Miracle-dz/UniFAR-FTUs huggingface dataset:
Decreased Hippocampal Volume is Related to White Matter Abnormalities in Treatment-Resistant Depression

C l i n M e d International Library Citation: Young CB, Eijndhoven PV, Nusslock R, Fernández G, Schene A, et al. (2016) Decreased Hippocampal Volume is Related to White Matter Abnormalities in TreatmentResistant Depression. Int J Brain Disord Treat 2:012 Received: April 27, 2016: Accepted: June 20, 2016: Published: June 22, 2016 Copyright: © 2016 Young CB, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Young et al. Int J Brain Disord Treat 2016, 2:012
Ventilatory mechanics in thoracic surgery

This thesis proved that chest wall motion analysis technology could be used in thoracic surgery to answer a number of clinical and physiological questions. We used it either as a diagnostic tool or for the evaluation of an intervention outcome. We divided its use as a diagnostic tool into two categories; 1- diagnosis before surgery and 2- diagnosis after surgery. In the evaluation of an intervention outcome, we divided its use after a number of interventions: 1. Cosmetic Surgery: Chapter 5: The Effect of Pectus Carinatum (Pigeon Chest) Repair on Chest Wall Mechanics 2. Prognostic Surgery: a) Chapter 4: The Effect of Chest Wall Reconstruction on Chest Wall Mechanics b) Chapter 10: Late Changes in Chest Wall Mechanics Post Lung Resection: The Effect of Lung Cancer Resection In COPD patients 3. Palliative Surgery: a) Chapter 6: The Effect of Lung Volume Reduction Surgery on Chest Wall Mechanics b) Chapter 3: The Effect of Diaphragmatic Plication (Fixation) on Chest Wall Mechanics 4. Post-operative Intervention: Chapter 8: The Effect of Thoracic Nerve Blocks on Chest Wall Mechanics
Efficient Hybrid Multi-Objective Evolutionary Algorithm

Summary In the artificial intelligence community the multi-objective optimization problem become very common and has been rapidly increasing attention. This significant is due to the fact that there is high number of real-world applications having optimization problems that include more than one objective function. As has been evident in the last ten years, the evolutionary algorithms are one of the best choices to solve multi-objective optimization problems. Although evolutionary algorithms are the most common approach to solve multi-objective optimization problems, there is still many issues and drawbacks that need solving and enhancing. In this paper a set of improved hybrid Memetic evolutionary algorithms are proposed to solve multi-objective optimization problems. The proposed algorithms enhance the performance of NSGA-II algorithm by using different new proposed and simple search schemes. Merging a simple and efficient search technique to NSGA-II significantly enhances the convergence ability and speed of the algorithm. To assess the performance of proposed algorithms, three multi-objective test problems are used from ZDT set. Our empirical results in this paper show that the proposed algorithms significantly enhance the NSGA-II algorithm performance in both diversity and convergence.
Avoiding Objects with few Neighbors in the K-Means Process and Adding ROCK Links to Its Distance

K-means is considered as one of the most common and powerful algorithms in data clustering, in this paper we're going to present new techniques to solve two problems in the K-means traditional clustering algorithm, the 1 problem is its sensitivity for outliers, in this part we are going to depend on a function that will help us to decide if this object is an outlier or not, if it was an outlier it will be expelled from our calculations, that will help the K-means to make good results even if we added more outlier points; in the second part we are going to make K-means depend on Rock links in addition to its traditional distance, Rock links takes into account the number of common neighbors between two objects, that will make the K-means able to detect shapes that can't be detected by the traditional K-means. General Terms Data Clustering Algorithms, K-means, ROCK, Centroids' Initialization.
Exploring Emirati EL teachers' beliefs about teaching and their relationship to classroom practices: a hermeneutic study

Research shows that teacher beliefs are central to understanding teacher behaviour. Studying teacher beliefs is crucial to understand and affect their practices. Research also shows that classroom practices are influenced and determined by contextual factors in the teaching environment. Hence, teacher beliefs and contextual circumstances influence teachers’ instructional choices and decisions, revealing a relationship between teacher beliefs and contextual factors as variables affecting teaching practices. This study explores female Emirati teachers’ beliefs about teaching and their contextual environment, examining the way in which they relate to classroom practices. The study focused on English language teachers in secondary schools in the Emirates of Dubai and Sharjah, United Arab Emirates. To approach this research inquiry, a qualitative paradigm based on Gadamerian hermeneutics was adopted. The data-gathering process consisted of semi-structured interviews and classroom observations. Eight teachers participated in this study for a period of eight months. The data were analyzed using a meaning-based interpretive approach that sought understanding at idiographic and nomothetic levels. The findings showed the predominance of a salient mother-sister image that described how the teachers viewed themselves and concurrently provided a lens to look into their professional world. Their understanding of the nature of teaching rested, rather than on notions of subject matter and methodologies, on the student-teacher relationship which was viewed as an integral part of the teaching-learning process. The holistic view of student development evidenced a strong emphasis on student social skills and values. Their classroom practices generally reflected consistency with teacher beliefs, although points of discrepancy were also found. Similarly, lack of student academic motivation and negative attitude towards English were identified as the most prevalent contextual factors affecting teaching practices. The nature of these teachers’ beliefs and perceived contextual factors and their relationship to teaching practices are discussed as well as the implications, limitations and recommendations for further research.
Network Intrusion Detection Using Multiclass Support Vector Machine

