Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiphoton Tomography and Cross-Polarization Optical Coherence Tomography for Diagnosing Brain Gliomas: Pilot Study

V.V. Dudenkova, Junior Researcher, Laboratory of Studying Optical Structure of Biotissues, Institute of Biomedical Technologies1; PhD Student, Faculty of Radiophysics2; K.S. Yashin, PhD Student, Department of Neurosurgery3; Junior Researcher, Laboratory of High-Resolution Microscopy and Gene Technology, Institute of Biomedical Technologies1; E.B. Kiseleva, PhD, Researcher, Laboratory of Studying Optical Structure of Biotissues, Institute of Biomedical Technologies1; S.S. Kuznetsov, MD, DSc, Professor, Department of Pathological Anatomy1; L.B. Timofeeva, PhD, Assistant, Department of Histology with cytology and embryology1; A.S. Khalansky, MD, PhD, Head of the Laboratory of experimental Histopathology of central Nervous System4; V.V. Elagin, Researcher, Laboratory of Studying Optical Structure of Biotissues, Institute of Biomedical Technologies1; E.V. Gubarkova, PhD, Junior Researcher, Laboratory of Studying Optical Structure of Biotissues, Institute of Biomedical Technologies1; M.M. Karabut, Junior Researcher, Laboratory of Studying Optical Structure of Biotissue, Institute of Biomedical Technologies1; N.P. Pavlova, Laboratory Technician, Laboratory of Studying Optical Structure of Biotissue, Institute of Biomedical Technologies1, I.A. Medyanik, MD, PhD, Senior Researcher, Group Microneurosurgery3; L.Ya. Kravets, MD, DSc, Professor, chief Researcher, Group Microneurosurgery3; N.D. Gladkova, MD, DSc, Professor, Vice Director for Science, Institute of Biomedical Technologies1
An Investigation of the Inter-Annual Wind Changes In Iran

In this study, an attempt has been made to evaluate long-term average variation and fluctuation of wind in Iran. For this purpose, wind database network was initially formed over Iran. Then, data from the base of a 30-year period, the daily period of 1/01/1982 to 31/12/2012, was supposed as the basis of the present study, and a cell with dimensions of 15 × 15 km of the studied area was spread. In order to achieve the wind three past decade's changes in Iran modern methods of spatial statistics such as, Moran global spatial autocorrelation, Moran Local insulin index and Hot spots, by using of programming in GIS environment, were accomplished. The results of this study showed that the spatial distribution of wind in Iran has the cluster pattern. In the meantime, based on Moran local index and Hot spots, wind patterns in the South, South-East, East, South West and West, have spatial autocorrelation positive pattern (too much windy pattern), and parts of the Caspian Sea coast, north and center of the country have negative spatial autocorrelation (low wind pattern). During the study period, a large part of the country (almost half of the total area) had a significant pattern or spatial autocorrelation.
Degree of Multi-tenancy and its Database for Cloud Computing

—Multi-tenancy, which allows a single application to emulate multiple application instances, has been proposed as a solution to this problem. By sharing one application across many tenants, multi-tenancy attempts to replace many small application instances with one or few large instances thus bringing down the overall cost of IT infrastructure. In this paper, we present importance of Multi-tenancy in cloud computing, degree of Multi-tenancy and Multi-tenancy in databases. It will helpful to understand about Multi-tenancy and its benefits in software as a service in cloud computing environment.
The Decision tree Mode for Prediction the Response to the Treatment in Patients with Chronic Hepatitis C

