Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization and Evaluation of HepDOCA-doxorubicin Tagged Magnetic Nanoparticles for Hyperthermia

This paper reports the hyperemia effect studies of drug-magnetic iron oxide nanoparticle conjugates (MION) for targeted cancer therapy. MIONs were synthesized by the method of co-precipitation using salts of iron as precursors. Chemically modified heparin derivative (heparin deoxycholate, hepDOCA) was complexed to chemotherapeutic drug, doxorubicin (DOX) and tagged to MIONs, which act as the drug-vectors. Each of these conjugates was characterized by SEM and DLS. To observe the effect of formulations, an inductor RF coil circuit was set up which ensured that the MIONs heat up in an AC magnetic field of 0.79 mT at 960 kHz. Hyperthermia treatment was performed on E.coli (DH5-α strain) cells and the growth of bacteria along with the protein released upon cell lysis was monitored. It was confirmed that HepDOCADOX-MION complex imparts damage to E.coli cells by the magneto-thermo-cytolysis on application of alternating magnetic field. *Corresponding author: Chandraprabha MN, Department of Biotechnology, MSRIT, Bangalore, India, Tel: 919845785174; E-mail: chandraprabhamn@yahoo.com Received November 23, 2016; Accepted December 22, 2016; Published December 31, 2016 Citation: Chandraprabha MN, Lokesh KNL, Rashmi RB, Roshna RG, Vijai SN (2016) Characterization and Evaluation of HepDOCA-doxorubicin Tagged Magnetic Nanoparticles for Hyperthermia. J Nanomed Nanotechnol 7: 416. doi: 10.4172/2157-7439.1000416 Copyright: © 2016 Chandraprabha MN, 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.
Sentiment Analysis of Twitter Data using Statistical

Social media today has becomes a very popular tool in society. Millions of users share their opinions on different topics like politics, technologies, product and many more. Therefore social media is a rich source of data for opinion mining and sentiment analysis. In this paper we use the twitter data for sentiment analysis. First we use the Latent Dirichlet Allocation (LDA) to identify the key terms. These key terms are used to represent each tweet in n dimensional vector. Using this tweet vectors, we build a sentiment classifier, which is able to determine positive, negative, and neutral sentiment of each tweet. Experimental result show that our proposed method is efficient and out performs.
Correlation between Marital Satisfaction and Mental Health in Nurses of Tehran Hospitals

Mental health plays a significant role in ensuring of dynamics and functioning of any community. Those people who have higher life satisfaction, experience deeper affections and feelings and have over ally higher health. The aim of this study was to identify any possible relationship between marital satisfaction and general health in nurses. A multi factorial correlation design was used to convey the study. Accessible sampling was used to select 200 married nurses, aged between 20 and 40 that were working in hospitals of Tehran. We used IMS marital satisfaction questionnaire and General Health Questionnaire (GHQ) to evaluate marital satisfaction and general health respectively among nurses. The data were analysed using Pearson correlation test, regression analysis and variance analysis. Results showed a positive significant correlation between marital satisfaction and general health (p<0.05), but there were no significant correlations between the duration of job and marital satisfaction or general health (p>0.05). Since the correlation between marital satisfaction and general health was positive, resolving marital problems and consequently increasing marital satisfaction can increase the level of general health which may increase the level of health in family and society.
A Miniaturized Microstrip Patch Antenna Array with Enhanced Bandwidth and Reduced Mutual Coupling for Wireless Application

The design of a novel miniaturized microstrip patch antenna array has been presented. The antenna consists of a single layer of Split Ring Resonators around the rectangular patch. The patch sizes are less than conventional designs. Simulations are performed to study the return loss, resonant frequency, bandwidth and mutual coupling between the antenna elements. The technique to reduce the return loss of the patches is also presented. The antennas are designed using the simulation tool HFSS and are suitable to use in IEEE 802.11 WLAN frequency band. Keywords— array antenna, metamaterials, microstripantenna, miniaturization, mutual coupling
Evaluation of the Same Day Diagnosis of TB Microscopy in Comparison with Spot-Morning-Spot Method in Selected Public Health Institutions, Addis Ababa, Ethiopia

