Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of a herbal hepatoprotective product on drug metabolism in patients of cirrhosis and hepatic enzyme function in experimental liver damage

A compound herbal product, mixture of 6 herbs, advocated as a hepatoprotective and hepatocorrective agent was investigated to determine its efficacy on various hepatic enzyme functions. Since chronic hepatocellular disease is known to be associated with impaired hepatic drug metabolism, the extent of restoration by the product, if any, in hepatic drug metabolising capacity of patients of cirrhosis was studied by estimation of serum antipyrine half-life. In patients of cirrhosis 3 weeks oral treatment with this compound reduced antipyrine half-life significantly (P 0.001) from 29.3n 1 1 h, to 17.9n 0.9 h after treatment. In experimental carbon tetrachloride induced acute and chronic liver damage in rats, pretreatment with this product was effective in inhibiting triglyceride accumulation in hepatic cells and in protecting the liver against increase in hydroxyproline content.
On automatically classifying software code review feedback in the context of internal quality

Recent empirical studies show that the practice of peer-code-review improves software quality. Therein, the quality is examined from the external perspective of reducing the defects/failures, i.e., bugs, in reviewed software. There is a very little to no investigation on the impact of peer-code-review on improving the internal quality of software, i.e., what exactly is affected in code, due to this process. To this end, we conducted an empirical study on the human-to-human discourse about the code changes, which are recorded in modern code review tools in the form of review comments. Our objective of this study was to investigate the topics which are typically addressed via the textual comments. Although, there is an existing taxonomy of topics, there is no automatic approach to categorize code reviews. We present a machine-learning-based approach to automatically classify the proposed code changes into its appropriate topic. We applied this approach on 468 code review comments of four open source systems, namely eclipse, mylyn, android and openstack. The result show that Textual and Organization categories are dominating topics. In an attempt to verify these observations, we analysed the code changes that developers performed on receiving these comments. We identified several refactorings that are congruent with the topics of review comments. Refactorings are mechanisms to improve internal structure of the code. Therefore, our work provides initial empirical evidence on the effectiveness of peer-code-review on improving internal software quality.
Evaluation of Decellularized Matrix and ß-Tricalcium Phosphate as Biomaterials for Bone Neoformation: In vivo Study

The aim of this study was to evaluate histologically the effect of two biomaterials, a biomaterial derived from porcine Urinary submucosa Bladder Matrix (UBM) and beta-TriCalcium Phosphate ( β-TCP), on bone defects. Twenty male New Zealand rabbits were used; the models were divided in two groups: the UBM group; the β-TCP group, and a Negative Control (NC) group. Fivemm defects were created in the femur of each model and then the different biomaterials were set in place depending on each grou p. At 4 and 8 weeks, the animals in the models were sacrificed and samples of the defect site were collected to perform a Hematoxylin a nd E sin stain (H&E). Histologically, β-TCP group at 4 and 8 weeks presented neoformation of bone-like and cartilage-like tissue, with the presence of inflammatory infiltrate; at 4 and 8 weeks, the UBM group presented neoformation of bone-like and cartilage-like tissue with a low presence of inflammatory infiltrate, and the NC group presented the formation of connective tissue and, in a low proporti n, neof rmation of bone tissue and cartilage. Both biomaterials, UBM and β-TCP, exhibited the capacity to promote bone neoformation; however, the UBM-based biomaterial produced a better-organized tissue with a lower inflammatory response compared with the β-TCP group.
Comparison of Gaze Cursor Input Methods for Virtual Reality Devices

ABSTRACT Virtual reality (VR) devices have recently become popular; however, research on input methods for VR devices is lacking. The main input methods of current commercial devices can be classified into two categories: manual selection using a controller and gaze selection. This study aims to derive the optimal input method and timing for VR devices by analyzing the performance of these input methods. A study is conducted in which participants wear a VR headset and select an activated input button from a 3 × 3 array on a VR device with two button sizes and two input methods. The manual selection method exhibits a shorter task completion time but a greater error number compared to the gaze selection method. For the gaze selection method, the task completion time and target search time were shortest when the gaze timing was 1 s. Further, the button size was determined to be statistically significant only when the manual selection method was used. The results of this study can be used as a reference in future VR user experience and product design.
Implementation and Evaluation of Analog-PIR-Sensor-Based Activity Recognition

