Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Detection of Cluster Structure Changes using Relative Density Self-Organizing Maps

Knowledge of clustering changes in real-life datasets is important in many contexts, such as customer attrition analysis and fraud detection. Organizations can use such knowledge of change to adapt business strategies in response to changing circumstances. Analysts should be able to relate new knowledge acquired from a newer dataset to that acquired from an earlier dataset to understand what has changed. There are two kind of clustering changes, which are: changes in clustering structure and changes in cluster memberships. The key contribution of this paper is a novel method to automatically detect structural changes in two snapshot datasets using ReDSOM. The method identifies emerging clusters, disappearing clusters, splitting clusters, merging clusters, enlarging clusters, and shrinking clusters. Evaluation using synthetic datasets demonstrates that this method can identify automatically structural cluster changes. Moreover, the changes identified in our evaluation using real-life datasets from the World Bank can be related to actual changes.
Towards a 3D analysis in Cherenkov γ -ray astronomy

The development of a 3D or cube analysis to simultaneously fit a spectral and morphological model to the data is a challenge in Cherenkov gamma-ray astronomy. The strong variation of the instrument response functions and of the residual cosmic rays background with the observation conditions makes it very difficult to build a coherent background model across the whole energy range. Nevertheless, with improving sensitivities and angular resolution of current Cherenkov telescopes and next generation instruments such as the Cherenkov Telescope Array, the complex morphology of the regions with diffuse emission or multiple sources requires the development of this technique. We developed a prototype for cube analysis along with corresponding background models for varying observations conditions. The prototype as well as the production of background model was implemented in the software Gammapy, an open source Python package for gamma-ray Astronomy that provides tools to simulate and analyse the gamma-ray sky for imaging atmospheric Cherenkov telescopes. To validate the method, we performed a systematic comparison between this cube analysis and the classical 1D spectral fitting on point sources using a Monte Carlo simulation from the H.E. S.S. collaboration.
Recent research into the production potential of indigenous cattle with special reference to the Sanga

A review based on recent research is presented on the production of Sanga (Nguni) cattle in South and South West Africa. The high calving rate of Sanga cattle (89,6%) compared to an average of 77,4% of four other breeds was the most outstanding feature. Nguni heifers reached puberty much earlier (349,9 days) than Bonsmara (419,0 days) and Drakensberger (407,2 days) breeds. Low calving losses were evident even with an early mating system (12 months). Indigenous cattle breeds are more tick resistant and may possibly be more efficient in production than exotic breeds. Evaluation of indigenous breeds in crossbreeding systems owing to their outstanding maternal performance is recommended. 'n Oorsig gebaseer op die jongste navorsing oor produksie van Sanga(Nguni)-beeste in Suid- en Suidwes-Afrika word aangebied. Die hoe kalfpersentasie van 89,6% vir Sanga-beeste teenoor'n gemiddeld van 77,4% vir vier ander rasse was die mees uitstaande kenmerk. Nguni-verse het puberteit heelwat vroeer (349,9 dae) as Bonsmara- (419,0 dae) en Drakensbergerverse (407,2 dae) bereik. Lae kalfmortaliteit selfs met 'n vroee paringstelsel (12 maande) is aangetoon. Inheemse beesrasse is meer bosluisweerstandbiedend en kan selfs meer doeltreffend in produksie as eksotiese beesrasse wees. Die evaluering van inheemse rasse in kruisteeltstelsels as gevolg van hulle besondere maternale prestasies word aanbeveel. Keywords : Calving rate, efficiency, indegenous cattle, Nguni, production, Sanga.
Methyl methanesulphonate induced chromosomal variations in a medicinal plant Cichorium intybus L. during microsporogenesis

