Miracle-dz/UniFAR-FTUs huggingface dataset:
Accessibility to digital technology: Virtual barriers, real opportunities

ABSTRACT The potential of digital technology to assist persons with disabilities has always been known. The capabilities of digital devices have been improving so impressively for so long, that the assumption that in parallel the same is happening with accessibility is common. Unfortunately, accessibility for persons with disabilities is neither certain nor constant, and in fact, a conscious and systemic effort is required to ensure that the potential of digital technologies for inclusion is realized. Digital accessibility is best understood as a chain of dependencies where training, hardware, software, content, and standards must work together harmoniously, and each of these elements must be understood as a dynamic process. For example, smartphones can be incompatible with hearing aids required by the deaf, touch screens too sensitive for those with motor impairments, and web pages often lack the text labels needed by screen reading software used by the blind. Even if each of these examples is fixed, the accessibility may be short lived if the production process behind that hardware or software was not corrected, as the digital world is constantly being updated. Training, hardware design, software development, content production, and standards definition processes, must be pursued taking accessibility and affordability into account.
Explosive detection using high-volume vapor sampling and analysis by trained canines and ultra-trace detection equipment

The dog's nose is an effective, highly-mobile sampling system, while the canine olfactory organs are an extremely sensitive detector. Having been trained to detect a wide variety of substances with exceptional results, canines are widely regarded as the 'gold standard' in chemical vapor detection. Historically, attempts to mimic the ability of dogs to detect vapors of explosives using electronic 'dogs noses' has proven difficult. However, recent advances in technology have resulted in development of detection (i.e., sampling and sensor) systems with performance that is rapidly approaching that of trained canines. The Nomadics Fido was the first sensor to demonstrate under field conditions the detection of landmines with performance approaching that of canines. More recently, comparative testing of Fido against canines has revealed that electronic vapor detection, when coupled with effective sampling methods, can produce results comparable to that of highly-trained canines. The results of these comparative tests will be presented, as will recent test results in which explosives hidden in cargo were detected using Fido with a high-volume sampling technique. Finally, the use of canines along with electronic sensors will be discussed as a means of improving the performance and expanding the capabilities of both methods.
Aspergillus Flavus reprogrammed morphological and chemical attributes of Solanum lycopersicum through SlGSH1 and SlPCS1 genes modulation under heavy metal stress

ABSTRACT Cadmium (Cd) and chromium (Cr) in agricultural soils is becoming a serious threat in tomato. The complete removal of these heavy metals (HMs) from contaminated soil is challenging. However, the use of plant endophytes might be beneficial. The pragmatic role of endophytic fungi Aspergillus flavus (Ch-01) in tomato under Cd and Cr stress was, therefore, investigated. A. flavus enhanced growth attributes in tomato seedlings under Cd and Cr stress. Besides, it remediated Cd and Cr toxicity by reducing their translocation from the roots to the upper part of the tomato plants. In fact, A. flavus associated plants developed tolerance against Cd and Cr toxicity via the expression of SlGSH1 and SlPCS1 genes. Both genes helped in metal chelation and mitigation of Cd and Cr toxicity. From the results, it is concluded that A. flavus is a plant growth promoting and HMs alleviating endophyte, hence it might be used as a biofertilizer.
Effects of A 12-Week Rebound Therapy Exercise on Energy Consumption and Body Mass Index in Patients With Spinal Cord Injury

* Corresponding Author: Morteza Sadeghi, PhD. Address: Department of Corrective Exercise and Sport Injuries, Faculty of Sports Sciences, University of Isfahan, Isfahan, Iran. Tel: +98 (913) 2175212 E-mail: m.sadeghi@spr.ui. ac.ir Introduct﻿ion: Energy Consumption (EC) and Body Mass Index (BMI) are the major complications associated with Spinal Cord Injury (SCI), which can be improved by exercise rehabilitation. Thus, the present study aimed to evaluate the efficiency of using rebound therapy (exercise on a trampoline) on EC and BMI in individuals with SCI.
PCR technology for screening genetically modified soybeans

