Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Diabetes Mellitus and Analysing Risk-Factors Correlation

INTRODUCTION: Diabetes mellitus is a common disease of the human body caused by a group of metabolic disorders where the sugar levels exceed a prolonged period, and that is very high than the usual time. It not only affects different organs of the human body but also harms a large number of the body system, in particular the blood veins and nerves. OBJECTIVES: Early predictions of this phenomenon can help us to control the disease and also to save human life. For achieving the goal, this research work mainly explores various risk factors such as kidney complications, blood pressure, hearing loss, and skin complications related to this disease using machine learning techniques and make a decision. METHODS: Machine learning techniques provide an efficient result to extract knowledge by constructing predicting models from diagnostic medical datasets collected from 200 diabetic patients from the Medical Centre Chittagong, Bangladesh using 16 attributes. Obtaining knowledge from such data can be useful to predict diabetes. In this work, we perform four popular machine learning algorithms, such as Support Vector Machine (SVM), Naive Bayes (NB), K-Nearest Neighbour (KNN) and C4.5 Decision Tree (DT), on adult population dataset to predict Diabetes Mellitus. RESULTS: C4.5 Decision Tree performs better than other algorithms for predicting diabetes with 73.5% accuracy, 72% F-measure, and 0.69 of AUC (area under ROC curve). Besides, we determine the correlation between different risk factors of Diabetes Mellitus. The highest correlation is 0.81 for blood pressure (Hypertension) complications with diabetes. CONCLUSION: In this study, both positive and negative correlation has been established between the various risk factors and diabetes. There is a positive correlation for predicting kidney complications (Nephropathy) and blood pressure (Hypertension) complications and a negative correlation at predicting hearing loss and skin complications (diabetes dermopathy) from diabetic patients. It helps a patient to be aware of the risk factors related to diabetes.
PERFORMANCE ANALYSIS OF STORAGE PROBLEMS IN BIG DATA USING COLUMN ORIENTED NOSQL DATABASES APPROACH

A column-oriented database management system stores data tables as segments of columns of data instead of rows, similar to relational database management systems. There has been a significant amount of excitement and recent work on column-oriented database systems. These databases show good performance of an order of magnitude better than traditional row-oriented database systems on analytical workloads such as those found in data warehouses, decision support, and business intelligence applications. The aim of this research work is to evaluate the two most commonly used column oriented databases in order to show their capability in tackling Big Data storage challenges. These databases are Cassandra and HBase. The databases are also compared in terms of insert, latency, reads and writes performance taking into consideration the typical workloads. The comparison allows users to choose the most appropriate database according to the specific mechanisms and application need, but in some features one outperforms other.
Compensation in seasonal leaf area dynamics and leaf longevity after defoliation in Buddleja davidii

Summary Buddleja davidii is a major invasive weed and its success is attributed to its ability to recover rapidly following defoliation. To quantify the impacts of defoliation on seasonal leaf area dynamics, we measured rates of leaf area growth and loss on cohorts of leaves on control plants and on plants that were defoliated by 66% repeatedly at monthly intervals throughout two growing seasons. The rate of leaf area growth was closely related to cumulative air temperature, but the maximum rate for the defoliated plants in the first season was 2.2 times that of the control plants. This compensational leaf growth resulted in 52% greater total emergent leaf area, attributable to increased node production (34%) and leaf size (35%), compared with control plants. Leaf longevity during the first growing season in the defoliated plants was 12% greater than that in the control plants. During the second season, the degree of compensation was greatly reduced, attributable to reduced leaf size in defoliated plants compared with the control. Total emergent leaf area over both seasons in the defoliated treatment exceeded control values by only 15%. The impact of leaf loss on the vigour in this invasive shrub may, in the short term, be less significant than would be predicted. However, the impacts of continued defoliation are likely to increase markedly in subsequent years. The study provides the basis for modelling leaf area dynamics and plant growth in response to defoliation associated with biocontrol release programmes.
Silver Nanoparticle Antiviral Property Over Masks And Other Clothing For Healthcare worker’s.