—Intrusion detection is a topic of interest in current scenario. Statistical IDS overcomes many pitfalls present in signature based IDS. Statistical IDS uses models such as NB, C4.5 etc for classification to detect Intrusions. Multiclass Support Vector Machine is able to perform multiclass classification. This paper shows the performance of MSVM (1-versus-1, 1-versus-many and Error Correcting Output Coding (ECOC)) and it’s variants for statistical NBIDS. This paper explores the performance of MSVM for various categories of attacks .
Subjective Evaluation using LSA Technique

Information and communication technologies are effectively used in educational administration and teaching-learning process. There is a need to utilize them for educational evaluation. Subjective evaluation and assessment are essential part of education system. For evaluation of subjective examinations, several statistical and mathematical techniques such as Latent semantic analysis, and maximum entropy are being used. Latent semantic analysis (LSA) is one such technique used for evaluation of non-technical prose. In this paper LSA technique is applied to evaluation of technical answers. The LSA algorithm clusters the text into groups on the basis of similarity. The detailed LSA algorithm is included in the paper. A prototype based on the LSA algorithm is developed using soft-computing platform MatLab and the programming language Java. The prototype so developed has been tested by conducting class tests of students of under-graduate classes of computer science courses. The results are analyzed and observed to be satisfactory. It is concluded that LSA technique can also be applied for the evaluation of technical answers.
Comparative study and evaluation of various data classification techniques in data mining

: Data Mining is knowledge discovery process in database designed to extract data from a dataset and transforms it in to desired data. data processing action is similarly acclimated in get of constant patterns and/or analytical relationships amid variables, and a new to validate the accusation by applying the detected patterns to new subsets of knowledge. Data categoryification is one in every of the info mining technique to map great amount of data set in to applicable class. Data categoryification is reasonably supervised learning that is employed to predict class for information input, wherever categories are predefined.Supervised learning is that part of automatic learning which focuses on modeling input/output relationship the goal of supervised learning is to identify an optimal mapping from input variables to some output variables, which is based on a sample of observations of the values of the variables. Data classification technique includes various applications like handwriting recognition, speech recognition, iris matching, text classification, computer vision, drug design etc. objective of this paper is to survey major techniques of data classification. Several major classification techniques are Artificial neural network, decision trees, k-nearest neighbor (KNN), support vector machine, navie-bayesian classifier, the aim of study to make comparative analysis of major data classification techniques.
Multi Scale Decomposition And Non-Local Means Based Satellite Image Resolution Enhancement

:- Multi scale decomposition based on dual-tree complex wavelet transform and non-local means is presented for SRE (satellite image resolution enhancement) of the satellite images. Resolution enhancement schemes (which are not based on wavelets) suffer from the drawback of losing high frequency contents (which results in blurring). The discrete wavelet transform-based (DWT) RE scheme generates artifacts (due to a DWT shift-variant property). A wavelet-domain approach based on dual-tree complex wavelet transform (DT-CWT) and nonlocal means is used for RE of the satellite images. A satellite input image is decomposed by DT-CWT (which is nearly shift invariant) to obtain high-frequency sub bands. The high-frequency sub band and the low-resolution (LR) input image are interpolated using the bi-cubic interpolator. The high frequency sub bands are passed through an NLM filter to cater for the artifacts generated by DT-CWT. The filtered high-frequency sub bands and the LR input image are combined using inverse DT-CWT to obtain a resolution-enhanced image. The simulated results will show that technique used in this process provides better accuracy rather than prior methods.
Effect of WEKA Filters on the Performance of the NavieBayes Data Mining Algorithm on Arrhythmia and Parkinson’s Datasets

