Miracle-dz/UniFAR-FTUs huggingface dataset:
Cooperative nest defense by European Starlings ( Sturnus vulgaris ) during a predatory threat

Cooperative nest defense has been documented in various passerine species. Parents typically swoop and alarm-call at any predator near their nest, often attracting predominantly male conspecifics to help with nest defense. Potential reasons for males to engage in communal nest defense include direct benefits such as deterring a predator from their own nest area, by-product mutualism (paternity uncertainty in nearby nests), reciprocity, kin selection, and quality advertisement. European Starlings ( Sturnus vulgaris ) are a semicolonial and gregarious cavity-nesting passerine with biparental care. They have a mixed reproductive strategy that includes both extra-pair paternity and intraspecific brood parasitism. Therefore, both paternity and maternity uncertainty could occur in conspecific nests. Our objective was to examine whether conspecific nest defense occurred in this species, and if it did, whether both males and females participated. We exposed adult European Starlings breeding in 16 nest boxes to a taxidermy mount of an American red squirrel ( Tamiasciurus hudsonicus; experimental treatment) and a similarly sized and shaped rock (control) mid-way through the nestling period when nestlings were 11 or 12 days old. Significantly more starlings (parents and conspecifics) responded in the experimental than control trials, and they responded with a significantly higher aggregate score of defensive responses, demonstrating both the effectiveness of the taxidermy mount in eliciting defensive responses and the presence of cooperative nest defense in this species. Both males and females participated in mobbing at conspecific nests during the experimental trials. This study is the first to determine that male and female European Starlings engage in cooperative defense of conspecific nests
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The study of electrical breakdown behaviors in microgaps has drawn intensive attention around the world due to the miniaturization of electronic devices that allows electronic circuits to be packaged more densely, making possible compact computers, advanced radar and navigation systems, and other devices that use very large numbers of components. Therefore, a clear understanding of the electrical breakdown behaviors in microgaps is required to avoid the dielectric breakdown or to trigger the breakdown at microscale. This chapter introduces the significance of understanding breakdown characterization and reliability assessment for electrostatically actuated devices, magnetic recording devices, photomasks, RF MEMS switches, and micromachines and points out the derivation of the classical Paschen’s law at microscale. Then it summarizes the state-of-the-art research work on the methodology, influencing factors, dynamics, and physical mechanisms of electrical breakdown in microgaps, which is expected to expand the general knowledge of electrical breakdown to the microscale regime or more and benefits the reliability assessment and ESD protection of microscale and nanoscale devices.
International Journal of Recent Technology and Engineering (IJRTE)

The proliferation of shopping malls in virtually all economics of the world both that of the developed and developing ones can be linked to its patronage. This patronage which is gradually causing the loss of grip of the traditional market setting has been studied in line with gender, age, income, location, the image of the malls and type of shoppers amongst others. Due to the modern outfit and patronage, tenants of the malls have to be prepared for its rental payments. However, no study has specifically linked the patronage of malls with such. Therefore to achieve this aim two shopping malls located virtually in the same place were studied; the cocoa mall and heritage mall Ibadan. The study which is a cross-sectional survey entailed the distribution of copies of questionnaires to the tenants, interview with the manager of the malls and observation of frequency of shoppers to the malls. Data obtained were analyzed using the Chi-Square test of significance at 95% confidence level and it was revealed that the patronage of the malls is associated with its rental values. The researchers hereby opine that since it appears that much patronage tends to increase rental values of malls, managers are encouraged to ensure that they enhance their patronage to enjoy a marginal increase in rental payment. This will also be beneficial to tenants going by the enhanced economic returns evident in a higher occupancy rate.
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Mora Romagnola breed, one of the Italian local pig breeds, owes its name to its colour, dark brown tending to black. Currently 31 farms are registered in the herdbook started in 2001 with about 270 breeding females and 67 boars. During the 1990s, only 18 animals were left, all concentrated in one single farm. The breed was investigated within the H2020 project TREASURE, and a collection and review of available literature data on reproductive and productive traits of Mora Romagnola pig breed were carried out. The average age of sows at first parturition was 22 months, whereas age at culling was 58 months. On average, Mora Romagnola pig breed has 8.0 piglets per parity with 1.4 parities per year. Slaughter weight was on average 163 kg with a dressing yield of 80%. Few information is available for meat quality traits. Although studies on Mora Romagnola pig are scarce, the current review gives the first insight into this local pig breed.
International Journal of Recent Technology and Engineering (IJRTE)

