Despite the recognized influence of body mass on combat techniques, the relationship between body segment mass (BSM) and combat moves remains unexplored. This study aimed to examine the relationship between striking arm mass (SAM), kicking leg mass (KLM), and body mass (BM) with the dynamic forces of the direct punches (DP), palm strikes (PS), elbow strikes (ES), front kicks (FK), and countermovement jumps (CMJ) performance. Sixteen male military cadets (22.3 ± 1.8 years, 181.4 ± 7.0 cm, 82.1 ± 8.5 kg) performed combat techniques, with performance measured by using a force plate and body segment mass assessed by Dual-energy X-ray absorptiometry. Spearman's correlation analysis, the Wilcoxon test, and Cohen's d were applied. Results indicated the relationship between KLM or BM and FK impulse (r = 0.64, p = 0.01; r = 0.52, p = 0.04, respectively) and CMJ impact force (r = 0.80, p ≤ 0.01; r = 0.70, p ≤ 0.01, respectively). Moreover, FK peak and impact forces were moderately correlated with CMJ jump height (r = 0.74, p ≤ 0.01; r = 0.77, p ≤ 0.01). The highest relationship was found between KLM and FK impulse; however, the difference in variability explained by KLM versus body mass is only 12%. This suggests that knowledge of BSM did not provide a significantly better estimate of the dynamic forces of the punches and FK than BM.

Despite the recognized influence of maximum or acceleration strength on combat techniques and countermovement jump (CMJ) performance, the relationship between body segment weights and combat techniques remains unexplored. This study aimed to examine the impact of body segment weights, including striking arm weight (SAW), kicking leg weight (KLW), and trunk weight (TW), on the dynamics of direct punches (DP), palm strikes (PS), elbow strikes (ES), front kicks (FK), and CMJ performance. Sixteen male military cadets (22.3±1.8 years, 181.4±7.0 cm, 83.0±8.1 kg) performed combat techniques, with performance measured by using a force plate and body segment weights assessed by Dual-energy X-ray absorptiometry. Spearman's correlation analysis was applied. Results indicated a strong correlation between KLW and FK impulse (r = 0.64, p ≤ 0.01) and CMJ impact force (r = 0.80, p ≤ 0.01). SAW showed moderate correlations with DP impulse (r = 0.53, p ≤ 0.05) and ES impulse (r = 0.54, p ≤ 0.05). Additionally, FK peak and impact forces were strongly correlated with CMJ jump height (r = 0.74, p ≤ 0.01; r = 0.77, p ≤ 0.01), and FK peak force moderately correlated with CMJ peak velocity (r = 0.63, p ≤ 0.05). These findings suggest targeted arm strength training could enhance striking abilities, while improvements in leg acceleration strength may directly boost kicking performance and vertical jump capabilities, which are crucial in combat scenarios.

Background We investigated to determine the effectiveness of verbal feedback in learning the round-off back somersault on the balance beam with stable landing. Methods: The research material consisted of female gymnasts (n = 16). They were randomly assigned to one of two groups: FKE group (n = 8) with feedback on key elements, or FAE group (n = 8) with 100% feedback on all errors made in the phase structure of the task. Results: Based on research, it was established that key elements could be identified in the preparatory, main and final phases. Mixed ANOVA showed that significant differences (p < 0.05) were noted due to the teaching method used (Group x Time factor) when performing the gymnastic routine of round-off back somersault with stable landing on the balance beam. Based on the Welch t test for independent data it was revealed that the group with feedback on the key elements obtained significantly higher mean scores from judges at the end of the experiment. Conclusions: The findings of the present study point to a possibility of offering coaches teaching methods that increase the effectiveness of learning complex motor skills and indicate a possibility of applying such solutions in groups of female gymnasts both in training and during competitions.

Background: Scientific literature on COVID-19 is still limited about long-term impacts on the all-body systems and they treatments. The aim of the study was to create a safe protocol-based in-tervention to improve functional and equilibrium abilities in older adults impacted by COVID-19. Methods: The study completed 46 people (intervention group: n=26; control group: n=20). Re-sistance training (RT) was held twice a week, 60 min per session for 8 weeks. The postural stability and quality of life questionnaire (WHQOOL) were conducted during pre- and post-testing. Results: Results indicated significant differences in overall stability index (OSI) with eyes open (EO), ante-rior-posterior stability index (APSI) EO, fall risk index 6-2 (FRI6-2) values in males (p

Evidence suggests that COVID-19 infection can cause lasting health consequences. Multidiscipli-nary rehabilitation services have been recommended to reduce the sequalae. However, the effec-tiveness of physical exercise interventions remains insufficiently documented. The aim of this study was to develop and implement a specific and well tolerated protocol-based, intervention to reduce muscle weakness in older adults impacted by COVID-19. Forty six older adults random-ized into Intervention and Control Groups. Isometric and isokinetic strength assessments were conducted for selected muscle groups using JBA Staniak® torquemeter and Biodex System 3 dy-namometer. Functional abilities were evaluated with the Time Up and Go test and Chair Stand Tests. Men in intervention group demonstrated a significant improvement in static conditions for knee flexors (KF), trunk extensors (TE) and trunk flexors (TF) and in dynamic conditions for knee extensors (KE). Women in intervention group showed significant improvement in static condition for EF, KF, TE and TF and in dynamic for a KE and for a KF. The interaction GROUP x TESTING SESSION was significant for Chair test (s) and Chair test (n). Our results demonstrate the effec-tiveness of a well-tolerated, protocol-based approach that can be used to diminish long lasting functional deficits in post-covid survivors.

Background: The prevalence of falls among the older population underscores the imperative of comprehending human adaptations to gait perturbations. Dual-belt treadmills offer a controlled setting for such investigations. The purpose of this study was to examine the effect of acceleration of one belt of the treadmill during three different phases of the gait cycle on kinematic and kinetic parameters and relate these changes to unperturbed gait. Methods: Twenty-one healthy young females walked on a treadmill in a virtual environment, in which five unexpected perturbations were applied to the left belt at the Initial Contact (IC), Mid Stance (MS), and Pre-Swing (PS) phase of the gait cycle. Data from the undisturbed gait and the first disturbance of each trial were extracted for analysis. Results: All perturbations significantly affected the gait pattern, mainly by decreasing the knee extension angle. The perturbation in the IC phase had the most significant effect, resulting in a 248.48% increase in knee flexion torque. The perturbation in the MS phase mainly affected plantar flexion torque, increasing it by 118.18%, while perturbation in the PS phase primarily increased the hip extension torque by 73.02%. Conclusions: The presence of perturbations in the IC and PC phases caused the most aggressive and significant changes in gait parameters.

Aiming to improve medical diagnosis and treatment, artificial intelligence (AI) has emerged as a transformational force in the healthcare industry. In this article, we examine how AI is increasingly being used to improve healthcare, with an emphasis on how it is changing medical diagnosis and treatment. We explore the opportunities, threats, and ethical concerns of incorporating AI into healthcare practice. In addition, we feature important AI applications in radiology, pathology, cardiology, and cancer. AI has great potential to improve patient outcomes, diagnostic accuracy, and the ability to provide individualized treatment plans in the future if it is used and refined with care.

In this paper the one-to-one correspondences and equivalences between ideals, primals, filters and grills are introduced. It is shown the local functions and the topological spaces induced by them are the same. From this point of view, the topological properties with respect to one topology can be derived from topological properties valid in the corresponding topology.

Objective: This study aimed to assess the impact of artificial intelligence (AI)-driven noise reduction algorithms on metal artifacts and image quality parameters in cone-beam computed tomography (CBCT) images of the oral cavity. Materials and Methods: This retrospective study included 70 patients, 61 of whom were analyzed after excluding those with severe motion artifacts. CBCT scans, performed using a Hyperion X9 PRO 13 × 10 CBCT machine, included images with dental implants, amalgam fillings, orthodontic appliances, root canal fillings, and crowns. Images were processed with ClariCT. AI deep learning model (DLM) for noise reduction. Objective image quality was assessed using metrics such as the differentiation between voxel values (ΔVVs), the artifact index (AIx), and the contrast-to-noise ratio (CNR). Subjective assessments were performed by two experienced readers, who rated overall image quality and artifact intensity on predefined scales. Results: Compared with native images, DLM reconstructions significantly reduced the AIx and increased the CNR (p<0.001), indicating improved image clarity and artifact reduction. Subjective assessments also favored DLM images, with higher ratings for overall image quality and lower artifact intensity (p<0.001). However, the ΔVV values were similar between the native and DLM images, indicating that while the DLM reduced noise, it maintained the overall density distribution. Orthodontic appliances produced the most pronounced artifacts, while implants generated the least. Conclusion: AI-based noise reduction using ClariCT. AI significantly enhances CBCT image quality by reducing noise and metal artifacts, thereby improving diagnostic accuracy and treatment planning. Further research with larger, multicenter cohorts is recommended to validate these findings.

While the role of safe riding behavior as a safety contributor for cyclists has been increasingly studied in recent years, there have been few studies analysing cycling behavior in relation to crash-related outcomes in Baltic countries. Indeed, to the best of our knowledge, this is the first time this issue has been addressed in the case of Latvia. Aim: The objective of this study was to assess the relationships among self-repotted cyclists’ behavior, traffic safety literacy, and their cycling crash involvement rates. Method: A total of 299 cyclists aged M=32.8 from across Latvia (42% females) participated in an online survey, which comprised questions regarding respondents’ demographics, frequency of riding, and the number of crashes in the past five years. The Cycling Behavior Questionnaire (CBQ) and the Cyclist Risk Perception and Regulation Scale (RPRS) were applied to assess cyclists' behavior patterns and traffic safety literacy. Results: According to the findings, it can be inferred that cyclists frequently engage in riding errors and traffic violations while cycling. Those who exhibit more antisocial behavior patterns are also more likely to be involved in road crashes. Conversely, cyclists with greater positive behavior rates more often also tend to possess better knowledge of traffic rules and exhibit a heightened risk perception, indicating a greater awareness of road traffic safety. Conclusion: All in sum, this study underscores key age differences, with older individuals significantly less involved in riding crashes, exhibiting fewer driving errors and a higher level of risk perception, which serves as a crucial factor in road safety. At the practical level, these results stress the need to address both traffic safety literacy and protective cycling factors of cyclists, in a manner to improve overall road safety and promote active transport modes in Latvia.

Recent discovery of triangular boron Nanotubes makes it a competitor of carbon in many respects. Closed forms of M-polynomial of nanotubes produce closed forms of many degree-based topological indices which are numerical parameters of the structure and, in combination, determine properties of the concerned nanotubes. In this report, we give M-polynomials of triangular boron nanotubes and recover many important topological degree-based indices of these nanotubes. We also plot surfaces associated to these nanotubes.

The appropriate concentration of vitamin D in the athlete’s body is essential for its proper functioning, especially in terms of muscular health, by enhancing recovery and oxygen consumption. Soccer players are required to perform frequent sprints and change of directions during training and competition. The aim of the present study was to establish whether the level of vitamin D (measured by 25-hydroxyvitamin D concentrations- 25(OH)D) in blood serum has any influence on speed (s) and change of direction (COD, s) performance. Material and methods: Twenty male soccer players from the top league in Poland participated in the study. All subjects' were evaluated for the serum concentration of 25(OH)D at the beginning of the preseason. . The linear sprint test was performed at 5m and 30m and COD (time and deficit), was evaluated at 30m at the beginning and after 6 weeks of preparatory period. Results: The results revealed that 50% of soccer players had an insufficient level or a deficit of 25(OH)D (≤ 30 ng/ml), with 20% having a significant deficiency of 30 ng/ml).There were no statistically significant correlations between the training effect for the variables ∆5m (before - after) and ∆30m (before - after). Statistically significant positive correlations were found between the training effect for the variables ∆COD (before - after) (R=0.62/p=0.003) and ∆deficit (before-after) (R=0.47/p=0.039). With a higher concentration of vitamin D in the blood, the training effect for COD and the deficit increased, which was visible in the faster performance of the COD test. No statistically significant differences were found for the mean values of the variables ∆5m (before - after) and ∆30m (before - after) in the group of subjects whose 25(OH)D concentration was 30mg /ml. Significant differences were noticed for the variables ∆COD (m=0.60 [s]) and ∆deficit (m=0.56[s]) in the group of subjects whose 25(OH)D concentration was 30mg /ml. The training effect was significantly higher for the group of subjects whose 25(OH)D concentration was above 30 mg/ml, which was observed by the faster performance of the COD test in this group of subjects. Conclusions: The serum concentration of vitamin D affects training adaptations of muscles. A lower concentration of Vitamin D seems to have a detrimental effect on the change of direction performance. Soccer players whose blood serum 25(OH)D concentrations were >30mg/ml achieved better results in the applied fitness tests.

Integrating artificial intelligence (AI) and natural language processing (NLP) technologies with project-based learning experiences in Science,Technology, Reading, Engineering, Arts, and Mathematics (STREAM) education offers the potential to enhance student engagement, critical thinking,problem-solving, and interdisciplinary learning. This paper presents a comprehensive approach to implementing AI and NLP technologies, such as ChatGPT, in STREAM project-based learning experiences, highlighting the potential advantages and challenges of this innovative educational approach. The proposed method encompasses personalized learning pathways, AI-powered research assistance, collaborative AI tools, real-time feedback, virtual mentoring, advanced simulation, and objective assessment. We also discuss the implications of this integration for educators, institutions, and students, along with recommendations for future research and development in this emerging field.

