Miracle-dz/UniFAR-FTUs huggingface dataset:
Maintaining Bone Health and Integrity During Androgen-deprivation Therapy for Prostate Cancer

Since the early 1990s, earlier diagnosis and improved treatment options have caused a steady decline in the prostate cancer mortality rate. Consequently, many of the 186,000 men in the US who will be diagnosed with prostate cancer in 2008 may live for many years with the disease and any long-term treatment-related adverse effects (AEs). Androgen-deprivation therapy (ADT) has become an accepted standard of care for prostate cancer treatment and its use is recommended in various stages of the disease. However, ADT is not without AEs, some of which may have long-term consequences. Of particular concern is the increased risk for fracture associated with ADT, especially in patients treated for many years. Clinicians who treat prostate cancer patients should be aware of the potential AEs associated with ADT and of strategies for preventing and/or treating them. This article reviews the prevalence and consequences of bone loss and fractures in men with prostate cancer and without bone metastases receiving ADT, and discusses prevention and treatment strategies.
Prediction of difficulties during laparoscopic cholecystectomy by preoperative clinical examination and ultrasonography

Background: Cholelithiasis (gall stone disease) is a well-known disease worldwide. Ultrasonography is the most common screening test for cholecystitis and cholelithiasis. Laparoscopic Cholecystectomy is considered the treatment of choice for symptomatic gall stone disease. It is important to know the different clinical, radiological parameter and specific predictor that give some prediction of difficult LC. The aim of this study was to predict the difficulty of LC and the possibility of conversion to OC before surgery using the clinical and ultrasonographic criteria in our set up. Methods: The present study was carried out in the Department of surgery, Sarojini Naidu Medical College Agra, from November 2014 to October 2016. A total of 210 patients were enrolled for the laparoscopic cholecystectomy. All patients who were included in the study were undergone detailed history and clinical examination. A number of clinical and ultrasonographical parameters were noted. Results: Amongst the 210 patients admitted for laparoscopic cholecystectomy, 21 (10%) were male and 189 (90%) female, with age ranging from 12–60 years. The conversion rate in our study was 4.5% (9 of 210). In our study significant pre-operative factors which increased the conversion rate to open cholecystectomy includes male gender, obesity, abdominal scar of previous surgery, contracted and thickened gall bladder and patients having stone impacted at the neck of gall bladder. Conclusions: From this study, we conclude that preoperative ultrasonography is a good predictor of difficult laparoscopic cholecystectomy in the majority of cases and should be used as a screening procedure.
Anonymous Authentication of Data Stored on Distributed Cloud

: Authors propose an anonymous authentication for secure data storage in clouds for different departmental activities of an institute. In this scheme, the cloud verifies the authenticity of the user without knowing the users identity before storing data, also has the feature of access control in which only valid users are able to decrypt the stored information. Along with access control user revocation is also done that is existing user can be removed and cannot further access the data stored in cloud. The cloud storage is distributed. The cloud storage can distributed according to the requirement of the organization. System is very useful for sending messages anonymously. But only authorized user can do so i.e. anonymous but valid user only can send messages. This makes cloud computing a more secure approach. The scheme also gives the feature of text filtration which eliminates the meaningless words to optimize cloud storage. Moreover, our scheme gives the feedback policy needed for the performance improvement with different parameters anonymously. The main focus is on anonymous authentication so that one can give valid feedback, complains without revealing once identity. Authors aim to promote paperless work by means of e-notices. This approach can prove helpful for government and non-government organizations.
Event Related Potentials: Significant Lobe Areas and Wave Forms for Picture Visual Stimulus

