Miracle-dz/UniFAR-FTUs huggingface dataset:
How Metals and Amino Acids Effect Guaiacol Peroxidase Activity from Dill

Environmental pollution has been a serious problem since the start of the industrial revolution. The pollution usually comes from industrial wastes, waste water, heavy metal, etc. Heavy metals such as lead, mercury, tin are considered to be toxic to living organisms and enzyme activities. However, metal ions can play essential role in plants and animals as they are involved in fundamental processes such as photosynthesis, respiration and DNA synthesis. Plants with their antioxidant enzymes which are in plant defense system show some stress when they are exposed the metals. One of the iron-heme dependent antioxidant enzymes is peroxidase (POD) enzyme that catalyzes hydrogen peroxide mediated oxidation of different substrates such as phenols. In the present work, Guaiacol peroxidase (POD) was first characterized from the dill (Anethum Graveolens L.) with the optimum pH and temperature. Then, the effects of various metals and amino acids on the dill Guaiacol peroxidase (POD) activity were investigated. The POD activity was tested against eight different metals (Hg(II), Co (II), Cur(II), Fe(III), Mn(II), Pb(II), Zn(II) and Sn(II)) and five different amino acids (L-Cysteine, LPhenylalanine, LGysine, LArginine and L-Aspartic acid) with hydrogen peroxide and guaiacol. According to the results, Cu(II), Mn(II) and Fe(III) increase the POD activity, Co(II), Zn(II) and Pb(II) have almost no effect the enzyme activities and Hg(II) and Sn(II) decrease the POD activity. The tested amino acids had inhibitory effect to dill Guaiacol POD activity. Keywords— Amino acids, metals, peroxidase, dill.
A Progress of Scheduling Strategic based on Virtual Machines in Cloud Computing

- Cloud computing has come out to be an interesting and beneficial way of changing the whole computing world. The traditional way for task scheduling cannot meet the cloud market well enough. This paper introduces an optimized algorithm for cost based scheduling in cloud computing and its implementation. This scheduling algorithm measures both resource cost and calculation performance, it also improves the calculation/communication ratio by grouping the user tasks according to a particular cloud resource’s processing capability and sends the grouped jobs to the resource.
A Study of Life Satisfaction and Optimism in Relation to Psychological Well-Being Among Working and Non Working Women

Purpose of the present investigation was to study the life satisfaction and optimism in relation to psychological well being among working and non working women. The sample comprised of 150 (75 working and 75 non working) women of Aligarh. Satisfaction With Life Scale (SWLS, Diener, Emmons, Larson and Griffin, 1985) was used for measuring Life Satisfaction of women, Life Orientation Scale Revised (sheir and carver; 1994) was used for measuring optimism and Well Being Manifestation Measure Scale (WBMMS, Masse et. al., 1998) was used for measuring Psychological well being of women. Pearson Product-Moment Correlation and t-test were used for analyzing the data by SPSS 16 software. Result showed that there was significant positive correlation between life satisfaction and psychological well being. Result also revealed that there was significant positive correlation between optimism and psychological well being. In group differences, it was found that Working Women scored significantly higher on life satisfaction in comparison to Non Working Women. The result also showed that Working Women scored significantly higher on optimism in comparison to Non Working Women. Similarly, the results also revealed that Working Women scored significantly higher on five dimensions of psychological well being out of six dimensions as compared to Non Working Women. Further, it was found that Working Women also scored significantly higher on composite well being as compared to Non Working Women.
A Survey on the Classification Techniques In Educational Data Mining

: Due to increasing interest in data mining and educational system, educational data mining is the emerging topic for research community. educational data mining means to extract the hidden knowledge from large repositories of data with the use of technique and tools. educational data mining develops new methods to discover knowledge from educational database and used for decision making in educational system. The various techniques of data mining like classification. clustering can be applied to bring out hidden knowledge from the educational data. In this paper, we focus on the educational data mining and classification techniques. In this study we analyze attributes for the prediction of student's behavior and academic performance by using WEKA open source data mining tool and various classification methods like decision trees, C4.5 algorithm, ID3 algorithm etc.
A New Three-Stage Buck in Buck, Boost in Boost Grid-Tied Inverter

