Therefore, the structural design of each component is crucial. In this study, a roller cam rotary table is selected for analysis using the Finite Element Method, considering the constraints of the machine environment. The investigation includes Vibration mode shape, gravitational load, External loading, transient, spectral, and topology optimization inspection. The static analysis reveals weak points in the machine's structure. Modal analysis helps understand the natural frequencies that affect the machine's structure, resulting in mitigation of resonance during the machining process and enhancing machining precision. Finally, the modal impact test is conducted using accelerometers and an impact hammer whereas ME'scope curve fitting is employed to determine the mode shapes and natural frequencies. The results are compared to validate the accuracy of the analysis, with a deviation of 8.5%, 8.3%, and 1.4%. Topological optimization analysis is performed on machine components, aiming to reduce weight and improve natural frequencies as compared to the original design. Precision tests such as repeatability and segmentation accuracy are essential for rotary tables. These tests provide information about the errors at different angles, ensuring accuracy, reliability, and quality during the machining process. In this study, vibration signals from the rotary table are captured using a smart predictive diagnosis performance system (PDPS). An algorithm is used to analyze the normal vibration signals and establish a healthy model for continuous monitoring of the rotary table's health status. Principal Component Analysis (PCA) is applied to identify fault features and diagnose mechanical problems. This enables early detection of anomalies in the rotary table, reducing downtime and maintenance costs due to damage and improving the machine's efficiency.
Basic magnesium sulfate@TiO2 composite for efficient adsorption and photocatalytic degradation of 4-dodecylmorpholine in brine
Authors: Song Zhongmei , Zhang Huifang , Ma Liang , Lu Miao , Wu Chengyou , Liu Qingqing , Yu Xuefeng , Liu Haining , Ye Xiushen , Ma Zhen , Wu Zhijian
Published: February 2024

More than 70% of the potash fertilizer globally is produced by the froth flotation process, in which 4-dodecylmorpholine (DMP) serves as a reverse flotation agent. As the potash fertilizer production rapidly rises, the increased DMP levels in discharged brine pose a threat to the production of high-value chemicals. In this paper, composite particles of basic magnesium sulfate@TiO2 (BMS@TiO2) were prepared using a simple and mild loading method. These particles were utilized for the adsorption and photocatalytic degradation of DMP in brine. Compared with normal powdered materials, the granular BMS@TiO2 in this study can be easily separated from liquid, and the degradation intermediates will not enter the brine without causing secondary pollution. BMS@TiO2 consists of 5·1·7 phase (5Mg(OH)2·MgSO4·7H2O) whisker clusters embedding 2.3% TiO2. The adsorption equilibrium of DMP on BMS@TiO2 particles was achieved through electrostatic attraction and pore interception with the adsorption capacity of approximately 5 mg·g-1 after 6 hours. The photodegradation efficiency of DMP adsorbed on BMS@TiO2 reached about 92% within 16 hours, which is compared with that of pure TiO2 nanoparticles. Additionally, excellent stability and recyclability of BMS@TiO2 were also observed in five cycle tests of adsorption and photocatalytic degradation of DMP, and the possible photocatalytic degradation pathways and mechanism of DMP are proposed following molecular electrostatic potential analysis. This work provides a sustainable and environmentally friendly approach for eliminating organic micropollutants from water environments.
Gender sensitivity in nursing practice: Exploring the relationship with childhood experience of domestic violence and perception of sexism
Authors: Yun Sun Jeong , Kim Hye Young
Published: February 2024

Background
Gender sensitivity is the ability to recognize gender discrimination and inequality, starting with awareness of ‘gender difference’ issues. Research on nurses' gender sensitivity is very important because nursing is sensitive to gender differences and provides nursing care based on a holistic understanding of individuals. Therefore, this study will determine the impact of childhood experience of domestic violence and perception of sexism of nurses providing health care on gender sensitivity and provide basic data for disseminating the practical concept of gender equality within nursing organizations.
Methods
A cross-sectional survey was conducted among 146 nurses aged 24 years or older living in Daegu. The general characteristics of nurses, childhood experience of domestic violence, perception of sexism, and gender sensitivity were determined. Data were analyzed using SPSS for t-test, one-way analysis of variance, Pearson's correlation coefficient, and hierarchical regression analysis.
Results
Participants' gender sensitivity was not statistically significantly related to the extent to which they childhood experience of domestic violence, but it was negatively related to their perceptions of sexism (r = − .46, p < .001). Age (β = .13, p < .001) and perception of sexism (β = − .48, p = .002) were identified as factors influencing gender sensitivity. According to the regression model, the explanatory power of the factors influencing gender sensitivity among nurses was 42.7%.
Conclusion
To improve nurses' gender sensitivity, it is necessary to acknowledge cultural differences between generations and adopt a flexible and open approach within nursing organizations. Additionally, there is a need to strengthen the cultural awareness and capabilities of leaders within nursing organizations to increase perception of sexism. Meanwhile, because the standards for understanding the extent of childhood experience of domestic violence vary depending on society and culture, additional research is needed that considers sociodemographic differences.
Determination of direct tensile strength of rocks using a load converter
Authors: Baêsso Ana Carolina Dias , Vargas Eurípedes Amaral , Velloso Raquel Quadros , Marques Eduardo Antonio Gomes
Published: February 2024

