Miracle-dz/UniFAR-FTUs huggingface dataset:
MicroRNAs-Mediated Regulation of Skeletal Muscle GLUT4 Expression and Translocation in Insulin Resistance

The solute carrier family 2 facilitated glucose transporter member 4 (GLUT4) plays a key role in the insulin-induced glucose uptake by muscle and adipose tissues. In prediabetes and diabetes, GLUT4 expression/translocation has been detected as reduced, participating in mechanisms that impair glycemic control. Recently, a class of short endogenous noncoding RNAs named microRNAs (miRNAs) has been increasingly described as involved in the posttranscriptional epigenetic regulation of gene expression. The present review focuses on miRNAs potentially involved in the expression of GLUT4 expression, and proteins related to GLUT4 and translocation in skeletal muscle, seeking to correlate them with insulin resistance and diabetes. So far, miR-21a-5p, miR-29a-3p, miR-29c-3p, miR-93-5p, miR-106b-5p, miR-133a-3p, miR-133b-3p, miR-222-3p, and miR-223-3p have been reported to directly and/or indirectly regulate the GLUT4 expression; and their expression is altered under diabetes-related conditions. Besides, some miRNAs that have been linked to the expression of proteins involved in GLUT4 translocation machinery in muscle could also impact glucose uptake. That makes these miRNAs promising targets for preventive and/or therapeutic approaches, which could improve glycemic control, thus deserving future new investigations.
Design and Analysis of OCPA Secure Encrypted Databases

In this thesis we present the work done in the construction of new Database model eDB under the Database as a service (DaaS) framework. The main challenge in the DaaS model is to provide data security from service provider along with efficient computation of queries on the cloud database. To handle both the challenges (data security and efficient computation), we use multiple partial homomorphic encryption schemes where each scheme handles a specific database operator, and the data is encrypted under these multiple encryptions such that cipher texts of these schemes co-exist at the server. For analyzing the security of eDB, we formally define the security model (IND-OCPA) against our system and theoretically layout the arguments to prove the security of the system against the security model. We have also developed the idea of query processing for floating point numbers in encrypted database. A new efficient storage strategy in form of Encryption Dictionary is presented in this thesis. The query execution time for queries involving only order predicate clauses improved significantly in Encryption Dictionary model as to comparison with traditional horizontal storage model with a trade off on aggregate queries where it performed slightly bad.
Code Comprehending Measure (CCM)

software complexity, accurately, plays a vital role in life cycle of thesoftware. Many metrics have been proposed in the past like LOC,McCabes‟ cyclomatic measure, Halstead‟s measures and cognitivemeasures. This paper proposes a new method to measure thesoftware complexity, by not only taking into account the internalstructure of the algorithm in terms of the total cognitive weights ofthe basic control structures but also by quantifying the flow of databetween the various basic control structures and data volume factor(variables and operators) used within basic control structure. Thepreliminary tests show that this metrics is independent of theexisting measures. Comparison with some existing measures hasbeen done to prove the robustness of this new metrics.
Toward the Narrow Approach to Posttraumatic Stress Disorder Diagnostic Criteria: An Item Response Theory Analysis

ii Acknowledgments. iii List of Tables . vii List of Figures . viii List of Abbreviations . ix Introduction . 1 IRT Overview . 10 IRT versus CTT . 11 IRT Assumptions and Components . 13 Model Selection in IRT . 17 IRT and PTSD . 20 DIF across Gender . 25 Limitations of Existing PTSD and IRT Literature . 28 Method . 34 Participants and Procedure . 34 Measures . 36 Data Analytic Plan . 37 Results . 40 Best-fitting Model . 40
Pressure measurement with fiber-optic sensors: commercial technologies and applications

