Miracle-dz/UniFAR-FTUs huggingface dataset:
Employees’ Perception Towards the Implementation of Corp- orate Governance Principles: An Egyptian Perspective

The objective of this study is to examine how employees perceive corporate governance in their organisations and to explore the position that employees can take in the promotion of corporate governance in the Egyptian context. It empirically examines the employees’ perception towards corporate governance using a 5-point Likert-type questionnaire that was administered face to face and online. Despite the fact that some employees lack proper knowledge about the issues of corporate governance, the findings were encouraging as the majority of employees have emphasised its importance. The results of this study can be beneficial in developing a better understanding about corporate governance within different Egyptian institutions and in promoting the importance that employees can play in implementing
Pain Neuroscience Education Delivered by a Student Physical Therapist for a Patient with Persistent Musculoskeletal Pain

Patient: Female, 65-year-old Final Diagnosis: Fibromyalgia • neck pain radiculopathy • rotator cuff injury bilaterally Symptoms: Chronic pain Medication: — Clinical Procedure: Manual therapy • pain neuroscience education Specialty: Rehabilitation Objective: Unusual or unexpected effect of treatment Background: Persistent pain is one of the most common reasons individuals seek healthcare in the United States, costing $635 billion annually. At present, the medical literature outlines many treatments for persistent pain. Pain neuroscience education (PNE) is described in the literature as an educational intervention for patients with persistent pain that can be applied by a physical therapist. There is limited research on the application of PNE by a student physical therapist; however, this case report offers a unique opportunity to examine outcomes for this intervention when applied by a student physical therapist in conjunction with manual therapy and therapeutic exercise. Case Report: This case report examined the outcomes of PNE for a 65-year-old patient with a long-standing history of low back, cervical, shoulder, knee, and foot pain. Interventions included 7 sessions of PNE over 4 weeks delivered by a student physical therapist, in combination with manual therapy and exercise prescribed by a licensed physical therapist. Outcomes measured were fear avoidance belief questionnaire, visual analog scale, Tampa scale of kinesiophobia, neurophysiology of pain questionnaire, neck disability index, and Oswestry disability index. Conclusions: Outcomes included clinically significant decreases in subjective pain level, and kinesiophobia; however, there was only a minimal decrease in fear avoidance and no decrease in perceived disability. This case report provides preliminary evidence that positive outcomes can be achieved when PNE is delivered by a student physical therapist combined with manual therapy and therapeutic exercise from an expert clinician for patients with persistent musculoskeletal pain.
Effect of winter wheat cover cropping with no-till cultivation on the community structure of arbuscular mycorrhizal fungi colonizing the subsequent soybean

ABSTRACT Winter cover crops increase the amount of indigenous arbuscular mycorrhizal fungi (AMF) in the soil, providing beneficial effects such as enhancement of phosphorus uptake by the subsequent crop. However, its impact on the AMF community structure is not well understood. In the present study, we aimed to reveal the effect of winter wheat cover cropping with no-till cultivation on the AMF community structures in soil and roots of the subsequent soybean. For this purpose, we conducted a field experiment consisting of two treatments, no-till soybean cultivation after winter wheat cover cropping (NTWC) and conventional soybean cultivation after winter fallow management as a control (CONT). At the flowering stage of soybean, higher AMF colonization of soybean roots was observed in the NTWC plots compared with the CONT plots. Additionally, aboveground biomass and phosphorus uptake of soybean in the NTWC plots were significantly higher than those in the CONT plots. Molecular community analyses based on PCR-denaturing gradient gel electrophoresis (DGGE) of AMF 18S rRNA genes indicated that the AMF community structures in the soil and soybean root of the NTWC plots were clearly different from those of the CONT plots. The DGGE profiles showed that the wheat cover cropping preferentially increased some phylotypes belonging to Glomeraceae and Claroideoglomeraceae. In addition, most of the phylotypes were characteristically observed in the subsequent soybean root of the NTWC plots, strongly suggesting that these phylotypes colonizing the cover crop wheat were taken over by the subsequent soybean. Our study revealed the significant effect of winter cover cropping with no-till cultivation on the structure of AMF community colonizing the subsequent soybean.
Key Node Identification Method for Aviation Network Based on Support Vector Machines