The tensile strength of rocks is of great importance in many engineering and geophysical applications. Considered a key parameter in rock mechanics projects, its determination in the laboratory has been discussed for years by many researchers with two approaches: the direct tensile test, considered the ideal and most realistic, has its credibility compromised due to eventual poor execution issues; and, on the other hand, indirect tests, due to its practicality and dissemination around the world. In this context, the present work presents the results obtained with an equipment named compression to tension load converter (CTC), which allows the determination of the tensile strength of rocks in a direct and reliable way. A numerical analysis was carried out to study the stress distribution in the specimen during testing with the apparatus. Uniaxial compression tests, Brazilian and CTC tests were performed in a granitic rock from Southeastern Brazil, in order to compare the results obtained with results available in the literature. This work presents and discusses the results obtained with the CTC apparatus and compared them with results obtained with conventional indirect tensile strength tests.
The Proteus Effect on Human Pain Perception: Effects of Muscular Avatar Use and Gender Factors
Authors: Yim Youchan , Xia Zongheng , Kubota Yuki , Tanaka Fumihide
Published: February 2024

The Proteus Effect, which occurs when using an avatar in virtual reality, influences user behavior, changes attitudes, and improves physical performance. Here, we show that human pain perception can be alleviated by the Proteus effect. Experimental results show that participants reported significantly lower pain scores (15.982% reduction), as measured by the Pain Assessment Scale (PAS), when using a muscular avatar than when using a normal avatar. The experiments also revealed several significant gender factors. For example, participants reported significantly lower pain scores when using a gender-congruent avatar. In addition, the use of a muscular avatar was particularly effective for male participants. In contrast, female participants consistently reported lower pain scores when using the avatar regardless of its body type (muscular/normal). To further our understanding, we also measured participants' gender-related pain stereotypes using the Gender Role Expectations of Pain (GREP) questionnaire, as well as participants' sense of embodiment. The results of these questionnaires are consistent with the results of the PAS, suggesting possible relationships between stereotypes and the Proteus effect on pain perception, and between the degree of immersion in an avatar and the user's perception of pain.
Preparation and antibacterial properties of polypropylene composite with bisphenol A-type benzoxazine.
Authors: Shang Xiaoyu , Zhou Changlu , Zhang Xian , Xin Zhong
Published: February 2024

Polypropylene (PP) is a commonly used material in medical supplies. However, its lack of antibacterial properties has led to a frequent occurrence of healthcare-associated infections that need to be addressed. This study extensively investigates the antibacterial effects of bisphenol A-type benzoxazine (BA-a), revealing a relationship between the curing degree of BA-a and its antibacterial performance. A lower degree of curing corresponds to stronger antibacterial activity. Based on this relationship, a melt blending method at 170°C is determined to prepare PP/BA-a composite material, aiming to enhance the antibacterial properties. The antibacterial performance of PP/BA-a is evaluated by plate coating method. The results demonstrate that PP/0.8BA-a exhibits an antibacterial rate as high as 99.99% against E. coli and S. aureus. Migration experiments confirm the stability of the antibacterial effect. The extracts from PP/BA-a show no toxicity towards mouse fibroblast cells (L929). Furthermore, compared to pure PP, the addition of BA-a improves the thermal stability of PP/BA-a, with an increase of 56°C in the onset thermal decomposition temperature (T5%), enabling PP to better adapt to the high-temperature environment of moist heat sterilization. This study presents a novel method for obtaining highly antibacterial medical polymer materials (PP/BA-a) with broad application prospects.
Practices and attitudes of herbalists regarding informed consent in Uganda: A qualitative study
Authors: Nalubega Sumayiya , Kutyabami Paul , Twimukye Adeline , Mafigiri David. K. , Sewankambo Nelson. K.
Published: February 2024