Mainly three technologies are presently commercially available for pressure measurement with fiber-optic sensors: intensity-based, fiber Bragg gratings and Fabry-Pérot. The first one is probably the simplest and the cheapest but it is limited to applications where having 2 fixed or up to 4 flexible fibers is not an issue, whereas the two other technologies require only one fiber. With generally low sensitivity to pressure and prohibitive cost for non multiplexed measurements, fiber Bragg grating pressure sensors are still limited to marginal applications. Fabry-Pérot technology is the best compromise offering at affordable price a great flexibility in terms of pressure ranges, high sensitivity and miniature size suitable for most applications including disposable medical devices.
Mass Spectrometry-Based N-Glycomics of Colorectal Cancer

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide. An increased molecular understanding of the CRC pathology is warranted to gain insights into the underlying molecular and cellular mechanisms of the disease. Altered protein glycosylation patterns are associated with most diseases including malignant transformation. Recent advances in mass spectrometry and bioinformatics have accelerated glycomics research and present a new paradigm for cancer biomarker discovery. Mass spectrometry (MS)-based glycoproteomics and glycomics, therefore, hold considerable promise to improve the discovery of novel biomarkers with utility in disease diagnosis and therapy. This review focuses on the emerging field of glycomics to present a comprehensive review of advances in technologies and their application in studies aimed at discovering novel glycan-based biomarkers. We will also discuss some of the challenges associated with using glycans as biomarkers.
Fast Mixing for Discrete Point Processes

We investigate the systematic mechanism for designing fast mixing Markov chain Monte Carlo algorithms to sample from discrete point processes under the Dobrushin uniqueness condition for Gibbs measures. Discrete point processes are defined as probability distributions $\mu(S)\propto \exp(\beta f(S))$ over all subsets $S\in 2^V$ of a finite set $V$ through a bounded set function $f:2^V\rightarrow \mathbb{R}$ and a parameter $\beta>0$. A subclass of discrete point processes characterized by submodular functions (which include log-submodular distributions, submodular point processes, and determinantal point processes) has recently gained a lot of interest in machine learning and shown to be effective for modeling diversity and coverage. We show that if the set function (not necessarily submodular) displays a natural notion of decay of correlation, then, for $\beta$ small enough, it is possible to design fast mixing Markov chain Monte Carlo methods that yield error bounds on marginal approximations that do not depend on the size of the set $V$. The sufficient conditions that we derive involve a control on the (discrete) Hessian of set functions, a quantity that has not been previously considered in the literature. We specialize our results for submodular functions, and we discuss canonical examples where the Hessian can be easily controlled.
Salient local visual features for shape-based 3D model retrieval

In this paper, we describe a shape-based 3D model retrieval method based on multi-scale local visual features. The features are extracted from 2D range images of the model viewed from uniformly sampled locations on a view sphere. The method is appearance-based, and accepts all the models that can be rendered as a range image. For each range image, a set of 2D multi-scale local visual features is computed by using the scale invariant feature transform [22] algorithm. To reduce cost of distance computation and feature storage, a set of local features describing a 3D model is integrated into a histogram using the bag-of-features approach. Our experiments using two standard benchmarks, one for articulated shapes and the other for rigid shapes, showed that the methods achieved the performance comparable or superior to some of the most powerful 3D shape retrieval methods.
Teacher’s Perception of Principal Leadership on Self-efficacy

Few studies have identified the factors of principal leadership that affects teacher self-efficacy. But for Indonesia context, through the Ministry of Education and Culture’s (MoEC) programs, principals could exercise their leadership to improve teacher self-efficacy was not clearly stated in previous research. To address this gap in the literature, this case study examines what are the principal leadership practices influence teacher self-efficacy at elementary schools in Bandung, Indonesia. This study used triangulation data which include questionnaire, interview and observation to homeroom teachers and principals in two elementary schools in Bandung, Indonesia. As a result, there was no significant difference of teacher selfefficacy degree between model school and regular school. However, from the qualitative analysis, the most important principal leadership practices to improving teacher self-efficacy is preserve the working environment which provides the opportunities for their independent self-oriented learning. Keywords— principal leadership; teacher self-efficacy
Design, experimental validation, and comparison of two model-based EKF observers for lateral vehicle dynamics estimation

