Miracle-dz/UniFAR-FTUs huggingface dataset:
Epidemiology of Hepatitis B in Saudi Arabia from 2006 to 2021

Background This study describes the epidemiological pattern of acute hepatitis B virus (HBV) infection in Saudi Arabia from 2006 to 2021. It explores case frequency and the crude incidence rate (CIR) by year of diagnosis, age group, region, gender, and nationality of patients. Methods Retrospective data on acute hepatitis B cases diagnosed across 20 regions of Saudi Arabia during January 2006 to December 2021 were obtained from the Saudi Ministry of Health’s Statistical Yearbook. Statistical analyses were conducted using SPSS version 20.0, employing both parametric and non-parametric tests. Results The highest CIR was reported in the regions of Qunfudah, Jeddah, Tabuk, and Taif (28.6, 25.2, 25.1, and 23.4 per 100,000 people). In contrast, the lowest CIR was documented in the regions of Hail, Qurayyat, Jouf, and Hafr AL-Baten (3.6, 3.5, 2.9, and 1.2 per 100,000 people). Incidence rates were notably elevated in those aged 45 years and above (30.6 per 100,000 individuals), followed by the 15–44 age group (14.2 per 100,000 individuals), and were lowest in children aged 0–14 years (0.8 per 100,000 individuals). Regarding gender differences, HBV infection rates were 1.4 times higher in Saudi males than females and 2.2 times higher in non-Saudi males compared to females. Overall, Saudi nationals had a 4.2 times higher HBV infection rate than non-Saudis during the study period. Conclusion This study highlights diverse acute Hepatitis B infection rates across Saudi regions, with higher rates in Qunfudah, Jeddah, Tabuk, and Taif, and lower rates in Hail, Qurayyat, Jouf, and Hafr AL-Baten. Predominance among ages 45+, followed by 15–44, and lowest in 0–14 age groups was observed. Gender variations showed notably higher rates in Saudi and non-Saudi males. The notably higher prevalence among Saudi nationals implies key considerations for public health strategies.
Advancements in Downscaling Global Climate Model Temperature Data in Southeast Asia: A Machine Learning Approach

Southeast Asia (SEA), known for its diverse climate and broad coastal regions, is particularly vulnerable to the effects of climate change. The purpose of this study is to enhance the spatial resolution of temperature projections over Southeast Asia (SEA) by employing three machine learning methods: Random Forest (RF), Gradient Boosting Machine (GBM), and Decision Tree (DT). Preliminary analyses of raw General Circulation Model (GCM) data between the years 1990 and 2014 have shown an underestimation of temperatures, which is mostly due to the insufficient amount of precision in its spatial resolution. Our findings show that the RF method has a significant concordance with high-resolution observational data, as evidenced by a low mean squared error (MSE) value of 2.78 and a high Pearson correlation coefficient of 0.94. The GBM method, while effective, had a broader range of predictions, indicated by a mean squared error (MSE) score of 5.90. The Decision Tree (DT) method performed the best, with the lowest mean squared error (MSE) value of 2.43, which closely matched the actual data. The first General Circulation Model (GCM) data, on the other hand, exhibited significant forecast errors, as evidenced by a mean squared error (MSE) value of 7.84. The promise of machine learning methods, notably the Random Forest (RF) and Decision Tree (DT) algorithms, in improving temperature predictions for the Southeast Asian region is highlighted in the present study.
Bacillus thuringiensis Bt_UNVM-84, a Novel Strain Showing Insecticidal Activity against Anthonomus grandis Boheman (Coleoptera: Curculionidae)

