Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality of life of type 2 diabetes mellitus patients attending a tertiary care hospital of Northern India: A cross sectional study

Introduction: Diabetes mellitus is a chronic and progressive metabolic disorder. According to the World Health Organization (WHO) there is “an apparent epidemic of diabetes, which is strongly related to lifestyle and economic change. ” Objective of the study was to assess the quality of life of people living with type 2 diabetes mellitus and factors associated with quality of life. Methods: A hospital-based cross-sectional study was conducted on 215 patients with diabetes mellitus. Quality of life was assessed using a generic instrument SF 36. The data was analyzed using SPSS, version 24.0. An independent t test and analysis of variance (ANOVA) were used to compare the means of each domain of quality of life within groups of various independent variables. Results: The mean age of respondents was 52.5 ± 11.0 years. The majority (87.4%) of the patients were married, Hindu by religion (88.8%), and belonged to upper socio economic class (28.8%). The mean duration since diagnosis of diabetes was 7.82 ± 6.0 years, and 80.4 percent of patients were on oral hypoglycemic agents. Hypertension was found to be the most common (24.6%) comorbidity. Age, education, socioeconomic status, duration of diabetes, type of treatment, complication of diabetes, comorbidities, and body mass index (BMI) were found to be significantly associated with various domains of SF-36. Conclusions: Diabetes has an adverse effect on quality of life of patients with diabetes. The most affected domain in male and female patients was vitality domain followed by general health domain of quality of life.
THE EFFECT OF DIFFERENT METHODS AND SOLVENTS ON THE EXTRACTION OF POLYPHENOLS IN GINGER (Zingiber officinale

Food ingredients derived from plants are a rich source of polyphenols. In recent times, polyphenols have become popular for their therapeutic properties as antioxidants. 6-gingerol, the main bioactive phenolic compound in Zingiber officinale , is well known for its free radical scavenging capabilities in treating multiple ailments. The most common method for extracting polyphenols from plant materials is through the use of solvents. The extraction of polyphenols from plant matrix is largely dependent on the type of solvent used and the extraction method employed. However, due to the complexity of plant chemistry there is no obvious choice in solvent or extraction method. In this study we made use of three different solvents; acetone, ethanol, and methanol. Variations of two different methods were used. The reflux was run for 30 minutes at 95 and maceration was done at room temperature for 8 hours. Between the different methods, maceration extracts generally showed better TPC, 6-gingerol content and antioxidant activity. Ethanol was significantly the best extracting solvent due to its higher polarity index. While the maceration ethanol extracts significantly had the highest TPC and 6-gingerol content, its antioxidant activity was not significantly different from the ethanol reflux extracts. A significantly positive correlation was determined between TPC and antioxidant activity, with reflux extracts having a better correlation than the maceration extracts. A significant positive correlation was also drawn between TPC and 6-gingerol content.
Near Infrared Spectroscopy (NIRS) as a Tool to Analyze Phenolic Compounds in Plants

Phenolics are related to a number of pharmacological effects and form an important category among secondary plant metabolites. For many years well established and highly efficient methods such as UV spectroscopy, high perform- ance liquid chromatography, gas chromatography, liquid chromatography, mass spectrometry and capillary electrophore- sis have been used for determination. In the last years, near infrared spectroscopy with its benefits such as being non- invasive, rapid, almost no necessary sample preparation, on-/inline measurements, being able to determine physical and chemical parameters simultaneously, became a widely used analytical technique in phyto-analytics and is included in pharmacopeias to an increasing extent (1). This manuscript reviews recent applications of NIRS in the analysis of pheno- lic compounds in plant material.
The Effect of Culture on Entrepreneurial Networks

