Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the Factors affecting service quality of Zain Mobile subscribers in Albaha, Saudi Arabia

This study examines different service quality factors that may influence customer satisfaction towards Zain Company in Saudi Arabia. Moreover, this research tries to know the impact of these elements on SQ. Retail Service Quality Scale (RSQS) was used to collect primary data. The sample was collected by implying quota sampling technique. A sample of 970 questionnaires were filled by the Zain mobile subscribers’ in Albaha region. Out of all the received questionnaires, 891 completely filled questionnaires were finally included for the study. AMOS software was used to investigate the data using Structural Equations Modelling (SEM) analysis. It was found that three factors significantly impact SQ. these factors firstly Physical Aspect, then Problem solving and lastly Policy. Whereas two factors namely Reliability and second Personal interactions were found to be highly insignificant factor. This nonconformity of results occurred may be because of the social limitations in Saudi Arabia. Therefore there is a necessity to further examine as to why subscribers in Albaha region are less concerned in socialising and communicate with the retailer.
Inter-Task Association Critic for Cross-Resolution Person Re-Identification

Person images captured by unconstrained surveillance cameras often have low resolutions (LR). This causes the resolution mismatch problem when matched against the high-resolution (HR) gallery images, negatively affecting the performance of person re-identification (re-id). An effective approach is to leverage image super-resolution (SR) along with person re-id in a joint learning manner. However, this scheme is limited due to dramatically more difficult gradients backpropagation during training. In this paper, we introduce a novel model training regularisation method, called Inter-Task Association Critic (INTACT), to address this fundamental problem. Specifically, INTACT discovers the underlying association knowledge between image SR and person re-id, and leverages it as an extra learning constraint for enhancing the compatibility of SR model with person re-id in HR image space. This is realised by parameterising the association constraint which enables it to be automatically learned from the training data. Extensive experiments validate the superiority of INTACT over the state-of-the-art approaches on the cross-resolution re-id task using five standard person re-id datasets.
Rapid DNA extraction protocol from soil for polymerase chain reaction‐mediated amplification

A simple and rapid method of DNA extraction from soil was developed and DNA was made suitable for subsequent efficient amplification by the polymerase chain reaction (PCR). Key features of the extraction and purification were cold lysozyme- and SDS-assisted lysis with either freezing-thawing or bead beating, cold phenol extraction of the resulting soil suspension, CsCl and KAc precipitation and, finally, spermine-HCl or glass milk purification of DNA. Crude DNA preparations contained 4–20 μg DNA per g of soil extracted, and at least 50% of this was recovered in the final purified DNA preparations. The resulting DNA was pure enough to be restricted by various enzymes, and was amplifiable at concentrations of up to 20 ng of soil-derived DNA per 50 μl reaction mix. Amplification of a 683 bp target sequence, pat, was performed with different Taq DNA polymerases. Application of the protocol enabled us to detect target DNA derived from roughly 103 introduced Pseudomonas fluorescens (RP4 :: pat) cfu per g of soil. The fate of an introduced population in the soil could be followed to this limit with PCR-assisted detection of target DNA. In addition, target DNA was detected in soil 5 months after release, when the introduced organism was no longer detectable on selective agar plates. The extraction and purification protocol applied to various different soil types resulted in DNA of sufficient purity to permit amplification by PCR.
Molecular biology of plant laccases in relation to lignin formation

The lack of monocot laccase sequence data has been held as an argument against laccases playing a role in lignin polymerization. This overview focuses on plant laccase molecular biology in relation to lignin formation with emphasis on recently cloned monocot laccases from ryegrass (Lolium perenne). Laccase is found within the major seed plant groupings. Furthermore, as laccases have probably been duplicated before and after division into monocots, dicots and gymnosperms, it is hypothesized that all higher plants encode a multitude of laccases. Work published during the past decade indicates the existence of a strong relationship between laccase expression and lignification in several plant species. Likewise, analysis of the first plant laccase promoter shows that this laccase is putatively regulated by a group of transcription factors that have been shown to regulate several enzymes of the phenylpropanoid pathway. It is suggested that laccases may also serve other roles than participation in lignin formation in plant biology.
Questions Generation for Reading Comprehension Using Coherence Relations