A fusion scheme in multimodal biometric system is proposed in the name of Multimodal Feature Template Matching (MTM) system derived from the two picture fused values of average point and weighted assessment point. The main objective of MTM algorithm is to design the average point fusion and weighted average point by fusion of Iris and fingerprint features. The MTM algorithm is assigned with avgweights based on their verification accuracy. A hybrid approach of combining biometric image level information id presented. The raw information is merged at image level. This integration addressed, provides a small template and resilience to attacks. However it does not improve the recognition performance, but the performances is also less combination to its unimodal counterpart. Confidence level integration of compatible features of two different uncorrelated biometric traits fingerprint and iris provides sustainable improvement in performance accuracy compared to other integration methods as well as best unimodal system. Fingerprint and iris integration approaches presented in this proposed are more robust and reliable.
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Hormonal therapy is a major and effective tool in the treatment of prostate cancer patients. This is especially true for patients in the advanced stages of disease. Unfortunately, almost all prostate cancer cells will develop into castration‐resistant prostate cancer (CRPC) despite continued therapy and suppression of testosterone levels. Up until 5–6 years ago, there was little effective therapy for the treatment of CRPC patients. However, recently, a variety of methodologies and drugs such as cabazitaxel and sipuleucel‐T have been approved globally for the treatment of CRPC. Two novel drugs, abiraterone acetate and enzartamide, have also become available as potential treatment options. However, the anticancer effects of these two drugs are not always satisfactory in terms of prolonging survival. These drugs are also associated with adverse events and are expensive when compared with the costs of previously used anticancer drugs. In this section, we pay particular attention to hormonal therapies that do not include the use of abiraterone acetate or enzartamide. We believe that a detailed understanding of the range of currently available hormonal therapies, including their associated benefits and limitations, is important for supporting the prolongation of survival in patients with advanced prostate cancer. Therefore, this section offers a valuable discussion on the treatment strategies for prostate cancer including CRPC.
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Osteoblasts are derived from bone marrow mesenchymal stem cell (BMSC) precursors, which differentiate into mature osteoblasts and mediate bone formation. This process is called osteoblastogenesis. A deficiency in osteoblastogenesis of BMSCs can result in bone-related diseases including osteoporosis. Thus, developing drugs for targeting osteoblastogenesis from BMSCs has become one of the therapeutic strategies for osteoporosis. In China, kidney-nourishing Chinese herbal drugs such as ER-Zhi-Wan have been believed to be potential for treating osteoporosis through targeting osteoblast proliferation and differentiation. The key pathways for regulating osteoblastogenesis include canonical and noncanonical Wnt pathway, semaphorin-mediated pathway, and MAPK-mediated BMP2-Smad pathway. Some natural products have been confirmed to regulate more than one pathway and exert multi-target effect through the use of one compound or combined use of more than two compounds, such as wedelolactone and oleonuezhenide. In addition, tissue engineering provides a promising strategy in the field for targeting osteoblastogenesis. New types of biomaterials including hydroxyapatite (HAp) combined with Chinese medicine can exert enhanced effect on osteoblastogenesis and provide new therapy for treating osteoporosis.
Search Engine Optimization (SEO) in Promoting E-Commerce StartAja.com

StartAja.com is an e-commerce designed to help connecting business people who have similar interests in certain business area. Currently, StartAja.com hasn’t have digital marketing strategy yet to simplify keyword searches in promoting StartAja.com. This research’s objective is to formulate a Search Engine Optimization (SEO) strategy. By using SEO, StartAja.com is expected to be the top ranked e-commerce in search engine websites. Research data are obtained through observing the interface and functionalities of StartAja.com, and also its promotion requirements. This research has discovered the right combination of keywords to be used in SEO, to help optimize the promotion of StartAja.com.
Developing and Testing the Validity of Career Readiness-Personality (CR-P) Module for University Students

Career readiness and personality are the two main important aspects that need to enhance among the university students. Thus, the Career Readiness-Personality (CR-P) Module was developed as an intervention aim to increase the students’ career readiness and enhance their personality. The Career Readiness-Personality (CR-P) Module was developed based on The Social Career Cognitive Theory (SCCT) and Big Five Personality Model. The Social Career Cognitive Theory (SCCT) was introduced by Albert Bandura (1986) and Big Five Personality Model by McCrae & Costa (1987). This research aims to develop the CR-P Module and to determine the content validity of the CR-P Module for university students. The development of CR-P Module was based on the two sub modules known as Career Self-Efficacy and Big Five Personality. After the module development, the content validity of the module was evaluated by eight experts and the research findings showed that the value of content validity coefficient was 0.92. In conclusion, this research indicated that the CR-P Module has a high validity which can be utilized by university students.
Optimal Allocation of UPFC and IPFC in Network Considering Sensitivity of Line Flows under Single Line Contingency

