Miracle-dz/UniFAR-FTUs huggingface dataset:
Protein Recovery From Shrimp Waste Using Aqueous Two Phase System: Effect Of Process Parameters On Partitioning Using Response Surface Methodology

Extraction by aqueous two phase system is a powerful technique for separation, concentration, and purification of biomolecules. In the present study, the partitioning of protein from shrimp waste in aqueous two phase system of PEG/ potassium citrate has been investigated. The influence of molecular weight, pH, and NaCl concentration had a pronounced effect on the partition behavior of protein and hence it is studied. The protein partitioning decreases on increasing the molecular weight of PEG, whereas the partitioning increases with an increase in pH and NaCl concentration. This has been attributed to strong electrostatic interactions between the proteins and the polymer and is also related to exclude volume effects. The optimal conditions of the process were investigated using central composite design based on 2 full factorial designs. The best conditions of partitioning were achieved using ATPS composed of PEG 4000, sodium citrate salt, pH8, 1M Addition of sodium chloride, and 40 Tie Line Length. The maximum percentage yield of protein extracted from shrimp waste was found to be 83.64%. This work has presented the potential application of ATPS processes for the recovery of protein from shrimp waste, as an initial purification step in the development of a biotechnological process with commercial application.
Fungal Viruses: Promising Fundamental Research and biological Control agents of Fungi

Viruses that selectively infect fungi are named mycoviruses. Mycoviruses, which were discovered late, haven’t got the same attention as plant and animal viruses probably because most mycoviruses cause symptomless infections. The first report on mycovirus was published in 1962 [1] but to date, they have been isolated from all major taxonomic groups of fungi. Mycoviruses are mainly discovered by nucleic acids isolation and sequencing and characterized by comparisons between mycovirus-infected and free fungal strains. The origins of mycoviruses remain uncertain and some hypotheses are proposed. Our knowledge of mycoviruses is slowly but steadily accumulating.
Cross-correlation Based Algorithm for Fingerprint recognition Using MATLAB

 Abstract — This paper is a study and implementation of a correlation-based fingerprint recognition algorithm which is based on pixel values of images. This algorithm directly uses the gray-scale information of the fingerprints. The correlation-based fingerprint algorithm selects template, Pixel values of template is correlate with pixel values of all N number of images in existing database and looks for the maximum value in correlated data which is greater than some threshold value. Maximum value among correlated data gives the appropriate match of template from existing images in database. This paper involves implementation of cross-correlation based algorithm using MATLAB.
One Time Password Generation for Multifactor Authentication using Graphical Password

— Single factor authentication such as password authentication is no longer considered as secure in the Internet world. There is a rapid growth in demand for strong authentication on the highly critical web-based applications. A higher level security mechanism is needed to access the financial and banking applications. Existing system provides authentication mechanism based on the static password, personal identification number (PIN) etc. These methods are vulnerable against eavesdropping and replay attack. In this work, a two factor authentication scheme is proposed for user authentication. The presented scheme generates dynamic password for two factor authentication. This scheme will provide user assurance of authentication and will improve authentication level. The proposed scheme provides strong protection against cryptanalysis.
COMPARATIVE EVALUATION OF BLEB SCORES AND CENTRAL ANTERIOR CHAMBER DEPTH IN TRABECULECTOMY WITH CONVENTIONAL SUTURES VERSUS RELEASABLE SUTURES

Purpose: mainstay of surgical management. postoperative period and their resulting visual anterior chamber depth along with bleb scores in patients undergoing trabeculectomy with conventio Methods diagnosis of primary open angle glaucoma or primary angle closure glaucoma. The age of the patients in the study ranged from 40 females in the study. Group A: Group B: kept on a regular follow up for a minim on day1, Results: mean percentage fall from preoperative IOP was comparable on foll groups. increasing over the period of follow up. the two groups in the initial released, anterior chamber depth was lowest on the first postoperative day in both the group low CACD in group A(p=0.042). groups. Conclusion: as a safe and effective way to
P2P based video file swarming in Online Social Network