Background
Informed consent (IC) is a fundamental principle in medical ethics that upholds respect for patient autonomy. Although widely applied in healthcare, its feasibility and implementation in herbal medicine have been underexplored. This study therefore aimed to explore the practices and attitudes of herbalists regarding informed consent.
Methods
To achieve these objectives, a qualitative cross-sectional study was conducted from June to December 2020. Twenty-one in-depth interviews with herbalists and four key informant interviews with leaders of the different traditional medicine organizations were also conducted. The data were analyzed thematically using NVivo version 12 software.
Results
Sixteen of the twenty-one participants acquired oral herbal medicine knowledge from their relatives. Although a positive inclination toward obtaining IC was evident, the focus was on disclosing basic information. Discussions of alternative treatments and herbal specifics less frequent. Disease management decisions often involve shared responsibility within families or societies. Documented IC procedures are rare among herbalists, who deem consent forms unnecessary, although they recognize the potential benefits of IC in fostering trust and professionalism. Challenges hindering IC implementation included regulatory gaps, inadequate skills, and the absence of mechanisms to protect the intellectual property rights of herbal medicine.
Conclusion
This study illuminates how educational, cultural, familial, and regulatory factors influence herbalists' practices and attitudes toward informed consent.
A convergent semi-Lagrangian scheme for the game ∞-Laplacian
Authors: Carlini Elisabetta , Tozza Silvia
Published: February 2024

We propose a new semi-Lagrangian scheme for the game ∞-Laplacian. We demonstrate the convergence of the scheme to the viscosity solution of the given problem, showing its consistency, monotonicity, and stability. The proof of this convergence is established through the Barles-Souganidis convergence analysis. This analysis assumes convergence at the boundary in a strong sense and is applied to our proposed scheme, augmented with an artificial viscosity term.
MSC Classification: 65N06 , 35J25 , 35D40 , 65N12
Exploiting nonlinear spring oscillator chain as acoustic metasurfaces for high harmonic generation
Authors: Sun Chenghao , Wang Haoyu , Li Yuanyuan , Fei Zhonghan , Lai Yun , Liu Xiaozhou
Published: February 2024

This paper introduces a novel approach to design acoustic metasurfaces utilizing multiple nonlinear spring oscillator chains, which enables an exceptional ability to generate harmonics in the radiated sound field. The metasurface unit is a chain of masses connected by two nonlinear springs exhibiting two resonance frequencies. The fundamental and second harmonic components of the vibration amplitude are solved by the Multiple Scales Method (MSM). By strategically configuring the higher resonance frequency of the spring oscillator to be n times that of the lower frequency and exciting the system with the lower frequency, the energy transfers from the low-frequency mode to the high-frequency mode induced by nonlinearity, leading to the large vibration amplitude of the high-frequency mode. The robustness and validity of this method are substantiated through the excellent consistency between the theoretical and numerical results. Furthermore, we showcase a nonlinear metasurface with more high-harmonic transmission by judiciously adjusting the structural parameters. Parameter tuning including adjustments to the quadratic nonlinear coefficient, resonance frequency, and excitation frequency further underscores the robustness of this nonlinear system, providing insights for designing general nonlinear metasurfaces. Our work lays a solid foundation for realizing harmonics in nonlinear spring oscillators, extending the research scope of acoustic metasurfaces into nonlinear dynamics.
Redundancy Resolution of a Mobile Manipulator Using Learning Based Algorithm
Authors: Tolossa Tesfaye Deme , Gupta Rajeev , Orlando M. Felix , Hote Yogesh Vijay
Published: February 2024

A learning-based strategy for the trajectory tracking of redundant mobile manipulators (MM) was presented in this study. A five-degrees-of-freedom (DOF) manipulator is mounted on the differential drive (DD) mobile robot. The advantage of using a redundant system is to avoid joint limits, obstacles and singularities towards desired trajectory tracking. The proposed approach is based on Kohonen Self-Organizing Map (KSOM) enhanced a weighted least norm (WLN) matrix algorithm. This approach is the recommended neural network for inverse kinemat-ics solutions because of its stability, preserved topology, and capacity to optimize the joint space trajectory while producing a smooth minimal joint angle. A proposed method for redundancy resolution in MM has been simulated using MATLAB simulation code and the Gazebo real-time simulation pysical environment. The simulation results are evaluated with the joint limit method of redundancy resolution and other existing controllers for verification purpose. The conventional method of redundancy resolution is local optimum and infeasible for the end-effector motion in the entire workspace. The KSOM uses different steps of error correction that improve the system’s performance as well as ensure the global asymptotical stability of the system.
GPT-4 vs. GPT-3.5 AS CODING ASSISTANTS
Authors: Moussiades Lefteris , Zografos George , Papakostas George
Published: February 2024

Large Language Models are not limited to understanding and producing natural language. Instead, they do equally well in understanding and generating source code in various programming languages. At the time of writing, GPT-4 was considered the most potent large language model from OpenAI. This paper compares GPT-4 with its immediate ancestor, GPT-3.5, as coding assistants. More specifically, we have constructed appropriate tests to check whether the two systems can a) answer typical questions that can arise during code development, b) generate reliable code in response to user requirements, and c) contribute to code debugging. The test results for both models are impressive. However, the performance of GPT-4 is outstanding and signals an increase in the productivity of programmers and the reorganization of software development procedures based on these new tools.
Macrophages protect against sensory axon degeneration in diabetic neuropathy
Authors: Woolf Clifford , Hakim Sara , Jain Aakanksha , Petrova Veselina , Indajang Jonathan , Kawaguchi Riki , Wang Qing , Duran Elif , Nelson Drew , Adamson Stuart , Greene Caitlin
Published: February 2024

