Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Influencing Grazing Behavior by Using the Consciousness-Context-Behavior Theory—A Case Study from Yanchi County, China

Grazing behavior is a key factor that affects the sustainable development of the grassland social-ecological system. Grazing behavior is not only restricted by policies but also affected by the awareness of the herder of the grassland environment. To explore the influencing factors and mechanism behind grazing behavior, Yanchi County of Ningxia, a typical area of the “returning grazing land to grassland” project in Northwest China, was selected as a study area. Based on the consciousness-context-behavior theory, a questionnaire was designed, and 305 households were surveyed. Analysis of structural equation model results show: (1) the environmental sensitivity of herders and their satisfaction with the compensation mechanism regulated grazing behavior. When herders were more dependent on grassland, they were more willing to graze. (2) The grassland dependence, environmental sensitivity of herders, and herders’ satisfaction with the compensation mechanism had a significant interaction effect on grazing behavior. (3) Family livelihood diversification and the number of young and middle-aged laborers had a significant moderating effect on grassland dependence and grazing behavior. These findings are of vital importance for the government to formulate policies to promote the sustainable development of grasslands.
Applications of automation technology to fatigue and fracture testing; Proceedings of the Symposium, Kansas City, MO, May 22, 23, 1989

Consideration is given to automated systems implementation, test techniques, applications of networking and information management within a testing laboratory, control and data acquisition techniques, and applications where the computer provided enhanced analysis or simulation capability. Particular attention is given to a computer-controlled automated test system for fatigue and fracture testing, a test system for computer-controlled thermomechanical fatigue testing, a fracture mechanics test automation system for a basic research laboratory, fatigue crack-growth measurement using a digital image analysis technique, automated variable-amplitude fatigue crack growth technology, use of computer systems in high-temperature crack growth studies, automation software for a materials testing laboratory, and a data acquisition and control program for axial-torsional fatigue testing.
Gender Dissimilarities in Human Capital Transferability of Cuban Immigrants in the US: A Clustering Quantile Regression Coefficients Approach with Consideration of Implications for Sustainability

Female participation in the labor market has been increasing over time. Despite the fact that the level of education among women has also increased considerably, the wage gap has not narrowed to the same extent. This dichotomy presents an important challenge that the United Nations Sustainable Development Goals with respect to gender inequities must address. Hispanics constitute the largest minority group in the US, totaling 60.6 million people (18.5% of the total US population in 2020). Cubans make up the third largest group of Hispanic immigrants in the US, representing 5% of workers. This paper analyzes the conditional income distribution of Cuban immigrants in the US using the clustering of effects curves (CEC) technique in a quantile regression coefficients modeling (QRCM) framework to compare the transferability of human capital between women and men. The method uses a flexible quantile regression approach and hierarchical clustering to model the effect of covariates (such as years of education, the squared years of education, English proficiency, US citizenship status, and age at time of migration) on hourly earnings. The main conclusion drawn from the QRCM estimations was that being a woman had the strongest negative impact on earnings and was associated with lower wages in all quantiles of the distribution. CEC analysis suggested that educational attainment was included in different clusters for the two groups, which may have indicated that education did not play the same role for men and women in income distribution.
MD-SPKM: A set pair k-modes clustering algorithm for incomplete categorical matrix data

In order to solve the clustering problem with incomplete and categorical matrix data sets, and considering the uncertain relationship between samples and clusters, a set pair k-modes clustering algorithm is proposed (MD-SPKM). Firstly, the correlation theory of set pair information granule is introduced into k-modes clustering. By improving the distance formula of traditional k-modes algorithm, a set pair distance measurement method between incomplete matrix samples is defined. Secondly, considering the uncertain relationship between the sample and the cluster, the definition of the intra-cluster average distance and the threshold calculation formula to determine whether the sample belongs to multiple clusters is given, and then the result of set pair clustering is formed, which includes positive region, boundary region and negative region. Finally, through the selected three data sets and four contrast algorithms for experimental evaluation, the experimental results show that the set pair k-modes clustering algorithm can effectively handle incomplete categorical matrix data sets, and has good clustering performance in Accuracy, Recall, ARI and NMI.
Modeling and Identification of a Haptic Device having a Double Parallelogram Loop

Haptic interfaces are robotic devices intended to enhance the user's immersion in virtual environment s through the stimulation of the haptic sense. These devices make use of an articulated mechanical structure which introduces di stortion between the operator and the explored world. This di stortion must be identified in order to assess the quality o f the interface. Therefore, its base parameters must be calculated. In this study, we focus on a particular 3 degrees of freedom haptic interface which makes use of a double parallelogram loop. Its modeling is first introduced. It is based on the calculation of the base parameters. Then its identification using inverse m odel and least squares method is presented.
The Impact of Special Economic Zones (SEZs) on Economic Growth: Where the Absorption Capacity of Domestic Labor Stands?