Bacillus thuringiensis is a Gram-positive bacterium known for its insecticidal proteins effective against various insect pests. However, limited strains and proteins target coleopteran pests like Anthonomous grandis Boheman, causing substantial economic losses in the cotton industry. This study focuses on characterizing a Bacillus sp. strain, isolated from Oncativo (Argentina), which exhibits ovoid to amorphous parasporal crystals and was designated Bt_UNVM-84. Its genome encodes genes for the production of two pairs of binary Vpb1/Vpa2 proteins and three Cry-like proteins showing similarity with different Cry8 proteins. Interestingly, this gene content was found to be conserved in a previously characterized Argentine isolate of B. thuringiensis designated INTA Fr7-4. SDS-PAGE analysis revealed a major band of 130 kDa that is proteolytically processed to an approximately 66-kDa protein fragment by trypsin. Bioassays performed with spore-crystal mixtures demonstrated an interesting insecticidal activity against the cotton boll weevil A. grandis neonate larvae, resulting in 91% mortality. Strain Bt_UNVM-84 is, therefore, an interesting candidate for the efficient biological control of this species, causing significant economic losses in the cotton industry in the Americas.
Pensamento Computacional e Matemática na Educação Básica: uma abordagem para as transformações de base decimal para a base binária

No desenvolvimento do Pensamento Computacional as atividades desplugadas tem um papel muito importante, pois trabalham a ludicidade, despertam a criatividade e o interesse pela área da Computação. Desta forma, este trabalho tem como objetivo apresentar uma abordagem desplugada para o ensino das transformações de base decimal para a base binária. Para isso, ocorreu a elaboração e aplicação de dois jogos que abordam esses conceitos. O estudo de caso ocorreu com 89 alunos do 1º ano do Ensino Médio de duas escolas públicas. A análise dos resultados, através da aplicação de um questionário com questões abertas e fechadas, destacou que os jogos desenvolvidos na pesquisa se mostraram adequados para o ensino do conteúdo despertando o interesse dos alunos por essa temática.
Supporting Rural Livelihoods and Ecosystem Services Conservation in the Pico Duarte Coffee Region of the Dominican Republic

Successful conservation strategies have increasingly looked beyond bounded protected areas and toward integrated landscape approaches that conserve biodiversity while maintaining ecosystem services that benefit human communities and food production. More integrated approaches to conservation are particularly timely in agricultural landscapes, where individual farm-level choices can play a significant role in the management of habitat provisioning, nutrient cycling, recreation amenities, carbon sequestration, and the delivery of clean water. This study presents results of an interdisciplinary analysis with shade coffee farmers in the Pico Duarte region of the Dominican Republic. Findings suggest that small farms, as part of a diversified livelihood strategy, maintain a diverse tree canopy, which supports soil conservation and important watershed services. However, high poverty levels and strong economic pressures to convert to high-input, monoculture crops are threatening native tree species biodiversity and the provisioning of ecosystem services (e.g., delivery of clean water and carbon sequestration) to local beneficiaries, as well as to national and international actors. A coordinated effort to support smallholder shade coffee farmers across the landscape through agricultural extension, capacity building, and other market-and-non-market-based interventions offer the potential to improve rural livelihoods and ecosystem services conservation over the long-term.
Histopathological Study of Carcinoma Cervix through Reviewing of Female Genital Tract Cancer Cases of Pathology Archive, Benghazi University from (2002-2011)

Female genital tract (FGT) is the most common site for tumors in females. The most common type of (FGT) cancers is cervical, ovarian and endometrial carcinoma. There are other less common tumor's including tumors of the vagina, vulva and fallopian tubes. Cervical cancer is the second most commonly diagnosed cancer worldwide and the fourth leading cause of cancer death in women. To determine the frequency of (FGT) malignancy found at the pathology archive of the Pathology Department at the Faculty of Medicine in the University of Benghazi between the years 2002-2011. Also to define the proportion of cervix cancer cases as compared with other (FGT) that were recorded in the archive. Moreover, to study the histopathological type of cervical cancer, the age groups and at which grades of differentiation are mostly determined. Retrospective histopathological analysis of (FGT) 330 cancer cases diagnosed between (2002-2011). During the reviewing of (FGT) cancer cases of pathology archive all cases of cervical cancer between 2002-2011 were collected and all formalin-fixed paraffin-embedded (FFPE) tissue blocks of the patients with cervical cancer in that period were collected, and processed to stained slides. In an analysis of 330 FGT cancer cases registered in the pathology archive. (52%) were carcinoma of the endometrium and this was the commonest. This was followed by the carcinoma of the cervix (30.9%), ovarian tumors (13%), vaginal tumors (2%), fallopian tumors and vulva tumors (1%). The most common type of carcinoma cervix was squamous cell carcinoma (62%), adenocarcinoma was (31%) and the least common type was adenosquamous carcinoma (7%). The mean age of patients was 54.67 years. Most cases presented at the postmenopausal period (62.5%). Most cases were poorly differentiated (47.1%), followed by moderately differentiated (33.3%) and well-differentiated (17.6%).
Effect of a nurse-led lymphoma survivorship model of care: A pragmatic phase II pilot randomised controlled trial

