Miracle-dz/UniFAR-FTUs huggingface dataset:
Executive functions and self-efficacy in children with developmental dyslexia and parental attitudes of their mothers

Aim: The aim of this study was to compare executive functions and self-efficacy in children with dyslexia and/ or dysorthography relative to healthy controls, as well as the intensity of parental attitudes in their mothers. Method: Three groups of children: with developmental dyslexia and dysorthography (n = 49), with isolated dysorthography (n = 51), and without deficits (n = 59) underwent psychological assessment with the Stanford-Binet 5 Intelligence Scale, the Battery for diagnosing academic failure in pupils aged 10-12, the Battery for the diagnosis of cognitive performance in children aged 10-12 and the Personal Competence Scale. Their mothers completed the Parenting Attitudes Scale. Statistical analyzes were performed using IBM SPSS Statistics. Results: Monitoring time was longer in children with dyslexia and dysorthography compared to controls. Sim-ilarly, phonological and categorical fluency was poorer among children with dyslexia and dysorthography relative to the remaining two groups. No intergroup differences were observed in terms of verbal and non-verbal working memory, monitoring correctness, planning correctness and time, or self-efficacy, strength and persistence. The excessively demanding attitude was more frequent in mothers of healthy controls compared to those of children with dyslexia and dysorthography. No significant differences were found in the intensity of the attitude of acceptance, provision of autonomy, over-protectiveness or inconsistency in the investigated mothers. Conclusions: Due to deficits within phonological and categorical verbal fluency and a longer monitoring speed, children with dyslexia and dysorthography require stimulation within these executive domains. Among the strengths of children with developmental dyslexia and/or dysorthography are self-efficacy, strength and perseverance similar to those found in their healthy peers. Mothers of children with comorbid dyslexia and dysorthography manifest a lesser tendency to an excessively demanding attitude compared to mothers of healthy children.
Sustainable Utilization of Waste Oyster Shell Powders with Different Fineness Levels in a Ternary Supplementary Cementitious Material System

As cement manufacturing accounts for 8% of global CO2 emissions, there is an urgent need to tackle the environmental impacts of cement production and address the decarbonization of construction materials. Adopting supplementary cementitious materials (SCMs), including fly ash, slag, silica fume, etc., can be used as a partial replacement for ordinary Portland cement (OPC) to reduce CO2 emissions related to the OPC industry, while providing benefits for waste valorization. This study aims to explore the sustainable utilization of a waste oyster shell powder (OSP)–lithium slag (LS)–ground granulated blast furnace slag (GGBFS) ternary SCM system in green concrete. The effect of OSP fineness on compressive strength, hydration products, pore structure, and transport properties in ternary SCM-based mortars was studied using a wide array of experimental techniques, including thermogravimetric analysis (TGA), scanning electron microscopy (SEM) analysis, Mercury intrusion porosimetry (MIP), the water absorption test and the rapid chloride penetration test (RCPT). The results revealed that the concrete with the ternary SCMs showed equivalent compressive strength compared to reference specimens. The water absorption and chloride ion charge of the RCPT in the concrete containing the ternary SCMs decreased by up to 30% and 81.4%, respectively. It was observed that the specimens incorporating the OSP with a mesh size of 3000 exhibited the highest compressive strength and the most refined microstructure.
CHARACTERISTIC OF CMCASE OF Bacillus sp. ISOLATED FROM SOIL OF GUNUNG HALIMUN NATIONAL PARK*[Karakteristik CMCase Bacillus sp. Yang Diisolasi dari Tanah Taman Nasional Gunung Halimun]]