Nanoparticles is the emerging technique in current era and thus the following review paper present the synthesis of silver nanoparticles and application towards its uses as antiviral activity. The silver nanoparticles have diverted the mass attention of the scientific community and medical professionals due to their wide range of application in the biomedical fields. It especially has effective use against the microbes and infectious agents. An antiviral Nano-coatings developed by Professor Ashwini Kumar Agrawal of Indian Institute of Technology, Delhi has been approved by the Department of Science and Technology (DST), India for producing anti-COVID-19 Triple Layer Medical masks. As Silver is known to have strong antimicrobial activity against bacteria, viruses, fungus, and so on it can be used for producing these triple layer masks. In this review paper the various techniques are explained for the preparation of silver nanoparticles. Along with its importance, applications in the medical field and also can be used as antiviral agents in the preparation of masks, sanitizers, etc. IndexTerms nanoparticle, silver, biomedical,microbes,antiviral properties,coronavirus,COVID-19,precaution,medical applications
Interferon‐regulatory‐factor 1 controls Toll‐like receptor 9‐mediated IFN‐β production in myeloid dendritic cells

Activation of interferon regulatory factor (IRF)‐3 and/or IRF‐7 drives the expression of antiviral genes and the production of α/β IFN, a hallmark of antiviral responses triggered by Toll‐like receptors (TLR). Here we describe a novel antiviral signaling pathway operating in myeloid (m) dendritic cells (DC) and macrophages that does not require IRF‐3 and/or IRF‐7 but is driven by IRF‐1. IRF‐1 together with myeloid differentiation factor 88 (MyD88) or IL‐1 receptor‐associated kinase (IRAK)‐1 triggered IFN‐β promoter activation. IRF‐1 physically interacted with MyD88 and activation of mDC via TLR‐9 induced IRF‐1‐dependent IFN‐β production paralleled by rapid transcriptional activation of IFN‐stimulated genes. The NF‐κB‐dependent production of pro‐inflammatory cytokines, however, was not influenced by IRF‐1. TLR‐9 signaling through this pathway conferred cellular antiviral resistance while IRF‐1‐deficient mice displayed enhanced susceptibility to viral infection. These results demonstrate that TLR‐9 activation of mDC and macrophages contributes to antiviral immunity via IRF‐1.
89Zr-PET imaging of DNA double-strand breaks for the early monitoring of response following α- and β-particle radioimmunotherapy in a mouse model of pancreatic ductal adenocarcinoma

Rationale: The evaluation of early treatment response is critical for patient prognosis and treatment planning. When the current methods rely on invasive protocols that evaluate the expression of DNA damage markers on patient biopsy samples, we aim to evaluate a non-invasive PET imaging approach to monitor the early expression of the phosphorylated histone γH2AX in the context of pancreatic cancer targeted radionuclide therapy. Pancreatic ductal adenocarcinoma has a poor patient prognosis due to the absence of curative treatment for patients with advanced disease. There is therefore a critical need for the fast clinical translation of new therapeutic options. In line with these observations, our group has been focusing on the development of radiotheranostic agents based on a fully human monoclonal antibody (5B1) with exceptional affinity for CA19.9, an antigen overexpressed in PDAC. Two on-going clinical trials resulted from these efforts, one with 89Zr (diagnosis) and one with 177Lu (β-particle therapy). More recently, we successfully developed and evaluated in PDAC mouse models a targeted α-therapy strategy with high clinical translation potential. We aim to expedite the clinical translation of the developed radioimmunotherapy approaches by investigating the early therapeutic response and effect of radiation therapy in a PDAC mouse model via PET imaging. Methods: Mice bearing BxPC3 tumor xenografts were treated with α- and β-particle pretargeted radioimmunotherapy (PRIT), external beam radiotherapy (EBRT), or sham-treated (vehicle). The phosphorylated histone γH2AX produced as a response to DNA double strand breaks was quantified with the PET radiotracer, [89Zr]Zr-DFO-anti-γH2AX-TAT. Results: PET imaging studies in BxPC3 PDAC mouse models demonstrated increased uptake of [89Zr]Zr-DFO-anti-γH2AX-TAT (6.29 ± 0.15 %IA/g) following β-PRIT in BxPC3 PDAC xenografts as compared to the saline control group (4.58 ± 0.76 %IA/g) and EBRT control group (5.93 ± 0.76 %IA/g). Similarly, significantly higher uptake of [89Zr]Zr-DFO-anti-γH2AX-TAT was observed in tumors of the 225Ac-PRIT and EBRT (10 Gy) cohorts (7.37 ± 1.23 and 6.80 ± 1.24 %IA/g, respectively) compared to the negative control cohort (5.08 ± 0.95 %IA/g). Ex vivo γH2AX immunohistochemistry and immunofluorescence analysis correlated with in vivo 89Zr-anti-γH2AX PET/CT imaging with increased γH2AX positive cell and γH2AX foci per cell in the treated cohorts. When α-PRIT resulted in prolonged overall survival of treated animals (107.5 days) as compared to β-PRIT (73.0 days), no evidence of difference in [89Zr]Zr-DFO-anti-γH2AX-TAT uptake at the tumor site was observed, highlighting that DNA damage is not the sole radiobiology paradigm and that off-targeted (bystander) effects should be considered. Conclusions: PET imaging studies with [89Zr]Zr-DFO-anti-γH2AX-TAT following α- and β-particle PRIT in a BxPC3 PDAC subcutaneous xenograft mouse model allowed the monitoring of tumor radiobiological response to treatment.
Polymerization and Immobilization of Proteins Using Ethylchloroformate and Glutaraldehyde