Genotoxic effect of MMS on gametic cells of chicory has been investigated in the present study. Progenies were raised from seeds treated with four different concentrations that is 0.04, 0.06, 0.08, 0.10 % aqueous solutions of MMS. Anther-smear studies revealed a wide range of chromosomal anomalies such as stickiness, univalents, multivalents and precocious separation of chromosomes at metaphase; bridges, laggards and polyads at anaphase and telophase stages. Such abnormalities were dose dependent and increased along with the increasing concentrations of mutagen; therefore MMS can be used as a potential mutagen in induction of genetic variability in this plant.
Identification of CHD2 Nuclear Localization Signals

According to the American Cancer Society, cancer is a group of diseases characterized by uncontrolled growth and spread of abnormal cells. The genetic alterations that cause such uncontrolled growth can disrupt the proper functioning of affected organ systems and, ultimately, can result in death. It has been suggested in recent studies that chromatin remodeling machinery may play an important role in the prevention of these diseases (1). The CHD2 gene (Chromo-domain Helicase DNA binding protein 2) is a protein thought to play an essential role in the process of chromatin remodeling, and this gene is present in a chromosomal region that is frequently lost in various cancers. Thus, in an effort to understand the role of CHD2 deficiency in cancer formation, we have generated a mutant mouse model that is deficient for Chd2 expression. Preliminary data indicate that the Chd2 deficient mice are susceptible to cancer formation. Our latest research involves the identification of the region of the CHD2 protein that allows it to enter the nucleus, where chromatin remodeling takes place. Computational analysis of the protein indicates the presence of four putative nuclear localization signals (NLS) that may be responsible for this entry into the nucleus. Three of these signals are located in the C-terminus end of the protein while the fourth is located near the N-terminus of the protein. We generated a CHD2 expression clone that contains only the N-terminus signal, and an HA-tag has been attached. The expression of this protein fragment was analyzed by immuno-fluorescence and found to localize within the nucleus with only the first putative NLS.
Diagnosis of dengue fever: roles of different laboratory test methods

Background: Dengue fever is currently the most important arthropod borne viral disease. Since occurrence of dengue infections has been an epidemic in many parts of India and complications like DHF and DSS are increasing, while at the same time the diagnosis is challenging, particularly the laboratory diagnosis is confusing, this study was conducted to evaluate the different laboratory test methods and to compare their respective efficacy, timing, advantages and disadvantages. Methods: This study was done in the Department of Microbiology in collaboration with the Department of Medicine and Pediatrics in two tertiary care medical colleges and hospitals in eastern India. Blood samples from 319 patients with clinical features suggestive of Dengue fever were included in this study. Laboratory investigations were done which included immunological assays that were performed using commercially available kits - SD dengue duo NS1Ag + Ab combo rapid test, NS1 Ag capture ELISA, IgM capture ELISA, IgG capture ELISA test for dengue and other routine tests -full blood cell count, coagulation tests, routine biochemical and lipid profile were also done. Ethical considerations were taken care of and statistical evaluations were done. Results: An increased detection of IgM antibody (46.15%) was seen in the early febrile period (1-5 days) as compared to the mid-febrile period (6-10 days), and late febrile period (6-10 days) when it is 6.89%. IgG antibody is much less in early febrile period (4.16%). Compared to mid-febrile period (24.13%), and late febrile period (62.5%). IgM antibodies were detected in 44.5% of the samples, IgG antibodies were detected in 43.5% of the samples, Rapid test was positive in 36.9% and NS1AG ELISA was detected in 43.5% of the samples in the study. Conclusions: It can be inferred from our study that for detection of dengue in the early febrile period (1-5 days), estimation of dengue-specific serum IgM is the most sensitive antibody detection method.
Feature Selection Based on Rough Set Theory Using Feature Space Decomposition for Mixed-type Data Classification