This study designs to assess and infer the effect of Special Economic Zones under China-Pakistan Economic Corridor on the economic growth of Pakistan through technological spillovers and the absorption capacity of domestic laborers. The present study develops a theoretical model and an empirical panel model to test whether the intervention of Special Economic Zones in the Asian developing countries has affected their economic growth through domestic Human Capital. For relevant results, we have employed the GMM model for the panel data set. The results indicate that the technological enhancement accumulates the economy through various other selected indicators rather than domestic labor productivity. The human capital remains inconsequent in this nexus. This condition gives us guidelines to follow pro-human capital policies to accumulate domestic human capital before the intervention from the foreign firms on our soil. Subsequently, much waited for dynamic or long-run benefits in terms of human capital can be attained rather than static effects.JEL Classification: C23, D24, J24How to Cite:Waqar, S. , Badshah, I. , Bandeali, M. S. M. , & Ahmed, S. (2021). The Impact of Special Economic Zones (SEZs) on Economic Growth: Where the Absorption Capacity of Domestic Labor Stands? Etikonomi, 20(2), xx – xx. https://doi.org/10.15408/etk.v20i2. 19386.
Empowering Methodologies in Organisational and Social Research

This chapter considers the meaning and practice of empowering methodologies in organizational and social research. We begin by explaining the reasons why empowering research is urgently needed, which are related to the repositivization of research in a context of global academic precarity. Next, we reflect on the situatedness of knowing and knowledge in the context of core periphery relations between the global North and South. We discuss the epistemological arguments on which empowering methodologies rely and the ethical and political purposes they serve, drawing on concepts developed by feminist epistemologists and methodologists. We then consider the sensory, affective, embodied practice of empowering research which involves listening, seeing, moving and feeling, which we suggest can facilitate a more diverse, creative and crafty repertoire of research possibilities. Finally, we identify three aspects of empowering research, showing how they relate to each of the chapters that comprise this volume.
Snow mold fungus Racodium therryanum is phylogenetically Herpotrichia juniperi

Racodium therryanum is a snow mold causing snow blight and seed rot in conifers. The sexual stage of R. therryanum has not been found, however, it has been speculated that Herpotrichia juniperi, which causes brown felt blight, is the sexual stage of R. therryanum. In this study, we conducted phylogenetic analysis using 28S large subunit (LSU) rDNA, 18S small subunit (SSU) rDNA, translation elongation factor 1-alpha (tef1), and RNA polymerase II second largest subunit (rpb2). Four isolates were identified as R. therryanum based on their morphological characteristics; together with two strains of H. juniperi, they composed a clade supported by high bootstrap and Bayesian posterior probability values. Therefore, we conclude that the snow mold previously described as R. therryanum is phylogenetically H. juniperi.
Representation of Quality Attribute Techniques Using SPEM and EPF Composer

There are many development techniques used to assist development teams to achieve required levels of product quality such as safety, security and performance. These ``Quality Attribute Techniques'' (QAT) aim to identify, eliminate, reduce, control and minimise potential quality problems in the development of critical systems. Although widely used, these techniques are not normally well represented in software process models. This paper proposes two alternative representations of Quality Attribute Techniques using the SPEM metamodel and Eclipse Process Framework (EPF) Composer and shows how these techniques can be incorporated into software development process models. Safety techniques have been selected as a case example for evaluation. The evaluation identifies advantages and limitations of the SPEM and EPF Composer in terms of their ability to support representation and integration of Quality Attribute Techniques. Some improvements to SPEM and EPF Composer are suggested.
Pedestrian and Vehicle Detection in Autonomous Vehicle Perception Systems—A Review

