Miracle-dz/UniFAR-FTUs huggingface dataset:
RESOLUTION ENHANCEMENT OF SATELLITE IMAGES USING DUAL-TREE COMPLEX WAVELET AND CURVELET TRANSFORM

Resolution enhancement(RE) methods that are independent of wavelets i.e. interpolation methods leads to blurring as high frequency components are lost.RE scheme based on Discrete wavelet transform(DWT) leads to artifacts due to shift variant property. A complex wavelet-domain image resolution enhancement algorithm based on dual-tree complex wavelet transform (DT-CWT) with non local means(NLM) and curvelet transform is proposed. In this scheme, the low resolution image is undergone curvelet transform for denoising. The high frequency sub bands obtained by DT-CWT of the resultant denoised image are interpolated using Lanczos interpolator. The high frequency sub bands are further passed through an NLM filter to cater for the artifacts generated by DT-CWT.The low resolution input image and the filtered high frequency sub bands are combined using inverse DT-CWT to obtain a resolution-enhanced image. The quantitative peak signal-to-noise ratio (PSNR) and results are presented to reveal the superiority of the proposed technique through comparisons between state-of-the-art resolution enhancement methods.
Indigenous knowledge on the exploitation and utilization of medicinal plants by the Thengal Kachari tribe of Jorhat district, Assam, North-east India

The Thengal-Kacharis are one of the small ethnic communities belonging to the Indo-Mongoloid race with mythical ancestry. They are the present inhabitants of Jorhat, Golaghat, Dibrugarh, North-Lakhimpur, Dhemaji and Karbi Anglong district of Assam. The people of this community have thriving knowledge on common diseases as well their remedial therapies with the traditional use of different parts of natural herbals like roots, leaves and shoots etc. With the indigenous knowledge acquired, the Thengal-Kacharis are confident to treat patients suffering from different serious ailments. The present survey attempts to explore the application of some native medicinal plants traditionally used by the Thengal Kacharis to cure different ailments. The data generated in the study reports the ethno-medicinal properties of fifty nine different plants belonging to thirty eight different families the scientific knowledge on which would further help to lead phytochemicals and pharmacological research as well drug designing.
Impact of Traffic Heterogeneity on SEARCH Routing Algorithm for WSN

: Routing is an attractive area in wireless sensor networks for attempting to make it more efficient in terms of energy and other constraints imposed by revolutionary technologies. After emergence of Internet of Things, the new challenges also identified in which one of them are heterogeneity in terms of data rate (or traffic generation rate). Various kind of Heterogeneity like energy, link and computational was handled by many researchers but the consideration of data rate or heterogeneity was not attempted. This paper does an attempt to incorporate the traffic heterogeneity in existing routing algorithm SEARCH and studied its effect. The simulation results show that performance of an existing routing algorithm like SEARCH is affected and it is not able to handling traffic heterogeneity in a proper way.
Formulation and Evaluation of Bioerodible Bilayered Buccal Tablets Containing Atenolol

July September 2017 1170 JCPS Volume 10 Issue 3 Formulation and Evaluation of Bioerodible Bilayered Buccal Tablets Containing Atenolol Venkatalakshmi Ranganathan, Sasikala Chinnappan, Yajaman Sudhakar Faculty of Pharmacy, MAHSA University, Jalan SP 2/7, Bandar Saujana Putra, Jenjarom, Selangor, Malaysia-41200 School of Pharmacy, International medical University No.126, Jalan Jalil Perkasa 19, Bukit Jalil, 57000 Kuala Lumpur, Malaysia Department of Technical Education, S.V. Government Polytechnic, Tirupathi, Andhra PradeshIndia-517507 *Corresponding author: E-Mail: rvenkatmpharm@gmail.com, Mobile-0060163747705 ABSTRACT The oral mucosa has confirmed principally valuable and provides more advantages than other dosage forms such as: bypass of the GIT, improving the bioavailability of drug that has high first-pass metabolism, controlled drug delivery, ease of application and immediate withdrawal of delivery by detaching the system. The aim of the study was to formulate and evaluate buccal atenolol bilayered tablet for systemic delivery. The buccal tablets were designed by direct compression using ethyl cellulose and mucoadhesive polymers namely, Sodium alginate, Hydroxyl propyl cellulose and Methyl cellulose. All the formulations were studied to physicochemical evaluation such as hardness, thickness, friability, surface pH, swelling index and weight variation. The mean surface pH and ex-vivo residence time of the tablets was found to 6-7.1 and 6.7±0.99 to 7.00±2.1, which is favorable for oral mucosa. In-vitro drug release studies demonstrated that atenolol release from the selected tablets followed diffusion kinetics with a good drug release and it is confirmed that the tablet has the ability to deliver the drug. The present study indicates great potential of erodible mucoadhesive bilayered atenolol buccal tablet for systemic delivery of circumventing the hepatic first pass metabolism.
Identification and Classification of Bulk Fruits Images using Artificial Neural Networks

