Miracle-dz/UniFAR-FTUs huggingface dataset:
Forecasting Emergency Department Capacity Constraints for COVID Isolation Beds

Predicting patient volumes in a hospital setting is a well-studied application of time series forecasting. Existing tools usually make forecasts at the daily or weekly level to assist in planning for staffing requirements. Prompted by new COVID-related capacity constraints placed on our pediatric hospital's emergency department, we developed an hourly forecasting tool to make predictions over a 24 hour window. These forecasts would give our hospital sufficient time to be able to martial resources towards expanding capacity and augmenting staff (e.g. transforming wards or bringing in physicians on call). Using Gaussian Process Regressions (GPRs), we obtain strong performance for both point predictions (average R-squared: 82%) as well as classification accuracy when predicting the ordinal tiers of our hospital's capacity (average precision/recall: 82%/74%). Compared to traditional regression approaches, GPRs not only obtain consistently higher performance, but are also robust to the dataset shifts that have occurred throughout 2020. Hospital stakeholders are encouraged by the strength of our results, and we are currently working on moving our tool to a real-time setting with the goal of augmenting the capabilities of our healthcare workers.
Fluid limits for the Queue-Based Carrier Sense Multiple Access algorithms with polynomial rates

We study in this paper a variation of the acclaimed CSMA random access protocol where back-off rates depend on the state of the network through queue lengths. We prove convergence of the fluid limits to a deterministic process up to the time a queue reaches 0 on the fluid scale under a condition relating the exponent in the polynomial rates and the geometry of the interference graph. We outline the difficulties arising at that time and solve them in the case of a complete interference graph. This paper relies on a new method to obtain a fully coupled stochastic averaging principle and can hopefully lead to more result in heavy load situations.
Antimicrobial resistant gene prevalence in soils due to animal manure deposition and long-term pasture management

The persistence of antimicrobial resistant (AMR) genes in the soil-environment is a concern, yet practices that mitigate AMR are poorly understood, especially in grasslands. Animal manures are widely deposited on grasslands, which are the largest agricultural land-use in the United States. These nutrient-rich manures may contain AMR genes. The aim of this study was to enumerate AMR genes in grassland soils following 14-years of poultry litter and cattle manure deposition and evaluate if best management practices (rotationally grazed with a riparian (RBR) area and a fenced riparian buffer strip (RBS), which excluded cattle grazing and poultry litter applications) relative to standard pasture management (continuously grazed (CG) and hayed (H)) minimize the presence and amount of AMR genes. Quantitative PCR (Q-PCR) was performed to enumerate four AMR genes (ermB, sulI, intlI, and blactx-m-32) in soil, cattle manure, and poultry litter environments. Six soil samples were additionally subjected to metagenomic sequencing and resistance genes were identified from assembled sequences. Following 14-years of continuous management, ermB, sulI, and intlI genes in soil were greatest (P < 0.05) in samples collected under long-term continuous grazing (relative to conservation best management practices), under suggesting overgrazing and continuous cattle manure deposition may increase AMR gene presence. In general, AMR gene prevalence increased downslope, suggesting potential lateral movement and accumulation based on landscape position. Poultry litter had lower abundance of AMR genes (ermB, sulI, and intlI) relative to cattle manure. Long-term applications of poultry litter increased the abundance of sulI and intlI genes in soil (P < 0.05). Similarly, metagenomic shotgun sequencing revealed a greater total number of AMR genes under long-term CG, while fewer AMR genes were found in H (no cattle manure) and RBS (no animal manure or poultry litter). Results indicate long-term conservation pasture management practices (e.g., RBS and RBR) and select animal manure (poultry litter inputs) may minimize the presence and abundance of AMR genes in grassland soils.
Safety and long-term outcomes of early gastric cardiac cancer treated with endoscopic submucosal dissection in 499 Chinese patients