Purpose: Increasing numbers of haematology cancer survivors warrants identification of the most effective model of survivorship care to survivors from a diverse range of haematological cancers with aggressive treatment regimens. This review aimed to identify models of survivorship care to support the needs of haematology cancer survivors. Methods: An integrative literature review method utilised a search of electronic databases (CINAHL, Medline, PsycInfo, PubMed, EMBASE, PsycArticles, Cochrane Library) for eligible articles (up to July 2014). Articles were included if they proposed or reported the use of a model of care for haematology cancer survivors. Results: Fourteen articles were included in this review. Eight articles proposed and described models of care and six reported the use of a range of survivorship models of care in haematology cancer survivors. No randomised controlled trials or literature reviews were found to have been undertaken specifically with this cohort of cancer survivors. There was variation in the models described and who provided the survivorship care. Conclusion: Due to the lack of studies evaluating the effectiveness of models of care, it is difficult to determine the best model of care for haematology cancer survivors. Many different models of care are being put into practice before robust research is conducted. Therefore, well-designed high-quality
Quantitative Rapid Magnetic Immunoassay for Sensitive Toxin Detection in Food: Non-Covalent Functionalization of Nanolabels vs. Covalent Immobilization

In this study, we present a novel and ultrasensitive magnetic lateral flow immunoassay (LFIA) tailored for the precise detection of zearalenone, a mycotoxin with significant implications for human and animal health. A versatile and straightforward method for creating non-covalent magnetic labels is proposed and comprehensively compared with a covalent immobilization strategy. We employ the magnetic particle quantification (MPQ) technique for precise detection of the labels and characterization of their functionality, including measuring the antibody sorption density on the particle surface. Through kinetic studies using the label-free spectral phase interferometry, the rate and equilibrium constants for the binding of monoclonal antibodies with free (not bound with carrier protein) zearalenone were determined to be kon = 3.42 × 105 M−1s−1, koff = 7.05 × 10−4 s−1, and KD = 2.06 × 10−9 M. The proposed MPQ-LFIA method exhibits detection limits of 2.3 pg/mL and 7.6 pg/mL when employing magnetic labels based on covalent immobilization and non-covalent sorption, with dynamic ranges of 5.5 and 5 orders, correspondingly. We have successfully demonstrated the effective determination of zearalenone in barley flour samples contaminated with Fusarium graminearum. The ease of use and effectiveness of developed test systems further enhances their value as practical tools for addressing mycotoxin contamination challenges.
Hyperspectral Image Analysis of Food Quality

Assessing the quality of food is a vital step in any food processing line to ensure the best food quality and maximum profit for the farmer and food manufacturer. Traditional quality evaluation methods are often destructive and labour intensive procedures relying on wet chemistry or subjective human inspection. Near-infrared spectroscopy can address these issues by offering a fast and objective analysis of the food quality. A natural extension to these single spectrum NIR systems is to include image information such that each pixel holds a NIR spectrum. This augmented image information offers several extensions to the analysis of food quality. This dissertation is concerned with hyperspectral image analysis used to assess the quality of single grain kernels. The focus is to highlight the benefits and challenges of using hyperspectral imaging for food quality presented in two research directions. Initially, the visualisation and interpretation of hyperspectral images are discussed. A Bayesian based unmixing method is presented as a novel approach to decompose a hyperspectral image into interpretable components. Secondly, hyperspectral imaging is applied to a dedicated application of predicting the degree of pre-germination in single barley kernels using a customised classification framework. Both contributions serve to illustrate the improvement of adding image information to NIR systems in food quality assessment applications.
Therapeutic Endoscopic Ultrasound for Complications of Pancreatic Cancer