By using several cross-linking agents, water insoluble protein polymers have been prepared and employed as immunoadsorbents (14). Of these reagents, ethylchloroformate (1) and glutaraldehyde (2) allowed the preparation of the most effective, stable, and specific immunoadsorbents. Glutaraldehyde is a dialdehyde known to react mainly with &-amino groups of peptides, especially lysine (5). Ethylchloroformate forms covalent bonds between free amino and carboxyl groups of polypeptide chains (1). Addition of one of these cross-linking agents to a solution of low protein concentration produces, in general, protein polymers of low molecular weight which are water-soluble, while its addition to a solutiop of high protein concentration yields protein polymers of high molecular weight which are generally water-insoluble. Our experiments showed that this insolubilization was optimal around the isoelectric point of each protein, while the antigenor antibodybinding capacity was best preserved when insolubilization was carried out at pH 5. Therefore, in order to have the possibility of rendering insoluble all proteins, at optimal conditions, even when their isoelectric point was far from 5 or when their concentration was low, the use of bovine serum albumin (BSA) as an auxiliary protein was introduced. This protein was chosen because its isoelectric point is 4.9, it possesses many lysine residues, and it is relatively cheap and easily available. When glutaraldehyde or ethylchloroformate is added to a solution containing various proteins and BSA, a cross-linking between these various protein molecules and those of BSA occurs. If the reaction is carried out at pH 5, BSA is insolubilized along with the other proteins. In that case BSA acts as the insoluble supporting matrix. Cross-linking agents can also be employed for ,the introduction of active groups into an insoluble matrix which can subsequently be used for the immobilization of proteins. Thus, when there is an excess of glutaraldehyde, one of its two aldehyde groups reacts with free amino or amide residues present in polyacrylamide gels. After washing, the remaining free active aldehyde group is available for combination with amino groups of proteins added subsequently (8).
Athena-LISA Synergies

While the science cases of Athena and LISA are individually outstanding, the additional science that the concurrent operation of the two missions could achieve may provide breakthroughs in scientific areas beyond what each individual missions is designed for. They cover topics as diverse as high-redshift systems of merging black holes over a wide range of mass and mass ratios, and bright quasars in active galaxies. These topics are explicitly covered in this White Paper. The additional science encompasses a series of fundamental questions in modern physics and astrophysics, such as: the dynamics of fluid particles in time varying, strong gravity environments; the onset of nuclear activity in the core of galaxies hosting massive black holes; the physical origin of relativistic jets around spinning black holes, and their launch and interaction with the galactic environment; the cosmic distance scale; and the measurement of the speed of gravity.
Cross-project Reopened Pull Request Prediction in GitHub

