Miracle-dz/UniFAR-FTUs huggingface dataset:
Nutritional importance of Lepidium sativum L. (Garden cress/ Chandrashoor): A Review

Lepidium sativum (Garden cress) belonging to Cruciferae family, widely grown in India, Europe and US. It has been considered as an important medicinal plant since the Vedic era. Garden-cress seeds are used as a medicine in Ayurvedic System of Medicine. Lepidium sativum description is available in the Ayurvedic classical text with the name as Chandrasoora, Chandrika, Vasapushpa, and the seeds, known as hurf or halim in local language in India. In Ayurvedic Medicine prescribed to prevent postnatal complications. Also, it has health promoting properties which can be used as a functional food. It is also useful in the treatment of dysentery, pain in the abdomen, blood and skin disorders, injuries, tumors, and eye diseases. Garden cress may stimulate the production of breast milk and prevent postnatal complication. Garden cress seeds are bitter. A Galactogogue is a substance that promotes lactation in humans and other animals. The effects of the germinating seeds were studied to determine the potential for slowing down the hydrolysis of starch to glucose in diabetic persons. Garden cress is genetically related to watercress and mustard, sharing their peppery, tangy flavor and aroma.
RECOGNITION OF HEALTHY AND UNHEALTHY MAIZE LEAVES BASED ON TEXTURE FEATURES

: In this paper, we proposed a method for identification of diseases in maize leaf using texture features like GLCM and Haar Wavelet for different components of YCbCr, HSV and gray scale. kNN classifier is used to classify the data. Maize leaf images are converted into YCbCr color model. The chromatic red(Cr) component of YCbCr is used for segmentation. The accuracy of the classifier is 93.33% with GLCM, when compared to other component chromatic red(Cr) component of YCbCr gives better result.
Assessment of Groundwater Quality in Tirupur Environs, Tamil Nadu, India

Groundwater is a valuable and the widely dispersed resource of the earth. This most valuable resource is sometimes inadequate due to improper use of surface and groundwater aquifers. The wide-range of textile industrial process and urbanization activities in the study area affects the groundwater. For groundwater examination, sixty two bore well water samples have been collected and analyzed for different physic-chemical parameters. Along with major cation and anions, fluorde, and total hardness were evaluated. Quality of groundwater for drinking purpose and irrigation are evaluated. Based on Gibb’s diagram, evaporation and chemical weathering of rock-forming minerals are influencing the quality of groundwater. On the basis of Richard classification and sodium percentage, the suitability of groundwater for irrigation purpose is presented in this paper.
Statistical Methods for Bayesian Clinical Trial Design and DNA Methylation Deconvolution

Matthew A. Psioda: Statistical Methods for Bayesian Clinical Trial Design and DNA Methylation Deconvolution (Under the direction of Joseph Ibrahim and Wei Sun) We consider the Bayesian clinical trial design problem in situations where a historical trial is available to inform the design and analysis of a future trial. Currently the FDA requires that all proposed designs exhibit reasonable type I error control. Traditionally, frequentist type I error control has been required. This is currently the case in the Center for Drug Evaluation and Research but no longer in the Center for Devices and Radiological Health. The requirement that a design exhibit frequentist type I error control necessitates that all prior information be discarded. We propose several Bayesian solutions that balance the need to control type I errors with the desire to utilize high quality prior information. For scenarios where the historical trial informs the parameter being tested, we propose Bayesian versions of the type I error rate and power that are defined with respect to the posterior distribution for the parameters given the historical data and conditional on the respective hypothesis being true. We demonstrate that in designs that control the Bayesian type I error rate, meaningful amounts of prior information can be borrowed but that the size of the new trial must be relatively large to justify borrowing a large amount of historical information. We tailor our design methodology for survival applications using proportional hazards and cure rate models. We also develop Bayesian adaptive designs for large cardiovascular outcomes trials (CVOTs) which incorporate control information from a historical CVOT conducted in a similar patient population. We propose an all-or-nothing adaptive design utilizing the power prior as well as a dynamic borrowing adaptive design utilizing a novel extension of the joint power prior. Separately, we present a statistical deconvolution method for DNA methylation data from bisulfite sequencing experiments. We propose a joint model for methylation data from a set of
Revealing Image Forgery on Digital Images by applying Contrast Enhancement

