Miracle-dz/UniFAR-FTUs huggingface dataset:
Major Vault Protein of the Protozoan Raphidiophrys contractilis Has a Binding Property to β-1,3-Glucan and is Involved in Food Capturing

A centrohelid heliozoan Raphidiophrys contractilis was found to recognize curdlan, an insoluble β-1,3-glucan, as food. When a suspension of curdlan gel was added to the heliozoans, the gel particles were ingested into food vacuoles. By affinity purification with curdlan gel, a protein of 100 kDa was isolated as the only β-1,3-glucan-binding protein from the detergent-extracted cell homogenate of R. contractilis. The protein was subjected to mass spectrometry with a reference contig dataset obtained by transcriptome analysis. From the obtained partial nucleotide sequences and additional PCR-based sequence determination, the protein was identified as major vault protein (MVP), the main component of Vault complex. The R. contractilis MVP reacted with an antibody against human MVP, and specific binding to β-1,3-glucan was verified by a competition assay with laminarin, a soluble-type β-1,3-glucan. The heliozoans were mixed with prey flagellate Chlorogonium capillatum and extracellular fluid was collected during food-uptake. The fluid was then subjected to pull-down assay with curdlan gel, by which multiple protein species were detected including MVP as one of the major proteins, suggesting that MVP is secreted from the heliozoans during food uptake as a component of a large protein complex. The involvement of the heliozoan MVP in prey recognition suggests a possible novel function of this protein in self/nonself discrimination.
An Efficient Iris Feature Encoding and Pattern Matching for Personal Identification

— R ecognize people identity becomes an essential problem, Iris based biometric system provides accurate personal identification. Feature encoding and pattern matching are major task in the iris recognition. In our proposed system gives how to set a model to extract the feature of different irises and match them is especially important for it determines the results of the whole system directly. Gabor wavelets are able to provide optimum conjoint representation of a signal in space and spatial frequency. A Gabor filter is constructed by modulating a sine/cosine wave with a Gaussian. Feature Encoding was implemented by convolving the normalised iris pattern with 1-D Gabor filters. For Matching hamming distance will be calculated and accurate recognition was achieved.
Using latent class mixture models to define sepsis endotypes

Severe sepsis is associated with high mortality and is a common problem in the United States. Recently, studies have shown that efforts focused on lowering cytokine levels improve survival. The aim of this work is to define sepsis endotypes using longitudinal cytokine measurements. Sepsis endotypes were defined using latent class mixture models. Latent class mixture models were modeled using a natural log transformation of the actual time measurements. The outcome was the natural log of the cytokine value. No other covariates were modeled and a parameterized link function using a basis of I-splines was chosen over a linear transformation to increase flexibility in the latent class trajectories. The number of latent classes were determined by a combination of the lowest BIC and clinical significance. After creating models for a variety of subsets derived from the source population, it was determined that mortality within a particular trajectory class is not only dependent upon the baseline cytokine value, but also dependent upon the rate of decent after baseline. A class with high baseline cytokine values that decrease quickly has lower mortality rates than classes who do not decline quickly. It was also determined that those who have increasing cytokine values from baseline to 6 hours have worse outcomes than those who decrease in the same time frame. Public Health Significance: Given the public health significance of sepsis, understanding prognosis is extremely important. Previously, having a high IL6 measurement implied a poor prognosis. Our results show that many factors play into the determination of prognosis and patients can be treated accordingly.
ANTIEPILEPTIC ACTIVITY OF RUBIADIN ISOLATED FROM THE ROOTS OF RUBIA CORDIFOLIA IN MICE

Epilepsy is a disorder of the central nervous system. A seizure occurs when the brain’s nerve cells misfire and generate a sudden uncontrolled surge of electrical activity in the brain. Seizures can be controlled with modern medicines and surgical techniques and are found to have so many side effects. Natural products from folk remedies are an alternative source of anti-epileptic drugs with better safety and efficacy profiles. Rubiadin is an anthraquinone glycoside isolated from roots of Rubia cordifoia (Manjishta) known for a number of pharmacological activities. The present study was aimed to assess the anti-epileptic activity of isolated rubiadin from Rubia cordifolia. The evaluation of anti-epileptic activity was carried out with maximal electric shock (MES) and Pentylene Tetrazole (PTZ) models. Epileptic seizure were induced in mice of either sex and the challenged animals treated with Whole Rubia cordifolia root extract & isolated Rubiadin suspension at two doses 100 mg & 500 mg respectively. The isolated Rubiadin suspension at 500 mg dose showed significant reduction in MES and PTZ induced epileptic seizure which is compared with whole-plant extract in mice. INTRODUCTION: Human beings have relied on natural products as a resource for drugs for thousands of years. Plant-based drugs have formed the basis of traditional medicine systems that have been used for centuries in many countries such as Egypt, China and India 1 . Phytotherapy still plays an important role in the management of diseases, mainly among low-income populations of African and Asian extraction. In developing countries like Nigeria, the World Health Organization (WHO) recommended the initiation of programs designed to use medicinal plants more effectively in traditional health care systems 2 .
Development of Behavioral Based System from Sports Video