: Accurately identifying the key nodes of aviation network through technical means has important theoretical significance and reference value for the normal operation of aviation network in peacetime and defense and repair in wartime. A key node identification method based on Support Vector Machines (SVM) is proposed. Firstly, it evaluates the comprehensive importance of nodes based on analytic hierarchy process (AHP). Then, it selects three simple indices and establishes the importance evaluation model based on the mapping relationship between simple indices and comprehensive importance of SVM. The simulation on American aviation network indicates that it can obtain satisfactory identification effect
Effective macrophage delivery using RAFT copolymer derived nanoparticles

Reversible addition fragmentation chain transfer (RAFT) polymerisation provides a highly controlled means to assemble copolymers of different architectures for a variety of applications, including drug delivery. Polymers consisting of a butyl methacrylate-co-methacrylic acid p(BMA-co-MAA) hydrophobic block and a poly(ethylene glycol) methyl ether methacrylate p(PEGMA-475) hydrophilic block were synthesised via RAFT polymerisation and self-assembled into micelles. A range of micelle particles of different sizes were obtained by varying the composition of the block copolymers. The micelles were crosslinked to form nanoparticles and fluorescently labelled to study cellular internalisation. The prepared nanoparticles were extensively taken up by primary murine macrophages and a promising candidate was identified. To demonstrate effective delivery of a cell impenetrable cargo a fluorescent dye, 4′,6-diamidino-2-phenylindole (DAPI), was encapsulated inside the nanoparticles and successfully delivered to macrophages. The nanoparticles’ stability at increased temperatures and at low concentrations, the tunability of their synthesis and their extensive internalisation by macrophages and performance makes them highly promising delivery vehicles for a range of therapeutics and imaging agents.
Research and Method for In-line Inspection Technology of Girth Weld in Long-Distance Oil and Gas Pipeline

With the increasing demand for energy, long-distance oil and gas pipeline has become the main mode of transportation of oil and gas resources. High pressure, inflammable and explosive medium, complex and changeable route environment and other factors make the safe transportation of pipeline concerned. The girth welds of oil and gas pipeline have always been the weak part of the pipeline due to the technical level during the construction, on-site welding practices and operation environment, and the girth weld cracking is one of the main failure forms of oil and gas pipeline. It is an effective way to ensure the safety of pipeline to adopt various advanced and targeted inspection to identify pipeline defects, judge the types of defects, and then carry out safety evaluation and maintenance. This paper analyzes the main failure factors of girth weld of oil and gas pipeline, and systematically summarizes the content and methods of various in-line inspection on girth weld in view of these failure factors, so as to provide reference for the development and application of in-line inspection technology on girth weld of oil and gas pipeline.
A Generalized Long-term Load Forecasting Model Using Modified Grey Wolf Optimization Algorithm

Annual accurate predicting is important for long-term planning of the electricity company because it always seeks to achieve the reliability and sustainability for the electrical services. The process of long term load forecasting (LTLF) is implemented in several manners depending on random variables affecting the consumption of the load. This paper introduces two different strategies that have been utilized for annual electrical peak load (PL) for Jordan. The first strategy used in this paper is based on different historical features gathered form national electric power company (NEPCO) such as (population growth, the gross domestic product of the country and the historical annual PL). The second strategy is based on the historical electrical peak load only. The work includes a comparison process using three different optimization algorithms particle swarm (PSO), grey wolf (GWO) and modified grey wolf (MGWO-based on the concept of aligned) to train a feed forward neural network (FFN). The proposed MGWO-FFN gives the best results of both the twostrategies than GWO-FFN and PSO-FFN. Results of the two strategies are presented and indicate the superiority of the second strategy on the first one.
Identification and compensation of stiffness and damping between short and long stroke in wafer stage

The disturbance of cable force is an important aspect that should be taken into account for precision motion systems involved in CNC machine tools, wafer scanners, etc. In this paper, unlike paying attention to the cable force loaded on long stroke in previous works, the disturbance between long and short stroke had been analyzed in details. To minimize the disturbance force loaded on short stroke of motion system, a disturbance model identification and the corresponding compensation approach method was proposed. A two-step identification in frequency domain was developed such that the parameters of stiffness and damping between long and short stroke can be estimated. Then a state feedback method using ESO and estimated parameters had be applied to compensate the disturbance, which improved the servo performance of short stroke significantly. Finally, the effectiveness of the proposed method is illustrated through numerical simulation.
Effect of beam oscillating pattern on laser welding of steel to PMMA

