Earticle

Tectona grandis (teak) is one of the most important timber species worldwide and India is one of the major teak growing countries. Though some volume equations were developed for teak in India but the models developed were neither evaluated using robust statistical criteria nor validated. Hence, the objective of this study was to develop statistically tested appropriate volume equation to predict total wood volume (over- and under-bark) for teak trees in Gujarat. A total of 41 trees with age varying from 15 to 33 years and diameter at breast height (dbh) from 7.3 to 30.8 cm were felled for the purpose. Linear and non-linear equations were used to model the relationship of the total wood volume with respect to dbh and total height. The equations tested mostly fitted well to the data. Model evaluation and validation indicated that models should be calibrated with local data for greater accuracy in the prediction.

Due to the low efficiency and poor accuracy of current college teaching intelligence evaluation methods, an improved method is proposed. Firstly, an improved apriori (IApriori) algorithm is utilized to filter evaluation indexes and establish a teaching quality evaluation indicator system. Secondly, considering the high complexity and low accuracy of the backpropagation neural network (BPNN), principal component analysis (PCA) is taken to reduce the input data's dimension. An improved sparrow search algorithm (ISSA) is simultaneously utilized to optimize the parameters of BPNN. Finally, a PCA-ISSA-BPNN teaching intelligence evaluation model is constructed. The experiments validated that when the number of transactions was 1,000, the IApriori only took 0.32 seconds to run. While the number of projects was 11, IApriori ran in 15.28 seconds. The evaluation accuracy of the PCA-ISSA-BPNN model reached 99.05%, the F1 value was 96.43%, the recall was 97.26%, and the AUC was 0.981. The above data show that IApriori has a higher efficiency in data mining and can more effectively screen evaluation indicators. This research method can effectively and accurately evaluate teaching quality, and has a positive impact on promoting student development, advancing teaching reform, and improving teaching quality.

Coordination plays a critical role in basketball training, significantly influencing athletes' performance in actual games. To enhance the overall technical and tactical application level of Liaoning Petrochemical University women's basketball players, this study investigates the evaluation of training coordination. Because traditional backpropagation (BP) neural network evaluation methods exhibit low accuracy, a radial base function (RBF) evaluation prediction model based on cooperative game theory is proposed. An evaluation index system for the training coordination of women's basketball players is established to calculate the weights of each index and rank their importance, and the RBF neural network is utilized for evaluation and prediction. Using actual training data from the university's female basketball players, the study analyzes balance, reaction ability, agility, and processing speed during training. Simulation experiments demonstrate that the proposed method achieves considerable accuracy, validating its effectiveness. This provides a robust technical tool for real-time monitoring of training outcomes.

Technological substitution is the process by which a radical technology replaces the dominant technology in an industry. The processes of diffusion and substitution have been modeled extensively (Technology & innovation, 2010). However, the formulation of classical quantitative models encompasses only part of the theoretical space. These models impose many simplified constraints to the achievement of analytical resolution. The interior design organization needs to establish a set of technical system requirements by describing the scope of the accessibility needs of the organization against current technology use. Because of complicated design resources and ongoing advances in design technologies, design systems face the challenge of prioritizing new technologies for supporting. The problem is small design organization administration often displays a lack of concern toward the evaluation of technology integration. In this paper, I will identify the influence of a design organization's technology, and predict how future technology will inform, support, and potentially hinder productivity, culture, and work satisfaction within a design organization in the industry. In addition, I will use current design organizational behavior and leadership models to support my predictions. Finally, I will examine a proven approach to assist designers with evaluating technology integration in interior design organization. The goal is to develop a high quality, professional development scorecards for the evaluation. I will conduct both the evaluation of technology integration and CRM performance evaluation is recommended to assess the effectiveness of technology integration. Therefore, the evaluation of integration technologies oriented design hold the promise of solving the organization application integration challenge. The evaluation of integration technology is a significant pattern for processing such a vision. The careful selection of an integration technology for this purpose is crucial in contributing toward the success of such an interior design organization endeavor.