This paper presents, optimal location for deployment of Unified Power Flow Controller (UPFC) and Interline Power Flow Controller (IPFC) in network considering sensitivity of line flows under single contingency. A sensitive approach is proposed which is considered based on Ranking Index (RI) and Performance Index (PI). A unitary change of power flow (PF) in each transmission line after outage of a branch element can be obtained from proposed index. The proposed Index is used to quantify loading level of network after a given outage. Contingencies are structured in descending order depending on value of proposed Index. Sensitivity factors are obtained by differentiating PF indices subject to parameters of UPFC and IPFC devices. Optimal deployment of UPFC and IPFC device is considered by the value of sensitivity factors attained by considering line outages in order of their severities which is given by proposed Index. The efficacy of proposed approach is computed and programmed on 5bus and IEEE 14bus networks under MATLAB environment.
International Journal of Recent Technology and Engineering (IJRTE)

Diabetes Mellitus is an endless glycolysis issue, where the inappropriate administration of this illness can prompt to cardiovascular sickness, kidney malady, eye infection, nerve ailment, pregnancy difficulty and Dental intricacy. The datasets, so for gathered and preprocessed, involve certain qualities which are extremely satisfactory for diabetes mellitus conclusion. The utilization of this credits needs to upgrade the preparation and test order of patients to whether the patient to endure for tablet or insulin. Data Classification could be a prime undertaking in Data mining handling. Accuracy in information grouping undertaking can help the bunching of huge dataset fittingly. In this paper we have tested and proposed a Rule Based K-Means calculation as one of the critical strategy in idealistic field for sorting diabetic patients into two classes for accomplishing better outcomes. KeywordsRule Based K-Means, SVM, Decision tree, Naïve
International Journal of Recent Technology and Engineering (IJRTE)

In financial management, the equity market performance is the critical element of equity market returns volatility wherever the shareholder’s resilience around the instability subsists. The data is collected from the authenticated secondary sources for the analysis. This paper shows that the 2008economicpredicament, as well as the effect above proceeding developing financial prudence of the globe, is found in the equity return instability connation of developing financial prudence (2004-2015). By the GARCH model, it can be examined that as the information from the U.S.A. stock market news has an essential consequences on the earnings of the S&P 500 stock market index, the indices of the east, as well as south Asian nations, has also influenced by the news of U.S.A. The GARCH model is estimated for the U.S.A. stock market news has a substantial effect or not on East and South Asian nation's daily share market returns. The outcomes show that market earnings in the equity market in east and south Asian nations are incredibly reliant on their historical earnings. It is found that Tokyo Topic (4.8929) is a highly volatile stock index among the East and South Asian stock returns, and the low volatile stock index is DSEX (0.0068). The news of the U.S.A. stock market has affected the equity market of India, Japan, China, and Korea, which are included in the East and South Asian stock market. In all the country’s share markets, found most significant variance in the equity income instability. This study is essential for the shareholders looking for the diversification in the portfolio, domestic institutional investors and foreign institutional
International Journal of Recent Technology and Engineering (IJRTE)

441 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number: B1513078219/19©BEIESP DOI: 10.35940/ijrte.B1513. 078219  Abstract: This paper presents the analytical design method for surface mounted BLDC motor to meet the performance requirements of submersible Pump for agriculture application. The design calculations involved assumption of various design variables viz. Stacking factor, leakage factor, Flux densities in stator and rotor yokes and flux density in the stator teeth etc. With these assumptions the geometry of the intended motor is derived. The geometrical information like the rotor diameter, rotor and stator thickness and stator teeth thickness etc. obtained from the analytical calculations are used as input to Finite Element Model (FEM) Analysis tool FEMAG. The Torque-Speed characteristics, back EMF, flux densities in various parts of the motor are obtained from FEM Analysis and the same are compared with the results obtained from Analytical design. Various designed parameters like airgap length, stack length and magnet widths are varied and their influence on the characteristics of the intended BLDC motor is obtained through FEM Analysis. Based on the analytical models and FEM Analysis the design parameters are tweaked until the desired performance for the agriculture pump is accomplished.
A Novel Categorical Data Attribute Split Technique in Decision Tree Learning