Diabetic peripheral neuropathy (DPN) is a common complication of diabetes, causing sensory loss and debilitating neuropathic pain1,2. Although the onset and progression of DPN have been linked with dyslipidemia and hyperglycemia3, the contribution of inflammation in the pathogenesis of DPN has not been investigated. Here, we use a High Fat High Fructose Diet (HFHFD) to model DPN and its metabolic syndrome in mice. Diabetic mice develop persistent heat hypoalgesia after three months, but a reduction in epidermal skin innervation only manifests at 6 months. Using single-cell sequencing, we find that CCR2+ macrophages infiltrate the sciatic nerves of diabetic mice well before axonal degeneration is detectable. We show that these infiltrating macrophages share gene expression similarities with nerve crush-induced macrophages4 and express neurodegeneration-associated microglia marker genes5 although there is no axon loss or demyelination yet. Inhibiting this macrophage recruitment in diabetic mice by genetically or pharmacologically blocking CCR2 signaling results in a more severe heat hypoalgesia and accelerated skin denervation. These findings reveal a novel neuroprotective recruitment of macrophages into peripheral nerves of diabetic mice that delays the onset of terminal axonal degeneration, thereby reducing sensory loss. Potentiating and sustaining this early neuroprotective immune response in patients represents, therefore, a potential means to reduce or prevent DPN.
A study on the identification technique of high- amplitude "bright spots" in the Huagang Formation of the X gas field in the Xihu Depression
Authors: Li Yangsen
Published: February 2024

Due to the small number of exploration wells and similar AVO (Amplitude Versus Offset) types of different fluids in the study area, the use of conventional P (fitting intercept), G (fitting gradient), P×G, P + G and other hydrocarbon detection attributes can no longer effectively identify the fluid properties of the study area, and it is urgent to find a hydrocarbon detection method suitable for the effective reservoirs in the area. Through the analysis and statistics of single-point pre-stack AVO of the drilled wells, the intercept and gradient intersection template for fluid identification are established. The gas-bearing sandstones show obvious AVO characteristics of class II ~ III, and different fluid types are basically distinguishable in the intersection template. We propose the scalar Poisson ratio attribute by borrowing the idea of the study of Poisson impedance, which can enhance the sensitivity of the identification of gas-bearing in the study area, and it can be used in the gas-bearing in the Xihu Depression. Good application results have been achieved in the hydrocarbon detection in the middle and deep layers, and progress has been made to improve the reliability of hydrocarbon detection in the reservoirs in the less well area.
Optimizing vancomycin dosing in pediatrics: A machine learning approach to predict trough concentrations in children under four years of age
Authors: Yin Minghui , Jiang Yuelian , Yuan Yawen , Li Chensuizi , Gao Qian , Lu Hui , Li Zhiling
Published: February 2024

Background
Vancomycin trough concentration is closely associated with clinical efficacy and toxicity. Predicting vancomycin trough concentrations in pediatric patients is challenging due to significant interindividual variability and rapid physiological changes during maturation.
Aim
This study aimed to develop a machine-learning (ML) model to predict vancomycin trough concentrations and determine optimal dosing regimens in pediatric patients using various machine-learning (ML) algorithms.
Method
A single-center retrospective observational study was conducted from January 2017 to March 2020. Pediatric patients who received intravenous vancomycin and underwent therapeutic drug monitoring (TDM) were enrolled. Seven ML models [linear regression (LR), gradient boosted decision trees (GDBT), support vector machine (SVM), decision tree (DT), random forest (RF), Bagging, and extreme gradient boosting (XGBoost)] were developed using 31 variables. Performance metrics including R-squared (R2), mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE) were compared, and important features were ranked.
Results
The study included 120 eligible trough concentration measurements from 112 patients. Of these, 84 measurements were used for training and 36 for testing. Among the seven algorithms tested, XGBoost showed the best performance, with low prediction error and high goodness of fit (MAE = 2.55, RMSE = 4.13, MSE = 17.12, and R2 = 0.59). Blood urea nitrogen, serum creatinine, and creatinine clearance rate were identified as the most important predictors of vancomycin trough concentration.
Conclusion
An XGBoost ML model was developed to predict vancomycin trough concentrations and aid in drug treatment predictions as a decision-support decision-support technology.
The Potential of a Small Melanocytic Lesion to Transform into Choroidal Melanoma: A Retrospective Study and Literature Review
Authors: Garcia-Caride Sara , Formoso Laura , Maciñeira Elia De Esteban , Silva-Rodriguez Paula , Pardo Maria , Bande Manuel F , Blanco-Teijeiro María Jose
Published: February 2024

