Miracle-dz/UniFAR-FTUs huggingface dataset:
The Potential Role of miRNAs in Schizophrenia: Diagnostic and Therapeutic Applications

Schizophrenia is a severe mental disorder which affects the normal functioning of the brain. To date, the etiology of schizophrenia is unclear; therefore, the diagnosis of schizophrenia is controversial. Biomarkers that reflect the dysregulations observed in schizophrenia may potentially assist the diagnosis of the disorder. Given the critical need for new diagnostic markers and diseasemodifying treatments, expanding the focus of genomic studies of neuropsychiatric disorders to include the role of non-coding RNAs is of growing interest. MicroRNAs small non-coding RNA transcripts expressed throughout the brain that can regulate neuronal gene expression at the posttranscriptional level. Dysregulation or altered expression of miRNAs is associated with abnormal brain development and pathogenesis of neurodevelopmental diseases. This review highlights the potential of miRNA levels to be used in the diagnosis of psychiatric disorders and offer novel targets for therapeutic development.
Clinical and Therapeutic Implications of Cancer Stem Cells: A Review

Cancer is a disease of genes. Although a number of pathogenesis have been proposed for cancer, a unifying model of tumorigenesis is yet to be established. Furthermore, the mortality rate associated with cancer has not decreased in spite of the advances in therapy. Many questions still remain unanswered regarding the pathogenesis, therapy, and recurrence. Researchers have now proposed that cancer initiation and progression is driven by a small subpopulation of cancer cells called the cancer stem cells (CSCs). These cells have also been implicated in recurrence, metastasis and therapy of cancer. This review highlights the clinical and therapeutic implications of CSCs.
Bacteriological Study of Conjunctivitis

Introduction: Clinical evaluation and microbiological analysis is valuable for specific treatment. This study was undertaken to study the pattern of presentation and determine the bacterial profile of conjunctivitis. Material and Methods: This is a clinical and laboratory-based study carried out in the Departments of Ophthalmology and Microbiology at Karnataka Medical College Hospital, Hubli for period of two years. Clinical data and Conjunctival swabs collected from 100 patients with clinically diagnosed conjunctivitis, were analysed by standard methods. Results: Greater incidence is seen among children with a male preponderance. In culture studies, normal flora were isolated in 4 of the cases while pathogenic bacteria were isolated in 53%. Gram stain examination yielded 25% results suggestive of bacterial infection. Wright's staining of chronic conjunctivitis cases indicates a probable bacterial aetiology in 5 cases. Coagulasepositive staphylococci and Klebsiella pneumoniae emerged as the first and second most common causative bacteria of conjunctivitis. Ciprofloxacin emerged as the most effective drug. Conclusion: This study provides to the ophthalmologist a working knowledge of the causal microbes, their common presentation, clinical course and antibiotic sensitivity pattern. This helps in effectively managing bacterial conjunctivitis.
Speaker Verification System Using Gaussian Mixture Model & UBM

— In This paper presents an overview of a state-of-the-art text-independent speaker verification system. The objective of automatic speaker recognition is to extract, characterize and recognize the information about speaker identity. First, an introduction proposes a modular scheme of the training and test phases of a speaker verification system. Then, the most commonly speech parameterization used in speaker verification, namely, cepstral analysis, is detailed. Gaussian mixture modeling, which is the speaker modeling Technique used in most systems, is then explained. This project introduces and motivates the use of Gaussian mixture model (GMM) for text-independent speaker recognition. The individual Gaussian components of a GMM are shown to represent some general speaker-dependent spectral shapes that are effective for modelling speaker identity. The present work Background Model (GMM– UBM) is also made.
Advanced Research in Computer Science and Software Engineering

