Miracle-dz/UniFAR-FTUs huggingface dataset:
Targeting Cathepsin L in Cancer Management: Leveraging Machine Learning, Structure-Based Virtual Screening, and Molecular Dynamics Studies

Cathepsin L (CTSL) expression is dysregulated in a variety of cancers. Extensive empirical evidence indicates their direct participation in cancer growth, angiogenic processes, metastatic dissemination, and the development of treatment resistance. Currently, no natural CTSL inhibitors are approved for clinical use. Consequently, the development of novel CTSL inhibition strategies is an urgent necessity. In this study, a combined machine learning (ML) and structure-based virtual screening strategy was employed to identify potential natural CTSL inhibitors. The random forest ML model was trained on IC50 values. The accuracy of the trained model was over 90%. Furthermore, we used this ML model to screen the Biopurify and Targetmol natural compound libraries, yielding 149 hits with prediction scores >0.6. These hits were subsequently selected for virtual screening using a structure-based approach, yielding 13 hits with higher binding affinity compared to the positive control (AZ12878478). Two of these hits, ZINC4097985 and ZINC4098355, have been shown to strongly bind CTSL proteins. In addition to drug-like properties, both compounds demonstrated high affinity, ligand efficiency, and specificity for the CTSL binding pocket. Furthermore, in molecular dynamics simulations spanning 200 ns, these compounds formed stable protein-ligand complexes. ZINC4097985 and ZINC4098355 can be considered promising candidates for CTSL inhibition after experimental validation, with the potential to provide therapeutic benefits in cancer management.
Ultrasound Imaging of Bone Cortex Using Block-Based Reconstruction

Without considering the significant acoustic impedance contrast between bone and soft tissue, traditional imaging methods with unique sound velocity assumption are challenging to generate accurate ultrasound image of bone cortex, such as time-domain synthetic aperture (TDSA), and phase shift migration (PSM). Furthermore, TDSA restores the image point-by-point, and PSM reconstructs the target layer-by-layer, leading to the relatively high computation cost. To overcome these limitations, this work proposed a block-based fast ultrasound imaging method using velocity model estimation (BR-FUI-VE). After the estimation of sound velocity model via travel-time inversion, the imaging process involved block-by-block reconstruction, merely extrapolating the received wavefield to the top of the target block. This facilitated the reconstruction of entire tissue block (e.g., soft tissue or bone tissue) in a single step through 2D fast Fourier transform (2D-FFT). The effectiveness of the method was demonstrated by one simulated specimen, two cortical phantoms, and two ex-vivo goat tibias. The estimated sound velocity model showed mean relative errors below 14%, and the mean errors of the cortical thickness were less than 0.32 mm. The results of ex-vivo experiments were in good agreement with the reference models measured by micro computed tomography (μCT). Moreover, BR-FUI exhibited significantly reduced time complexity compared to TDSA and PSM, allowing a 5-layer image (i.e., goat tibia) to be reconstructed in just 0.3 seconds. Unlike the conventional synthetic aperture (SA), the proposed BR-FUI-VE method was proven to be an effective modality for accurate and efficient cortical bone imaging.
A Rasch Analysis of Achievement Goal Orientation Scale in Language Education Context

Motivation plays a crucial role in determining students’ academic achievement. An important aspect of motivation is student achievement goals or Achievement Goal Orientation. The trichotomous model of Achievement Goal Orientation has been widely used: Mastery Goal Orientation, performance approach Goal Orientation, and Performance-Avoidance Goal Orientation. Educators must be familiar with the orientation students adopt, as it shapes their approach during teaching and learning. This paper examines the validity and reliability of Achievement Goal Orientation in a language education context. One hundred twenty-three secondary school students attended the survey, involving 55 (44.7%) males and 68 (55.3%) females. The instrument was adopted from Elliot and Church's Achievement Goal Orientation Questionnaire (1997) and was modified into the language domain. The initial version of the instrument consisted of 20 items, while the final version, after modification, consisted of 13 items. The Rasch Measurement Model was used to validate the instrument. All the psychometric properties confirmed the validity and reliability of the instrument. Rasch analysis revealed that the scale showed strong evidence of validity and reliability in the language education setting. It is suggested that language teachers and experts use the scale to improve language learners' performance. The findings of this study may be tested in other fields of study to get more robust validation results for further validation of the scale.
Genetic architecture of adult-plant resistance to stripe rust in bread wheat (Triticum aestivum L.) association panel