-This paper presents an identification and classification of different types of bulk fruit images using artificial neural networks. Schemes for visual classification usually proceed in two stages. First, features are extracted which represents the image and Second, a classifier is applied to the extracted features to reach a decision regarding the represented type of images. We have considered five different types of fruit images namely, Apple, Chickoo, Mango, Orange and Sweet lemon. The algorithms are developed to extract 18 color and 27 texture features. A Back Propagation Neural Network (BPNN) is used to classify and recognize the fruit image samples, using three different types of feature sets, viz, color, texture, combination of both color and texture features. The study reveals that the combination of color and texture features are out performed the individual color and texture features in identification and classification of different bulk fruit image samples.
Factors Predicting Response to Neoadjuvant Therapy of Hepatic Metastasis from Colorectal Carcinoma

C l i n M e d International Library Citation: Cortés Guiral D, Fernández-Aceñero MJ, García-Olmo D, Pastor Idoate (2015) Factors Predicting Response to Neoadjuvant Therapy of Hepatic Metastasis from Colorectal Carcinoma. Int J Pathol Clin Res 1:009 Received: August 14, 2015: Accepted: August 31, 2015: Published: September 03, 2015 Copyright: © 2015 Guiral DC. 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. Guiral et al. Int J Pathol Clin Res 2015, 1:1 ISSN: 2469-5807
Characterization and Retrogradation of Maize Starch by Asymmetrical Flow Field Flow Fractionation

In this work, the capacity of AF4 coupled with multiangle light scattering (MALS) and differential refractive index (dRI) detectors to monitor the maize starch retrogradation behavior in situ was investigated. AF4 provides separation of starch molecular based on their hydrodynamic sizes, and MALS-dRI yields the molar mass and the radius of gyration. The two key operation conditions of AF4 analysis (i.e. injection amount and cross flow rate) were optimized. Under optimization operation conditions of AF4 analysis, the effect of storage conditions (i.e. storage time and storage temperature) on maize starch retrogradation was studied by AF4-MALS-dRI. The results reveal that AF4-MALS-dRI seems to be a useful tool for the better understanding of starch retrogradation mechanism.
Illness Perception and Coping among Hypertension Patients

This study examined the illness perception and coping among the hypertension patients. The purpose of the study was to understand how hypertension patients perceive their problem of illness and how they cope with it. The Study was carried out in Bhopal and Lalitpur District with hypertension patients aged between 26 and 75 years. Finding revealed that patients suffering from hypertension have different degrees of perception for different aspects of illness and the differences in the frequencies of various coping behavior. The correlation between illness perception and coping behavior of patients suffering from hypertension.
Investigation of angular error during taper cutting in Inconel 718 using WEDM process

The current research work presents the effect of process parameters on angular error during taper cutting using WEDM process. Taper cutting is an unique operation of WEDM process, which provides an effective way for machining conductive, high strength and temperature resistant materials and has the capability to produce components with complex features and curved surfaces. During this process the wire is subject to deformation, which creates deviation in the inclination angle of the machined part. As a result, the machined part loses its precision. In this paper, the effect of process parameters on angular error (AE) in WEDM taper cutting is presented. Taguchi L27 orthogonal array is used to gather information regarding the process with less number of experimental runs. The contribution of each process parameters towards the Angular error is identified. Analysis of Variance (ANOVA) is also conducted to determine the statistical significance of process parameters during taper cutting in WEDM process. Key Words— WEDM, Angular Error, Taper Cutting, Inconel 718. ——————————  ——————————
Investigation of Digestion kinetics and gas production of fat coated protein sources using in vitro gas production technique