—this paper presents a systematic literature review of P2P VOD networking. Online social networks (OSNs) (e.g., Facebook, Twitter) are now among the most popular sites on the Web. An OSN provides a powerful means of establishing social connections and sharing, organizing, and finding content. For example, Facebook presently has over 500 million users. Unlike current file or video sharing systems (e.g., BitTorrent and YouTube), which are mainly organized around content, OSNs are organized around users. OSN users establish friendship relations with real world friends or virtual friends, and post their profiles and content such as photos, videos, and notes to their personal pages.
Prevalência, gravidade, fatores de risco e seguimento da sibilância em lactentes da região centro-sul de São Paulo, SP - Estudo Internacional de Sibilância em Lactentes (EISL)

Objectives: To study the prevalence and severity of wheezing disorders in the first year of life in infants and its relationship with medical diagnosis of asthma in the southern region of São Paulo, Brazil, employing the standardized protocol of the “Estudio Internacional de sibilancia en lactentes” (EISL) – phase 1. Methods: Parents of infants attended for routine evaluation in public health centers were interviewed in southern São Paulo. All had answered the standardized EISL’s written questionnaire between March 2005 and August 2006. Results: In this study, 1014 parents or caregivers completed the questionnaire correctly. Forty six percent of the infants had at least one wheezing episode in their first year of life, with onset at 5.0 ± 3.0 months (mean ± standard deviation), and 270 (26.6%) had three or more episodes. The use of inhaled β2-agonist, inhaled corticosteroid or leukotriene receptor antagonist, nocturnal symptoms, visits to emergency room, respiratory distress, and hospitalization due to severe wheezing were significantly more frequent in this last group. Parents of 35 wheezing infants (7.5%) reported that their children had a medical diagnosis of asthma, which was associated with the use of inhaled corticosteroids, respiratory distress and six or more wheezing episodes at the first year of life. However, less than 40% of the asthmatic infants used inhaled corticosteroids or leukotriene antagonist as specific treatment. Conclusions: The prevalence of wheezing episodes among one year-old infants living in São Paulo is high and starts early in life. Although more than 25% of infants have expressed recurrent wheezing associated with signs of severity and comorbidities, the percentage of infants identified and treated as asthma was low.
Distributed incomplete pattern matching using unsupervised weighted bloom filter

Pattern matching in distributed incomplete environment can be achieved by collecting all the distributed data at data centre and then perform pattern matching at data centre afterwards. This method will cause the problem of traffic in the network and the system may leads to bottleneck. The proposed technique solves this problem by performing pattern matching at each base station individually. When data is distributed, local data at each base station is incomplete compare to the global data. We use unsupervised weighted bloom filter algorithm (UWBF) which takes only qualified IDs and their corresponding weights from each base station and perform aggregation and verification at data centre. This method will save cost and prevent bottleneck in network. Unsupervised learning is applied here to perform pattern matching on un-trained patterns. The security in network is achieved by applying encryption and decryption techniques.
LEVERAGING CROWD SOURCING FOR EFFICIENT MALICIOUS USERS DETECTION IN LARGE-SCALE SOCIAL NETWORKS

Crowd sourcing is increasingly being used as a means to tackle problems requiring human intelligence. With the ever growing worker base that aims to complete micro tasks on crowd sourcing platforms in exchange for financial gains, there is a need for stringent mechanisms to prevent exploitation of deployed tasks. Quality control mechanisms need to accommodate a diverse pool of workers, exhibiting a wide range of behavior. A pivotal step towards fraud-proof task model is understanding the behaviors patterns of microtask workers. In this paper, we predict the prevalent malicious activity on crowd sourcing platforms and study the behavior exhibited by trustworthy and untrustworthy workers, particularly on crowd sourced surveys. Based on our analysis of the typical malicious activity, we define and identify different types of workers in the crowd, propose a method to measure malicious activity.
A Service-Based Framework for ETL Process Based on Metadata