Improving the capabilities of faculty members, including competencies of emotional intelligence in professors, can play a major role in various education levels of success and achievement, adjustment, and mental health in students, and is a fundamental solution to the promotion of higher education quality. For accurate examination of the issue, the present study aimed to determine the association between basic science professors' emotional intelligence and the ability to teach at the School of Medicine of Iran University of Medical Sciences. The present descriptive-analytical study was conducted at the School of Medicine of Iran University of Medical Sciences by census sampling of faculty members of the basic sciences. We included 98 faculty members in the study. The research tools included Dr. Haghani's "Emotional Intelligence in Teaching" questionnaire and Dr. Akbari's "Teaching Ability" questionnaire. We analyzed data through descriptive statistics and analytical tests, including Spearman's correlation test, Pearson test, t-test, and two-way analysis of variance. The mean score of faculty members' emotional intelligence was 111.51±9.3 equal to 89.93±7.5 percent, and the median score of total teaching ability of the questionnaire was 101.89±8.59 equal to 87.84±7.4 percent. There was a positive correlation between faculty members' emotional intelligence and teaching ability. (p= 0.0001, r= 0.71). The faculty members' emotional intelligence can be a determinant in their teaching ability. Their emotional intelligence was evaluated as good and there was a positive relationship between emotional intelligence and teaching ability.

Titania is one of the most comprehensively studied nanostructures due to its widespread applications in production of catalytic, gas- sensing and corrosion- resistance materials [1]. M-polynomial of nanotubes has been vastly investigated as it produces many degree-based topological indices which are numerical parameters capturing structural and chemical properties. These indices are used in the development of quantitative structure-activity relationships (QSARs) in which the biological activity and other properties of molecules are correlated with their structure like boiling point, stability, strain energy etc of chemical compounds. In this paper, we determine M-polynomials of single-walled titanium (SW TiO2) nanotubes and recover important topological degree based indices of them to theoretically judge these nanotubes. We also use Maple to plot surfaces associated to different types of single-walled titanium (SW TiO2) nanotubes.

The integration of Artificial Intelligence (AI) into education has the potential to revolutionize traditional teaching and learning methods. AI can offer personalized learning experiences, streamline administrative tasks, enhance feedback mechanisms, and provide robust data analysis. Numerous studies have demonstrated the positive impact of AI on both student outcomes and teacher efficiency. However, caution must be exercised when implementing AI in education, considering potential risks and ethical dilemmas. It is essential to use AI as a tool to support human educators rather than replace them entirely. The adoption of AI in education holds the promise of creating more inclusive and effective learning environments, catering to students of diverse backgrounds and abilities. As AI technology continues to advance, the education sector can anticipate even more innovative applications, further shaping the future of learning. This abstract provides an overview of the multifaceted landscape of AI in education, highlighting its potential benefits, associated challenges, and the importance of responsible integration.

This study explores the complexities of sport manager selection, investigating the impact of affirmative action, recruitment strategies, organizational culture, diversity initiatives in board selection, and career advancement insights from coaches' perspectives. To conduct this investigation, a purposive sampling technique was employed, selecting 65 prominent sports managers and coaches from Romania. Participants, aged between 35 to 58 years old, boasted an average of 10 to 20 years of sports experience and were chosen based on specific criteria, including academic qualifications. Data collection occurred over an extended period, spanning from fall 2022 to spring 2024, through semi-structured interviews with sport managers and coaches. The findings unveiled persistent challenges in effectively implementing affirmative action measures, as sport managers grapple with balancing the promotion of deserving candidates while maintaining continuity in board culture. Achieving meaningful diversity necessitates nuanced approaches that consider both candidate quality and cultural compatibility. Moreover, the study sheds light on coaches' perspectives when considering executive council positions, highlighting various pathways to career advancement. Recruitment practices prioritized informal methods, emphasizing board cohesion. Despite the recognized importance of diversity, challenges persist in selecting candidates solely based on demographic representation. The study provides valuable insights into promoting diversity and inclusivity within sports organizations' executive councils. Future research directions may include exploring longitudinal trends and delving into the qualitative experiences of underrepresented groups, with the aim of advancing understanding and promoting equity within sports organizations.

This longitudinal study aimed to analyze the effects of a team rowing-based training program on physical fitness and anthropometric parameters in female breast cancer survivors (n=40; 56.78±6.38 years). Participants were divided into two groups: one rowed in fixed seat rowing (FSR) boats (n=20; 56.35±4.89 years) and the other in sliding seat rowing (SSR) boats (n=20; 57.20±7.7 years). Both groups engaged in two 75-minute sessions per week for 24 weeks. Significant improvements were observed in both groups in terms of weight (FSR: -1.93 kg, SSR: -1.75 kg), body mass index (FSR: -0.73 kg/m², SSR: -0.67 kg/m²), waist circumference (FSR: -2.83 cm, SSR: -3.66 cm), and hip circumference (FSR: -2.02 cm, SSR: -2.88 cm). Muscle strength improved in lower extremities (jump test: FSR: 2.99 cm, SSR: 3.11 cm) and upper extremities (dominant: FSR: 4.13 kgf, SSR: 4.34 kgf; non-dominant: FSR: 3.67 kgf, SSR: 3.32 kgf). Aerobic capacity also improved, with the SSR group showing a greater increase (FSR: 63.05 m, SSR: 93.65 m). Flexibility tests revealed better results in the SSR group for both dominant (SSR: 1.75 cm vs. FSR: -5.55 cm) and non-dominant limbs (SSR: 1.72 cm vs. FSR: -3.81 cm). These findings suggest that the type of rowing modality can influence physical fitness outcomes, with the SSR group showing superior improvements compared to the FSR group.

Background/Objectives: High-intensity anaerobic physical training frequently results in muscle damage among boxers and kickboxers, which can impede performance and recovery. Vibrational therapy (VT) and passive rest (PR) have been employed as methods to enhance muscular recovery and performance. This study evaluates the effectiveness of these two recovery methods on upper limb muscle strength and lactate levels in plasma after high-intensity exertion. Methods: Eighteen elite boxers and kickboxers, aged 19-32 years, underwent tests employing VT and PR as recovery methods in a controlled, crossover study. Muscle performance was assessed via isokinetic dynamometry, and lactate levels were measured pre-exercise, post-exercise, and post-recovery. The study adhered to the Declaration of Helsinki guidelines and was approved by the relevant bioethics committee. Results: The results showed that VT led to a faster recruitment of muscle fibers and improved muscle endurance as indicated by decreased fatigue work indices compared to PR. However, no significant differences were observed in peak torque or lactate levels between the two recovery methods. The VT group exhibited quicker recovery times in torque generation and better performance in fatigue resistance. Conclusions: VT appears to provide superior muscular recovery compared to PR following intense anaerobic effort, particularly in terms of muscle strength endurance and activation speed. These findings support the potential of VT in sports recovery protocols, although similar lactate response suggests that metabolic recovery rates are not significantly affected.

The rapid convergence of Artificial General Intelligence (AGI), autonomous drones, and applied robotics presents a transformative opportunity for many sectors. However, this advancement also raises critical ethical and existential questions, particularly in warfare. This paper explores the concept of entropy as a metaphor for the potential disorder introduced by these increasingly complex technologies. We examine the risks of AGI surpassing human control in conflict situations, where autonomous decision-making could have disastrous consequences. We then analyze autonomous drones, scrutinizing their impact on warfare tactics and the ethical dilemmas surrounding independent, real-time decision-making. Finally, we investigate applied robotics in military operations, focusing on the delicate balance between enhanced capabilities and the potential for uncontrollable systems. Through a multidisciplinary lens, drawing on technology ethics, military strategy, and AI safety, this paper utilizes the concept of entropy to highlight the need for caution in developing these technologies. We propose a scientifically grounded and ethically sound framework to guide policymakers, technologists, and ethicists in navigating the path between innovation and global stability. This framework concludes with recommendations for responsible development and deployment strategies that can mitigate the risks associated with these powerful tools.

In this paper, carbon nanotubes modified screen-printed electrode (CNTs/SPE) was prepared and the CNTs/SPE was employed for the electrochemical determination of antioxidant substance Chlorogenic acids (CGAs). A pair of well-defined redox peak of CGA was observed at the CNTs/SPE in 0.10 mol∙L^-1 acetic acid-sodium acetate buffer (pH 6.2) and electrode process is adsorption-controlled. Cyclic voltammetry (CV) and differential pulse voltammetry (DPV) method for the determination of CGA were proposed based on the CNTs/SPE. Under the optimal conditions, the proposed method exhibited linear ranges from 4.73×10^-7 to 4.45×10^-5 mol∙L^-1, the linear regression equation was Ipa(µA) = 4.1993 C (mol∙L^-1)+1.1039 (r = 0.9976) and the detection limit for CGA could reach 3.25×10^-6 mol∙L^-1. The recovery of matrine was 94.74~106.65% (RSD = 2.92%) in coffe beans. The proposed method is quick, sensitive, reliable, and can be used for the determination of CGA.

The purpose of this longitudinal study was to determine the effects of a rowing training program on physical fitness and body composition in female breast cancer survivors (56.78 ± 6.38 years). Over six months, the participants (n=40) performed two training sessions per week for an average of 75 minutes, combining resistance and muscle strength exercises with rowing. To evaluate the impact of the program, physical fitness tests and anthropometric measurements were carried out before and after the training protocol. The results show statistically significant improvements in measures such as weight (-1.84 kg), BMI (-0.7 kg/m2), hip (-3.24 cm) and waist circumference (-2.45 cm). In addition, variables associated with physical fitness also improved including leg strength (3.04 cm), dominant handgrip strength (4.24 kgf), non-dominant handgrip strength (3.49 kgf), aerobic endurance (78.35 m) and muscle flexibility (3.96 cm). We can therefore conclude that a rowing-based exercise program is an effective strategy to improve physical fitness in this type of population, yielding improvements in both anthropometric measurements and basic physical capacity variables, essential factors for better health and quality of life.

Interest on psychosocial predictors of doping has been increasing as a way of finding new approaches to reduce use of performance-enhancing drugs. This investigation aimed to test the psychometric properties of an instrument to asses doping attitudes in Brazilian athletes. The PEAS was validated to Brazilian sports through a process of translation, back-translation and content validity assessment, presenting satisfactory evidences based on its content (CVC&gt;0.80). Then, 994 athletes, from different sexes, types of sports and competitive levels, answered to the Brazilian version of the PEAS. Results showed satisfactory evidences of validity based on its response process, internal structure [X2/df = 2.04; RMSEA = 0.032 (0.026-0.038); CFI = 0.96; TLI = 0.95] and reliability (Cronbach’s α, McDonald’s ω, and CR &gt; 0.70). Network analysis was also used to further explore PEAS’s internal structure. Overall results provide support for the adoption of the PEAS for Brazilian athletes and possibly other Portuguese-speaking countries.

Artificial Intelligence (AI) is revolutionizing decision-making procedures in healthcare information systems (HIS), increasing the efficacy, accuracy, and personalization of healthcare. Notwithstanding remarkable progresses, yet there remain gaps in the holistic comprehension and implication of AI-driven technologies across various HIS scenarios. These gaps, consisting limited integration of AI across a variety of HIS parts and inadequate emphasize on interpretability and privacy, motivate our study to conduct a structured evaluation of recent AI applications in this domain. In this study, we present a novel taxonomy for the AI implication in medical decision-making. We analyzed 30 articles and categorized them into six groups including: Clinical Decision Support Systems (CDSS), Predictive Analytics, Natural Language Processing (NLP), Computer-Aided Diagnostics (CAD), Robotic-Assisted Surgery, and Virtual Health Assistants (VHAs/chatbots). Our study aims to propose a holistic perspective of the fast evolving perspective of AI in HIS. The majority of the investigated studies were published from 2023 and 2022, with Springer as the leading publisher (33%). Python and MATLAB were the most well-known simulation languages, applied in 48% and 20% of the papers, respectively, reflecting the technical trends in the area. By emphasizing on pivotal criteria like interpretability, accuracy, and privacy, this research aims to elucidate the crucial issues and development driving AI-driven decision-making in HIS.

The aim of the study was to assess the impact of two lengths of Nordic walking (NW) training interventions combined with time restricted eating (TRE) on improving body composition parameters, lipid profile, and levels of selected adipokines in women with disrupted body mass. Overweight and obese women (n=55, age: 21-85) were recruited. Four groups were selected: 6 weeks (SG6, n=13) and 12 weeks intervention (SG12, n=13); and two control groups: CON6 (n=13); and CON12 (n=13). The training sessions took place 3 times a week (60 minutes each) and were conducted outdoor under the supervision of professional coach. The training intensity was determined individually. The extended NW program combined with TRE induced a significant weight reduction in SG12 by 1.96 kg (p=0.010) and fat tissue by 1.64 kg (p=0.05). The proposed interventions did not affect LBM, TBW [kg], VFA and lipid profile. The LDL/HDL ratio changed with small size effect. Leptin concentration differed between groups (p=0.006), but not over time. For resistin, the differentiating factor was time (p=0.019, with lower results observed after the intervention). The change in leptin concentration was negatively correlated with its baseline concentration. Extended to 12 weeks, this intervention allows for an improvement in body composition. Neither 6 nor 12 weeks of training and fasting affected the lipoprotein profile.