Background: The need to collect serial sputum specimens over multiple patient visits for pulmonary tuberculosis results in a protected diagnostic process with rates of patients with high rates of patient dropout. Recent studies on Spot Morning Spot (SMS) method of examination PTB reported that the first two specimens have high smear positivity in line with this WHO changed its policy to minimize the number of sputum specimens from three to two. Methods and Materials: Across-sectional study was conducted in 16 conveniently selected private clinics, governmental health centers, public and private hospitals from September 2017-December 2018. Individuals attending the selected health institutions for the diagnosis of MTB submitted three sputum samples for routine diagnosis (the standard approach). One additional sample was collected 1 h after the first sputum (the same-day approach). One sputum sample was cultured. The diagnosis was performed using ZN sputum smear microscopy and Light-Emitting Diodes Fluorescent Microscopy (LED-FM) technique. Data were entered and analyzed using SPSS version 16. We used sensitivity, specificity and predictive values for the different methods. Result: A total of 209 participants enrolled, 43 (21%) were identified culture positive, 39 (18.7%) were detected by the same day approach and 40 (19.1%) by the standard approach. On the other hand, LED-FM and ZN microscopy detected 39 (18.1%) and 48 (23%) tuberculosis cases respectively. Sensitivity was 88.4% for ZN microscopy and 95.3% for LED-FM and the specificity was 99.4% and 95.9% for ZN and LED-FM microscopy respectively. Conclusion: Using the same day approach together with LED-FM would reduce workload, TAT, patient drop out and increase the smear detection rate. Therefore it is necessary to give in-service and off service training for health personnel towards the use of LED-FM, conventional approach and the same day approach in the diagnosis of TB.
Effects of Ramadan Fasting on Some Biochemi- cal Parameters in healthy subjects

During the fasting month of Ramadan, Muslims are obliged to fast during daytime hours and restrict food and drink intake to the period after sunset. Modifications in the circadian distribution of the eating and sleeping schedule result in various changes in different biochemical parameters. In this study the effect of fasting on glucose, insulin, Cortisol, triglyceride, cholesterol, high density lipoprotein (HDL), low density lipoprotein (LDL), estradiol, testosterone, thyroid stimulating hormone (TSH), FT4 and FT3 during and post fasting was measured. Blood samples were taken from 26 adult male subjects during and post fasting. The results obtained showed a significant decrease in glucose and TSH levels, while the levels of insulin triglyceride, free thyroxine (FT4) and free triiodothyronine (FT3) showed a significant increase. This study showed that there are changes in dietary habits depending on cultural rituals, often practices during Ramadan, among Muslim societies. Consequently that may affect various components of metabolic importance.
Evaluation of the imaging aspects of brain tumors by Magnetic Resonance Spectroscopy

Background: Magnetic resonance spectroscopy (MRS) is an established tool for in-vivo evaluation of the biochemical basis of human diseases. Magnetic resonance spectroscopy (MRS) provides a means to assess functional (metabolic activity) of the brain. On one hand, such lucid depiction of ‘live biochemistry’ helps one to decipher the true nature of the pathology while on the other hand one can track the response to therapy at sub-cellular level. Brain tumors have been an area of continuous interrogation and instigation for mankind. Our aim was to do valuation of these lesions by MRS. Methods: This study was conducted in a tertiary care hospital in which all patients underwent magnetic resonance imaging (MRI) at the same setting as the MRS examination. The MRS examination was performed with the stimulated echo acquisition mode (STEAM) pulse sequence in all children, and occasionally the point resolved spectroscopy (PRESS) sequence also was used. Qualitative spectra were obtained in all patients, and at times quantification data also were obtained. Results: We found that our spectra over the brain neoplasms were consistent with the MRS findings of brain neoplasms in the literature. There was markedly elevated choline with markedly decreased or absent N-acetylasparate and at times elevated lactate and lipid peaks. In children with meningiomas, there was also an elevated alanine peak. We found MRS to be extremely useful in 1) characterizing a brain mass as a neoplasm, 2) differentiating radiation necrosis and radiation-induced meningiomas from the recurrent primary tumor, 3) following treatment response of the primary neoplasm, 4) differentiating residual or recurrent primary neoplasm from postsurgical changes, and 5) identifying inactive neoplasms or neoplasms in remission. Conclusion: By having a basic understanding of the automated MRS in the normal brain for the different pulse sequences (STEAM and PRESS), it is possible to understand the abnormal MRS spectra seen in brain neoplasms.
SMART HOME SYSTEM USING IOT

