Miracle-dz/UniFAR-FTUs huggingface dataset:
Short-term efficacy and safety of repaglinide versus glimepiride as augmentation of metformin in treating patients with type 2 diabetes mellitus

Background: Consistent evidence is still lacking on which one, glimepiride plus metformin or repaglinide plus metformin, is better in treating type 2 diabetes mellitus (T2DM). Therefore, this study was conducted to compare the short-term efficacy and safety of these two methods in treating T2DM. Methods: The literature research dating up to August 2018 was conducted in the electronic databases. The randomized controlled trials (RCTs) comparing the short-term (treatment period ≤12 weeks) efficacy and safety of these two methods in treating patients with T2DM were included. No language limitation was used in this study. The decreased hemoglobin A1c (HbA1c), fasting plasma glucose (FPG), and 2h plasma glucose (2hPG) levels were used as the primary outcome to assess the efficacy, and the adverse events and hypoglycemia were used as the secondary outcome to assess the safety. Results: In total, 11 RCTs composed of 844 T2DM patients were included. The results showed that there were no significant differences in decreasing HbA1c and FPG levels between the two methods, but the estimated standardized mean differences favored the repaglinide plus metformin. Meanwhile, the repaglinide plus metformin was significantly more effective in decreasing 2hPG levels than glimepiride plus metformin. In addition, fewer patients reported adverse events and experienced hypoglycemia in the repaglinide plus metformin group. Conclusion: These results indicated that the repaglinide plus metformin might have some advantages over glimepiride plus metformin in the short-term treatment of patients with T2DM, and should be further explored.
Analyses of Subgenomic Promoters of Hibiscus Chlorotic Ringspot Virus and Demonstration of 5′ Untranslated Region and 3′-Terminal Sequences Functioning as Subgenomic Promoters

ABSTRACT Hibiscus chlorotic ringspot virus (HCRSV), which belongs to the genus Carmovirus, generates two 3′-coterminal subgenomic RNAs (sgRNAs) of 1.4 kb and 1.7 kb. Transcription start sites of the two sgRNAs were identified at nucleotides (nt) 2178 and 2438, respectively. The full promoter of sgRNA1, a 118-base sequence, is localized between positions +6 and −112 relative to its transcription start site (+1). Similarly, a 132-base sequence, from +6 to −126, defines the sgRNA2 promoter. Computer analysis revealed that both sgRNA promoters share a similar two-stem-loop (SL1 + SL2) structure, immediately upstream of the transcription start site. Mutational analysis of the primary sequence and secondary structures showed further similarities between the two subgenomic promoters. The basal portion of SL2, encompassing the transcription start site, was essential for transcription activity in each promoter, while SL1 and the upper portion of SL2 played a role in transcription enhancement. Both the 5′ untranslated region (UTR) and the last 87 nt at the 3′ UTR of HCRSV genomic RNA are likely to be the putative genomic plus-strand and minus-strand promoters, respectively. They function well as individual sgRNA promoters to produce ectopic subgenomic RNAs in vivo but not to the same levels of the actual sgRNA promoters. This suggests that HCRSV sgRNA promoters share common features with the promoters for genomic plus-strand and minus-strand RNA synthesis. To our knowledge, this is the first demonstration that both the 5′ UTR and part of the 3′ UTR can be duplicated and function as sgRNA promoters within a single viral genome.
Reversible Data Hiding with Contrast Enhancement by Histogram Shifting

In this paper, a new reversible Data Hiding algorithm (RDH) is presented for the images with poor visual quality . The proposed method can do the data hiding and improves the visual quality of the host image at the same time. The visual quality of the host image improved by enhancing the contrast. In this algorithm the highest two peaks in the histogram are chosen for data embedding, peaks before and after those two peaks are shifted repeatedly to achieve the contrast enhancement. Some side data also embedded along with the intended data into the host image, for the complete recovery. The proposed algorithm was tested on two images, the evaluated results shown that the contrast of the images was improved after data embedding . Hence this algorithm achieves the data hiding and contrast enhancement simultaneously.
Random walks based multi-image segmentation: Quasiconvexity results and GPU-based solutions

We recast the Cosegmentation problem using Random Walker (RW) segmentation as the core segmentation algorithm, rather than the traditional MRF approach adopted in the literature so far. Our formulation is similar to previous approaches in the sense that it also permits Cosegmentation constraints (which impose consistency between the extracted objects from ≥ 2 images) using a nonparametric model. However, several previous nonparametric cosegmentation methods have the serious limitation that they require adding one auxiliary node (or variable) for every pair of pixels that are similar (which effectively limits such methods to describing only those objects that have high entropy appearance models). In contrast, our proposed model completely eliminates this restrictive dependence - the resulting improvements are quite significant. Our model further allows an optimization scheme exploiting quasiconvexity for model-based segmentation with no dependence on the scale of the segmented foreground. Finally, we show that the optimization can be expressed in terms of linear algebra operations on sparse matrices which are easily mapped to GPU architecture. We provide a highly specialized CUDA library for Cosegmentation exploiting this special structure, and report experimental results showing these advantages.
Neurological impairments and sleep–wake behaviour among the mentally retarded