—In GitHub, pull requests may get reopened again for further modiﬁcation and code review. Prediction of within-project reopened pull requests works well if there is enough amount of training data to build the training model. However, for new projects that have a limited amount of pull requests, using training data from other projects can help to predict the reopened pull requests. Therefore, it is important to study cross-project reopened pull request prediction and help integrators in new projects. In this paper, we propose a cross-project approach that consists of building a decision tree training model based on an external project as a source project to predict the reopened pull requests in another project. We evaluate the effectiveness of cross-project prediction on 7 open source projects containing 100,622 pull requests. Experiment results show that the cross-project prediction achieves accuracy from 78.76% to 96.52%, and F1-measure from 53.34% to 90.58% across 7 projects. We examine the feature importance using the decision tree predictor and ﬁnd that the number of commits is the most important feature in the majority of projects.
Metabolism and evaporative water loss of Western Australian geckos (Reptilia : Sauria : Gekkonomorpha)

Resting metabolic rate (RMR) and evaporative water loss (EWL) were measured, and resistance (R) to evaporative water loss and water use index (WUI = EWL/RMR) were calculated, for 22 species of Western Australian gecko. For all available gecko data, body mass and temperature explained 85% of the variability in RMR (=14.5 mass0.833 100.0398 Ta µL h–1), and 70% of the variability in EWL (=0.126 mass0.539 100.049 Ta mg h–1 ). For Western Australian geckos, RMR and EWL were significantly influenced by body mass, using conventional regression and phylogenetic analyses. Resistance to evaporative water loss (R) was not significantly affected by body mass. Water use index was inversely related to body mass: WUI = 21.9 M–0.344 mg mL O2–1. There were significant differences between species for R and for standardised residuals of RMR, EWL and WUI. R was not correlated with phylogeny, and was significantly higher (P = 0.020) for saxicolous geckos (1467 s cm-1) than terrestrial geckos (797 s cm–1); arboreal geckos had an intermediate R (977 s cm–1). Species that ate termites had lower standardised linear regression residuals (P = 0.003) for RMR than did species that ate more general diets. Standardised residuals for EWL were almost significantly related to microhabitat (P = 0.053). Standardised residuals for WUI were significantly related to microhabitat (P = 0.016); saxicolous species had lower WUI than terrestrial species. Standardised linear regression residuals of the residuals from autoregression (which should be independent of both mass and phylogeny effects) still significantly correlated RMR and diet, but not EWL or WUI with microhabitat.
Information Preserving XML Schema Embedding 1

A central technical issue for the exchange, migration and integration of XML data is to find mappings from documents of a source XML (DTD) schema to documents of a target schema. While one can certainly define XML mappings in a query language such as XQuery or XSLT, such queries may be large and complex, and in practice it is often needed that XML mappings (1) guarantee type-safety and (2) preserve information. It is clearly desirable that the document produced by an XML mapping conforms to a target schema, guaranteeing type safety. But this may be difficult to check for mappings defined in XQuery or XSLT [Alon et al. 2001]. Further, since in many applications one
THE POLITICAL ECONOMIST