-A system for detecting and analyzing behavior of a sports person from their facial expression extracted from a sports video from the basis of this project . Shot Segmentation, Object Frame Selection, Image Segmentation, Facial Feature Extraction and Facial Expression Recognition (FER) are the major steps included in developing Cognitive Analysis of Facial Expression Recognition system from Sports Video. The overall outcome involves in making the system recognize the basic expressions such as happy, sad, anger, disgust, surprise and fear along with neutral expression of a sports person.
Improving Security in Wireless Sensor Networks

: Wireless sensor networks are becoming significantly vital to many applications, and they were initially used by the military for surveillance purposes. One of the biggest concerns of WSNs is that they are very defenseless to security threats. Due to the fact that these networks are susceptible to hackers; it is possible for one to enter and render a network. For example, such networks may be hacked into in the military, using the system to attack friendly forces. Leap protocol offers many security benefits to WSNs. However, with much research it became apparent that LEAP only employs one base station and always assumes that it is trustworthy. It does not consist of defense against hacked or compromised base stations. In this paper, intensive research was undertaken on LEAP protocols, finding out its security drawbacks and limitations. A solution has been proposed in order to overcome the security issues faced in implementing this protocol whilst employing more than one base station. The performance of the proposed solution has been evaluated and simulated to provide a better network performance.
WYMIARY DOŚWIADCZEŃ W USŁUDZE EDUKACYJNEJ W SZKOLNICTWIE WYŻSZYM

Artykul przedstawia wyniki badania ilościowego (ankieta), na podstawie ktorego zidentyfikowane zostaly moduly doświadczen w usludze edukacyjnej w szkolnictwie wyzszym. W ich sklad wchodzą wymiary: intelektualny, relacyjny (2 moduly), behawioralny (2 moduly), emocjonalny i sensoryczny. Ponadto zweryfikowano związek wyroznionych modulow z lojalnością studentow wobec uczelni i postrzeganiem jej wizerunku. Związek ten najsilniejszy jest dla modulow intelektualnego i emocjonalnego. W koncowej cześci artykulu zawarte są praktyczne implikacje wynikające z badania.
Pose-Invariant Face Recognition on Video with Image Super-Resolution Krishnasree

: TheVideo-based face recognition has received major consideration in the past few years. However, the facial images in a video sequence attained from a distance are normally small in size and have low visual quality. The small size images make the recognition task difficult in real world applications and affect the accuracy of face tracking. Also it usually contains significant pose variation, which significantly reduces the performance of frontal face recognition. Here proposes a face identification framework capable of handling the full range of pose variations and uses learning-based single image super resolution(SISR) method to obtain a high resolution (HR) face image from a single given low resolution (LR) face image. This system first extracts the face image from the video sequence and perform super resolution. Then converts the problem of pose-invariant face recognition into a partial frontal face recognition problem. The feature transformation degrades recognition ability by transforming the features from the gallery and probe images to a general discriminative subspace. Finally, face matching is performed.
Methodology and Algorithms in Data Mining

-With this paper, the construct of information mining was summarized and its significance towards its methodologies was illustrated. The data mining supported Neural Network and Genetic rule is researched well and therefore the key technology and ways in which to realize the information mining on Neural Network and Genetic rule also are surveyed. This paper conjointly conducts a proper review of the realm of rule extraction from ANN and GA.
Optimization of cold rolling mill process to improve productivity and Product Quality of steel-an overview

There are many advances on metal rolling technologies over the past half century, but due to intense global competition and the requirements for increasingly thinner, higher quality rolled metal products continue to force metal producers to seek new ways to outperform one another. The need to optimize cold rolling mill to achieve profitability, and the significant costs associated with capital upgrades, mean that the application of innovative rolling technologies presents the most attractive near term solution for many steel manufacturer to improve quality and productivity. Set-up generation or pass schedule is an important aspect in the operation of Single stand reversing and tandem cold rolling mills. It defines speeds and powers for the drives, stand reductions, roll forces and entry & exit tensions and % reduction in each pass for the cold mill control system. This paper focuses on the various optimization techniques used in cold rolling mill process to achieve productivity and Quality of steel through literature review. Various Process models for cold rolling mills have been intensively developed in the last years, hoping to increase quality of steel strip and productivity of rolling processes. Nevertheless, characteristics are only achieved using models sufficiently to be accurate and robust. The availability of accurate models is associated for cold rolling process parameter optimization, has been intensely explored
ENHANCING PEDAGOGY WITH CONTEXT AND PARTNERSHIPS: SCIENCE IN HAND

