Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular Diagnosis of Pneumonia Using Multiplex Real-Time PCR Assay RespiFinder® SMART 22 FAST in a Group of Moroccan Infants

Background In Morocco, pediatric pneumonia remains a serious public health problem, as it constitutes the first cause of mortality due to infectious diseases. The etiological diagnosis of acute respiratory tract infections is difficult. Therefore, it is necessary to use Multiplex real-time polymerase chain reaction assay tests in a routine setting for exact and fast identification. Objectives In this paper, we present the clinical results of pediatric pneumonia and describe their etiology by using molecular diagnosis. Study design: Tracheal secretion was collected from infants presenting respiratory distress isolated or associated with systemic signs, attending the unit of Neonatology between December 1, 2016, and Mai 31, 2018. Samples were tested with the multiplex RespiFinder® SMART 22 FAST which potentially detects 18 viruses and 4 bacteria. Results Of the 86 infants considered in this study (mean age 31 ± 19 days) suspected of acute respiratory tract infections, 71 (83%) were positive for one or multiple viruses or/and bacteria. The majority of acute respiratory tract infections had a viral origin (95%): respiratory syncytial viruses (A and B) (49%), rhinovirus (21%), coronaviruses 229E (11%), humain metapneumovirus (5%), influenza A (3%), influenza H1N1 (1%), adenovirus (2%), and parainfluenza virus type 4 (2%). Among our patients, 6% had Mycoplasma pneumoniae. Coinfections were not associated with severe respiratory symptoms. Conclusion The clinical spectrum of respiratory infections is complex and often nonspecific. Thus, the early and fast detection of related causative agents is crucial. The use of multiplex real time polymerase chain reaction may help choose an accurate treatment, reduce the overall use of unnecessary antibiotics, preserve intestinal flora, and decrease nosocomial infection by reducing the length of hospitalization.
Depression, Anxiety, and Stress among Rural South Indian Women—Prevalence and Correlates: A Community-Based Study

Abstract Background The burden of common mental disorders (CMDs) which includes depression, anxiety, and stress-related disorders are on the rise in India. Women in rural areas form one of the high-risk groups with respect to CMDs due to their compromised status of living. Objective The aim of the study was to estimate the prevalence of depression, anxiety, and stress, and the predictors to depression among women in rural Puducherry. Methods A community-based, cross-sectional study was performed in 2016, among women aged 18 to 59 years, residing in the rural area of Puducherry. Prevalence of CMDs was determined using the Depression Anxiety Stress Scale (DASS)-21. Using a systematic random sampling method, women were interviewed in their houses. The socio-demographic characteristics along with risk factors for depression were captured using a semi-structured proforma. A multivariable logistic regression model was used to determine the predictors of depression. Results A total of 301 women were surveyed and their mean age (SD) was 34.9 (10.2) years. The prevalence of depression, anxiety, and stress was found to be 15% (95% CI: 11.3–19.3), 10.6% (95% CI: 7.5–14.5), and 5% (95% CI: 3–8), respectively. Multivariable analysis identified that lesser education and living separately/divorced to be significant predictors for depression in these women. Conclusion About one in six adult women living in a rural area was found to be depressed, which is considerably high. This emphasizes the need for screening among women for common mental disorders in primary care settings, especially in rural areas so that early diagnoses happen and thus reduce the impact due to mental disability.
A Comparative Study of Geometric Hopfield Network and Ant Colony Algorithm to Solve Travelling Salesperson Problem

The classical methods have limited scope in practical applications as some of them involve objective functions which are not continuous and/or differentiable. Evolutionary Computation is a subfield of artificial intelligence that involves combinatorial optimization problems. Travelling Salesperson Problem (TSP), which considered being a classic example for Combinatorial Optimization problem. It is said to be NP-Complete problem that cannot be solved conventionally particularly when number of cities increase. So Evolutionary techniques is the feasible solution to such problem. This paper explores an evolutionary technique: Geometric Hopfield Neural Network model to solve Travelling Salesperson Problem. Paper also achieves the results of Geometric TSP and compares the result with one of the existing widely used nature inspired heuristic approach Ant Colony Optimization Algorithms (ACA/ACO) to solve Travelling Salesperson Problem.
Multi Level PWM Switched Voltage Source Inverter