- Mobile devices are the part of our day-to-day life from last few years. Consequently, providing facilities and security are becoming increasingly prominent features on mobile devices. In this paper, we have to develop a home automation system that interfaces with Android mobile devices. The mobile device and system can communicate with each other via Wi-Fi. The mobile application can be loaded and interfaces with system from any compatible device. Commands to ON/OFF electrical equipment like lights, fans, air conditioners etc. and setting timer at home or any organization can be sent easily and quickly from the mobile devices via a simple and comfortable GUI application, which is easy to use for the any normal users. The system then acts and respond to these commands by taking actions per commands and gives the result to the user. The user can also see the result on Android mobile application within the range of Wi-Fi. Therefore, it's a good choice to design a home automation for luxurious life that aims at designing an advanced home automation system using Wi-Fi technology.
Auto-Upgrading of Signature Case-Base used for Efficient Detection of Identity and Authenticity

: Handwritten signatures, used for identifying a person, suffer from two major drawbacks: they are inherently inconsistent, and they can easily be counterfeited. In this work a classifier is built applying Case-Based Reasoning techniques to resolve these issues by preserving authentic sets of off-line signature images of people within cases. For identification purpose, a bit-sequence containing the most frequent discretized mode value for each global feature is retained per person, and the corresponding pattern forms an index to the case pertaining to each person. Identity is established by finding the nearest matching case, while searching the base with discretized global feature pattern obtained from a test signature. Authentication of the test signature is achieved by comparison with weighted central metrics obtained from feature sets and dynamic time warping values. Essentially median vectors and inter quartile ranges are calculated and preserved for the cases apriori to serve as authenticity indices. As part of an incremental upgradation scheme, a newly authenticated test signature automatically gets preserved in the base, either as an additional specimen, or by replacing the worst of the existing lot if it qualifies as a better one, thus improving the discerning power of the system. The proficiency of the classifier is assessed through accuracy measurements on two sets of data - one downloaded from a standard database [19] and the other collected by the researchers.
Video based Face Recognition using Image Processing Techniques

- Video-based facial recognition has received significant attention in recent years due to its widespread applications. The main challenges faced during face recognition has large variability of images due to pose variations, illumination conditions, facial expressions and image occlusion. Similarly surveillance and mobile cameras are of low cost devices which affects the video frames quality which results in severe motion blur, out-of-focus blur and large range pose variation. To achieve Face recognition from video image processing and machine learning techniques are used. The steps for processing involves Image acquisition, Image segmentation, feature extraction, classification and face detection. The features extracted are used in training the classifiers for images that are processed. Hence most recent algorithms developed give an idea of state of art of face recognition technology in video.
Exploiting the Core Academic Performance Prediction Parameters Using a Neuro-Fuzzy Model