A new kind of buck in buck, boost in boost grid tied inverter is analysed in this paper. In this family of inverters only a single power stage works at high frequency at a time. This reduces the losses due to switching and hence improves efficiency. There is only minimum filtering inductance in the power loop and over filtering does not take place. The analysis of the operating modes of the inverter is done through the equivalent circuits of various stages in a half-bridge configuration of the inverter. The closed-loop simulation of a 230V/50 Hz, 2kW is included.
Physico-chemical characterization and thermal behaviour study of Lignocellulosic biomass obtained from a few wild grasses of Kamrup (Assam) and Thoubal (Manipur) for biofuel production

We report here the physico-chemical characterization and thermal behaviour investigation of six species of wild grasses (Phragmites karka (Retz.), Thysanolaena agrostis Nees, Neyraudia reynaudiana, Coelorachis striata, Erianthus fultus and Sclerostachya fusca ) collected from Assam and Manipur for their biomass content towards the alternative renewable biofuel production. This study investigates the physical analysis (proximate analysis, Thermogravimetric analysis (TGA), X-Ray diffraction (XRD) and Calorific value), chemical analysis (ultimate analysis and Fourier Transform Infra-Red (FTIR) and fibre analysis (cellulose, hemicellulose, lignin etc). The results confirmed that combustion conditions define the characteristics of each biomass sample having a different zone of degradation profile. Thermal degradation profile was seen at temperatures such as hemicellulose at 250-300 0 C followed by cellulose at 300-350 0 C and finally lignin at 350-500 0 C. The crystallinity index was found maximum in Phragmites karka (33.82) and minimum in Coelorachis striata (13.54). The calorific value of the biomasses was calculated and the maximum was found in Erianthus fultus (16.20 MJ/Kg). FTIR analysis of these lignocellulosic grass biomass revealed that functional groups were present with a vast spectrum of wave number starting from 3400 to 873 cm. The cellulose content derived from fibre analysis was found to be maximum in Erianthus fultus (39.2%). All these properties combined together shows that these lignocellulosic biomass can act as the potential candidate for bio-energy production.
Ameliorative Effect of Bryophyllum pinnatum against Induced Mercuric Chloride Toxicity in Rat: A Haemato-Biochemical Study

1 Department of Veterinary Pathology, R.V. C, B.A.U, Kanke, Ranchi-06, Jharkhand, India 2 Department of Livestock Products Technology, R.V. C, B.A.U, Kanke, Ranchi-06, Jharkhand, India 3 Department of Veterinary Pathology, W.B. U.A. F.Sc, 37, K.B. Sarani, P.O. Belgachia, Kolkata 700 037, WB, India 4 Department of Veterinary Pathology, R.V. C, B.A.U, Kanke Ranchi-06, Jharkhand, India *Corresponding author
A Survey on Web Spam and Spam 2.0

In current scenario web is huge, highly distributive, open in nature and changing rapidly. The open nature of web is the main reason for rapid growth but it has imposed a challenge to Information Retrieval. The one of the biggest challenge is spam. We focus here to have a study on different forms of the web spam and its new variant called spam 2.0, existing detection methods proposed by different researches and challenges that are still unanswered.
A SECURED LSB IMAGE STEGANOGRAPHY SYSTEM USING EDGE DETECTION, LZW COMPRESSION AND HYBRID ENCRYPTION METHODS