A Multilevel switched voltage source inverter is designed. It consists of three single-phase inverter modules and each module is composed of a switched voltage source and inverter switches. The major advantage is that the peak value of the phase output voltage is twice as high as that of the conventional neutralpoint-clamped PWM inverter. Thus, the proposed inverter is suitable for applications with low voltage sources such as batteries, fuel cells, or solar cells. Furthermore, three-level output waveforms of the inverter can be achieved without the switch voltage unbalance problem. Since the average neutral point potential of the inverter is zero, a common ground between the input stage and the output stage is possible. Therefore, it can be applied to a transformer less power conditioning system. The SVS inverter is verified by a PSIM simulation.
An Android based application to find misplaced phone (FIND IT)

: The proposed system will implement an android application which will help the users to find the phone misplaced in the vicinty. Nowadays, everyone is dependent on their mobile phones for almost everything and if the phone is misplaced for a while he/she becomes impatient. In addition to this if the phone is on silent mode, this worsens the problem. Using this application will help the user to find the phone without manually searching for it. Thus, saving time of the user. This application will work in two different modes viz. 1. Finding the phone with Voice Recognition. 2. Finding the phone with Message.
Identification of Diabetic Retinopathy from fundus images using CNNs

the Diabetic Retinopathy is the diabetes-mellitus to human vision that is the main cause of vision loss. The early stage detection of diabetic retinopathy is can play eminent role in the diabetes treatment. The fundus of retinal image is utilized to recognize the symptoms of diabetic retinopathy. Moreover, the above phenomena led us to propose this paper; here we propose segment based learning approach for identification of diabetic retinopathy. The segment based image level is required to obtain the identification of diabetic retinopathy images, the classifiers and features are equally learned from the data. Then, we adapt pre-trained CNN as the fine tune to achieve the segment level estimation of diabetic retinopathy. For identification of diabetic retinopathy, we achieve accuracy 96.97 and 98.46% at 20 and 30% and also achieve AUC (Area under Curve) 97.51 and 98.50 at 20 and 30% on the Kaggle dataset. Our proposed model outperforms much better than other models.
CARDIOMETABOLIC RISK: INDEPENDENT ROLE OF VISCERAL AND LIVER FAT

It is known that visceral adiposity is closely related to cardiometabolic abnormalities and visceral fat accumulation leads to drainage of free fatty acids (FFA) to liver via portal vein. This in turn leads to hepatic insulin resistance, increased intra-cellular triglyceride (TG) content, and increased synthesis and secretion of atherogenic lipoproteins. Studies have shown that only 15% of FFA delivered to the liver comes from visceral adipose tissue, while remainder comes from larger subcutaneous fat depot. It is also reported that subcutaneous fat has minimal association with cardiometabolic risks. Independent association of visceral fat and liver fat with cardiometabolic risks (CMR) is not yet clear. This review summarizes all available evidences obtained in clinical studies using computed tomography (CT) and magnetic resonance imaging (MRI) indicating independent association of visceral and liver fat with CMR. Currently, MRI is considered to be the „gold standard‟ technique for determining abdominal fat measures non-invasively. Observations from the studies using two different imaging techniques yields contradictory results by far; with MRI based studies showing liver fat to be stronger predictor of CMR than visceral fat as against the results from CT based studies. Further, the review highlights on the dearth of similar evidences with respect to Indian population considering ethnic differences in abdominal fat accumulation and concludes with the gap in existing research.
EFFECT OF WATER-BINDER RATIO AND NAOH MOLARITY ON THE PROPERTIES OF HIGH CALCIUM FLY ASH GEOPOLYMER MORTARS AT OUTDOOR CURING

