Miracle-dz/UniFAR-FTUs huggingface dataset:
COMPARING THE EFFECTIVENESS OF COMPUTER AND MOTOR CONTROL-BASED COGNITIVE REHABILITATION ON IMPROVING EXECUTIVE FUNCTIONS IN STUDENTS WITH ADHD

Attention Deficit/Hyperactivity Disorder is thought to be a neuro-developmental disorder whose main symptom is executive dysfunction. The aim of this study was to compare the effectiveness of computer and motor control-based cognitive rehabilitation on improving executive functions in students with attention deficit/ hyperactivity disorder. The number of 30 children aged 6 to 12 years with attention deficit/hyperactivity disorder were randomly placed in two experimental groups in the form of quasi-experimental research and clinical trial design with pre-test and post-test. To measure the variables, continuous performance test, Wisconsin cards, previous multi-stimulus test, modified Stroop test and simple reaction time test were applied. Data analysis using repeated measures analysis of covariance indicated that motor control and computer-based cognitive rehabilitation was effective in improving executive functions; however, the effect of motor control-based cognitive rehabilitation was higher on sustained attention, while computer-based cognitive rehabilitation produced greater effects on the working memory, cognitive flexibility and reaction time. On the other hand, the impacts of both types of intervention on response inhibition was the same. Therefore, it can be concluded that computer and motor control-based cognitive rehabilitation improves the executive functions of children suffering from attention deficit/hyperactivity disorder.
Review of Traceability System of Food Safety

Facing a series of food-related accidents,consumers worldwide pay increasing attentions on food safety.The food traceability system has a basic function to ensure food safety and has become one of the principal measures to reduce risks.This paper summaries the traceability mechanism in the existing literature,and analyses the mutual influence from the aspects of consumers,producers,governments and existing traceability systems.Besides the above,this paper points out existing problems in the study of the traceability system and the direction of the future research.
A Novel Approach to Restoration of Tropical Dry Forest in Hawaii

Tropical dry forests comprise nearly half of the world’s tropical and subtropical forests [1], crossing large areas of southeastern Africa, eastern Bolivia, central Brazil, the Caribbean, and the Asia Pacific region. The tropical dry forests are the most threatened of the major tropical forest types [2,3]. Due to its convenience for land clearance and suitability for agriculture, much of the tropical dry forests have been burned and cleared to make way for agricultural production and cattle grazing, and now continuously face the greatest anthropogenic disturbances[4]. Hundreds of millions of people depend on dry forests but these valuable ecosystems are rapidly disappearing worldwide.
PATA: Fuzzing with Path Aware Taint Analysis

Taint analysis assists fuzzers in solving complex fuzzing constraints by inferring the influencing input bytes. Execution paths in real-world programs often reach loops, where constraints in these loops can be visited and recorded multiple times. Conventional taint analysis techniques experience difficulties when distinguishing between multiple occurrences of the same constraint. In this paper, we propose PATA, a fuzzer that implements path-aware taint analysis, i.e. one that distinguishes between multiple occurrences of the same variable based on the execution path information. PATA does so using the following steps. First, PATA identifies variables used in constraints and constructs the Representative Variable Sequence (RVS), consisting of occurrences of all representative constraint variables and their values. Next, PATA perturbs the input, matches its RVS with that of the original input, and looks for value changes to identify the influencing input bytes for each entry in the RVS. Finally, PATA mutates the corresponding input bytes to solve constraints in the given path. To demonstrate the effectiveness of PATA over conventional taint analysis methods, we evaluated its performance on the benchmarks Google’s fuzzer-test-suite and LAVA-M against AFL, MOPT, TortoriseFuzz, VUzzer, Angora, Redqueen, and Greyone. On Google’s fuzzer-test-suite, PATA outperformed these state-of-the-art fuzzers by 29%–1830% and 7%–87% in the number of unique paths found and basic blocks covered, respectively. More importantly, it found more bugs than the comparison fuzzers, including 17 unlisted ones. On LAVA-M, PATA performed the best out of all evaluated fuzzers and found 2602 bugs. On open-source projects, PATA found 40 previously unknown bugs, with 12 of them confirmed as CVEs.
NATURAL LANGUAGE INTERFACE FOR QUERYING LINKED DATA USING CASE-BASED REASONING