— Brain Computer Interfaces (BCIs) are direct interfaces for communication between the brain and computer. Even Related Potentials (ERPs) are a very important sub area of Brain Computer Interfaces which illustrate electrical potentials associated with auditory, sensory, motor or cognitive events. This is an emerging area that can be used to provide better solutions for disabled people, diagnose diseases, credibility assessments, virtual reality, robotic movements and so on. For this research, Electroencephalogram (EEG)- based Event Related Potentials on picture visual stimulus data set have been used for a single subject. Then pre-processing techniques were applied such as epoching, averaging, and artifact removing. Pre-processed signals were decomposed to obtain independent components using Independent Component Analysis (ICA) and noisy and artifactural components were removed. The processed dataset was used to identify most significant lobe areas, wave types and the influence of the P300 wave for picture visual stimulus by using EEGLAB. The result indicates that the most significant lobe areas responsible for picture visual stimulus are parietal lobe & occipital lobe. P5 is the best wave form to detect picture-based visual stimulus and P3 is mostly responded with Alpha frequency band and N4 is mostly responded with Beta frequency band.
Identity-Based Distributed Provable Data Possession in Multicloud Storage

Remote data integrity checking is of crucial importance in cloud storage. It can make the clients verify whether their outsourced data is kept intact without downloading the whole data. In some application scenarios, the clients have to store their data on multicloud servers. At the same time, the integrity checking protocol must be efficient in order to save the verifier's cost. From the two points, we propose a novel remote data integrity checking model: ID-DPDP (identity-based distributed provable data possession) in multicloud storage. The formal system model and security model are given. Based on the bilinear pairings, a concrete ID-DPDP protocol is designed. The proposed ID-DPDP protocol is provably secure under the hardness assumption of the standard CDH (computational Diffie-Hellman) problem. In addition to the structural advantage of elimination of certificate management, our ID-DPDP protocol is also efficient and flexible. Based on the client's authorization, the proposed ID-DPDP protocol can realize private verification, delegated verification, and public verification.
Review and study paper on wireless sensor network and few advancements

In this paper, the author aims at describing a wireless sensor network. Wireless sensor network consisting of spatially distributed autonomous devices using the sensor to monitor physical or environmental conditions. The wireless sensor network can be used in wide range of applications including environmental monitoring, habitat monitoring, various military applications, smart home technologies and agriculture. Wireless sensor networks constitute one of the promising application areas of the recently developed wireless sensor networking techniques. Various clustering Schemes have been discussed and employed in both homogenous and heterogeneous wireless sensor network.
Sugarcane Disease Detection Using Data Mining Techniques

— Leaf diseases may lead to severe loss in agricultural yields. To improve agricultural yields the identification and classification of leaf disease is essential. The Sugarcane leaf diseases can be manually identified by the disease syndrome based on the experience. In this process, mostly a misguidance of plant leaf disease symptoms may be identified. Hence, in this paper we propose an accurate and automated process of leaf disease identification. The R Datasets are used to perform experimental study. Techniques like Multilayer perceptron (MLP), J48 pruned trees and clustering algorithm like k-means are used for predicting sugarcane leaf diseases by using Weka tool and shown its potential results.
Path Optimization of Tube Sheet Welding Robot based on improved Genetic Algorithm

: To improve the efficiency of robot tube sheet welding, an effective genetic algorithm is proposed to solve the path optimization problem which can be summarized as a traveling salesman problem. The initial population is constructed by natural number encoding, and the fitness function is established by the quality of arc welding path of the torch. The partially mapped crossover (PMX), 2-opt mutation and elite selection operator are applied to evolve the individuals. Calculation results show that the proposed algorithm is better than the basic genetic algorithm, the machining path of robot tube sheet welding is shorten and the efficiency is improved.
Enhancing Performance in Terms Of Energy Consumption of Cluster Based Protocol by the use of Priority Queue

:- The multi channel TCP communication utilized channel estimation in order to transfer the received packets towards destination node. As more and more packets collected at cluster head, congestion takes place causing packet drop. Packet drop ratio subsequently decreases lifetime of network and energy consumption due to packet aggregation increases. The proposed literature tackle problem of packet drop with priority Queue. Packets are assigned with priority and in case of congestion packets with least priority are blocked. By doing so aggregate energy along with packet drop ratio subsequently decreases. Simulation is conducted in MATLAB. The performance analysis indicate enhancement by 22%.
THE IMPACT OF PALM POLLEN AND GINKGO BILOBA SUPPLEMENTATION ON PRODUCTIVE PERFORMANCE, BIOCHEMICAL PARAMETERS AND IMMUNE RESPONSE OF BROILERS