-Data mining is the process of selecting, exploring and modeling a large database in order to discover model and pattern that are unknown [1]. Enormous gathered data in Health care Information society are scattered with different archive systems which are not connected with one another. This unorganized data leads to delay in monitoring, improper planning, defocus the analysis which leads to inaccuracy in decision making. The purpose of this study is to explore Supervised and Non Supervised WEKA filters on the data mining algorithm NavieBayes which is used for classification the data sets of Arrhythmia and Parkinson’s diseases. This in turn helps in increasing the performance accuracy of the classifier used for knowledge discovery [2] . Both the Datasets were taken from UCI Repository [3]
International Journal of Advance Research in Computer Science and Management Studies

Abstract: In this work, we propose a forensic technique for the reverse engineering of double JPEG compression in the presence of image resizing between the two compressions. Our approach aims at exploiting the fact that previously JPEG compressed images tend to be distributed near the points of a lattice and is based on the extension of the technique proposed in [6] for nonaligned double JPEG compression. the proposed technique moves a step further, since it also provides an estimation of both the resize factor and the compression parameters of the previous JPEG compression. Such additional information is important, since it can be used to reconstruct the history of an image and Performa more detailed forensic analysis. One of the major difficulties encountered in image processing is the huge amount of data used to store an image. Thus, there is pressing need to limit the resulting data volume. It is necessary to find the statistical properties of the image to design an appropriate compression transformation of the image; the more correlated the image data are, the more data items can be removed. A wavelet transform combines both low pass and high pass filtering in spectral decomposition of signals so it becomes more complex and take more time. Lossless compression is preferred for archival purposes and often for medical imaging, technical drawings, maps and logos, where the loss of information is not acceptable. As our main objective is to work with a different interpolation algorithm for image compression. With various parameters such as minimum entropy, Qfactor, quality factor etc. for compressing the color images without losing any contents of the images and to maintain the storage memory space.
Keratinocyte growth factor prevents intraalveolar oedema in experimental lung isografts

Primary graft dysfunction, characterized by intraalveolar oedema, is a major obstacle in pulmonary transplantation. We evaluate the potential of keratinocyte growth factor (palmiferin, ∆N23-KGF) to prevent oedema in lung transplants. Intratracheal instillation of 5 mg/kg ∆N23-KGF was performed in Lewis rats on days 3 and 2 before explantation. Control animals obtained an equivalent volume of vehicle. Left lungs were isogeneically transplanted and the graft recipients were sacrificed one day later for stereological analysis of intraalveolar oedema and bronchoalveolar lavage. The total protein and phospholipid content as well as surfactant proteins were measured. Surfactant activity was analyzed with a pulsating bubble surfactometer. In grafts from control treated donors, the fraction of intraalveolar oedema amounted to 3.4+1.1% of the total parenchymal volume. Treatment of donor lungs with ∆N23-KGF reduced oedema to a fraction of 1.6+0.8%. In the lavage fluid of pulmonary grafts from ∆N23-KGF-treated donors, the total protein content was decreased compared to vehicle-treated lung transplants, whereas phospholipids did not differ. The protein fraction contained increased amounts of surfactant protein-C after ∆N23-KGF-treatment and surfactant function was improved. Treatment of donor lungs with palifermin protects against intraalveolar oedema formation upon transplantation. This effect appears to be mediated by an improved surfactant homeostasis.
Comparative efficacy of different schedules of administration of medicinal plants infusion on hematology and serum biochemistry of broiler chicks

The research study was undertaken to investigate the effect of different schedules of administration of medicinal plants infusion of aloe vera gel, barbery, garlic and ginger on hematology and serum biochemistry of broilers chicks. For this purpose 240, day old broilers chick (A) purchased were from a local dealer, divided in to four groups A, B, C and D and reared in separate pens for 35 days in an open sided house. These groups were divided into two vaccinated and non-vaccinated sub-groups for the different treatments. Each sub group was carrying three replicate (10 chicks/replicate). Group A was kept as control, while B, C and D were given infusion @ 10 ml/lit of water. The schedule was designated as the group B received infusion at alternate day, group C received infusion on alternate three days in a week and group D received infusion at alternate week. Relevant data was recorded throughout the experiment till the termination of experiment. Significant increase in hemoglobin concentration, PCV and total leukocyte count (TLC) was observed in group C. Significant reduction was recorded in ALT and ALP in group B, while AST and serum glucose in group C and increased in serum protein was found in group B. Decreased (p<0.05) total cholesterol, triglyceride, LDL, VLDL, and increased HDL (p<0.05) were experienced in group B. Comparing the values of risk ratio of, VLDL to HDL, Total cholesterol to HDL and LDL to HDL were found significantly lower in group B, while total cholesterol to VLDL was found significantly lower in group C. It is concluded that schedule on the basis receiving infusion three days in a week is more potent than other schedule of research study.
Design and Development of Heart Rate Variability Measurement Device in Real Life Application

