Miracle-dz/UniFAR-FTUs huggingface dataset:
A Structural Model of Health-Related Quality of Life Based on Parenting Stress and Spiritual Well-Being with the Mediating Role of Locus of Control in Parents of Children with Specific Learning Disorder

Background: Raising children with Specific Learning Disorder (SLD) is a stressful experience that may influence the Health-Related Quality of Life (HRQOL) of parents of children with SLD. Objective: The present study aimed to investigate the mediating role of locus of control in the relationship of parenting stress and spiritual well-being with HRQOL in parents of children with SLD. Materials & Methods: This is a descriptive cross-sectional study. The study population comprised all parents of children with SLD in 2020-21, among whom 174 parents were selected through convenience sampling. The research instruments included the SF-36 Questionnaire, Parenting Stress Index, the Spiritual Well-Being Questionnaire, and the Locus of Control Scale. The proposed model was evaluated using path analysis. Results: there was a significant relationship between spiritual well-being and HRQOL, locus of control and HRQOL, parenting stress and locus of control, and between spiritual well-being and locus of control (P<0.01). However, no significant relationship was found between parenting stress and HRQOL. Indirect paths of parenting stress were significantly correlated with HRQOL through the mediating role of locus of control and there was a significant relationship between spiritual well-being and HRQOL with the mediating role of locus of control (P<0.01). Conclusion: This study revealed that locus of control is a significant mediator in the relationship of parenting stress and spiritual well-being with HRQOL in parents of children with learning disorder.
Data Warehousing Methods and Techniques: A Survey of Literature to Identify Current Research Needs

-Data warehousing systems are backbone of decision making process for large business organizations. These systems provide strong platform for informed decision making in the current age of globalization and competitive environment. Effectiveness of data warehousing systems that are being developed is the result of continuous evolution and advancement in the technology. Though, immense research has been done in the past on this technology, still more research is required to further improve its quality and utilization. In this paper we have tried to present outcome of thorough reference of details of research efforts put up by various research groups in key areas of the technology like data warehouse modelling & design, ETL process designing, Business Intelligence (BI), data mining, data warehouse maintenance, and OLAP design. The objective of our study is to determine past sequence of advancements, current state of the art, and future course of research needs in this domain.
Deflection curve analysis on cable booms

To resolve such excessive boom deflection problems of large-tonnage crawler cranes as long-boom system lifting and extensive-range working conditions,the auxiliary cables are installed in boom systems to enhance the boom stability.By employing elastic stability theory for nonlinear analysis on cable boom systems,the boom deflection curve formula is deduced for variable section boom system.Therein,this approach will simplify the cable design with fast boom deflection curve calculation beneath any cable length and position.
An algorithmic framework for computational estimation of soil freezing characteristic curves

Many numerical models for simulating freezing and thawing phenomena of soil have been developed due to emerging geotechnical issues in cold regions. In particular, coupled thermo‐hydro‐mechanical (THM) analysis is used to evaluate complicated deformation, thermal, and moisture transport behavior of freezing–thawing soils. This study proposes a soil‐freezing characteristic curve (SFCC) that is robust and adaptive with various computational frameworks, including the THM approach. The proposed SFCC can also account for different soil types by incorporating the particle size distribution. Here an automatic regression scheme is adopted to update the SFCC associated with deformation and thermal changes. In addition, a smoothing algorithm is adopted to prevent a sharp change of the SFCC due to phase transition between the liquid water and crystal ice. Based on experimental works in the literature, the applicability of our model is demonstrated when the initial water contents and soil particle distribution differ. We further investigate the performance of the proposed SFCC as a constitutive model within a simplified THM framework. Our results show that the proposed model captures the desired behavior of different soil types in the freezing process, such as freezing temperature depreciation, the effect of compaction, and mechanical loading on unfrozen water content.
THE EFFECT OF ORGANIZATIONAL COMMITMENT, SERVANT LEADERSHIP, AND EMPOWERMENT ON EMPLOYEE PERFORMANCE WITH ORGANIZATIONAL CITIZENSHIP BEHAVIOR AS A MEDIATION AT REGIONAL GENERAL HOSPITAL dr. ZAINOEL ABIDIN BANDA ACEH