This study was conducted to evaluate the effects of palm pollen and Gingko Biloba as feed additives, on productive performance, biochemical parameters and immune response of broiler chickens. A total of 210 one day-old chicks of Ross 308 hybrid were divided into 3 groups, (each n=70). First group (Control group), the chicks were fed on basal diet(C), second group (P), were fed on the same diet enriched with 0.5 % palm pollen, third group (G), were fed on the same diet enriched with 0.5 % Gingko Biloba (GB). During 45 days of the experimental period, the broiler performance including feed intake and body weight gain, final body weight, feed conversion ratio (FCR), carcass weight, thigh and breast weight , liver weight, biochemical parameters and antibodies titer for Newcastle and Infectious Bursal diseases vaccines were measured. Significant differences were observed between different treatments and control, at the end of the experiment (45 days), the highest body weight gain was recorded by (P) Palm Pollen enriched group (2345.45±190 g) followed by (C) control group (2170±277g) then came (G) Ginkgo Biloba (1927.27±98.4g). The impact on FCR followed the same order of live body weight. Better biochemical and immune responses were recorded in both treated groups than control one. The carcass yields were found that, thigh weight higher in P followed by C then G, while breast were higher in treated groups. From the results of this experiment, it can be concluded that addition of palm pollen to broiler diets significantly improved the body weight gain and feed conversion indices all over the period of raising while, Ginkgo Bioloba improved immune response and biochemical parameters of broilers. Finally, we could recommended the use of palm pollen as growth promoters and immune enhancer and Ginkgo Biloba as immune enhancer only, at feeding practices.
Single-criteria Collaborative Filter Implementation using Apache Mahout in Big data

— In everyday life recommendation system plays an important role and collaborative filtering (CF) is used widely in many e-commerce applicationsfor online product recommendation. A recommender system is mainly used for better predictions as better decision making by using preferences during searching, shopping etc. The preferences of other users, user's past preferences and big data is the driving force behind Recommendation systems. In this paper, we present collaborative filter types and their main challenges. Using the open source library Apache Mahout, we implemented collaborative filter using single-criteria to recommend items to particular users. Also, we showed the flow of Apache Mahout command’s execution to process the huge data using LogLikelihood similarity algorithm in big data scenario.
A Secure Scalable and Efficient Access Control Using Public Verifiable Schema in Cloud Computing

: Several data hiding methods have been recently proposed which can provide the security by hiding the data. Integrity of the data is having risk in the cloud. The Cloud Server (CS) could plan to hide the data, when data loss caused by server hacks or failures to keep up reputation. The randomization is predictable to increase the security of the system and also increase the capacity. One of the good cryptographic solutions to this problem is Cipher text Attribute Based Encryption (CP-ABE). Key technology is one of the significant factors in information sharing. In proposed system by applying encryption the information system presents an additional challenge with regard to the user revocation. Dynamic revocation of cipher policy attribute based encryption mechanism is potential to eliminate access from users without delivering new keys to other users. In this proposed system users individually request the owner to add, update, and modify or remove the value of one attribute freely without knowledge of other attribute.
Examining Utilitarian and Hedonic Motivations in Online Shopping in India : Moderating Effect of Product Browsing Behavior