Autonomous Vehicles (AVs) have the potential to solve many traffic problems, such as accidents, congestion and pollution. However, there are still challenges to overcome, for instance, AVs need to accurately perceive their environment to safely navigate in busy urban scenarios. The aim of this paper is to review recent articles on computer vision techniques that can be used to build an AV perception system. AV perception systems need to accurately detect non-static objects and predict their behaviour, as well as to detect static objects and recognise the information they are providing. This paper, in particular, focuses on the computer vision techniques used to detect pedestrians and vehicles. There have been many papers and reviews on pedestrians and vehicles detection so far. However, most of the past papers only reviewed pedestrian or vehicle detection separately. This review aims to present an overview of the AV systems in general, and then review and investigate several detection computer vision techniques for pedestrians and vehicles. The review concludes that both traditional and Deep Learning (DL) techniques have been used for pedestrian and vehicle detection; however, DL techniques have shown the best results. Although good detection results have been achieved for pedestrians and vehicles, the current algorithms still struggle to detect small, occluded, and truncated objects. In addition, there is limited research on how to improve detection performance in difficult light and weather conditions. Most of the algorithms have been tested on well-recognised datasets such as Caltech and KITTI; however, these datasets have their own limitations. Therefore, this paper recommends that future works should be implemented on more new challenging datasets, such as PIE and BDD100K.
A Study on Railway Surface Defects Detection Based on Machine Vision

The detection of rail surface defects is an important tool to ensure the safe operation of rail transit. Due to the complex diversity of track surface defect features and the small size of the defect area, it is difficult to obtain satisfying detection results by traditional machine vision methods. The existing deep learning-based methods have the problems of large model sizes, excessive parameters, low accuracy and slow speed. Therefore, this paper proposes a new method based on an improved YOLOv4 (You Only Look Once, YOLO) for railway surface defect detection. In this method, MobileNetv3 is used as the backbone network of YOLOv4 to extract image features, and at the same time, deep separable convolution is applied on the PANet layer in YOLOv4, which realizes the lightweight network and real-time detection of the railway surface. The test results show that, compared with YOLOv4, the study can reduce the amount of the parameters by 78.04%, speed up the detection by 10.36 frames per second and decrease the model volume by 78%. Compared with other methods, the proposed method can achieve a higher detection accuracy, making it suitable for the fast and accurate detection of railway surface defects.
Co-occurrence pattern of congeneric tree species provides conflicting evidence for competition relatedness hypothesis

In plants, negative reproductive interaction among closely related species (i.e., reproductive interference) is known to hamper the coexistence of congeneric species while facilitation can increase species persistence. Since reproductive interference in plants may occur through interspecific pollination, the effective range of reproductive interference may reflects the spatial range of interspecific pollination. Therefore, we hypothesized that the coexistence of congeners on a small spatial scale would be less likely to occur by chance but that such coexistence would be likely to occur on a scale larger than interspecific pollination frequently occur. In the present study, we tested this hypothesis using spatially explicit woody plant survey data. Contrary to our prediction, congeneric tree species often coexisted at the finest spatial scale and significant exclusive distribution was not detected. Our results suggest that cooccurrence of congeneric tree species is not structured by reproductive interference, and they indicate the need for further research to explore the factors that mitigate the effects of reproductive interference.
The Evaluation of TVET Instructor’s Training Needs Analysis Using Curriculum Development Based on Vocational Ability Structure in Malaysia

185 Abstract—This paper aims to evaluate the use of a method called Curriculum Development Based on Ability Structure (CUDBAS) in evaluation TVET Instructor’s Training Needs Analysis. This method profiles each instructor into a structured measurement based on ability of work. The results from the measurements are analysed systematically with the goal to reduce the competency gap among the instructors and simultaneously identify experts within this group to be fully utilized across agencies and ministries in Malaysia. As a result, training can be planned and implemented effectively with cost saving by matching trainer and trainee into a single system toward the right trainer, right training and right time. An online survey was conducted to evaluate user’s satisfaction level of using the system from multiple public agencies those currently using the method. The result of the survey is analysed in order to explain the influence of the identified factors that lead to user’s satisfaction. The ouput of the result may cause implement of TNA (Training Need Analysis) using CUDBAS to be be more widely use within public agencies in Malaysia.
Engineering Graduate Attribute Development (EGAD) Project

This paper describes the objectives and progress of the Engineering Graduate Attribute Development (EGAD) project. This is a Canadian collaborative project sponsored by the National Council of Deans of Engineering and Applied Science (NCDEAS), in collaboration with Engineers Canada. EGAD's mandate is to develop resources and training for assessing graduating student attributes in undergraduate engineering programs for the purpose of improving the quality of engineering education in Canada, specifically in response to CEAB's graduate attribute requirements.
Designing a logistic regression study using surrogate measures for exposure and outcome