Purpose
This research aimed to identify critical risk factors for the malignant transformation of small melanocytic choroidal lesions (SMCL)
Methods
A retrospective longitudinal study was conducted on 218 SMCL cases at the University Hospital of Santiago de Compostela from January 2013 to January 2023. Patients were selected based on their diagnosis of SMCL and their undergoing of comprehensive multimodal imaging such as optical coherence tomography, ultrasonography, and fundus autofluorescence. The primary focus was on evaluating demographic data, symptomatic presentations, and detailed imaging features.
Results
The cohort consisted of 43% males and 57% females, with a mean age of 69 years. Notably, 19% of the lesions were symptomatic, and 25.5% exhibited orange pigment. Approximately 33% of the tumours were proximate to the optic disc. Multivariate analysis revealed orange pigment presence and a lesion height greater than 2 mm as significant predictors of transformation. The Cox and Snell R-squared coefficient of 0.292 indicated that these factors accounted for about 29.2% of the variability in lesion transformation. The average follow-up period was 52 months, during which 4.6% of the SMCLs evolved into CM.
Conclusion
This study highlights the substantial role of lesion height exceeding 2 mm and the presence of orange pigment as key risk factors for the transformation of SMCL into CM. These findings are instrumental in aiding clinicians to identify and monitor high-risk patients, enabling early and potentially more effective interventions. Future research is essential to further explore these risk factors and to establish a more comprehensive understanding of SMCL progression to CM.
Victim’s Identification and Social Categorization: First- and Second-Order Effects on Altruistic Behavior
Authors: Regasa Wubeshet , Galmarini Umberto , Porro Giuseppe
Published: February 2024

We explore in laboratory how donations to a charity can be influenced by the identifiability and the social categorization of the recipients. We find that donors give more, on average, to unidentified than to identified beneficiaries, since the latter are more likelyto receive small donations than the former. Donations are the same, on average, to in- and to out-group beneficiaries; however, an in-group recipient is more likely to receive a top or a very small donation than an out-group one, whereas the latter is more likely than the former to receive an intermediate donation. Both first- and second-order effects are associated to the Dynamic Identity Fusion Index elicited from participants toward the ‘Multicultural world’.
JEL Codes: C91, D64, L31.
Regorafenib exerts an inhibitory effect on the proliferation of human lung fibroblasts by reducing the production of several cytokines
Authors: Nakamura Natsuki , Tabata Rie , Tabata Chiharu
Published: February 2024

Background
Pulmonary fibrosis is a disease that leads to respiratory failure and death. There has been little progress in therapeutic strategies for pulmonary fibrosis. There have been several reports on the cytokines associated with pulmonary fibrosis, including IL-6 and TGF-β1. Angiogenesis is one of the most important phenomena in the pathogenesis of PF. Previously, we reported the preventive effects of thalidomide against pulmonary fibrosis via the inhibition of neovascularization by angiogenic factors such as VEGF. Regorafenib is a multikinase inhibitor, which inhibits tyrosine kinase receptors such as VEGFR1-3 and TIE2. In the clinical setting, regorafenib has been widely used for anti-cancer therapy for metastatic colorectal cancer. In this study, we examined the preventive effects of regorafenib against pulmonary fibrosis.
Methods
We investigated whether regorafenib had an inhibitory effect on the proliferation, viability, and production of several cytokines in lung fibroblasts.
Results
We demonstrated an inhibitory effect of regorafenib on the proliferation and viability of lung fibroblasts. Moreover, regorafenib reduced the production of several cytokines associated with the pathogenesis of pulmonary fibrosis, including IL-6, VEGF and TGF- β1, and collagen synthesis from lung fibroblasts.
Conclusions
These data suggest that regorafenib may have potential clinical applications in the prevention of pulmonary fibrosis.
An effective reduction method with Caughey damping for spurious oscillations in dynamic problems
Authors: Serfőző Dániel , Pere Balázs
Published: February 2024

The numerical solution of dynamic problems often results spurious oscillations that deteriorates the accuracy. In order to eliminate them, a damping effect must be included in the numerical scheme. However, the concrete shape of the damping characteristics has a great importance in the efficiency of oscillation reduction. In this article, a novel approach has been introduced with adjustable damping character. The damping effect is exerted as viscous damping according to the formulation of Caughey damping. Using the proposed method, a wide range of different damping curves can be approximated with high accuracy. The newly developed method is mainly useful for contact-impact and wave propagation problems.
Unveiling the neuroplastic capacity of the bilingual brain: Insights from healthy and pathological individuals
Authors: Quiñones Ileana , Gisbert-Muñoz Sandra , Amoruso Lucia , Manso-Ortega Lucia , Mori Usue , Bermudez Garazi , Gil-Robles Santiago , Pomposo Iñigo , Carreiras Manuel
Published: February 2024