Delapan isolat bakten diisolasi dari lanah Taman Nasional Gunung Halimun dipelajari posisi laksonomi dan karaktcr fisiuloginyu. Kemanipuan sclululilik dari 8 isolat Icrscbut diuji dengan membandingkan luas koloni dan zona bening yang terbentuk pada koloni yang ditumbuhkan pada CMC.Selanjutnya Karakteristik CMC-ase dari satu isolat yang mempunyai kemampuan sclulolitik yang paling tinggi diuji. Isolat dengan cepal menggunakan CMC scbagai sumber carbon utama pada suhu 30° C dengan keeepatan pertumbuhan 1.71 '. 1,58"',dan 1.50 ' pada pH ft. 7 dan 8. Tidak ada pertumbuhan yang bcrarti pada kultur yang nienggunakan Avicel sebagai sumber karbon utama.Aktivitas CMCase maksiinum sebcsar6 Unit terjadi pada pH 7 setclah 4 hari kultivasi. Maksimum pertumbuhan scl dicapai pada hari ke 4. Penambahan gliikosa incnstimulusi pertumbuhan binmassa tctatpi menghambat aklivitas enzim. Km dan Vmuk dari CMC-ase adalah IDmM dan2. (,8mM.d'.
Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review

Diabetes is one of the main causes of the rising cases of blindness in adults. This microvascular complication of diabetes is termed diabetic retinopathy (DR) and is associated with an expanding risk of cardiovascular events in diabetes patients. DR, in its various forms, is seen to be a powerful indicator of atherosclerosis. Further, the macrovascular complication of diabetes leads to coronary artery disease (CAD). Thus, the timely identification of cardiovascular disease (CVD) complications in DR patients is of utmost importance. Since CAD risk assessment is expensive for low-income countries, it is important to look for surrogate biomarkers for risk stratification of CVD in DR patients. Due to the common genetic makeup between the coronary and carotid arteries, low-cost, high-resolution imaging such as carotid B-mode ultrasound (US) can be used for arterial tissue characterization and risk stratification in DR patients. The advent of artificial intelligence (AI) techniques has facilitated the handling of large cohorts in a big data framework to identify atherosclerotic plaque features in arterial ultrasound. This enables timely CVD risk assessment and risk stratification of patients with DR. Thus, this review focuses on understanding the pathophysiology of DR, retinal and CAD imaging, the role of surrogate markers for CVD, and finally, the CVD risk stratification of DR patients. The review shows a step-by-step cyclic activity of how diabetes and atherosclerotic disease cause DR, leading to the worsening of CVD. We propose a solution to how AI can help in the identification of CVD risk. Lastly, we analyze the role of DR/CVD in the COVID-19 framework.
Direct Urine Resistance Detection Using VITEK 2

Urinary tract infections (UTIs) are the most common infectious diseases in both communities and hospitals. With non-anatomical or functional abnormalities, UTIs are usually self-limiting, though women suffer more reinfections throughout their lives. Certainly, antibiotic treatment leads to a more rapid resolution of symptoms, but also it selects resistant uropathogens and adversely affects the gut and vaginal microbiota. As uropathogens are increasingly becoming resistant to currently available antibiotics, it could be time to explore alternative strategies for managing UTIs. Rapid identification and antimicrobial susceptibility testing (AST) allow fast and precise treatment. The objective of this study was to shorten the time of diagnosis of UTIs by combining pathogen screening through flow cytometry, microbial identification by matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS), and the VITEK 2 system for the direct analysis of urine samples. First, we selected positive urine samples by flow cytometry using UF5000, establishing the cut-off for positive at 150 bacteria/mL. After confirming the identification using MALDI-TOF MS and filtering the urine samples for Escherichia coli, we directly tested the AST N388 card using VITEK 2. We tested a total of 211 E. coli from urine samples. Cefoxitin, ertapenem, imipenem, gentamicin, nalidixic acid, ciprofloxacin, fosfomycin, and nitrofurantoin had no major important errors (MIE), and ampicillin, cefuroxime, and tobramycin showed higher MIEs. Cefepime, imipenem, and tobramycin had no major errors (ME). Fosfomycin was the antibiotic with the most MEs. The antibiotic with the most minor errors (mE) was ceftazidime. The total categorical agreement (CA) was 97.4% with a 95% CI of (96.8–97.9)95%. The direct AST from the urine samples proposed here was shorter by one day, without significant loss of sensibility regarding the standard diagnosis. Therefore, we hypothesize that this method is more realistic and better suited to human antibiotic concentrations.
Outcomes of Mini-Percutaneous Nephrolithotomy in Children and Adolescents: A 10-Year Single-Centre Experience From Kuwait