One of the most important tasks of the vehicle dynamics estimation problem is to obtain the longitudinal, lateral, and vertical forces acting upon the wheels. These variables are fundamental for studying vehicle controllability and stability. However, they are difficult to obtain in terms of measurement techniques. Regarding lateral/tire forces, two observers based on the state-observer Extended Kalman Filter (EKF) theory and on the dynamic responses of a vehicle instrumented with standard sensors are proposed, discussed and compared in this study. The first observer estimates the lateral forces per axle using a random walk model, and then calculates the individual lateral tire forces on the basis of the vertical tire forces distribution. The second observer directly estimates the lateral forces per tire using a transient relaxation model. The developed observers are able to work in real-time in normal and in critical driving situations. Performances are tested using a laboratory car running on a wet track.
Competence Visualizer: generating competence patterns of organizational groups

This paper describes and evaluates the design of Competence Visualizer (CV), a competence system generating competence patterns of organizational groups. The system provides novel features that: (1) make it possible to survey competence status of teams in varying sizes at a specific moment; (2) handle information about both existing competencies and competence interests; and (3) manage snapshots of a particular point of time and development over a certain period regarding existing competencies and competence interests. The results from the system evaluation include fields of application, future design challenges, and organizational issues. A first conclusion is that competence systems need the potential to handle flexible visualizations of existing competencies as well as competence interests of organizational members. A second conclusion is that organizational issues, such as incentives and management, are critical in order to attain data quality in a competence system.
Comparison of pressure‐saturation characteristics derived from computed tomography and lattice Boltzmann simulations

A Shan‐Chen–type multiphase lattice Boltzmann (LB) model was applied to observed computed microtomography data from water‐air and water‐Soltrol displacement experiments in a glass bead porous medium. Analysis of the Bond, Reynolds, and Capillary numbers for these systems showed that capillary forces were dominant removing the need to model viscous, gravitational, and density effects. A numerical parameterization of the LB model yielded lattice surface tension and contact angle, and appropriate pressure boundary conditions. Two scaling relations provided a link between lattice pressure and physical pressure and lattice time and physical time. Results showed that there was a good match between measured and simulated pressure‐saturation data for the water‐air system, but that there were large differences between the simulations and observations for the water‐Soltrol system. The discrepancies for the water‐Soltrol system were probably due to inconsistencies between experimental conditions and simulated conditions such as nonzero contact angle in the experiments. Analysis of saturation profiles indicated increasing saturation near the wetting boundary and decreasing saturations near the nonwetting boundary. We attribute these saturation transitions to pore‐neck and percolation effects. While computationally intensive, results of this study were very encouraging for the application of LB simulations to microscale interfacial phenomena. Future studies will carry out a further validation in terms of interfacial areas, contact lines, and fluid distributions.
Efficient Iris Recognition through Improvement of Feature Vector and Classifier

In this paper, we propose an efficient method for personal identification by analyzing iris patterns that have a high level of stability and distinctiveness. To improve the efficiency and accuracy of the proposed system, we present a new approach to making a feature vector compact and efficient by using wavelet transform, and two straightforward but efficient mechanisms for a competitive learning method such as a weight vector initialization and the winner selection. With all of these novel mechanisms, the experimental results showed that the proposed system could be used for personal identification in an efficient and effective manner.
Association of primary open-angle glaucoma with mitochondrial variants and haplogroups common in African Americans