The present scenario requires a large amount of digital content in the context of forums, directories, videos, classes, etc. Questions can thus play a significant role in digital media by quizzes, questions. Producing Question is the job of automatically producing questions from natural language, acting as one of the main fields of natural language human-computer interaction. we focus on generating fact-seeking, questions using the knowledge base. We implemented a system that takes a reading comprehension text as input and outputs all questions for the selected domain. Our system makes the GQ process threestage. 1. Content selection selected for question generation 2. Question formation (content transformations to get the question), 3. Evaluate the quality of generated question. The framework system is implemented as an end-to-end system that expects a human to specify a topic. The resulting output is a set of questions in natural language, that Follows the input domain. We show the effectiveness of our approach with previous Heilman and Smith MH method.
SIMULATION OF GROWTH AND MORPHOLOGICAL DEVELOPMENT OF MAIZE UNDER CONTRASTING WATER REGIMES

The use of crop growth models for resource management decisions such as weed control will require the detailed simulation of plant structures and functions in order to determine crop response to resources. A crop growth model was constructed on the computing facility at the National Center for Supercomputing Applications which was intended to simulate the effect of changing water status on plant growth processes. The model was tested against field data collected during an experiment in which the morphology of a maize crop growing under an imposed water deficit over a shallow water table was compared to that of an irrigated control treatment. The effects of this deficit on soil and canopy water status, leaf tip appearance, and on the distribution of growth with node number were compared for the simulated and recorded data. The use of simple equations describing the partitioning of growth to successive nodes enabled reasonably accurate estimates to be made of the distribution of leaf, sheath and internode m.
Nickel and rubidium uptake by whole oat plants in solution culture

Nickel and rubidium uptake by oat plants (Avena sativa L. cv. Victory) were examined in relation to solution temperature, solution concentrations, metabolic inhibitors, anaerobic root conditions, transpiration and time. Over a 4-h period, uptake rates for both Ni2+ and Rb+ remained constant at 23°C. Decreasing temperatures to 2°C, 20 μM concentrations of 2,4-dinitrophenol (DNP), or anaerobic root conditions decreased Ni2+ and Rb+ uptake rates by 97 to 86% in whole plants. Treatment of excised roots with 20 μM DNP decreased Ni2+ uptake by 93%. Nickel and Rb+ uptake rates measured as a function of the external solution concentration followed a typical parabolic curve. Km (0.012 mM) and Vmax [2.72 μmol (g dry weight)-1 h-1] values for Ni2+ were nearly 7 times lower than those for Rb+ [0.09 mM and 19.2 μmol (g dry weight)-1 h-1]. In all experiments, Ni2+ and Rb+ showed qualitatively similar uptake patterns, but Rb+ uptake was quantitatively more sensitive than Ni2+ to experimental manipulations.
Florística e estrutura da vegetação arbustivo-arbórea do sub-bosque de um povoamento de Eucalyptus grandis W. Hill ex Maiden em Viçosa, MG, Brasil

The objective of the present study was to analyze the floristic composition and structure of tree-shrub vegetation in understory of Eucalyptus grandis W. former Hill Maiden, Paraiso Forest Reserve, Vicosa, MG. Forty adjacent 5 x 5 m plots were demarcated and arranged in 5 x 50 m transects, in which individuals were measured, identified and classified in relation to seed dispersal syndromes and successional categories. Eight hundred and eighty four individuals belonging to 50 species and 22 families were recorded. The species with the highest Importance Value were Psychotria sessilis, Siparuna guianensis and Erythroxylum pelleterianum, particularly with regard to high density. Late secondary species with zoochorous dispersal syndromes prevailed in density. The founded floristic richness can be considered high for a Eucalyptus grandis understory and reflects the potential for using the species as catalyst for native tree-shrub vegetation in degraded areas.
Smart Irrigation and Management of Cash Crops using IoT