An in vitro rumen gas production (GP) technique was utilized to evaluate fish and soybean meal coated with different types of fat for total gas production and digestion kinetics. About 200 mg of sample was weighed and inserted in glass syringes, then mixed with the inoculum and artificial saliva, incubated at 39°C in a ventilated oven and GP was recorded after zero to 96 h of incubation. There were differences among different fat coated proteins and uncoated control treatment in total GP during incubation, and the treatments differed (P<0.05) in rate and potential of gas production. The result of the present study showed that experimental fats which mixed with fish and soybean meal resulted in significant reduction in GP (P<0.05). Furthermore, the values of b and a+b reduced significantly since these supplemental proteins coated with both types of fat in comparison to uncoated treatments (P<0.05). Consequently, one of the possible approach is to reduce total GP from dairy cattle is coating some portions of dairy cow dietary concentrate (non-fibrous and high in protein or starch content) with supplemental fats in the form of long chain free fatty acids, particularly in high concentrate feeding feedlot cattle or dairy cattle.
Chemical composition of cold‐pressed blackberry seed flour extract and its potential health‐beneficial properties

Abstract The blackberry seed flour was cold‐extracted using 50% acetone and examined for its phytochemical composition and health‐beneficial properties including in vitro gut microbiota modulatory, free radical scavenging, anti‐inflammatory, and antiproliferative capacities. Among identified thirteen components of blackberry seed flour extract through UHPLC‐MS analysis, sanguiin H6 was the primary component and followed by ellagic acid and pedunculagin. For health‐beneficial properties, the blackberry seed flour extract increased the total number of gut bacteria and shifted the abundance of specific bacterial phylum, family, or genus. The extract had RDSC, ORAC, HOSC, and ABTS•+ scavenging capacities of 362, 304, 2,531, and 267 μmol Trolox equivalents (TE)/g, respectively. In addition, the blackberry seed flour extract showed capacities for anti‐inflammation and antiproliferation by suppressing LPS induced IL‐1β mRNA expressions in the cultured J774A.1 mouse macrophages and the proliferation of LNCaP prostate cancer cells. The results suggest potential health benefits and further utilization of blackberry seed flour as functional foods.
AIEFS and HEC based emotion estimation using physiological measurements for the children with autism spectrum disorder.

The emotion of the children with Autism Spectrum Disorder (ASD) cannot be identified and recognized easily. The research in automated emotion recognition methods is steadily growing thrust in the last few years due to applicability in various domains which would benefit from a clear understanding of human emotional states. The studies have shown that a human’s physiological parameters are directly related to his/her psychological reaction from which the emotions can be estimated. There is a strong relationship between human emotion and physiological signals. The major aim of this work is to identify preferable Artificial Intelligent Ensemble Feature Selection (AIEFS) framework and Heterogeneous Ensemble Classification (HEC) model for such a concept. The experiment was necessary to achieve the uniformity in the various aspects of emotion elicitation, data processing, feature selection using EFS, and estimation evaluation using HEC and in order to avoid inconsistency problems. Here, three base classifiers such as Support Vector Regression with Genetic Algorithm (SVR-GA), Multinomial NaiveBayes (MNB) and Ensemble Online Sequential Extreme Learning Machine (EOS-ELM) that learn different aspects of the emotion dataset samples are used together to make collective decisions in order to enhance performance of health-related message classification. The results indicate that the combination of AIEFS with HEC exhibited the highest accuracy in discrete emotion classification based on physiological features calculated from the parameters like ECG, respiration, skin conductance and skin temperature. Specific discrete emotions were targeted with stimuli from the IAPS database. This work presents experiment based comparative study of four feature selection methods and five machine learning methods commonly used for emotion estimation based on physiological signals.
Analyzing User Behaviour of IPTV using Hidden Markov Model