This article studies the problems of available ETL tools firstly and introduces the service of ETL pattern based on Metadata, and then summarizes different types of Metadata and their application. And shows a comparison between current frameworks of ETL process and service-based framework, based on component distribution. According to this ETL service pattern, fundamental framework of ETL service is placed higher in the rank and many important services are studied such as Metadata management services, Metadata meaning services, form change of ETL rules, meaning process services, SQL code generation and optimization services, process control services and so on. Finally, meaning-based approach and ETL rules dependent algorithms are studied. It is proved in practice that this model and the proposed frameworks in the article can increase the effectiveness of ETL largely.
Comparison of Fuzzy Clustering Algorithms in Intrusion Detection System

– According to the growth of the Internet technology, there is a need to develop strategies in order to maintain security of system. One of the most effective techniques is Intrusion Detection System (IDS). Clustering which is commonly used to detect possible attacks is one of the branches of unsupervised learning. Fuzzy clustering algorithms play an important role to reduce spurious alarms and Intrusion detection, which have uncertain quality. This paper Compare and Review fuzzy c-means and Gath-Geva and Gustafson-Kessel algorithms in order to Intrusion detection in system .
CAPITAL STRUCTURE AND FINANCIAL PERFORMANCE OF AGRICULTURAL COMPANIES LISTED IN NAIROBI SECURITIES EXCHANGE, KENYA

This study sought to determine the influence of capital structure on financial performance of agricultural companies listed in NSE. The study adopted longitudinal research design with targeted population being the six agricultural companies listed in NSE. Secondary data was obtained from published financial statements for the period 2010-2014. Desk research instrument was used to obtain the data. Census was carried on the six companies listed in the NSE. The empirical data was analyzed using the Statistical Package for Social Sciences (SPSS), to establish the relationship between the variables for study. Pearson’s Correlation Coefficient and Multivariate Regression Analysis was used. The findings of this study showed that an increment in debt ratio will lead to an increment in financial performance, and debtequity combinations increase will lead to a significant reduction in after tax profits of the companies and capital structure affects financial performance. The study recommends that debt ratio and debt-equity to be well managed for performance to be realized.
A Survey on Coverage Problem in Wireless Ad Hoc and Sensor Networks

— A wireless sensor network (WSN) is composed of a group of small power-constrained nodes with functions of sensing and communication, which can be scattered over a vast region for the purpose of detecting or monitoring some special events.Today One of the fundamental issues in sensor networks is the coverage problem, which reflects how well a sensor network is monitored or tracked by sensors. In this paper, we formulate this problem as a decision problem, whose goal is to determine whether every point in the service area of the sensor network is covered by at least k sensors, where k is a given parameter. The sensing ranges of sensors can be unit disks or non-unit disks. We present polynomial-time algorithms, in terms of the number of sensors, that can be easily translated to distributed protocols. The result is a generalization of some earlier results where only k = 1 is assumed. Applications of the result include determining insufficiently covered areas in a sensor network, enhancing fault-tolerant capability in hostile regions, and conserving energies of redundant sensors in a randomly deployed network. Our solutions can be easily translated to distributed protocols to solve the coverage
An Optimised Approach on Object and Text Detection from Real Time Data using Histogram Equalization Technique

The initiation of artificial intelligence, gave a curious approach towards the artificial neural networks. The developers are trying to make computers think and perform tasks just like humans. Artificial Neural Networks was developed with the view in mind to make computers to do so. The machines that are to be used in the field of robotics, medicines, industry needs to be so smart that they should be able to perform the day to day tasks easily without needing the human help. Take the case of self-driven cars, it is very crucial for the AI to make out the scenario in the real time and act accordingly take the necessary actions like breaking or evading in the traffics. Since the introduction of the object detection by the AI Researchers at Facebook, it has become easier for us to identify the objects in the images. While the object identifiers can use the image identification in the still images but there is a need to identify the text in the images. The techniques can be used for identification of the objects and texts in the real time scenario also. The present work here shows that image identification can work not only for the object identification but also identifies the text in the images as well. A CLAHE algorithm is developed to identify these objects in the images and text and classify these entities into the
Response rate to vaccination against Hepatitis B virus among health care workers at St. Dominic Hospital, Akwatia, Ghana