Simple Summary Complications of pancreatic cancer include the development of blockage of the bile duct preventing drainage of the liver, blockage of the stomach and duodenum preventing the passage of food and increase in pain levels. Endoscopic ultrasound is a procedure performed through the mouth where a flexible tube with a camera and an ultrasound probe attached allow for visualization of organs around the stomach and small intestine, such as the pancreas, the bile duct, and the liver. It was originally designed to help diagnose pancreatic cancer, but with advances in technology, it can now be used to treat the aforementioned complications without performing surgery. This paper reviews the new advances in technologies and techniques performed through endoscopic ultrasound with an emphasis on clinical trials that have been done to provide an overview of the safety and effectiveness of these procedures. Abstract Progression of pancreatic adenocarcinoma can result in disease complications such as biliary obstruction and gastric outlet obstruction. The recent advances in endoscopic ultrasound (EUS) have transformed EUS from a purely diagnostic technology to a therapeutic modality, particularly with the development of lumen-apposing metal stents. In terms of biliary drainage, EUS-guided choledochoduodenostomy and EUS-guided hepaticogastrostomy offer safe and effective techniques when conventional transpapillary stent placement via ERCP fails or is not possible. If these modalities are not feasible, EUS-guided gallbladder drainage offers yet another salvage technique when the cystic duct is non-involved by the cancer. Lastly, EUS-guided gastroenterostomy allows for an effective bypass treatment for cases of gastric outlet obstruction that enables patients to resume eating within several days. Future randomized studies comparing these techniques to current standard-of-care options are warranted to firmly establish therapeutic EUS procedures within the treatment algorithm for this challenging disease.
Climate Change, Adaptation and Higher Education - Securing our Future

SARUA, in partnership with the University of Mauritius, hosted a Southern African Higher Education Leadership Programme to review the present contribution of higher education in southern Africa and to explore opportunities for scaling up existing initiatives so that it can make a meaningful impact on the way the region responds to climate change, adaptation and sustainability. This leadership dialogue sought to take advantage of increasing the momentum gained, the relationships formed, and the knowledge created by a number of recent initiatives, to explore the nexus between climate change, adaptation and higher education. The aim of the leadership dialogue was to determine the progress made in regard to integrating climate change into higher education teaching and learning, knowledge production and community engagement.
AI EMPOWERED DIAGNOSIS OF PEMPHIGUS: A MACHINE LEARNING APPROACH FOR AUTOMATED SKIN LESION DETECTION

Pemphigus is a skin disease that can cause a serious damage to human skin. Pemphigus can result in other issues including painful patches and infected blisters, which can result in sepsis, weight loss, and starvation, all of which can be life-threatening, tooth decay and gum disease. Early prediction of Pemphigus may save us from fatal disease. Machine learning has the potential to offer a highly efficient approach for decision-making and precise forecasting. The healthcare sector is experiencing remarkable advancements through the utilization of machine learning techniques. Therefore, to identify Pemphigus using images, we suggested machine learning-based techniques. This proposed system uses a large dataset collected from various web sources to detect Pemphigus. Augmentation has been applied on our dataset using techniques such as zoom, flip, brightness, distortion, magnitude, height, width to enhance the breadth and variety of the dataset and improve model’s performance. Five popular machine learning algorithms has been employed to train and evaluate model, these are K-Nearest Neighbor (referred to as KNN), Decision Tree (DT), Logistic Regression (LR), Random Forest (RF), and Convolutional Neural Network (CNN). Our outcome indicate that the CNN based model outperformed the other algorithms by achieving accuracy of 93% whereas LR, KNN, RF and DT achieved accuracies of 78%, 70%, 85% and 75% respectively.
A GENERATIVE MODEL FOR DEEP FAKE AUGMENTATION OF PHONOCARDIOGRAM AND ELECTROCARDIOGRAM SIGNALS USING LSGAN AND CYCLE GAN