Two activities, one on heat/work and one on dynamic equilibrium, are described for three high school classes (n=55) in the USA. The curriculum addressed showcases strategies to use with science, technology, engineering, and mathematics (STEM) students. The two lessons described follow the context ACS method (Application, Career opportunities, and Societal impact). ACS, or real-world context application, relies on a strong foundation of teaching concepts while developing enhanced learning experiences for K-12 students. The research described probes the problem of student engagement and content learning in STEM coursework and provides evidence for the potential of utilizing context ACS. The activities demonstrate how to use ACS to maximize student engagement and emphasize formative assessment during lesson implementation. Analysis of the data shows that students exposed to ACS lessons drawing from partnerships to connect real-world applications to core content make gains of 17% in aggregate. Key words: context learning, engineering, partnerships, science education, STEM education.
Verifying the Robustness of Text-based CAPTCHAs offered by Local E-Commerce Sites

CAPTCHAs are extensively used on the internet in order to distinguish between humans and bots. Numerous design alternatives of CAPTCHAs are introduced in last decade or so but still Text-based CAPTCHAs are most prevalent on the web due to its easy implementations. Text-based CAPTCHAs offer distorted text in images. The users are asked to read the text in order to prove them as humans. Although this is a trivial task for humans but it is still difficult for machines to decode such distorted characters with background clutter. The main challenges involved are preprocessing, segmentation and recognition. In this research, we have attempted to verify the robustness of CAPTCHAs offered by local e-commerce sites of Pakistan. We have successfully decoded the CAPTCHAs offered by these sites. Our proposed algorithms achieved promising results on all attacked CAPTCHAs. Using our thresholding methods, CFS, Recognition based segmentation methods and machine learning techniques; we have successfully decoded the said CAPTCHAs with an overall precision of up to 82.4%.
Fuzzy analysis for M/M/C finite capacity queueing model

In this paper we show that queueing theory can accurately model the flow of in-patient in hospital. Further Robust Ranking technique is used to find the expected mean queue length and waiting time in queue. The numerical results for Lq and Wq are calculated under fuzzy environment. Further, the analytical results are also numerically verified for Lq and Wq.
Music Genre Classification using SVM

:- Automatic music genre classification is very useful in music indexing. Tempogram is one of the feature extraction method uses in classification of musical genre that is based temporal structure of music signals. Searching and organizing are the main characteristics of the music genre classification system these days. This paper describes a new technique that uses support vector machines to classify songs. Support vector machines classify audio into their respective classes by learning from training data. The proposed feature extraction and classification models results in better accuracy in music genre classification.
International Journal of Advance Research in Computer Science and Management Studies

: Ontology is the currently emerging for representing the context domain. Ontology is one of the techniques for describing the knowledge and for finding the relationship between the concepts. In semantic web Technology, for specifying relationship between the concepts the ontology is one of the tools used. For achieving the interoperability between the existing different ontologies in both the heterogeneous and heterogeneous environment uses onto-matching, this is the fundamental method. The ontology uses the language known as Owl (web Ontology language). OWL is used to explicitly represent the meaning of the terms and the relations between the terms. The goal of this paper is to provide the brief survey about ontology and ontology mapping approaches.
Honeypot: Concepts, Types and Working

- In couple of decades number of attacks on IT organization has increased. Among them small and medium sized organization’s risk is higher because of lower security architecture in their system. Attackers use SQL injection and XSS type of attacks to exploit the vulnerability of the system or the organization. A mechanism which is created to learn about the attackers’ method of attack and pattern and also used to get useful information about the intrusive activity is Honeypot. Honeypots can be classified according to the level of interaction as low-interaction, medium-interaction, high-interaction and the purposed for which it is used as research honeypot and production honeypot. Detailed study about the types of honeypot is included in this paper. Various honeypot results are enlisted in this paper to show that how honeypot works in real-time environment and how it responds when any unwanted activity occurs in the network
Yield and yield components of local cowpea (Vigna unguiculata L.) landraces grown in mixed culture with maize (Zea mays L.) in vertic cambisols in the Northern part of Tanzania