In this article, strength development high calcium fly ash geopolymer mortar cured at ambient temperature was investigated. The outcome of HCFA fly ash geopolymer mortars on the flow ability and strength improvement of geopolymer mortars were predicted by an established statistical models using response surface methodology (RSM). The ambient cured geopolymer mortars were triggered with a solution of sodium hydroxide (NaOH) and sodium silicate. The investigation reveals that increase in alkaline solution to binder ratio reduces the compressive strength of the mortars and subsequently improves the workability. All the geopolymer mortars were able to achieve more than 15 N/mm 2 at an early age. At 28 days curing, the compressive strength of outdoor curing range between 30 to 70 N/mm 2 for all the mixes. All the models developed appeared to be significant with percentage error of less than 5%. The predicted and real data’s were found to be in good agreement. It Effect of Water-Binder Ratio and Naoh Molarity on the Properties of High Calcium Fly Ash Geopolymer Mortars at Outdoor Curing http://www.iaeme.com/IJCIET/index.asp 1340 editor@iaeme.com was also observed that the setting time of the designed geopolymer mortar increases at higher concentration of NaOH for both final and initial setting time. This makes high calcium fly ash suitable for repair and cast in situ applications as it exhibit enhanced early age strength growth in comparison with low calcium fly ash geopolymers.
Design of a Secure Computation Protocols for Distributed Association Rule Mining on Partitioned Data

In several applications, data mining play vital role in a distributed database scheme. In this scenario misuse of data may exist. But sometimes, data owners may be related to such misuse. Therefore, data owners do not require their data to be mined, because which contain sensitive information. Privacy preserving is for providing security of the data in the data mining schema. In this paper, an encryption and decryption protocols for secure distributed association rule mining is proposed. We applied commutative encryption and decryption for privacy preserving distributed mining of association rules. This protocol provides better security and better performance than existing once.
Impact of examined lymph node count on long-term survival of T1-2N0M0 double primary NSCLC patients after surgery: a SEER study

Purpose The relationship between examined lymph nodes (ELN) and survival has been confirmed in several single early-stage malignancies. We studied the association between the ELN count and the long-term survival of T1-2N0M0 double primary non-small cell lung cancer (DP-NSCLC) patients after surgery, based on the Surveillance, Epidemiology and End Results (SEER) database. Methods A total of 948 patients were identified and their independent prognostic factors were analyzed. These factors included the ELN count, which related to overall survival (OS) and the cancer-specific survival (CSS) of synchronous (n = 426) and metachronous (n = 522) T1-2N0M0 DP-NSCLC patients after surgery. Results X-tile analysis indicated that the cutoff value for the sum of ELNs was 22 for both OS and CSS in the synchronous DP-NSCLC group. Patients with a sum of ELNs >22 were statistically more likely to survive than those with ≤22 ELNs. X-tile analysis revealed that the ELN count of the second lesion was related to both OS and CSS in the metachronous DP-NSCLC group. The optimal cutoff value was nine. These results were confirmed using univariate and multivariate Cox regression analyses. Conclusion Our findings indicate that ELN count was highly correlated with the long-term survival of T1-2N0M0 double primary NSCLC patients after surgery.
Automatic Eigen Face Method

: Muzzle print recognition is the process of finding any muzzle in the image. It is a two-dimension procedure used for detecting muzzles and analyzing the information contained in the muzzle image. Here the muzzle images are projected to a feature space or face space to encode the variation between the known muzzle images. In this paper Principal Component Analysis (PCA) is used for dimension reduction and the projected feature space is formed using fuzzy algorithm. The above method can be used to recognize a new muzzle in unsupervised manner
COMPARISON OF FEATURE SELECTION METHODS FOR CHRONIC KIDNEY DATA SET USING DATA MINING CLASSIFICATION ANALYTICAL MODEL