Image manipulation is a malicious threat that is occurring nowadays. The trustworthiness of images is lost. Malicious users have many photo editing software's to manipulate images in many ways such as brightness changes, contrast manipulations and creating composite images. Here in this, it proposes two novel methods to detect contrast manipulations and composite images. First, it detects the manipulation of images by identifying the image's block level histogram. Second, we propose to identify the manipulation occurring in the images using a high frequency metric method. Once both the methods outputs are obtained it combines the outputs to obtain a final output. Finally it will be able to detect the manipulation that has occurred to the image. Results are summarized at the end and our system is compared with methods used.
Energy Heat Balance For Buildings, A Review Analysis

The analyses for energy heat balance for buildings are reported in this paper. The parameters influencing the interaction of heat balance was taken into account. Other aspect considered in this work is the building location and surroundings which plays a key role in regulating its temperature and illumination. The result of the estimation of the heat load and heat gains to the buildings were all reported in this paper. Keywords; façade material, insulation values, heat load, energy cost, heat gain. building envelope ————————————————————
Identification of Long Non-coding RNAs Expressed During Early Adipogenesis

Long non-coding RNAs (lncRNAs) are transcripts with a length of more than 200 nucleotides that lack protein-coding capacity. LncRNAs play important roles in the regulation of genes during many biological processes, development and disease progression, such as obesity. Obesity is an increasing health concern around the world. Although multiple studies linking lncRNAs and fully differentiated adipocytes have been published, the systematic analysis of those lncRNAs involved in early preadipocyte differentiation, when fate determination decisions are made, has not been reported. In order to fill this gap, we conducted strand-specific RNA-Seq on mouse 3T3-L1 preadipocyte cells and compared the expression profiles before and after early differentiation for 2 days. We identified 82 lncRNAs that significantly changed their expression after early differentiation, 98% of which were newly discovered in association with early adipogenesis. The most remarkable lncRNAs were U90926, Wincr1, Kcnq1ot1, Malat1 and Hotairm1. Expression patterns for these identified genes were also highly correlated with markers of adipogenesis, including PPARγ, CEBPα, FABP4 and FASN. Further analysis implies that many of those altered lncRNAs might coordinately inhibit Wnt/β-catenin signaling pathway to promote preadipocyte differentiation. This work strongly suggests that lncRNAs are critical in the proliferation and differentiation of adipose tissue.
Protein Flexibility and Cellular Signaling

Traditional view of cellular signaling was based on the assumption that each protein has only two states, active an inactive, like a light switch, that can be “on” or “off”. This view was applied to cell surface receptors and downstream signaling proteins, including G proteincoupled receptors (GPCRs) and their immediate signal transducers, G proteins and arrestins. Arguably the most enduring model of GPCR signaling, extended ternary complex model [1] explicitly posited the existence of the receptor in two states, R (inactive) and R* (active). Based on this assumption, the model posited that G proteins interact only with the R* state, forming the signaling ternary complex agonist-R*-G protein [1]. As the signaling of prototypical GPCR, rhodopsin, was quenched by receptor phosphorylation followed by the binding of arrestin [2], the field assumed that G proteins, GPCR kinases (GRKs), that selectively phosphorylate active GPCRs (reviewed in [3]), and arrestins recognize the same active state of the receptor, so that GPCR desensitization can be explained by a simple competition between G proteins and arrestins for the active receptor [4,5]. This view was extrapolated to the whole GPCR family [6]. The first biophysical data appeared to support this simplistic model: GPCR activation was found to require a rigid body motion of the transmembrane helices [7]. Inter-helical distance measurements using pulse EPR technique double electron-electron resonance (DEER) in the inactive and light-activated rhodopsin generally agreed with this model [8], although close inspection of distance distributions shows multiple peaks in some cases, which suggests that things may not be that simple [8]. Crystal structures of inactive [9] and light-activated [10,11] rhodopsin, as well as the structures of a prototypical non-visual GPCR, β2-adrenergic receptor (β2AR), also in the inactive [12] and active agonist-liganded state [13] revealed the expected helix movement upon activation and appeared consistent with this two-state model.
TRADE AND GROWTH IN NIGERIA: AN EMPIRICAL INVESTIGATION (1970-2014)