Smart Irrigation systems are helpful, particularly for the individuals who travel. Whenever introduced and modified legitimately, they can even spare our cash and help in water protection. Dead yard grass and plants should be removed and that can be costly however the investment funds from programmed water system frameworks can go past that. Watering with a hose or with oscillator squanders water. Programmed water systems frameworks can be customized to release increasingly exact measures of water in a focused zone, which advances water protection since the sending and utilization of wired frameworks in remote zones is generally unfeasible because of mind-boggling expenses, remote is the best arrangement. In this study,a solution to demonstrate the feasibility of Automatic Irrigation and continuous monitoring system especially for cash crops is proposed. We have connected the field sensors to the Internet through Wi-Fi or Ethernet or Modem and controlled via a web page which is accessed using the Static IP address. The Field side irrigation controller node is composed of a NodeMCU, sensors and solenoid valves. The sensing parameters can be displayed as values in the web server and continuous monitoring can be done through PC, Laptops and Android Phone
Point Cloud Components Tools for the Representation of Large Scale Landscape Architectural Projects

Point clouds represent a digital collection of three-dimensional coordinates or points that can have additional metadata associated with each point (WHITE 2013). Advancements in the field of reality capture technology are transforming the process of obtaining digital spatial data of our environment (ERVIN 2003) but the application potential of these reality based datasets has many prospects which need to be explored (GRUEN 2009).
Define the Factors Affecting the Shift to Cloud Computing in Malaysian Universities

Cloud computing is the way to increase capacity without vital investment in new infrastructure, training new personnel, or licensing new software [1]. As higher educational sectors are under growing pressure, and to provide more for quality education [2] in the current financial crisis and the increasing need, universities can utilize the potential benefits of cloud computing to provide improved services with few resources [3]. This paper presents a comprehensive study on the obstacles and advantages in cloud computing which affected at shifting to cloud computing services in Malaysian universities, and comparison of this present research results with the previous studies.
Correlation between Tourniquet Duration and Reactive Hyperemia in the Upper Limb

The physiological reaction of postocclusive local reactive hyperemia is regulated by neurovascular mechanisms and it reflects the function of microcirculation. Thermoregulatory changes occur first, in the form of increased skin surface temperature, which is usually followed by an increase in local blood flow. This study investigated a correlation between tourniquet duration on the upper arm, and the appearance of reactive hyperemia in the distal parts of the upper limb. Changes were registered with infrared thermometer and infrared thermography, which provided us a highly precise view of distribution of reactive hyperemia. Changes of oxygen saturation of peripheral arterial blood and blood pressure were also recorded. Our research has shown that longer duration of tourniquet leads to more intense and longer lasting reactive hyperemia in the palmar region, followed by higher temperatures of the skin surface, without any changes in postocclusive values of SpO2.
Isolation and characterization of a cinnamoyl-CoA reductase gene from perennial ryegrass (Lolium perenne)

Summary Cinnamoyl-CoA reductase (CCR, EC 1.2.1.44) catalyses the conversion of hydroxycinnamoyl-CoA thioesters to cinnamaldehydes at the entry point to the monolignol-specific branch of the lignin biosynthetic pathway. A gene encoding CCR in perennial ryegrass ( LpCCR1 ) was isolated and fully sequenced. LpCCR1 contains five exons of similar sizes to other CCRs and four introns in conserved positions. The 5′ untranslated region contains motifs common to lignin biosynthetic genes. LpCCR1 is present as a single copy gene and maps to LG7 in perennial ryegrass. LpCCR1 is constitutively expressed, is stimulated by mechanical wounding, and transcript abundance in stems increases with maturity.
Evaluation of Paintball, Mark–Resight Surveys for Estimating Mountain Goat Abundance