Taiwan's bed and breakfast (B&B) development has been more than 25 years ago, from the first generation of retirement to the B&B industry, serving tourists from all over the world accom-modation, providing breakfast and accommodation mode to the present, after the change of employees from the second generation, more and more attention is paid to the cultivation and cultivation of business ability. With the advent of the era of AI technology networking, the ca-pabilities required for B&B operation are more focused on all aspects of service, and the good marketing ability of B&B can promote a green chimney-free tourism economy, which is also a favorite industry of various governments and the public. This study explores the basic vocational competency indicators required for running a B&B, with (1)EQ emotion management skills, (2)Financial management ability, (3)(SK) technical skills, and (4)Marketing and promotion management capabilities. Through the study method, the K-S Z test was determined by the con-sensus conclusion of expert reliability and validity p value

Introduction: Cleft lip with or without cleft palate (CL/P) is the most common congenital face anomaly in the world of multifactorial etiology. Objective: To determine the prevalence and characteristics of cleft palate. To identify associated risk factors to guide prevention and/or prenatal detection for early intervention and better health outcomes. To assess the rehabilitation protocols after operations in cleft palate. Design: Retrospective descriptive and clinical study. Patients: One hundred and three children with cleft palate treated in the Department of Head and Neck Surgery Clinic for Children and Young Adults, Department of Clinical Pediatrics, University of Warmia and Mazury, were included in the study. Methods: Records evaluation was conducted regarding sex, cleft type, mother occupation, parents education, histories of cleft in any of parents. The data were analyzed using R (R core team 2021) and the ordinal logistic regression analyses. Results: Children of stressed mothers during pregnancy had 9.4 times higher odds of having bilateral cleft. While there was no evidence that children sex, order of birth, and body mass as well as risk of maternal toxicity at work or reporting infections or drugs toxicity had a significant effect on the dependent variable. Conclusions: Children of parents with cleft history and having low educated mothers had higher probability of bilateral cleft palate. Children of stressed mothers during pregnancy had higher odds of having bilateral cleft. In literature, there is a lack of reports about rehabilitation in different operations methods in children with cleft palates.

The study conducts a comparative analysis of solar radiation estimation methods, assessing the efficacy of the Heliosat-2 algorithm against ground measurements across seven distinct countries: Netherlands, Spain, Japan, Namibia, South Africa, Saudi Arabia, and India. To achieve this, it utilizes two distinct satellite data sources—Himawari-8 for Japan and Metosat Second Generation-MSG for the rest of the countries—spanning the years Jan 2022 to April 2024. A robust methodology for determining albedo parameters specific to Heliosat-2 was developed. During cloudy days, the estimates provided by Heliosat-2 generally exceeded the ground measurements in all the countries. Conversely, on clear days, there was a tendency for underestimation, as indicated by the median value of the mean bias (MB) across most of the countries. The Heliosat-2 model slightly underestimates daily radiation values, with a median MB ranging from −27.5 to +10.2 W.m⁻². Notably, the median root mean squared error (RMSE) on clear days is significantly lower, with values ranging from 24.8 to 108.7 W.m⁻², compared to cloudy days where RMSE values lie between 75.3 and 180.2 W.m⁻². In terms of R² values, both satellites show a strong correlation between the estimated and actual values, with a median value consistently above 0.86 on a monthly scale and over 92% of daily data points falling within ±2 standard deviation.

Developing sustainability competences is an important endeavor for education, as competence development can be complex and requires appropriate approaches. In the case of preparing future educators, this becomes even more important, because of their multiplier role. The current study presents how a project, based on living-lab methodology, helped preservice preschool teachers, attending a course on sustainability issues, develop sustainability-specific professional action competence. Students collaborated with an organization and a school and were trained to deliver to 6-year-old pupils, activities concerning the protection of sea turtles. The process included reflection, based on a given template. After the intervention, the preservice preschool teachers reflected upon their role and professional performance and discussed how they, benefited from this project. They further analyzed through a group interview, how the Living Lab methodology raised their professional confidence and self-efficacy, and helped them develop content knowledge, pedagogical content knowledge, and a sense of purpose and motivation for teaching about sustainability. Outcomes indicate that participants felt confident and efficacious to teach about sustainability, and developed their content knowledge, pedagogy content knowledge, motivation, and volition due to a strong sense of purpose and responsibility. The overall process facilitated the development of critical thinking, systemic thinking, reflection, and collaboration..

The purpose of this study is to examine the match-related performance (scores and penalties) of the athletes in the Junior EJC (European Judo Championship) and U23 EJC categories before and immediately after the Covid-19 quarantine, according to gender and weight category groups. Our sample was based on the junior and U23, male and females, 2019-2020 Junior European Judo Championships and 2019-2020 U23 European Judo Championships. A total of 1431 matches in these tournaments were analyzed: male (n=812) and female (n=619). The main findings of this study showed that most matches in both the male and female categories resulted in ippon (2019-2020 average: 64,35% for Junior male, 70,55% for U23 male and 69,3% for Junior female, 64,4% for U23 female). No significant differences (p &gt; 0.05) were observed between gender and age groups concerning the match scores. In the formation phase of the technique, considerations of high- and low-intensity actions, and analysis of the speed of athletes during matches in official competitions can help to better understand the dynamics of the variability of movements in judo matches. In addition, suggestions are presented to be applied to athletes in different age categories who are on the way to become Olympic athletes.

The objective of this paper was to study the expression pattern of the GLOD4 gene in the testis and its regulatory effect on testicular cells. Currently, the regulated mechanism through are unclear. Here, we explored how GLOD4 functions in goat leydig cells to enhance our understanding of spermatogenesis and improve reproduction in breeding rams. In this study, we demonstrated that the localization of GLOD4 in testicular cells using immunohistochemistry and subcellular localization analyses. Subsequently, we analyzed the GLOD4 expression pattern in 4 age-based groups (0, 6, 12, and 18 months old) using real-time quantitative polymerase chain reaction (qRT‒PCR) and protein blotting. Finally, we performed GLOD4 gene silencing and overexpression studies in testicular cells from goats and explored the effects of GLOD4 on cell proliferation, the cell cycle, steroid hormone secretion and the expression of candidate testosterone hormone-regulated genes. GLOD4 was mainly expressed in testicular leydig cells, and the subcellular localization results showed that the GLOD4 protein was mainly localized in the cytoplasm and nucleus. Silencing of GLOD4 significantly suppressed the mRNA expression levels of the testosterone secretion-related genes CYP11A1, 3β-HSD and CYP17A1 and the mRNA expression levels of cell-cycle related genes CDK6, PCNA, and Cyclin E. Moreover, the cell cycle was blocked at the G2/M phase after GLOD4 silencing, which significantly suppressed testosterone secretion. In contrast, GLOD4 overexpression significantly increased the mRNA expression levels of the testosterone secretion-related genes CYP11A1, 3β-HSD, and CYP17A1 and increased the expression of the cell-cycle related genes CDK6, PCNA, and Cyclin E. Moreover, GLOD4 overexpression promoted the cell cycle from G0/G1 phases to enter the S phase and G2/M phases,promoted the secretion of testosterone. Taken together, our experimental results indicate that GLOD4 may affect the development of cells in Qianbei Ma goats of different ages by influencing the cell cycle, Proliferation and testosterone hormone synthesis. These findings enhance our understanding of the functions of GLOD4 in the cells of goats.

Photovoltaic (PV) systems, which are renewable energy sources, are increasingly being utilized in distributed generation. To maintain a stable energy balance, energy storage systems such as batteries (BAT) play a vital role. Electric vehicles (EVs) offer a promising solution with rechargeable battery systems for operation. The BATs must maintain their state of charge within design boundaries, despite intermittent PV and load power fluctuations, and advanced power control and management techniques are essential for their effective operation. The article evaluates an intelligent controller that uses a Sliding Mode Control adaptive deep learning algorithm Convolutional Neural Networks (SMC-CNN) and a unique Strategy for managing supervisory power. (SPMS) for photovoltaic systems with battery energy storage for better regulation of DC bus voltage. SMC-CNN offers exceptional resilience and seamless functionality, minimizing fluctuations in DC bus voltage in the control strategy design requirements. The primary goals are maintaining a consistent power supply and ensuring continuous service by preventing system components from exceeding capacity. This study aims to enhance the control of DC bus voltage in the PV and battery system, with the primary significance focusing on the following aspects. The advanced SPMS has been created, incorporating control system constraints to enhance SOC balancing speed and reduce fluctuations in DC bus voltage. Power flow management involves optimizing energy flow between the PV system, battery system, and load while minimizing battery capacity requirements. The proposed SMC-CNN and SPMS are demonstrated through real-time simulation using Matlab/Simulink, as demonstrated in comprehensive case studies.

This study aimed to evaluate the effects of Blazepod technology when incorporated with various training regimens on the essential elements of physical fitness in volleyball, such as agility, speed, visual response time, and vertical leap. Thirty-six participants (age :17.33±0.48 y, height: 183.78±6.34 cm, weight: 77.14±5.16 kg) were in-volved in this study. In randomized design, three equal groups with two experimental groups and one control group were involved in the study over a period of six weeks: (GE1) used Blazepod technology to workout at a low level; (GE2) used Blazepod technology to workout at a higher intensity; (CG) did not employ Blazepod technology, but it adhered to the same fundamental training curriculum. We conducted agility, speed, reaction time, and vertical jump tests before, midway and after the study to determine optimal training volume, intensity, and frequency. A significant main effect of time (P0.01), and time×group interaction (P>0.001) were found for all tests. Post hoc test showed that the two experimental groups gadget significantly improved in all performance variables (P

Aim: This study aimed to evaluate the effectiveness of a plyometric training program designed to enhance agility, speed, and social interaction among boys with mild intellectual disability (ID) aged 10-12, within the Special Olympics framework. Participants: Thirty-two boys (mean age = 10.69 ± 0.8 years; mean IQ = 61 ± 7) from three inclusive education centers participated in the study. Methods: The intervention consisted of a 10-week plyometric training program, conducted twice a week. Pre- and post-intervention assessments included the Reaction Time Test, 4-Corner Agility Test, 10-Meter Speed Run, 4x5 Meter Relay Test, and the Friendship Activity Scale (FAS). Results: The study found significant improvements across all measures. Reaction time decreased by 0.83 seconds (t = 7.44, p < 0.001), 4-corner agility improved by 0.77 seconds (t = 11.93, p < 0.001), 4x5 meter speed improved by 0.61 m/s (t = 17.37, p < 0.001), and 10-meter run speed improved by 1.55 m/s (t = -12.76, p < 0.001). Additionally, the FAS score increased by 0.81 points (t = 9.59, p < 0.001), indicating enhanced social interactions. Conclusion: The plyometric training program significantly improved agility, speed, and social interaction in children with mild ID, demonstrating the effectiveness of inclusive, adaptive physical education strategies within the Special Olympics framework.

Aging causes various degenerative diseases in the older adult population. Senescence, a state of permanent cell-cycle arrest accompanied by the production of various pro-inflammatory factors known as senescence-associated secretory phenotype (SASP), is considered a significant contributor to the aging process and its chronic diseases. Ample evidence showed that various stressors could induce senescence, including DNA damage, telomere shortening and damage, activation of oncogenes, and mitochondrial dysfunction. Numerous credible findings indicate that environmental agents can induce senescence, including UV radiation, a high-fat diet, heavy metal exposure, and cigarette smoke. These findings posed the possibility that many more environmental agents may induce senescence and accelerate aging but remain unidentified. Senescence also becomes more intriguing due to its promising future as a pharmacological target to blunt the detrimental effects of aging and prevent aging-related diseases, either by eliminating the senescent cells or by controlling the SASP. On the other hand, investigating senescence has become more intricate due to the need for a multi-marker approach and translation in vivo analysis. This review will discuss senescence and its biomarkers, how to identify gerontogens in vivo, and also the development of senotherapy that targets senescent cells.

This study presents a comprehensive investigation into the spectrum and determinants of child abuse and neglect in Nkpor-Uno, a community in Anambra State, Nigeria. Through a descriptive surveys design, the study explores various forms of abuse and neglect experienced by children, as well as the underlying factors contributing to these phenomena. The population for the study consisted of 1000 parents/ caregivers who are residents of Nkpor-uno. The sample for the study consisted of 100 respondents, purposive sampling techniques was used for the study. The questionnaire was a self-designed structured questionnaire. Data collected were analyzed using frequency, mean and standard deviation. Findings reveal alarming prevalence rates of child maltreatment, including physical, emotional, sexual abuse, and neglect. Socioeconomic factors such as poverty, parental substance abuse, family dynamics, and inadequate sex education emerged as significant contributors to child maltreatment. The study underscores the urgent need for targeted interventions and support systems to address the root causes of abuse and neglect and safeguard the well-being and development of children in Nkpor-Uno. By raising awareness, enhancing access to resources, and promoting positive parenting practices, we can strive towards building a safer and healthier environment for children, ensuring they are protected from harm and given the opportunity to thrive.

In recent years, bioengineered and biotechnological products have gained tremendous attention to identify unique biologic features associated with oncology. To overwhelm the complexity of tumor personalized medicines (PM) or vaccines could be a promising way-out to be considered. Cancer is a heterogeneous disease. This characteristic variability of cancer provides itself to the emergent era of PM i.e., precision oncology. The prime objective of PM is merely to deliver the right treatment to the right patient at the right time. For instance, imatinib was effectively targeted chronic myeloid leukemia. To date, attainment in using PM approaches to cancer treatment have been mixed. The next-generation sequencing (NGS), and the use of several biomarkers (e.g., HER2, BRAF, ALK, etc.), to drive precise cancer treatment through a timely and cost-effective manner. In current review, author summarizes the advancement in the field of PM such as CRISPR-Cas9, NGS, pharmacogenomics, and the benefits of machine learning techniques. The precise communication between healthcare professionals, regulatory bodies, and patients is essential to translate advances in PM into immense benefits for patients with cancer globally.