Research on the neural imprint of dual-language experience, crucial for understanding how the brain processes the first (L1) and second language (L2), remains inconclusive. Conflicting evidence suggests either similarity or distinction in neural processing, with implications for bilingual patients with brain tumors. Preserving dual-language functions after surgery requires considering pre-diagnosis neuroplastic changes. Here, we combine univariate and multivariate fMRI methodologies to test a group of healthy Spanish-Basque bilinguals and a group of bilingual patients with gliomas affecting the language-dominant hemisphere while they overtly produced sentences in either their L1 or L2. Findings from healthy participants revealed the presence of a shared neural system for L1 and L2, while also identifying regions with distinct language-dependent activation and lateralization patterns. Specifically, while the L1 engaged a more left-lateralized network, L2 production relied on the recruitment of a bilateral basal ganglia-thalamo-cortical circuit. Notably, based on language lateralization patterns, we were able to robustly decode (AUC: 0.86 ± 0.18) the language being used. Conversely, bilingual patients exhibited bilateral activation patterns in both their L1 and L2. For the L1, regions such as the cerebellum, thalamus, and caudate acted in concert with the sparsely activated language-specific nodes. In the case of L2, the recruitment of the default mode network was notably prominent. These results demonstrate the compensatory engagement of non-language-specific networks in the preservation of bilingual speech production, even in the face of pathological conditions. Overall, our findings underscore the pervasive impact of dual-language experience on brain functional (re)organization, both in health and disease.
Deep Learning Based Identification and Interpretability Research of Traditional Village Heritage Value Elements: A case study in Hubei Province
Authors: TAN Gangyi , ZHU Jiangkun , CHEN Zhanxiang
Published: February 2024

The preservation and transmission of traditional villages is crucial to the prosperity and development of ethnic cultures. However, current traditional village surveys usually require a large number of experts and scholars to conduct field research, which is an expensive and time-consuming method, especially for large-scale tasks. Therefore, this study proposes an automatic classification method based on deep learning (DL) for the identification of traditional village heritage value elements (TVHVE). The study evaluates four selected convolutional neural network (CNN) frames using traditional villages in Hubei Province as a sample dataset. The results show that Residual Network152 (ResNet152) is the most suitable CNN frame for identifying TVHVE in Hubei. The stability and consistency of various TVHVE present in the ResNet152 model were evaluated using Area Under Curve (AUC) and Precision Recall Curve (PRC), which indicated satisfactory prediction performance for most elements, except for specific elements such as tombstones and stone carvings, which showed lower accuracy. In addition, the study sheds light on the areas of concern of the model with respect to different TVHVE images and elucidates the reasons behind the confusion between elements through semantic clustering based on image classification and interpretability analysis using the Gradient-Weighted Class Activation Mapping (Grad-CAM) heat map. By using an automated classification method based on DL, this study significantly reduces the cost and effort associated with traditional surveys. At the same time, insight into areas of concern and confusion in the model improves guidance for conservation efforts and provides valuable references for subsequent research.
The effect of vortex beam on controlling the optical bistability in graphene quantum dots
Authors: Gharamaleki Ali Hamrah , Kevin Saeideh
Published: February 2024

We theoretically investigate optical bistability (OB) and optical multistability (OM) in a three-level cascade-type graphene quantum dot system placed in a Fabry-Perot cavity. The results obtained demonstrate that the OB intensity threshold can be controlled by the intensity and detuning of the driving field. Furthermore, since the three applied fields create a closed-loop system, their relative phase is utilized to manipulate OB and OM. The applied coupling field is assumed to be a vortex beam which provides two additional parameters for controlling OB. Our findings reveal that the OB intensity threshold is sensitive to the orbital angular momentum and azimuthal phase of the coupling vortex beam.
An novel circuit board fault diagnosis network using infrared thermal image
Authors: Xudong Song , liu chao , Yi Weiguo
Published: February 2024