The objective of the present study was to evaluate the relationship between the sleep–wake behaviour and neurological impairments among mentally retarded people. The sleep–wake behaviour of 293 mentally retarded subjects living in a rehabilitation center was studied by a standardized observation protocol carried out by trained staff members. The protocol consisted of brief check‐ups of the subjects’ sleep–wake status at 20‐min intervals for five randomly chosen 24‐h periods during 4 months. From the raw data five sleep–wake behaviour variables were formed. The data concerning the subject characteristics (age, body mass index (BMI), gender, degree of mental retardation, presence of locomotor disability, that of epilepsy, blindness or deafness and the usage of psychotropic medications) were collected from the medical records. Two main findings emerged: (1) severe locomotor disablity, blindness and active epilepsy were found to be independent predictors of increased daytime sleep and increased number of wake–sleep transitions and (2) the subjects with a combination of two or all three of these impairments had a significantly more fragmented and abnormally distributed sleep than those with none or milder forms of these impairments. Age, BMI, degree of mental retardation and the studied medications played a minor role in the sleep disturbances of the study population. Finally, deafness was not found to be associated with any of the measured sleep–wake variables.
A critical reflection on Big Data: Considering APIs, researchers and tools as data makers

This paper looks at how data is ‘made’, by whom and how. Rather than assuming data already exists ‘out there’, waiting to simply be recovered and turned into findings, the paper examines how data is co–produced through dynamic research intersections. A particular focus is the intersections between the application programming interface (API), the researcher collecting the data as well as the tools used to process it. In light of this, this paper offers three new ways to define and think about Big Data and proposes a series of practical suggestions for making data.
Scene-Specific Memory for Objects: A Model of Episodic Memory Impairment in Monkeys with Fornix Transection

A series of five experiments investigated the relationship between object memory and scene memory in normal and fornix-transected monkeys. An algorithm created formally defined background and objects on a large visual display; the disposition of some particular objects in particular places in a particular background constitutes a formally defined scene. The animals learned four types of discrimination problem: (1) object-in-place discrimination learning, in which the correct (rewarded) response was to a particular object that always occupied the same place in a particular unique background, (2) place discrimination learning, in which the correct response was to a particular place in a unique background, with no distinctive object at that place, (3) object discrimination learning in unique backgrounds, in which the correct response was to a particular object that could occupy one or the other of two possible places in a unique background, and (4) object discrimination learning in varying backgrounds, in which the correct response was to a particular object that could appear at any place in any background. The severest impairment produced by fornix transection was in object-in-place learning. Fornix transection did not impair object discrimination learning in varying backgrounds. The results from the other two types of learning task showed intermediate severity of impairment in the fornix-transected animals. The idea that fornix transection in the monkey impairs spatial memory but leaves object memory intact is thus shown to be an oversimplification. The impairments of object memory in the present experiments are analogous to the impairments of episodic memory seen in human amnesic patients.
Immobilization Techniques for Microarray: Challenges and Applications

The highly programmable positioning of molecules (biomolecules, nanoparticles, nanobeads, nanocomposites materials) on surfaces has potential applications in the fields of biosensors, biomolecular electronics, and nanodevices. However, the conventional techniques including self-assembled monolayers fail to position the molecules on the nanometer scale to produce highly organized monolayers on the surface. The present article elaborates different techniques for the immobilization of the biomolecules on the surface to produce microarrays and their diagnostic applications. The advantages and the drawbacks of various methods are compared. This article also sheds light on the applications of the different technologies for the detection and discrimination of viral/bacterial genotypes and the detection of the biomarkers. A brief survey with 115 references covering the last 10 years on the biological applications of microarrays in various fields is also provided.
Compliant gait assistance triggered by user intention

An automatic gait initialization strategy based on user intention sensing in the context of rehabilitation with a lower-limb wearable robot is proposed and evaluated. The proposed strategy involves monitoring the human-orthosis interaction torques and initial position deviation to determine the gait initiation instant and to modify orthosis operation for gait assistance, when needed. During gait, the compliant control algorithm relies on the adaptation of the joints' stiffness in function of their interaction torques and their deviation from the desired trajectories, while maintaining the dynamic stability. As a reference input, the average of a set of recorded gaits obtained from healthy subjects is used. The algorithm has been tested with five healthy subjects showing its efficient behavior in initiating the gait and maintaining the equilibrium while walking in presence of external forces. The work is performed as a preliminary study to assist patients suffering from incomplete Spinal cord injury and Stroke.
Clinical Management of Gender Dysphoria in Children and Adolescents: The Dutch Approach