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a severe disease in wheat worldwide, including Ethiopia, causing up to 100% wheat yield loss in the worst season. The use of resistant cultivars is considered to be the most effective and durable management technique for controlling the disease. Therefore, the present study targeted the genetic architecture of adult plant resistance to yellow rust in 178 wheat association panels. The panel was phenotyped for yellow rust adult-plant resistance at three locations. Phonological, yield, yield-related, and agro-morphological traits were recorded. The association panel was fingerprinted using the genotyping-by-sequencing (GBS) platform, and a total of 6,788 polymorphic single nucleotide polymorphisms (SNPs) were used for genome-wide association analysis to identify effective yellow rust resistance genes. The marker-trait association analysis was conducted using the Genome Association and Prediction Integrated Tool (GAPIT). The broad-sense heritability for the considered traits ranged from 74.52% to 88.64%, implying the presence of promising yellow rust resistance alleles in the association panel that could be deployed to improve wheat resistance to the disease. The overall linkage disequilibrium (LD) declined within an average physical distance of 31.44 Mbp at r2 = 0.2. Marker-trait association (MTA) analysis identified 148 loci significantly (p = 0.001) associated with yellow rust adult-plant resistance. Most of the detected resistance quantitative trait loci (QTLs) were located on the same chromosomes as previously reported QTLs for yellow rust resistance and mapped on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6A, 6B, 7A, and 7D. However, 12 of the discovered MTAs were not previously documented in the wheat literature, suggesting that they could represent novel loci for stripe rust resistance. Zooming into the QTL regions in IWGSC RefSeq Annotation v1 identified crucial disease resistance-associated genes that are key in plants’ defense mechanisms against pathogen infections. The detected QTLs will be helpful for marker-assisted breeding of wheat to increase resistance to stripe rust. Generally, the present study identified putative QTLs for field resistance to yellow rust and some important agronomic traits. Most of the discovered QTLs have been reported previously, indicating the potential to improve wheat resistance to yellow rust by deploying the QTLs discovered by marker-assisted selection.
Air Quality Study at Different Elevation Levels Using Drone Payload Air Quality Measurement Device (D-PAQ)

Construction sites can be found in both urban and rural areas, often in close proximity to residences. They can thus cause home pollution due to the distance and the materials used. This study aims to visualize PM2.5, PM10, temperature and humidity by producing air quality mapping and correlating parameters at the stadium and construction site. An Arduino-based air quality measurement payload device was developed to measure the air quality by different levels. The drone was used to collect air quality data by mounting the device to the drone. Measurements were taken at three different elevations for each study area, and the application software generates the air quality map based on the location coordinates. The correlation evaluation of the concentration of PM2.5 and PM10 with temperature and humidity was then determined. The results showed that the concentrations of PM2.5 and PM10 at the construction site are much higher compared to the stadium due to the construction activities nearby. Keywords: air quality, unmanned aerial vehicle, mapping
Can Generative Artificial Intelligence Write an Academic Journal Article? Opportunities, Challenges, and Implications

This article offers an in-depth reflection on the author’s experiences with Generative Artificial Intelligence (Gen AI), ChatGPT 4.0. The author started the journey from their initial need for software for English proofreading and editing services to their interest in exploring pre-service teachers’ application of Gen AI in lesson planning. Based on prompt engineering techniques, an iterative three-stage manuscript generation process—brainstorming, refinement, and writing—with ChatGPT is detailed. A short paper generated by ChatGPT is presented. Although Gen AI is a valuable tool in providing insights and assistance in research idea generation and design, academic writing, and English writing learning, the author cautions that critical thinking plays a vital role in ensuring accuracy, ethical considerations, and the preservation of rigorous scholarly standards. As Gen AI emerges as a game-changer in academia and education, this article highlights the importance of balancing its emerging capabilities with maintaining traditional academic and educational values.
An efficient hybrid CS‐DP application for generation expansion planning problem

This article proposes a new hybrid approach for generation expansion planning (GEP) based on cuckoo search (CS) and dynamic programming (DP). Generally, the GEP problem is known as having very large search space and highly nonlinear complex combinatorial optimization. The global optimal solution is to solve with the full enumeration DP. However, the computation time grows exponentially when the planning horizon and candidate options increase, which is called ‘curse of dimensionality’. To solve this problem, a hybrid CS‐DP approach is proposed with three techniques for solution quality and convergence characteristic enhancement. First, the CS is integrated into the DP structure for the optimum solution of the very large search space problem. Second, the feasible search concept can eliminate infeasible solutions from the searching process. Finally, the memory exploration search is applied to prevent repeated searches. To measure its effectiveness, the proposed method is applied to 15 existing power plants, with 5 candidate options and 2 test cases: 14 year and 20 year study periods. The experimental results are compared with classical and metaheuristic optimizations. The test results indicate that the proposed hybrid CS‐DP achieves higher solution quality and superior convergence characteristics than other methods. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
International mechanisms for the protection of human rights under martial law