- E-learning is defined as a Virtual Learning Environment (VLE) which provides resources for interaction between students and teachers. The latest advancement in the field of Information Technology and enhanced use of internet has facilitated tremendous proliferation towards usage of E-learning. It provides a new way of distributing information with better efficiency and lesser cost by clustering similar resources into groups of meaningful data using data mining algorithms. One of the recent advancement in e-learning is adaptive e-learning. This type of learning provides the content to the users according to their current level of learning. The learning abstraction system consists of huge amount of data so there is a requirement of some specific way to retrieve useful data with speed and ease. The traditional approach does not take into account the fact that the mental level of the learners varies significantly from person to person. Consequently it would be unfair if every learner gets access to similar kind of data. Adaptive E-learning is a concept which provides content dynamically to users according to their mental level by employing data mining technique.We propose the use of k-means algorithm for implementing adoptive learning.
1428-1433 Dilip Kumar Sharma 378

*Corresponding Author: Dr. Dilip Kumar Sharma, Botany Research Lab, P.G. Department of Botany, Agrawal P.G. College, Jaipur – 302003, Rajasthan, India 1428 SEED-BORNE DISEASES OF BRINJAL (SOLANUM MELONGENA L.) AND THEIR CONTROL MEASURES: A REVIEW Dilip Kumar Sharma*, Nandini Sharma and Shafkat Rana Botany Research Lab, P.G. Department of Botany, Agrawal P.G. College, Jaipur 302003, Rajasthan, India P.G. Department of Botany, S.G. G. Govt. College, Banswara, Rajasthan, India
110-113-Madhuri Gupta

Thyroid dysfunction is associated with chronic obstructive pulmonary disease depending upon severity of disease. The aim of this study was to evaluate thyroid function impairment among stable and acute exacerbation COPD patients with age matched healthy controls and correlation of thyroid function tests with pulmonary function test and arterial blood gas analysis. 60 {30 stable (group1) and 30 exacerbation (group2)} COPD patients and 30 age matched healthy controls (group3) were studied. There was a significant difference with respect to BMI, mean serum FT3 in between group 1&2; group 2&3 and group 1&3. Mean serum TSH was within normal limits but had lower values than controls. FT4 was within normal limits. It had no significant difference between all groups. Mean serum FT3 was negatively correlated with bicarbonate levels whereas FT4 was negatively correlated to Hb levels . No correlation was found in between Pulmonary Function Test and ABG analysis with thyroid function impairment. In conclusion among all groups of COPD patients, impaired thyroid function is associated with respiratory workload, as thyroid hormones regulate the metabolic rate and in exacerbation phase due to critical illness thyroid dysfunction reflects non-thyroidal illness syndrome. Kewords: COPD, thyroid hormones, acute exacerbation, pulmo nary function test, arterial blood gases Accepted October 03 2012
AN IMPROVED OLSR PROTOCOL USING MULTIPOINT RELAY SELECTION IN MANET

-Flooding is an important communication primitive in mobile ad hoc networks. And also serves as a building block for more complex protocol such as routing protocol. In any flooding mechanism one must balance reliability against message overhead. On the one hand, increasing reliability generally involves sending a greater number of redundant messages and thus increases message overhead. Redundant messages are needed to reach all nodes and to recover from packet loss, hence reducing the overhead will generally decrease reliability. Selective broadcast of that packet improves the reliability as well as packet drop. These compensation packets are constructed from dropped data packets, based on techniques from AODV, AOMDV. The OLSR protocol (Multi-relay selection) inherits these stability of the link state algorithm, due to this proactive nature it has an advantage of having the route immediately available when needed. OLSR protocol is an optimization of a pure link state protocol for mobile ad hoc networks. The OLSR minimizes flooding of this control traffic by using only the selective nodes called multipoint relay, to diffuse this messages in networks. Only the multipoint relay of nodes transmits its broadcast messages.
Multi Band Hysteresis Current Controlled Flying Capacitor Multi Level Inverter Based Shunt Active Power Filter for Distribution Systems