Genetically modified (GM) crops involve transferring a specific stretch of DNA into the plant’s genome and giving it new or different characteristics. Since the first industrial application of transgenic crops in the United States in 1996, GM crops are becoming increasingly common in the market. At present, not all crops in the Chinese market are clearly marked as to whether they are GM crops or not. In order to protect consumer’s option to select their preferred products, we decided to conduct experiments to identify soybeans on the market. We hypothesized that soybeans on the market with unknown origin were GM soybeans. Then we established a detecting method using genetic technology and screened the soybeans. In this study, we used GTS 40-3-2 as a positive control, which contains genomic DNA, foreign DNA enolpyruvylshikimate-3-phosphate synthase (EPSPS) and other exogenous elements, and GTS 40-3-2 SOYA BEAN (blank) as negative control, which contains genomic DNA only. To amplify the foreign DNA, we optimized the polymerase chain reaction (PCR) procedure by attempting different annealing temperatures to establish the PCR detection method. According to the electrophoresis results, in the samples from a local store, only genomic DNA lectin could be amplified, which indicated the samples were non-GM soybeans. Our study not only provides a detection method but also lays a foundation for testing soybean and processed soybean products of unknown origin.
TOWARDS NÔM HISTORICAL DOCUMENT OPTICAL CHARACTER RECOGNITION

: Nôm script is the ancient ideographic writing system of the Vietnamese for hundreds of years in the past (from the 10th century to the 20th century), hence, it embodies invaluable heritage of Vietnamese historical cultures, politics, economics, medicine practices and many more. To contribute to the preservation of Nôm script, in this paper, we focus on the task of building Nôm Optical Character Recognition model - one of the important and prerequisite components that supports vast digitizing Nôm documents. Our OCR baseline achieves a recognition rate of 71.80% mAP on top-1 and 80.54% mAP on top-5 for our testing dataset Truyện Kiều (1902); 72.96% mAP on top-1 and 82.36% on top-5 for the testing dataset Truyện Lục Vân Tiên.
Effective prediction model for preventing postoperative deep vein thrombosis during bladder cancer treatment

Objective To begin to understand how to prevent deep vein thrombosis (DVT) after an innovative operation termed intracorporeal laparoscopic reconstruction of detenial sigmoid neobladder, we explored the factors that influence DVT following surgery, with the aim of constructing a model for predicting DVT occurrence. Methods This retrospective study included 151 bladder cancer patients who underwent intracorporeal laparoscopic reconstruction of detenial sigmoid neobladder. Data describing general clinical characteristics and other common parameters were collected and analyzed. Thereafter, we generated model evaluation curves and finally cross-validated their extrapolations. Results Age and body mass index were risk factors for DVT, whereas postoperative use of hemostatic agents and postoperative passive muscle massage were significant protective factors. Model evaluation curves showed that the model had high accuracy and little bias. Cross-validation affirmed the accuracy of our model. Conclusion The prediction model constructed herein was highly accurate and had little bias; thus, it can be used to predict the likelihood of developing DVT after surgery.
Investigation on performance in water jet pump under turning conditions

Turning has a significant effect on the performance of water-jet pump. Here, the axial flow water-jet pump was used as the research object, the performance and inner flow characteristics of water-jet pump under different turning angle were simulated through numerical simulation. The thrust, vorticity, bubbles in impeller, vapor volume fraction and surface load of blade were analyzed in detail when the turning angles were ±10°, ±20°, and ±30°, respectively. The results demonstrate that the thrust of the water-jet pump decreases linearly with the increase of the turning angle. At the same angle, the thrust of the water-jet pump when turning right is larger than that when turning left, and the maximum thrust difference is 9.14% of that without the turning angle. As the turning angle increases, the overall pressure of the water-jet pump decreases and the streamline distribution gets turbulent gradually. The vortex direction is the same as the turning direction basically. And the vortex distribution range is smaller when turning right under the same turning angle. The cavitation bubbles in the impeller occur firstly at the rim of the blade inlet and develop to the middle of the blade as the turning angle increases. The cavitation area is concentrated on the blade at turning side and the cavitation area when turning right is smaller than that when turning left.
A Review and Analysis of The Existing Literature on Monochromatic Photography Colorization Using Deep Learning

