Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Affecting Adherence to Antiretroviral Treatment in Harari National Regional State, Eastern Ethiopia

Background. The efficacy of antiretroviral treatment (ART) depends on strict adherence to the regimen, but many factors have been identified for nonadherence. Method. To identify the factors for non-adherence to ART, a cross-sectional study was conducted on people living with human immunodeficiency virus (HIV) and attending the ART service at Hiwot Fana and Jugal hospitals; it was done from October to December, 2010. Adherence was defined as taking 95% of the prescribed doses in the week before the survey. Data were collected using a standard interview questionnaire and were analyzed using SPSS Version 16. Result. Among the 239 study participants, the magnitude of adherence to ART in the week before interview was 87%. The main reasons for nonadherence were forgetting (47.2%), traveling (18.9%), and being busy doing other things (15.1%). There was not any independent predicator identified for adherence to ART. Conclusion. Compared to other similar studies in Ethiopia, in this study a high adherence rate was found. Forgetfulness was the most common reason for the nonadherence. Therefore, the ART counseling needs to give emphasis to using memory aids. In addition, a further study on adherence rate and its determinants with multiple adherence measurements is recommended.
An Integrated Page Ranking Algorithm for Personalized Web Search

Today search engines constitute the most powerful tools for organizing and extracting information from the Web. However, it is not uncommon that even the most renowned search engines return result sets including many pages that are definitely useless for the user. This is mainly due to the fact that the very basic relevance criterions underlying their information retrieval strategies rely on the presence of query
The chaparral vegetation in Mexico undernonmediterranean climate: the convergence and Madrean-Tethyan hypothesesreconsidered.

A comparative study between an unburned evergreen sclerophyllousvegetation located in south-central Mexico under a wet-summer climate,with mediterranean regions was conducted in order to re-analyzevegetation and plant characters claimed to converge under mediterraneanclimates. The comparison considered floristic composition,plant-community structure, and plant characters as adaptations tomediterranean climates and analyzed them by means of a correspondenceanalysis, considering a tropical spiny shrubland as the external group.We made a species register of the number of species that resproutedafter a fire occurred in 1995 and a distribution map of the evergreensclerophyllous vegetation in Mexico (mexical) under nonmediterraneanclimates.The Tehuacán mexical does not differ from the evergreensclerophyllous areas of Chile, California, Australia, and theMediterranean Basin, according to a correspondence analysis, whichordinated the Tehuacán mexical closer to the mediterranean areasthan to the external group.All the vegetation and floristic characteristics of the mexical, aswell as its distribution along the rain-shadowed mountain parts ofMexico, support its origin in the Madrean-Tethyan hypothesis of Axelrod.Therefore, these results allow to expand the convergence paradigm of thechaparral under an integrative view, in which a general trend to ariditymight explain floristic and adaptive patterns detected in theseenvironments.
Determination of Original Nondegraded and Fully Degraded Magnetic Properties of Material Subjected to Mechanical Cutting

The cutting process has a substantial influence on the ferromagnetic material properties of electrical steel sheets. In this paper, the properties of the degraded and nondegraded zones result from data obtained by two Epstein frame measurements using sample strips of two different widths. The magnetic characteristics of the degraded and nondegraded material are inserted into a finite-element model, which accounts for arbitrary geometries. The simulation results for the influence of degradation on a stator lamination stack are verified by measurements at three different frequencies and two different materials.
Virtual Machine Images as Structured Data: The Mirage Image Library

The rise of infrastructure-as-a-service (IaaS) clouds, both private and public, has created new problems in managing large collections of virtual-machine (VM) images. VM images must be kept up-to-date with security patches and scanned for malicious or improperly licensed software. Because images are bulky, attention must be paid to the latencies of deployment and capture. Large collections of VM images also present new opportunities which, while not completely realized today, do not exist with collections of physical machines. Users can search for images that contain the software they want, configured as they want it. Collections can be mined for patterns in order to answer questions like “which database management systems does our company use? ” Images can be compared with one another. This paper describes Mirage, an image library that addresses these problems and opportunities and is pluggable into various clouds. Mirage stores images in a format that indexes their filesystem structure, instead of as opaque disk images. Like other libraries, Mirage provides features for image capture and deployment. In addition, Mirage maintains a provenance tree that records how each image was derived from other images; allows operations, like patching and scanning, that normally require a VM instance to execute offline; and enables analyses such as image search and comparison. Other papers have used Mirage [16, 13, 17] or described parts of the system [8]. This paper is the first overview of the complete system. It also describes three novel features that reduce the costs of translating between disk images and the Mirage format: a content-addressed store optimized for VM image data; a simple yet flexible indexer that supports a variety of filesystem and image types; and delta deployment, which uses precomputed deltas between images to speed up format conversions. Finally, we relate our experience with Mirage in the IBM Workload Deployer product (IWD) [3], which serves images to a customer’s own private cloud, and in the Research Compute Cloud (RC2) [10], which is a production IaaS cloud.
Effect of Various Feedstocks on Compost Properties and Use