With the emergence of Linked Data in RDF format, query systems should execute structured queries in SPARQL. Still, only expert programmers can specify their information needs and cope with Linked Data sources’ diversity and heterogeneity. Therefore, understanding Natural Language (NL) queries to construct correct SPARQL queries is a great challenge for these query systems to access multiple heterogeneous semantic sources and Linked Data sets. This paper presents a new approach for querying Linked Data with NL queries. Our method identifies the topic and search criteria of the NL query based on the Case-Based Reasoning (CBR) technique. Next, we match the identified topic and search criteria to their corresponding entities in the dataset. Then, we represent the query as triples based on the semantic relations provided by the dataset. Finally, our system executes the SPARQL queries generated from the query triples, based on the proposed generation rules, to query the dataset and retrieve the relevant answers. Experiments showed that the proposed approach is efficient compared to the existing systems in terms of precision and recall.
Why do we need to integrate the Indigenous culture to achieve Holistic Sustainability?

This paper proposes a vision of the re-discovery of Arabian Gulf communities’ culture and a revival of local knowledge in a bid to support, promote, and move towards a more sustainable future for the region. Information and skills about the local desert environment, formed over many years, traditional ways of doing things and methods for coping with the harsh environment, may provide invaluable insights into how the region in general, and Qatar in particular, can develop in harmony with its environment rather than against it. By championing local methods and cultural norms, natural resources can be conserved, biodiversity protected and natural environments restored. This paper explores local knowledge by referring to older local experts on some of the techniques they used to deal with environmental conditions. The study revealed that most of the old ways of dealing with natural resources take into account two basic elements: protection and support the environment to renew. These two concepts must be integrated within the goals of development projects in the region that are essentially suffering from scarcity of natural resources.
Common Belief in Choquet Rationality with an “Attitude”∗

We consider finite games in strategic form with Choquet expected utility. We characterize a preference-based notion of belief, define Choquet rationalizability, and characterize it by Choquet rationality and common beliefs in Choquet rationality in the universal capacity type space in a purely measurable setting. We also show that Choquet rationalizability is equivalent to iterative elimination of strictly dominated actions (not in the original game but) in an extended game. This allows for computation of Choquet rationalizable actions without the need to first compute Choquet integrals. Choquet expected utility enables us to investigate common belief in ambiguity love/aversion. We show that Choquet rationality and common belief in Choquet rationality and ambiguity love/aversion leads to smaller/larger sets of action profiles, respectively.
Cloning and Functional Veri cation of Gene GmELF4-LIKE4 in Soybean [Glycine max (L.) Merr]

Background: Soybean grain is an important oil crop with high-quality vegetable protein and vegetable oil. Extreme weather can cause crop yield reduction, among which drought is most likely to cause a decline in annual soybean yield. How to overcome the impact of drought on soybean yield has become a major work in current breeding research. Results: In our study, the gene GmELF4-LIKE4 was obtained through RNA-Seq and differential gene screening technology, and the plant over expression vector and RNAi vector were constructed. Then, the Colombian Arabidopsis thaliana and soybean JN18 were genetically transformed and added to the Agrobacterium-mediated method in to T2 generation. We have verified in Arabidopsis thaliana that over expression of ELF4-LIKE4 will delay the flowering of Arabidopsis thaliana, while inhibition of ELF4-LIKE4 expression will advance the flowering period. At the same time, we verified the regulation analysis of GmELF4-LIKE4 on EARLY FLOWERING 3 and CONSTANTS-like in soybeans, and found that GmELF4-LIKE4 positively regulates ELF3 and COL; meanwhile, over expression soybeans and RNAi soybeans were tested in drought. Stressing the relative conductivity, malondialdehyde content and peroxidase activity under 0 days and 5 days, the result indicate that the over expression of GmELF4-LIKE4 gene can reduce the drought resistance of soybean. This study laid a theoretical foundation for the identification of GmELF4-LIKE4 gene function and the breeding of drought-resistant varieties. Conclusion: We found that overexpression of GmELF4-LIKE4 will delay the flowering period of Arabidopsis thaliana and reduce the drought resistance of soybeans. Conversely, inhibiting GmELF4-LIKE4 will advance the flowering of Arabidopsis thaliana and increase the drought resistance of soybeans.
The Regionalization Effect in Facial Expression Recognition