In practical industrial applications, infrared thermography fault diagnosis has received widespread attention. In order to detect the internal component faults of circuit boards, this paper proposes an novel circuit board fault diagnosis network using infrared thermal image.Firstly, a network LGC-Net network is proposed to improve ResNet50, and a two-layer attention module and a channel feature extraction module are introduced into the ResNet50 network, which strengthens the network's ability to extract global features and improves the model's extraction of features such as multi-scale key detail features of the input feature maps and the target contour, etc. Optimization of the residual structure and model pre-training plus fine-tuning are used for the Diagnostic model construction, so that the accuracy of fault diagnosis has been greatly improved. Finally, the acquired board infrared thermography dataset is preprocessed and experimented with a diagnostic fault network Experiments show that the LGC-Net network proposed in this paper has a fault diagnosis accuracy of 98.92%, which is 1.9% higher than the optimal accuracy of the classical network fault diagnosis, while the diagnosis time of a single infrared thermography is 246ms, which is 299ms lower than the shortest time consumed by other models for diagnosis.The experimental results show that the method proposed in this paper is able to efficiently identify infrared thermography faults of circuit board components, to improve the accuracy of circuit board fault diagnosis.
Investigation of cholinesterase and α-glucosidase enzyme activities, and molecular docking and dft studies for 1,2-disubstituted cyclopentane derivatives with phenyl and benzyl units
Authors: Artunç Tekin , Çetinkaya Yasin , Taslimi Parham , Menzek Abdullah
Published: February 2024

Six known products were prepared from reaction of adipoyl chloride with 1,2,3-trimethoxyphenyl according to the literature. From one of them, four new 1,2-disubstituted cyclopentane derivatives with phenyl and benzyl units were synthesized by reactions such as hydrazonation, catalytic hydrogenation and bromination. The obtained compounds were examined for their in vitro inhibitory activity against acetylcholinesterase (AChE), α-glucosidase, and butyrylcholinesterase (BChE) enzymes. All compounds showed inhibition at nanomolar level with Ki values in the range of 45.53 ± 7.35-631.96 ± 18.88 nM for AChE, 84.30 ± 9.92–622.10 ± 35.14 nM for BChE, and 25.47 ± 4.46–48.87 ± 7.33 for α-Glu. In silico molecular docking studies of the potent compounds were performed in the active sites of AChE (PDB: 1E66), BChE (PDB: 1P0I), and α-glucosidase (PDB: 5ZCC) to compare the effect of bromine atom on the inhibition mechanism. The optimized molecular structures, HOMO-LUMO energies and molecular electrostatic potential maps for the compounds were calculated by using density functional theory with B3LYP/6–31 + G(d,p) and investigated.
Analysis of the burden of autism spectrum disorders in adolescent’s worldwide from 1990 to 2019
Authors: Liu Zhuoqiong , Liu Yangyang , Yang Jiaxin , Yan Liru , Li Qiushi , Gao Ying
Published: February 2024

Purpose
To analyze the burden of autism spectrum disorders (ASDs) worldwide and its change trends from 1990 to 2019.
Methods
The adolescent’s (aged 10–24 years) ASD burdens were quantified in terms of age-standardized incidence rate (ASIR), age-standardized disability-adjusted life years (DALYs) rate, and their corresponding estimated annual percentage changes (EAPCs).
Result
From 1990 to 2019, the ASIR of ASDs trended upward. In high-Socio-demographic Index (SDI) regions, the burden of ASDs was highest and increased much more than in other areas (EAPC in the age-standardized DALYs = 0.32; EAPC in the ASIR = 0.36). From 1990 to 2019, the age-standardized DALYs due to ASDs increased the most in High-income Asia Pacific (EAPC = 0.09), East Asia (EAPC = 0.22), and High-income North America (EAPC = 0.79); the ASIR of ASDs increased the most in Southern Latin America (EAPC = 0.10), High-income Asia Pacific (EAPC = 0.11), and High-income North America (EAPC = 0.80); and the ASIR and age-standardized DALYs due to ASDs increased the most in the USA (EAPC = 0.87 and 0.86, respectively).
Conclusion
From 1990 to 2019, the burden of ASDs continually increased globally, but there were significant differences in the burden between regions and countries.
Evaluation and Assessment of Teaching Quality and Students’ Performance using Machine Learning
Authors: Chakrabarti Samiddha , De Parthasarathi
Published: February 2024

In quality education, we except good teaching. To improve the academic performance of a student it is important to monitor the students’ activities and attentiveness. The traditional way to do that is Examination and regular counselling; But an exam can’t conclude overall academic performance of a student, counselling is not enough to estimate the difficulties that students are facing in classroom, the level of attention of students in classroom and the favorite subjects of the students. And it’s also important to monitor the teachers’ teaching quality. In this work we proposed an AI model, by which we can analysis the students’ emotion, activities and attentiveness in the classroom with the help of high-resolution configured camera in the classroom. The model detects the facial expressions of each student in classroom to recognize the emotion of each student; and detect the eyes, lips and head movement of each student to recognize the activities of the students. And analyze these recognized activities for each student to classify the attentiveness status (attentive or inattentive) of each student. And an overall activities and emotion of all the students will be analyzed to evaluate the teacher’s teaching quality at the class – If most of the students are inattentive or not happy, means the teacher’s teaching methods is not helping the students and vice versa. The proposed machine leaning model not only analyze performance of the student and teaching method, it also alerts the teachers about the unwanted activities of the student in the classroom in real-time.
RETRACTED: The Value of Legitimacy: What Does Comparability Cost?
Authors: Wheatley Clark , Clark Dina , Turner Elizabeth
Published: February 2024