Composting is a natural biological process which results in the degradation of organic waste to a stable end product, commonly referred to as compost, which can be utilized for various agricultural purposes. Increasing landfill costs and regulations which limit many types of waste accepted at landfills has increased interest in composting as a component of waste management (Goldstein and Spencer, 1990, Goldstein, 1991). Composition of waste varies from yard waste, municipal solid waste (MSW), source separated MSW, agricultural production and processing waste and various other industrial organic waste. With such diversity in waste products coupled with variation in the composting processes one would expect extreme variability in the chemical and physical properties of final product as reported by (Cook et al. 1994; He et al. 1992; Bugbee, 1994; Elwell et a1 1994).
INTER-ORGANIZATIONAL ISSUES TOWARD A "GREENER" SUPPLY CHAIN

Recent changes in environmental legislation have focused company thinking on business practices, particularly concerning the importance of integrating environmental concerns like outsourcing and procurement in supply chain networks. Supply chain partners are becoming progressively more accountable not only for their internal practices, but also for their suppliers' behavior because implementing a "greener" supply chain is far from an individual strategy. The objective of this paper is to study the difficulties that may be encountered by a focal firm with its partners from the perspective of implementing environmental practice issues, or improving these practices if they already exist. In this paper we develop an integrative conceptual framework to show the role of relationship types, contract design and clauses to coordinate the relationship between a focal firm and its supplier in the implementation of a green supply chain.
The Effect of Housing on Portfolio Choice

Economic theory predicts that home ownership should have a negative effect on risk-taking in financial portfolios. However, empirical work has not found a strong relationship between housing and portfolios. We identify two reasons for the divergence between the theory and data. First, it is critical to distinguish between home equity wealth and mortgage debt, as they have opposite-signed effects on portfolio choice. Second, it is important to isolate variation in home equity and mortgage debt that is orthogonal to unobserved determinants of portfolios. We estimate a model that permits home equity and mortgage debt to have different effects on portfolio shares. We isolate plausibly exogenous variation in home equity and mortgages by using differences across housing markets in average house prices and housing supply elasticities as instruments. Using data for 60,000 households, we find that increases in property value (holding home equity constant) reduce stockholding significantly, while increases in home equity wealth (holding property value constant) raise stockholding. Our estimates imply that the stock share of liquid wealth would rise by 1 percentage point – 6% of the mean stock share – if a household were to spend 10% less on its house, holding fixed wealth. We conclude that housing has substantial impacts on portfolio choice, as theory predicts.
Nov e l Mobile Network Service for Road Safety

-------------------------------------------------------------------- ABSTRACT --------------------------------------------------------------- This paper describes a Mobile Network Service helps Road Safety Purpose. A preprocessing steps reduces the search space in a safety way. Mobile Network Service applies Safety improvement and Location tracing, a technique that focuses the optimization on critical regions. The result indicates that the Mobile Network Services reliably identifies high quality solutions.
Tangled Web of Concept Relations. Concept relations for ISO 1087-1 and ISO 704

The paper discusses factors that are relevant when constructing a typology of concept relations for terminology work by focusing especially on ISO 704:2009 Terminology work - Principles and methods and ISO 1087-1:2000 Terminology work - Vocabulary - Part 1: Theory and application standards and their future revisions. At first prerequisites for a concept relation typology are discussed generally. The standards are then scrutinized as to how they introduce, define and classify concept relation types, and modifications are suggested. A concept relation typology is presented as an example of a comprehensive, generalizable and extendable typology.
Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout

Background Awareness campaigns are ubiquitous, but little is known about their potential effectiveness because traditional evaluations are often unfeasible. For 40 years, the “Great American Smokeout” (GASO) has encouraged media coverage and popular engagement with smoking cessation on the third Thursday of November as the nation’s longest running awareness campaign. Objective We proposed a novel evaluation framework for assessing awareness campaigns using the GASO as a case study by observing cessation-related news reports and Twitter postings, and cessation-related help seeking via Google, Wikipedia, and government-sponsored quitlines. Methods Time trends (2009-2014) were analyzed using a quasi-experimental design to isolate spikes during the GASO by comparing observed outcomes on the GASO day with the simulated counterfactual had the GASO not occurred. Results Cessation-related news typically increased by 61% (95% CI 35-87) and tweets by 13% (95% CI −21 to 48) during the GASO compared with what was expected had the GASO not occurred. Cessation-related Google searches increased by 25% (95% CI 10-40), Wikipedia page visits by 22% (95% CI −26 to 67), and quitline calls by 42% (95% CI 19-64). Cessation-related news media positively coincided with cessation tweets, Internet searches, and Wikipedia visits; for example, a 50% increase in news for any year predicted a 28% (95% CI −2 to 59) increase in tweets for the same year. Increases on the day of the GASO rivaled about two-thirds of a typical New Year’s Day—the day that is assumed to see the greatest increases in cessation-related activity. In practical terms, there were about 61,000 more instances of help seeking on Google, Wikipedia, or quitlines on GASO each year than would normally be expected. Conclusions These findings provide actionable intelligence to improve the GASO and model how to rapidly, cost-effectively, and efficiently evaluate hundreds of awareness campaigns, nearly all for the first time.
Where Do Market Categories Come From and How? Distinguishing Category Creation From Category Emergence

This paper reviews several streams of research on market category formation. Most past research has largely focused on established category systems and the antecedents and consequences of categorical positioning (i.e., categorical purity vs. spanning; combination vs. replacement) but relatively ignored the formative processes leading to new categories. In this review, we address this lacuna to posit that scholarship would benefit from clearly disentangling category emergence from category creation. We analytically describe the differences between the two and elaborate the boundary conditions that guide and define which process is more likely to occur in a given market. Our review contributes to illuminating the role of organizational agency and strategic actions in market categories and their formation, which deserve greater attention as a result of their theoretical and practical implications.
Facial Expression Recognition using Neural Network

This approach proposed a system for the recognition of the facial expression, which can be using cross-correlation of optical flow and mathematical models from the facial points. That defined these facial points of interest in the first frame of an input face sequence image, which utilized manually marker. The facial points were automatically tracked by using a cross-correlation based on optical flow, and extracted feature vectors. The mathematical model extracted features from feature vectors. We were used to classifying expressions when an ELMAN neural network was used. The performances of the proposed facial expressions recognition were computed using Cohn–Kanade facial expressions database. The proposed method achieved a high recognition rate. Keyword—facial expression recognition, optical flow, mathematical model, neural network
The effects of concentric training at two angular velocities on trained and untrained strength gains

This study aimed to determine whether the non-dominant unilateral concentric isokinetic knee extensors and flexors strength training at 60°/s and 180°/s results in speed specific strength gains in trained and untrained limb. Twenty three female kinesiology students (age: 21±2 years ; BH: 168±5 cm ; BW: 62±8 kg) were divided to slow training (STG) or fast training (FTG) group. Both groups performed a 4-week non-dominant unilateral concentric isokinetic knee extensors and flexors strength training at 60°/s and 180°/s, respectively. Statistically significant strength gains occurred in trained and untrained extremity at both angular velocities in STG, while FTG improved only trained extremity strength at both angular velocities. Repeated measures ANOVA showed there were no statistically significant differences between trained extremity effect sizes, while statistically significant differences occurred between the groups in lower velocities strength gains at untrained extremity. Unilateral concentric isokinetic training causes general and speed specific strength gains in trained and untrained extremity, respectively. Fast group showed speed specific strength gains in untrained limb.
The Persistence of African Swine Fever Virus in Field-Infected Ornithodoros erraticus during the ASF Endemic Period in Portugal

African swine fever (ASF) is an important disease of pigs and outbreaks of ASF have occurred in Europe on multiple occasions. To explore the period for which the European soft tick species Ornithodoros erraticus (Acari: Argasidae) is able to act as a reservoir of African swine fever virus (ASFV) after infected hosts are removed, we collected specimens from farms in the provinces of Alentejo and Algarve in Portugal during the endemic period and tested them subsequently using cell culture and experimental infection. We show that ticks from previously infected farms may contain infectious virus for at least five years and three months after the removal of infectious hosts. Furthermore, in two cases infectious virus was successfully isolated from ticks on restocked farms that had not yet suffered a re-emergence of disease. Experimental transmission to pigs was demonstrated in batches tested up to 380 days after an outbreak. These results clarify the epidemiological role of O. erraticus ticks in the persistence of ASFV in the field, provide additional evidence to support its role in the re-emergence of a sporadic outbreak of ASF in Portugal in 1999 and suggest that the current quarantine legislation and restocking advice when these ticks are present on the pig farm premises is appropriate.
Queen-Ant-Aware-Based Algorithm for Wireless Sensor Networks Routing