Interferon plus Ribavirin is the standard treatment for chronic hepatitis C is often accompanied by adverse side effects and unfortunately fails in almost half of cases. The ability to predict such failures previous to treatment could save a great deal of pain and expense for the patient with HCV. Decision tree with CART classification algorithm was developed to forecast response to therapy with 200 chronic hepatitis C patients. The data was divided where 150 cases were used to create the classifier and 50 cases for validation. HAI (hepatitis activity index), Fibrosis, ALT, age, and Gender were used as predictors for response of therapy. The overall classification error was 20% and 80% was the best accuracy, sensitivity and specificity were 0.80, 0.89% and 78%, respectively were results from validation stage as the following, true cases are 40 from 50 (total number of validation cases) and false cases 10 (represent error 20%). This model will help the physicians to build a decision before patient undergo treatment. [M. Hassan; M. I. Abdalla; S. R. Ahmed; W. Akil; G. Esmat; S.Khamis; M. ElHefnaw. The Decision tree Mode for Prediction the Response to the Treatment in Patients with Chronic Hepatitis C. New York Science Journal 2011; 4(7): 69-79]. (ISSN: 1554-0200). http://www.sciencepub. net/newyork.
Domestic Violence And Alcohol Dependence: Cross Sectional Study In A Tertiary Care Setting

Background: Domestic violence is an all-pervasive, serious social malady with major public health implications. Alcohol use is among the most controversial and widely debated component in conceptual and predictive model of domestic violence. Objectives: a) Variation of Domestic violence (Intimate partner violence) by background characteristics, b) Prevalence of domestic violence among spouses of inpatients at deaddiction centre, c) To find characteristics, dimensions, severity of domestic violence experienced by the partners & d) To assess psychological status of both perpetrators
PROXY SIGNATURE SCHEME FOR WARRANT PARTIAL DELEGATION

The idea of a proxy signature scheme was first presented by Mambo et al. [1] in 1996. Their proxy signature scheme allows an original signer to delegate his signing right to a proxy signer to sign the message on behalf of an original signer. Later, the verifier, which knows the public keys of original signer and a proxy signer can check a validity of a proxy signature issued by a proxy signer. Till now we have the following types of delegations. In general, there are three different types of delegations: full delegation, partial delegation and delegation by warrant. In a full delegation proxy signature scheme, a proxy signer uses the same private key as an original signer and creates the proxy signature as an original signer does. The drawback of a full delegation comes from a difficulty of distinctive between an original signer and a proxy signer. In a partial delegation proxy signature scheme, the original signer derives the proxy key from his private key and passes it to the proxy signer in a secure channel. In the proxy signature scheme with delegation by warrant, an original signer provides the proxy signer a special message namely warrant. The warrant certifies that a proxy signer is legal and contains signer identity, delegation period and the types of a message on which a proxy signer can sign. Also, there are two types in the second one: protected and unprotected proxy signature schemes. In unprotected proxy signature scheme, a proxy signature is generated by both the proxy signer and an original signer. In this case, the verifier cannot distinguish the identity of a signer. In the protected proxy signature scheme, a proxy signature is generated by the proxy signature key of an original signer and also with a private key of a proxy signer. PROXY SIGNATURE SCHEME FOR WARRANT PARTIAL DELEGATION
Study of Spam Intrusion Detection Techniques

Spam refers to immaterial or unwanted messages sent over the Internetto a large number of users to spread inappropriate advertisement messages and malware. The paper aims to propose the most feasible machine learning techniques to be used for spam detection in computer networks. The most common form of spam messages out there are email spams. The purpose of the paper is to provide a comprehensive comparison amongst the different techniques and thereby come up with the most apposite technique for the same. The paper seeks to describe each technique in detail by providing the way in which it can perform spam detection. The focusis on obtaining a single technique that would be helpful and suitable in all ways to perform spam detection with maximum efficiency.The techniques compared are ZeroR, Bagging, Random Forest, Rotation Forest and J48.
Effect of Feeding Castor Seed Cake Based Diets on Growth, Nutrient Utilization, Immune Response and Carcass Traits in Lambs