Abstract We evaluated mark–resight estimates of mountain goat (Oreamnos americanus) abundance using paintball marks at Seven Devils and Black Mountain, Idaho, USA. We marked mountain goats with recreational paintball equipment fired from a helicopter. Blue-violet dye marks were difficult to distinguish from dark, soiled areas on goats, while orange, yellow, and red oil-based paint marks were easily recognized, highly visible, and persisted for at least 71 days. Marking rates varied with equipment function and pilot effectiveness and ranged between 6.3 and 14.6 goats marked/hour of flight time. Precision of abundance estimates was reasonable with mark samples ≥51% of N̂. We analyzed a 3-occasion survey at Black Mountain using Program MARK to determine the likelihood and magnitude of potential sources of bias. Model Mb, which allows a behavioral response to capture, was best supported by the data, while model Mt, which allows time-varying capture probabilities, had reasonable support. The pattern of time-varying capture probabilities likely was a by-product of trap-shy behavior. Model Mb was 3 times more likely than model Mt to be the best approximating model, given the data. Behavioral response to marking and time-varying capture probabilities can be accommodated with >2 survey occasions. However, the strong evidence for a behavioral response implies that Lincoln–Petersen estimates of abundance are inappropriate. The set of candidate models did not include a model that would accommodate heterogeneity of individual sighting probabilities, which remains a concern with the mark–resight approach.
THE EFFECTS OF TECHNOLOGY, ORGANISATIONAL, BEHAVIOURAL FACTORS TOWARDS UTILIZATION OF E-GOVERNMENT ADOPTION MODEL BY MODERATING CULTURAL FACTORS

In the new knowledge-age economy, which revolutionary changes in science and technology have buttressed, information and knowledge have become critical elements in economic competitiveness and developing countries must engage in more active roles in formulating national policies and strategies promoting an information economy to garner benefits via economic and social growth development. E-Government is believed to play a fundamental role in achieving these ends. This study objective are to examines factors associated with the adoption of B2G e-government in Iraq and to determine the impacts of its adoption on these businesses by examining the effects of technology, organisational, and behavioural factors towards the utilization of the E-Government Adoption Model among Iraqi Business Organizations using moderating cultural factors in a quantitative exploratory approach. The study utilized listed on the Iraq Stock Exchange including banking, insurance, investment, and service and industrial companies, hotels, and corporate communications sectors. The results of hypothesis testing show several significant relationships such as relative advantages, Compatibility, Security, Management Support, Performance Expectancy, Perceived Usefulness on e-government, and Ease of Use by moderating uncertainty to e-government, IT Infrastructure by moderating language on e-government adoption.
Impact of Surface Mesh Simplification on Hemodynamic Simulations

In this paper we present an approach to quantify the effect of triangular surface simplification on hemodynamic modeling. This work is organized in three parts. First, we briefly present the basic concepts inherent in hemodynamic modeling. Then, we describe the approach of triangular surface simplification. The simplified triangular surfaces are used as input as well as a parabolic inlet velocity profile to the hemodynamic modeling procedure. As a validation, the third part will be focused on two examples carotid blood flow characterization for a healthy patient and one with stenosis in the carotid artery. We quantified the differences between the generated models by evaluating the eucledean similarity, rate of change and RMSE between the measured and modeled velocity obtained with different mesh densities. We conclude with the important effect of re-meshing on the modeled results and we propose a minimum threshold of facets which ensures a good simulated velocity profile with a minimum error rate.
A FRAMEWORK FOR HANDLING BIG DATA DIMENSIONALITY BASED ON FUZZY-ROUGH TECHNIQUE