Purpose To estimate the population frequencies of all common mitochondrial variants and ancestral haplogroups among 1,999 subjects recruited for the Primary Open-Angle African American Glaucoma Genetics (POAAGG) Study, including 1,217 primary open-angle glaucoma (POAG) cases and 782 controls, and to identify ancestral subpopulations and mitochondrial mutations as potential risk factors for POAG susceptibility. Methods Subject classification by characteristic glaucomatous optic nerve findings and corresponding visual field defects, as defined by enrolling glaucoma specialists, stereo disc photography, phlebotomy, extraction of total DNA from peripheral blood or saliva, DNA quantification and normalization, PCR amplification of whole mitochondrial genomes, Ion Torrent deep semiconductor DNA sequencing on DNA pools (“Pool-seq”), Sanger sequencing of 3,479 individual mitochondrial DNAs, and bioinformatic analysis. Results The distribution of common African haplogroups within the POAAGG study population was broadly similar to prior surveys of African Americans. However, the POAG case population was found to be enriched in L1c2 haplogroups, which are defined in part by missense mutations m.6150G>A (Val83Ile, odds ratio [OR] 1.8, p=0.01), m.6253C>T (Met117Thr, rs200165736, OR 1.6, p=0.04), and m.6480G>A (Val193Ile, rs199476128, OR 4.6, p=0.04) in the cytochrome c oxidase subunit 1 (MT-CO1) gene and by a variant, m.2220A>G (OR 2.0, p=0.01), in MT-RNR2, which encodes the mitochondrial ribosomal 16s RNA gene. L2 haplogroups were predicted to be overrepresented in the POAG case population by Pool-seq, and the difference was confirmed to be significant with Sanger sequencing, that targeted the L2-associated variants m.2416T>C (rs28358580, OR 1.2, p=0.02) and m.2332C>T (OR 1.2, p=.02) in MT-RNR2. Another variant within MT-RNR2, m.3010G>A (rs3928306), previously implicated in sensitivity to the optic neuropathy-associated antibiotic linezolid, and arising on D4 and J1 lineages, associated with Leber hereditary optic neuropathy (LHON) severity, was confirmed to be common (>5%) but was not significantly enriched in the POAG cases. Two variants linked to the composition of the gut microbiome, m.15784T>C (rs527236194, haplogroup L2a1) and m.16390G>A (rs41378955, L2 haplogroups), were also enriched in the case DNA pools. Conclusions These results implicate African mtDNA haplogroups L1c2, L1c2b, and L2 as risk factors for POAG. Approximately one in four African Americans have these mitochondrial ancestries, which may contribute to their elevated glaucoma risk. These haplogroups are defined in part by ancestral variants in the MT-RNR2 and/or MT-CO1 genes, several of which have prior disease associations, such as MT-CO1 missense variants that have been implicated in prostate cancer.
Genetic Variations in MicroRNA-Related Genes Are Novel Susceptibility Loci for Esophageal Cancer Risk

MicroRNAs (miRNA) can act as oncogenes or tumor suppressors and modulate the expression of approximately one third of all human genes. To test the hypothesis that adverse alleles in miRNA-related genes may increase the risk for esophageal cancer, we assessed the associations between esophageal cancer risk and 41 potentially functional single nucleotide polymorphisms (SNP) in 26 miRNA-related genes in a case-control study of 346 Caucasian esophageal cancer patients (85.5% with esophageal adenocarcinoma) and 346 frequency-matched (age, gender, and ethnicity) controls. Seven SNPs were significantly associated with esophageal cancer risk. The most notable finding was that the SNP rs6505162, which is located in the pre-mir423 region, was associated with a per-allele odds ratio of 0.64 [95% confidence interval (95% CI), 0.51-0.80; P for trend < 0.0001]. This association remained significant after we corrected for multiple comparisons. A common haplotype of the GEMIN4 gene was associated with a significantly reduced risk of esophageal cancer (odds ratio, 0.65; 95% CI, 0.42-0.99). We did a combined unfavorable genotype analysis to further evaluate the cumulative effects of the promising (risk associated) SNPs. In comparison with the low-risk group (fewer than three unfavorable genotypes), the medium-risk group (three unfavorable genotypes) had a 2.00-fold (95% CI, 1.31-3.08) increased risk and the high-risk group (more than three unfavorable genotypes) had a 3.14-fold (95% CI, 2.03-4.85) increased risk (P for trend < 0.0001). Results for the risk of esophageal adenocarcinoma were similar to the overall risk results. The present study provides the first evidence that miRNAs may affect esophageal cancer risk in general and that specific genetic variants in miRNA-related genes may affect esophageal cancer risk individually and jointly.
NileTMRG at SemEval-2016 Task 5: Deep Convolutional Neural Networks for Aspect Category and Sentiment Extraction