Rapid growth of steganographic and cryptographic techniques has a great attention in digital era. Every one need privacy in this internet world. As number of users increases secret communication becomes more and more important. Transposal of data size and file quality through communication channel plays a major challenge for steganographic technique. Least significant bit is one of the simple and major steganography techniques in spatial domain, insertion of data at least significant bits has high visual quality but not robust against distortion hence not well secured. In the proposed method, the secret data is encrypted by using Hybrid encryption method i.e. AES[Advance Encryption Standard] and ECC[Elliptic Curve Cryptography] method to safe guard the secret communication. Then, Lempel Ziv Welch technique compresses the required amount of data to represent information quantity. Then Edge detection technique detects the sharp feature of image to hide secret data. The main feature of proposed method is to give better security by using the concepts of cryptography and Image steganography. Even though the adversaries have the knowledge of secret information fails to extract the correct information. Improvement may seen by comparing the results of base paper and proposed method. Better encryption methods are considered to provide better security along with steganography.
Establishment of Regeneration system for Taif peach ( Prunus persica L . Batsch ) cultivar ( Balady cultivar ) in Taif

Peach (Prunus persica L. Batsch) is one of the most important stone fruits in different parts of the world. Peach trees are essentially infected by many different pests and diseases. One of basic requirement for successful transformation system is reliable high-frequency regeneration. Shoot organogenesis could be induced from stored mature embryos of Taif peach (Prunus persica L.) cultivar in vitro. In this study, the influences of different cytokinin (TDZ) levels and dark incubation periods on shoot regeneration were determined. Taif peach cultivar regenerated in the presence of TDZ and darkness for the first 13 days of the culture. Dark incubation at the early stage of culture was critical for obtaining higher regeneration efficiencies from stored Taif peach embryos. Media containing 3.6 μM TDZ with 2. 5μM IBA was more effective than other TDZ levels in inducing shoot regeneration. The highest regeneration frequency was obtained with concentrations of 3.6 μM TDZ (62.5%) in combination with dark incubation. Root percentage of the regenerated shoots was 38.2% by addition of 10.74 μM NAA in the medium. Regeneration of adventitious shoots from stored mature embryos of Taif peach cultivar is obtained. Therefore, it could be suggested that Taif peach cultivar has a potential for genetic transformation through this regeneration protocol. [Mohamed A. Nagaty Establishment of Regeneration system for Taif peach (Prunus persica L. Batsch) cultivar (Balady cultivar) in Taif, KSA. Journal of American Science 2012; 8(4): 232-239]. (ISSN: 1545-1003). http://www.americanscience. org.31
A RESOURCEFUL INTRUSION DETECTION SYSTEM FOR MANET USING ROUGH SET THEORY AND SUPPORT VECTOR MACHINE

— Mobile impromptu Networks has more difficult vulnerabilities compared with wired networks. Mobile impromptu networking (MANET) has become a vital technology in current years attributable to the speedy proliferation of wireless devices. They’re extremely at risk of attacks thanks to the open medium, dynamically ever-changing topology and lack of centralized watching purpose. It’s vital to look new design and mechanisms to safeguard these networks. Intrusion detection system (IDS) tools are appropriate for securing such networks. The most tasks of IDS is to get the intrusion from collected information. a number of the options of collected information is also redundant or contribute very little to the detection method. Therefore it's essential to pick out the vital options to extend the detection rate. Most of the present intrusion detection systems detect the intrusion by victimization sizable amount of knowledge options collected from network. During this work, we have a tendency to propose anomaly primarily based intrusion observation system to detect the malicious activities by collection statistics from network. Conjointly we have a tendency to use SVM machine learning technique associate degreed Rough pure mathematics that are wont to observe the attacks in an economical approach. Rough pure mathematics preprocesses the feature information to scale back the procedure complexness. The support vector machine is trained by victimization feature set from the Rough pure mathematics for sleuthing abnormal behavior.
The Effect of Pre-Harvest Methyl Jasmonate Treatment on the Selected Volatile Compounds and Endogenous Hormones Contends in the Pulp of Grape Berries