This study aims to examine the model of the influence of organizational commitment, servant leadership, and empowerment on employee performance, by utilizing organizational citizenship behavior (OC behavior) as a mediator. The study was conducted at the dr. zainoel Abidin (RSUDZA) in the city of Banda Aceh. The population is all medical and non-medical personnel, totaling 1029 people. Sampling using accidental sampling technique, to obtain as many as 288 people. The variable measurement scale used is the Likert scale. The research model was analyzed using Structural Equation Modeling (SEM) using Amos software. The results of direct hypothesis testing prove that commitment does not affect OC behavior, Servant leadership and empowerment affect OC behavior, commitment and empowerment have no effect on performance, servant leadership and OC behavior affect performance. The indirect hypothesis testing proves that OC behavior does not mediate the role of commitment on performance, and OC behavior partially mediates the role of servant leadership and empowerment on performance. This explains that the RSUDZA performance improvement model is a function of strengthening servant leadership, increasing empowerment, and strengthening OC behavior. This test result model can be an academic basis for future researchers in developing further research. For RSUDZA, this model can be used for making advanced management regulations to improve its performance. RSUDZA
Factors affecting the success of small and medium-size enterprises in southeast provinces

Small and medium-sized enterprises (SMEs) play an important role in socio-economic development, contributing significantly to GDP, creating jobs, and stabilizing the economy. Compared to other countries in the region and the world, Vietnamese SMEs still have many limitations in terms of scale and contribution levels and have not yet fully brought into play their full potential (Phung The Dong, 2019). However, recent studies indicate that SMEs are more likely to fail than large firms, even though they are often seen as important internal drivers of a country's economy (Bloch and Bhattacharya, 2016; Lo et al, 2016). According to Gnizy et al (2014), characteristics including: resource constraints, informal strategy, inflexible structure and lack of strategic planning processes may have contributed to the failure of surname. Recent studies suggest that if we can better understand why small and medium businesses fail, we should be able to increase the odds of success. However, it has proven extremely difficult to predict which factors will succeed and fail. This has recently become a hot topic because it has been difficult for researchers to explain and predict why some firms succeed and others fail (Olaison & Sorensen, 2014). In this study, the author has found out factors such as: Social responsibility, Government support, finance, management, marketing ability, access to technology innovation, have a positive impact on the success of SMEs in Southeastern provinces
Ziziphus: Scalable Data Management Across Byzantine Edge Servers

Edge computing while bringing computation and data closer to users in order to improve response time, distributes edge servers in wide area networks resulting in increased communication latency between the servers. Synchronizing globally distributed edge servers, especially in the presence of Byzantine servers, becomes costly due to the high communication complexity of Byzantine fault-tolerant consensus protocols. In this paper, we present Ziziphus, a geo-distributed system that partitions edge servers into fault-tolerant zones where each zone processes transactions initiated by nearby clients locally. Global synchronization among zones is required only in special situations, e.g., migration of clients from one zone to another. On the one hand, the two-level architecture of Ziziphus confines the malicious behavior of nodes within zones requiring a much cheaper protocol at the top level for global synchronization. On the other hand, Ziziphus processes local transactions within zones by edge servers closer to clients resulting in enhanced performance. Ziziphus further introduces zone clusters to enhance scalability where instead of running global synchronization among all zones, only zones of a single cluster are synchronized.
Dynamic contests with fatigue

We study experimentally symmetric “best-of-(2n − 1)” multi-stage contest series in which two players compete repeatedly until one of them wins n times. We introduce history dependence into the players’ probabilities of winning at a given stage, termed “fatigue. ” Fatigue materializes if a player’s total effort in previous stages is different from her opponent’s. We find that subjects react strongly to treatments with different parameterizations of fatigue. In contrast to the often reported burnout behavior, subjects strategically choose low levels of effort a significant portion of time. We also observe strong dependence of effort on the players’ standing in the series.
Evaluation of Transfer Learning for Mask Detection