Human rights are fundamental to any just and equitable society. However, under martial law conditions, protecting them can be a challenge. However, in practice the situation of internal armed conflicts and violence is the largest threat and obstacle to their implementation. Hence, the perspective to the protection of the right to life during an armed conflict is based predominantly on the norms and regulations of international humanitarian law, which safeguard protection only to persons thereunder. The purpose of this article is to work out the priority measures for the protection of human rights in the conditions of martial law drawing on the insight into the foreign experience. To address the said goal, the present article utilized cognitive dialectical methods, the method of idealization, formalization and modeling of the response strategy in case of human rights violation. Because of the conducted study, a response strategy was elaborated in case of human rights violations under war conditions. The findings of this article are important for lawyers, public officials, and civil society organizations working to protect human rights under conditions of martial law, seek to administer the standards and practices of international regulation of universal human and citizen rights in individual administrative cases.
An Exploration of Nurses’ Experience Following a Face-to-Face or Web-Based Intervention on Patient Deterioration

A web-based clinical simulation program, known as FIRST2ACT (Feedback Incorporating Review and Simulation Techniques to Act on Clinical Trends), was designed to increase the efficacy of clinicians’ actions in the recognition and immediate response to a patient’s deterioration. This study, which was nested in a larger mixed method project, used ten focus groups (n = 65) of graduate, enrolled, registered nurses, associate nurse unit managers, and general managers/educators/coordinators from four different institutions to investigate whether nurses felt their practice was influenced by participating in either a face-to-face or web-based simulation educational programme about patient deterioration. The results indicate that individuals who were less “tech-savvy” appreciated the flexibility of web-based learning, which increased their confidence. Face-to-face students appreciated self-reflection through performance evaluation. While face-to-face simulations were unable to completely duplicate symptoms, they showed nurses’ adaptability. Both interventions enhanced clinical practice by improving documentation and replies while also boosting confidence and competence. Web learners initially experienced tech-related anxiety, which gradually subsided, demonstrating healthcare professionals’ resilience to new learning approaches. Overall, the study highlighted the advantages and challenges of web-based and face-to-face education in clinical practice, emphasising the importance of adaptability and reflective learning for healthcare professionals. Further exploration of specific topics is required to improve practice, encourage knowledge sharing among colleagues, and improve early detection of patient deterioration.
Study on utilization of agricultural water resources with high efficiency in Zhangwei river plain I.Parameter calibration and validation

As an important river system of Haihe river plain,Zhangwei river plain is among those typical regions with severely water shortage in Northern China.In this paper,in order to optimize irrigation schedule,Shuffled Complex Evolution(SCE-UA) was used to calibrate the crop parameter of Soil and Water Assessment Tool(SWAT) in two stations which are to be or near the plain.The sensitivity of parameters was analyzed based on actual evapotranspiration by remote sensing(RS),and the most sensitive parameters were chose.The next step was to optimize the parameters and give its uncertainty analysis by using "Sequential Uncertainty Fitting Algorithm"(SUFI-2). Based on the calibrated parameters,under the consideration of uncertainty of the model,the yield of long term simulation of winter wheat and summer maize rotation system were validated.The results of calibration and validation laid a firm foundation for the further research on optimization of water product function and irrigation regime.
Rewards Effects Through Entrepreneurial Orientation to the Performance of the Indi 4.0 Manufacturing Industry

Purpose: The main intention of this study is to better comprehend the potential of rewards, entrepreneurial orientation (EO), and their impact on the performance of Indonesian manufacturing firms transforming into Industry 4.0. Design/methodology/approach: This study achieved its objectives by conceptual analysis of the rewards relationship with the performance of an organization, expectancy theory, resource-based view (RBV) theory, and extant literature. Findings: This study indicates that a comprehensive rewards policy alone is insufficient to improve the performance of the Indonesian manufacturing industry. The fully mediating models hypothesised with the application of expectancy theory and RBV models suggested that the dimensions of EO have significant impacts on improving the performance of the manufacturing firm. Practical Implications: This study measures the adoption of EO as a mediator in examining the mechanism of rewards management to improve the performance of the manufacturing industry underpinned by the expectancy and RBV theories. Originality/Value: The originality of this study is to demonstrate that the implementation of rewards management in the Indonesian manufacturing firm can be enhanced using a proper mechanism, to improve better firm’s performance.
A Novel Adversarial Detection Method for UAV Vision Systems via Attribution Maps