Grapevine is one of the most valued and widely cultivated fruit crop worldwide, with their pleasant flavor and valuable health effects. During the consequent ripening at ambient temperature, the volatile compounds of table grape often decreased, to affect their sensory evaluation. The development of new and effective methods to increase the volatile compounds of berries is necessary. Present study was carried out to investigate the pre-harvest methyl jasmonate (MeJA) treatment on the selected volatile compounds and endogenous hormones content from ‘Shine Muscat’ berries pulp. The results indicated that, pre-harvest application of MeJA (0.1 mM or 0.01 mM) on grape berries generally enhanced the production of terpenes, like nerol, linalool, alpha-terpineol; While some C6 compounds were reduced, such as (E)-2-hexenol, hexanol, (Z)-3-hexenol, hexanal and (E)-2-hexenal. The endogenous hormones like IAA (indole acetic acid), ABA (abscisic acid) and JA (jasmonate acid) content were also changed after MeJA treatment. We also observed that MeJA palys a key role in fruit endogenous hormones level and volatile compounds by increasing the expression level of several related genes, such as aroma-related genes Vvter, Vv-syn and hormone-related genes VvOPR3, VvAuI, VvEth, VvNCED1. We hypothesize that, MeJA as an effective elicitor affects the volatile compounds by altering endogenous hormones level in berries pulp of ‘Shine
BRAIN TUMOR CLASSIFICATION USING MACHINE LEARNING

: Medical imaging has be coming as a transpire discipline in diversified medical diagnosis. It has been plays a vital role in automatic detection, which bestows information about abnormalities for further treatment. The traditional approach of detecting MRI has been based on manual inspection, which has become inappropriate for vast volume of data. Automated tumor detection has gaining importance that conserves the time of radiologist. In this paper, brain tumor has been detected from MRI images by utilizing classification technique based on Support Vector Machines (SVM). The performance of SVM has been compared with the neural classifier such as back propagation network. Here feature extraction from MRI Images has been done by gray scale and texture features. This intelligent system improves accuracy rate and reduces error rate of MRI brain tumor using SVM .
Influence of Industrial and Agricultural Additives to Clay Mitigates Fuel Consumption on Red Bricks Manufacturing

The aim of this study is to manufacture model building green bricks with different cheap solid additives [industrial and agricultural], petro-coke, animal dung, and saw-dust as an internal fuel. Model samples were manufactured, dried smoothly, and then fired through a suitable predetermined firing technique at range of temperature, 750, 800, 850, 900 and 1000C. The experimental measurement was performed on these samples at Brick and Road Research Institute (BRRI) University of Khartoum, Sudan in order to evaluate internal and external fuel consumption in red brick production and mitigation measures of environmental contamination. The main bricks properties used for assessment are loss-on-ignition, density and crushing strength that related to the lowest specific fuel consumption and cost. Numerous measurements on samples have compared relative to internal and external energy and fuel consumption. The petro-coke sample was found to be the best, with the lowest fuel consumption, higher crushing strength and very good density of clay bricks as well as with the minimum firing cost. The results reveal the firing temperature is significantly affected densities properties of the clay bricks additive material above 900C, while the crushing strengths and loss-on-ignition are increasing steadily to 1000C.
Emotion Recognition from Speech: A Survey

— Emotion recognition from speech is an important area in research that represents human-computer interaction. The main purpose of this paper is to present literature review of different features and techniques used for speech emotion recognition. The survey represents the importance of choosing different classification model and features for speech emotion recognition. Speech emotion recognition databases are also reviewed in this paper for the purpose of identifying the number of speakers, language used and emotion classification till date.
Mining Bio Medical Literature Using Ontology Based Text Mining