The evidence is overwhelming that the decisions of governments in poor countries are significantly different than in developed countries. On average, developing countries are more tolerant of corruption, more apt to expand government employment opportunities than to offer high quality education, and less likely to enforce contracts and property rights. It is no surprise, then, that in striving to understand economic development scholars have come to focus closely on the role of domestic politics and political institutions. The political explanations of persistent economic underdevelopment that have attracted greatest attention seem to boil down to three (broad) hypotheses: countries that lack political checks and balances and competitive elections cannot credibly guarantee secure property and contract rights and therefore grow slowly; interest group influence leads governments to resist development-promoting policies; and social and cultural factors, such as caste and clientelism, cripple government decision making in poor countries. This note suggests that more attention in the future should turn to a fourth factor, the dynamics of political competition and systematic differences across countries in how politicians gather voter support. One important hypothesis emerging from this fourth line of inquiry is that the extent of voter information and the credibility of pre-electoral promises of competing politicians explain dramatic policy differences between countries. Like the first hypothesis, this line of argument is explicitly comparative. It also recognizes that political credibility and voter information are likely to have historical roots. However, it goes beyond formal institutions in framing the political economy of development. Like the second and third hypotheses, this approach is concerned with the political incentives underlying specific government decisions. However, it it is more comparative in its approach and, substantively, focuses more specifically on political strategies for obtaining citizen support. This fourth approach can therefore explain phenomena that are taken as “exogenous” in much of the countryspecific literature. For example, much of the literature evokes clientelism as a fundamental feature of countries – as a basic unit of analysis. This fourth argument suggests that clientelism is a product of deeper phenomena, and it is these phenomena that explain crosscountry differences in performance.
Vibrio cholerae cytolysin is composed of an α‐hemolysin‐like core

The enteric pathogen Vibrio cholerae secretes a water‐soluble 80‐kD cytolysin, Vibrio cholerae cytolysin (VCC) that assembles into pentameric channels following proteolytic activation by exogenous proteases. Until now, VCC has been placed in a unique class of pore‐forming toxins, distinct from paradigms such as Staphyloccal α‐hemolysin. However, as reported here, amino acid sequence analysis and three‐dimensional structure modeling indicate that the core component of the VCC toxin is related in sequence and structure to a family of hemolysins from Staphylococcus aureus that include leukocidin F and α‐hemolysin. Furthermore, our analysis has identified the channel‐forming region of VCC and a potential lipid head‐group binding site, and suggests a conserved mechanism of assembly and lysis. An additional domain in the VCC toxin is related to plant lectins, conferring additional target cell specificity to the toxin.
Zooplankton in Advective Environments: The Hudson River Community and a Comparative Analysis

The temporal dynamics and spatial distributions of zooplankton in the tidal freshwater portion of the Hudson River were studied over a 3-yr period. We tested the hypothesis that advective transport regulates zooplankton biomass in the Hudson and in lakes, estuaries, and rivers for which we have published values. In the Hudson, zooplankton biomass was negatively correlated with discharge over the entire season (P < 0.0001) as well as during the warmer period of the year (P = 0.007) when biomass was greatest. The spatial distribution of zooplankton over 160-km transects was heterogeneous. Downstream changes in the abundance of a dominant species, Bosmina longirostris, indicate that certain areas of the river support net population growth whereas other areas are population sinks. We infer that zooplankton biomass in the Hudson is a function of the balance between reproduction determined by resources and losses due to advection. Zooplankton biomass differs among lakes, estuaries, and rivers in a manner consis.
Large-scale Japanese-Chinese Scientiﬁc Dictionary Construction via Pivot-based Statistical Machine Translation

Pivot-based statistical machine translation (SMT) (Wu and Wang, 2007) has been shown a possible way of constructing a dictionary for the language pairs that have scarce parallel data (Tsunakawa et al., 2009). The assumption of this method is that there is a pair of large-scale parallel data: one between the source language and an intermediate resource rich language (henceforth called pivot), and one between that pivot and the target language. Once this assumption suffices, we can use the source-pivot and pivot-target parallel data to develop a source-target term1 translation model for dictionary construction. There are two main advantages of pivot-based SMT for dictionary construction. One is that because pivot-based SMT uses the log linear model as conventional phrase-based SMT (Koehn et al., 2007) does, various features can be integrated to improve the accuracy. The other is that this method can address the data sparseness problem of directly merging the source-pivot and pivot-target terms, because it can use the portion of terms to generate new terms. However, the potential of this method has not been fully explored. Small-scale experiments in (Tsunakawa et al., 2009) showed very low accuracy of pivot-based SMT for dictionary construction.2 This paper presents our study to construct a largescale Japanese-Chinese (Ja-Zh) scientific dictionary, using large-scale Japanese-English (Ja-En) (49.1M sentences and 1.4M terms) and English-Chinese