An experiment was conducted to study the effect of utilizing Castor (Ricinus communis) Seed Cake (CSC) (30-45% Crude Protein; CP) as sole protein supplement, replacing groundnut cake (GNC) on growth performance, nutrient utilization, immune response and carcass traits in lambs. Two isonitrogenous and isocaloric complete diets (10.5% CP and 58% TDN) were formulated with 13% GNC and 10% CSC and fed ad libitum to 14 Nellore male lambs (27.54+1.154 kg), divided at random into two groups of seven animals for a period of 150 days. The lambs in both groups grew linearly with average daily gain of 75.33 and 74.28 g, respectively with no significant difference. Inclusion of CSC did not affect the Dry Matter (DM) and CP intake and was comparable to that of control lambs but the intake of metabolizable energy was lower (p<0.01) in CSC fed lambs. The lambs fed either GNC or CSC utilized DM and nutrients with similar efficiency. Inclusion of CSC in complete diets of lambs did not affect the nutrients digestibility, balances of nitrogen, calcium and phosphorus, hematological (haemoglobin, total erythrocyte and leucocyte counts) and biochemical constituents (total protein, albumin, globulin and creatinine) except for higher (p<0.01) digestibility of crude fibre in CSC fed lambs compared to GNC feeding. While, the antibody titers against heat killed Brucella abortus and chicken RBC antigens assessed at 75 day of feeding and the skin indurations against PHA-P mitogen, assayed at 150 day of feeding was lower (p<0.01) with CSC feeding. The carcass characteristics (dressing percentage, proportion of meat, bone and fat, proportion of edible and non-edibles, whole sale cuts, organ weights and chemical composition of Longissimus dorsi muscle) were not influenced by inclusion of CSC as sole protein supplement. Histopathological lesions observed were mild to moderate areas of necrosis, congested blood vessels with increased kuffer cell activity in liver, swollen kidney tubules with increase in mononuclear cell infiltration, decreased goblet cell activity and infiltration of neutrophils in intestines. The study suggested no adverse effect on the nutritional performance and carcass traits of lambs with inclusion of 10% CSC in complete diets but the immune response was depressed and lesions of pathological significance was observed in vital organs compared to GNC fed lambs.
Microstrip Line Low Pass Filters Based on Metamaterial Component

Stepped impedance microwave low pass filters (LPFs) are presented. The conventional stepped impedance LPF with cut off frequency of 1. 9 GHz is proposed. Replacing split ring resonator (SRR) instead of low impedance line in conventional design is presented to get compact, low insertion loss (IL), sharp cutoff, and high selectivity LPF. The proposed filter have better result compared to conventional counterpart. The simulated results indicated that the proposed filter achieved flat pass-band without ripples, corresponding to numbers of unit cells of SRR structure. Numerical result for the stepped impedance microwave LPFs are obtained. The filters are simulated by the computer aided design software (Ansoft HFSS) tool.
Improving the Quality of Image Using Particle Swarm Optimization

Image improvement is one of the important image processing capabilities. It can be used to transform one image to another to improve the view of it for human viewers, or to extract finer details of images which may provide better input for other automated image analysis systems. Image improvement is considered as an optimization problem. We can use particle swarm optimization (PSO) is used to solve it. The quality of the intensity image is improved by a transformation function, in which parameters are optimized by PSO based on given criterion function. For image improvement task, a transformation function is required which takes the intensity value of each pixel from the input image and generates a new intensity value for the corresponding pixel to produce the improved image. To evaluate the quality of the enhanced image automatically, a quality function is needed which tells about the quality of the improved image.
Adiponectin in Relation to Glucose and Insulin Resistance in Asthma Patients

Although there is evidence of a positive association between asthma and obesity in adults and children, the specific mechanisms responsible for these observations are not obvious. The purpose of this study was to examine the relation of serum adiponectin with to marker indicators of blood glucose and spirometry indexes in asthma patients. For this purpose, Forty eight sedentary males with mild to moderate asthma were enrolled to the study by voluntarily. All patients underwent anthropometrical measurements, a resting spirometry testing and fasting blood sampling for measuring serum adiponectin, insulin and glucose. Insulin resistance and Beta cell function were assessed using the homeostasis model assessment for insulin resistance formula derived from fasting insulin and glucose levels. Pearson correlation method used to determine the relationship between adiponectin with the other variables. A statistically significant inverse correlation was observed between serum adiponectin with insulin, glucose, insulin resistance and marker indicators if asthma diagnosis such as FEV1 (p < 0.05). In addition, serum adiponectin level was positive correlated with Beta cell function (p < 0.05). Based on our results, it seems that In addition to spirometry testing, serum adiponectin is a indicator of asthma diagnosis in obese subjects. Also, serum adiponectin is a precise predictor of glucose and its determinatives in asthma patients.
SYNTHESIS, PHARMACOLOGICAL AND TOXICOLOGICAL EVALUATION OF AMIDE DERIVATIVES OF IBUPROFEN

