Miracle-dz/UniFAR-FTUs huggingface dataset:
Reduced Levels of Testosterone Induce LDL Oxidation and Atherosclerotic Lesions Involving Inflammatory Imbalance and Reduced Macrophage Apoptosis

Atherosclerosis is among the major cardiovascular diseases that cause death in the world. Men who are deficient in androgen hormones are more susceptible to this disease. The aim of this study was to evaluate the influence of reduced levels of testosterone on the lipid profile, pro and anti-inflammatory cytokines, apoptosis of peritoneal macrophages and the development of atherosclerosis in LDLr-/-mice, as well as on the levels of OxLDL in healthy male humans. Tissues and organs of the experimental animals were used to evaluate lipid deposition in aorta and apoptosis of peritoneal macrophages. In humans the levels of testosterone and OxLDL were analyzed in blood samples from healthy male subjects, who were divided into two groups: low level and high level of testosterone. Animals with decreased testosterone did not present changes in the lipid profile or the levels of IL-6 and TNF-α. However, a decrease in IL-10 and an increase in the IL-6/IL-10 and TNF-α/IL-10 ratios were observed. An increase in the aorta lipid deposition was observed and a decrease in macrophage apoptosis was also demonstrated. In humans, there was an increase of OxLDL in the group with lower levels of testosterone. The findings suggest that decreasing endogenous testosterone levels may induce the development of atherosclerosis, with participation of inflammatory response and macrophage apoptosis. This is reinforced by our human studies, where individuals with low testosterone levels had higher LDL oxidation, which may predict a high atherosclerotic risk for these men.
A HYBRID RECOMMENDER SYSTEM IN E-COMMERCE USING CUSTERED CONTENT BOOSTED COLLABORATIVE FILTERING

: Most recommender systems use Collaborative Filtering or Content-based methods to predict new items of interest for a user. While both methods have their own advantages, individually they fail to provide good recommendations in many situations. Incorporating components from both methods, a hybrid recommender system can overcome these shortcomings. In this paper, we present an elegant and effective framework for combining content and collaboration. Our approach uses a content-based predictor to enhance existing user data, and then provides personalized suggestions through collaborative ﬁltering followed by clustering. We present experimental results that show how this approach, Clustered Content-Boosted Collaborative Filtering, performs better than a pure content-based predictor, pure collaborative ﬁlter, and a naive hybrid approach.
Landslide prediction system, Multi-parameters based landslide prediction, landslide prediction software I. INTRODUCTION Landslide is a frequently occurring natural hazard in hilly regions. Major landslide prone areas in India are the Himalayas, Indo-Burmese Range, Western and Eastern Ghats, Nilgiris

The paper describes details of real time landslide monitoring and prediction system using wireless sensor networks (WSNs). The system consists of wireless nodes, gateway, base radio, server, geosensors and solar power arrangement. The system continuously monitors different parameters affecting landslide. Landslide prediction is done based on multivariate statistical analysis of various parameters and analytical hierarchy process method. The system provides different audio-visual alarms and short message services depending on prediction of landslide danger levels so that precautionary measures can be taken by nearby residents and local governing body. The paper also enumerates calibration procedure of geosensors used for landslide prediction by conducting laboratory trial in simulated condition.
PRE-RECTIFICATION TECHNIQUE -THE NODE RECOVERY SYSTEM FOR SECURE AND DISTRIBUTED DATA DISSEMINATION IN WSN

A wireless detector network consists of little detector nodes, that's able of assembling info from the environment and speaking to the controller through Wi-Fi transceivers. Restricted battery energy is employed to manipulate the detector nodes and is tremendously troublesome to trade or recharge it, as soon as the nodes die. It's in general elaborate or no longer possible to trade the batteries of the detector nodes. On the reverse hand, the final destination is as a rule rich in energy. On account that the detector power is that probably the most valuable useful resource inside the WSN, powerful utilization of the energy to fortify the community period has been the most important center of attention of abundant of the analysis on the WSN. This will influence the community efficiency. In most of current protocols authors considered handiest on the centralized knowledge dissemination approaches without more protection and vigor consideration. We generally tend to set up the protection vulnerabilities in previously planned protocols and that we lengthen the secured and dispensed information delivery process with vigor concerns. It’s the first allotted expertise discovery and dissemination protocol that enables community homeowners and permitted customers to disperse expertise items into WSNs without relying on the bottom station and with community existence time administration. The present DiDrip [1] protocol is handiest concentrating on the security factor. In our venture we advise as more desirable dissemination protocol, which is used to fortify the nice of service disorders. In our stronger work we advocate a approach to increase the vigor efficiency in distributed wireless sensor network.
Intelligent Load Balancing Approach for Cognitive Radio Networks