Aims: Early gastric cardiac cancer (EGCC) has a low risk of lymph node metastasis with the potential for endoscopic therapy. We aimed to evaluate the short- and long-term outcomes of endoscopic submucosal dissection (ESD)-resected EGCCs in a large cohort of Chinese patients and compare endoscopic and clinicopathologic features between EGCC and early gastric non-cardiac cancer (EGNC). Methods: We retrospectively studied 512 EGCCs in 499 consecutive patients and 621 EGNCs in 555 consecutive patients between January 2011 and March 2018 at our center. We investigated clinicopathological characteristics of EGCC tumors, ESD treatment results, adverse events, and postresection patient survival. Results: Compared with EGNC patients, EGCC patients were significantly older (average age: 66 years versus 62 years, p < 0.001). The percentage of the gross 0–IIc pattern was higher in EGCCs (46.1%) than in EGNCs (41.5%), while the frequency of the 0–IIa pattern was lower in EGCCs (14.9%) than in EGNCs (22.4%) (p = 0.001). Compared with EGNCs, EGCCs showed smaller size, deeper invasion, fewer ulcerated or poorly differentiated tumors, but more cases with gastritis cystica profunda. The prevalence of ESD-related complications was higher in EGCCs (6.1%) than in EGNCs (2.3%) (p = 0.001). In EGCCs, the disease-specific survival rate was significantly higher in patients of the noncurative resection group with surgery (100%), compared with that (93.9%) without surgery (p < 0.001). Conclusion: Clinicopathological characteristics were significantly different between EGCCs and EGNCs. ESD is a safe and effective treatment option with favorable outcomes for patients with EGCC. Additional surgery improved survival in patients with noncurative ESD resection.
EGFRvIII expression and isocitrate dehydrogenase mutations in patients with glioma

Molecular pathology and personalized medicine are still being evolved in Saudi Arabia, and genetic testing for the detection of mutations as cancer markers have not been established in the diagnostics laboratories in Saudi Arabia. The aim of the present study was to determine the prevalence of isocitrate dehydrogenase (IDH1 and IDH2) mutations and epidermal growth factor receptor variant (EGFRv)III transcript expression in Saudi Arabian patients with glioma. Out of 117 brain tumors tested by reverse transcription-quantitative PCR for EGFRvIII, 41 cases tested positive. In the glioblastoma (GBM) category, 28/55 tumors were positive, in astrocytoma tumors 5/22, and in oligodendrogliomas 4/13 cases were positive respectively. EGFRvIII transcript was sequenced by capillary electrophoresis to demonstrate the presence of EGFRvIII-specific junction where exons 2–7 were deleted. In the present study 106 tumors were sequenced for IDH1 exon-4 mutations using the capillary sequencing method. The most common substitution missense mutation c.395G>A was found in 16 tumors. In the case of adamantinomatous craniopharyngioma, a novel missense mutation in c.472C>T was detected in IDH2 gene. Using next-generation sequencing (NGS), 74 tumors were sequenced for the IDH1 gene, and a total of 8 missense variants were identified in 36 tumors in a population of Saudi Arabia. The missense mutation (c.395G>A) was detected in 29/36 of tumors. A novel intronic mutation in c.414+9T>A was found in 13 cases in the IDH1 gene. In addition, one case exhibited a novel synonymous mutation in c.369A>G. Eleven tumors were found to have compound mutations in the IDH1 gene. In IDH2 gene, out of a total of 16 variants found in 6 out of 45 tumors, nine were missense, five were synonymous and one was intronic. This is the first report from Saudi Arabian laboratories analyzing glioma tumors for EGFRvIII expression, and the first study from Saudi Arabia to analyze IDH mutations in gliomas using the capillary and NGS methods.
The role of Transfer RNA-Derived Small RNAs (tsRNAs) in Digestive System Tumors

Transfer RNA-derived small RNA(tsRNA) is a type of non-coding tRNA undergoing cleavage by specific nucleases such as Dicer. TsRNAs comprise of tRNA-derived fragments (tRFs) and tRNA halves (tiRNAs). Based on the splicing site within the tRNA, tRFs can be classified into tRF-1, tRF-2, tRF-3, tRF-5, and i-tRF. TiRNAs can be classified into 5′-tiRNA and 3′-tiRNA. Both tRFs and tiRNAs have important roles in carcinogenesis, especially cancer of digestive system. TRFs and tiRNAs can promote cell proliferation and cell cycle progression by regulating the expression of oncogenes, combining with RNA binding proteins such as Y-box binding protein 1 (YBX1) to prevent transcription. Despite many reviews on the basic biological function of tRFs and tiRNAs, few have described their correlation with tumors especially gastrointestinal tumor. This review focused on the relationship of tRFs and tiRNAs with the biological behavior, clinicopathological characteristics, diagnosis, treatment and prognosis of digestive system tumors, and would provide novel insights for the early detection and treatment of digestive system tumors.
Effects of food hydrocolloids on quality attributes of extruded red Jasmine rice noodle