In order to diagnose a range of cardiac conditions, it is important to conduct an accurate evaluation of either phonocardiogram (PCG) and electrocardiogram (ECG) data. Artificial intelligence and machine learning-based computer-assisted diagnostics are becoming increasingly commonplace in modern medicine, assisting clinicians in making life-or-death decisions. The requirement for an enormous amount of information for training to establish the framework for a deep learning-based technique is an empirical challenge in the field of medicine. This increases the risk of personal information being misused. As a direct result of this issue, there has been an explosion in the study of methods for creating synthetic patient data. Researchers have attempted to generate synthetic ECG or PCG readings. To balance the dataset, ECG data were first created on the MIT-BIH arrhythmia database using LS GAN and Cycle GAN. Next, using VGGNet, studies were conducted to classify arrhythmias for the synthesized ECG signals. The synthesized signals performed well and resembled the original signal and the obtained precision of 91.20%, recall of 89.52% and an F1 score of 90.35%.
IT Optimization with Cloud Computing: A SAP Cloud perspective for Education and Research

This journal article discusses how IT optimization is achieved through Cloud Computing. The author unfolds examples of real-world organizations that implemented Cloud based solutions to demonstrate the practicality and advantages of Cloud adoption. The article also brings into limelight, for the first time, the compilation of case-studies from the education and research industry that implemented SAP Cloud solutions and how they were able to derive gains. The author further builds up the gathered information and proposes a step-by-step approach to continually optimize IT in the Cloud, to attain best Cloud performance and cost
Phenotypic Variability for Leaf and Pod Color within the Snap Bean Association Panel

The color of vegetables is an important factor in consumer food choices and in cultivar choice by growers and processors for production. In absorbing a broad spectrum of light, leaves support plant development by influencing factors such as biomass accumulation, chlorophyll content, and reproductive growth. The edible organ of the snap bean (Phaseolus vulgaris L.) is the pod, and its color is not only one of the most important traits for commercial consideration, but also influences phytonutrient content. Although chlorophyll provides the base color, other compounds such as carotenoids and flavonoids may affect leaf and pod color. Darker yellow- or blue-green pods are preferred for processing, but there is more leeway for fresh market, with lighter-colored pods being acceptable. This research characterized leaf and pod color variation in the 378-member Snap Bean Association Panel. Leaf and pod colors were measured with a colorimeter using the L*a*b* scale, which was then transformed to L* (lightness), C* (chroma), and H° (hue angle) for analysis. Both green and wax bean accessions had predominantly green leaves, even though both exterior and interior colors of pods varied by accession. The leaves at the upper level in the canopy were lighter than lower and middle-level leaves. C* of leaves was similar across environments but leaves from the field were greener than leaves of greenhouse-grown plants when converted to Royal Horticultural Society (RHS) values, even though they had similar H°. L* did not differ for corresponding leaf positions of both field and greenhouse leaves. Purple pods were darker (lowest L*) and yellow pods were lighter (highest L*). Although wax beans had similar exterior and interior colors, accessions with purple exterior of pods had green interiors. Green pods were generally two times higher for L* and lower in C* compared with leaves. Pod interior L* was darker than exterior in both years. Pod exterior L* was not significantly different among accessions, whereas pod interior L* differed significantly between years. Broad sense heritabilities ranged from 0.69 to 0.88 for L*, 0.12 to 0. 87 for C*, and 0.81 to 0.89 for H°. Although greater variation was observed in pods than leaves, lower heritability was determined. Moderate correlations between leaf L* and the interior and exterior pod L* implies that it would be possible to select for pod color on the basis of leaf color, with verification using standard cultivars.