Lecturer, Department Of Electrical Engineering, L. E. College Morbi-363642, India, ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract -This paper presents application of flying capacitor multi level inverter in high voltage shunt active power filter. The proposed strategy uses three independent multi band hysteresis current regulators to generate gating signal for multi level inverter. Flying capacitor multi level inverter is used for high voltage and high power application with low distortion of source current waveforms at low switching frequency. A new flying capacitor voltage balancing technique is proposed which maintain constant capacitor voltage with desired current wave shape. Five level flying capacitor multi level inverter topology has been considered for active filtering of 11 kV distribution systems. The fast dynamic response of active power filter with low total harmonic distortion of source current has been achieved with the proposed strategy.
Multimodal Anti-Inflammatory Approach to Osteoarthritis Management - Review of T Cell Immunomodulation with Undenatured (Native) Collagen Type II, and LOX Inhibition with Boswellia

Osteoarthritis, known to be a degenerative disease, is now seeing increasing evidence of also having an inflammatory pathophysiology involving multiple pathways. T cell mediated immune response to joint cartilage collagen is now one of the recognized pathways causing cartilage destruction. T helper cell activation, involvement of pro-inflammatory cytokines and increased destruction of cartilage by Matrix Metalloproteinase enzymes, along with a relative suppression of anti-inflammatory cytokines and T regulatory cells appear to be important inflammatory mechanisms perpetuating continuous cartilage loss. Conversion of Phospholipids released from tissue injury to arachidonate and thereafter to prostaglandins and leukotrienes by the Cyclo-oxygenase 2 (COX2) and Lipo-oxygenase 5 (5LOX) enzymes respectively, is also well known. While COX2 inhibition via Non-steroidal anti-inflammatory drugs is well established in Osteoarthritis, the role of Leukotrienes in increasing inflammatory activity and cartilage destruction requiring appropriate inhibition needs further emphasis. Therefore, controlling cartilage destruction in Osteoarthritis through addressing these multiple inflammatory pathways can be a rational therapeutic approach. This article aims to elaborate on the pharmacotherapeutic approaches involving modulating T cell immune response to cartilage and inhibiting the LOX pathways by Undenatured (Native) Collagen Type II and Boswellia extract respectively.
ICTs and Supply Chain: The Competitiveness of Small and Medium Scale Enterprises (SMEs)

— The number of Small and Medium Enterprises (SMEs) operating in the Adum Central Business District (CBD) of Kumasi, Ghana continues to grow at an increasing rate, but still they do not conform to the right standards and appropriate parameters. No matter what business activities they embark on some Information and Communication Technologies (ICTs) can be effectively used to enhance their operations. This paper finds out the adequacy of dissemination of ICTs and its level of deployment in the operations of SMEs of trade businesses in the Adum CBD and establishes the level of awareness of computers and their related technologies among owner-managers. In order to do an in-depth assessment of the situation, the CBD was put into zones A, B, and C and enterprises were selected at random. Interview procedures and administered questionnaires were used to obtain data for analysis. In effect, the study established that though the level of awareness is high, only 23% of these SMEs use computers whilst 49% use mobile phones to support their businesses. Also, 54% of these enterprises do not have access to the Internet. Thus, the exploitation and deployment of ICTs remain a greater challenge to these enterprises. It is recommended that the Ministry of Trade and Industry and other stakeholders organize programmes to enlighten owner-managers on the prospects of using ICTs to gain competitive advantage. In addition, the ICT industry must be revamped and freed from bottlenecks surrounding access to hardware and software.
Crosstalk Effects on Global Interconnects in Multi core Processors

One of the most harmful effects of noise on circuit operation is the degradation of signal integrity causing uncertainty in the signal delay. The uncertainty of the propagation delay of a signal can cause a catastrophic violation of the timing constraints within a system. For capacitively coupled interconnect lines, In this paper the effect of signal degradation for different interconnects lengths have been observed and simulations are done at 32nm and 45nm technology nodes.
RASP Data Perturbation – An Efficient Query Services in Cloud