With the rapid advancement of unmanned aerial vehicles (UAVs) and the Internet of Things (IoTs), UAV-assisted IoTs has become integral in areas such as wildlife monitoring, disaster surveillance, and search and rescue operations. However, recent studies have shown that these systems are vulnerable to adversarial example attacks during data collection and transmission. These attacks subtly alter input data to trick UAV-based deep learning vision systems, significantly compromising the reliability and security of IoTs systems. Consequently, various methods have been developed to identify adversarial examples within model inputs, but they often lack accuracy against complex attacks like C&W and others. Drawing inspiration from model visualization technology, we observed that adversarial perturbations markedly alter the attribution maps of clean examples. This paper introduces a new, effective detection method for UAV vision systems that uses attribution maps created by model visualization techniques. The method differentiates between genuine and adversarial examples by extracting their unique attribution maps and then training a classifier on these maps. Validation experiments on the ImageNet dataset showed that our method achieves an average detection accuracy of 99.58%, surpassing the state-of-the-art methods.
Perfil de salto vertical, velocidad, flexibilidad y composición corporal de porteros de balonmano en categorías inferiores (Jump height, velocity, flexibility and anthropometric profile of handball goalkeepers in young categories)

El objetivo de este estudio se centra en la determinacion del perfil antropometrico y condicional del portero de balonmano de categorias inferiores pertenecientes a equipos de la Federacion de Balonmano de la Comunidad Valenciana. La muestra consta de 26 porteros masculinos de balonmano de edades comprendidas entre los 11 y los 20 anos. Las pruebas realizadas para el perfil antropometrico fueron altura, peso, IMC, porcentaje de grasa corporal y kilogramos de masa magra, mientras que para el perfil condicional fueron sprint 5 metros y 15 metros, sit and reach y salto vertical (SJ, CMJ y ABK). Se realizo un analisis de la varianza de un factor (ANOVA) y una prueba post-hoc (Tukey) para establecer las diferencias estadisticas entre los grupos en las diferentes variables de estudio. Los mejores resultados se produjeron en el Grupo 3 (G3), excepto en la prueba sit and reach que se produjo en el Grupo 2 (G2). La mayor diferencia se produjo entre el Grupo 1 (G1) y el Grupo 3 (G3), mostrando diferencias significativas en ocho de las once variables analizadas. Los resultados muestran que el portero de balonmano posee una edad madurativa avanzada. Las categorias de mayor edad presentan mejores resultados en los test realizados existiendo mayores diferencias entre los grupos en el perfil antropometrico que en el aspecto condicional. Abstract. The aim of this paper is to determinate the anthropometric and conditional profile of young handball goalkeepers that belong to teams of Valencian Handball Federation. The sample is based on an evaluation of 26 male handball goalkeepers aged between 11 to 20 years. The tests performed for the anthropometric profile were height, weight, BMI, percentage of body fat and kilograms of lean muscle mass, while for the conditional profile were 5 meters sprint and 15 meters sprint, sit and reach and vertical jump (SJ, CMJ and ABK). An inferential analysis was performed using a one-way analysis of variance (ANOVA) and a post-hoc test (Tukey) to establish the differences between groups in the different study variables. The best results occurred in group 3, except in the sit and reach test that occurred in group 2. The biggest differences were appreciated between group 1 and group 3, showing significant differences in eight of the eleven variables analyzed. The results show that the handball goalkeepers show an advanced maturity age. The older categories show better results in the tests performed with bigger differences between groups in height anthropometric profile than in the conditional aspect.
Fear of COVID-19 when experiencing pregnancy or childbirth in the pandemic: what are the associated factors?

ABSTRACT Objective: to identify factors associated with fear of COVID-19 among women who experienced pregnancy or childbirth during the pandemic. Methods: a cross-sectional study, nested within a prospective cohort, using an online survey, from August 2021 to February 2022, based on descriptive data analysis. Results: of the 431 participants, 52.8% were postpartum women and 20.1% were pregnant women. With regard to fear of COVID-19, a mean score of 20.46 was obtained (moderate fear). The highest fear scores were present in women whose newborns were admitted to hospital in neonatal critical units (p=0.032), and the lowest among those covered by supplementary health (insurance) (p=0.016). Conclusion: among pregnant and postpartum women, high fear of COVID-19 translated into the possibility of having newborns admitted to hospital in a critical unit. The importance of supporting actions to support pregnant/postpartum women’s mental health in relation to COVID-19 or other threats that may influence the neonatal outcome stands out.