The authors have requested that this preprint be removed from Research Square.
Multilevel and multicomponent intervention to promote colorectal cancer screening among underserved Vietnamese Americans: A cluster randomized trial
Authors: Ma Grace X. , Zhu Lin , Tan Yin , Do Phuong , Guerrier Guercie , Wang Min Qi , Nguyen Minhhuyen , Tran Tam , Pham Philip
Published: February 2024

Purpose The fecal immunochemical test (FIT) is a non-invasive method for colorectal cancer (CRC) screening, particularly effective in underserved Vietnamese American communities with low screening rates. This study reports on a culturally tailored multilevel intervention, incorporating FIT, aimed at increasing CRC screening among these populations aged 50 or above in the Greater Philadelphia metropolitan area.
MethodsFrom 2017 to 2020, we conducted a two-arm cluster randomized controlled trial to test the efficacy of a culturally tailored, multicomponent multilevel intervention aimed at increasing CRC screening uptake via enhanced self-awareness and self-efficacy, improved access to care, and changes in social norms and removal of stigma. The intervention group received multicomponent, multilevel CRC intervention including provision of a FIT self-sampling kit, with intervention approaches informed by the Centers for Disease Control's Clinical Preventive Services (CPS) Guidelines for adults 50+. The control group received only the CPS education.
ResultsThe study sample consisted of 746 eligible Vietnamese American participants recruited from 20 community-based organizations, with 95% having limited English proficiency. At 12-month follow-up, the intervention group showed substantially higher rates of FIT completion (89.56% vs. 7.59%, p < .001) and any CRC testing (91.48% vs. 42.41%, p < .001) compared to the control group.
Conclusion The results suggest that the community-based, culturally-tailored multilevel intervention, which incorporates with FIT self-testing, effectively enhances CRC screening among low-income Vietnamese Americans. Additionally, these results underscore the significance of community-oriented strategies, like collaborating with relevant community-based organizations, in achieving CRC screening targets.
Graphene oxide enhanced nanocellulose/chitosan biodegradable aerogel pad for fresh pork preservation
Authors: Zhang Ning , Xu Xiaokang , Zhang Simiao , Zhou Mei , Huang Yutong , Sun Weiqing , Ma Jing , Wu Lifeng
Published: February 2024

This study aimed to to prepare a degradable bacteriostatic aerogel pad that can absorb pork exudate extension for long pork shelf life. The addition of Graphene oxide(GO) was used to improve the bacteriostatic and mechanical characteristics of nanocellulose(CNC) and chitosan(CTS) matrix materials, and the bacteriostatic aerogel was obtained by freeze-drying technique. The results showed that when GO concentration was 0.4wt%, the antibacterial aerogel network had uniform structure, good mechanical properties and water/oil adsorption, and exhibited effective growth and reproduction inhibition against Escherichia coli and Staphylococcus aureus. Under the condition of 4℃, the bacteriostatic aerogel with 0.4wt% GO could be used as the packaging pad of fresh pork, absorbed the juice oozed during the storage process of pork, prolonged the fresh pork's shelf life and postponed the color, pH, and TVB-N changes.
Experimental Investigation of Tribological Properties for Enhancement of Engine oil with addition of Nanoparticles Additives
Authors: Aher Amrut Sahebrao , Pandey Vijay Kumar
Published: February 2024

Oil was polluted by adding an added substance in the motor oil to further develop its oil properties to lessen wear and contact of the motor. In present paper, tribological examinations will be performed on lubricating oil containing Zinc Dialkyldithiophosphate (ZDDP), Molybdenum Disulphide (MoS2), and Tungsten Disulfide (WS2) particles and their consolidated impact to explore the tribological execution of the ointment. In the current review ten unique blends of mineral oil and added substances were examined. To accomplish homogeneous blending, it is mixed attractively over an attractive stirrer keeping up with steady temperature. Utilizing the 4 Ball Wear design might be utilized to compute the wear scar attributes and mineral oil's coefficient of grating. Also, the coefficient of grating and wear scar breadth for the H blend were outstandingly lower contrasted with the reference lubricating oill (SAE 15W40). As per ASTM D-4172 (mineral oils setups), a steel ball is turned against three fixed steel balls that have been lubricated a specific load, speed, temperature, and time in the 4-Ball Wear test. The exhaustive examination of these properties recommends that the SAE 15W40 mineral oil with the predefined added substances, especially in the H mix, could offer enhanced lubrication performance compared to regular mineral oil.