The use of artificial intelligence (AI) applications in education has the potential to revolutionize the learning experience for international students, who face unique challenges when studying in a foreign country. This paper explores various examples of AI applications in education and their potential impact on international students. AI applications such as personalized learning experiences, adaptive testing, predictive analytics, and chatbots for learning and research are examined for their potential to improve learning efficiency and provide customized education support. It also explores the significant risks and limitations associated with AI technologies, such as privacy, cultural differences, language proficiency, and ethical implications. To maximize the potential benefits of AI applications in higher education, it is crucial to implement appropriate safeguards and regulations. This paper provides a starting point for research on the potential impact of artificial intelligence on international students’ educational experiences and how AI may be integrated into educational administration and learning processes.

Multiple myeloma (MM) accounts for about 10 to 15% of all diagnosed hematologic malignancies and about 1-2% of all cancer cases. Approximately 80-90% of MM patients develop bone disease and the changes rarely regress. It is only possible to stop or slow their progression. A major role in bone destruction in MM is attributed to the Wnt signaling pathway, and its action can be modified by various types of interventions including training and diet. Therefore, the aim of this project was to evaluate the effects of a Nordic Walking (NW) training cycle and intermittent fasting (IF) on the levels of selected bone turnover markers associated with the Wnt pathway in patients with MM. Results from 35 patients divided into training (NW and IF NW) and non-training (IF and control) groups were included in the analysis. A 6-week training cycle involving 60-minute workouts 3 times a week was conducted. Body mass and composition and the levels of: vitamin D, calcium and phosphorus, beta2-microglobulin and albumin were examined before and after completion of training cycle. Markers of bone turnover were also determined: sclerostin (SOST), Dickkopf-related protein 1 (DKK-1), osteoprotegrin (OPG), osteopontin (OPN) and Tartrate-resistant acid phos-phatase 5b (TRACP 5b). There was no negative effect of IF or combined training and fasting on the nutritional status of the patients (the level of albumines was unchanged). Both training groups showed an increase in serum concentrations of the active metabolite of vitamin D (IF NW and NW: p=0.001 and p=0.022, re-spectively). The change in the concentration of this vitamin negatively correlated with the con-centration of TRACP 5b (r=-0.413, p=0.014). Evaluating the concentrations of markers related to bone turnover, a reduction in the concentrations of SOST (time: p=0.026, time vs. group: p=0.033) and TRACP 5b (time: p

The aim was to identify if surface electromyography (sEMG) parameters are indicative of post-activation potentiation (PAP)/post-activation performance enhancement (PAPE), in terms of twitch potentiation and voluntary performance. Three databases were used in March 2024, with the following inclusion criteria: (a) original research, assessed in healthy human adults, (b) sEMG parameters were measured. The exclusion criteria were: (a) studies with no PAP/PAPE-protocol, (b) non-randomized control trials. The following data were extracted: study characteristics/demographics, PAP/PAPE-protocols, sEMG parameters, twitch/performance outcomes, and study findings. A modified physiotherapy evidence database (PEDro) scale was used for quality assessment. Fifteen randomized controlled trials (RCTs), with a total of 199 subjects were included. The M-wave amplitude (combined with a twitch torque outcome) was shown to generally be indicative of PAP. The sEMG amplitude (in some muscles) were found to be indicative of PAPE during ballistic movements, while a small decrease in the MdF (in certain muscles) were shown to reflect PAPE. Changes in the Hmax/Mmax ratio were found to contribute (temporally) to PAP, while the H-reflex amplitude was shown to be neither indicative of PAP nor PAPE. This review provides preliminarily findings suggesting that certain sEMG parameters could be indicative of PAP/PAPE. However, future research is warranted.

Incorporating AI tools like ChatGPT into higher educational settings has been beneficial for education, yet the extent of user satisfaction with the information provided by these tools, known as user information satisfaction (UIS), remains underexplored. Our study introduces a UIS model specifically designed for ChatGPT's application in the educational sector. Drawing from established UIS theory, we crafted a model centered around seven essential factors that influence the effective use of ChatGPT, aiming to guide both educators and learners in overcoming common challenges such as plagiarism and ensuring the ethical use of AI. We gathered data from Indonesian university participants and applied Structural Equation Modeling using Smart-PLS 4.0 for our data analysis. The results reveal that completeness, precision, timeliness, convenience, and the format of information as the most influential factors driving user satisfaction with ChatGPT. Interestingly, our research indicated that the accuracy and reliability of the information, typically deemed paramount, were not the primary concerns in the academic use of ChatGPT. Our findings lead to a recommendation for a cautious approach to the integration of ChatGPT in higher education. We advocate for a strategic use that recognizes its innovative potential while also acknowledging its limitations, thus ensuring a responsible and effective application in educational contexts. This balanced perspective is crucial for integrating AI tools into the academic fabric without compromising educational integrity or quality.

Amidst the dynamic landscape of education, this paper embarks on a transformative journey that explores the integration of Artificial Intelligence (AI) in literature and language education. Through a qualitative exploratory approach, purposeful and maximum variation sampling method, the researcher delves into the experiences of educators and learners, unraveling the multifaceted dimensions of AI-driven pedagogy in SMC. Drawing upon a theoretical framework encompassing Constructivism, Connectivism, and Socio-Cultural Theory, the study examines AI's role in reshaping pedagogical landscapes, fostering critical thinking, and expanding access to education. The results resonate with participants' narratives, unveiling AI's potential in fostering personalized learning pathways, enhancing collaborative engagement, and bridging digital divides. Ethical considerations in AI education are explored, leading to the proposition of responsible guidelines. These findings underline the transformative power of AI in education, aligned with the institution's commitment to quality education and innovation. Overall, the study calls for ongoing exploration, emphasizing the qualitative research method's depth and richness, as well as the theoretical framework's guidance in realizing the study's objectives. As AI continues to shape education's frontiers, this research underscores the significance of adaptability, ethical awareness, and holistic engagement for school administrators, educators, learners, and researchers alike.

Students have historically fared poorly on the West African Examinations Council’s (WAEC) mathematics exam. This study investigated senior high school students’ difficulties with studying Geometry in the Cape Coast Metropolis, Central Region, Ghana. Using the descriptive survey design, data were collected from 300 Senior High School Two (SHS 2) students using simple random sampling. Students responded to the questionnaire and a 30-item multiple-choice achievement test on geometry. Four geometry concepts students perceived difficult to study are Circle theorems, Perpendicularity of Tangent and radius of a circle, Angle between Tangent and a chord and Tangents from an external point. The reasons for the difficulty in studying geometry topics are the unavailability of instructional materials, the geometry topics being complex, and teachers not teaching geometry concepts to the students’ understanding. Students’ gender did not influence the learning of concepts in geometry at a 0.05 level of significance. There was an insignificantly weak positive correlation between the students’ performance and their perceived difficult geometry concepts. It was concluded that the Ministry of Education does not provide relevant instructional materials to the various schools to teach geometry concepts. Schools do not organise workshops and seminars for teachers on effectively teaching geometry concepts in mathematics.

The main purpose of the study was to study the effects of a specific rowing ergometer training program on the athletic performance of young adolescents (n=56; 11.73 ± 1.4 years old) com-pared to a workout based on general strength training. Eight-week training program was im-plemented, with four sessions per week and two-hours per session. Sample was divided in two groups: a control group (CG) that performed circuit training with exercises aimed at building general strength and an experimental group (EG) who focused on specifically training on a rowing ergometer (rowing machine). The data obtained in a rowing meter test over the compe-tition distance were analyzed to obtain the average power attained (W) at the beginning of the training, at the middle (4 weeks), at the end of the training (8 weeks) and one year after the ex-perimentation. The results show that, although both forms of training improve the average W obtained in both categories, the EG subjects (+29.94W) obtained better averages in all phases of the study compared to the CG (+5.88W). Furthermore, this increase was greater in male rowers (+ 34.06W) than in female rowers (+24.54W). These results reveal that a specific rower rowing ergometer training program has a significant effect than a general strength program and these effects can even be observed a year after the intervention.

Background: Generative artificial intelligence (Gen-AI) has emerged as a transformative tool in research and education. However, there is a mixed perception about its use. This study assessed the use, perception, prospect, and challenges of Gen-AI use in higher education. Methods: This is a prospective, cross-sectional survey of university students in the United Kingdom (UK) distributed online between January and April 2024. Demography and perception of Gen-AI and other AI tools were assessed and statistically analysed to assess the difference in perception between various subgroups. Results: A total of 136 students responded to the survey of which 59% (80) were male. The majority were aware of Gen-AI and other AI use in academia (61%) with 52% having personal experience of the tools. Grammar correction and idea generation were the two most common tasks of use, with 37% being regular users. Fifty-six percent of respondents agreed that AI gives an academic edge with 40% holding a positive overall perception about the use in academia. Comparatively, there was a statistically significant difference in overall perception between different age ranges (I² = 27.39; p = 0.002) and levels of education (I² = 20.07; p < 0.001). Also, 83% of students believe AI use will increase in academia with over half agreeing it should be integrated into learning. Plagiarism (33%), privacy issues (14%), and lack of clarity by the university (13%) remain the top concerns regarding the use of Gen-AI and other AI tools in academia. Conclusions: Gen-AI and other AI tools are being used and their use will continue to grow in higher education. While current use is challenging due mainly to plagiarism fear and lack of clarity by the university, most users believe AI should be integrated into the university curriculum.

As the world faces unprecedented environmental challenges and the rapid advancements of artificial intelligence (AI), it is crucial for universities to adapt their chemistry education to remain relevant and contribute to sustainability and the United Nations' Sustainable Development Goals (SDGs). This report offers critical insights into the development of university chemistry education over the next 10-20 years, forecasts its development over the next 10-20 years, and offers recommendations for the Ministry of Education and universities to ensure the continued relevance of chemistry programs in the face of AI.

Preventive Maintenance (PM) is a periodic maintenance strategy, which has great results for devices in extending their life, increasing productivity, and most importantly, help avoid unexpected breakdowns and their costly consequence. A preventive maintenance scheduling (PMS) is determining the time for carrying out PM, and it represents a sensitive issue in terms of impact on production if the time for the PM process is not optimally distributed. In this study, hybrid heuristic methods were used to solve the PMS problem, as genetic algorithm and Tabu research were adopted. The optimal solution was reached in a short time compared to previous studies in which optimal methods were used, integer programming and nonlinear integer programming. Also, sensitivity analysis was applied to measure the robustness and strength of the method used, where an optimal solution was obtained for all experiments and in record time. This method can be used for power plants in privet or public sectors, to generate an optimal PMS, to save money, and to avoid water or electricity cuts.

The Cosmic Theory of Structure (CTS) model has undergone significant refinement to address the hierarchy problem by incorporating the concept of running couplings. This update provides a more robust framework for understanding the formation and evolution of cosmic structures, offering a natural explanation for mass scales due to quantum effects. We present new validations using gravitational wave data from events GW150914 and GW151226, neutrino oscillation data from IceCube, dark matter density data from the Planck survey, and quantum field interaction data. The enhanced model demonstrates improved alignment with observational data, reinforcing the CTS model's predictive power and its potential to unify gravity and quantum physics within a single theoretical framework.

In this follow-up study, we aimed to assess the effectiveness of the “I do not smoke, I exercise”, anti-smoking preventive health education program. The program was based on the Theory of Planned Behavior supplemented with life-skills teaching and targeted at high school students. The intervention comprised ten one-hour online sessions, administered by physical education instructors. The study cohort comprised 222 students (109 boys, 113 girls) from 11 secondary schools, with an average age of 16.42 ± 1.36 years. Data collection involved pre- and post-intervention self-assessment questionnaires. The examined variables included attitudes towards smoking, intention to smoke, subjective norm, perceived behavioral control (PBC), knowledge about smoking, smoking behavior, exercise behavior, attitudes toward the program's implementation, and satisfaction with the program. Separate paired samples t-test revealed a significant improvement in students' knowledge about smoking, perceived behavioral control, and overall program satisfaction following the intervention. However, no significant changes were observed in the remaining variables. These findings suggest that the health education smoking prevention intervention incorporates techniques and strategies that influence the Perceived Behavioral Control variable, emphasizing students' strong interest in educationally theorized programs integrating technology into their design. Future studies should consider further examination of tobacco control strategies within the high school context.

The BL Lacertae (BL Lac) object OJ 287 underwent an intense X-ray activity phase, exhibiting its brightest recorded X-ray flare in 2016-2017, characterized by much softer X-ray spectra and, concurrently, its first-ever recorded very-high-energy (VHE) emission (100--560 GeV), reported by the VERITAS observatory. Broadband spectral energy distribution reveals a new jet emission component similar to high-synchrotron-peaked BL Lac objects, thereby implying the soft X-ray spectrum for the synchrotron emission. Using the advantage of simultaneous X-ray and VHE spectral information, as well as the source being a low-synchrotron-peaked BL Lac object, we systematically explored the extragalactic background light (EBL) spectrum by demanding that the VHE spectrum cannot be harder than the X-ray spectrum. We used three different phenomenological forms of the EBL spectral shape (power-law, parabola, and polynomial) motivated by current constraints on the EBL with the Bayesian Monte Carlo approach to infer the credible EBL range. Our study favors an almost flat power-law spectral shape and is consistent with previous studies. The other spectral forms capable of capturing curvature though result in a better statistics value; the improvement is statistically insignificant given the additional parameters.