The modern market is highly competitive. It has progressed from traditional competition between enterprises to competition between supply chains. To ensure that enterprise can form the best strategy consistently, it is necessary to evaluate the trust of other enterprises in the supply chain. First, this paper analyzes the background and significance of supply chain trust research, analyzes and expounds on the qualitative and quantitative methods of supply chain trust evaluation, and summarizes the research in this field. Analytic hierarchy process (AHP) is the most frequently used method in the literature to evaluate and rank criteria through data analysis. However, the input data for AHP analysis is based on human judgment, and hence there is every possibility that the data may be vague to some extent. Therefore, in view of the above problems, this study improves the global trust method based on chain iteration. The improved global trust evaluation method based on chain iteration is more flexible and practical, hence, it can more accurately evaluate supply chain trust. Finally, combined with an actual case of Zhaoxian Chengji Food Co. Ltd., the paper qualitatively analyzes the current situation of supply chain trust management and effectively strengthens the supervision of enterprises to cooperative enterprises. Thus, the company can identify problems on time and strategic adjustments can be implemented accordingly. The effectiveness of the evaluation method proposed in this paper is demonstrated through a quantitative evaluation of its trust in downstream enterprise A. Results suggest that the subjective preferences of and historical transactions together affect the final evaluation of trust.

Altmetrics is an emergent research area whereby social media is applied as a source of metrics to evaluate scientific impact. Recently, the interest in altmetrics has been growing. Traditional scientific impact evaluation indictors are based on the number of publications, citation counts and peer reviews of a researcher. As research publications were increasingly placed online, usage metrics as well as webometrics appeared. This paper explores the potential benefits of altmetrics and the deep relationship between each metrics. Firstly, we found a weak-to-medium correlation among the 11 altmetrics and visualized such correlation. Secondly, we conducted principal component analysis and exploratory factor analysis on altmetrics of social media, divided the 11 altmetrics into four feature sets, confirming the dispersion and relative concentration of altmetrics groups and developed the altmetrics evaluation model. We can use this model to evaluate the scientific impact of articles on social media.

More and more cloud computing services are being applied in various fields; however, it is difficult for users and cloud computing service platforms to establish trust among each other. The trust value cannot be measured accurately or effectively. To solve this problem, we design a service-oriented cloud trust assessment model using a cloud model. We also design a subjective preference weight allocation (SPWA) algorithm. A flexible weight model is advanced by combining SPWA with the entropy method. Aiming at the fuzziness and subjectivity of trust, the cloud model is used to measure the trust value of various cloud computing services. The SPWA algorithm is used to integrate each evaluation result to obtain the trust evaluation value of the entire cloud service provider.

In recent years, construction projects have been forced to cope with lack of skilled labor and increasing hazard circumstance of human operations. A construction robotic system has been frequently accomplished as one alterative for overcoming these difficulties in increasing construction quality, enhancing productivity, and improving safety. However, while the complexity of such a system increases, there are few ways to carry out an assessment of the system. This paper introduces a knowledge-based multi-criteria decision-making process to assist decision makers in systematically evaluating an automated system for a given project and quantifying its system performance index. The model employs linguistic terms and fuzzy numbers in attempts to deal with the vagueness inherent in experts' or decision makers' subjective opinions, considering the contribution resulted from their knowledge on a decision problem. As an illustrative case, the system, called Robotic-based Construction Automation, for constructing steel erection of high-rise buildings was applied into this model. The results show the model's capacities and imply the application to other extended types of construction robotic systems.

Model-driven and component-oriented development is increasingly being used in the development of embedded systems. When combined, both paradigms provide several advantages, such as higher reuse rates, and improved system quality. Performing model-driven and component-oriented development should be accompanied by a component model and a method that prescribes how the component model is used. This article provides an overview on the MARMOT method, which consists of an abstract component model and a methodology for the development of embedded systems. The paper describes a feasibility study that demonstrates MARMOT's capability to alleviate system design, verification, implementation, and reuse. Results indicate that model-driven and component-based development following the MARMOT method outperforms Agile development for embedded systems, leads to maintainable systems, and higher than normal reuse rates.