__________________________________________ Abstract—Presently most of the wireless service providers are encountering increasing spectrum shortage due to ever increasing demands from users. This spectrum shortage also affects channel utilization due to comparatively high congestion levels. The main reason that leads to useless utilization of the radio range is the spectrum licensing system itself. Due to this static and rigid allocation, wireless systems have to work only on a dedicated band of spectrum and cannot change the transmission band as changing the environment. One of the solutions that have been proposed to solve this critical problem is to use unlicensed devices in the available licensed bands. Therefore, dynamic spectrum access techniques based on load balancing are proposed to provide efficient spectrum utilization. In Cognitive Radio Network (CRN) a large number of very frequent connection requests from both primary and secondary user’s results in dynamic demand for a number of target channels. In this work an intelligent load balancing scheme has been proposed whose aim is to help cognitive user to find suitable channel in case of overload so as to enable the resumption of unfinished transmission as quickly as possible. The simulation results of the proposed scheme show that the model works well in reducing channel overload thereby reducing delay time in Cognitive Radio Networks.
REVIEW ON VIRTUAL MACHINE RESOURCE ALLOCATION IN CLOUD-FOG COMPUTING SYSTEMS

:- Cloud is a resource pool from where resources can be accessed. Fog computing has been proposed to deal with a vast number of connected devices. As the resources are finite, it is very difficult to fulfill all demanded resources by the consumer and so that it is not possible to meet cloud consumers QOS requirement. Virtual machine allocation is allocation of a set of virtual machines to a set of physical machines located on data centers. Here the objective is to increase the revenue by increasing the resource usage by allocating the VM in the efficient manner so that resource utilization will get increase and hence more revenue will be generated. This paper provides a view on the current state research to allocate virtual machine in the area of fog computing and internet of things technology.
International Journal of Advance Research in Computer Science and Management Studies

: Various methods or experiments can be used for face recognition and detection however two of the main include an experiment that evaluates the impact of facial landmark localization in the face recognition performance and the second experiment evaluates the impact of extracting the HOG features from a regular grid and at multiple scales. We study the question of feature sets for robust visual object recognition. The Histogram of Oriented Gradients significantly outperform other existing methods like edge and gradient based descriptors. We study the influence of each stage of the computation on performance, concluding that fine-scale gradients, fine orientation binning, relatively coarse spatial binning, and high-quality local contrast normalization in overlapping descriptor blocks are all important for good results. Comparative experiments show that though HOG is simple feature descriptor, the proposed HOG feature achieves amazing results with much lower computational time.
Ocular Findings in Susac Syndrome

Purpose: To describe retinal changes in Susac Syndrome (SS), report its evolution and the importance of follow-up in these patients. Setting: The patient was being followed in the Ophthalmology Department of Irmandade Santa Casa de Misericórdia de São Paulo (ISCMSP) São Paulo, Brazil. Methods: Case report of a patient with SS and evaluation of alterations observed in ophthalmological, neurological and otological examinations. Discussion: SS lesions can affect the vessels of the retina, brain and inner ear with artery occlusions. The patient in this case had mild changes in the structures that make up the triad of SS. Conclusion: In order to avoid possible relapses of the disease and to maintain a good prognosis, it is necessary to observe regular follow-up and initiation of early treatment to prevent damages that compromise such structures and may cause irreversible deficits to the patient.
Towards Environmental Retrofitting of Egyptian Transitional Spaces: Courtyard-Building in Alexandria University, Egypt

Consuming huge amount of energy and emitting large amount of heat can be assumed as one of the main problems facing urban environment in the world today. These problems associated with current high urban density and less of vegetation within urban fabric. For instance, in Egypt, Universities are today facing rising problem of offering more educational spaces especially in large cities such as Cairo and Alexandria. The study thus focuses on Revival Egyptian buildings in Alexandria University based on hierarchical transitional spaces. As Egyptian transitional spaces, such as courtyards historically were essential outdoor spaces for multiple uses and purposes. As part of retrofitting research project of existed transitional spaces in Alexandria University, this paper focused on one parameter which is building height. This is by targeting to find the maximum height of courtyard building with minimum negative effect on air and thermal flow. This simulation is done with consideration to the surrounding urban context in Alexandria University. The simulation approach is based on two years of field measurement of thermal conditions and air velocity in the Universityrsquos transitional spaces. The study is usingfield-measurement data for nurturing the Computational Fluid Dynamics (CFD) model, and for validating the simulation results. The Computational Fluid Dynamics (CFD) study is done by introducing four cases of different building heights to investigating the changing air and thermal flow inside the existed courtyard. nbsp
Security of Intelligent Building Network Based on Wireless Sensor Network