Promoting the sustainable development of resource-based cities is of great significance to the ecological protection and high-quality development of the Yellow River Basin. Combining the environmental status and economic development, we objectively evaluate the ecological safety level of resource-based cities in the Yellow River Basin, compare and analysis the main factors affecting the ecological safety of different resource-based cities, and formulate precise and differentiated ecological safety protection measures in river basins to achieve high-quality development. Taking the Yellow River Basin as an example, this paper analyses the ecological level of the Yellow River Basin based on the theory of sustainable development, calculates the ecological safety level of 30 resource-based cities in the Yellow River Basin from 2006 to 2020 by TOPSIS model, and makes convergence analysis by classification. Through the DID empirical test of sustainable development planning policy on ecological safety factors, distinguish the development characteristics of different resource-based cities. The results show that: (1) the ecological safety level of resource-based cities in the Yellow River Basin is generally developing well, and there are differences among different types of resource-based cities; (2) the kinetic energy of sustainable development of resource-based cities in the Yellow River Basin is mainly industrial transformation, and the power of science and technology is insufficient; (3) local governments pay limited attention to environmental protection, and the sustainable development planning of resource-based cities in 2013 mainly promotes the adjustment of industrial structure of resource-based cities.

Tuberculosis (TB) remains a global health threat, necessitating innovative strategies for control and prevention. This comprehensive review explores the Mycobacterium tuberculosis Lysine Exporter (LysE) gene, unveiling its multifaceted roles and potential uses in controlling and preventing tuberculosis (TB). As a pivotal player in eliminating excess L-lysine and L-arginine, LysE contributes to the survival and virulence of M. tuberculosis. This review synthesizes findings from different electronic databases and includes 13 studies focused on the LysE of M. tuberculosis. The research unveils that LysE can be a potential drug target, a diagnostic marker for TB, and a promising candidate for vaccine development. The absence of LysE in the widely used BCG vaccine underscores its uniqueness and positions it as a novel area for TB prevention. In conclusion, this review underscores the significance of LysE in TB pathogenesis and its potential as a drug target, diagnostic marker, and vaccine candidate. The multifaceted nature of LysE positions it at the forefront of innovative approaches to combat TB, calling for sustained research efforts to harness its full potential in the global fight against this infectious disease.

Understanding vaccine hesitancy in organ transplant recipients (OTR) is critical, given clear, alt-hough attenuated, benefits from vaccination. Adult OTR were surveyed regarding vaccine-related values and a novel outcome variable called Vaccine Acceptance Composite Score (VACS) was built as the average Likert score of 7 domains of vaccination confidence. Of 46 OTR included (93.5% kidney transplant recipients), 32.6% were female, 13.3% Black, 6.77% Hispan-ic/Latino/a/x; median age was 58 years. Patients were most concerned about COVID-19 vac-cine-associated risks (46.3%), its potential effect on allograft (47.6%) and motives of government officials involved with vaccine policy (55.6%). Politically conservative patients were likely to have a significantly lower VACS, while those who lived with someone ≥65 had a higher VACS. The VACS was not significantly associated with race, income, religious beliefs, comorbidities, COVID-19 history, or influenza vaccination status. Higher VACS was significantly associated with ≥3 and ≥4 COVID-19 immunizations. This study highlighted political beliefs and elderly household members as correlates of vaccine acceptance among OTR. The VACS may be a useful tool to help standardize multifaceted analyses in vaccination-focused behavioral research, as well as identify individuals and groups at risk for vaccine hesitancy, who may benefit from tai-lored outreach and educational interventions.

Human milk (HM) feedings are associated with reduced risks of neurodevelopmental and neurocognitive delays and systemic inflammatory diseases in infants born prematurely and/or at a low birth weight. Utilizing a neonatal piglet model, HM feedings were compared to bovine milk-derived infant formula (IF)-feedings with the aim of understanding the underlying mechanisms involved in reducing these risks. Six male piglets at postnatal-day (PD)2 were randomized into two feeding groups: HM-fed (n = 3) or IF-fed (n = 3) for 28 days. At 3- and 4-weeks-old, piglet memory and learning performance were assessed using novel object recognition (NOR). At PD30 piglets were euthanized, and whole brains were excised, weighed, and preserved for further analyses, and brain microglial morphology, and systemic inflammatory cytokines were quantified. During NOR, HM-fed piglets had significantly more non-novel revisits at both 3- and 4-weeks-old compared to IF-fed piglets. Microglia of HM-fed piglets had longer processes, more branch points, more endpoints, and a larger territorial volume compared to IF-fed piglets at PD30. In a neonatal piglet model, HM-feedings may improve cognition and reduce brain inflammatory response compared to IF-feedings.

Background: Bioelectrical impedance (BIA) and ultrasound (US) have become popular for estimating body fat percentage (BF%) due to their low cost and clinical convenience. However, agreement of these devices with gold standard method still require investigation. The aim was to analyze the agreement between a gold standard %BF assessment method with BIA and US devices. Methods: Twenty-three men (age 30.1 ± 7.7 years, 82.5 ± 14.9 kg, 1.77 ± 0.05 m) underwent Dual Energy X-Ray Absorptiometry (DXA), BIA (tetrapolar) and US (three-site method) %BF assessment. Pearson and concordance correlations were analyzed. T-test compared means between methods, and Bland Altman plots analyzed agreement and proportional bias. Alpha was set at &lt; .05. Results: Pearson coefficients between BIA and US with DXA were high (BIA = 0.94; US = 0.89; both p &lt; .001). Concordance coefficient was high for BIA (0.80) and moderate for US (0.49). BF% measured by BIA (24.5 ± 7.5) and US (19.4 ± 7.0) were on average 4.4% and 9.6% lower than DXA (29.0 + 8.5%), respectively (p &lt; .001). Lower and upper agreement limits between DXA and BIA were -1.45 and 10.31, while between DXA and US were 2.01 and 17.14, respectively. There was a tendency of both BIA (p = .09) and US (p = .057) to present proportional bias and underestimate BF%. Conclusions: Despite the correlation, the mean difference between the methods were significant, and the agreement limits are very wide. This indicate that BIA and US, as measured in this study, have limited potential to accurately measure %BF compared to DXA, especially in individuals with higher body fat.

Considering the unquestionable role of education in economic development, it has an impact at a macroeconomic level—contributing to enhancing productivity and innovation, reducing poverty and promoting social cohesion—and at a personal level—ensuring the improvement of knowledge, skills and individual capabilities and promoting social values like empowerment and equality. Notably, quality education is recognized as one of the Sustainable Development Goals (SDGs), which, jointly with other behaviors and attitudes, could impact the development of societies in other fields like health and well-being, cultural preservation, environmental sustainability and even peace and stability—all of them also listed as SDGs. However, the capacity, or not, to reach higher levels of compliance with quality in education (SDG 4) varies from country to country, according to the 2023 Sustainable Development Report results. Thus, the present study used a fuzzy set qualitative comparative analysis to assess the conditions for attaining higher levels of quality education based on the different indicators used to measure SDG 4. The analysis will allow comparisons of results among different countries and provide information about the initiatives that could be relevant to increasing quality education worldwide and for policymakers.

In order to solve the problem of large eddy current loss and high temperature rise caused by large amount of permanent magnet, a new type of combined magnetic pole permanent magnet motor is proposed in this paper. The sinusoidal distribution subdomain model of non-uniform air gap rotor is established by using Laplace equation, and the analytical expression of eddy current loss of rotor in uniform air-gap and non-uniform air-gap is derived. The effect of rotor eccentricity on eddy current loss is obtained. According to the characteristics of distributed winding of non-uniform air gap combined pole permanent magnet motor, equivalent treatment is performed to obtain the equivalent thermal conductivity, so as to establish equivalent thermal network model of motor, calculate the temperature value of each component of the motor, and verify the correctness of the thermal network model through the method of magnetothermal bidirectional coupling. Finally, an experimental platform is set up to carry out temperature rise experiments on the two prototypes respectively. Experimental results show that the non-uniform air-gap rotor structure can effectively reduce the rotor eddy current loss and motor temperature rise, and also verify the accuracy of the analytical model calculation results.

The sweetpotato whitefly, Bemisia tabaci MEAM1, is a pest known to significantly impact tomato development and yields through direct damage and virus transmission. To manage this pest, the current study compared the effectiveness of various insecticide rotations. Field trials included rotations involving synthetic insecticides, biochemicals, and microbial agents, applied according to their labeled highest concentrations. Results indicated that while standard synthetic insecticides consistently reduced whitefly egg and nymph counts significantly, microbial biopesticide rotations also achieved reductions, although less consistently. This study demonstrated that while traditional chemical treatments remain highly effective, integrating microbial biopesticides containing Beauveria bassiana and Cordyceps javanica present a viable alternative that could mitigate resistance development and reduce environmental impact. The findings suggest the potential for optimizing integrated pest management (IPM) and Insecticide Resistance Management (IRM) strategies by incorporating a variety of modes of action to sustainably manage B. tabaci MEAM1 populations in agricultural settings.

During choriogenesis in insects, chorion (eggshell) is formed by surrounding follicular epithelial cells in ovarioles. However, the regulatory endocrine factor(s) activating choriogenesis and the chemical components on eggshell deserve further exploration. In two representative Coleopterans, a Coccinellid Henosepilachna vigintioctopunctata and a Chrysomelid Leptinotarsa decemlineata, genes encoding the 20-hydroxyecdysone (20E) receptor heterodimer, ecdysone receptor (EcR) and ultraspiracle (USP), and two chitin biosynthesis enzymes UDP-N-acetylglucosamine pyrophosphorylase (UAP) and chitin synthase (ChS1), were highly expressed in ovaries of the young females. RNA interference (RNAi)-aided knockdown of either HvEcR or Hvusp in H. vigintioctopunctata inhibited oviposition, suppressed the expression of HvChS1, and lessened the positive signal of Calcofluor staining on the chorions, which suggests the reduction of a chitin-like substance (CLS) deposited on eggshells. Similarly, RNAi of LdEcR or Ldusp in L. decemlineata constrained oviposition, decreased the expression of LdUAP1 and LdChS1, and declined CLS contents in the resultant ovaries. Knockdown of LdUAP1 or LdChS1 caused similar defective phenotypes, i.e., reduced oviposition and CLS contents in the L. decemlineata ovaries. These results, for the first time, indicate that 20E signaling activates choriogenesis in two Coleopteran species. Moreover, our findings propose the deposition of a CLS on the chorions.

Artificial Intelligence (AI) and Machine Learning (ML) approaches that could learn from large data sources have been identified as useful tools to support clinicians in their decisional process; AI and ML implementations have had a rapid acceleration during the recent COVID-19 pandemic. However, many ML classifiers are “black box” to the final user, since their underlying reasoning process is often obscure. Additionally, the performance of such models suffer from poor generalization ability in presence of dataset shift. Here, we present a comparison between an explainable-by-design (“white box”) model (Bayesian Network (BN)) versus a black-box model (Random Forest), both studied with the aim to support clinicians of Policlinico San Matteo University Hospital in Pavia (Italy) during the triage of COVID-19 patients. Our aim is to evaluate whether the BN predictive performances are comparable with those of a widely used but less explainable ML model such as Random Forest and to test the generalization ability of the ML models across different waves of the pandemic.

The Qiushuwan Cu-Mo deposit, located in the East Qinling molybdenum belt, which is a major mining site recognized for its enormous reserves of medium-sized molybdenum. In order to enhance our comprehension and ascertain supplementary mineral resources, it is critical to conduct an in-depth investigation of both the deep and peripheral regions. The primary goal of this study is to investigate the Qiushuwan Copper Molybdenum Mine, which is located in Zhenping County, Henan Province. The spread spectrum-induced polarization (SSIP) method is utilized as a means of conducting mining exploratory analysis. Significant findings have been obtained through the collection of SSIP data, geological analysis, and electrical parameter study of rock and ore samples along profile-80. By conducting a meticulous examination of the SSIP data at suitable frequencies, two prominent conductive ore bodies, specifically C2 and C4, have been successfully discovered. C2 exhibits a correlation with granite porphyry and molybdenum veins, while C4 is linked to a skarn deposit that contains a concentration of copper ore. The spatial differences in conductivity within the research area have been precisely characterized using resistivity models obtained from the SSIP data. The precision and dependability of our conclusions have been confirmed through the integration of borehole data and the matching of geological sections with inversion models. The recovered core samples show a diverse range of minerals, containing both valuable ores and minerals that have undergone alteration. Pyrite constantly appears with molybdenite in the majority of samples. The aforementioned results provide a strong foundation for future exploration initiatives and sustainable resource exploitation, enabling informed decision-making in the effective use and administration of natural resources. This study adds to the existing body of knowledge on the Qiushuwan Cu-Mo deposit and improves exploration methods in the region by utilizing the SSIP approach. The findings are a useful asset for geologists, mining experts, and stakeholders, offering essential knowledge for future exploration and sustainable utilization of resources.

According to the World Health Organization (WHO), dementia is the seventh leading reason of death among all illnesses and one of the leading causes of disability among the world’s elderly people. Day by day the number of Alzheimer’s patients is raising. Considering the increasing rate and the dangers, Alzheimer’s disease should be diagnosed carefully. Machine learning is a potential technique for Alzheimer’s diagnosis but general users do not trust machine learning models due to the black-box nature. Even, some of those models do not provide the best performance because of using only neuroimaging data. To solve these issues, this paper proposes a novel explainable Alzheimer’s disease prediction model using a multimodal dataset. This approach performs a data-level fusion using clinical data, Freesurfer MRI segmentation data, and psychological data. For Alzheimer’s disease vs cognitively normal prediction, the random forest classifier provides 100% accuracy. Furthermore, Alzheimer’s disease and non-Alzheimer’s dementia should be classified properly because their symptoms are similar. To the best of our knowledge, we are the first to present a three-class classification on Alzheimer’s disease vs cognitively normal vs non-Alzheimer’s dementia and achieved 99.86% accuracy using an ensemble model. Besides, a novel Alzheimer’s patient management architecture is also proposed in this work..