It is universally known that, through the process of colorization, one aims at converting a monochrome image into one of color, usually because it was taken by the limited technology of previous decades. Our work introduces the problem, summarizes the general deep learning solutions, and discusses the experimental results obtained from open-source repositories. Although the surveyed methods can be applied to other fields, solely the content of photography is being considered. Our contribution stands in the analysis of colorization in photography by examining used datasets and methodologies for evaluation, data processing activities, and the infrastructure demanded by these systems. We curated some of the most promising papers, published between 2016 and 2021, and centered our observations around software reliability, and key advancements in solutions employing Generative Adversarial Networks and Neural Networ
Do you know what you did last summer? Visualizing personal behavior in Google services

People use web-based services extensively, but have few tools at their disposal to view and monitor their past uses. We present a visualization tool that pulls user data from Google services such as Blogger, Calendar, and Documents, and shows users who they have interacted with and what content they have shared. The goal of this research is to understand what people are able to report about their own past behavior and to design a tool to support self-monitoring and reflection. We also consider questions of privacy, data synthesis, and social visualization.
REAL-TIME 3D RECONSTRUCTION OF DYNAMIC SCENES WITH MULTIPLE KINECT V2 SENSORS

3D reconstruction of dynamic scenes is an important task in the field of multimedia which arouses widespread interest in recent years. Although several novel 3D applications have been unlocked with the increasing popularity of commercial RGB-D cameras like Microsoft Kinect, Azure, and Intel RealSense, real-time performance is still a big problem. In this paper, an open-solution, low-latency, real-time 3D reconstruction system is presented. The proposed system runs in a simple architecture where multiple Kinect v2 sensors are connected to a single computer. It consists of a series of modules including capture, alignment, and post-processing. The data stream of all sensors will pass through these modules in turn, generate point clouds, and finally fusion to a single 3D model. To improve the real-time performance, this system adopts a pipeline design that uses multiple threads to execute all modules concurrently. Besides, the first-in-first-out feature of the queue is utilized for data transmission and thread separation. At last, experimental results are presented to verify the system's effectiveness concerning the 3D reconstruction visual quality and real-time performance.
Model-free estimation of defect clustering in integrated circuit fabrication

This paper describes a model-free method for estimating some yield metrics that are used to track integrated circuit fabrication processes. Our method uses binary probe test data at the wafer level to estimate the size, shape and location of large-area defects or clusters of defective chips. Unlike previous methods in the yield modeling literature, our approach makes extensive use of the location of failing chips to directly identify clusters. An important by product of this analysis is a decomposition of wafer yield that attributes defective chips to either large- or small-area defects. Simulation studies show that our procedure is superior to the time-honored windowing technique for achieving a similar breakdown. In addition, by directly estimating defect clusters, we can provide engineers with a greater understanding of the manufacturing process. It has been our experience that routine identification of the spatial signatures of clustered defects and associated root-cause analysis is a cost-effective approach to yield and process improvement.
Highly efficient removal of hexavalent chromium using hexagonal disc shaped barium hydrogen phosphate