Due to the innovative technologies in telecom industry and Internet Protocol TV (IPTV) became a reality. Many service providers across the globe are investing significantly to render Video on Demand (VoD) and other services through IPTV. Videos consume high bandwidth and they are to be multicast with acceptable service quality. Therefore it is indispensable for service providers to understand technicalities of IPTV and make necessary steps to have compatible infrastructure. Moreover IPTV user behaviour will have significant impact on the services rendered by the providers. Optimization of resources and services is possible provided the trends in the customer behaviour. As users of IPTV can have interactive usage of content delivered, their usage behaviour and events can affect quality of services. In this context, it is essential to characterize customer behaviour and analyze the same to have insights that can help service providers to have strategies to improve business by providing quality services to subscribers. In this paper our focus is on the usage behaviour of IPTV users besides their zapping patterns. We employed a stochastic model known as Hidden Markov Model (HMM) which has finite set of states and probability of state transmissions. Besides HMM has hidden states that capture user behaviour with respect to IPTV. The results of our research revealed the behaviour of users at different times and especially zapping rate. Index Terms – IPTV, user behaviour analysis, hidden Markov model, channel zapping ——————————  ——————————
CONTRIBUTION OF THE MANUFACTURING SECTOR IN THE AGG REGATE NSDP FOR EACH MAJOR INDIAN STATE: A STUDY OF ITS DISTRIBUTION PATTERN AND VARIABILITY

This study assesses the quantum of disparities in t he manufacturing sector among the seventeen major I ndian states by studying the distribution of the Net Stat e Domestic Product of the manufacturing sector of e ach state in the aggregate NSDP for the prereform period (1973-74 to 1991-92) and the postreform period (1992-93 to 2013-14). ‘Independent samples ttest’ has been employed to study whether or not there exists a statistically s ignificant difference in the average shares of manufacturing sector’s NSDP a cross the two time periods under study. The statist ical ool of quartile deviation has been used to analyse the ext nt of variability in the shares of manufacturing s ector’ NSDP for each major Indian state. The maximum increase in the ave rage share of manufacturing sector’s NSDP from the pre reform to the post reform period has been recorded by Himacha l Pr desh followed by Bihar, the results of both be ing statistically significant at 1% level. The analysis further revea led the presence of maximum variability in the shar e of the manufacturing sector in the aggregate NSDP as depic t d by quartile deviation for the state of Odisha b oth in the pre-reform period and the post reform period, where as the lowest variability in the pre-reform period has been witnessed for Himachal Pradesh and in the post reform period f r West Bengal.
Isolation of Plant Hormone (Indole-3-Acetic Acid) Producing Rhizobacteria and Study on their Effects on Tomato (Lycopersicum esculentum) Seedling

Twenty one rhizobacteria were isolated from rhizospheric soils of Uttarakhand Tarai region. The isolated soil bacteria were screened for the production of indole acetic acid, phosphate solubilisation and siderophore production. Out of 21 isolates, 3 isolates (P3, P9, and P19) were screened for indole-3-acetic acid (IAA) production that are Gram negative, catalase positive and starch hydrolysis positive. Isolate P19 was the best IAA producer strain (50.25μg/ml) while isolate P3 was lowest IAA producer (15.25μg/ml) comparatively. All three isolates showed siderophore production while phosphate solubilisation was shown by only P19 isolate. All the three isolate showed nitrogen fixing activity in G-NFMM media. Effect of IAA producing PGPR alone and in different combinations was studied on seed germination of tomato plant. Treatment with PGPR isolates in combination of P3+P9+P19 on tomato seedling showed maximum shoot length (8.6cm), root length (3.0cm), shoot fresh weight (0.104g), root fresh weight (0.005g), fresh plant weight (0.109g) and dry plant weight (0.018g) as compared to control and other PGPR combinations. The consortia of three isolated bacterial strains showed significant effects on seed germination rate. Production of indole acetic acid (IAA) and siderophore was also observed by isolated strains. Thus, the use of combination of PGPR isolates is advocated for excellent growth performance of plants.
On the Use of Edge Features and Exponential Decaying Number of Nodes in the Hidden Layers for Handwritten Signature Recognition