Networking is an important aspect of business. For entrepreneurs in particular, the strength of a network could offer important resources and opportunities through both close and distant contacts, which are known in network theory as strong and weak ties. This thesis analyzes the impact of entrepreneurs’ network tie strength on firm performance by analyzing networks in different countries through a correlational meta-analysis. The moderating factor of culture was analyzed to understand the impact of how individualistic and collectivist cultures affect network tie strength. Through analyzing 23 different primary studies (N=4041) from various individualistic and collectivist countries, the meta-analysis determined that culture does not have a statistically significant moderating impact on network strength on firm performance. I discuss the implications of these findings for entrepreneurs and business networks.
Naos: Serialization-free RDMA networking in Java

Managed languages such as Java and Scala do not allow developers to directly access heap objects. As a result, to send on-heap data over the network, it has to be explicitly converted to byte streams before sending and converted back to objects after receiving. The technique, also known as object serialization/deserialization, is an expensive procedure limiting the performance of JVM-based distributed systems as it induces additional memory copies and requires data transformation resulting in high CPU and memory bandwidth consumption. This paper presents Naos, a JVM-based technique bypassing heap serialization boundaries that allows objects to be directly sent from a local heap to a remote one with minimal CPU involvement and over RDMA networks. As Naos eliminates the need to copy and transform objects, and enables asynchronous communication, it offers significant speedups compared to state-of-the-art serialization libraries. Naos exposes a simple high level API hiding the complexity of the RDMA protocol that transparently allows JVM-based systems to take advantage of offloaded RDMA networking.
Speech-driven Articulator Motion Synthesis with Deep Neural Networks

This paper implements a deep neural networks (DNN) approach for speech-driven articulator motion synthesis, which is applied to speech-driven talking avatar animation synthesis. We realize acoustic-articulatory mapping by DNN. The input of the system is acoustic speech and the output is the estimated articulatory movements on a three-dimensional avatar. First, through comparison on the performance between ANN and DNN under a series of parameters, the optimal network is obtained. Second, for diﬀerent context acoustic length conﬁgurations, the number of hidden layer units is tuned for best performance. So we get the best context length. Finally, we select the optimal network structure and realize the avatar animation by using the articulatory motion trajectory information output from the DNN to control the articulator motion synthesis. The experiment proves that the method can vividly and eﬃciently realize talking avatar animation synthesis.
Achievable zero-error rate regions using novel location assisted coding (LAC) for short range FSO communications

—Recent free-space optical (FSO) communication technologies have demonstrated the feasibility of building WiFO, a high capacity indoor wireless network using the femtocell architecture. In this paper, we introduce a cooperative transmission framework using location assisted coding (LAC) technique to increase the overall wireless capacity. For a given network topology, LAC provides three different schemes with different coding/decoding procedures. Based on these schemes, achievable zero-error rate regions for WiFO using LAC will be characterized. Both numerical and theoretical analyses are given to validate the proposed coding schemes.
Development of a checklist to detect errors in meta-analyses in systematic reviews of interventions: study protocol

Background : Systematic reviews underpin clinical practice and policies that guide healthcare decisions. A core component of many systematic reviews is meta-analysis, which is a statistical synthesis of results across studies. Errors in the conduct and interpretation of meta-analysis can lead to incorrect conclusions regarding the benefits and harms of interventions; and studies have shown that these errors are common. Enabling peer reviewers to better detect errors in meta-analysis through the use of a checklist provides an opportunity for these errors to be rectified before publication. To our knowledge, no such checklist exists. Objective : To develop and evaluate a checklist to detect errors in pairwise meta-analyses in systematic reviews of interventions. Methods : We will undertake a four-step process to develop the checklist. First, we will undertake a systematic review of studies that have evaluated errors in the conduct and interpretation of meta-analysis to generate a bank of items to consider for the checklist. Second, we will undertake a survey of systematic review methodologists and statisticians to seek their views on which items, of the bank of items generated in step 1, are most important to include in the checklist. Third, we will hold a virtual meeting to agree upon which items to include in the checklist. Fourth, before finalising the checklist, we will pilot with editors and peer reviewers of journals. Conclusion : The developed checklist is intended to help journal editors and peer reviewers identify errors in the application and interpretation of meta-analyses in systematic reviews. Fewer errors in the conduct and improved interpretation will lead to more accurate review findings and conclusions to inform clinical practice.
Analysis and simulation of multilevel inverter system