- Text mining is a new and exciting area of computer science research that tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. Significant developments in the area of biomedical text mining during the past years have demonstrated its great promise for supporting scientists and medical practitioners in developing new knowledge from the biomedical literature. Identifying and classifying relevant medical information in short texts and finding the semantic relations among these information is a challenging task of mining Bio Medical Literature. This can be achieved by extracting information from published literatures. In order to share the vast amounts of biomedical knowledge effectively, textual evidence needs to be linked to ontologies as the main repositories of formally represented knowledge. Ontologies are conceptual models that aim to support consistent and unambiguous knowledge sharing and that provide a framework for knowledge integration.
Multi-Faceted Approach to Automated Classification of Business Web Pages

- Data Services Companies routinely aggregate commercial business content automatically from entity websites on a large scale. A key product is the base information on new and upcoming businesses which have a potential value for business information databases and CRM products. A legal name, contact information, business activity and name of principal/leadership team are valuable basic information that can be aggregated. However there is cost involved in crawling all the pages to identify the right page where the four key information points are located. A business website has an average of 5 pages and pinging and crawling each page involves IP cost at granular level and virtual machines capacity at a high level. The efficiency of the current process and algorithms in use is not satisfactory and results in increased cost of operation. However, because the current algorithms are “Black Box”, companies find it hard to tweak the algorithm to better suit its needs and achieve higher accuracy figures. The research is aimed at building an effective model to classify pages and reduce the crawl volume and control running costs. The objective is to predict the most likely pages to pass on for extraction and the most unlikely pages for bypassing.
Data Hiding System Using Cryptography & Steganography: A Comprehensive Modern Investigation

- In excess of the past few decades with progression in era of information society, computer networks and their related applications are becoming more and more popular. As the use of internet and reliance on the world wide system growing rapidly in daily life increase the number of networked machines which have leads unauthorized activity not only from external attackers, but also from internal attackers, such as disgruntled employees and people abusing their privileges for personal gain. The precious information is always prone to maximum attacks over the network. Attacks may occur due to system vulnerabilities or security breaches, such as system misconfiguration, user misuse or program defects. Attackers can also combine multiple security vulnerabilities into an intelligent attacking system. Therefore, an efficient security model is needed to defense secrete information over the network system. However, a number of approaches have been proposed in context to enhance the security of secrete information but each of them has its own limitation. These limitations represent problem with the current security systems and have led to an increasing interest in design and implementation of an efficient method to secure the secrete information. This paper presents a comprehensive investigation of two popular security techniques, cryptography and steganography, which performs better in comparison of other existing standard and automated security methods.
Efficient Publish/Subscribe System using Filtering Algorithm for Location Based Service

: The services which are location based are used in many applications. In these systems any user request for particular service through query to a server and server gives feedback according to location. For providing this facility a push model, or server initiated model come into picture. For using this facility user has to enter their interest for finding their need. Because of this model user will get related information which is going to be need in proposed method. We create index based on R-tree by collecting the tokens into R-tree nodes. They Propose an R-tree based index by integrating textual descriptions into R-tree nodes and develop efficient filtering algorithms and effective pruning techniques to achieve high performance. Using this model we can do sorting or decrease some unnecessary information by filtering algorithm which helps to increase efficiency of system but also reduces cost of such publisher/subscriber application. This method can work on both ranking queries and conjunctive queries. The results which are experimented by us can filter 500 messages/sec.
Autonomous Rough Terrain Rescue Mobile Robot

: The mobile rescue robot is developed to improvise the search and rescue operation. This consist of two systems, ﬁ rst the base station and the other mobile robot itself. The base station is used for monitoring the mobile robot. The video sent by the mobile robot is stored in the database for further use. The video is timestamped with the time, date and the longitude and latitude values. This help us to know where the humans are located. GPS data is sent wirelessly to the base station via ZigBee module. A PIR sensor is used to detect the humans. The autonomous operation will ease the operator from controlling the robots movement. This robot can be used in earthquake disasters and to monitor or ﬁ nd humans in man caused disasters such as hostage situations. The mobile robot is built to go on rough terrain.