Background: Hepatitis B is a major contributor to the burden of infectious diseases worldwide. Many preventive measures have been employed, however, active immunization with hepatitis B vaccine remains the single most important hepatitis B prevention measure. WHO recommends that all health care workers (HCWs) should be vaccinated against HBV. However, proportions of individuals do not respond to the recommended standard three dose of HBV vaccination and remain susceptible to the infection.Objectives: This study was to assess the response rate to vaccination against HBV among health care workers and to determine predictors of non-response to HBV vaccine in HCWs. Methods and Materials: A prospective study carried out at the Saint Dominic Hospital, Akwatia, involving 100 HCWs from 29 August, 2018 to 4 June, 2019. All the participants received the standard protocol of 3 intramuscular injections of HBV vaccine (Engerix B) at 0, 1, and 6 months. Qualitative and quantitative serum anti-HBs was determined 1-2 months after the last injection in order to detect the responders and non-responders.Results: Majority (54.0%) of the participants were males. The Median age of the study participants was 35 (29, 47) with age range of 2065 years. Out of the 100 HCWs 90 (90%) were responders and 10 (10%) were non-responders to hepatitis B vaccine. Nonresponders had increased odds of being female, though this was not statistically significant (COR=1.47 (0.42 5.17). Conclusion: All HCWs should undergo confirmatory testing of immune response after completion of scheduled standard HBV immunization. This will ensure safety of all HCWs against HBV infection.
A PRESIDENTIAL LEADERSHIP EFFECTIVENESS AT THE JORDANIAN UNIVERSITIES: A CASE STUDY OF THE HASHEMITE UNIVERSITY

The purpose of this study is to identify how do individuals who have worked for and with the president describe him regarding his leadership effectiveness as he led the Hashemite University during his time period, and analyze the significant differences in the university participants based on their gender (male, female) and job role (faculty member, staff). Data collection randomly selected from faculties and administrative units, the actual response rate for faculty members were (131) and staffs were (214). A 48 items survey covered the six areas of leadership effectiveness were used in the survey comprising presidential leadership effectiveness. The responses indicated that the most leadership effectiveness for the university president was for the Adaptive Change Agent, closely followed by the Innovator, the Visionary was the third, the Relationally Strong was fifth, and the Team Builder was Sixth. There was significant difference at the 0.05 level between male and female participants in the (Team Builder) in favor of male. There were significant differences at the 0.05 level between faculty members and staff participants in the (Adaptive Change Agent), (Good Fit), (Visionary) in favor for faculty members. While the significant differences at the 0.05 level between faculty members and staff participants in the (Team Builder), and (Innovator) in favor for staff.
Design and Simulation of Modified ALU Based on QLUT

: In today’s world where use of semiconductor technology is so wide area occupied by the circuit and delay are main points of concern. Interconnections are known to be main reason of the problem. With the use of multi valued logic (MVL). MVL is preferable our conventional binary logic as it gives optimum speed and better data handling capacity. In this paper we propose an ALU which is based on Quaternary logic look up table. Designed ALU is compatible with Standard CMOS technology. The Schematics are designed in S spice and simulation is done in T spice of the Tanner software.
The bidirectional capacity of bacterial antigens to modulate allergy and asthma