This paper describes our participation in the SemEval-2016 task 5, Aspect Based Sentiment Analysis (ABSA). We participated in two slots in the sentence level ABSA (Subtask 1) namely: aspect category extraction (Slot 1) and sentiment polarity extraction (Slot 3) in English Restaurants and Laptops reviews. For Slot 1, we applied different models for each domain. In the restaurants domain, we used an ensemble classifier for each aspect which is a combination of a Convolutional Neural Network (CNN) classifier initialized with pretrained word vectors, and a Support Vector Machine (SVM) classifier based on the bag of words model. For the Laptops domain, we used only one CNN classifier that predicts the aspects based on a probability threshold. For Slot 3, we incorporated domain and aspect knowledge in one ensemble CNN classifier initialized with fine-tuned word vectors and used it in both domains. In the Restaurants domain, our system achieved the 2 nd and the 3 rd places in Slot 1 and Slot 3 respectively. However, we ranked the 8 th in Slot 1 and the 5 th in Slot 3 in the Laptops domain. Our extended experiments show our system could have ranked 2 nd in the Laptops domain in Slot 1 and Slot 3, had we followed the same approach we followed in the Restaurants domain in slot 1 and trained each domain separately in Slot 3.
A tool for teacher reflection on the response to diversity in schools

This article describes the design process of a tool for teacher reflection on the response to the diversity of students in schools. The tool has been checked by 31 British and Spanish researcher ‘inter-judges’ to ensure its content validity. These professionals were asked to draw on their knowledge and experience of response to diversity, inclusive education and research methodology. The paper includes (1) the discourse created through the semi-structured interviews with the British participants during the revision of the initial version of the tool, (2) the rating of the material generated through a group discussion of researchers from the home university of the authors in Spain, and (3) the evaluation of other Spanish reviewers, who completed a custom-built evaluation chart, using the aggregated individual method. The quantitative and qualitative information gleaned from the chart was analyzed with IBM SPSS 22.0 and Atlas.ti 7 software. The findings, opinions and suggestions to change have been incorporated into the final version of the tool, which we have called Themis Inclusion Tool. The conclusions drawn are that it is a new resource that may serve as a starting point for improvement processes geared towards more inclusive practices in schools.
Non-Language Characteristics of Instructional Services for Language-Minority Students

Educational policies toward immigrant and language-minority populations are a matter of considerable debate, as is the scientific research that forms the basis for these policies. This study examined the educational programs and instructional services that public elementary schools in the United States mainland (state of New Jersey) provided to children arriving from Puerto Rico. (N = 251 children, 155 classrooms, 71 schools.) The data show that the various types of school programs that educators design especially for language-minority students (such as English-as-a-Second-Language and bilingual education programs) differ from each other and from mainstream English-monolingual programs not only in the features that pertain to the language of instruction but also in other characteristics, frequently overlooked: for example, the number and types of instructors per student, instructors’ qualifications, and fragmentation of instruction. These program characteristics are, at least in theory, as likely to influence student achievement as are those that pertain to the language of instruction. The findings raise questions about the validity of conclusions often drawn from studies of the effectiveness of bilingual education or other school programs for language-minority populations.
Confidence-based Concept Discovery in Multi-Relational Data Mining

Multi-relational data mining has become popular due to the limitations of propositional prob- lem definition in structured domains and the ten- dency of storing data in relational databases. Several relational knowledge discovery systems have been de- veloped employing various search strategies, heuris- tics, language pattern limitations and hypothesis eval- uation criteria, in order to cope with intractably large search space and to be able to generate high- quality patterns. In this work, a new ILP-based con- cept discovery method is described in which user- defined specifications are relaxed. Moreover, this new method directly works on relational databases. In ad- dition to this, a new confidence-based pruning is used in this technique. A set of experiments are conducted to test the performance of the new method.