Recognizing facial expressions is an important way of recognizing emotions and communicating. The process of recognizing emotional faces is important and complex. Many studies have found that there is a regionalization effect in the recognition of facial expression, whereby areas such as the eyes or the mouth have different effects on the recognition of different facial expressions. The present study used mixed faces, i.e., only the eyes or mouth represented emotional information, and examined 31 college students emotion recognition for these mixed faces. It was found that individuals responded more quickly to and rated the emotional level higher for the mixed faces of
EXPLORING ORGANIC AGRICULTURE IN ICELAND THROUGH THE LENS OF ECOLOGICAL ETHICS: IMPLICATIONS FOR KYRGYZSTAN

In view of global climate change and the pressing issue of land degradation, sustainable agricultural practices such as organic farming represent one of the viable solutions. This research contributed to better understanding of the concept of sustainability by placing emphasis on the ethical aspect in organic farmers’ decision-making and elaborated on the thresholds and opportunities for organic agriculture development in Iceland and Kyrgyzstan. The study employed semi-structured interviews and a literature survey for data collection. Twelve stakeholders in the organic sector from varied geographical regions of Iceland were interviewed. A thematic analysis of the interview transcripts was conducted. The respondents reported that organic farmers’ mindsets could be characterized through their ethical values connected to nature and society. Among the key values participants mentioned were care for the environment, with the accent placed on soil and human health, respect for nature, dedication and commitment to organic principles, and fairness to customers. The following main thresholds for the enhancement of organic agriculture in Iceland were identified: a public policy vacuum, lack of a strategic vision and political leadership, poor linkages among the stakeholders of the organic agriculture sector, inadequate system for financial support to stimulate organic conversion, and unrealized organic market potential. Based on these thresholds, recommendations for the organic sectors of Iceland and Kyrgyzstan were formulated. Specific recommendations for the Kyrgyz organic sector included prioritization of organic farming in policies, organic market development, promotion of role modeling, Land Restoration Training Programme Keldnaholt, 112 Reykjavik, Iceland UNU Land Restoration Training Programme ii establishment of an interactive platform for the stakeholders, and greener agendas in research and education. The findings indicate that ethical values are essential aspects of organic farmers’ decision-making and should be considered in the policy-making process. On a larger scale, this research illustrates the importance of farmers’ ethics in reaching sustainability and tackling environmental issues.
Lane Detection by Dynamic Origin Technique for Advanced Driver Assistance System

— Lane detection is one of the key steps for developing driver assistance and vehicle automation features. A number of techniques are available for lane detection as part of computer vision tools to perform lane detection with different levels of accuracies. In this paper a unique method has been proposed for lane detection based on dynamic origin (DOT). This method provides better flexibility to adjust the outcome as per the specific needs of the intended application compared to other techniques. As the method offers better degree of control during the lane detection process, it can be adapted to detect lanes in varied situations like poor lighting or low quality road markings. Moreover, the Piecewise Linear Stretching Function (PLSF) has also been incorporated into the proposed method to improve the contrast of the input image source. Adding the PLSF method to the proposed lane detection technique, has significantly improved the accuracy of lane detection when compared to hough transform method from 87.88% to 98.25% in day light situations and from 94.15% to 97% in low light situations.
THE IMPACT OF FINANCIAL DEVELOPMENT ON ECONOMIC GROWTH