The current study retrospectively reviewed data for all children and adolescents who underwent mini-percutaneous nephrolithotomy (PCNL) at Ibn Sina Hospital and Sabah Al Ahmad Urology Centre in Kuwait over 10 years. Accordingly, the 40 patients underwent mini-PCNL. Among them, 21 patients (52.5%) had varying degrees of hydronephrosis, with mild to moderate severity accounting for nearly half of them, whereas six (15%) had multiple stones. The median operative time was 54.5 (43.3-64) minutes. Moreover, 11 patients needed flexible ureteroscopy (URS) and double-J (DJ) ureteric stent, and one patient required DJ ureteric stent only. None of the cases developed intraoperative bleeding. The median hospital stay of the included patients was three (2.3-4) days. Residual stone was observed in 11 patients (27.5%), with a median size of 3 (2 to 7) mm. The incidence of postoperative complications was 27.5% (n = 11 patients), with three patients experiencing postoperative bleeding (7.5%) and eight patients developing a fever (20%). All patients had mild postoperative pain. However, no leakage, sepsis, or pelvic injury occurred. None of the patients required revision. In conclusion, mini-PCNL was a safe and effective procedure in children and adolescents with renal stones.
Learning traits and capture mode of learning disability with classification in e-learning for detecting learning disability using machine learning

Learning Disabilities (LD) are a type of disability that affects people of normal or above-average intelligence. The ability to learn is harmed, and this could last a lifetime. Some children may have a single learning problem, while others may have multiple learning disorders that overlap. Learning disability may include disabilities in various areas related to reading, language and mathematics. Learning disabled children are a broad collection of kids who may face challenges in a variety of areas. For example, one child with a learning disability may have major reading challenges, whereas another may have no reading difficulty at all but struggles with written communication. Learning difficulties are developmental abnormalities that commonly appear during the course of a child’s schooling. These limitations cause a considerable gap between an individual’s genuine potential and day-to-day performance. The purpose of this study is to provide a taxonomy of the many learning qualities of LD, as well as the types of characteristics that cater to which learning disabilities, and to identify the modalities in which a particular learning disability can be captured. Based on these characteristics , we design an e-learning system to detect the presence of learning disability using machine learning.
Factors Influencing COVID-19 Vaccine Uptake among Nepali People in the UK: A Qualitative Study

Vaccination saves lives and can be an effective strategy for preventing the spread of the COVID-19, but negative attitudes towards vaccines lead to vaccine hesitancy. This study aimed to explore the factors influencing the uptake of the COVID-19 vaccine in the Nepali community in the United Kingdom (UK). This qualitative study included in-depth interviews with 20 people from Nepal living in the UK. Interviews were conducted by a native-Nepali speaker and all interviews were audio-recorded, transcribed, and translated into English before being analysed thematically. Our study found that attitudes towards COVID-19 are generally positive. Nine overlapping themes around barriers to COVID-19 vaccination were identified: (a) rumours and mis/disinformation; (b) prefer home remedies and yoga; (c) religion restriction; (d) concern towards vaccine eligibility; (e) difficulty with online vaccine booking system; (f) doubts of vaccine effectiveness after changing the second dose timeline; (g) lack of confidence in the vaccine; (h) past bad experience with the influenza vaccine; and (i) worried about side-effects. Understanding barriers to the uptake of the COVID-19 vaccine can help in the design of better targeted interventions. Public health messages including favourable policy should be tailored to address those barriers and make this vaccination programme more viable and acceptable to the ethnic minority communities in the UK.
Learning from Acceleration Data to Differentiate the Posture, Dynamic and Static Work of the Back: An Experimental Setup