Big Data is a huge amount of high dimensional data, which is produced from different sources. Big Data dimensionality is a considerable challenge in data processing applications. In this paper, we proposed a framework for handling Big Data dimensionality based on MapReduce parallel processing and FuzzyRough for feature selection. This paper proposes a new method for selecting features based on fuzzy similarity relations. The initial experimentation shows that it reduces dimensionality and enhances classification accuracy. The proposed framework consists of three main steps. The first is the preprocessing data step. As for the next two steps, they are a map and reduce steps, which belong to MapReduce concept. In map step, FuzzyRough is utilized for selecting features. In reduce step, the fuzzy similarity is presented for reducing the extracted features. In our experimental results, the proposed framework achieved 86.4% accuracy by using decision tree technique, while the accuracy of the previous frameworks, which are performed on the same data set, achieved accuracy between 70 to 80%.
SUPPLY CHAIN DESIGN – WHERE TO ALLOCATE LOGISTICS FACILITY

Current market condition make companies searching for every possibility how to better satisfy their customers either by higher level and scope of logistics services or by lower price than competitors. Supply chain design plays a key role in meeting corporate and supply chain strategy as establish a framework in which operation could be realised. Therefore it highly influences rate of customer satisfaction and efficiency not only of one company but of a whole supply chain. Supply chain design is a complex problem requiring involvement wide range of quantitative and qualitative factors. Regrettably, mainly quantitative ones are used as they can be more easily gathered and processes. Moreover, the fact that supply chain design has long been the area of operation research science concertation on quantitative data that could be incorporated into mathematical models prevailed among researchers. Therefore, authors of this paper want to outline the complexity of factors in both aspect quantitative and qualitative ones that should be used within supply chain design.
Model for Artificial Emotion from a Utilitarian Point of View

Implementation of Emotion in Artificial intelligence is an open field and intensive research is being done on this topic for the past decades. This paper proposes a model for triggering six basic emotions described by Paul Ekman by using the concept of Pleasure and Pain. Using pleasure-pain, we classify events into Desirable and Undesirable events. The model uses a probability graph for determining the probability of a certain event happening through a certain path and the intensities of the emotions are a function of pleasure-pain and the corresponding probability derived from the graph. In the end of the paper, we conclude through an illustration that the model is capable of capturing the dynamic nature of emotions.
Denoising in Magnetic Resonance Images using Improved Gaussian Smoothing Technique

Magnetic Resonance Images (MRI) are usually prone to noise like Rician and Gaussian noise. It is very difficult to perform image processing functions with the presence of noise. The objective of our work is to investigate the best method for denoising the MRI images. This study included 25 MRI subjects selected from the Open Access Series of Imaging Studies (OASIS) - 3 database. The 25 brain image subjects includes cases of both men and women aged 60 to 80. The input RGB image is first converted to gray scale image in which the contrast, sharpness, shadow and structure of the color of image are preserved. The proposed work uses an improved Gaussian smoothing technique for denoising Magnetic Resonance Images by constructing a modified mask for Gaussian smoothing. The performance of the proposed technique has been compared with various filters like median filter, Gaussian filter and Gabor filter. The performance evaluation was carried out by metrics like Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Structural Similarity (SSIM) index. The experimental results show that the Improved Gaussian Smoothing Technique (IGST) performs better than other methods. All experiments were conducted using Scikit Learn version 0.20 and Scikit Image version 0.14. 1 under Python version 3.6. 7.
Supplementary Materials: Nested Scale-Editing for Conditional Image Synthesis

The detailed implementation of our decoder network architecture for image inpainting is shown in Fig.3 in the main paper. At each spatial scale, the number of channels for feature activation is 512. The conditional code is the feature vector of the occluded image encoded by a standard encoder network. The detailed implementations of the encoder network are listed in Table 1. We use negative slope of 0.2 for all LeakyReLU layers throughout the network. We employ the following abbreviation: N = Number of filters, K = Kernel size, S = Stride, P = Padding. ”Conv” and ”SN” denote convolutional layer and instance normalization respectively.