Handwritten signatures are playing an important role in finance, banking and education and more because it is considered the “seal of approval” and remains the most preferred means of authentication. In this paper, an offline handwritten signature authentication algorithm is proposed using the edge features and deep feedforward neural network (DFNN). The number of hidden layers in DFNN is configured to be at least one layer and more. In this paper, an exponential decaying number of nodes in the hidden layers was proposed to achieve better recognition rate with reasonable training time. Of the six edge algorithms evaluated, Roberts operator and Canny edge detectors were found to produce better recognition rate. Results showed that the proposed exponential decaying number of nodes in the hidden layers outperform other structure. However, more training data was required so that the proposed DFNN structure could have more efficient learning.
Neural network generation for estimation of tissue optical properties

Monte Carlo Simulations (MCSs) allow for the estimation of photon propagation through media given knowledge of the geometry and optical properties. Previous research has demonstrated that the inverse of this problem may be solved as well, where neural networks trained on photon distributions can be used to estimate refractive index, scattering and absorption coefficients. To extend this work, time-dependent MCSs are used to generate data sets of photon propagation through various media. These simulations were treated as stacks of 2D images in time and used to train convolutional networks to estimate tissue parameters. To find potential features that drive network performance on this task, networks were randomly generated. Generated networks were then trained. The networks were validated using 4-fold cross validation. The consistently performing top 10 networks typically had an emphasis on convolutional chains and convolutional chains ending in max pooling.
Update Breast Cancer 2020 Part 1 – Early Breast Cancer: Consolidation of Knowledge About Known Therapies

This review is intended to present the latest developments in the prevention and treatment of early breast cancer. The risk of breast cancer can be increasingly better characterised with large epidemiological studies on genetic and non-genetic risk factors. Through new analyses, the evidence for high-penetrance genes as well as for low-penetrance genes was able to be improved. New data on denosumab and atezolizumab are available in the neoadjuvant situation as is a pooled appraisal of numerous studies on capecitabine in the curative situation. There is also an update to the overall survival data of pertuzumab in the adjuvant situation with a longer follow-up observation period. Finally, digital medicine is steadily finding its way into science. A recently conducted study on automated breast cancer detection using artificial intelligence establishes the basis for a future review in clinical studies.
Experiences in the use of misoprostol in the management of first trimester missed abortion in a low resource setting

Background: The use of misoprostol in the management of first trimester abortion is an evolving clinical practice in most parts of sub-Saharan Africa. Objective: To determine the effectiveness and acceptability of misoprostol in the evacuation of the uterus in first trimester missed abortion. Study Design: This was a non-randomized trial. Setting: This study was conducted in the Gynecologic Unit, Abubakar Tafawa Balewa University Teaching Hospital Bauchi, Nigeria. Materials and Methods: Consented consecutive patients with first trimester missed abortion were recruited in the study. Each patient was given sublingual misoprostol 600 µg to be repeated after 6 hours if abortion process was not initiated. They were followed-up after two weeks and offered contraceptive counseling. However, if active vaginal bleeding persisted, patients were reviewed after 1 week, scanned and offered surgical evacuation (manual vacuum aspiration) on confirmation of residual products of conception. Telephone review was conducted for patients who defaulted follow-up. Data were analyzed using the Statistical Package for the Social Sciences version 16. P value was considered significant at a < 0.05 at 95% CI. Results: Sixty-one patients with missed abortion were managed between 1 st January and December 2013 with a mean age, parity and gestational age of 27.6 ± 5.6 years, 3.6 ± 2.3 and 7.6 ± 2.0 weeks, respectively. Fifty-six patients (92%) achieved complete evacuation. Mean interval between the first dose of misoprostol and abortion was 5.1 ± 2.2 hours and mean duration of vaginal bleeding was 5.9 ± 1.6 days (range: 3-14 days). Side effects were minor mainly nausea/vomiting, and all the patients with complete evacuation showed satisfaction with the method and preferred it to surgical evacuation. Conclusion: Misoprostol is very effective in the management of first trimester missed abortion in our setting and should be the treatment method of first choice.