Introduction The multilevel inverter was first introduced in 1975. The three level converters the first multilevel inverter introduced. A multilevel converter is a power electronic system that synthesizes a desired output voltage from several levels of dc voltages as inputs. With increasing number of dc voltage sources, the converter output voltage waveform approaches a nearly sinusoidal waveform while using a fundamental frequency-switching scheme. The primary advantage of multilevel inverter is their small output voltage, results in higher output quality, lower harmonic component, better electromagnetic compatibility, and lower switching losses [2]. Multilevel inverter includes an array of power semiconductors and capacitor voltage sources, the output of which generates voltages with stepped waveforms with less distortion, less switching frequency, higher efficiency, lower voltage devices and better electromagnetic compatibility [4]. The commutation of the switches permits the addition of the capacitor voltages, which reach high voltages at the output, while the power semiconductors must withstand only reduced voltage. Bridge Inverter Three Level Mode Another characteristic is that the “H” topology has many redundant combinations of switches’ positions to produce the same voltage levels. As an example, the level “zero” can be generated with switches in position S(1) and S(2), or S(3) and S(4), or S(5) and S(6), and so on [7] [8] [9]. Another characteristic of “H” converters is that they only produce an odd number of levels, which ensures the existence of the “0V” level at the load . For example, a 51-level inverter using an “H” configuration with transistor-clamped topology requires 52 transistors, but only 25 power supplies instead of the 50 required when using a single leg [8]. Therefore, the problem related to increasing the number of levels and reducing the size and complexity has been partially solved, since power supplies have been reduced to 50%. Fig 1.a shows the circuit diagram of H-bridge inverter operated in three level output mode. Fig 1a H-Bridge Inverter for Three Level Output Mode
Old is Not Always Gold: Early Identification of Milestone Patents Employing Network Flow Metrics

Bibliometrics has been employed previously with patents for technological forecasting. The primary challenge that technological forecasting faces is early-stage identiﬁcation of technologies with the potential to have a signiﬁcant impact on the socio-economic landscape. With this aim, we carry out an exploratory study using various network-based metrics on patent citation network to identify patents which are possible candidates for major inﬂuence in the immediate future. To effectively uncover these patents shortly after they are issued, we need to go beyond raw citation counts and take into account both the citation network topology and temporal information. We posit that, as with scholarly citations, not all patent citations carry equal importance with age. This information is captured by dynamic network ﬂow metrics that take the effect of time on the citations into account. Identifying top patents can aid in re-ranking of search results in a patent search. We carry out our experiments on two standard collections of patents and present some insightful re-sults and observations based on rigorous analysis.
PATH ANALYSIS BETWEEN CONSTRUCTS OF TECHNOLOGY ACCEPTANCE MODEL (TAM) (A CASE STUDY ON RECEIPT OF VIRTUAL ARMS SOLUTION FTS D - 423 IN INDONESIAN EASTERN FLEET TRAINING COMMAND)

Indonesian Eastern Fleet Training Command currently has the facilities to train professional soldiers in the shooting.A simulator facility in the form of computer-based clinic shooting is called Virtual Arms Solution FTS D-423 (VAS). Need to analyse the relationship between perceived ease of use and usefulness of VAS in order to determine thelevel of acceptance. Both these factors are modelled by the Technology Acceptance Model (TAM) which canexplain the factors that influence the actual receipt of the use of technology. After that, the relationship between thetwo factors that have been modelled with the Technology Acceptance Model to be treated using Path Analysis(Path Analysis). Where the path analysis was used to analyse the causal relationships between variables in order todetermine the effect of the direct and indirect causes of the variable to a variable result. Based on the analysis anddiscussion, it is obtained as follows that the ease and usefulness of a positive effect on Attitude using VAS positiveeffect on Behavioural Intention using VAS. Behavioural intentions affect the Actual Usage.Keywords: Virtual Arms Solution, Technology Acceptance Model, Path Analysis.
A Stochastic Model with Jumps for the COVID-19 Epidemic in the Greater Abidjan Region during Public Health Measures