The trade-growth nexus is well articulated in modern trade theories. This paper set out to test the trade-growth relationship in the Nigerian economy between 1970 and 2014. Three econometric models were specified for the study and estimated using Ordinary Least Square (OLS) regression technique. The data of the macroeconomic variables used in the models were obtained from Central Bank of Nigeria Annual Statistical Bulletin. The empirical results from the econometric analysis indicate that there was a shift / structural break in the Nigeria economy as a result of trade liberalization of 1986-1989. The results suggest that the growth impact of trade on the Nigerian economy derives mainly from the static gains of trade resulting from opening of the economy and weakly form dynamic long term gain. It was recommended among others, that there is need for active pursuit of trade policies that will stimulate total factor productivity of domestic industries, ensure gradual scaling down of barriers to trade and promote domestic and foreign investment in the service industry.
Is Spinning Safe? Exercise Induced Rhabdomyolysis

Spinning is a non-contact; popular Indoor based stationery cycling exercise. Regarded as safe, it is recommended for both genders and is most popular with the middle aged and in pregnant athletes [1-3]. We present a case of spinning induced Rhabdomyolysis to increase this potential side effect in those starting spinning.
Detection and Molecular Characterization of Circulating Tumor Cells (CTCs) in Patient with Metastatic Melanoma: A Potential Application of Liquid Biopsy

Melanoma specific anti NG2 antibody conjugated with iron oxide nanoparticles that have been developed to isolate, detect, and culture CTCs from melanoma xenograft models and blood from patients with metastatic melanoma. The enrichment process involved, lysis of RBC from blood samples using RBC lysis buffer enhances the cancer cell recovery by immunomagnetic labeling and separation. Efficient cell capture was validated using fluorescently labeled cancer cells spiked into healthy human blood and clinical utility was demonstrated in specimens from patient with metastatic melanoma. The spiking experiment results with greater than 70% recovery in four sets of experimental. Spontaneous metastasis melanoma model, found that the number of CTCs increased during the tumor progression and correlated to lymphatic as well as lung metastasis development in vivo. CTCs were detected in 6 out of 7 patients’ blood samples that contained metastatic melanoma. The CTCs were positive for melanoma specific molecular markers such as S100, HMB45, MelaA, MITF and the CTCs were positive for anti NG2-Q-dot and pERK2-Q-dot staining. The BRAFV600e gene expression pattern resulted that the CTCs were expressed BRAFV600e similar to the control melanoma cells. The iron oxide antibody nanoparticle isolation method is a highly reliable and cost effective detection method of CTCs from patients with metastatic melanoma and CTCs cells can be culture for additional analytical studies or potential drug sensitivity testing.
A 0.18µm and 2GHz CMOS Differential Low Noise Amplifier

— We have proposed a 2 GHz CMOS Differential Low Noise Amplifier (LNA) for wireless receiver system. The LNA is fabricated with the 0.18 µm standard CMOS process. Cadence design tool Spectre_RF is used to design and simulation based on resistors, inductors, capacitors and transistors. Power constrained methodology is used for the design of Differential Low Noise Amplifier. Consuming 9mA current at 1.8V supply voltage, the proposed LNA exhibits a power gain of 15.87 dB, noise Figure (NF) of 2.4 dB, S 11 of -9.842 dB and S 12 of -42.86dB. The input IP3 (IIP3) at 2 GHz is -2.86127 dBm, and consumes 16.2 mW of power.
An Efficient Overload Relay Control Mechanism based Routing Protocol for Connecting VANET to Internet over IEEE 802.11p