SUMMARY Suppose that a binary or polytomous outcome variable is related to a possibly continuous exposure variable through a logistic regression model, and that prior to sample selection subjects can be characterized according to 'surrogates' for outcome and exposure. The surrogate variables are assumed to satisfy certain conditional independence properties commonly used in errors-in-variables models. This paper considers the problem of using the surrogate variables to select subjects for measurement of the true values with the goal of minimizing the variance of an estimate of the log odds ratio. We describe three possible sampling plans and show that the log odds ratio parameter can be estimated in each plan using ordinary logistic regression.
Passing to Win: Using Characteristics of Passing Information for Match Winner Prediction

: Predictingthe football match results has received great attention both in sports industry and academic ﬁelds. Many researchers have studied on predicting the match outcome using the simple features such as the number of shots and passes. However, little attention has been paid to using pass interaction features, which can represent how players in a match interact to each other. To this end, we propose a win-lose prediction model that predicts a match result using the pass interaction and other features, achieving high accuracy of 79.5%. By conducting an ablation study, we ﬁnd that the proposed interaction features play an important role in accurately predicting match results. We believe our work can provide important insights both for industry and academic researchers who want to understand the characteristics of winning teams.
Production and Purification of Specific IgY Against InvG Protein of Salmonella typhimurium

Background: Salmonella infections are one of the most important causes of human and animal diseases, worldwide. InvG gene is one of the main genes of type III secretion system and leads to initial binding of the bacteria to the host cells. In the recent decades IgY technology has been detected as an efficient alternative procedure to generate antibody for applying in immunotherapy. Objectives: This research attempted to produce and detect IgY against the recombinant InvG protein of Salmonella typhimurium and evaluate specificity of anti-InvG IgY against the recombinant InvG antigen. Methods: Polymerase chain reaction was carried out to amplify InvG gene with InvG one pair of specific primer of Salmonella typhimurium. pTZ57R/T and pET32a vectors were used to clone and sub-clone InvG gene. Recombinant pET32a-InvG plasmid was transferred to E. coli BL21 (DE3). Expression induction was carried out using 1.5 mM isopropyl β-D-1-thiogalactopyranoside. Next, the recombinant InvG protein was injected to laying hens. Western-blotting and Dot-blotting analysis and iELISA were carried out to determine the specify of anti-InvG IgY. Results: This research produced specific InvG egg yolk antibodies by injecting InvG protein to the hens. The anti-InvG IgY corroborated to bind specifically with the InvG protein of Salmonella typhimurium. Conclusions: The finding of the present research confirmed that anti-InvG IgY could be suggested as a candidate for passive immunization and protection against Salmonella typhimurium.
The San1 Ubiquitin Ligase Avidly Recognizes Misfolded Proteins through Multiple Substrate Binding Sites

Cellular homeostasis depends on robust protein quality control (PQC) pathways that discern misfolded proteins from functional ones in the cell. One major branch of PQC involves the controlled degradation of misfolded proteins by the ubiquitin-proteasome system. Here ubiquitin ligases must recognize and bind to misfolded proteins with sufficient energy to form a complex and with an adequate half-life to achieve poly-ubiquitin chain formation, the signal for protein degradation, prior to its dissociation from the ligase. It is not well understood how PQC ubiquitin ligases accomplish these tasks. Employing a fully reconstituted enzyme and substrate system to perform quantitative biochemical experiments, we demonstrate that the yeast PQC ubiquitin ligase San1 contains multiple substrate binding sites along its polypeptide chain that appear to display specificity for unique misfolded proteins. The results are consistent with a model where these substrate binding sites enable San1 to bind to misfolded substrates avidly, resulting in high affinity ubiquitin ligase-substrate complexes.
An Examination of the Effects of Cultural, Climatic, Structural, and Technological Factors on Knowledge Management Effectiveness

Abstract : Knowledge management (KM) has become a key initiative in many organizations seeking to better manage "what they know" and as a source of competitive advantage (Nidumolu, Subramani & Aldrich, 2001; Teece, 1998). KM has become an integral part of many different organizations (Grover & Davenport, 2001) and based on the increasing level of activity in both academic and practitioner journals, research activity is also increasing. Given the importance of knowledge to an organization (Davenport, Delong & Beers, 1998), the increase is not surprising. KM refers to management's conscientious efforts to use tools and approaches to locate, refine, transfer, and apply the knowledge and experience available to the company (von Krogh, 1998). Generally, KM refers to the overall effort to manage knowledge within an organization. In contrast, a KM system (KMS) is the information technology component of a KM program (Alavi & Leidner, 2001). Technology is extremely important to KM through the capabilities it provides in the form of communications, collaboration, and the storage of vast amount of data, information, and knowledge.