Hosting a data query services in cloud using public cloud computing infrastructures which has been deployed world-wide has become an appealing solution for advantages on scalability and cost-saving. Data owner does not want to move the sensitive data to cloud unless data confidentiality and query privacy guaranteed. On the other hand, a secured query service should still provide efficient query processing and significantly reduce the in-house workload to fully realize the benefits of cloud computing. We propose the random space perturbation (RASP) data perturbation method to provide secure and efficient range query and kNN query services for protected data in the cloud. The RASP data perturbation method combines order preserving encryption, dimensionality expansion, random noise injection, and random projection, to provide strong resilience to attacks on the perturbed data and queries. It also preserves multidimensional ranges, which allows existing indexing techniques to be applied to speedup range query processing. The kNN-R algorithm is designed to work with the RASP range query algorithm to process the kNN queries. Attacks on data and queries have been carefully analyzed under a precisely defined threat model and realistic security assumptions. Extensive experiments have been conducted to show the advantages of this approach on efficiency and security. Index Terms – Range query, kNN Query, Query Services in
Uncertainty in Environmental Risk Assessment

To determine the possible impact on human health and other biota due to hazardous substances into the environment the idea of environmental risk assessment is very much important. Environmental data are often questionable as well as imprecise and as such uncertainty is associated in any study related with these kind of data. Randomness and incompleteness are two main origins of uncertainties in risk assessment. To model and analyze these uncertainties there are two main ways viz. probability theory and fuzzy logic set theory. The random variability in environmental parameters can be described by probability functions defined by stochastic approach. On the other hand, the lack of information regarding environmental parameters is analyzed by possibilistic theory
Cloud-Scheduling Algorithm using Hyper heuristic Approach: Study and Implementation

Cloud computing is a parallel and distributed system. Simple and easy to implementation of Rule-based scheduling algorithms widely used in many cloud computing systems. Results of these scheduling strategies are usually far from optimal. However Performance of this scheduling algorithm is improved by using heuristic algorithm. The paper present Heuristic scheduling algorithm is a Hyper-heuristic scheduling algorithm to find better scheduling solutions for cloud computing systems. Algorithm uses two operators. The algorithm implemented and compared with different algorithms in a simulated environment using a CloudSim. Result show that hyper heuristic algorithm reduces makespan as compared with other algorithm.
CONTROL OF DYNAMIC VOLTAGE RESTORER BY CHAOTIC ACCELERATED PARTICLE SWARM OPTIMIZATION TO IMPROVE POWER QUALITY INDICES

---------------------------------------------------------------------***-------------------------------------------------------------------Abstract: – Dynamic voltage restorer (DVR) is the mostly used custom power device for improving power quality indices. The main function of DVR is to mitigate the problems of voltage sag and voltage swells. In this paper, DVR is used to control voltage sag as its main objective and to reduce total harmonic distortion (THD) as the second objective. DVR is controlled by proportional-integral (PI) controller. To obtain the optimal values for the coefficients of the PI controller a new control strategy called chaotic accelerated particle swarm optimization (CAPSO) algorithm which is an advanced version of PSO is used. An appropriate objective function for the optimization process is developed by the combination of fuzzy logic and neural network. The simulation results are obtained in MATLAB/SIMULINK software and a comparison is made between the results obtained from simulation of classic PI controller, standard PSO and CAPSO
COVERAGE VS NODE & DEPLOYMENT CHARACTERISTICS FOR WIRELESS SENSOR NETWORKS

Coverage is a very important parameter because it measures how effectively a target field is monitored by the sensor network. This paper provides a comparative statistics for the impact of various node characteristics on the area coverage. In this paper, we have also focused on sensor networks with two types of nodes that differ in their capabilities, and discussed the effects of heterogeneity of sensing on the network coverage. This work can serve as a guideline for designing large-scale sensor networks cost-effectively. The work can also be extended to more complicated heterogeneous wireless sensor networks with more than two types of sensors.
Performance Analysis of Various Thresholds for Correction of Ocular Artifacts from Single Channel EEG in WT and EMD domains