This study aims to test the experimental relationship between the development of the financial sector and the economic growth of Algeria during the period 2005-2014. In order to reach this relationship, the researcher used the data of Panel models. The study included thirteen Algerian commercial banks. Using the PANEL model data, the results showed a positive impact on the development of the financial sector in stimulating the economic growth of Algeria during the period of the study. This effect is reflected in the banking sector through the volume of assets and the ratio of credit facilities granted to the private sector as a percentage of GDP to economic growth which reflects the role of banks in financing private sector activity and supports the hypothesis that there is an impact of financial development on Algeria's economic growth.
EFFECTS OF PHOSPHORUS AND IRON ON BIOMASS PRODUCTION AND NUTRIENTS PARTITIONING IN SOYBEAN CULTIVARS UNDER WATER STRESS CONDITION

A pot experiment was conducted to investigate the effects of P and Fe application on the biomass production and nutrients partitioning of two soybeans (Glycine max. L. Merr) cultivars grown in carbonated chernoziom (low in Fe and P) under water stress conditions. P and Fe were applied at two levels (0 and 100 mg P kg-1 soil; 0 and 5 mg Fe kg-1 soil). Control plants were grown at 70% water holding capacity (WHC) while their counterparts were subjected to 35% WHC water stress at initial flowering stage for two weeks. Considerable variability was observed in leaves, roots dry mass accumulation and nodulation among the soybean cultivars (Zodiac, Licurici) at both P and Fe levels in relation to water regimes. The results showed that drought significantly reduced biomass production irrespective of nutrient supply and its adverse effect was more pronounced at low nutrient supply. Leaf development and nodules growth were the most sensitive to water deficit and insufficient nutrient supply. Adequate P and Fe supply increased dry matter production and nutrient concentrations for soybean cultivars. Phosphorus concentration in plant parts was significantly higher at nil Fe compared with Fe application. Phosphorus application decreased Fe allocation to the leaves. The experimental results demonstrated that there was a positive effect of P and Fe adequate nutrition on P use efficiency. Hence, the sufficient phosphorus and iron supply maintained growth at high level, improved P and Fe status and partially alleviated drought effect on soybean plants.
The complete chloroplast genome sequence of Quercus ningangensis and its phylogenetic implications

Quercus ningangensis is an economically and ecologically important tree species belonging to the family Fagaceae. In this study, the complete chloroplast (cp) genome of Q. ningangensis was sequenced and assembled, and 18 published cp genomes of Quercus were retrieved for genomic analyses (including sequence divergence, repeat elements, and structure) and phylogenetic inference. With this study, we found that complete cp genomes in Quercus are conserved, and we discovered a codon composition bias, which may be related to genomic content and genetic characteristics. In addition, we detected considerable structural variations in the expansion and contraction of inverted repeat regions. Six regions with relatively high variable (matK-rps16, psbC, ycf3 intron, rbcL, petA-psbJ, and ycf1) were detected by conducting a sliding window analysis, which has a high potential for developing effective genetic markers. Phylogenetic analysis based on Bayesian inference and maximum likelihood methods resulted in a robust phylogenetic tree of Quercus with high resolution for nearly all identified nodes. The phylogenetic relationships showed that the phylogenetic position of Q. ningangensis was located between Q. sichourensis and Q. acuta. The results of this study contribute to future research into the phylogenetic evolution of Quercus section Cyclobalanopsis (Fagaceae).
Analysis of Orthogonal Test on Influence Factors of Fatigue Performance of Asphalt Mixture

The influence level of gradation,asphalt range,bitumen-aggregate ratio,strain level interval time and test temperature on fatigue performance of mixture is studied through intuitive analysis and variance analysis by carrying out optimized indoor fatigue test with guidance of orthogonal test.The influence rule of all factors is analyzed, which provides reference for fatigue-resistance design of asphalt mixture.
Tablets in the Classroom? Effective or a Distractive Engagement?