— The connection of vehicular ad hoc network (VANETs) to Internet is typically established by roadside units (RSUs). Link stability and number of hops are often used as the primary metrics in the relay selection to find the route between vehicles and these RSUs. In case of high vehicles density, basing only on those features, one vehicle may be selected as relay for multiple vehicles and if the number of relay requests exceeds the service capacity of this vehicle, it might get overloaded, which will increase bottlenecks in the network, and affect the connection throughput of VANETs due to continues dropping packets and frequent MAC retransmissions. In this paper, we extend an existing stability based routing protocol which connects VANETs to the Internet via IEEE 802.11p technology with an efficient overload relay control mechanism, with the objective to distribute uniformly traffic load in the network and make efficient use of network bandwidth. The proposed overload relay control based routing protocol reduces significantly the routing overhead and the collision in the network basing on contention-based-forwarding (CBF) for broadcasting control messages. The simulation results show that the proposed protocol enhances throughput, and decreases the packet loss and overhead.
MARKETING TRENDS & FUTURE PROSPECTS OF HERBAL MEDICINE IN THE TREATMENT OF VARIOUS DISEASE

Traditional medicine also known as indigenous or folk medicine comprises medical knowledge systems that developed over generations within various societies before the era of modern medicine. I have gone through literature review published in online journals and related websites, then after study of all the literatures I found that global pharmaceutical market was worth US $550 billion in 2004 and is expected to exceed US $1100 billion or more by the year 2015. The herbal industry shares about US $100 billion with good growth potential. The World Bank report trade in medicinal plants, botanical drugs products and raw materials is growing at annual growth rate of about 15% (WHO). Within the European community botanical medicine represents an import share of the pharmaceutical market. Natural products compounds discovered from medicinal plants (and their analogues thereof) have provided numerous clinically useful drugs in the treatment of chronic and or acute disease and still remain as an essential component in the search for new medicines. So, these traditionally used plants can be explored effectively in order to find New Chemical Entity for the treatment of chronic and acute disease. Hence the small but having greater future perspectives review was performed systematically.
Computer-Based Test (Cbt) System For University Academic Enterprise Examination

As flexible and online learning mediated by ICT becomes more pervasive, there is a growing need for educators to consider modes of assessment using similar tools. Computer Based Test (CBT) is an effective solution for mass education evaluation. Though, a variety of e-assessment approaches and systems have been developed in recent times, yet lack of flexible timing functionality to automatically log-off candidates upon expiration of allotted time, result integrity comprise, stand-alone deployment, lack of flexibility, robustness and scalability as well as human error are major limitations of the existing platforms. In this paper, a web-based online examination system is developed to address these aforementioned drawbacks. The system is designed to facilitate the examination processes and manage challenges surrounding the conduct of examination, auto-submission, auto-marking and examination result report generation. The conceptual design including the Data Flow Diagram (DFD), the Use Cases and the Entity-Relationship Model (ERM) for the system developed is also presented. The programming tools used for the front-end development of the system are Hypertext Markup Language (HTML) and Microsoft Visual Studio 2012 integrated development environment while Microsoft SQL Server 2008 is used as the database backend. The CBT system was evaluated at the Federal University, Oye-Ekiti, Ekiti State prometric centre. Performance assessment was carried out by two-hundred and fifty (250) volunteer users of the CBT system and the average performance scoring indicate that the system scores high in terms of reliability, robustness and flexibility with easy to use graphical user interface. The volunteers comprise of software developers, students, lecturers and network engineers. The test proved the validity of using this web-based CBT system to evaluate a large mass of students in various institutions of learning across the globe.
A Clustering and Genetic Algorithm based Feature Selection (CLUST-GA-FS) for High Dimensional Data