Novel hexagonal disc‐shaped barium hydrogen phosphate was synthesized and analyzed by X‐ray diffraction, X‐ray photoelectron spectroscope, scanning electron microscope, transmission electron microscopy, thermogravimetric analysis, Brunauer–Emmett–Teller, and FTIR. The effects of adsorbent dose, adsorption time, initial concentration, initial pH, temperature, and sodium chloride on hexavalent chromium, Cr (VI), adsorption by BaHPO4 were studied. Effective Cr (VI) adsorption capacity was observed in the pH range of 4–5. The temperature‐dependent adsorption data showed sorption is endothermic and spontaneous in nature. The adsorption occurs via electrostatic interaction and is described by second order kinetic, and the adsorption isotherm was best fitted with the Langmuir model. The equilibrium adsorption capacity and maximum adsorption capacity were found to be 128.7 mg/g and 146.8 mg/g, respectively at room temperature and pH 6. Adsorbent is stable, recyclable, environmentally friendly, and can be produced on a large scale at a low cost. This can be utilized for the treatment of Cr (VI) contaminated water.
The Influence of Cultural Experiences on the Associations between Socio-Economic Status and Motor Performance as Well as Body Fat Percentage of Grade One Learners in Cape Town, South Africa

Fundamental movement skills (FMS), physical fitness (PF) and body fat percentage (BF%) are significantly related to socio-economic status (SES). However, it remains unclear why previous studies have had different findings regarding the direction of the association between SES and FMS, PF and BF%. A suggested explanation is that the direction of the link can be influenced by cultural experiences and traditions. Therefore, the aim of the current study was to investigate links between SES and FMS, PF, BF% of Grade One learners from two different ethno-geographic areas in Cape Town, South Africa. Grade One children (n = 191) (n = 106 boys and n = 85 girls; age (6.7 ± 0.33)) from different socio-economic areas in Cape Town, South Africa, were selected to participate in the study. South African schools are classified into five different quintiles (1 = poorest and 5 = least poor public schools). For this study, two schools were selected, one from quintile 2 and the other from quintile 5. BF% was assessed according to Slaughter’s equation. FMS were measured using the Gross Motor Development Test-2 (TGMD-2) and PF via five tests: 1. dynamic strength of lower limb (broad jump); 2. dynamic strength of upper limb and trunk (throwing a tennis ball); 3. speed agility (4 × 10 m shuttle running); 4. cardiorespiratory fitness (20 m shuttle run endurance test (Leger test)) and 5. flexibility (sit and reach test). An analysis of covariance (ANCOVA) found that BF% and WHtR were significantly greater in children with higher SES (Z = 6.04 p < 0.001; Hedg = 0.54), (Z = 3.89 p < 0.001; Hedg = 0.32). Children with lower SES achieved significantly better TGMD-2 standard scores in the locomotor subtest, compared to their peers with higher SES. In the object control subtest, no significant SES-related difference was found. However, ANCOVA showed that girls performed better in FMS than boys. In PF, the main effect of SES was observed in dynamic strength of trunk and upper limb (throwing) and flexibility, where children with lower SES performed significantly better. No significant difference was found in cardiorespiratory performance (CRP) (Beep test), even though children with lower SES achieved better results. Results from the current study suggest that links between SES, PF, FMS and body fat percentage in children seem to be dependent on cultural and traditional experiences. These experiences should therefore be included as an important factor for the development of programmes and interventions to enhance children’s lifelong motor behaviour and health strategies.
Age-Invariant Face Recognition to Aid Visually Impaired People

Este trabalho propõem uma abordagem para auxiliar pessoas com deficiência visual no reconhecimento de pessoas independente da idade. O objetivo é desenvolver um sistema que utilize uma abordagem de reconhecimento facial, com foco na invariância na idade, que retorne bons resultados comparados aos resultados obtidos na revisão da literatura. A abordagem estudada utiliza Redes Neurais Convolucionais profundas CCNs, pré-treinadas pelo conjunto de dados VGGFace2, para extrair descritores de características de imagens de faces e classificar com o algoritmo de classificação Linear SVM. Como pode ser visto no decorrer do trabalho, a abordagem retornou 89,9% de acurácia, utilizando o conjunto de dados FG-NET, com 1002 imagens. E utilizando o conjunto de dados CACD, que contém 163.446 imagens divididas em quatro subconjuntos diferentes, três conjuntos para treino e um para teste, a abordagem retornou 85,2%, 82,4% e 88,2% de acurácia para cada modelo treinado com um conjunto de treinamento diferente.
ORAC: a modern observing system for UKIRT