Advantages of wireless sensor networks have germinated many new applications in both military and civil domains. Many researchers are engaged in designing new protocols for sensor networks where energy awareness is an essential consideration. We identify the trends that wireless sensor networks should be maneuverable by user from Internet and propose a new algorithm that can fulfill remote information acquisition and operation through Internet, by which the user can avoid unnecessary damages from dangerous environment. In this paper we develop a new model which is fit for transmitting remote information. Additionally, we describe our queen-ant-aware-based algorithm in details and simulate this algorithm. Finally, we conclude with several open research issues of this new protocol.
Performance of Positive Buck-Boost Converter with Mode Select Circuit and Feed-Forward Techniques Using Fuzzy Logic Controller

- This project is a highly efficient & novel control strategy for improving the transient in the output voltage of a dc-dc positive buck-boost converter which is required for low portable devices. The portable devices development of semiconductor manufacturing technology, conversion efficiency, power consumption, and the size of devices have become the most important design criteria of switching power converters. For portable applications better conveniences extension of battery life and improves the conversion efficiency of power converters . It is essential to develop accurate switching power converters, which can reduce more wasted power energy. The proposed topology can achieve faster transient responses when the supply voltages are changed for the converter by making use of the feed forward network . With mode select circuit the conduction & switching losses are reduced the positive buck–boost converter operate in buck, buck–boost, or boost converter. By adding feed-forward techniques, the proposed converter can improve transient response when the supply voltages are changed. Hence Positive buck-boost converters with mode select circuit &feed forward techniques using fuzzy logic converter is designed And the modeling & experimental results were verified in MATLAB/ Simulink
Abstract—self-compacting Concrete (scc), a New Kind of High

performance concrete (HPC) have been first developed in Japan in 1986. The development of SCC has made casting of dense reinforcement and mass concrete convenient, has minimized noise. Fresh self-compacting concrete (SCC) flows into formwork and around obstructions under its own weight to fill it completely and self-compact (without any need for vibration), without any segregation and blocking. The elimination of the need for compaction leads to better quality concrete and substantial improvement of working conditions. SCC mixes generally have a much higher content of fine fillers, including cement, and produce excessively high compressive strength concrete, which restricts its field of application to special concrete only. To use SCC mixes in general concrete construction practice, requires low cost materials to make inexpensive concrete. Rice husk ash (RHA) has been used as a highly reactive pozzolanic material to improve the microstructure of the interfacial transition zone (ITZ) between the cement paste and the aggregate in self compacting concrete. Mechanical experiments of RHA blended Portland cement concretes revealed that in addition to the pozzolanic reactivity of RHA (chemical aspect), the particle grading (physical aspect) of cement and RHA mixtures also exerted significant influences on the blending efficiency. The scope of this research was to determine the usefulness of Rice husk ash (RHA) in the development of economical self compacting concrete (SCC). The cost of materials will be decreased by reducing the cement content by using waste material like rice husk ash instead of. This paper presents a study on the development of Mechanical properties up to 180 days of self compacting and ordinary concretes with rice-husk ash (RHA), from a rice paddy milling industry in Rasht (Iran). Two different replacement percentages of cement by RHA, 10%, and 20%, and two different water/cementicious material ratios (0.40 and 0.35), were used for both of self compacting and normal concrete specimens. The results are compared with those of the self compacting concrete without RHA, with compressive, flexural strength and modulus of elasticity. It is concluded that RHA provides a positive effect on the Mechanical properties at age after 60 days. Base of the result self compacting concrete specimens have higher value than normal concrete specimens in all test except modulus of elasticity. Also specimens with 20% replacement of cement by RHA have the best performance.
Generating Test Data for Dynamically Discovering Likely Program Invariants

Dynamic detection of program invariants is emerging as an important research area with many challenging problems. As with any dynamic approach, the accuracy of dynamic discovery of likely program invariants depends on the quality of test cases used to detect invariants. Therefore, generating suitable test cases that support accurate detection of program invariants is crucial to the dynamic approach for invariant detection. In this paper, we explore new directions in using the existing test data generation techniques to improve the accuracy of dynamically detected program invariants. First we discuss the augmentation of existing test suites to improve the accuracy of dynamically discovered invariants. The augmentation of the test suite may be done prior to running the dynamic analysis if the variables and expressions whose values will be monitored at runtime are known in advance. On the other hand, the dynamic analysis may be run first using an available test suite to obtain an initial guess of program invariants. These guessed invariants may then be used to generate test cases to augment the test suite. We also propose the use of existing test data generation techniques in improving the accuracy of invariants guessed using an already available test suite.