Today, social changes have made education inevitable and has been made possible at any time and place to the learner. The change in generation, challenges young and mature learners to cope up with the rapid developments and new technologies evolving from time to time. Change is difficult: it either leads to distraction or engagement. New Learning Management Systems (LMS) evolve, making it highly essential for teachers and learners to integrate mobile technology into their learning. Convenience, flexibility, engagement, interactivity and mobility are major factors that make learning more attractive to a learner. Though a wireless device in the classroom could threaten to distract student attention, on the positive side it also enhances student engagement. Research shows that mobile computing devices like the iPad are finding their way into classrooms in growing numbers. With schools of higher education permitting learners to be digitally active within the campus, the distribution of mobile technology “has an impact on teaching, learning and the connections between formal and informal learning, work and leisure”. This study summarises previous research and proposes a clear pathway into future research and planning for a New Trend Learning Environment (NTLE) for portable devices. Implementing such a solution is practically viable and should increase engagement and retention rates of learners of the 21st century and beyond. A framework is proposed to develop and implement a Multi-Media Learning System (MMLS) for portable devices to teach tertiary students in the school of Business and IT at WelTec.
New Model of Salam sale for Agricultural Development Finance

The new financial economic model derived from the traditional Salam situation. This scenario is based on the idea behind the treatment of risks facing traditional Salam applications, which includes high rates of inflation and the exit of financing from its approved aspects, which cannot enable the farmer or producer to disburse this monetary benefit in the fields of agriculture. Then Banks and financial institutions lose huge amounts of money that are wasted. In addition, lack of understanding of the process of obtaining loans between farmers and producers, this new model can solve many problems and risks in the classic sales of Salam, which rely mainly on granting cash loans. The paper works to monitor and limit the risks posed by the traditional Salam and pushes that agricultural financing loses. It is most important input to financing and then corrects the paper and it relies on this innovative model, which aims to provide the necessary inputs to farmers and producers. This paper attempts to solve this problem by providing inputs directly by updating production through regular and timely operation of modern scientific inputs. The study identified the structural equation model to analyze the results of the analysis of descriptive statistical data, which resulted in the preferred cash financing for farmers as a desirable situation. However, farmers carry unpaid loans, achieve multiple losses faced by the bank, and make it give up its leading role in agricultural financing, and rely on other formulas with purely commercial outcomes. The new innovative financial model is suitable for developing agricultural finance in all countries of the world and making it more appropriate with the requirements of agricultural financing strategies put forward by countries and international institutions.
DISTRIBUTED COLLABORATIVE FRAMEWORK FOR DEEP LEARNING IN OBJECT DETECTION A THESIS IN Computer Science Presented to the Faculty of the University of Missouri-Kansas City in partial fulfillment of the requirements for the degree MASTER OF SCIENCE By SIRISHA RELLA

Object detection has gained much attention in recent years because of its ability to localize and classify the objects in videos and images that can be incorporated into many applications. Traditional object detection algorithms need substantial computational resources to build a model. There is an increasing demand for a practical approach to constructing object detection models adapted to the local context, limited computing resources, and application logics while supporting real-time inferencing without degrading accuracy and performance. In this thesis, we proposed a distributed-collaborative framework to build practical object detection models. The framework is based on a novel approach for collaborative group inferencing that is designed with a single-class-single-model mechanism for multiple objects in a distributed manner. For useful grouping, we made use of the intraclass correlation from existing models during inferencing. Results from the case studies with Pascal VOC 2007 and our data collected through Google Street View showed that the proposed model significantly improved performance while making it potentially suitable for customized application building with limited computing resources. A prototype for the proposed model has been built, and a neighborhood application has been demonstrated to validate the proposed work.