The use of masks has become crucial in combating the Coronavirus pandemic. Unfortunately, the regulation of wearing a mask is not being upheld by many citizens which is contributing to the spread of the disease. To aid the efforts of regulations and to maintain safety in public areas, both large like parks or small like public transport, Artificial Intelligent systems can play a vital role. In this article, we explore the use of transfer learning across 5 models (Mobile Net V2, InceptionV3, Resnet50V2, VGG16 and DenseNet121) and measure their effectiveness in mask detection. Due to the lack of a large, diverse and annotated dataset, we explore the use of transfer learning using supervised methods and present the results of the experiments upon the Keras open-sourced models. We find an average of 99% accuracy for all 5 models. However, when we use K-Fold Cross Validation to account for bias, we find significant differences in results with the highest accuracy being achieved by VGG16 at 98.6%. With the mixture of the standard method of training and testing alongside K-Fold Cross Validation, we present our findings for the use of transfer learning for mask detection. © 2022. Zahin Akram, Arifuzzaman Arman, Mohammad Rakib Imtiaz and Syed Athar Bin Amir. This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
Implementing Defeasibile Datalog in RDFox

This literary review will centre around how one might implement the concept of nonmonotonicity and defeasibility into RDFox - a classical reasoner, written in C++, that is based on datalog - through the use of a defined algorithm that was designed to handle defeasibil-ity in databases. A high level background will be given concerning the relevant theory, as well as the tools to be used (i.e. datalog and RDFox). This will then be followed by a discussion about and explanation of the algorithm to be incorporated. Finally, there will be a discussion on similar work done in this field and on this particular topic. This review will not focus as much on the theoretical side of the implementation, as it will the computation and practical side of it - that is, the implementing of defeasibility in RDFox. However, if one requires more information on the theory, one could find it in this works partner lierature review, (Pownall and Meyer, 2018) [1].
NATURE-INSPIRED COLORS AND SHAPES IN CLOTHING DESIGN

Nature is an inexhaustible source of inspiration for fashion designers when it comes to colours, materials, textures and pattern of garments or accessories. Its suggestive potential, the infinite imaginative resources that nature forms generates and reveals alwyas remain relevant, continuously feeding the creative imagination. The flexibility of shapes, angles, overlays of volumes, all these we find in clothes, in prints, in the search of cutouts, in the way that many designers chose to put their mark on their fashion creations in order to harness the expressive language of human body. The purpose of this article is to offer models of clothing based on combinations of colors and shapes inspired bu natural sources. The colors used from natural sources and their values in the RGB color model were presented. Also, the procedure for obtaining a four-color wheel and the method for creating “rose” curves were described. Different geometric shapes based on the rose curve were defined. Based on he selected colors and the defined shapes, the design of 3 models of nature-inspired dresses was made in order to visualize how the proposesd colors and shapes will look in a completed garment, Discussion and a comparative analysis have been made with the results obtained by other authors.
Development and Demonstration of The WEC-Sim Wave Energy Converter Simulation Tool