The Dutch approach on clinical management of both prepubertal children under the age of 12 and adolescents starting at age 12 with gender dysphoria, starts with a thorough assessment of any vulnerable aspects of the youth's functioning or circumstances and, when necessary, appropriate intervention. In children with gender dysphoria only, the general recommendation is watchful waiting and carefully observing how gender dysphoria develops in the first stages of puberty. Gender dysphoric adolescents can be considered eligible for puberty suppression and subsequent cross-sex hormones when they reach the age of 16 years. Currently, withholding physical medical interventions in these cases seems more harmful to wellbeing in both adolescence and adulthood when compared to cases where physical medical interventions were provided.
Improved Reversed Nested Miller Frequency Compensation Technique With Voltage Buffer and Resistor

This brief introduces and develops a novel frequency compensation technique for three-stage operational transconductance amplifiers. The new compensation topology exploits a voltage buffer and a nulling resistor to achieve a double pole-zero cancellation, occurring beyond the gain-bandwidth product. To verify the effectiveness of the compensation scheme, an amplifier has been fabricated in a standard 0.5-mum CMOS process. Experimental measurements are found to be in good agreement with the theoretical analysis and show an improvement in small-signal and large-signal performances
Multi-document Chinese name disambiguation based on Latent Semantic Analysis

Name disambiguation has received considerable attention as an important subtask of NLP (Natural Language Processing). Given many potential references of person entities, the goal is to find out for each reference involved in the context the most possible person entity it refers to. However, many researches in this field either focus on name disambiguation within a single text or employ machine learning models on multi-document without any consideration of semantics. In this paper we propose a new algorithm based on LSA (Latent Semantic Analysis) for the multi-document disambiguation task for Chinese name. The method employs SVD (Singular Value Decomposition) to reduce the original high dimensional text space to comparatively lower dimensional semantic space and then cluster possible reference words on the semantic space to get the result. Experiments on a real world dataset which is collected from a BBS site show that the proposed method can generate reasonable result.
G-networks with resets

Gelenbe Networks (G-networks) are a class of queuing models which include new types of customers called "signals," which are either "negative customers" and "triggers" [1, 2]. Queuing networks typically do not have provisions for some customers being used to eliminate other customers, or to redirect other customers among the queues. In other words, customers in traditional queuing netwroks cannot exert direct control on other customers. G-network models overcome some of these limitations and still preserve the computationally attractive "product form" property of certain Marovian queuing networks. In addition to ordinary customers, G-networks contain "negative customers" which eliminate normal customers, and "triggers" which move other customers from some queue to another [4, 5]. Multiple class versions of these models are discussed in [7, 8], and in [9] many additional results are provided. These queuing networks have generated much interest in the literature.
A word sense disambiguation method for feature level sentiment analysis

Sentiment analysis is an automatic method used to determine that the opinion of a person about a subject is positive or negative. One of the most important tasks in sentiment analysis is to disambiguate the sense of words according to context. Most errors in sentiment analysis are because of improper sense disambiguation. Few methods for this purpose have been proposed in literature. However, they are not able to properly determine the context of word in a sentence. In addition, the lexicon dictionaries used by these methods lack word senses and also do not provide a context matching technique. These issues need to be addressed in order to improve the performance of sentiment analysis so that it can be used by customers and manufacturers for decision making. In this paper, we propose a feature level sentiment analysis system, which produces a summary of opinions about product features. A word sense disambiguation method is introduced which accurately determines the sense of a word within a context while determining the polarity. In addition, a heuristic based method is proposed in order to determine the text where opinion about a product feature is expressed. The results show that the proposed methods achieve better accuracy than existing methods.
Cloning a genomic region required for a high‐affinity iron‐uptake system in Rhizobium meliloti 1021

A collection of transposon‐induced mutants of Rhizobium meliloti 1021 defective in siderophore‐mediated iron assimilation were obtained and classified as biosynthetic, transport or regulatory. Several of the mutations were cloned and the adjacent sequences were used to acquire complementing DNA from the wild type. A single genomic region of about 35kb complemented all of the mutants deficient in production of the siderophore.
Evolution of a New Gene Substituting for the leuD Gene of Salmonella typhimurium: Characterization of supQ Mutations