Pain, fever and inflammation have been associated with mankind since beginning. Nonsteroidal antiinflammatory drugs (NSAIDs) are the first choice drugs used for the treatment of pain, degenerative inflammatory joint diseases and rheumatic disorders. NSAIDs were found to be associated with undesirable side effects ranging from dyspepsia to symptomatic and complicated gastric and duodenal ulcers. The greatest degree of damage is generally caused by NSAIDs which contain a free carboxylic group. In our approach, Ibuprofen containing free carboxylic group has been modified into various amide derivatives using different aromatic as well as aliphatic amines, which resulted in masking of the carboxylic moiety. Evaluation of the amide derivatives of ibuprofen resulted in improved analgesic, gastroprotective as well as antiinflammatory activity.
3D Technology in the Automotive Industry

— In today’s contemporary society, the use of computer applications to enhance the process of producing or manufacturing products have become a common phenomenon. One example of such computer applications is the 3D printing software, which has been adopted by a range of corporations to optimize their manufacturing and production process. The focus of this project is on the improvement of the manufacturing technology process by use of 3D printing software in the automobile industry. The following research will cover the introduction and background of the research, description of the problem statement and analysis of literature on publications illustrating the significance of 3D technology in the automotive industry. The discussion of the research methodology used to execute the research will also be outlined, and the section will be followed by the analysis and presentation of findings of the research. Lastly, the summary of the key points of the research will be provided, and it will be accompanied by the conclusion and recommendations of the research. The findings of this study will be beneficial to the stakeholders of the automotive industry in learning how 3D printing technology can be utilized in the creation of high-quality vehicles at reduced costs.
PRACTISING UNSUPERVISED CLUSTERING WITH GAUSSIAN MIXTURE MODELS

- This paper discusses the unsupervised clustering practice of largely distributed data by utilizing Expectation Maximization (EM) and Maximum Likelihood (ML) in Gaussian Mixture Model. Results in this paper state the fact that it is a better approach to represent a largely distributed data with a number of clusters having various different means but minimum variance possible. Instead of describing it with only a single distribution having a single mean but large variance among the data points.
A Review on the Evolution of Resource Description Framework

The enormous growth in computational speed and storage leads us to distributed and cloud computing. Today, the world runs on digital data, with the invention of the web, most of our data and resources are stored in the web. It has a vast amount of data which continues to grow at greater speed. In the past few years, technology has progressed with the increase in data size, creating boundless demand for a place to store and retrieve it. With this rapid increase, the issue of data scalability has become very important and various solutions using several new technologies have been developed to emphasize on scalability and query efficiency. One such standard that has been graded by the World Wide Web Consortium is the Resource Description Framework (RDF). This data model technology can be utilized to build an efficient and scalable system to retrieve the web resources. Cloud Computing, an emerging technology, also seems to offer some incredible benefits related to data scalability and efficiency. A new technique that takes the advantage of both RDF data management system and Cloud is being adopted to resolve the scalability issues, making it easy to apply all the data operations.
Infections in Burn Patients

Burn patients have a high susceptibility to infections due mainly to a disruption of the skin barrier and to a dysbiosis of the immune system. Infections are a main cause of morbidity and mortality among these patients. Among other damages, infections impair cicatrization, lead to graft loss, prolong treatment, and, consequently, prolong the length of stay and raise costs. The most frequent sites of infection are burn wounds, respiratory tract, urinary tract and bloodstream. The epidemiology of infections in burn patients is different from that of non-burned. Hence, they require a specialized and multi-disciplinary approach. In the present article, general aspects of the epidemiology and microbiology of infections in burn patients, as well as infection control practices, are discussed.
A Review on Sequential Pattern Mining Algorithms