Information on body posture, postural change, and dynamic and static work is essential in understanding biomechanical exposure and has many applications in ergonomics and healthcare. This study aimed at evaluating the possibility of using triaxial acceleration data to classify postures and to differentiate between dynamic and static work of the back in an experimental setup, based on a machine learning (ML) approach. A movement protocol was designed to cover the essential degrees of freedom of the back, and a subject wearing a triaxial accelerometer implemented this protocol. Impulses and oscillations from the signals were removed by median filtering, then the filtered dataset was fed into two ML algorithms, namely a multilayer perceptron with back propagation (MLPBNN) and a random forest (RF), with the aim of inferring the most suitable algorithm and architecture for detecting dynamic and static work, as well as for correctly classifying the postures of the back. Then, training and testing subsets were delimitated and used to evaluate the learning and generalization ability of the ML algorithms for the same classification problems. The results indicate that ML has a lot of potential in differentiating between dynamic and static work, depending on the type of algorithm and its architecture, and the data quantity and quality. In particular, MLPBNN can be used to better differentiate between dynamic and static work when tuned properly. In addition, static work and the associated postures were better learned and generalized by the MLPBNN, a fact that could provide the basis for cheap real-world offline applications with the aim of getting time-scaled postural profiling data by accounting for the static postures. Although it wasn’t the case in this study, on bigger datasets, the use of MLPBPNN may come at the expense of high computational costs in the training phase. The study also discusses the factors that may improve the classification performance in the testing phase and sets new directions of research.
Unemployment and labor force participation in Canada

ABSTRACT We examine the long run relationship between labour force participation and unemployment rate in Canada using data from 1975M01 to 2019M12. A cointegration analysis is conducted at the aggregate, across gender, and by age. Support is found for an added worker affect for males and a discouraged worker effect for females. Findings by age reveal that the working age females exhibits the discouraged effect. However, we cannot confirm the added worker effect for any male age groups.
The Anesthetic Effect and Safety of Dexmedetomidine in Cesarean Section: A Meta-Analysis

Objective To evaluate the anesthetic effect and safety of dexmedetomidine in cesarean section. Methods The Cochrane Library, EMBASE, and PubMed databases (established until September 2020) were searched by computer. Two authors independently screened and extracted literature related to the application of dexmedetomidine in the cesarean section according to inclusion and exclusion criteria. The control group received either subarachnoid block (lumbar anesthesia) or combined lumbar anesthesia and epidural anesthesia (combined lumbar epidural anesthesia) with bupivacaine or combined bupivacaine and fentanyl. The observation group was additionally given dexmedetomidine based on the control group, to analyze the anesthetic effect and safety of dexmedetomidine in cesarean section. Results A total of 580 cesarean delivery women were included in 8 studies, and the results showed that the peak time of sensory block in the observation group was shorter than that in the control group (standard mean difference = −0.28; 95% confidence interval: -0.48, -0.08; P = 0.006), sensory block lasted longer than that in the control group (standard mean difference = 1.49; 95% confidence interval: 1.21, 1.78; P < 0.00001), the sedation rate was higher than that in the control group, the onset of the first postoperative pain was significantly delayed compared with that in the control group, and the incidence of postoperative pain, nausea and vomiting, postoperative chills, and fever was lower than that in the control group (P < 0.05). Conclusion Dexmedetomidine combined with lumbar anesthesia or combined lumbar epidural anesthesia for women in cesarean section has more clinical benefits and better safety.
Intestinal Tuberculosis Presenting with Gastrointestinal Bleeding in Patient on Warfarin Therapy

Background Intestinal tuberculosis (ITB) constitutes less than 5% of overall cases of extrapulmonary disease and mostly affects the ileocecal region. The presentation and radiologic findings in enteric tuberculosis can mimic Crohn's disease (CD). Case Presentation. We present a case report of an African woman who presented to a Kenyan hospital with lower gastrointestinal bleeding while on anticoagulation for valvular atrial fibrillation, and was diagnosed with intestinal tuberculosis after colonoscopy, biopsy, and positive staining for tuberculous bacilli. Conclusion Intestinal tuberculosis causing gastrointestinal bleeding is rare but should be suspected in patients living in TB endemic regions.
Virtual Reality for Industrial Application - The Influence of Presence and its Relation to Usability and User Experience