Our goal in this paper is to adapt to the context of the Greater Abidjan Region (Côte d'Ivoire) an existing model reflecting the evolution of the COVID-19 epidemic in Wuhan (China). This model is a deterministic compartmental model which is translated by a system of ordinary differential equations. We are reinvesting this model to obtain the parameters of the epidemic in the great Abidjan. We study some mathematical aspects of this deterministic model. Using data from the evolution of the COVID-19 epidemic in Abidjan, we obtain constants corresponding to the Greater Abidjan Region epidemic. We are performing numerical simulations using these constants to predict the behavior of the epidemic in the Greater Abidjan Region. The initial model does not take into account certain disturbances and sudden shocks which could disturb its behavior. In the Greater Abidjan Region, some continuous or sudden events disrupt the behavior of the epidemic. To stick to the realities of the Greater Abidjan Region, we introduce a white noise and jumps that correspond to the different disturbances that can occur. We obtain a stochastic model of COIVD-19 with jumps. We prove that our new model with jumps has a positive global solution. In certain conditions, this solution oscillates in the set of the disease-free equilibrium of the deterministic model. We perform numerical simulations which corroborate our theoretical results.
Non-Parallel Voice Conversion with Autoregressive Conversion Model and Duration Adjustment

Although N10 system in Voice Conversion Challenge 2018 (VCC 18) has achieved excellent voice conversion results in both speech naturalness and speaker similarity, the sys-tem’s performance is limited due to some modeling insufﬁ-ciency. In this paper, we propose to overcome these limita-tions by introducing three modiﬁcations. First, we substitute an autoregressive-based model in order to improve the conversion model capability; second, we use high-ﬁdelity WaveNet to model 24kHz/16bit waveform in order to improve conversion speech naturalness; third, a duration adjustment strategy is proposed to compensate the obvious speech rate difference between source and target speakers. Experimental results show that our proposed method can improve the conversion performance signiﬁcantly. Furthermore, we validate the performance of this system for cross-lingual voice conversion by applying it directly to the cross-lingual task in Voice Conversion Challenge 2020 (VCC 2020). The released ofﬁcial subjective results show that our system obtains the best performance in conversion speech naturalness and comparable performance to the best system in speaker similarity, which indicate that our proposed method can achieve state-of-the-art cross-lingual voice conversion performance as well.
Design of Dual-Band Millimeter-Wave Antenna for 5G (26-39 GHz)

The first generation of wireless mobile telephony appeared in the 1980s. Since then, the mobile phone generation cycle is about 10 years and the 5G is announced commercially for 2020. With the advent of 5G networks, a need to connect most devices and gadgets together and to the internet has become inevitable. Therefore, high performance antennas are needed to meet more and more higher requirements for new systems. Wideband, wide-scanning array have been receiving great attentions for achieving large bandwidth over a wide scan volume. The aim of this internship is to design an antenna operating in the 26-39 GHz bands of future ultra 5G systems. This document starts with a general introduction of ORANGE. Then it follows with the presentation of the project and its technical existing solutions. The middle part treats the design of a 6-15GHz connected slot array loaded with artificial dielectrics and its transformation into a 26-39 GHZ dual band antenna. The last part deals with the prospects of this project and the general review of the internship.
Latent Semantics Approach for Network Log Analysis: Modeling and its application