High resolution information on nucleotide arrangement in the genome of any or-ganism is critical to understand its genetic makeup, function, and evolutionary his-tory. For years, DNA sequencing has provided crucial breakthroughs in the field of genomics and molecular biology. With the advent of technology, Next Generation Sequencing has now transformed the whole genome sequencing prospects, thus unveiling the novel and interesting features of an organism genome that can behold. Next generation sequencing platforms offer realistic approach to identify and anal-yses whole genome with high throughput, accuracy, scalability in a very short time span. Information obtained can be further used in improving our existing healthcare systems, designing novel and personalized therapeutic modules, making the envi-ronment sustainable and proactively preparing ourselves for future pandemics and outbreaks. This article discusses the various NGS technologies and approaches, their advantages, drawbacks, and futuristic usage in different fields. Though still in nascent stages and marred with flaws, with ongoing advancement, NGS will indeed have promising impacts in the future.

Lean body mass (LBM) is correlated with powerlifting performance in athletes competing in different bodyweight classes. However, it remains unknown whether changes in LBM are correlated with performance changes in powerlifters preparing for a competition. Aim of the study was to investigate the changes in LBM and performance in powerlifters preparing for a competition. Eight male powerlifters (age 31.7±9.8years, height 1.77±0.06m, weight 99.2±14.6kg) and three female powerlifters (age 32.7±16.3years, height 1.54±0.06m, weight 66.6±20.9kg), participated in the study. Athletes followed individualized periodized training programs for 12 weeks aiming to maximize their performance for the national championship. Maximum strength (1-RM) in squat, bench press, and deadlift, body composition, grip strength, anaerobic power, quadriceps’ cross sectional area and vastus lateralis muscle architecture were measured before and after the training period. Significant increases were found after the training period in squat (5.8±7.0%, P

Polycystic Ovary Syndrome (PCOS) is the most common endocrine disorder that affects women of reproductive age representing the primary cause of anovulatory infertility. The nonapeptide oxytocin (OT) plays an important role in cognitive, emotional, and reproductive functions in human beings. Oxytocin receptors are expressed in several body parts including the ovaries. Despite this, the possible role played by oxytocin in symptoms of PCOS is not clear. The present systematic review aimed at understanding, the presence of possible oxytocin level alterations in PCOS, the connection between alterations of OT levels and the symptoms of PCOS, and the effect of oxytocin administration in PCOS. After a systematic search in the principal databases, seven studies, five human and two animal, were included. Most of the studies highlighted the role played by oxytocin in fertility issues related to PCOS. Studies that analyzed oxytocin basal levels in PCOS women agreed that PCOS is associated with a reduction in the serum level of oxytocin. Two studies found that in PCOS the serum levels of oxytocin were lower than healthy controls. One human and one animal study agreed about lower levels of PCOS, confirming a possible implication of a dysfunction of OT, in the pathogenesis of PCOS.

The growing expansion of the economy and population has resulted in an increased inclination towards the utilization of groundwater resources. Conducting a geophysical survey is a widely employed method for subsurface mapping and the detection of groundwater. A geophysical study was conducted in Nanshan township, Huarong County, located in the Hunan province of the South-Central region of China. The investigation involved the utilization of a 2D Electrical Resistivity Imaging technique employing forward and inverse pole-dipole electrode array. A total of six survey lines were established, each with an electrode distance from the nearest measuring point to exceeding 800 m. The maximum current electrode separation was utilized in this setup. The spacing between the electrical resistivity sounding points was established at regular intervals. The findings from the exploration indicate the existence of multiple faults within the surveyed region. The study additionally identified two regions of structural failure, which occurred due to the convergence of faults oriented in different directions. This convergence led to the fracturing of rocks, an increase in water content, and a decrease in resistivity. The findings from the exploration were utilized in the formulation of five verification target boreholes. The results of this study offer significant insights that can inform future investigations into groundwater exploration endeavors within the region.

The temporary immersion system bioreactor named GreenTray®[2], [3]presents advantages over the existing ones. Firstly, there is no need to use forceps to move the shoots or plantlets in or out of the recipient, neither the use of scalpel to divide them. Secondly, the basis of the shoot can remain in the GreenTray® and can sprout again in several cycles of growth. These two characteristics reduce the costs in the process of micropropagation. Besides, shoots or plantlets development is enhanced by the aeration of the recipient, thus enriching with CO2 the recipient atmosphere. The chapter describes and provides images and values of interest in (1) the micropropagation process of some commercial Prunus or Pyrus rootstocks; (2) the plantlet growth under autotrophic conditions; and (2) the inoculation of plants with pathogens that reproduce in vitro the symptoms observed in vivo, using the GreenTray® bioreactor.

(1) The purpose of this study was to compare the percentages of quarterly change for each of the variables analysed (height, weight, body fat percentage and muscle mass) as a function of the quarter in a sample of adolescent football players. (2) The sample consisted of young male football players of different categories belonging to a high-performance football academy, (more than 5 years in football and have spent 1 full year at the academy). (3) Two-way repeated measures ANOVA revealed for the anthropometric variable, P_value

This paper presents MADS (Multi-Agents for Data Science), an innovative and simple open-source multi-agent framework designed for systemic pipeline execution in applied supervised machine learning. By leveraging the capabilities of multi-agent systems (MAS), we introduce a universal approach to optimize and streamline machine learning pipelines. Our framework highlights the differences between various types of agents, such as reinforcement learning (RL) agents and large language model (LLM) agents, and their distinct contributions to the process. While we currently employ LLM agents to automate and enhance machine learning tasks, we acknowledge the potential of incorporating RL agents in future iterations to further improve performance and adaptability. The primary objective is to enhance the efficiency, scalability, and adaptability of supervised learning applications across various domains. This integration addresses the complexity and manual effort typically associated with machine learning workflows, paving the way for more automated, robust, and scalable solutions. Our approach demonstrates significant improvements in task automation, reduced human intervention, and enhanced model performance. The MADS framework, which will soon be available as an open-source implementation, represents a pivotal contribution to the field of machine learning, promising to facilitate broader adoption and collaborative advancement.

Brain aging causes a wide variety of changes at molecular and cellular levels, leading to the decline of cognitive functions and increased vulnerability to neurodegenerative disorders. The research aimed at understanding the aging of the brain has made much progress in recent decades. Technological innovations such as single-cell RNA-sequencing (scRNA-seq), proteomic analyses, and spatial transcriptomic analyses have facilitated the research on the dynamic changes occurring within neurons, glia, and other cells along with their impacts on intercellular communication during aging. In this review, we introduce recent trends of how neurons and glia change during aging and discuss the impact of the brain microenvironment such as the blood-brain barrier (BBB).

In this article we compute many topological indices for the family of Möbius ladder. At first we give general closed form of M-polynomial of this family and recover many degree based topological indices out of it. We also compute Zagreb indices and Zagreb polynomials of this family.

The main inhibitory neurotransmitter in the mammalian brain is 4-aminobutyric acid (GABA). Phthalimide acts as a sodium channel antagonist, one of the finest targets for treating epilepsy is the sodium channel and JNK kinase activity is inhibited to treat epilepsy. a novel compound with multiple targets of action for the treatment of epilepsy also anti-oxidant activity has been designed. The compounds are designed in two series aldehydes and aniline. Docking of all the designed compounds has been done with the suitable protein GABA-AT, sodium channel, JNK protein, and anti-oxidant from protein bank. QSAR was done for constructing many linear regression models. In combination with the developed Docking and QSAR outcomes, ADMET has been performed for the active compounds. The result shows that 11 of the compounds have excellent binding energy in docking with all the receptors and also have good QSAR results and follow the ADMET. The structural understanding of human GABA-AT inhibition was obtained from molecular dynamics simulation studies for compound no. 11 at 5 nanoseconds. Synthesis and pharmacological activity also suggest that the designed compound no.11 be considered the best Novel Compound.

Efficient gene transfer and expression tool is lacking for shrimps and shrimp cells. To solve this, this study has developed a shrimp DNA virus-mediated gene transfer and expression system, consisting of insect Sf9 cells for viral packaging, shrimp viral vector of pUC19-IHHNV-PH-GUS and baculoviral vector of Bacmid or Bacmid-VP28 encoding shrimp WSSV envelope protein VP28. The pUC19-IHHNV-PH-GUS vector was constructed by assembling the genomic DNA of shrimp infectious hypodermal and hematopoietic necrosis virus (IHHNV), which had shortened inverted terminal repeats, into pUC19 backbone, and then an expression cassette of baculoviral polyhedron (PH) promoter-driven GUS reporter gene was inserted immediately downstream of IHHNV for proof-of-concept. It was found that the viral vector of pUC19-IHHNV-PH-GUS could be successfully packaged into IHHNV-like infective virions in the Sf9 cells, and gene transfer efficiency of this system had been evaluated and verified in three systems of Sf9 cells, shrimp hemolymph cells and tissues of infected shrimps, but GUS expression could be detected only in the cases when the viral vector was co-transfected or co-infected with a baculovirus of Bacmid or Bacmid-VP28 due to the Bacmid-dependence of PH promoter. Moreover, the packaging and infection efficiencies could be significantly improved when Bacmid-VP28 was used instead of Bacmid.

Models of subsurface structures are important for successful deposit exploration but are challenged by the need to integrate data from different geophysical methods. In the present study, we evaluated a method of joint inversion in which audio-magnetotelluric (AMT) and dual frequency induced polarization (DFIP) data sets are inverted simultaneously to produce a consistent 2D resistivity model to show a clear image of subsurface structures. To achieve the objectives, we conducted AMT and DFIP surveys first on the same survey line within the Dongjun lead-zinc deposit in inner Mongolia by developing 31 AMT survey sites with an interstation separation of 40 m on a 1440 m survey track and operated in fifty-three frequencies in the range 1–10,400 Hz to record the resistivity distribution of subsurface to depths exceeding 800 m. The same survey setup up was applied to the DFIP method by utilizing the SQ-3C model with a pole-dipole array configuration and conducted measurements at frequencies of 4 Hz and 4/13 Hz. We first separately inverted AMT and DFIP measurements. The two-dimensional (2D) model obtained from AMT data revealed distinct low resistivity anomalies in the middle of the 2D inversion model. In contrast, the DFIP inversion model showed a high resistive body in the same region. In response to the discrepancies observed in the separate 2D inversion models, we implemented a joint inversion for both the AMT and DFIP datasets. The joint inversion resistivity model shows surficial conducting bodies and a high conductive body along the profile with relatively high Percent Frequency Effect (PEF) indicating high chargeability. The final joint inversion resistivity model clearly images the large silica alteration zone and the Pb-Zn mineralization. This study demonstrates the feasibility of a joint inversion methodology and highlights the value of integrating geophysical methods through joint inversion for enhanced characterization and exploration of lead-zinc ores.

Two new dimacrolide sesquiterpene pyridine alkaloids (DMSPAs), dimacroregelines A (1) and B (2), were isolated from the stems of Tripterygium regelii. The structures of both compounds were characterized by extensive 1D and 2D NMR spectroscopic analyses, as well as HRESIMS data. Compounds 1 and 2 are two rare DMSPAs possessing unique 2-(3′-carboxybutyl)-3-furanoic acid units forming the second macrocyclic ring, representing the first example of DMSPAs bearing an extra furan ring in their second macrocyclic ring system. Compound 2 showed inhibitory effects on the proliferation of human rheumatoid arthritis synovial fibroblast cell (MH7A) at a concentration of 20 μM.

The clinical features of increasing muscle weakening are shared by a diverse set of illnesses known as muscular dystrophies. In early childhood, males with Duchenne muscular dystrophy (DMD) exhibit proximal muscle weakening and calf enlargement, making it the most frequent X-linked disease of muscular dystrophy in children. Development of motor skills is typically delayed, and wheelchair confinement eventually leads to early death from heart or lung problems. In terms of function, ambulation, quality of life, and life expectancy, treatment approaches like corticosteroid therapy and intermittent positive pressure breathing have improved. This is a case report of a 6-year-old kid who had early ambulatory stage Duchenne Muscular Dystrophy and complained to the neuro-physiotherapy department about frequent falls, walking difficulties, and dyspnea when walking. Other grievances included being unable to get off the ground and having trouble ascending stairs. He had physiotherapy and dynamic neuromuscular stabilization for his complaints. The main goals of treatment were educating the family, respiratory training, preventing ankle plantar flexors, maintaining strength, balance and gait training.

In an era characterized by technological disruption and unprecedented challenges posed by the COVID-19 pandemic, this scholarly investigation explores the role of Artificial Intelligence (AI) in shaping Leadership Dynamics in Higher Education Institutions (LDHE) within the specific socio-cultural and regulatory environment of China. Utilizing Structural Equation Modeling (SEM) as operationalized through the SMART_PLS software, this research harnessed data from a robust sample of 381 key stakeholders in China higher education. The study's empirical findings indicate a noteworthy impact of AI-informed decision-making processes on LDHE, which was further mediated by the variable of AI Literacy among leadership. Moreover, the consequences of the ongoing pandemic served as a moderating factor in this relationship. These nuanced outcomes not only contribute to the theoretical discourse surrounding educational leadership and technological integration but also provide actionable insights for policy formulation and institutional strategies in an increasingly complex educational landscape.