It has been well-known that the Nonpoint Source (NPS) pollutions are the primary contributors to water quality degradation in the receiving water bodies as well as the Point Source (PS) pollutions. To develop an effective management practice for water quality improvement, pollutant loads must be first estimated. In many studies, the Numeric Integration (NI) method has been used because of its ease of application, irrespective of the total number of samples collected for each storm event. Thus, there have been needs for more accurate pollutant load estimation with a limited number of water quality samples. In this study, NI method and regression method using the USGS ESTIMATOR model were comparatively used to calculate the pollutant loads for the Wolgokri watershed, Gangwon Province. The $NO_{3}$-N, T-N, and T-P loads using NI method and ESTIMATOR model were 13.85 kg/ha, 45.92 kg/ha, and 1.887 kg/ha, and 11.93 kg/ha,43.20 kg/ha, and 1.650 kg/ha, respectively. The estimated loads using ESTIMATOR model were lower than those using NI method by $86\%$, $94\%$, and $87\%$. These discrepancies in the estimated loads using a different load estimation method could be explained in that the total number of samples were not sufficient enough for NI method. Thus, ESTIMATOR model is recommended for the frequently stream discharge and less frequently measured water quality data.

Driven by the vague assessment big data, a product service system (PSS) evaluation method is developed based on a hybrid model of multi-weight combination and improved TOPSIS by relative entropy. The index values of PSS alternatives are solved by the integration of the stakeholders' vague assessment comments presented in the form of trapezoidal fuzzy numbers. Multi-weight combination method is proposed for index weight solving of PSS evaluation decision-making. An improved TOPSIS by relative entropy (RE) is presented to overcome the shortcomings of traditional TOPSIS and related modified TOPSIS and then PSS alternatives are evaluated. A PSS evaluation case in a printer company is given to test and verify the proposed model. The RE closeness of seven PSS alternatives are 0.3940, 0.5147, 0.7913, 0.3719, 0.2403, 0.4959, and 0.6332 and the one with the highest RE closeness is selected as the best alternative. The results of comparison examples show that the presented model can compensate for the shortcomings of existing traditional methods.

Purpose: This study was conducted in order to explore home visiting therapists' self-perceived role, problems, and supplement points of the home-based rehabilitation (HR) program based on the community-based rehabilitation (CBR) model. Methods: Four home visiting physical therapists, who conducted the HR program, participated in this study. After completion of the HR program, in-depth interviews were conducted using a semi-structured questionnaire for participants to explore their self-perceived role, problems, and supplement points of the HR program. Results: Participants regarded the role of the HR program as for "the linkage between recipient & society", "maintenance & improvement of recipients' physical function", and "education of recipient about the way of self rehabilitation". The problems and supplement points were derived from all phases of the HR program, including "human & material resources", "training program for human resources for HR service", "selection of recipient of HR service", "contents of the intervention for HR service", and "duration of HR service". Conclusion: These findings indicate that participants well recognized the intention of the HR program based on the CBR model, and suggest that high-quality human resources with rich expertise and experiences, a training program for HR service led by experts, and selection of recipients led by experts are necessary for an effective HR program. In addition, strategies and capacities specified to HR service should be identified, and applied to the training program for human resources for HR service. The results of this study could provide useful information when the government decides on the next guideline for home visiting health service.

Supplier evaluation is of great significance in green supply chain management. Influenced by factors such as economic globalization, sustainable development, a holistic index framework is difficult to establish in green supply chain. Furthermore, the initial index values of candidate suppliers are often characterized by uncertainty and incompleteness and the index weight is variable. To solve these problems, an index framework is established after comprehensive consideration of the major factors. Then an adaptive weight D-S theory model is put forward, and a fuzzy-rough-sets-AHP method is proposed to solve the adaptive weight in the index framework. The case study and the comparison with TOPSIS show that the adaptive weight D-S theory model in this paper is feasible and effective.