---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract:- Medical Data Analysis is one of the applications of data mining that plays a vital role in human's lives. Data mining has become famous in healthcare management to predict, to detect or to find the hidden patterns and information in health data. In the healthcare commerce different kind of data mining approaches are used to mine the interesting pattern of diseases using the statistical medical data with the help of different machine learning techniques. The conventional disease diagnosis system uses the observation and knowledge of doctor without using the complex clinical data. The planned system assists doctor to predict sickness properly and also the prediction makes patients and medical insurance suppliers benefited. This paper implemented a feature model construction and comparative analysis for improving prediction accuracy of chronic kidney disease dataset in four phases. In first phase, Z-Score normalization algorithm is applied on the original kidney datasets collected from UCI repository. In the second phase of kidney dataset prediction, by the use of Step wise Regression Classification (SRC) Model and Built around the Random Forest Classification algorithm (BRFC) feature selection, subset (data) of Kidney dataset from whole normalized Kidney patient dataset is obtained which comprises only significant attributes. Third phase, classification algorithms are applied on the kidney data set. In the fourth phase, the accuracy will be calculated using Mean Absolute error (MAE), Root Mean square Error (RMSE), Relative Absolute Error(RAE), Root Relative Square Error(RRSE) and kappa values. MLP(Multilayer Perceptron Model) and SVM (Support Vector Model) classification algorithm is considered as the better performance algorithm after applying BRFC and SRC feature selection. Finally, the evaluation metrics can be calculated.
Design and Analysis of Efficient and Robust DWT based Image Steganography Technique

--The image steganography is known as a technique of hiding information in cover object such that the analysis of stego image doesn’t provides any clue of hidden data. The image steganography is not a new concept but the recent growth in the computer networks makes it live again because of large visual data sharing in computer networks and greater embedding capability than text and with a large number of compression formats which makes image suitable carrier for hidden data. In this paper we are designing and analyzing the Discrete Wavelet Transform (DWT) based technique. The DWT has its own advantage because of its matching with human visual perception which helps in deciding the embedding components that cannot be easily detected by a steganographic analysis or human vision. The paper analyzes this technique for different attacks, different block sizes and for different cover image to hidden image sizes.
Screening of H . pylori Positive Patients for the Potential Presence of Atrophic Gastritis through Studying the Gastric Panel and Anti-Helicobacter Antibodies

Abstract—Helicobacter pylori, is a gram-negative bacterium that colonizes the human stomach. Persistent H. pylori infection is associated with chronic gastritis, peptic ulcer disease, and in some cases atrophic gastritis, mucosa associated lymphoid tissue (MALT) lymphoma (MALToma), and gastric cancer. Several methods have been employed for the diagnosis of H. pylori infection, such as culture, determination of the presence of the microorganism in stained smears and in histological sections. The preformed urease test and PCR which require esophagogastroduodenoscopy to obtain fragments of gastric mucosa in spite of their sensitivity and specificity are not indicated for epidemiological surveys. The study was conducted to survey the acute and chronic infections with H. pylori and their potential association with atrophic gastritis by selecting eighty eight patients, who underwent upper gastrointestinal endoscopy. Patients were grouped according to the results of rapid urease detection kit as H. pylori positive group, n=44 and H. pylori negative group, n=44. Diagnostic markers were assayed for the detection of infection with H. pylori with the concomitant atrophic gastritis that are at higher risk for having gastric ulcers and cancer. These markers include anti-helicobacter IgM, IgG, Gastrin 17, Pepsinogen I, and Pepsinogen II. The mean of the patient’s age was 39.87+1.50 years with a range of 15-69 years and a mean of age of 38.34+1.98 was recorded for those who showed urease positivity while urease negativity associated with 41.41+2.25 mean of age. Males enrolled created 42% of all patients and control while females constituted the rest 58% of individuals recruited. Moreover, it was revealed that out of the 51 females enrolled, only 24 showed urease positivity while 27 were urease negative; on the contrary, males urease testing resulted in 20 and 17 positive and negative reactions, respectively. Thirty six urease negative individuals were reported as H. pylori IgG negative whereas 8 patients were equivocal while no case was recorded as positive for H. pylori IgG. Of the urease positive figures, 24 samples were reported as H. pylori IgG positive while the negative cases were 14 and 6 individuals showed equivocal reaction. Thirty seven urease positive individuals appeared as H. pylori IgM negative whereas 3 patients were positive while 4 cases showed equivocal reaction for H. pylori IgM. Of the urease negative group, 41 samples were reported
Design of Low Power Modified Wilson Current Mirror Based Level Shifter using Forced PMOS Method