: This work developed a Neuro-Fuzzy model as an intelligent computational framework to provide decision support for the admission of candidates into Higher Institutions. The traditional admission process is based on Unified Tertiary Matriculation Examination (UTME) and Post-Unified Tertiary Matriculation Examination (Post-UTME) scores, so long as the O-Level requirements are satisfied. This method has proven to have limitations. In this work, a five layer Adaptive Neuro-fuzzy Inference System (ANFIS) is modeled using a fuzzy logic input decision variables, taking into consideration the aggregate previous academic performances of the candidate and other related parameters that can influence academic performance. Historical records of students’ academic performances are used to build the fuzzy logic decision tree from which the initial fuzzy logic rules are extracted. The MATLAB NeuroFuzzy Designer is used for the modeling and training of the ANFIS model. Validation of the accuracy of the prediction using the affected student’s year 1, 2 , 3, 4 and 5 CGPAs, give the coefficients of multi determination to be approximately 0.96, 0.97 , 0.99, 0.98 and 0.96 respectively. These results show very high degree (97.2%) of accuracy, between the predicted and actual performance. These findings show that the developed model can be relied upon to make decisions on the admission of candidates into HAILs in any country of the world.
FAST Clustering Based Feature Subset Selection Algorithm for High Dimensional Data

— Data mining is the extraction of hidden predictive results from large databases. Feature selection is defined as process of selecting subset of relevant feature. The method for using a feature selection technique is that data may contain many redundant or irrelevant features. Of the many feature subset selection algorithms, some can effectively eliminate irrelevant features but fail to handle redundant features yet some of others can eliminate the irrelevant while taking care of the redundant features. Our proposed FAST algorithm falls into the second group. In early days, feature subset selection research has focused on searching for relevant features. This paper provides the implementation of this algorithm on high dimensional data.
Privacy Info Protection for a Video Using Frame Comparison Method in MATLAB Platform

: In today’s day to day life, a new method is required that can provide maximum security and authenticity to a video information. When information is transmitted over the networks, the chances of external attacks and noise interferences are more. So many techniques were introduced in the field of information protection. This paper gives more attention towards the video signals. We know that in every field of entertainment, videos are essential factor and sometimes it may contain highly confidential informations that shouldn’t get leaked . Not only in the entertainment fields, but also in the medical and military fields this method is applicable. This method involves the compression of videostream unlike other methods. The compression scheme used here is H.264/AVC compression, since it is the most advanced and is characterized by various features. Video compression techniques can reduce the volume of the file transmitted and stored . The proposed method involves mainly three steps; they are H.264/AVC encoding, data embedding and video extraction. The H.264/AVC coder is capable of performing the selective encryption of the videostream. Instead of encrypting the whole video information, some picture parameters are encrypted. This method can reduce the time required for encryption in comparison with other methods and still maintains the original picture quality.
Comparison of Two Predictive Scores for the Development of Incisional Hernia

Introduction: Incisional Hernia (IH) is a frequent complication of abdominal surgery, with an incidence of 10-23%, which can increase to 38% in specific risk groups. So far there is no ideal method to identify patients at high risk of developing IH, this variety in the criteria of inclusion of patients in different studies makes is very complicate to compare the results. The aim of this study is comparing the two predictive scores of incisional hernias (Hernia project Vs Van Ramshorst) with higher diagnostic performance and determine which is better to predict IH. Methods: An analytical, observational study was conducted between June and December 2018, in patients of both sexes, who were 18 years or older, undergoing midline laparotomy, regardless of their background diagnosis either urgently or scheduled between 2007 to 2016. The two different classifications, the Hernia Project score and Van Ramshorst score, were applied to each of the patients. With the identification of patients with hernia, two groups, healthy and ill, were performed and Bayesian statistics were made with it and to identify which scale best predicts the presence of this complication. Results: The records of 1085 patients undergoing midline laparotomy were reviewed. 296 patients were ruled out because their follow-up was not complete. Both tests were compared to determine the best diagnostic performance using the ROC curve and the area under the curve, finding that the Hernia Project Score has a larger area 0.724 compared to a 0.663 of Van Ramshorst. Discussion: In our patient cohort, the Hernia Project score has a greater predictive capacity, with an area under the best curve (0.72 vs. 0.66) however both They have a poor sensitivity and this is the main measure of the predictive capacity of any diagnostic test, so with these results, we can affirm that the Project hernia scale has a greater diagnostic capacity than the Van Ramshorst scale but still its diagnostic capacity is limited. Conclusions: Both scores have low sensitivity. We can affirm that the Hernia Project score has a greater diagnostic capacity than the Van Ramshorst score, but both have a limited diagnostic capacity.
Regular anisotropic filtering and multi-level thresholding for image segmentation