Cardiovascular diseases are among the main reasons for population death. High Blood pressure (BP), smoking, diabetes etc. are the main risk factors for generating cardiac anomalies. Cardiac dysfunctions can be noninvasively measured through heart rate variability (HRV refers to the time distance between the R waves of the ECG signal). Handheld portable ECG devices to monitor and analyse cardiac electrophysiology is increasingly popular in the recent times and becomes an inevitable add-on for smart devices[1] . Detecting and analysing cardiac features in real-time becomes an extremely challenging task in real-life situations. However, circumventing those limitations might give valuable diagnostic information on cardiac health. For this purpose, a portable wire-less hardware using pocket size micro controllers which could acquire ECG with an acceptable noise level and send the signals at a minimum distance is conceived[2].
EXTRACTION, PARTIAL PURIFICATION AND CHARACTERIZATION OF BACTERIOCIN FROM Lactobacillus casei NCIM NO.2732

Bacteriocins from lactic acid bacteria are considered as safe additives to control the frequent development of pathogens and spoiling microbes in food and feed. The present study deals with the screening of three standard strains of lactobacilli like Lactobacillus casei (NCIM No. 2732), Lactobacillus fermentum (NCIM No. 2166) and Lactobacillus plantarum (NCIM No. 2373) for bacteriocin production. The antibacterial activity was analyzed against two food borne pathogens, E.coli and Pseudomonas aeruginosa. Among the three strains, L.casei was found to be the most potent based on the zones of inhibition recorded against both the test organisms. The L.casei bacteriocin was partially purified by ammonium sulphate precipitation. Physico-chemical characterization of the partially purified bacteriocin revealed that the compound was relatively stable up to 70C for 30 min. Further heat treatment led to complete loss of activity. The pH stability studies of bacteriocin showed that there was a significant increase in the antibacterial activity from a pH of 3-7; no activity was recorded beyond pH 11. Evaluation of antibacterial activity at different storage periods at 4C revealed that up to 7 days the activity was stable and thereafter there was a gradual decrease in the activity. The proteinaceous nature of bacteriocin was confirmed by treatment with trypsin.
447-451 Jianlei Yuan

This study was conducted to enrich and purify the active constituent in Polygonum cuspidatum, and to study its anticancer activity. Extraction conditions of Polygonum cuspidatum were optimized by investigating the macroporous resin model, flow rate and ethanol concentration. MTT assay and electron microscopy were used to analyze the inhibitory effect of Polygonum cuspidatum extract on human SW480 cells. During the investigation of enrichment and purification process, the optimal conditions for enrichment of Polygonum cuspidatum extract with D101 macroporous resin were identified to be a 3-fold amount of 75% ethanol, and a flow rate of 2 BV/h. Under electron microscope, nuclear morphological changes are seen in SW480 cells treated with Polygonum cuspidatum extract; apoptotic characteristics are significant, and apoptotic bodies are formed eventually. MTT assay results showed that the inhibitory effect of Polygonum cuspidatum extract on SW480 cells increases with the increase of concentration and prolongation of action time within the experimental concentration range, which proves a doseand time-dependence of action. Polygonum cuspidatum extract has a marked inhibitory effect on human colon cancer SW480 cells.
Big Data: A Review on Security Perspective-Problems and Applications

: With the advent of increasingly versatile information growing every day, more and more methods are used to facilitate the growing information. This information (also known as big data), is the very essence of our technological advancement, but immense care must be taken to maintain the security and privacy that should go hand in hand while processing this information. In this paper, we shall look into the very definition of big data, how it is stored in a cloud system, the issues regarding security and privacy of the big data stored and what measures have been taken so far to overcome these problems.
Antimicrobial dyes based on heterocyclic and/or homocyclic systems for dyeing and textile finishing

This review article deals with the antimicrobial finishing of textiles with antimicrobial dyes based on heterocyclic / homocyclic systems also deals with the Antimicrobial Activity, Structural Features of Antimicrobial Functional Dyes, Requirements for Antimicrobial Finishing and various methods that sued for Evaluation of Antimicrobial Efficacy of these dyes (qualitative and quantitative). This review article also describes the major antimicrobial activity of dyes based on heterocyclic / homocyclic systems. Keeping in mind the multitude of existing systems, different dyes is classified as natural, direct, cationic, reactive and disperse dyes. In addition, this article review illustrates the use of these dyes for dyeing as well as antimicrobial textile finishing.  2014 Trade Science Inc. INDIA