In recent decades, the prevalence of allergic diseases including bronchial asthma, hay fever and atopic dermatitis, has risen steadily in high-income countries. The underlying mechanisms for this phenomenon remain largely unknown. Since the natural mutation rate is low, altered environmental and lifestyle conditions are thought to play an important role. Epidemiological and clinical studies have provided indirect evidence that infections may prevent the development of atopy and atopic disease. This is referred to as the “hygiene hypothesis”. According to the hygiene hypothesis, viral and/or bacterial infections could inhibit the T-helper (Th)-2 immune response associated with atopic reactions by stimulating a Th-1 response involved in defence of bacterial infections and delayed-type hypersensitivity reactions. In particular, the prenatal period and early childhood are considered to be critical for the establishment and maintenance of a normal Th-1/Th-2 balance. On the other hand, several studies suggested that infections exacerbate established allergic diseases, e.g. bronchial asthma, airway hyperresponsiveness and atopic dermatitis. Therefore, viral and/or microbial infections and/or their products may have bidirectional effects on the development of allergy and asthma. This review will focus on recent findings related to the interaction between allergic disorders and infectious diseases, with the main emphasis on bacterial infections.
A Survey of Various Chatbot Implementation Techniques

: In today’s era of artificial intelligence in machines. With the advances in AI, machines are day by day impersonating different human traits. AI conversational entities, also known as chatbots or chatterbot, are an excellent example. Chatbots are programs capable to perform near - natural conversation with real world people. In this work, we describe and compare the evolution of chatbots from a elementary model to a highly advanced intelligent system. Chatbots or chatterbots are currently gaining a lot of popularity especially in business sector as they have the potential to automate customer services and minimize human efforts. For a typical chatbot to perfectly imitate a human dialogue, it must analyze the input given by a user correctly first and then formulate a relevant and appropriate response.
LAPLACIAN MATRIX IN ALGEBRAIC GRAPH THEORY

In this paper we turn to the spectral decomposition of the Laplacian matrix. We show how the elements of the spectral matrix for the Laplacian can be used to construct symmetric polynomials that are permutation invariants. The coefficients of these polynomials can be used as graph features which can be encoded in a vectorial manner. We extend this representation to graphs in which there are unary attributes on the nodes and binary attributes on the edges by using the spectral decomposition of a Hermitian property matrix that can be viewed as a complex analogue of the Laplacian.
Big Data Challenges and its Tools

: As number of user‟s increases data also increases. The phrase big data refers to bulk volume of data which is complicated in nature because it involves both structured and unstructured type of data which is difficult to analyze. Many different sources like social media postings, sensors which gives climate information, digital information etc contribute huge amount of data to the big data. To extract useful patterns and readable patterns from the big data it is necessary to use data mining technique. Big data stream refers to the data stream which is large in variety, veracity and velocity. Data processing is not an easy job unless of identifying, responding and locating the data hence it is more challenging and difficult it has to be done in well automated manner.
Feeding Management Practices of Small holder Turkey Farmers in the Warm Wet Tropical Environment of Imo State, Nigeria

Primary data were generated from field surveys conducted with the aid of questionnaires, personal interviews, field measurements and conversation between May and August, 2005 on the feeding management practices of 90 smaller holder turkey farmers in Imo State. All of the farmers fed their turkeys with commercial chicken feeds. Fifty (50.00%) of the farmers used chicken layer rations for their breeder turkey, another 30(33.33%) used breeder ration and 15 (16.67%) fed any ration available in the market. Sixty (66.67%) farmers did not observe influence on feed consumption, while thirty (33.33%) observed seasonal influence on feed consumption. Thirty (33.33%) each of the farmers fed their turkeys twice and thrice, while 15(16.67%) each fed theirs ad libitum and once daily. Another 45 (50.00%) each of the farmers used broiler starter and chicks mash to raise their turkey from day old to 8 weeks, while 90(100.00%) used grower ration to feed their turkey to maturity. These results proved that the small holder turkey farmers do not fully understand the nutritional requirements and appropriate feeding management of turkeys at different stages of growth. [Report and Opinion. 2009;1(4):56-58]. (ISSN: 1553-9873).