Physicians use Electroencephalogram (EEG) to dissect different nervous system disorders like Alzheimer’s, Parkinson’s, Seizures, Epilepsy etc. EEG signals indicate bioelectric brain activity and are usually tainted with different artifacts due to movements of eye, heart and muscles and power line interference. Among these, ocular activities create significant artifacts and make the analysis difficult. This paper a new threshold is presented for removal of Ocular Artifacts (OA) from the single channel EEG signals in Wavelet Transform (WT) and Empirical Mode Decomposition (EMD) domains. Using the EEG Motor Movement/Imagery (eegmmidb) dataset, extensive computations are carried out and compared the performance of Proposed Threshold (PT) with current thresholds i.e., Universal Threshold (UT), Minimax Threshold (MT) and Statistical Threshold (ST) using several standard performance metrics: change in Signal to Noise Ratio (ΔSNR), Artifact Rejection Ratio (ARR), Correlation Coefficient (CC), Normalized Mean Square Error (NMSE). Results of these studies reveal that the PT is able to remove the OAs from EEG signals effectively maintaining the background neural activity in non artifact zones intact in contrast with those of existing ones.
An Advanced Fuzzy Constructing Algorithm for Feature Discovery in Text Mining

a big task to provide the accuracy of discovered relevance features in text documents for describing user requirements. Classification of data is biggest issue in more text documents because they have large number of words and data patterns. Most existing popular methods are used by word-based approaches. Still, they have all suffered from the problems of relevance and uncertainty. Over the years, there has been pattern-based methods should perform better result than word-based methods in describing user requirements. But, how to effectively use large scale patterns remains a typical problem in text mining. To overcome this problem, Fuzzy Relevance Feature Discovery Algorithm (FRFDA), classification techniques have been developed for relevance feature discovery. It describes both higher level and low level features based on word patterns. It is also classifies words into categories and updates those word weights based on their relevance and dispensation in patterns. The experimentation result proves that, the proposed FRFDA is better than existing manual and automation methods. The data set Reuters-21578 shows that the proposed model significantly outperforms faster and obtains better extracted features than other methods. Keywordsmining, fuzzy similarity, feature clustering, text feature extraction, text classification, Fuzzy Relevance Feature Discovery (FRFD), Reuters Corpus Volume (RCV).
Factors Associated with Visceral Fat Loss in Response to a Multifaceted Weight Loss Intervention

Background: Visceral adipose tissue is more metabolically active than other fat depots and is more closely associated with obesity-related diseases, such as cardiovascular disease and type 2 diabetes, than indicators of obesity, such as body mass index. Across various strategies to promote weight loss, including energy-reduced diet and exercise, variable effects on VAT compared to loss of total body fat have been reported. Methods: To examine the effect of a behavioral weight loss intervention using portion-controlled prepackaged entrées on VAT, we examined data and measurements from overweight/obese men and women (N=183) who were assigned to a weight loss intervention and prescribed a reduced-energy diet with either portion-controlled prepackaged entrées or self-selected meals in a randomized clinical trial. VAT was estimated with dual-energy X-ray absorptiometry at baseline and study end (12 weeks). Results: VAT loss was greater for the prepackaged entrees group (p=0.02), with an average loss of 29% compared to an average loss of 19% among participants consuming self-selected meals. VAT (mean [SEM]) was 1651 (71) g and 1546 (157) g at baseline and 1234 (59) g and 1278 (118) g at study end in the prepackaged entrees and self-selected meal groups, respectively. Greater VAT loss was associated with higher baseline weight and VAT, and greater weight loss, but not associated with age or physical activity. Conclusion: Prescribing portion-controlled prepackaged entrees in a behavioral weight loss intervention promotes a reduction in VAT, which should promote improved metabolic profile and reduced cardiovascular disease risk.