117 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number: A10220581C219/19©BEIESP ABSTRACT--Abstract: This study examined the connections between utilitarian as well as hedonic motives, leading to actual shopping intention. This investigation tried to build up an association of motives and was carried out to understand the role of product browsing behavior as a moderator in intention development towards online shopping. It explored an immediate connection between actual shopping intention and utilitarian motivations, and a partial association between intention and hedonic motivations. The outcomes show utilitarian motivations are not moderated by product browsing behavior of consumers.Whereas, hedonic motivations have a moderating impact of product browsing behavior. The study findings can be useful to marketers, policymakers and academic researchers to gain insights into the unexplored constructs related to online shopping in Indian context.
REVIEW OF COMPARATIVE STUDY OF KQML AND FIPA ACL

An agent is an autonomous software entity that has the ability to do its job on behalf of others. A new paradigm in intelligent system research focuses on the enhancement of a new era of intelligent-based communication technique, which can develop the enormous amounts of formally precise information obtainable on the system, to fabricate novel intelligent functionalities. KQML is a high-level, message-oriented communication language and protocol for information exchange independent of content syntax and applicable ontology. KQML and FIPA ACL are almost identical with respect to syntax, basic concepts and the principles they observe. But differ primarily in the details of their semantic frameworks. KQML includes preconditions, postconditions and completion conditions in semantic description but FIPA-ACL includes feasibility precondition and rational effect. This paper gives a comparative analysis of key parameters of both languages KQML and FIPA ACL on the basis of their foundation and functionality between intelligent agents.
Leveling: an Efficient VLC for Lossless Data Compression

Many of the standard compression methods are based, at their lowest level, in coding digital words of variable length or VLC, Huffman type, designed in 1952 or in any of its versions, as canonical. This article presents an VLC with greater efficiency than Huffman encoding, named as “Leveling”, which uses two variants, “Leveled Reordering” for low redundancy, e
Semi Supervised Text Classification with Universum

-Semi-Supervised learning is a special form of classification. Traditional classifiers use only labelled data (feature / label pairs) to train. Labelled instances however are often difficult, expensive, or time consuming to obtain, as they require the efforts of experienced human annotators. Meanwhile unlabelled data may be relatively easy to collect, but there has been few ways to use them. We use unlabelled (random) data for categorization. Labelled data are hard to obtain while unlabelled data are abundant, therefore semi-supervised learning is a good idea to reduce human labour and improve accuracy. Semi-supervised learning addresses this problem by using large amount of unlabelled data, together with the labelled data, to build better classifiers. Because semi-supervised learning requires less human effort and gives higher accuracy, it is of great interest both in theory and in practice. Universum, a collection of non-examples that do not belong to any class of interest, has become a new research topic in machine learning. Text categorization does not exist then the huge data cannot be classified.The most of the existing systems in the market to do are Ada boost technique, naïve bayes, support vector machine, neural network, Particle Swaram Optimization (PSO),etc. Fuzzy ANN and Bayesian probability algorithm are the process of semi-supervised text categorization and which results best compared to the existing techniques and are encouraging. Methodologies used in the system are Shannon info-gain , TF-IDF, K-means , Gaussian distribution , Fuzzy ANN , Bayesian probability , Atkinson index. Finally, the experiments use Reuters data set with several combinations. Experimental results indicate that the proposed algorithm can benefit from Universum examples and outperform several alternative methods, particularly when insufficient labeled examples are available. When the number of labeled examples is insufficient to estimate the parameters of classification functions, the Universum can be used to approximate the prior distribution of the classification functions. The experimental results can be explained using the concept of Universum introduced by Vapnik, that is, Universum examples implicitly specify a prior distribution on the set of classification functions. The key advantages of the proposed semi-supervised learning approach are: (a) performance improvement of any supervised learning algorithm with a multitude of unlabelled data, (b) efficient computation by the iterative boosting algorithm, and (c) exploiting both manifold and cluster assumption in training classification model.
Physiological and histological effects of alcoholic and aqueous extract of Nigella sativa seed on fertility potential in male mice