: These days, smart home applications such as concierge service for residents, home appliance control, and so on are attracting attention. To realize these applications, we need a system which recognizes various human activities accurately with a low cost device. There are many studies on the activity recognition in a smart home. We also have proposed an activity recognition technique in a smart home by utilizing digital-output-PIR (passive infrared) sensors, door sensors, and power meters. However, the study has an unsolved issue: we cannot distinguish similar activities happening at the same place, for example, “eating” and “reading” while sitting on a sofa. In order to cope with this challenge, we introduce ALPAS: analog-output-PIR-sensor-based activity recognition technique which recognizes the di ﬀ erent activities in the same place. Our technique recognizes user’s activity by utilizing machine learning with frequency components of the sensor’s output as features. However, because the number of features used in ALPAS is 1000 for each analog PIR-sensor, a large capacity memory is required. To reduce the number of features, we select a part of the sensing data. We call the starting point of the selected data as starting frequency (SF) and ending part as ending frequency (EF). We searched SF and EF using a grid search, and evaluated the recognition accuracy. We evaluated the proposed technique in a smarthome testbed. In the evaluation, ﬁve participants performed four di ﬀ erent activities while sitting on a sofa. As a result, we achieved F-Measure: 63.9% when the EF is 1.4Hz, and F-Measure: 50% or lower when the SF is 9.9Hz or higher.
AİLELERİN EĞİTİM SÜRECİNE KATILIMINA YÖNELİK MODELLER VE YAKLAŞIMLAR

O rencilerin toplumsal ya amda ba arili olabilmeleri ve kar ila tiklari problemlerin ustesinden gelebilmeleri icin okullarin velilerle i birli i icinde cali malari gerekir. Bu ara tirmada veli katilimini artirmaya yonelik literaturde yer alan model ve yakla imlari hakkinda bazi bilgiler verilmi tir, Veli katilimini artirmaya yonelik rehberlik ekilleri, ebeveynlerle ileti im ve etkile im bicimleri gibi bir dizi konunun oneminden bahsedilmi tir. Velilerle i birli inin artirilmasinin cocuklarinin e itiminde kar ila tiklari guclukleri a mada sa layaca i faydalar aciklanmi tir
Participation, Class Types, and Student Performance in Blended-learning Format

For the last century, the trend towards blended-learning as a preferred instructional strategy has gained increased momentum. “Blended-learning systems combine face-toface instruction with computer-mediated instructions” (Graham, 2005). As Shibley (2010) pointed out, “A blended course involves a mixture of face-to-face activities with online activities,” and “Usually face-to-face time is reduced by 50% but reductions range from 10% 90%” (Shibley, 2010). One of the major advantages of blended-learning is to maximize student mobility in a vibrant technology and socio-economic environment. For traditional classroom teaching, there were abundant research studies revealing that the classroom attendance had a positive impact on academic performance. However, there have been less explorations of the correlation between online attendance and student learning performance (Douglas, 2008). This research was to address the question whether there were significant differences between the three levels (low, adequate, and high) of virtual attendance in newly implemented blended-learning classes, in regard to students’ academic performance measured by the end-of-term overall scores. The research resulted in significant findings between different levels of e-learning attendance in regard to students’ end-of-term overall scores in blended-learning format. The statistical results asserted that for both programming and English classes, the virtual attendance in various e-learning activities played a critical role in student performance. The pre-planned and correlation tests revealed that, for students enrolled in different types of classes delivered in blended-learning format, the level of virtual attendance served as a strong predictor of students’ end-of-term overall grades. The significance of this research is to emphasize the importance of virtual attendance in blended-learning process. Benefiting from the effective prediction of students’ success based on their level of attendance, the findings in this research will help students themselves, student academic advisors, student finance advisors, professors, and academic administrators, to closely monitor all students’ onsite and virtual attendance records in blended-learning classes. Reducing every single failure in every single class can speed up student’s degree-completion by a time increment, resulting in a reduction in student tuition and fees, improving the time-to-degree cycles, help student’s entrance into P ge 22141.2 the labor market faster, and substantially increase student’s life-time earnings (Crede et al., 2010).
What does your Facebook profile reveal about your creditworthiness? Using alternative data for microfinance

Abstract Microfinance has known a large increase in popularity, yet the scoring of such credit still remains a difficult challenge. Credit scoring traditionally uses socio-demographic and credit data, which we complement in an innovative manner with data from Facebook. A distinction is made between the relationships that the available data imply: (1) LALs are persons who resemble one another in some manner, (2) friends have a clearly articulated friendship relationship on Facebook, and (3) BFFs are friends that interact with one another. Our analyses show two interesting conclusions for this emerging application: the BFFs have a higher predictive value then the person’s friends and secondly, the interest-based data that define LALs, yield better results than the social network data. Moreover, the model built on interest data is not significantly worse than the model that uses all available data, hence demonstrating the potential of Facebook data in a microfinance setting.
Anticipating the Internet: how the predictions of Paul Otlet, H.G. Wells and Vannevar Bush shaped the Digital Information Age

2 Acknowledgements . 4 List of figures . 5 Introduction . 6 Aims and objectives . 6 Scope and definition . 7 Preliminary literature review . 7 Research project design . 9 Methodology . 9 Work plan . 9 Resources . 10 Ethics and confidentiality . 10 I – Paul Otlet . 12 Life and works . 12 Predictions and analysis . 16 II – H.G. Wells . 22 Life and works . 22 Predictions and analysis . 24 III – Vannevar Bush . 29 Life and works . 29 Predictions and analysis . 31 Further analysis . 35 Comparison of predictions . 35 Influence on the creation and development of the Internet . 39 Conclusions . 42 Answers to research questions . 42 Evaluation of research project . 43 Suggestions for further research . 43 References . 44 Appendix I – Reflection . 51 Appendix II – Original research proposal . 52 Dominic Allington-Smith LIS Dissertation Project (INM363)
Experiencing Responsive Technology in a Mixed Work: Interactive music as embodied and situated activity