The steady improvement in telescope performance at UKIRT and the increase in data acquisition rates led to a strong desired for an integrated observing framework that would meet the needs of future instrumentation, as well as providing some support for existing instrumentation. Thus the Observatory Reduction and Acquisition Control (ORAC) project was created in 1997 with the goals of improving the scientific productivity in the telescope, reducing the overall ongoing support requirements, and eventually supporting the use of more flexibly scheduled observing. The project was also expected to achieve this within a tight resource allocation. In October 1999 the ORAC system was commissioned at the United Kingdom Infrared Telescope.
Caring for Patients in a Coma Following a Traumatic Brain Injury in Iran

The study described here is the process of caring for patients in a coma following a traumatic brain injury (TBI) in Iran. The data that were analyzed come from in-depth semistructured interviews of 20 key participants and associated memos and field notes. The MAXQDA 10 qualitative analysis software was used to assist with the coding of the data. Ten catagories and 26 subcategories were identified from the primary analysis, which fit well into four themes. The main themes that were identified were chaos and confusion, inconsistent quality, multilateral support, and improving care. The processes of caring for persons in a coma following a TBI were found to be an ever-changing, multidimensional, context-dependent process.
Research on Personal Credit Evaluation Based on Machine Learning Algorithm

With the rapid development of Internet finance and consumer credit, it is necessary to establish a reasonable personal credit evaluation model. This paper discusses the accuracy of six general personal credit evaluation models based on the Give Me Some Credit data set from Kaggle. A multiple-average machine learning model is established to improve the stability of the result. The research shows the NB classifier, Support Vector Machines, Random Forest and BP Neural Network have good prediction effect on individual credit default risk, while the accuracy of Logical Regression and Stepwise Regression is relatively low. The multiple averaging method can effectively reduce the volatility of the results, and the accuracy will not be significantly reduced under different proportion of training set and prediction set.
Fresh air-natural asset [telecommunication equipment cooling]

This paper outlines BT's approach to economic cooling of its telecommunication network equipment over the past two decades detailing how fresh air cooling has evolved with changes in operational philosophy and equipment technology during this period. With nearly 2,000 exchanges cooled with fresh air, including almost all of BT's trunk network telecommunication centres, the challenge for the future is to adapt fresh air cooling for future equipment, especially as the telecommunication industry is coming to terms with the increasing telecommunication equipment heat density which is expected to be in the order 5 plus kW/m/sup 2/ within 18 months. Discussed is the emphasis that BT places on conformance with European Telecommunication Standards Institute (ETSI) standards and in particular with environmental parameters in ETSI EN 300 019 and the use of Computational Fluidflow Dynamics (CFD) modeling techniques to achieve new fresh air cooling systems. The use of CID modeling techniques provided answers to numerous questions about how to deploy cooling solutions and how fool-proof they are and what, if any, safe guards were required to ensure successful application.
REVIEW OF INNOVATION AND COMPETITIVENESS A JOURNAL OF ECONOMIC AND SOCIAL RESEARCH

Purpose. The study aims to examine the nexus between agricultural productivity by connecting oil prices, economic growth, and financial development. Design/Methodology/Approach. A newly formulated ARDL model was used to estimate an agricultural productivity nexus model using annual time-series data from 1962 to 2016. Innovation and additive structural break unit root tests were applied to determine the existence of unit roots, and the results reaffirmed that all the variables were stationary at first difference. The Chow Breakpoint test was applied to confirm a structural break in the year 2008 caused by the effects of the 2008 financial crisis. Findings and Implications. The results depicted a long-run relationship linking agricultural productivity, oil prices, economic growth, financial development and a financial crisis. The results also showed that financial development and economic growth have positive effects on agricultural productivity. The empirical findings further suggested that an increase in oil prices and the prevalence of a financial crisis have severe adverse effects on agricultural productivity.