In order to study the intelligent buildings, the intelligent building network security of wireless sensor was explored. Because of its advantages of low cost, easy installation, low maintenance and update cost, wireless sensor network system was applied to intelligent building. In view of the characteristics of various influencing factors on the wireless sensor network working environment, node hardware cost and location accuracy, a secure localization algorithm based on DV-Hop was put forward. The security analysis results showed that the algorithm resisted external attacks and guaranteed the accuracy of location results. Based on the above findings, it is concluded that the algorithm can be used to protect the safety of wireless sensor network in building.
High Step-up Converter with Transformerless Inverter for PV-Grid connected Power System

Photovoltaic(PV) systems are expected to play an important role in future energy production. An asymmetrical interleaved high step-up converter is used to get high step up gain to step up the input energy which is obtained from PV panel without operating at an extreme duty ratio. The traditional inverter which is used to convert the converter output energy from DC to AC, contains a line frequency or a high frequency transformer between the inverter and Grid. Due to this isolation transformer, the efficiency of the system is reduced and also it increases the cost and size. In order to overcome these difficulties the efficient solution is to remove the isolation transformer, which may leads to appear of Common Mode(CM) ground leakage current on the parasitic capacitor between the PV panels and ground. The common mode current reduces the efficiency of power conversion stage and affects the quality of grid current. To eliminate this CM leakage current, virtual DC bus is proposed in this project. By connecting the grid neutral line directly to the negative pole of the DC bus, the stray capacitance between the PV panels and the ground is bypassed. The CM ground leakage current can be suppressed completely. This topology will be modulated by using unipolar SPWM technique to reduce the output current ripple and harmonics. IndexTerms—High Step-up,photovoltaic system,voltage multiplier module,transformerlessinverter,common mode current, unipolar SPWM,virtual DC bus,switched capacitor.
OC-038 Making The Change: Switching to Infliximab Biosimilars for IBD at North Bristol NHS Trust

Introduction Infliximab biosimilars have been available since February 2015, however at the time there was limited guidance on how to introduce the products. The PLANETRA and PLANETAS studies demonstrate that biosimilars are equivalent in clinical efficacy when compared to Remicade®. From the 1st July 2015, the gastroenterology department at NBT introduced biosimilar infliximab making cost savings of £200,000. A 50:50 gain share agreement was negotiated with the local Clinical Commissioning Groups and these savings will be re-invested into Gastroenterology services. Here we describe how a multidisciplinary approach led to a safe transition to biosimilar infliximab. Methods An additional pharmacist was funded to implement the switch using projected savings from the gain share. Patients who were established on Remicade® were sent a letter with details of the proposed switch and given the opportunity to raise any concerns in a consultation with the specialist pharmacists in Gastroenterology. Verbal consent was obtained prior to switching to Inflectra®. Practical guidance for the prescribing and dispensing of biosimilar infliximab was circulated to clinicians and pharmacy staff. Educational sessions were provided to the Medical Day Case Unit nurses. Adverse events were reported via the Yellow card® Scheme and the Biologics Therapy Audit. From December 2015, patients were asked to complete a survey to explore their experiences leading up to and during the switch. We decided not to study clinical outcomes as the sample size is misrepresentative and the follow-up period too short to draw meaningful conclusions. Results In total, 64/65 patients consented to the switch. Following the switch, 7 patients discontinued treatment (2 post-surgery; 5 switched to alternative biologic). We received a 46% response rate to the survey. Patient feedback was largely positive. 83% of patients received the written correspondence; 93% reported that they understood the information leaflet in part (23%) or in full (70%). 96% had the opportunity to speak to pharmacist before their first infusion. Overall, 97% of patients were satisfied with the changeover process. Conclusion We have demonstrated how a multidisciplinary approach allowed the successful switch to a biosimilar within 3 months and the potential benefits to be had. The additional pharmacist post, funded by the projected gain share, will be made a substantive this year allowing for closer monitoring and optimisation of biologic treatment. This will lead to further cost savings through discontinuation of these drugs where appropriate. Since the completion of this project, the BSG has revised their statement to acknowledge that there is sufficient evidence to recommend use of biosimilar infliximab in IBD. Disclosure of Interest L. Chung: None Declared, B. Arnold: None Declared, R. Johnson: None Declared, M. Lockett Conflict with: sponsored by MSD to attend conference in 2016
An Efficient Artificial Bee Colony Algorithm for Constrained Optimization Problems