To address the problems of insufficient semantic fusion between text and questions and the lack of consideration of global semantic information encountered in machine reading comprehension models, we proposed a machine reading comprehension model called BERT_hybrid based on BERT and hybrid attention mechanism. In this model, BERT is utilized to separately map the text and questions into the feature space. Through the integration of Bi-LSTM, attention mechanism, and self-attention mechanism, the proposed model achieves comprehensive semantic fusion between text and questions. The probabilities distribution of answers is computed using Softmax. Experimental results on the public dataset DuReader demonstrate that the proposed model achieves improvements in BLEU-4 and ROUGE-L scores compared to existing models. Furthermore, to validate the effectiveness of the proposed model design, we analyze the factors influencing the model’s performance.

Plant activators have emerged as promising alternatives to conventional pesticides for crop disease manage-ment due to their unique mode of action. By priming the plant's innate immune system, these compounds can induce systemic acquired resistance against a broad spectrum of pathogens without directly inhibiting their proliferation. Key advantages of plant activators include prolonged defense activity, lower effective dosages, and negligible risk of developing pathogen resistance. Among the various defensive pathways tar-geted, the salicylic acid (SA) signaling cascade has been extensively explored, leading to the successful devel-opment of commercial activators like benzothiadiazole for widespread application in crop protection. While the action sites of many SA-targeting activators have been preliminarily mapped to different steps along the pathway, a comprehensive understanding of their precise mechanisms remains elusive. This review provides a historical perspective on plant activator development and outlines diverse screening strategies employed across multiple levels, from whole-plant bioassays to molecular and transgenic approaches. We expound on the intricate components, biological relevance, and regulatory circuits governing the SA pathway, while criti-cally examining the structural features, bioactivities, and proposed modes of action of classical activators such as benzothiadiazole derivatives, salicylic acid analogs, and other small molecules. Insights from field trials as-sessing their practical applicability are also discussed. Furthermore, we highlight the current status, challenges, and future prospects in the realm of SA-targeting activator development globally, with a focus on recent en-deavors in China. Collectively, this comprehensive review aims to synthesize existing knowledge and provide a roadmap for future research toward developing more potent and mechanistically understood plant activa-tors that fortify crop immunity against disease.

Carnivore protoparvovirus 1 (CPPV-1) is a DNA virus causing gastrointestinal disease and immunosuppression in various terrestrial carnivores. Domestic dogs and cats are considered the primary CPPV-1 reservoirs. The habitat overlaps of wild carnivores and free-roaming dogs increases the threat of CPPV-1 transmission between them. This study explored the CPPV-1 distribution among wild carnivores through PCR screening and compared the DNA sequences of the partial capsid protein (VP2) between wild and domestic carnivores. In total, 181 samples were screened for the CPPV-1 VP2 gene, including 32 masked palm civets (Paguma larvata), 63 Chinese ferret badgers (Melogale moschata), and 86 crab-eating mongooses (Herpestes urva), from 2015 to 2019 in Taiwan. The average prevalence of CPPV-1 was 17.7% (32/181), with the highest prevalence in masked palm civets (37.5%). In addition, a masked palm civet was coinfected with two CPPV-1 strains. Among the 33 partial VP2 gene sequences, 23 were identical to sequences amplified from domestic dogs and cats in Asia and the remaining 10 were identified for the first time. This study demonstrated that CPPV-1 has circulated between domestic and wild carnivores in rural Taiwan. Therefore, further population control and health management of free-roaming domestic carnivores are recommended.

Danyore Valley area is a new prospect of copper-gold mineralization in the Gilgit-Baltistan province, Kohistan terrane, northern Pakistan. The mineralization is Cu-Au vein-type, localized within quartz veins and controlled by a fracture system mainly trending NW and NE. The host units belong to the Ladakh-Kohistan arc terrane, which covers northern Pakistan and north-western India and mainly comprises Precambrian basement units, Paleozoic to Cenozoic magmatic rocks, and sedimentary strata. The mineralized wall rocks consist of Mesozoic gabbro and diorite, which have undergone an intensive hydrothermal alteration. The study area, Danyore Valley, has yet to be explored. The geological background and mineralization type in literature are scarce. Moreover, the tectonic setting, petrogenesis, age, and magmatic evolution of the gabbro-diorite hosting unit still need to be better understood. Furthermore, the sources of metals and mineralized fluids and the types of mineralization and alteration are also unexplored. This research's contribution presents the field investigation, microscopic observations, whole rock geochemistry (major, trace, and REE), mineral analysis (EPMA), in situ LA–ICP–MS zircon U–Pb age dating, and zircon trace elements data for Danyore Valley Cu-Au prospect of Kohistan Batholith. The current research work's objectives are to (a) constrain the emplacement ages of the Danyore Valley host rocks, (b) determine the petrogenesis and tectonic environment of the gabbro-diorite wall rocks, and (c) identify the mineralization style and alteration patterns of Cu-Au occurrences. The U-Pb isotopic data of studied zircons from Danyore Valley diorite specimens yielded concordia ages from 111.60 ± 0.90 Ma to 112.18 ± 0.74 Ma. Correspondingly, the gabbro rock sample displayed a concordia age of 110.21 ± 0.99 Ma, indicating the crystallization time of the host bodies is mainly the early cretaceous period (∼110 Ma). The findings of this study reveal that the calc-alkaline affinity and arc-like geochemical characteristics of the gabbro and diorite rocks have been characterized by a significant enrichment in large-ion lithophile elements and an apparent depletion in high-field strength elements. The parent magma probably originated from a partial melting process of mantle depletion, and geochemical traits are characteristic of magmas associated with subduction zones. The Danyore Valley area of Kohistan terrane is defined by the existence of several mineralized quartz veins, which are mainly sulfide assemblages. The sulfide ore is mainly comprised of chalcopyrite, pyrite, and bornite, with a smaller amount of covellite and sphalerite and significant traces of gold, which are distributed mainly in sulfides. Copper and gold mineralization of Danyore Valley is associated with phyllic, propylitic, and carbonatization alteration assemblages. Metal-rich quartz veins exhibit a spatial correlation with diorite and gabbro rocks. The discovery of several surface Cu-Au vein-type mineralized areas accompanying outcrops of copper supergene enrichment at the Danyore Valley prospect is significant evidence (predictor patterns) of porphyry-style deposits in the Gilgit district, Kohistan terrane, northern Pakistan. This work also advocates the importance of the Danyore Valley prospect and Kohistan Batholith region for further detailed geological studies.

As companies increasingly undergo digital transformation, the role of talent management pro-cesses becomes pivotal in enhancing overall organizational performance. The research addresses the significance of talent management in corporate digital transformation, examining whether variations in the digitalization of these processes can be attributed to company size. A qualitative approach was employed, utilizing a questionnaire, collecting responses from 202 organizations across diverse sectors. Findings reveal disparities in digitalization throughout the talent man-agement process, with pronounced presence in the attracting, selecting, and rewarding phases, but diminishing in deployment and development, further declining in planning. A positive cor-relation between company size and adoption of specific digital platforms was observed. Larger enterprises exhibit greater utilization of digital platforms in talent deployment and development. Moreover, corporate communication tools are consistently utilized in the rewarding phase, irre-spective of company size. These findings offer practical insights for organizations to optimize their digitalization strategies based on their scale, thereby contributing to more effective and tailored digitalization endeavors. The uniqueness of this research lies in its exploration of the in-fluence of company size on the digitalization of talent management processes and its potential to explain variations across different stages of these processes.

Neuron degeneration is the most common old age complications worldwide. Alzheimer's disease (AD) is one of the most common neurodegenerative condition with limited drug options and significant adverse effects. Hence, there is a growing interest in exploring natural products for their potential pharmacological activities against AD. This study investigates the efficacy of Verbesina encelioides flower extract (VFE) in alleviating neurobehavioral damage induced by Scopolamine in rat mimicking AD model. GC-MS analysis showed that V. encelioides flower extract is rich in carotenoids like spirilloxanthin. Various behavioural models were used to assess the rats' learning and memory capabilities. Additionally, biochemical tests were conducted on the AD rat models to evaluate oxidative stress in the brain, including superoxide dismutase (SOD), nitric oxide (NO), reduced glutathione (GSH), and anti-acetylcholinesterase (AChE) enzyme assays. Findings from this study suggest that the VFE significantly improved the rats' cognitive aptitude and alleviated them from oxidative stress by reducing free radical generation. Based on the results obtained from GC-MS analysis, in silico interaction analysis of gingkolide A and spirilloxanthin with acetylcholinesterase was carried out. In summary, this study suggests that V. enceloides flower extract improves learning abilities and mitigates cognitive deficits caused by scopolamine. Thus V. enceloides could be potentially seen as natural therapeutic intervention against neurodegenerative disorders likes Alzheimer’s disease and dementia.

Excessive oxidative stress and exercise-induced fatigue reduce physical performance and can lead to dysfunction in antioxidant systems within muscular and hepatic tissues. Integrating natural substances with exercise may mitigate fatigue via anti-oxidant effects. This study aims to compare and evaluate the effects of exercise and supplementation with Sundarbans honey vs energy drinks on the strength, anxiety physiological profiles, and hepatic antioxidant capacity in mice undergoing extraneous exercise and fatigue. Forty-eight four-week-old Swiss albino mice were randomly assigned to one of eight groups: (1) Control, (2) Speed™ (Sp), (3) Royal Tiger™ (RT), (4) Sundarbans Honey (SH), (5) Exercise (Ex), (6) Exercise + Sundarbans Honey (Ex+SH), (7) Exercise + Speed™ (Ex+Sp), and (8) Exercise + Royal Tiger™ (Ex+RT). Supplements were administered via oral gavage: Sp (2.5 ml/kg BW), RT (2.5 ml/kg BW), and SH (1 g/kg BW), four times a week for 60 days. Mice in the Ex, Ex+SH, Ex+Sp, and Ex+RT groups underwent daily swimming and running. The strength, fatigue, anxiety levels, lipid profiles, and antioxidant biomarkers were evaluated post-treatment. The SH, Ex, and Ex+SH groups exhibited significantly enhanced physical performance (p

Ambulatory heart rate (HR) monitors that acquire electrocardiogram (ECG) or/and photoplethysmographm (PPG) signals from the torso, wrists, or ears are notably less accurate in tasks associated with high levels of movement compared to clinical measurements. However, reliable estimation of HR can be obtained through data fusion from different sensors. These methods are especially suitable for multimodal hearable devices, where heart rate can be tracked from different modalities, including electrical ECG, optical PPG, and sounds (heart tones). Combined information from different modalities can compensate for single source limitations. In this paper, we evaluate the possible application of data fusion methods in hearables. We assess data fusion for heart rate estimation from simultaneous in-ear ECG and in-ear PPG, recorded on eight subjects while performing 5-minute sitting and walking tasks. Our findings show that data fusion methods provide a similar level of mean absolute error as the best single-source heart rate estimation but with much lower intra-subject variability, especially during walking activities. We conclude that data fusion methods provide more robust HR estimation than a single cardiovascular signal. These methods can enhance the performance of wearable devices, especially multimodal hearables, in heart rate tracking during physical activity.

The integration of AI in educational settings, particularly through Large Language Models (LLMs), is accelerating, reshaping pedagogical approaches due to students' interactions with new learning tools. This study assesses the impact of generative AI on the educational experiences of computer and data science students at the Center for Informatics, University of Paraíba (CI/UFPB), Brazil. Through Exploratory Factorial Analysis (EFA) of five psychometric scales, the research examines students' acceptance of LLMs, their associated burnout levels, technology anxiety, and the prevalence of metacognitive and dysfunctional learning strategies associated with LLMs. Results indicate significant adoption of AI technologies among students, accompanied by a low incidence of technology anxiety, manifesting as fears of losing jobs to AI. However, a significant correlation was observed between academic burnout and dysfunctional learning strategies, which could likely be attributed to the rigorous academic environment. Additionally, the employment of metacognitive strategies in conjunction with LLMs reflects an advanced learning approach, yet challenges with functional learning strategies persist. This study contributes to the discourse on AI in education, highlighting the need for educational frameworks that support effective AI adoption while addressing the psychological demands on students.

Despite ongoing efforts, the relationship between groin strength and injury remains unclear. The challenge of accurately predicting injuries presents an opportunity for researchers to develop pre-vention strategies to reduce the occurrence of such injuries. Consequently, this issue requires further investigation to obtain insights into effective mitigation strategies. In 120 male soccer players the maximum isometric strength of the hip muscle groups was measured, and the strength ratios were calculated. Previous injury and anthropometric data were registered. Injury data were collected following the FIFA/UEFA consensus. The K- Nearest Neighbour (k-NN), was used to predict the incidence of injury, while the significant predictive variables of the k-NN algorithm were fitted into a multivariate logistic regression model (LR) to analyze the likelihood of players sustaining a groin injury. The LR model determined two variables as significant predictors of groin injury. Players were less likely to sustain a groin injury by 76% for each decrease of the Adductors/Abductors isometric strength ratio in the non-dominant limb (OR = 0.238, CI 95%= [(0.098-0.572]). Players with a history of previous injury had a 67% greater risk of sustaining an injury (OR = 0.333, CI 95%= [(0.1068-1.038]). Isometric hip adductor and abductor strength im-balances of the non-dominant lower limb and a history of previous injury were risk factors for groin injury in soccer players.

In the wake of globalization and the revolutionary impact of Artificial Intelligence (AI), literature and language education play a pivotal role in preparing the next generation to navigate an ever-changing world. This reflective concept paper explores the profound insights shared by educators, focusing on literature and language education amidst globalization and AI. Drawing on interviews and observations, teachers' reflections reveal the enduring value of literature in shaping young minds, fostering critical thinking, and promoting empathy. Additionally, they emphasize the importance of embracing multilingualism and cultural diversity to equip students for an interconnected world. In the face of challenges, educators showcase their resilience and adaptability, harnessing technology, particularly AI-driven tools, to foster future-ready learners. Identifying gaps and implications in literature and language education, this paper sets the stage for collective efforts among stakeholders to shape the future of education. Ultimately, teachers hold the key to nurturing a generation capable of embracing the complexities of the AI-driven global landscape with confidence and compassion, empowering students as transformative agents in a rapidly changing world.