Wide range level shifters are a fast energy efficient converter capable of converting low voltage to high voltage. Level Shifters are used to shift the voltage from one level to another level. Multi voltage system utilizes the advantage of level shifter. Multi voltage systems consist of low voltage as well as high voltage. Existing method was implemented by using LVT (Low Threshold Voltage Transistor) which produce the leakage power dissipation. Proposed method is implemented by using the Forced PMOS method to reduce the leakage power. Usually LS are inserted only while crossing low voltage domain to high voltage domain. In this paper modified Wilson current mirror based level shifter is designed by using stack technique. Measurement results were demonstrated using Mentor Graphics.
STEM CELL RESEARCH: A LATEST APPROACH IN RECENT ADVANCEMENTS

The present article is intended to discuss the importance of stem cells and their scientific research implications in treating disease with special emphasis to its future prospects. Stem cells are basic cells of all multicellular organisms having the potency to differentiate into wide range of adult cells. Self-renewal and totipotency are characteristic of stem cells. Though totipotency is shown by very early embryonic stem cells, the adult stem cells possess multipotency and differential plasticity that can be exploited for future generation of therapeutic options. Fortunately, the regulators of pleuripotency such as oct-4 & nanong protein are discovered and possibility of in vitro regulation of pleuripotency of stem cells is gaining strength. Genetic regulation of adult stem cells in the form of Bmi-1, Notch, sonic hedgehog & wnt gene is also being worked upon and future can be regulation of stem cell differentiation in vitro, in vivo or both. It is the knowledge of regulators of stem cells which has opened the therapeutic usage of stem cells in the form of neuron regeneration, treatment of bone defect, drug testing, gene therapy and cell based therapy in the form of muscle damage, spinal cord injury, cancer therapy etc. Cell based therapies might become commercial in coming years.
HERBAL APPROACHES FOR DIARRHOEA : A

Diarrhoea is the one of the most common cause of morbidity and mortality in many developing countries effecting mainly the infants and children’s. There are many synthetic drug treatments for diarrhoea like loperamide, bismuth subsalicylate and racecadotril. But these drugs have more side effects like nausea, abdominal discomfort, headache etc. Many herbal plants available which have anti-diarrhoeal activity with lesser side-effects than the conventional drugs. The review focuses on the various plants which have been proved for their anti-diarrhoeal activity in experimental animal models. This review also focused the invivo animal models such as castor oil induced diarrhoea, gastrointestinal motility test, magnesium sulphate induced diarrhoea and serotonin induced diarrhoea.
An Analytical Review of Web Page Recommendation System Based on Machine Learning

— Recommendation System (RS) are generally used in e-commerce industry to solve the complication of information overloading. Large amount of information is generating now, days due to which user face the difficulty in finding the relevant information of product and services matching to their taste and preferences. Data mining (DM) is the process of mining and extracting useful knowledge from large datasets. The tasks of DM are to do description and prediction of data to retrieve the information. RS is a subfield of information retrieval (IR) and IR is subfield of DM. Recommendation engines basically are data filtering and IR tool that make use of algorithms and data to recommend the most relevant item to particular user. The Various technique and approaches used by RS are content-based (CB) filtering, Collaborative Filtering (CF) and hybrid filtering techniques. This paper illustrates the role of Data Mining in Recommendation System and proposes a workflow of RS. Also describes the review of techniques, challenges of RS & compares recommendation systems of various e-commerce websites.
Data mining in social networking sites : A social media mining approach to generate effective business strategies

— Mining social media is a new plan to boom business. The Social media houses vast amount of user-generated data which can be used for data mining.Marketing enthusiasts are searching for means to utilize these mined business information for the intake of their sales/marketing and advertising teams. The mined information from social platforms can considerably impact business strategy of any business enterprise. In this paper we have attempted to quantify and classify such approaches by different authors. Further we suggest how this survey and study of the data mining approaches can benefit the understanding the importance of social media mining.