: Artificial Bee Colony (ABC) algorithm is a relatively new swarm intelligence algorithm which has shown a competitive performance with respect to other population-based algorithms. However, there are still some insufficiencies in ABC algorithm such as slow convergence and easily trapped in local optima. These drawbacks can be even more challenging when constraints are also involved. To address these issues an Efficient Constrained Artificial Bee Colony (eABC) algorithm is proposed where two new solution search equations are introduced respectively to employed bee and onlooker bee phases. In addition, smart flight operator is employed to be used in scout bee phase. This algorithm is tested on several constrained benchmark problems. The numerical results demonstrate that the eABC is competitive with other state of the art constrained ABC algorithms under consideration.
Data Utility Metrics for k-anonymization Algorithms

Shuchita Upadhyaya Professor, Department of Computer Science & Applications, Kurukshetra University, Kurukshetra136119 Email: Shuchita_bhasin@yahoo.com Abstract Privacy remains a major serious issue while publishing the data. In today’s environment some organizations publish their data for the purpose of research. Although during publishing organization keeps a check on attributes which can uniquely identify the information for individual, yet sometimes published information may prove to be an asset for an attacker, which may retrieve sensitive information about an individual. As a result, data protection along with its privacy is an important domain of research. Multiple techniques of anonymization have been proposed to secure the privacy of an individual and to reduce information losses. Out of the provided anonymization techniques kanonymity is one of the most popular technique which is based on the concept of generalization and puts a check on such type of attacks that helps to anonymize the data sets. In this paper first a brief discussion of various k-anonymity algorithms is presented. Further, various metrics have been discussed for verification of different data sets along with their illustration.
USING MACHINE LEARNING IN PEG SOLITAIRE STRATEGIC GAME

Machine learning is an important research area of computer science with rapid development. This is due to the growth in the database industry, the advancement of data analysis, research and the resulting market needs for methods that are capable of extracting valuable knowledge from large data stores. Using the concept of Machine Learning, we have tried to apply it to a strategic game Peg Solitaire. We have used adecisiontree, backtracking and pagoda function after analysis. Patterns are discovered, and further moves are taken in the game. It shows that ML is a perfect approach for a strategic game
INVESTIGATION OF FALSE DATA INJECTION IN SMART GRID TO MINIMIZE THE SECURITY RISKS IN AGC

-In smart grid, when the false data is injected to electronic monitoring system, the AGC will directly affects and potentially leads to blackouts. The main objective of this paper is to examine the attacks due to injection of false data in smart grid for the purpose of minimizing the risks in AGC. In the previous research, the Intrusion Detection System was used, in which they implemented Intrusion Detection Algorithm for the grid security system. But this method can’t be employed often due to mathematical complexity and difficulty in practical implementation. This paper presents a Game-Theory based method for the security of smart grid by relating the quantifiable risk managing techniques with decision making for protective measures. The significances of the injected data attacks are computed using risk assessment process. The calculated risks are then unified into the stochastic (Markov) security game classic as input parameters. The decisions of protective measures are attained by resolving the game using dynamic programming approach which considers the resource constraints. The Nash equilibrium results are used to acquire the Game Matrix. The simulation result indicates that the different risk events will leads to different security approaches. The attacker-defender interaction and the AGC risk minimization are validated through extensive simulation results using MATLAB/SIMULINK.
An Enhanced Throttled Load Balancing Approach for Cloud Environment

---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Cloud computing is advancing with a rapid speed. Already, it has been adopted by a huge set of users. Easy to use and anywhere access like potential of cloud computing has made it more attractive relative to other technologies. This has resulted in reduction of deployment cost on user side. It has also allowed the big companies to lease their infrastructure to recover the installation cost for the organization. Roots of cloud computing have extended from Grid computing. Along with the inherited characteristics of its predecessor technologies it has also adopted the loopholes present in those technologies. Some of the loopholes are identified and corrected recently, but still some are yet to be rectified. Two major areas where still scope of improvement exists are security and performance. The proposed work is devoted to performance enhancement for the user of the existing cloud system by improving the basic throttled mapping approach between task and resources. The enhanced approach has been checked using the cloud analyst simulator. The results are compared with the original and it has been found that proposed work is one step ahead of existing techniques.
Biomarkers in Periodontal Disease

The current clinical diagnostic criteria were introduced almost a half century ago continue to use as the basic of oral diagnosis in today’s clinical practice. But the disadvantages are they measure disease severity rather than disease activity. Evolvement with time is brought us to the era of biomarkers. Biomarkers are micro molecules that can be used as to measure health status, disease onset, treatment response and outcome. Various biological media like saliva and gingival crevicular fluid (GCF) are used to determine biomarkers in periodontal health and disease. Periodontitis being a multifactorial disease; it’s unlikely that a single biomarker will able to predict periodontal disease activity and severity. So combinations of biomarkers are used to predict the disease activity. The present review highlights the need for identification of biomarkers and the various substances used for the identification and difficulties and sensitivity of the biomarker in the diagnosis, progression and treatment outcome of periodontal disease.