The aim of this study was to examine the quality characteristics of extruded red Jasmine rice flour (RJF) noodle that had been prepared with hydrocolloids, namely guar gum (GG), carboxymethyl cellulose (CMC), and xanthan gum (XG) at the concentrations of 0.0 (control sample), 0.2, and 0.4% (w/w), respectively. The use of hydrocolloids had no effect on total phenolic contents, antioxidant properties (DPPH, ABTS, and FRAP), color, and X-ray diffraction patterns (p > 0.05). In contrast, the hydrocolloids tended to increase the expansion ration of the noodle. GG and CMC improved cooking, textural, and sensory properties. Ultimately, 0.2%-GG showed the lowest cooking loss (5.07%) when compared with others. Moreover, it also provided the noodle with better textural properties such as tensile strength, extensibility, hardness, cohesiveness, and chewiness (p < 0.05). For these reasons, the highest acceptability (6.75) for the noodle was achieved with GG02. XG resulted in lower overall acceptability (5.05), particularly the 0.4%-XG recipe (p < 0.05). Thus, usage of 0.2%-GG was the best option for improving the qualities of extruded RJF noodle. XG was deemed ineffective for improving the noodle.
Safety and Effectiveness of Isoniazid Preventive Therapy in Pregnant Women Living with Human Immunodeficiency Virus on Antiretroviral Therapy: An Observational Study Using Linked Population Data

Abstract Background Isoniazid preventive therapy (IPT) is widely used to protect against tuberculosis (TB) in people living with human immunodeficiency virus (HIV). Data on the safety and efficacy of IPT in pregnant women living with HIV (PWLHIV) are mixed. We used an individual-level, population-wide health database to examine associations between antenatal IPT exposure and adverse pregnancy outcomes, maternal TB, all-cause mortality, and liver injury during pregnancy through 12 months postpartum. Methods We used linked routine electronic health data generated in the public sector of the Western Cape, South Africa, to define a cohort of PWLHIV on antiretroviral therapy. Pregnancy outcomes were assessed using logistic regression; for maternal outcomes we applied a proportional hazards model with time-updated IPT exposure. Results Of 43 971 PWLHIV, 16.6% received IPT. Women who received IPT were less likely to experience poor pregnancy outcomes (adjusted odds ratio [aOR], 0.83 [95% confidence interval {CI}, .78–.87]); this association strengthened with IPT started after the first trimester compared with none (aOR, 0.71 [95% CI, .65–.79]) or with first-trimester exposure (aOR, 0.64 [95% CI, .55–.75]). IPT reduced the risk of TB by approximately 30% (aHR, 0.71 [95% CI, .63–.81]; absolute risk difference, 1518/100 000 women). The effect was modified by CD4 cell count with protection conferred if CD4 count was ≤350 cells/μL (aHR, 0.51 [95% CI, .41–.63]) vs 0.93 [95% CI, . 76–1.13] for CD4 count >350 cells/µL). Conclusions This analysis of programmatic data is reassuring regarding the safety of antenatal IPT, with the greatest benefits against TB disease observed in women with CD4 count ≤350 cells/μL.
Differentially expressed serum proteins in children with or without asthma as determined using isobaric tags for relative and absolute quantitation proteomics