Network log analysis helps network operators to troubleshoot their network. Many mathematical analysis methods rely on a set of time series corresponding to log type (log template) per device, as their input. However, they do not take full advantage of the meaning of logs despite log messages containing semantic information written in a free format. In this paper, we emphasize the use of this rich semantic information for network log analysis. More specifically, we propose an unsupervised latent semantics-based network log analysis. The key idea of the work is to build a latent semantics model of unobservable network functionalities (e.g., routing protocols, hardware) from generated logs, instead of inferring what is happening in the network from a network operator’s knowledge with log messages. This approach enables us to numerically cluster/compare the meaning of logs because each log message obtains a numerical distributed representation (a topic distribution). We discuss the validity of our approach with a set of logs collected at a nation-wide academic network for a year. We first show that our approach outperforms a popular data-driven approach (i.e., word2vec), which does not require any assumptions on the data, by evaluating the quality of the distributed representation of logs. Furthermore, through two network analysis scenarios, we demonstrate several benefits of our approach: intuitive interpretability of analysis results and bridging the gap between multi-vendors log messages.
Spectral Graph Embedding

These lecture notes introduce graph embedding, a technique consisting in transforming graph data into vector data. Speciﬁcally, the objective is to represent each node of the graph by a vector of low dimension, so that “close” nodes in the graph remain close in the vector space (for the Euclidean distance). This embedding can in turn be used to apply classical learning techniques, like classiﬁcation or clustering. We here present a classical approach based on the spectral decomposition of the Laplacian matrix. We also describe an approach based on the (generalized) singular value decomposition (SVD) of the adjacency matrix
Anti- quorum sensing activity of an oyster mushroom, Pleurotus florida

Pseudomonas aeruoginosa, a bioreporter strain was used as an indicator to monitor quorumsensing inhibition. Quorum sensing (QS) is a system of stimulus and response correlated to bacterial population density. The increasing incidence of multi-drug resistant pathogens has stimulated the search for novel anti-virulence compounds. Although many phytochemicals show promising anti microbial activity, their power lies in their anti-virulence properties. It is hypothesized that many naturally occurring terrestrial plants, algae and fungi traditionally used as medicines may also produce anti-QS compounds. To test this hypothesis, Pleurotus florida, the oyster mushroom was assessed qualitatively and quantitatively for its anti-QS activity using Pseudomonas aeuroginosa. A special swarm media that allow swarming motility growth of Pseudomonas aeuroginosa was used to conduct inhibition of swarm motility assay using mushroom extract. The methanol and chloroform extracts of the mushroom was tested for their inhibition of AHL (Acyl-Homoserine Lactone) production and biofilm formation. Inhibition of AHL for methanol extract ranged from 37.89-58.94% and for chloroform extract ranged from 50.05-70.05% at a concentration of 100-500μg/ml. Inhibition of biofilm formation for methanol extract ranged from 33.9-83.9% and for chloroform extract ranged from 60.07-82.1% at a concentration of 100-500μg/ml. The results of this study provided evidence that organic solvent extracts of the mushroom Pleurotus florida exhibited appreciable antiquorum sensing property and it justifies their use in the traditional medicine for the treatment of different multi-drug resistant microbes. © 2014 Elixir All rights reserved. ARTICLE INF O Articl e h istory: Received: 4 February 2014; Received in revised form: 20 March 2014; Accepted: 3 April 2014;
Psychiatry and the 21st Century

Abstract After a long and torturous path, an elusive quest for structure and order may have misled the American Psychiatric Association to overexpand the scope of its Diagnostic and Statistical Manual (DSM) codification of mental disorders. The DSM and guidelines came to represent American psychiatry to the world. Although important for epidemiological and statistical research, in volume and complexity, the DSM challenges clinicians. The DSM effort at categorization must be reconceived to acknowledge modern biological realities. Molecular and other selective biological sciences no longer dominate biology as they did at the time of DSM’s initial conception. Today, a Darwinian-Hippocratic combined biology leads psychiatry to address individuals and populations irretrievably and uniquely interdependent with environments. Unfortunately, the DSM, as currently conceived, fails to support this emerging 21st century biological grounding for psychiatry.