: Feature selection involves ﬁ nding the relevant and useful features that provide enhanced classi ﬁ cation results as the original set of features. Feature selection in a high dimensional data is even more signi ﬁ cant as it ﬁ nds the optimal set of features from a vast number of features. A clustering and genetic algorithm based feature selection (CLUST-GA-FS) algorithm is proposed and evaluated experimentally in this research work. The proposed algorithm has three stages namely irrelevant feature removal, redundant feature removal, and optimal feature generation. Mutual information ﬁ lter method is used to remove the irrelevant features in the ﬁ rst stage. The features are grouped into clusters by using graph based clustering method in the second stage. Also, the redundant features are removed and a representative feature is selected from each cluster in the second stage. In the ﬁ nal stage, the genetic algorithm is applied to the representative set of features and an optimal set of features is generated. The effectiveness of the proposed method is ensured using the well known classi ﬁ ers, namely Naïve Bayes, Multilayer Perceptron and Adaboost. The CLUST-GA-FS method is implemented on four publicly available high dimensional medical dataset and text data. The result demonstrates that CLUST-GA-FS improves the performance of the classi ﬁ ers.
A NOVEL APPROACH TOWARDS MINING LOCALLY FREQUENT ITEMSETS

Mining patterns that occur in a certain time frame is a well defined data mining problem. Many researchers have proposed different methods for the same. Taking time factor into consideration, different patterns can be extracted. These patterns cannot be extracted normally. These patterns are known as temporal patterns. Here we propose an efficient method of mining locally frequent patterns from temporal datasets. The real time databases are used to prove the efficacy of the method. The comparative studies prove that our method gives more results than the other well known method.
LEVELS AND AIR QUALITY INDEX OF SO2 AND H2S IN AMBIENT AIR OF JEMITA/ YOLA METROPOLIS, ADAMAWA STATE, NIGERIA

The Air quality of hydrogen Sulphide and Sulphur dioxide in Jimeta/Yola Metropolis were determined at ten different locations, using a portable hand held gas monitor ( crown instrument Ltd Oxon CE-89/336/EEC). The result showed that concentration of SO2 and H2S ranged between 0.03 to 0.135 and 0.030 to 0.057 ppm for both seasons. There high levels may be due to high traffic density, anthropogenic activity and seasonal variation. The difference in mean concentration between dry and rainy season were significant for both SO2 and H2S. The Concentration of SO2 and H2S exceeded the permissible limit of 0.1 and 0.01 ppm respectively. However, poses serious threat to the human, animals and plant. Therefore relevant agency should embark on enlightenment and sensitization campaign in order to reduce the air pollution of those locations.
A NEW SPEAKER VERIFICATION APPROACH FOR BIOMETRIC SYSTEM

- In this paper a new speaker verification method is proposed. Speaker Verification for various speakers has been done and the output for feature extraction like pitch extraction, formant extraction and generation of code vectors has been presented. The speech signal is acquired by using microphone from various speakers. The pitch and formant extraction is done using two windowing techniques such as Hanning window and Hamming window. Hanning window gives better pitch extraction compared to Hamming window. This method serves as an efficient method for the speaker verification as a biometric system.
Sentimental Data Analysis for prediction of public reaction using Hadoop Framework

: Sentiment analysis is taken into account to be a sub-class of machine learning and natural language processing. It's accustomed disencumber, identify, or depict opinions from completely diverse content structures, as well as news, reviews and editorials and sorts them as positive, neutral and negative. In this paper, we have an inclination towards investigating the effectiveness of linguistic possibilities for sensing the sentiment of Twitter messages. We have an inclination towards evaluating the usefulness of present lexical sources in addition to qualities that seize information regarding the natural and artistic language employed in microblogging. We take a administered attitude to the issue, however control current hashtags within the Twitter data for making training data. We are making use of Pig Latin in our system. We record the stream data and store it in . csv format file. Then we compare the words stored in file with AFINN dictionary and based upon the keywords provided, it will rate each keyword ranging from -5 to +5 depicting most negative to most positive comments. Those ratings are combined to obtain a numerical value and that is what gives us our prediction of public opinion.