Background Although asthma is one of the most common chronic, noncommunicable diseases worldwide, the pathogenesis of childhood asthma is not yet clear. Genetic factors and environmental factors may lead to airway immune-inflammation responses and an imbalance of airway nerve regulation. The aim of the present study was to determine which serum proteins are differentially expressed between children with or without asthma and to ascertain the potential roles that these differentially expressed proteins (DEPs) may play in the pathogenesis of childhood asthma. Methods Serum samples derived from four children with asthma and four children without asthma were collected. The DEPs were identified by using isobaric tags for relative and absolute quantitation (iTRAQ) combined with liquid chromatography tandem mass spectrometry (LC-MS/MS) analyses. Using biological information technology, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Cluster of Orthologous Groups of Proteins (COG) databases and analyses, we determined the biological processes associated with these DEPs. Key protein glucose-6-phosphate dehydrogenase (G6PD) was verified by enzyme linked immunosorbent assay (ELISA). Results We found 46 DEPs in serum samples of children with asthma vs. children without asthma. Among these DEPs, 12 proteins were significantly (>1.5 fold change) upregulated and 34 proteins were downregulated. The results of GO analyses showed that the DEPs were mainly involved in binding, the immune system, or responding to stimuli or were part of a cellular anatomical entity. In the KEGG signaling pathway analysis, most of the downregulated DEPs were associated with cardiomyopathy, phagosomes, viral infections, and regulation of the actin cytoskeleton. The results of a COG analysis showed that the DEPs were primarily involved in signal transduction mechanisms and posttranslational modifications. These DEPs were associated with and may play important roles in the immune response, the inflammatory response, extracellular matrix degradation, and the nervous system. The downregulated of G6PD in the asthma group was confirmed using ELISA experiment. Conclusion After bioinformatics analyses, we found numerous DEPs that may play important roles in the pathogenesis of childhood asthma. Those proteins may be novel biomarkers of childhood asthma and may provide new clues for the early clinical diagnosis and treatment of childhood asthma.
Treatment-Induced Neuropathy of Diabetes in Youth: Case Series of a Heterogeneous and Challenging Complication

Abstract Treatment-induced neuropathy of diabetes (TIND) is a small fiber neuropathy precipitated by rapid correction of hyperglycemia. Literature on TIND in pediatric diabetes is scarce. We present 7 cases of TIND in children and young adults, increasing awareness of this condition in pediatric diabetes and broadening the scope of published knowledge.
Alcohol use disorders in multidrug resistant tuberculosis (MDR-TB) patients and their non-tuberculosis family contacts in Nigeria

Introduction the main aim of this study was to determine the prevalence and associated factors of alcohol use disorder (AUD) in patients with Multi-Drug Treatment-Resistant Tuberculosis (MDR-TB) compared with their non-tuberculosis control, and its association with disease pattern and associated medical comorbidities. Methods MDR-TB patients (128) and their respective caregivers were interviewed in a treatment unit in Nigeria. Diagnosis of AUD was made using the Structured Clinical Interview for DSM-IV Axis I Disorder, information was obtained on the severity of the TB and associated health problems. Results prevalence of AUD was (21.9%) and was significantly higher among cases than in controls (2.3%), p = 0.006. Severe TB, OR = 3.33 (1.56-6.83), hematological diseases, OR = 2.34 (1.06-4.33) and HIV/AIDS, OR = 3.01 (1.67-7.01) were the strongest predictors of AUD at 95% CI. Conclusion: AUD was highly prevalent in MDR-TB and was associated with certain medical comorbidities and increased severity of the illness.
Molecular Phylogenetics and Biological Potential of Fungal Endophytes From Plants of the Sundarbans Mangrove

The Sundarbans forest in Bangladesh is the world’s largest mangrove. It is a unique ecosystem where living organisms face extreme challenges to compete for survival. Such competition results in the production of bioactive molecules which are useful for agriculture and human health. In this study, eighty fungal endophytes from nine mangrove plants growing in a region, as yet unexplored, of the Sundarbans were isolated by surface sterilisation and pure culture techniques. Among the eighty isolates subjected to a preliminary antimicrobial screening using an agar plug diffusion assay, only fifteen showed some promising activity. These were subsequently identified by polymerase chain reaction of their ITS gene. Extracts prepared from the identified isolates were screened for antimicrobial, antioxidant, cytotoxic and α-glucosidase inhibitory activities. Their total polyphenol and flavonoid content and their FRAP value were also determined. All endophytes are reported for the first time in the plants under investigation.
NITK-IT_NLP@NSURL2019: Transfer Learning based POS Tagger for Under Resourced Bhojpuri and Magahi Language