A new technique is proposed for splitting categorical data during the process of decision tree learning. This technique is based on the class probability representations and manipulations of the class labels corresponding to the distinct values of categorical attributes. For each categorical attribute aggregate similarity in terms of class probabilities is computed and then based on the highest aggregated similarity measure the best attribute is selected and then the data in the current node of the decision tree is divided into the number of sub sets equal to the number of distinct values of the best categorical split attribute. Many experiments are conducted using this proposed method and the results have shown that the proposed technique is better than many other competitive methods in terms of efficiency, ease of use, understanding, and output results and it will be useful in many modern applications.
International Journal of Recent Technology and Engineering (IJRTE)

Leadership as a leader factor can influence in moving employees to achieve organizational goals. In this study examines the problem of how the characteristics of transformational leadership and the extent of its impact can foster employee commitment to achieve organizational goals. By using qualitative research methods, it is expected to be able to discuss issues that are examined more broadly and in depth. Based on the research method, it can be explained that the transformational leadership characteristics of the Regional Head of Cimahi City, West Java, Indonesia through ideal influence, inspirational motivation, intellectual stimulation, and individual consideration can foster employee work commitment in achieving organizational goals. The Cimahi Regional Head in his transformational leadership is able to correlate and integrate transformational leadership characteristics (ideal influence, inspirational motivation, intellectual stimulation, and individual consideration). The regional head can build and grow the work commitment of subordinates, even exceeding what is expected, which has innovation and creativity in achieving organizational
International Journal of Recent Technology and Engineering (IJRTE)

Late years witness the improvement of distributed computing innovation. With the hazardous development of unstructured information, distributed storage innovation improves advancement. Notwithstanding, in current stockpiling pattern, client's information is completely put away in cloud servers. At the end of the day, clients lose their privilege of control on information and face security spillage chance. Conventional security assurance plans are normally founded on encryption innovation, yet these sorts of strategies can't viably oppose assault from within cloud server. So as to take care of this issue, we propose a three-layer stockpiling structure dependent on mist registering. The proposed structure can both exploit distributed storage and secure the protection of information. By at that point, we can place a little piece of information in neighborhood machine and mist server so as to ensure the security. In like manner, in context on computational information, this tally can figure the assignment degree put aside in cloud, darkness, and near to machine, autonomously. Through the theoretical security appraisal and primer assessment, the good judgment of our course of action has been supported, which is actually a historic Added to current dispersed amassing plot.
Prediction of Onset of Diabetes using Adaptive Boosting

Diabetes is one of the most common diseases, as per the survey in 2015, 30 million people in US are suffering from this disease, i.e about 90-95 percent of the population. If diabetes is untreated at the early stages, high blood glucose in the body leads to various other health problems like: eye problems, stroke, nerve damage, heart disease, stroke etc. Technology has seen an explosive growth in the development and use of Artificial Intelligence in various domains. The increased sophistication and capabilities of these tools are unlocking new possibilities in fields of Medicine, Agriculture, Manufacturing and Automobiles. The goal of this work is to predict the onset of diabetes using Machine Learning namely Adaptive Boosting. Boosting is a technique wherein a series of low accuracy classifiers are combined to create a high accuracy classifier. In many areas the problems are so complicated that simple algorithms such as KNN, Decision Tress are incapable of making predictions. Hybrid algorithms such as Random Forests and Gradient Boosting are gaining popularity due to these reasons are used by multinational companies one example being Netflix. In this work Decision Tree and Support Vector Machine methods has been considered with eight important attributes namely, Pregnancies, Glucose, Blood Pressure, Skin Thickness, Insulin, BMI, Diabetes Pedigree Function, Age and predicts if a person has diabetes. Multiple models are built using decision tree and support vector machine without Adaptive Boosting and with Boosting technique and the results are compared and evaluated. Result shows that support vector machine gives an improved overall accuracy of 80%.
International Journal of Recent Technology and Engineering (IJRTE)

Diabetes mellitus is defined as a one of the chronic and deadliest diseases which combined with abnormally high level of sugar (glucose) in the blood. The classification technique helps in diagnosis the symptoms at starting stages. This paper focused to prognosticate the chance of diabetes in patients with extremely correct classification of Diabetes. The classification algorithms viz., Naïve Bayes, Logistic Regression, and Decision Tree can be used to detect diabetes at an early stage. The algorithm performances are evaluated based on various measures like Recall, Precision, and F-Measure. Experiments are conducted where the time complexity of each of the algorithm is measured. Accuracy is also measured over correct classification and misclassification instances, observed that a Logistic Regression algorithm has much better performance when compared to the other type classifications. Using Receiver Operating Characteristic curves the results are verified in a systematic manner.