Intercropping, one of the cropping systems in developing countries,1,2 is a practice by smallholder farmers of cultivating two or more crops in the same space and time,3 with a view to minimize risks of crop failure due to weather variability. With this type of cropping system all the environmental resources are utilized for the maximization of crop production and productivity.2,4–10 In Tanzania and elsewhere in the tropics, intercropping is mostly practiced by small scale farmers characterized by subsistence agriculture, low agricultural mechanization, high labour and low yield farming on small parcels of land.11 Since intercropping has been reported to increase both the amount of biomass, crop yield per unit area of land harvested and crop failure mitigation,12,13 farmers in the area practices mixed culture systems with a view that if one crop fails during the cropping season due to unequal distribution of rainfall and variability the other intercrop will be available for the household. According to Rusinamhodzi et al.14 intercropping can support increased aggregate yields per unit input, and thus ensure improved soil quality, food security and poverty alleviation through increased income. Several other benefits with regards to intercropping has been highlighted as increased land use efficiency; light capture and its use,15 soil moisture and nutrients; controlling weeds, insects, and diseases,16 increase in the length of production cycles; improved seed quality and better control of water quality through minimizing the use of inorganic N fertilizers, replacing them by the use of legumes.17 Typically this cropping system include maize (Zea mays L), millet (Pennisetum glaucum L) and sorghum (Sorghum bicolor L) as cereal crops components and beans (Phaseolus vulgaris), cowpea (Vigna unguiculata L), groundnut (Arachis hypogaea), pigeonpea (Cajanus cajan) and soybean (Glycine max) as legume crops components. However, in this study maize was intercropped with different types of cowpea local variety as used by local farmers. It has been shown that leguminous plants can benefit the intercrop cereals during the same season through N excretion and nodule decomposition,18 although according to Senaratne et al.19 each legume specie has different ability to supply N to its corresponding associated cereal neighbor. It is similarly assumed that intercropping cereals with legume crops, is that the legume, when associated with
FDI and ICT effects on productivity growth in Middle East countries

Economic growth theories predict that economic growth is driven by investments in Information and Communication Technology (ICT). In this paper we studied the effects stemming from Foreign Direct Investment (FDI) and Information and Communication Technologies (ICT) on productivity growth. The analysis is based on panel data covering Middle East countries during the period 1990–2010. The growth accounting results indicate that the growth contribution of ICT and FDI was quite low this countries. The econometric results showed a positive and significant impact of ICT and FDI in these countries. Keywords: FDI, ICT, growth, productivity, economic development.
The static synchronous compensator (STATCOM) using voltage source inverters has been accepted as a competitive alternative to the conventional static VAr compensator (SVC) using thyristor-controlled reactors STATCOM functions as a synchronous voltage source. It can provide reactive power compensatio

44 Abstract—This paper proposes a transient stability improvement using hybrid controller design for STATCOM with static synchronous time critical error and better damping system oscillations after a short circuit fault. This article on a STATCOM Control for transient stability improvement has proposed a hybrid system with fuzzy and neural controller to meet with the addition of Lyapunov stability criterion to the ability and conditions as well. The performance is analyzed using digital simulation with (SMIB) with infinite bus.
Semantic Relation Based-Ranking Approach for Web Search Engines

—The majority of Semantic Web search engines retrieve information by focusing on the use of concepts and relations restricted to the query provided by the user. In this paper, we propose a relation-based page rank algorithm to be used in conjunction with Semantic Web search engines that simply relies on information that could be extracted from user queries and on annotated resources. Relevance is measured as the probability that a retrieved resource actually contains those relations whose existence was assumed by the user at the time of query definition.
Internet of things based sensing system for substation automation in smart

Substation Automation is a key concept in Smart Grid Technology. The present work proposes an Internet of Things (IoT) based system for the monitoring, visualization, storage and analysis of sensor data in an easy, cost effective and reliable manner. MQ Telemetry Transport (MQTT) protocol is used to communicate and transfer data between different sensor nodes using Raspberry Pi 3 as the MQTT broker. The sensor nodes are capable of wirelessly transferring the sensor data using an Arduino Uno and ESP8266. The sensor data can be conveniently accessed by any device on the network from the MQTT broker by subscribing to it. The given sensing system intends to complement and enhance the capabilities of the present substation automation environment. It incorporates the possibility of remote accessibility and better data analysis of the sensor data in the Substation environment. An Arduino a part of the ongoing implementation of the system which will be described in further works.
Recent status of Spark Assisted Chemical Engraving: A Review

The Electrochemical Discharge Machining (ECDM) is an advance technology; it has ability to machine some electrical nonconductive materials such as ceramics and glass. The Spark Assisted Chemical Engraving (SACE) technology is based on ECDM phenomenon. SACE is a process of glass machining by using electrochemical discharges, it gives smooth surface and high aspect ratio. The Spark Assisted Chemical Engraving has a broad range of applications in the field of MEMS interfacing, micro fluidic devices and microfactories. In this paper overall developments of SACE are reviewed up to present date with special reference to the electrochemical trends.