Feature selection plays a key role in many classification problems dealing with mixed-type data. The main idea of feature selection is to reduce the dimensionality of the input space while preserving the classification accuracy by selecting the most relevant input features. The rough set theory can be an appropriate way of measuring the importance of features in a classification problem, as seen in recent studies. Previous papers related to feature selection based on the rough set theory also considered property of mixedtype data, however, they were insufficient to investigate the properties of numerical and categorical features. To overcome the limitation, we suggest a concept of feature space decomposition and maintain the properties of each feature. In addition, for fair measure between numerical and categorical feature, we use Heterogeneous Euclidean-overlap Metric (HEOM). Finally, we conduct and show the experimental results to compare our proposed method with several benchmarking methods and select the appropriate features through the forward selection algorithm with various mixed-type data.
The Influence of Parkinson’s Disease and Neurotypical Aging on Cognitive Performance Among Volunteers for an Exercise-based Rehabilitative Intervention

PURPOSE To determine the impact of aging versus combined aging and disease on cognition in older adults with and without Parkinson’s disease (PD) who were volunteers for exercise based rehabilitation research. METHODS We used a multiple linear regression approach to analyze cognitive outcome measures of rehabilitation volunteers with and without PD. RESULTS Significant associations were identified between increased age and decreased performance on 8 of the 14 outcomes analyzed after controlling for false discovery rate. Of those 8 outcomes, multivariate regression analyses demonstrated an effect of disease on performance in only 4/8. In all cases, PD was associated with superior, rather than decreased performance after controlling for age. Results were unaffected by sex and education. Post-hoc comparison with available age norms demonstrated that differences between PD and Non-PD volunteers could be primarily attributed to the Non-PD group substantially underperforming versus age norms. CONCLUSIONS In rehabilitative exercise studies using volunteers, many cognitive domains decline with increasing age, consistent with previous neuropsychological studies without a rehabilitation component. However, older “neurotypical” volunteers may potentially underperform PD volunteers after controlling for age. This may be an important design consideration for rehabilitation studies with cognitive outcomes. IMPLICATIONS FOR REHABILITATION An increasing number of rehabilitation studies incorporate cognitive outcomes. Whether the overall cognitive profile of rehabilitation volunteers differs from that of neurotypical aging remains to be established. Rehabilitation volunteers with Parkinson’s disease may outperform putatively neurotypical volunteers after controlling for covariates. Cognitive impairments associated with PD in neuropsychological studies may not generalize to exercise rehabilitation volunteers.
Bearing children in unstable times: psychological traits and early parenthood in a lowest-low fertility context, Rostock 1990 - 1995

In this paper, we analyze a unique longitudinal data set from Rostock in Eastern Germany. Data collection began in the communist era and has been followed up until today. Employing proportional-hazard models, we use psychological individual-level measures (such as personality traits, social and cognitive resources, coping styles, etc.) at age 20 as determinants of the subjects´ subsequent transition rate to parenthood. We find strong evidence to support the notion that psychological factors function as proximate determinants of differential fertility. We conclude that psychological individual-level data are important in understanding patterns, especially during times when society faces massive and incalculable upheavals.
Zweier Ideal Convergent Sequence Spaces Defined By Orlicz Functions

An ideal I is a family of subsets of positive integers N which is closed under taking finite unions and subsets of its elements. In this article we introduce ideal convergent sequence spaces using Zweier transform and Orlicz function. We study some topological and algebraic properties. Further we prove some inclusion relations related to these new spaces.
Presmoothed Landmark estimators of the transition probabilities

This project was funded by FEDER Funds through “Programa Operacional Factores de Competitividade - COMPETE” and by Portuguese Funds through FCT - “Fundacao para a Ciencia e a Tecnologia”, in the form of grant PEst-OE/MAT/UI0013/2014.
Large-scale-integrated silicon photonics using microdisk and microring resonators

We review our recent work on silicon photonic devices for on-chip optical interconnects and optofluidics. On the optical interconnects front, we demonstrate coupled-resonator optical waveguides with gapless inter-cavity coupling for on-chip wide-bandwidth high-order optical channel filters and optical delay lines. We propose a 5×5 matrix switch comprising two-dimensionally cascaded microring resonator-based electrooptic switches for network-on-chip applications and demonstrate a 2×2 matrix switch as a proof-of-concept. We demonstrate cavity-enhanced photocurrent generation in a p-i-n diode embedded microring resonator for wavelength-selective photodetection and monitoring on-chip optical networks. We also investigate a serial-cascaded double-microring-based silicon photonic circuit for high-speed on-chip clock-recovery applications. On the optofluidics front, we study silicon nitride based waveguides with integrated microfluidic channels for optical manipulation of microparticles.
Exploring microRNA Regulation of Cancer with Context-Aware Deep Cancer Classifier