Epilepsy is one of the most common neurological disorders, and topiramate (TPM) is one of the most effective drugs that can render patients seizure-free. The focus of the present study was to evaluate the immunological safety of TPM in a mouse model. We examined the in vitro effect of TPM on immune functions of BV2 microglial cells, RAW 264.7 macrophages, B cells, T cells, and dendritic cells. We also examined the in vivo effect of TPM on mouse immune organs, such as lymph node, spleen, and thymus. When cells were directly treated with TPM at concentrations from 1 to $30{\mu}g/ml$, TPM did not affect nitrite production by BV2 cells and macrophages, proliferation of B cells and T cells, or maturation of dendritic cells. In addition, TPM did not change the weight and cellularity of lymph nodes, spleen, and thymus in vivo at doses from 3 to 100 mg/kg injected i.p. into mice once a day for 4 consecutive days. These data showed that TPM, which is widely used as an anti-epileptic drug, is immunologically safe.

The purpose of this study is to examine how evaluation metrics influence the perception and performance of question answering (QA) systems, particularly focusing on their effectiveness in QA tasks. We compare four different models: BERT, BioBERT, BioClinicalBERT, and RoBERTa, utilizing ten EPIC-QA questions to assess each model's answer extraction performance. The analysis employs both semantic and lexical metrics. The outcomes reveal clear model-specific behaviors: Bio-ClinicalBERT initially identified irrelevant phrases before focusing on relevant information, whereas BERT and BioBERT continually converge on similar answers, exhibiting a high degree of similarity. RoBERTa, on the other hand, demonstrates effective use of long-range dependencies in text. Semantic metrics outperform lexical metrics, with BERTScore attaining the maximum accuracy (0.97), highlighting the significance of semantic evaluation. Our findings indicate that the choice of evaluation metrics significantly influences the perceived efficacy of models, suggesting that semantic metrics offer more nuanced and insightful assessments of QA system performance. This study contributes to the field of natural language processing and machine learning by providing guidelines for selecting evaluation metrics that align with the strengths and weaknesses of various QA approaches.

The eye irritation potential of drug candidates or pharmaceutical ingredients should be evaluated if there is a possibility of ocular exposure. Traditionally, the ocular irritation has been evaluated by the rabbit Draize test. However, rabbit eyes are more sensitive to irritants than human eyes, therefore substantial level of false positives are unavoidable. To resolve this species difference, several three-dimensional human corneal epithelial (HCE) models have been developed as alternative eye irritation test methods. Recently, we introduced a new HCE model, MCTT HCE$^{TM}$ which is reconstructed with non-transformed human corneal cells from limbal tissues. Here, we examined if MCTT HCE$^{TM}$ can be employed to evaluate eye irritation potential of solid substances. Through optimization of washing method and exposure time, treatment time was established as 10 min and washing procedure was set up as 4 times of washing with 10 mL of PBS and shaking in 30 mL of PBS in a beaker. With the established eye irritation test protocol, 11 solid substances (5 non-irritants, 6 irritants) were evaluated which demonstrated an excellent predictive capacity (100% accuracy, 100% specificity and 100% sensitivity). We also compared the performance of our test method with rabbit Draize test results and in vitro cytotoxicity test with 2D human corneal epithelial cell lines.

WiMAX is intended for fourth generation wireless mobile communications where a group of users are provided with a connection and a fixed length queue. In present literature traffic of such network is analyzed based on the generator matrix of the Markov Arrival Process (MAP). In this paper a simple analytical technique of the two dimensional Markov chain is used to obtain the trajectory of the congestion of the network as a function of a traffic parameter. Finally, a two state phase dependent arrival process is considered to evaluate probability states. The entire analysis is kept independent of modulation and coding schemes.