The National Renewable Energy Laboratory (NREL) and Sandia National Laboratories (SNL) have developed WEC-­‐Sim to provide the wave energy converter (WEC) design community with an open-­‐source simulation tool. WEC-­‐Sim models the BLOCKIN BLOCKIN system BLOCKIN BLOCKIN dynamics BLOCKIN BLOCKIN of BLOCKIN BLOCKIN WEC BLOCKIN BLOCKIN devices BLOCKIN BLOCKIN using BLOCKIN BLOCKIN multi-­‐ body dynamics methods and simulates hydrodynamic forces using coefficients predicted from potential flow models. In this paper we describe the methodology used in WEC-­‐Sim and demonstrate the use of the code by simulating three WEC devices. Specifically, we model a two-­‐ body point absorber and two oscillating surge devices. For each device we describe how the WEC-­‐Sim model was setup and present simulation results, BLOCKIN BLOCKIN such BLOCKIN BLOCKIN as BLOCKIN BLOCKIN predictions BLOCKIN BLOCKIN of BLOCKIN BLOCKIN device BLOCKIN BLOCKIN motions BLOCKIN BLOCKIN and power production. For verification and validation purposes, results are compared to corresponding results from other modeling tools and experimental data. BACKGROUND AND MOTIVATION Open-­‐source numerical modeling tools have helped the wind energy industry achieve commercial viability by enabling the rapid development, analysis, and certification of wind turbine systems. The recent emergence of the WEC BLOCKIN BLOCKIN industry BLOCKIN BLOCKIN in BLOCKIN BLOCKIN the BLOCKIN BLOCKIN U.S. BLOCKIN BLOCKIN and BLOCKIN BLOCKIN across BLOCKIN BLOCKIN the BLOCKIN BLOCKIN globe BLOCKIN BLOCKIN has created a need for an equivalent set of WEC design and analysis tools to help advance WEC technologies. Device developers are currently relying heavily on commercial modeling tools, such as OrcaFlex, WaveDyn, and AQWA to meet their modeling needs. However, with the wide range of device archetypes currently being developed, and the fast pace of innovation in the WEC BLOCKIN
D3.8 Report on methods for security testing for variant and configurable systems

This deliverable reports the XIVT developments and achievements on security testing of variant and configurable systems. The first part contains an overview of the state-of-the-art in security testing with respect to those aspects which are most relevant to the techniques investigated within the XIVT project. The second part gives an overview of the security testing methods and tools developed in XIVT. Some of these methods are associated with specific use cases, others are agnostic to them.
Role of Development Finance Institutions in Developing the Nigerian Agricultural Sector .

This study investigates the role of development finance institutions (DFIs) in agricultural sector development in Nigeria. African Development Bank (AfDB), World Bank and International Development Association (IDA) were the underlying DFIs while agriculture value added formed the basis for measuring agricultural sector development. Data on the variables were sourced from World Development Indicators (WDI) and analyzed using error correction mechanism (ECM). The unit root test results indicate that all the variables are not stationary. However, they become stationary after first differencing and as such they all integrated of order one. The cointegration test results revealed that the variables have long run relationship. The result showed that the first and second lag of agriculture value added impacted negatively on its current. One-period lag of AfDB loan has significant positive relationship with current value of agriculture value added. The result showed that agriculture value added increased by 0.079 percent due to 1 percent increase in lag of AfDB loan. It was also found that the lagged values of World Bank and IDA loans exert significant negative impact on agriculture value added. The Parsimonious ECM revealedthat the model has an adjustment speed of 59.2 percent. Based on the findings, it is recommended that policymakers should prioritize the allocation of AfDB loans into productive sectors of the economy with particular emphasis on agriculture with a view to driving the development process in the real sector.
TCRM_A_347622 197..211

Background: Hypertension commonly co-exists with depression and is associated with adverse health outcomes. This meta-analysis aimed to examine whether combination treatment can improve the outcomes of patients with comorbid hypertension and depression. Methods:We searched for relevant randomized controlled trials (RCTs) published through July 2021 using PubMed, Web of Science, China National Knowledge Infrastructure, and Wanfang Data. RCTs on patients with an antihypertensive outcome and data on mean blood pressure differences were extracted for both intervention and control groups. Continuous and dichotomous measures of outcomes were pooled using weighted mean differences (WMD) and risk ratios (RR) with 95% confidence intervals (CI) by random or fixed effects. Subgroup and meta-regression analyses were performed to identify any existing heterogeneous sources. Results: A total of 27 RCTs with 2606 participants were included. Combination treatment significantly improved systolic blood pressure (SBP) by 11.27 mmHg (WMD = −11.27, 95% CI: −14.12 to −8.43), I = 95.4%), diastolic blood pressure (DBP) by 8.21 mmHg (WMD = −8.21, 95% CI: −10.73 to −5.69), I = 96.9%), and antihypertensive efficiency by 42% (RR = 1.42, 95% CI: 1.32 to 1.52, I = 0.0%) compared with in the control group. Combination treatment improved SBP and DBP levels in patients aged <65 years compared with those in patients aged ≥65 years (p = 0.020 and 0.007, respectively). Conclusion: Pooled evidence suggests that combination treatment significantly improves both blood pressure levels and antihypertensive efficiency in hypertensive patients with depression. Elderly patients with comorbid hypertension and depression may require a more collaborative approach to improve their outcome. Registration: PROSPERO registration number CRD42020213430. Registered on November 08, 2020.
PHENOLOGY, ARCHITECTURE, YIELD AND FATTY ACID CONTENT OF CHIA IN RESPONSE TO SOWING DATE AND PLANT SPACING