BACKGROUND MicroRNAs (miRNAs) are small, non-coding RNA that regulate gene expression through post-transcriptional silencing. Differential expression observed in miRNAs, combined with advancements in deep learning (DL), have the potential to improve cancer classification by modelling non-linear miRNA-phenotype associations. We propose a novel miRNA-based deep cancer classifier (DCC) incorporating genomic and hierarchical tissue annotation, capable of accurately predicting the presence of cancer in wide range of human tissues. METHODS miRNA expression profiles were analyzed for 1746 neoplastic and 3871 normal samples, across 26 types of cancer involving six organ sub-structures and 68 cell types. miRNAs were ranked and filtered using a specificity score representing their information content in relation to neoplasticity, incorporating 3 levels of hierarchical biological annotation. A DL architecture composed of stacked autoencoders (AE) and a multi-layer perceptron (MLP) was trained to predict neoplasticity using 497 abundant and informative miRNAs. Additional DCCs were trained using expression of miRNA cistrons and sequence families, and combined as a diagnostic ensemble. Important miRNAs were identified using backpropagation, and analyzed in Cytoscape using iCTNet and BiNGO. RESULTS Nested four-fold cross-validation was used to assess the performance of the DL model. The model achieved an accuracy, AUC/ROC, sensitivity, and specificity of 94.73%, 98.6%, 95.1%, and 94.3%, respectively. CONCLUSION Deep autoencoder networks are a powerful tool for modelling complex miRNA-phenotype associations in cancer. The proposed DCC improves classification accuracy by learning from the biological context of both samples and miRNAs, using anatomical and genomic annotation. Analyzing the deep structure of DCCs with backpropagation can also facilitate biological discovery, by performing gene ontology searches on the most highly significant features.
The Applicability of the Social Enterprise in a Small State: The Case of Malta**

The main objective of this study is to assess the social, financial and corporate governance (CG) implications of the proposed social enterprise (SE) legislation in Malta. In light of such implications, the study also assesses the applicability of the SE under such legislation. A mixed methodology was adopted. Fifteen interviews were held with experts. Such data was supplemented by 52 valid responses to a questionnaire sent both to co-operatives and voluntary organisations (VOs) in Malta. The study concludes that the proposed legislation has various positive social, financial and CG implications and that the SE, as being proposed, is applicable and filling a void within the Maltese environment. Although such legislation offers both a new legal form and a label, its reference to the Companies Act which ignores SEs’ unique social dimension is questionable. Alternatively, a holistic SE regulatory framework may be developed. Furthermore, statutory thresholds, such as for dividend distribution and trade income, are to be possibly rendered more flexible. This study aspires to raise awareness about the implications of a proposed regulatory framework in Malta, hence hopefully promoting the application of the concept.
When knowing more means knowing less: Understanding the impact of computer experience on e‑learning and e‑learning outcomes