Scopolamine-induced cognitive impairment in mice models acute cholinergic dysfunction associated with early functional features of Alzheimer's disease (AD). This study evaluated the neuroprotective potential of curcumin-loaded nanoliposomes (Cur-NL), a bioavailable curcumin formulation, using behavioral, molecular, and biochemical approaches. Male mice received oral Cur-NL (250, 500, or 1000 mg/kg) for 30 days, followed by a single intraperitoneal injection of scopolamine (2 mg/kg). Cognitive performance was assessed by the open field test and Barnes maze. Acetylcholinesterase (AChE) activity, acetylcholine (ACh) levels, hippocampal gene expression, and reactive oxygen species (ROS) accumulation were analyzed to investigate underlying mechanisms. Cur-NL significantly improved spatial learning and memory and restored cholinergic balance by normalizing AChE activity and ACh levels. Treatment also attenuated hippocampal neuroinflammation, oxidative stress, and ROS accumulation. Cur-NL modulated genes related to amyloid processing and synaptic plasticity, suppressing App and Bace1 and upregulating Adam10 and Bdnf. Network analyses supported the involvement of cholinergic, inflammatory, and synaptic signaling pathways. These findings indicate that Cur-NL confers multitarget neuroprotection in a scopolamine-induced model and may serve as a candidate for managing early cholinergic-related cognitive decline. Important limitations should be acknowledged: curcumin concentrations in plasma and brain were not quantified, and a free-curcumin comparator was not included. The findings should therefore be interpreted as evidence of efficacy of the tested Cur-NL preparation, not as a comparative demonstration of nano-liposomal superiority over free curcumin. Direct pharmacokinetic and head-to-head comparative studies are required to establish the formulation-specific contribution of nano-liposomal delivery.

In promoting basketball sports among female college students, this paper introduces fuzzy sets of interval type-2 into the agility assessment model for our university's female basketball players. During the assessment, the expert language variables are converted to the second class of the interval. It combines the fuzzy analytic hierarchy process (AHP) and the entropy weight approach for calculating weights, integrating the VIKOR method to construct a fuzzy interval type-2 AHP-entropy weight-VIKOR risk assessment model. Based on the fuzzy logic of type I, this model explores the influence relationships among factors, effectively reduces information loss through the collaboration of multiple expert judgments, and enhances evaluation accuracy. Lastly, this model is used to evaluate the agility of women's basketball players. It has strong operability and feasibility compared to actual results and provides an effective evaluation basis.

본 논문은 체육교과 핵심성취의 관련 개념, 의미, 위계적 관계를 빗대어보고, 학생들의 체육교과 핵심성취를 함양하기 위한 공공체육과목 의무화 사업의 이론 적 근거와 문제점, 그리고 그 대책을 종합적으로 분석하였다. 이를 토대로 기존의 평가지표를 요약하고, 체육교과의 핵심성취에 기초한 대학 필수 공공체육과목의 평가모형을 구성하였다. 지수의 가중치를 산정하기 위해서는 AHP 방법을 이용하 며, 실증연구를 위해서는 퍼지종합평가 방법을 이용한다. 결 과: 평가모형은 과학 적이고 객관적인 6개의 1단계 지수와 21개의 2단계 지수로 구성되어 있으며, 대 학의 공공체육 의무과목 수강생 평가에 적용될 수 있고, 평가를 위한 과학적 참 고자료와 근거를 제공할 수 있다.

This paper combs the relevant concepts, connotations, and hierarchical relationships of the core accomplishment of physical education, and comprehensively analyzes the theoretical basis, problems, and countermeasures of the undertaking of compulsory public physical education courses to cultivate students’ core accomplishment of physical education. On this basis, the existing evaluation indexes are summarized, and the evaluation model of compulsory public physical education courses in universities based on the core accomplishment of physical education is constructed. The AHP method is used to calculate the index weight, and the fuzzy comprehensive evaluation method is used for empirical research. Results: The evaluation model consists of 6 first-level indexes and 21 second-level indexes, which is scientific and objective, and can be applied to the evaluation of students of compulsory public physical education courses in universities, and can provide scientific reference and basis for evaluation.

文献梳理体育学科核心素养的相关概念、内涵及层次关系，逻辑分析高校公共 体育必修课承担培育学生体育学科核心素养的理论依据、问题与对策；以国内外 理论、文献为支撑，归纳已有评价指标，构建基于体育学科核心素养的高校公共 体育必修课学生评价模型；利用AHP层次分析法分析指标权重，利用模糊数学综 合评价法进行实证研究。结果：高校公共体育必修课作为培育大学生体育学科核 心素养有其应然性，所构建的评价模型由6个一级指标、21个二级指标构成是科 学、客观的，可为高校公共体育必修课学生评价指导提供科学的参照和依据。