Alpha-isopropylmalate isomerase, the second specific enzyme in the biosynthesis of leucine, is coded for by two genes, leuC and leuD. Leucine auxotrophs, harboring leuD mutations including a deletion of the entire leuD gene, revert to leucine prototrophy owing to mutations at a locus, supQ, substantially distant to the leucine operon. A large number of independently isolated supQ mutations were characterized. A significant increase in the spontaneous frequency of supQ mutations was found after mutagenesis with 2-aminopurine, N-methyl-N′-nitro-N-nitrosoguanidine, diethyl sulfate, and nitrous acid. The supQ function in most of these strains is temperature sensitive, resulting in more efficient suppression with decreasing temperature. At higher temperatures, the supQ limits the growth rate of leuD supQ mutant strains. All supQ mutations are co-transducible with proA and proB, with co-transduction frequencies ranging from 5.4 to 99.9% for different supQ mutations. Many supQ mutations were isolated, especially after nitrous acid mutagenesis, that had acquired a simultaneous proline requirement. The data support the idea of two genes, supQ and newD, whose protein products form a complex. The newD gene product, without any genetic alteration, is capable of substituting for the missing leuD protein. However, mutations in the supQ gene (point mutations or deletions) are necessary to make the newD protein available, which is normally tied up in a complex with the supQ protein.
Recover the lost Phasor Measurement Unit Data Using Alternating Direction Multipliers Method

This paper presents a novel algorithm for recovering missing data of phasor measurement units (PMUs). Due to the low-rank property of PMU data, missing measurement recovery can be formulated as a low-rank matrix-completion problem. Based on maximum-margin matrix factorization, we propose an efficient algorithm based on alternating direction method of multipliers (ADMM) for solving the matrix completion problem. Comparing to existing approaches, the proposed ADMM based algorithm does not need to estimate the rank of the target data matrix and provides better performance in computation complexity. In addition, we consider the case of measurements missing from all PMU channels and provide a strategy of reshaping the matrix which contains the received PMU data for recovery. Numerical results using PMU measurements from IEEE 68-bus power system model illustrate the effectiveness and efficiency of the proposed approaches.
Notice of Violation of IEEE Publication PrinciplesModified Syntactic Method to Recognize Bengali Handwritten Characters

Several approaches have been proposed to recognize handwritten Bengali characters using different curve-fitting algorithms. The syntactic methods that are used to recognize printed Bengali alphabetic characters tend not to be suitable enough to properly distinguish Bengali handwritten characters. The proposed curve-fitting algorithm helps accurately recognize various strokes of different patterns (e.g., line and quadratic curve), thus drastically reducing the error elimination burden. As compared to existing approaches, the proposed modified syntactic method demonstrates significant improvement in recognizing Bengali handwritten characters.
Vitamin B6 improves blood parameters in rats fed a protein-deficient diet and subjected to moderate, long-term exercise

Vitamin B6 is necessary for many enzymatic pathways (glucose and lipid metabolism, DNA/RNA synthesis, or modulation of gene expression) and affects immune cell function and blood-forming processes. We hypothesised that supplementing a protein-deficient diet with vitamin B6 may reduce the negative impact of protein malnutrition. Here, we evaluated the effect of moderate, long-term exercise (ninety days) on selected blood parameters in rats fed a normal diet, a protein-deficient diet, or a protein-deficient diet supplemented with vitamin B6. Selected haematological, immunological, and biochemical parameters were examined. A protein-deficient diet lasting 90 days caused significant reduction in body mass, increased activity of aminotransferases (asparagine and alanine), an increased percentage of innate cells in the blood, and decreased haemoglobin concentration in the blood. Adding vitamin B6 significantly increased body and muscle mass, decreased liver parameters, and caused normalisation of haemoglobin concentration and the proportion of white blood cells in the blood. These results indicate that vitamin B6 supplementation significantly improves the health of protein-malnourished rats and paves the way for the development of novel anti-malnutrition therapies.
Concurrent Training Decreases Cortisol but Not Zinc Concentrations: Effects of Distinct Exercise Protocols

Objectives. To investigate the effects of distinct concurrent training (CT) protocols on zinc and cortisol concentrations and test the correlation between these blood variables. Methods. Samples of serum zinc and cortisol were assessed from 10 male subjects (27.1 ± 4.8 years old; BMI 25.38 ± 0.09) before and immediately after each study session: control (CS = no exercises), concurrent training 1 (CT1 = indoor cycling + strength training), and concurrent training 2 (CT2 = strength training + indoor cycle) with five days of interval between each. Results. There were no significant changes in zinc concentrations after the CS (Δ% = 8.45; p = 0.07), CT1 (Δ% = 4.77; p = 0.49), and CT2 (Δ% = −2.90; p = 0.12) sessions. Cortisol levels showed significant decrease after CS (Δ% = −6.02; p = 0.00), CT1 (Δ% = −26.32; p = 0.02), and CT2 (Δ% = −33.57; p = 0.05) sessions. There was a significant correlation between the variables only at CS (zinc post versus cortisol pre: r = 0.82 and cortisol post: r = 0.82). Conclusions. CT decreases cortisol concentrations regardless of the sequence performed. No changes were found in zinc concentrations after the study sessions. The reduction in serum cortisol concentrations appear to occur by a mechanism independent of the zinc status.