Students often report feeling more overloaded in courses that use e-learning environments compared to traditional face-to-face courses that do not use such environments. Discussions here consider online design and organizational factors that might contribute to students’ reports of information overload. It was predicted that certain online factors might contribute to stimulus overload and possibly students’ perceived overload, rather than information overload per se. User characteristics and a range of design and organizational factors that might contribute to perceived overload are discussed and hypotheses of how such factors might affect learning outcomes are also discussed. An experiment was conducted to test predictions that (i) students’ past online experience, (ii) the organization and relevance of online information, and (iii) the level of task difficulty affect (i) learning outcomes, (ii) students’ perceptions of information overload, and (iii) students’ perceptions of having enough time to complete experimental tasks. A total of 187 participants were tested in four experimental conditions that manipulated the organization and relevance of online material that students had to learn (ie, (i) a stimulus-low environment, where the material to be learned was presented as scrolling text, with no other stimuli present; (ii) a familiar environment, where the material to be learned was set within the borders of a familiar course Web site; (iii) a stimulus-rich or stimulus-noisy environment, where the material to be learned was set within the borders of an Amazon.com Web page (a Web site where you can search for, and buy books, videos and other products online); (iv) a PDF file environment, where the material to be learned was presented as a PDF file that resembled an online duplicate of the same material in the course textbook). Findings suggested that overly busy online environments that contain irrelevant information (ie, stimulus-rich or stimulus-noisy online environment) had a negative impact on learning for students ranked “high” on experience with e-learning technologies, but no impact on learning for other students (as measured by a knowledge test of material studied during experimental sessions). There is no doubt that online environments contain vast amounts of information and stimuli; often some of which are irrelevant and distracting. How one handles irrelevant or distracting information and stimuli can have a significant impact on learning. Surprisingly, results here suggest that overload affected only experienced students. Perceptual load hypotheses are discussed to explain what initially seemed to be counterintuitive results. This paper examines literature that considers factors that can affect learning online, strategies for how teachers can ensure positive outcomes for the technology-based classroom, and strategies for avoiding online pitfalls that might leave students frustrated or burdened with feelings of overload.
Flotation separation of scheelite from calcite using sodium polyacrylate as depressant

The depressing properties of sodium polyacrylate (PA-Na) for calcite from scheelite were studied by microflotation experiments, zeta potentials, X-ray photoelectron spectroscopy (XPS) and density functional theory (DFT) calculation. Flotation results revealed that the selective depression effect of PA-Na was better than that of sodium silicate (Na2SiO3), and PA-Na can depress calcite more effectively than scheelite. The flotation recovery of scheelite and calcite kept at about 75% and 15% respectively at the pulp pH 9.3~9.6 and PA-Na concentration from 37.5 mg/dm3 to 50 mg/dm3. The zeta potentials of the minerals were significantly altered and the zeta potential of calcite became more negative than scheelite. XPS analysis deduced the occurrence of chemisorption between PA-Na and mineral surfaces, and the chemisorption of PA-Na on calcite was stronger than on scheelite. The results from DFT calculation demonstrated that the absolute value of the adsorption energy in the presence of PA-Na on the surface of calcite {104} was larger than on the surface of scheelite {111}. With the combination of the analysis, it could be concluded that calcite was more easily depressed than scheelite, and this finding remarkably matched with the microflotation experimental results. Furthermore, by using PA-Na as depressant, the flotation separation of scheelite from calcite can be achieved by controlling the flotation pH and PA-Na dosage.
Educational Action Research to Achieve the Essential Competencies of the Future

Abstract This article analyses the conformity of the educational action research (EAR) process for the improvement of selected competencies that will be necessary in the near future for each active and responsible person. The most requested competencies in the near and midterm future are determined in accordance with near future structural requirements of labour demand, determined by international organoizations. The contribution is based upon the outcomes of the action research carried out in the internet environment, by Bachelor students majoring in information technologies at Riga Technical University, Latvia. Working in groups, they supplemented each other’s ideas, developing living theories. The content analysis of the students’ supplementary submissions and living theories was carried out to identify the features indicating the development of student actions towards the improvement of the most necessary competencies in the near future. To accomplish the objective of action research, at first, the most requested competencies in the near and midterm future were determined. Then the changes of the features, mentioned during the three action research cycles were identified. Finally, the most important features of the students’ actions indicating the development of two of key competencies, namely, Novel and adaptive thinking and Design Mindset, were identified. Perfection of referred competencies is viewed as the substantial part of education for sustainable development (ESD). The conclusions were drawn about the development of students’ competencies according to the future needs identified during the action research process on the internet.