Chia is a new introduced genotype from North of Guatemala and Central Mexico, used as a raw material in producing supplements, beverages, medicine and processed foods because its high content of polyunsaturated fatty acid (PUFA) omega-3 in its oilseed. Yield and quality traits can be maximized with the successful establishment. In order to successfully cultivate chia under climate conditions of Egypt, the critical factors of cropping system; sowing date and plant spacing, were the main impetus for this study. Four sowing dates from 15 September (SD1) to 1 November (SD4) with 15 days’ interval and two plant spacing 30 (PS1), and 40 cm (PS2) were conducted at the Experimental Farm of Faculty of Agriculture, Tanta University (30 47′ N: 31 0′ E) during seasons of 2017/2018 and 2018/2019. Results indicated that the length of each phenological stage and total life period differed among sowing date and spacing treatments. The sowing date of 1 October (SD2) provided better climatic conditions that recorded highest seed yield ha, harvest index and oil yield ha with high PUFAS level as well as acceptable contents of protein, fiber, carbohydrates and ash. Sown plants at PS1 showed higher seed and oil yield ha than PS2. Our results revealed that SD2×PS1 was the best treatment generated maximum seed yield ha, oil yield ha, high content of PUFAS, maximum ω3: ω6 ratio as well as achieving higher harvest index. Results revealed that the environment in 30 47′ N: 31 0′ E provide good conditions for growth and development of chia and 1 October (SD2) with 30 cm plant spacing (PS2) are recommendable for chia cultivation under this zone.
R eal -T ime C omputational I ntelligence P rotection F ramework A gainst A dvanced P ersistent T hreats

An Advanced Persistent Threat (APT) is a set of stealthy and continuous computer hacking processes in which an unauthorized person gains access to a network and stays there undetected for a long period of time. The “advanced” process sig-niﬁes sophisticated techniques using zero-days malware to exploit vulnerabilities in systems. The “persistent” process suggests that an external command and control sys-tem is continuously monitoringand extracting data from a speciﬁc target. The “threat” process indicates human involvement in orchestrating the attack. APT attacks target organizations in sectors with high-value information, such as military networks, national defense, manufacturing and the ﬁnancial industry. Traditional digital security mechanisms face such vulnerabilities in a conventional manner, they create often false alarms and they fail to forecast them. As APT activities are stealthy because they use Tor anonymity network, the command and control network tra ﬃ c associated with APT can be undetected at the network layer level. Deep log analyses and log correlation from various sources cannot be useful in detecting APT activities and network agents are not able to collect logs TCP ( Transfer Control Protocol ) and UDP ( User Datagram Protocol ) directly from assets into a syslog server. This paper proposes an innovative fast and accurate Real-time Computational Intelligence Protection Framework against Advanced Persistent Threats (CIPFaAPT). It is about an automate forensic analysis system that uses Online Sequential Extreme Learning Machines. It can process millions of data points in real-time, establishing, or learning a “normal” baseline, comparing data points to past behavior and
Application of wavelet soft-threshold de-noising and GRNN in monthly load forecasting

Based on the de-noising theory of wavelet soft-threshold and the general regression neural network (GRNN), according to the property of increase trend and seasonal fluctuation of monthly history load, the paper proposes a new monthly load forecasting model. First, it de-noises data of load using wavelet soft-threshold and uses the horizontal and vertical de-noised history data as input of GRNN building the monthly load forecasting model. Then the new model is applied to forecast monthly load of somewhere. The forecasting result shows that it has good robustness and practicality as well as high precision.