: Sequential Pattern Mining is one of the data mining technique which determines sequential patterns from immense sequential database. Many wide applications follows sequential pattern mining which includes web usage mining, customer’s behavior in shopping h istory, weather forecasting, medical disease analysis, scientific experiments, etc. In the area of sequential pattern mining abundant research has been performed. In this paper we review a progress on some of the sequential pattern mining algorithms. This paper will explain the evaluation factors, the approach they are following and pros and cons of those algorithms. Finally paper will explain a little of demanding issues that need to be solved in future.
OBJECT DETECTION AND TRACKING FOR VIDEO SURVEILLANCE

Object detection and tracking is important and challenging tasks in many computervision applications such as surveillance, vehicle navigation, and autonomous robot navigation. This paper is focused on five existing object detection and tracking techniques. Also this paper presents the moving object detection and tracking using reference Background Subtraction. In proposed method, first frame of video is directly consider as Reference Background Frame and this frame is subtract from current frame to detect moving object and then set threshold T value. If the pixel difference is greater than the set threshold T, then it determines that the pixels from moving object, otherwise, as the background pixels. But this fixed threshold suitable only for an ideal condition is not suitable for complex environment with lighting changes. So, this paperused dynamic optimization threshold method to obtain a more complete moving objects.
IDENTIFICATION AND HPLC QUANTIFICATION OF AFLATOXINS IN GROUNDNUT (ARACHIS HYPOGAEA L.) SAMPLES COLLECTED IN RAYALASEEMA AREA, ANDHRA PRADESH

The present investigation reports the fungal Aflatoxins contamination in groundnut samples collected in different locations in the Rayalaseema area, Andhra Pradesh, India. Aflatoxins were extracted by liquidliquid extraction method using chloroform solvent. The qualitative and quantitative analysis of aflatoxins present in the samples was done using TLC and HPLC techniques. Among the eight samples in the study two samples S3 and S6 were less infected with aflatoxin-producing fungi, and hence aflatoxins were detected in HPLC study. Samples S1 and S4 consist of only B2 and G2 aflatoxins respectively. The chromatogram obtained for sample S2 shows two peaks representing G2, B2 aflatoxins with 0.84 ng/g, 13.0 ng/g quantity. Sample S5 was also found to have two peaks representing G2, B2 aflatoxins with 10.9 ng/g, 0.55 ng/g quantity respectively. Sample S8 chromatogram consists of two peaks represents aflatoxin G1 and G2 with 0.89 ng/g, 13.3 ng/g quantity respectively. Among the samples in the study, a high number of aflatoxins was identified in sample S7. In S7 sample aflatoxin G1, G2 and B2 were identified. The quantity of aflatoxin G1 was found to be very high (20.6 ng/g) and Remaining aflatoxins G2 and B2 were found to be 3.7 ng/g, 4.7 ng/g respectively. Based on the results findings for the analysis of aflatoxins in groundnut samples six samples were found to be contaminated with aflatoxins. Even though the aflatoxins content found less amount, crop management practices that reduce infection in the field and during harvesting may help to prevent the contamination of ground nuts from fungal strains. INTRODUCTION: Aflatoxins are mycotoxins produced by two species of Aspergillus, a fungus found especially in areas with hot and humid climates 1 . These aflatoxins are occurred in food products such as groundnuts, tree nuts, maize, rice, figs and other dried foods, spices, crude vegetable oils, and cocoa beans, as a result of fungal contamination before and after harvest. QUICK RESPONSE CODE DOI: 10.13040/IJPSR.0975-8232.10(3). 1312-18 The article can be accessed online on www.ijpsr. com DOI link: http://dx.doi. org/10.13040/IJPSR.0975-8232.10(3). 1312-18 14 aflatoxins are mostly studied and among them only six of these molecules (B1, B2, G1, G2, M1, and M2) are normally found in foods. The most toxic among all types, aflatoxin B1, is produced by both A. flavus and A. parasiticus 2, 3 . As aflatoxins are known to be genotoxic and carcinogenic, exposure through food should be kept as low as possible. Because of potential health hazards to humans, regulatory levels have recently been documented. Currently, the worldwide range of limits for aflatoxin B1 (AFB1) and total AF (AFT) are 1-20 and 0-35 ng/g, respectively 4-8 . Many researchers have developed several methods for the determination of aflatoxins in food items .