Laser welding of 1 mm-thick steel and PMMA was employed via beam oscillating. Three modes of beam oscillation, transverse, longitudinal and circular were explored. Due to the stirring effect, the beam oscillation improves the weld formation and promotes the flow of bubbles in the molten layer. The circular oscillation gives the strongest weld homogeneous without overheat discoloration defect. The bonding strength was 38% more than the weldment without beam oscillation. The weld strength improvement was attributed to the variation of the oscillating speed varies the time-frequency distribution of the beam energy. This technology reduces the morphological defects and increases the uniformity of the weld. The improvement mechanism of beam oscillation on bubble behavior and melt flow behavior is also discussed.
Mobile Robot Position Estimation using Milstein Algorithm

Stochastic differential equation (SDE) became a very important mathematical tool in modeling and performance analysis of many systems due to the white noise appeared in them. one of the significant problems is the time delay problem which appeared in many teleoperated systems which has a significant effect in the system performance. The target in this paper is to approximate the mobile robot future position to decrease the time delay in teleoperation. As a result of white noise, heading angle equation of the mobile robot will be converted into a SDE. The approximated solution has been improved by using a higher order of convergence numerical algorithm (Milstein algorithm) with order of convergence equal one for better estimation of future position of mobile robot. The error has been decreased in many parts of the robot path. A simulated results and a comparison between the two numerical algorithms are explained.
Measurement method of pillow spring based on machine vision

In the current maintenance of pillow springs of railway freight cars in our country, the measuring method of manually using measuring scale and measure gauges is still common. In order to improve the quality and efficiency of the pillow spring measurement, and to support the automatic upgrade of the pillow spring maintenance line, a new method for measuring the size of the pillow spring based on machine vision is proposed. By analyzing the requirements and characteristics of pillow spring detection and matching, a visual measurement system was designed to replace manual measurement, and openCV was used for image processing, feature extraction and size calibration. Compared with manual measurement, the measurement accuracy and efficiency of this method are higher. Experiments were conducted under different lighting conditions, and the measurement results have good repeatability and stability, indicating that the method has good robustness to the light intensity of the pillow spring environment.
Surface Defects Detection of Car Door Seals Based on Improved YOLO V3

At present, the surface defects of car door seals are generally detected by manual operation, which is inefficient and costly. This paper presents a new detection method to find the surface defects of car door seals with the application of modified YOLO V3 algorithm. Firstly, the K-means clustering algorithm was employed to analyze the number and size of the candidate box of the target detection. Then, the feature pyramid was constructed in the first module of the trunk feature extraction network. Finally, the attention mechanism SE module was added in the output part of darknet53 and two feature gold towers extraction network of the trunk feature. The improved YOLO V3 algorithm was carried out on the defect data set of automobile door seals. The results indicate that compared with the original YOLO V3 algorithm, the improved YOLO V3 mAP reaches 52.71%, increasing by 3.28%.
Modeling and Simulation of the Google TensorFlow Ecosystem

Recently, many powerful machine learning (ML) systems or ecosystems have been developed to render ML solutions feasible for more complex applications. Google TensorFlow ecosystem is one of the most famous and popular machine learning ecosystem. Because of some emerging technologies, such as big data, Internet of Things (IoT), high-performance computing (HPC), the power of datacenters are expected to be applied in Artificial Intelligence (AI) field. However, when performing ML tasks in datacenters, new challenges and issues arise, such as data management. Understanding the behaviors of the Google TensorFlow ecosystem is our main objective. We adopt the reference architecture method and extend our reference architecture created in our literature survey. We add additional deeper layers and identify more than 10 new components to enrich our reference architecture. Based on the reference architecture, we create a predictive model of Google TensorFlow and integrate it into a discrete event simulator OpenDC. We design simulation experiments to validate our model and evaluate the performance of the TensorFlow ecosystem in HPC environments.
The Conceptual Framework for Development of Quality of Life Assessment in Stroke Patients According to Icf Model: Narrative Review

The incidence of stroke was increasing worldwide. The complications following stroke affected the quality of life (QOL) in stroke patients. The QOL is an important indicator which provided an information of succeed in treatment plan. Since an International Classification of Functioning, Disability and Health (ICF model) was created as a framework for the measurement of functional disability that is utilized among physicians, nurses and rehabilitation-related allied health professionals to develop a more comprehensive treatment plan, it was lacking of QOL assessment aspect. Hence, added QOL assessment in ICF model could be an effective tool which promotes an effective treatment plan. Moreover, no available study which use ICF model outcome able for reflect all domains of QOL in stroke patients. The present study aims to introduce a conceptual framework that is compliant with ICF model for the development of the assessment in which outcome is able to reflect all domains of QOL. Results There were various available QOL assessment such as General HRQOL questionnaire and Specific HRQOL questionnaire. However, among those available QOL assessment tools, they still incomplete to represent the QOL of stroke patients. Therefore, we provided a new conceptual framework for cover all QOL aspects. The information provided in the present study could be beneficial for a healthcare provider in their treatment plan which leads to an effective treatment plan to improved QOL in stroke patients. Conclusion, A conceptual framework for QOL assessment in stroke patients that cover all aspects of life as stated by the ICF model in which measuring outcomes able to aid better treatment planning and yield an effective rehabilitation outcome.
Combine to Conquer: Innovations in the Use of