Virtual and augmented reality are two big buzzwords in the industrial context and they are increasingly used. A main argument for the use of virtual techniques are their economic benefits, which are confirmed by pilot studies. However there is a research gap on how virtual techniques influence the user. This study addresses the impacts of virtual environments on presence, usability and user experience compared to a real environment. Therefore two groups of participants take part in a geocaching tour through the real or virtual city center of Chemnitz and rate the presence of the environment as well as the usability and user experience of a mobile navigation application. The results of 60 participants show that there are general differences between the environments and verify the strengths and weaknesses of virtual environments: Virtual techniques have a positive influence on the user, like a more engaging experience and a perceived higher hedonic quality of the product. Beside these benefits the negative effects have to be considered too, because they influence the ratings of the user. This study shows the potential of virtual techniques for the user and also the deficits, that need to be improved.
Artificial neural network based modeling for the degradation of tannery wastewater in sequential batch reactor

Any wastewater treatment system must have a complete model to provide a tool for predicting the system’s performance and to serve as the foundation for regulating the process’s operation. This would save running expenses while also examining the stability of the environmental bal - ance. This process is challenging and reaches a high degree of non-linearity due to the presence of bio- organic elements that are difficult to define using mechanistic techniques. Predicting plant operating characteristics using standard experimental approaches is time consuming and difficult, making it difficult to regulate such operations effectively. Using a radial function neural network, a research was successfully simulated to analyse the performance of sequential batch reactors on a lab scale. The information gathered is used in a neural network to treat tannery waste water in a sequential batch reactor. Degradation of organic compounds is represented in this method by a trained neural network. The degradation investigations used different dilutions such as 25%, 50%, 75%, and 100% for an initial substrate concentration of 6,240 mg COD/L and at different hydraulic retention times (5, 4, 3, and 2 d). The neural network-based model is thought to have been effective in establishing the system’s properties with high precision. This research uses an artificial neural network (ANN) modelling technique to obtain the knowledge base of a genuine SBR, which is then used as a process model.
Effect of weed control on growth and productivity of soybean

A field experiment was carried out at research farm of Rajasthan College of Agriculture, Udaipur during Kharif 2014 in randomized block design (RBD) with 14 treatments pre-emergence application of pendimethalin 0.75 kg/ha + hand weeding 30 DAS resulted broad spectrum of weed control besides gives higher grain yield. This weed management method found to be promising to control weeds of soybean crop and would play an important role in areas where labour is too expensive and time is a constraint.
Prediction Of Thermal Effects O F Magnitude For Hram Event In Fuel-filled Tank Using The Rayleigh-plesset Equation

To reduce the vulnerability of both civilian and military aircraft, it is important to take the hydrodynamic ram (HRAM) effect into account when designing their fuel tanks. HRAM is especially dangerous for liquidfilled thin walled lightweight structures that cannot be armoured due to weight penalty reasons. However, the response of the tank structure during HRAM events depends on a coupling model between fluid and structure. Water is generally used as a liquid candidate for experimental observations of HRAM, since it is a safe and affordable solution. However, its characteristics in thermal transfers are far different from the ones of hydrocarbons, and it may influence the bubble behaviour and thus its resulting loading on the tank walls. A good understanding of all these aspects is still needed to enhance the tank designs. Similarities in bubble behaviour between HRAM and underwater explosion situations were observed in recent high-speed tank penetration/water entry experiments. A confined version of the Rayleigh-Plesset equation – which is classically used for bubble dynamics analysis (including underwater explosion) – has been previously proposed to simulate a bubble created by an HRAM event. The work the presented work is a first attempt to the estimation of the influence of thermal effects in HRAM processes, by using the Rayleigh-Plesset equation in confined regime.