: In this article, we present a new image segmentation method, based on anisotropic filtering and multilevel thresholding . For segmentation, we proceed in two steps. In the first step, anisotropic filtering technique is used to filter the original image. In the second step, we identify the most significant peaks of the histogram. For this purpose, an optimal multi-level thresholding is used based on the two-stage Otsu optimization approach. The algorithm is demonstrated through the segmentation of textured images . The classification accuracy of the proposed method is evaluated and a comparative study versus existing techniques is presented. The experiments were conducted on an extensive set of gray level images. Satisfactory segmentation results have been obtained showing the effectiveness and superiority of the proposed method .
Development of a Domestic Device

253 Abstract—We used electrocardiography, electromyography, photoplethysmography, galvanic skin response, and skin temperature to analyze emotions in two participant groups. We presented emotionally triggering images (featuring happiness, sadness, fear, and disgust) to 23 male participants while simultaneously measuring neurophysiological signals. The average age of the participants was 22.91±2.15. Participants with HAM-D scores higher than 7 were considered to be depression-prone. Of the 23 participants, 5 had HAM-D scores higher than 7. We obtained 46 characteristic factors for the participants in the two groups, and subjected the data to a nonparametric Wilcoxon two-sample test. The resulting accuracy rate for the emotion “disgust” was the highest of the four emotions tested.
Appraisal Relationship between Service Quality and Customer Satisfaction in Organized Retailing at Bangalore City, India

The studies examine the dimensions and their levels of service quality that have significant effect on customer satisfaction in organized retailing. The results illustrated that the dimensions of service quality such as tangible, reliability, responsiveness, competence, credibility, accessibility, and customer knowledge were positively correlated to customer satisfaction in organized retailing. However, by using Statistic software SPSS 17.0 Version only four factors, namely, reliability, customer knowledge, credibility and tangible have significant effect on customer satisfaction that indicated to improve customer satisfaction. Therefore, the management of organized retailing is supposed to focus on reliability, customer knowledge, credibility and tangible to ahead of its competitors. Ultimately customers would remain loyal to an organization and this brings continued profitability and success in business in future. Keyword: Service quality, Customer satisfaction, Organized Retailing, Bangalore city
An Efficient Pre-Processing Method to Extract Blood Vessel, Optic Disc and Exudates from Retinal Images

Automatic detection of retinal feature is always been a challenging factor in the diagnosis and treatment of diabetic retinopathy. Most of the retinal images are of low contrast due to poor illumination during the acquisition process. Hence the feature extraction from unevenly illuminated retinal background is really a challenging task. Image preprocessing is preliminary step, which is most required to ensure high quality for further proceedings. This paper discusses the overview of existing preprocessing methods and presents performance of the proposed method. The principal component analysis (PCA) method is used to enhance the retinal image. The proposed method reduces noise and preserves edges from the retinal images and enhances low contrast images. An efficient preprocessing technique is tested on retinal images from various privately available databases using MATLAB software and the amount of accuracy rate is increased from the result obtained by the proposed method.
Transforming a Night Video into Day Video using Fusion and Color Enhancement

When a video is captured during nighttime or under dim light then it is difficult to monitor and identify the objects in that video. Hence enhancement of video surveillance system is needed for security purposes. The proposed method uses robust fuzzy C means clustering algorithm for fusion of night image with day reference image, and applies color transfer methods such as retinex with wavelet transform to get clarity of objects for human visual perception. The effectiveness of proposed method is shown with the practical results.