Part-of-Speech (POS) tagging is the primary step in the language processing task and also known to perform well automatically with a massive amount of training data. But the POS annotated training data are not available for most of the languages. The languages which do not have sufﬁcient resources to build statistical Natural Language Processing (NLP) applications are called low-resource languages. This paper presents the machine learning-based POS tagging for low resource languages Bhojpuri and Maghali. The work is submitted to the Shared task on Low-level NLP Tools for Bhojpuri Language and Mag-ahi Language at NSURL 2019. We develop a traditional feature-based SVM method and transfer learning-based sequence tagger using new BERT embedding, which enables better generalization to unseen words and provides regularization. The results with given minimal amounts of POS annotated data on Bho-jpuri and Maghali languages show that our proposed architecture outperformed the results of the other participants and achieved the new state-of-the-art POS tagger.
Integration of physiological knowledge into hybrid species distribution modelling to improve forecast of distributional shifts of tropical corals

Predicting species distributional shifts in future climate scenarios representing conditions that do not exist in the current world is a challenge. Species distribution models may result in misrepresented projections for species living in extreme conditions if based on truncated response functions. Model extrapolation may not detect declines that could occur if future environment conditions exceeded the physiological tolerance of the species. We developed a novel method aimed to overcome this constrain by incorporating the physiological response function of a tropical hydrocoral to temperature as a predictor variable in a Hybrid SDM.
Prediction of abnormal left ventricular geometry in patients without cardiovascular disease through machine learning: An ECG-based approach.

Cardiac remodeling is recognized as an important aspect of cardiovascular disease (CVD) progression. Machine learning (ML) techniques were applied on basic clinical parameters and electrocardiographic features for detecting abnormal left ventricular geometry (LVG), even before the onset of left ventricular hypertrophy (LVH), in a population without established CVD. After careful screening, we enrolled 528 subjects with and without essential hypertension, but no other indications of CVD. All patients underwent a full echocardiographic evaluation and were classified into 3 groups; normal geometry (NG), concentric remodeling without LVH (CR), and LVH. Abnormal LVG was identified as increased relative wall thickness (RWT) and/or left ventricular mass index (LVMi). We trained nonlinear predictive ML models, to classify subjects with abnormal LVG and calculated SHAP values to perform feature importance and interaction analysis. Hypertension, age, body mass index over the Sokolow-Lyon voltage, QRS-T angle, and QTc duration were some of the most important features. Our model was able to distinguish NG from all others (CR+LVH), with accuracy 86%, specificity 75%, sensitivity 95%, and area under the receiver operating curve (AUC/ROC) 0.89. We also trained our model to classify NG and CR (NG+CR) against those with established LVH, with accuracy 89%, specificity 97%, sensitivity 50%, and AUC/ROC 0.85. Our ML algorithm effectively detects abnormal LVG even at early stages. Innovative solutions are needed to improve risk stratification of patients without established CVD, especially in primary care settings, and ML may enable this direction. Keywords: remodeling, hypertrophy, machine learning, electrocardiogram, hypertension.
Yorùbá Gender Recognition from Speech using Attention-based BiLSTM

Gender recognition in speech processing is one of the most challenging tasks. While many studies rely on extracting features and designing enhancement classiﬁers, classiﬁcation accuracy is still not satisfactory. The remarkable improvement in performance achieved through the use of neural networks for automatic speech recognition has encouraged the use of deep neural networks in other voice techniques such as speech, emotion, language and gender recognition. An earlier study showed a signiﬁcant improvement in the gender recognition of pictures and videos. In this paper, speech is used to create a gender recognition scheme based on neural networks. Attention-based BiLSTM architecture is proposed to discover the best approach for gender identiﬁcation in Yor ` ub ´ a. Acoustic features, including time, frequency, and cepstral features are extracted to train the model. The model obtained the state-of-the-art performance in speech-based gender recognition with 99% accuracy and F 1 score.
Using Convergent Sequential Design for Rapid Complex Case Study Descriptions: Example of Public Health Briefings During the Onset of the COVID-19 Pandemic

Conceptualizing the public health response to the COVID-19 pandemic response as a complex adaptive system is useful to study its key features of emergence, interdependency, and adaptation yet practical guidance for mixed methods researchers remains limited. This study contributes an illustrative example and discussion for guiding how a mixed methods convergent sequential research design, informed by complexity theory and drawing upon open-access datasets, can rapidly generate complex case study descriptions. This article serves as an essential reference for identifying points of integration within a sequential convergent design using text mining to manage large data volumes and studying complex phenomena using a complexity informed case study-mixed methods approach to generate novel public health insights.