The aim of this study is to investigate the effect of alcoholic and aqueous extracts of Nigella sativa seeds on the reproductive values, some sexual hormones level and histological change of treated and normal male mice at one spermatogenesis cycle (five weeks). Sixty albino Swiss male mice were used as animal model, they divided into six groups equally, and 1st group served as control group, the 2 group was treated orally with 150 mg/kg. B.w. of aqueous extract of Nigella sativa seeds, the 3 group treated with alcoholic extract 150 mg/kg. B.w. The 4 group was treated with 100 mg\Kg of CCl4 and the 5 th group treated with CCl4 (100 mg\Kg) and aqueous extract (150 mg/kg. B.w), finally 6 group treated with CCl4 (100 mg\Kg) and alcoholic extract (150 mg/kg. B.w). The parameters were determined, sperm characteristic (sperm concentration, motility, viability and abnormal sperm) levels of testosterone, FSH and LH hormones and histopathological study. The results of the present study showed that the treatment with CCl4 caused a significant decrease (P>0.05) in the sperm concentration, motility and increase the dead sperm and abnormalities. The results showed significant (P< 0.05) increases in sperm concentration, motility and decrease in dead and abnormal sperm in groups treated with aqueous and alcoholic extract of Nigella sativa. The animals treated with aqueous and alcoholic extract combination with CCl4 showed improvement in sperm concentration and motility compared to group treated with CCl4. The FSH, LH and testosterone significant (P< 0.05) increased in treated groups with aqueous and alcoholic extract of plant compared to group treated with CCl4 and improvement in group treated with aqueous and alcoholic extract combination with CCl4. The histopathological sections of testis of treated mice with CCl4 showed sever changes in testicular architecture. This was attributed to the cytotoxic activity of CCl4. CCl4 exposure induced histopathological changes in the testis including morphological alterations of the seminiferous tubules. Seeds extract have positive fertility and histopathological effects on the testis of mice.
Nutraceutically Enriched Rice Based Food to Mitigate Malnutrition in Bangladesh

Rice is the synonym for food in people residing in Ganga Meghna Brahmaputra basin area and has been one of the major traditional sources of carbohydrates and proteins since the prehistoric days. By the end of 2017, eighty-six high-yielding varieties (HYVs), including both inbreeds and hybrids, have been released by Bangladesh Rice Research Institute (BRRI). At present, total rice production (cleaned or milled rice basis) is about 34.8 MT, enough to satisfy the domestic requirement to feed more than 160 million population with the surplus of 2.06 MT. In contrast, there has been comparatively less progress on addressing the quality aspects of rice. Thus, emphasis should now be to focus on the grain quality and nutrition research towards rice grain nutraceutical properties to reveal its aptitude to combat with non-communicable diseases such as heart disease, cancer, diabetics etc. By the course of time, Grain Quality and Nutrition Division of BRRI has identified some promising nutraceutically enriched HYVs such as black rice, antioxidant enriched rice, low glycemic index rice, anti-depressive alias gamma amino butyric acid (GABA) enriched pre germinated brown rice and micronutrient enriched rice, specially zinc enriched rice. Since in Bangladesh, rice based processed food items are available namely flattened, popped and puffed rice to meet local demand as traditional food items, we assume that there is a potential scope to enhance nutraceutical enriched rice based food considering malnutrition mitigation and humanitarian relief operation into account. In this study we have formulated energy dense nutraceutical enriched rice based food formulation specially cake and biscuits having energy density ranging from 5.0 5.5 per 100g serving respectively. Rice based balanced and nutritious food intake may possibly reduce the amount of unprocessed whole rice consumption gradually. By attaining required dietary allowance, rice based food may help sustain food security in Bangladesh in a way to properly and effectively utilizing the rice grain. It will open diversified uses of rice and rice based food products in Bangladesh.
International Journal of Advanced Research in Computer Science and Software Engineering

— In this paper an analysis is made to find frequent patterns by using Apriori and FP-Growth algorithms for Arabic corpus . First of all frequent item sets are retrieved and then Frequent patterns will be analysed using Quran as a case study. In our experiment for Arabic corpus, FP-Growth shows better performance when compare with Apriori algorithm