The Brazilian Network Information Centre (NIC.br) is a non-profit civil entity created in 2005 to implement the decisions and projects designed by the Brazilian Internet Steering Committee (CGI.br). As part of its portfolio, NIC.br conducts annual surveys of the companies with 10+ employees operating in Brazil. The ICT Enterprises survey on the use of Information and communication technologies in Brazilian enterprises (ICT Enterprises) aims to measure presence of information and communication technologies (ICT) in the companies with 10+ employees, covering topics such as infrastructure, use and appropriation by the private sector of new technologies, as well as perception of potential benefits of these to their activities.
Structural equation model evaluating the impact of isolation and workfamily conflict on burnout among teleworking professionals

The study of structural equation model evaluating the impact of isolation and work-family conflict on burnout among teleworking professionals aimed to scrutinize and investigate the casual relationship among isolation, work-family conflict and burnout. The research utilized a 2-step structural equation modelling technique based on review of related literature. The population and samples were selected from teleworking professionals in Thailand. Research tools were questionnaire with rating scales and a convenience sampling method was applied. The model fit, reliability and validity were analysed by using a confirmatory factor analysis. A causal relationship was analysed by structural model and path analysis. The results showed that the model was moderately fitted with empirical data and had an acceptable reliability and validity. The results yielded a positive direct effect of isolation on burnout. Moreover, work-family conflict acted as a partial mediator or indirect effect on the relationship between isolation and burnout. Based on these results, the organization should emphasize on employee work-life balance aspect even in a teleworking environment to mitigate work-family conflict risk. Furthermore, supervisors or managerial level employees should focus on communication among their subordinates even if they are working out of the office to mitigate isolation risk. Future research should be qualitative or mixed method to delve deep down for a richer qualitative interpretation and cohort or longitudinal research should be done in order to study these effects in the long run. © 2021 Kasetsart University. Article Info Article history: Received 17 March 2020 Revised 23 May 2020 Accepted 2 June 2020 Available online 31 July 2021
Understanding Siamese Networks for Visual Object Tracking

Visual tracking of an arbitrary object has drawn great attention in the computer vision community for years. Visual object tracking methods based on Siamese networks achieved state-of-the-art results with balanced accuracy and speed in the past few years. Understanding those trackers may shed light on future research on this topic, which makes it no less important than just incrementally improving the performance of the trackers. In this report, we give a comprehensive analysis of multiple representative trackers based on Siamese Networks. Speciﬁcally, we depict the developments of Siamese networks in visual object tracking from the earliest one Siamese-FC to the lat-est ones. Besides, we give both quantitative and qualitative analysis of the performance and discrimination power of Siamese networks based trackers, by evaluating them on several canonical tracking benchmarks including VOT and OTB datasets and visualizing feature maps. We also identify several causes of failures. Some future research directions are proposed in the end.
Representing the Unknown in Speci(cid:12)cation

During the operation of software-controlled physical system, there are times when the values of environmental variables are not known by the control software. To correctly specify and reason about such systems, a spec-i(cid:12)cation language must allow variables to take a special unde(cid:12)ned value that signi(cid:12)es that the value of the variable is unknown. Adding an unde(cid:12)ned value to the type system of a language, however, complicates the semantics of the language because it causes many of the arithmetic operators to become partial functions. In this paper we discuss di(cid:11)erent approaches to managing unde(cid:12)ned values and present our approach for the speci(cid:12)cation language RSML (cid:0) e . We provide a loose semantics that allows simulation/execution of incomplete models, and a tight semantics, which, given a completed model, is used for code-generation and static analysis. To prevent misuse of unde(cid:12)ned values, we present a test that ensures that predicates in RSML (cid:0) e cannot evaluate to unde(cid:12)ned, and that variables cannot implicitly take on unde(cid:12)ned values.