Wearable Biosensor Technology (WBT) has emerged as a transformative tool in the educational system over the past decade. This systematic review encompasses a comprehensive analysis of WBT utilization in educational settings over a 10-year span (2012-2022), highlighting both the evolution of this field and its integration to address challenges in education by integrating technology to solve specific educational challenges, such as enhancing student engagement, monitoring stress and cognitive load, improving learning experiences, and providing real-time feedback for both students and educators. By exploring these aspects, the review sheds light on the potential implications of WBT for the future of learning. A rigorous and systematic search of major academic databases, including Google Scholar and Scopus, was conducted in accordance with PRISMA guidelines. Relevant studies were selected based on predefined inclusion and exclusion criteria. The articles selected were assessed for methodological quality and bias using established tools. The process of data extraction and synthesis followed a structured framework. Key findings include the shift from theoretical exploration to practical implementation with the EEG being the predominant measurement, aiming to explore mental states, physiological constructs, and teaching effectiveness. Wearable biosensors are significantly impacting the educational field, serving as an important resource for educators and a tool for students. Their application has the potential to transform and optimize academic practices through sensors that capture biometric data, enabling the implementation of metrics and models to understand the development and performance of students and professors in an academic environment, as well as to gain insights into the learning process.

Reviewed are recent efforts leading to chemo-enzymatic syntheses of strongly fluorescent ribosides of nucleobase analogs, potentially applicable in analytical biochemistry and cell biology. Described are syntheses and properties of fluorescent purine, 8-azapurine and etheno-purine ribosides, obtained using various types of the purine nucleoside phosphorylase (PNP) as catalysts of ribosylation, and -ribose-1-phosphate (r1P) as a second substrate. In several instances, the ribosylation sites were different than the canonical purine N9. Some of the obtained ribosides show fluorescence yields close to 100%. Their main applications are assays of PNP, nucleoside hydrolases, and other enzyme activities both in vitro and, possibly, within the living cells, using fluorescence microscopy.

In this article, we describe a simple procedure for evaluating the sterility of nutrient media using a shear-horizontal surface acoustic wave (SH-SAW) biosensor. We used the SH-SAW biosensor platform to monitor the time-dependent phase responses of the material for the media that binds to a monolayer of 3-mercaptopropanyl-N-hydroxy succinimide on the biosensor surface. Increases in the phase shift less than 50% of the starting phase shift recorded 180 minutes after the sterilization indicate a successful sterility test of the media. Our devices were then applied to sterility testing using a viable Escherichia coli (E. coli) K-12 solution to confirm our hypothesis. Filtered LB Broth was the negative control, and a 24-hour culture of E. coli was the positive control. Before testing, the cell solution was pelleted, the media decanted and then replaced with a 1x phosphate-buffered saline solution (1x PBS). Since we know that the N-hydroxysuccinimide residues will bind to amine groups, only in cases where microbial species are present will the surface binding increase greater than 50%. We confirmed our hypothesis using SH-SAW biosensors and overnight E. coli cultures. The sensitivity for our 250 MHz quartz SH-SAW sensors was calculated based on the response from the E. coli K-12 solution over the linear dynamic range, which appears to be 2x104 – 2x107 CFU per ml and has a sensitivity of S = 1.655x105 o m2 Kg-1. The limit of detection (LOD) for these sensors was calculated to be approximately 2x10-9 grams (g) which is estimated to be approximately 2,000 Escherichia coli (E. coli) K-12 cells. However, the sensitivity and insertion loss remained approximately unchanged before and after coating the sensor with 3,3'-Dithiobis(succinimidyl) Propionate (DSP).

Blockchain technology (BCT) has the potential for sustainable development, enhancing business efficiency, reducing costs, and strengthening data security. Despite its potential, adoption among small and medium-sized enterprises (SMEs) is low due to the need for significant changes in technology infrastructure and the challenge of interoperability. A cross-sectional survey was done with 226 Hong Kong SMEs. The PLS-SEM results highlighted favorable transformation conditions as the most critical factor for SMEs considering the adoption of BCT. These conditions address both internal and external readiness for adopting the disruptive strategy. Other contributing factors to BCT adoption include trust in BCT developers, perceived usefulness and ease of use, government support, and perceived security. The research results contributed to the literature on disruptive technology acceptance, adoption, transformation conditions, technology readiness, and SMEs’ technology adoption. Government-supported policies and initiatives can promote BCT adoption, including educational programs, case studies, and resources for readiness. Financial support and regulatory frameworks can further encourage adoption. BCT developers can demonstrate the value of their systems, effectively communicate potential ROI and cost savings, and provide user-friendly interfaces to increase SMEs’ intention to adopt BCT.

Successful geophysical exploration works in Gucheng-Yaxi area located in Gaochun District, Jiangsu province, China, have been limited partly due to complex geological condition of the area and high artificial noise in data acquired using electrical and electromagnetic methods. In this work, we deployed the new anti-interference spread spectrum induced polarization method (SSIP) and audio magnetotellurics (AMT) method to detect a copper-polymetallic deposit in the area. Two-dimensional (2D) inversion results at Gucheng-Yaxi Area revealed a high chargeability anomalous zone on SSIP profile that coincided with a zone of moderate resistivity located between two resistor bodies on AMT profile. A follow up 1200 meters drill hole was established at this high chargeability-moderate resistivity zone which encountered polymetallic (copper, lead, zinc, gold and silver) mineralization at the depth ≥ 400 m. Drill hole data analysis showed that mineralization occurs interspaced in marble rock mass at varies depth. Furthermore, several low resistivity-weak chargeability sections were revealed and inferred attributed to Cretaceous sediments and faults. These faults are thought to have played critical role in the polymetallic mineralization genesis. In summary, this work demonstrated the successful of application of SSIP and AMT at detecting a metallic deposit in an area with high artificial noise. Hence the geophysical prospection potential of Gucheng-Yaxi area is great.

Citizen science substantially contributes to large-scale biodiversity monitoring and the enhancement of public literacy. While both of the contributions largely depend on the public’s self- regulated learning. In this study, we employed a mix- method approach, incorporating both a questionnaire survey of 133 participants and interviews with 12 volunteers, aiming to explore the feature of self- regulated learning in citizen science, as well as identify the main factors impacting it. The volunteers are all different ages, from different jobs, with varying educational backgrounds. The findings revealed that the educational background of volunteers did not significantly impact their self-regulated learning. However, an increased frequency of participation was linked to higher levels of self-regulated learning. Furthermore, achievement goal orientation mediates the prediction of self-regulation by scientific epistemology. These insights underscore the importance of enhancing citizen science's impact on scientific literacy by fostering self-regulated learning among participants. This can be achieved through explicit instruction in scientific epistemology and by fostering a sense of achievement to boost achievement goal orientations. Additionally, our study advocates for the promotion of social interaction between students and out- of- school citizen scientists in school-based citizen science projects. The main innovation of this study is to consider volunteers as learners, not merely as contributors of data.

This article analyzes the Franco-Spanish invasion of Vietnam from 1858 to 1860. Research is based on documents such as correspondence, reports, archives and diplomatic treaties as well as monographs from the time France intended to invade Vietnam through missionary activities until the end of the Franco-Spanish invasion. The article focuses on three basic issues that are the causes of the alliance, the evolution of the French and Spanish coalition invasion in Vietnam and its impact on stakeholders. The research results on the Franco-Spanish invasion of Vietnam indicated that the invasion carried out by this alliance was more special than that of the other French coalitions before. The invasion was based on an alliance without any commitment to the interests and responsibilities of the parties. The goals of France and Spain in this invasion were different. That led to conflict between France and Spain during the invasion and the fall of the alliance. France achieved its goal through an invasion that turned Vietnam into a colony, while Spain had barely achieved its desire to have commercial and missionary interests in the area.

As modern systems are becoming more complex their control strategy cannot longer relay only on measurement information that usually comes from probes but also from mathematical models. Those systems models can lead to unbearable computation times due to their own complexity, turning the control process non-viable, which leads to the implementation of surrogate models that enable to achieve estimates within acceptable time to take decisions. A control trained with Deep Reinforcement Learning algorithm, using a Physics-Informed Neural Network to obtain the temperature map on the following time step, replaces the need of running Direct Numerical Simulations. On this work we considered an 1D heat conduction problem, which temperature distribution feeds a control system to activate a heat source aiming to obtain a constant, previously defined, temperature value. With this approach, control training becomes much faster without the need of performing numerical simulations or laboratory measurements, as well the control is taken based on Neural Network enabling its implementation on simple processors to edge computing.

This study explores the public library service evaluation domain through user-generated content on Google Maps, highlighting digital feedback's significant yet underexplored potential in understanding public library patronage across Taiwan's six major cities. Utilizing a mixed-methods research design, this study integrates Google Maps review content analysis with Social Network Analysis to delineate public perceptions and identify areas for service enhancement in public libraries. It innovatively leverages personal experiences extracted from over 60,000 Google Maps reviews to evaluate public library services in cities such as Taipei, New Taipei, Taoyuan, Taichung, Tainan, and Kaohsiung. The research taps into the National Library of Taiwan's National Library Statistics System to provide a robust analysis of library performance and user satisfaction, offering a novel perspective by emphasizing user-centric feedback from Google Maps as a primary data source. This approach provides quantitative data on library usage and geographic distribution and enriches our understanding of the qualitative experiences of library users. In analyzing the keywords from Google Maps reviews of public libraries, we categorize and interpret these under the three core LibQUAL+ dimensions—Affect of Service, Information Control, and Library as Place. The findings expose variances in perceived service quality among the cities, with Kaohsiung and Taichung receiving the highest accolades for service satisfaction. Simultaneously, the study identifies potential areas for improvement, particularly in cities with lower satisfaction ratings like Taipei. This personalized feedback illustrates the intimate relationship between public libraries and their communities, offering invaluable insights for policymakers and library management to enhance service delivery and user experience.

Epithelial ovarian cancer (EOC) has not significantly benefited from advances in immunotherapy, mainly because of the lack of well-defined actionable antigen targets. Using proteogenomic analyses of primary EOC tumors, we previously identified 91 aberrantly expressed tumor-specific antigens (TSAs) originating from unmutated genomic sequences. Most of these TSAs derive from non-exonic regions, and their expression results from cancer-specific epigenetic changes. The present study aimed to evaluate the immunogenicity of 48 TSAs selected according to two criteria: presentation by highly prevalent HLA allotypes and expression in a significant fraction of EOC tumors. Using targeted mass spectrometry analyses, we found that pulsing with synthetic TSA peptides leads to a high-level presentation on dendritic cells. TSA abundance correlated with the predicted binding affinity to the HLA allotype. We stimulated naïve CD8 T cells from healthy blood donors with TSA-pulsed dendritic cells and assessed their expansion with two assays: MHC-peptide tetramer staining and TCR Vβ CDR3 sequencing. We report that these TSAs can expand sizeable populations of CD8 T cells and, therefore, represent attractive targets for EOC immunotherapy.

Traumatic Brain Injury (TBI) is one of the leading causes of death and disability worldwide. Patient treatment and management pose a challenge for healthcare systems. The prognosis of these patients may be influenced by factors such as sex. This study aims to describe the clinical parameters of patients hospitalized in the Intensive Care Unit (ICU) of a Spanish hospital due to Trauma Brain Injury and to establish differences based on sex. Methodology: An observational, cross-sectional, and analytical study was conducted from March 2015 to December 2019. All patients admitted to the ICU during this period who presented isolated significant Traumatic Brain Injury, defined as an abbreviated injury scale (AIS) ≥ 3, were included. Data on baseline characteristics, mechanism of injury, substance use, and acute management in the prehospital and hospital stages (including the need for hospitalization) were recorded. A descriptive and in-ferential analysis was conducted using the chi-square test. Results: A total of 950 patients were ultimately included. The majority of the patients were men (723) with a mean age of 45.16 (± 17.55). There were statistically significant differences in terms of the mechanism of injury (p

Background and Objectives: Cancer as the second leading cause of death in the United States poses a huge healthcare burden. Barriers to access to advanced therapies influence the outcome of cancer treatment. In this study, we examined whether insurance types affect the quality of cancer clinical care regarding access to an important monoclonal antibody, ramucirumab. Materials and Methods: Data for 13,340 cancer patients with Purchased or Medicaid insurance from the All of Us Database were collected for this study. The Chi-square test of proportions was employed to determine the significance of patient cohort characteristics and ramucirumab usage between Purchased and Medicaid insurance groups. The independent t-test was utilized to assess the influences of other determinants on insurance types. Results: Cancer patients who are African American, with lower socioeconomic status, or with lower educational attainment are more likely to be insured by Medicaid. Analysis of survey questions demonstrated the relationship between income and education level with insurance type as Medicaid cancer patients were less likely to receive primary care and specialist physician access and more likely to request lower cost medications. In addition, those with Medicaid insurance were identified to have poorer access to expensive therapeutics like ramucirumab compared to those with Purchased insurance.  Conclusions: The inequities of the US healthcare system are observed for cancer patient care; access to physicians and therapeutics are highly varied and dependent on insurance types. Socioeconomic status determines insurance type, which unfortunately generates a significant impact on cancer treatment and disease outcome.