How is performing with responsive technology in a mixed work experienced by performers, and how may the notion of embodied cognition further our understanding of this interaction? These questions are addressed here analysing accounts from singers performing the author’s mixed work Metamorphoses (2015). Combining semi-structured interviews and inspiration from Interpretative Phenomenological Analysis, questions concerning the ‘self’ when listening, singing, moving and relating to fellow musicians, as well as the relationship towards the computer, are explored. The results include a notion of the computer as neither separated nor detached but both, and highlight the importance of the situation, including not only the here and now but also social and cultural dimensions. The discussion emphasises the role of sensorimotor interaction and bodily experience in human meaning-making.
Factors of Spatial Visualization: An Analysis of the PSVT:R

The Purdue Spatial Visualization Test: Visualization of Rotations (PVST:R) is among the most commonly used measurement instruments to assess spatial ability among engineering students. Previous analysis that explores the factor structure of the PSVT:R indicates a single-factor measure of the instrument. With this as a basis, this research seeks to examine the psychometric properties of the test. This paper presents the findings of single and multi-factor analyses of the PSVT:R given to 335 students enrolled in an introductory engineering design graphics course. Initial analysis did not support a single factor solution. Further examination of pattern analyses and communalities are suggestive of the possibility that the PSVT:R may load on multiple factors. The magnitude of the variance is not explained by a single factor and whether the PSVT:R can be considered a single construct measure of mental rotation ability is not supported by this study. This represents a potential divergence from the current literature and may call into question the replicability of the test’s psychometric properties.
Assessment of the Level of Knowledge and Practice on Intravenous Cannulization among Staff Nurses of Selected Tertiary Care Hospital in Dhaka City

Intravenous (IV) cannulization is common invasive procedure used in clinical practice of hospital. Intravenous cannulization is the methods of insertion of a flexible plastic device with a stylet available, inserted to the vein to administer medications, fluids of blood transfusions. The Objective of the study was to find out the level of knowledge and practice on intravenous cannulization among staff nurses of selected Tertiary Care Hospital in the Dhaka city. The study was descriptive type of cross-sectional in nature. The main study was conducted from March-August 2013 in Dhaka Medical College Hospital, Bangabandhu Sheikh Mujib Medical University, Delta Medical College Hospital, Dhaka, Bangladesh. The instruments used for the study were self-administrated questionnaire and observational checklist. A total of 290 staff nurses who met the inclusion criteria were selected from different units of hospital by using simple random sampling technique. Mean age of the respondents was 32.11±5.3 years. The majority of respondents were female (87.2%). Maximum, 94% of respondents were completed upto Diploma in Nursing. Among the respondents, 18.3%, 50%, 24.3% and 6.9% had expressed one type of IV cannula, two types of IV cannula, three types of IV cannula and 6.9% four types of IV cannula. A majority of 49.7 % had found Good knowledge level followed by 25.5% had average knowledge, 21.7% had excellent knowledge and 3.1% had poor knowledge. About 53.8 % had found poor knowledge level followed by 39.3% had average knowledge and 5.9% ad Good knowledge, whereas only 1.0% had excellent knowledge regarding indication and contraindication on IV cannulization. About 2.67% respondents had Excellent, 12% had Good, 73.33 % had Average Practice and 12% had poor practice.
Learning Analytics for Self-Regulated Learning

The Winne-Hadwin model of self-regulated learning (SRL) [27], elaborated by Winne’s [16, 18, 28] model of cognitive operations and motivation, provides a framework for conceptualizing key issues concerning kinds of data and analyses of data for generating learning analytics about SRL. Trace data are recommended as observable indicators that support valid inferences about metacognitive monitoring and metacognitive control constituting SRL. Characteristics of instrumentation are described for gathering ambient trace data via software learners use to carry out everyday studying. Critical issues are discussed: what to trace about SRL, attributes of instrumentation for gathering ambient trace data, computational issues arising when analyzing trace data alongside complementary data, scheduling and delivering learning analytics, and kinds of information to convey in learning analytics intended to support productive SRL
Signal theory and processing for burst-mode and ScanSAR interferometry

ScanSAR data provides wide swath coverage and fast revisit times at the expense of resolution. Moreover, the ENVISAT/ ASAR alternating polarisation mode uses the burstmode acquisition to map the scene quasi-simultaneous in two polarisations. Both modes are also attractive for interferometric applications, e.g. efficient topographic mapping of large areas and monitoring of large scale motions. A single-pass ScanSAR interferometer was flown during the 11-day Shuttle Radar Topographic Mission (SRTM). Repeat-pass ScanSAR data are routinely available from RADARSAT-1 and ENVISAT/ ASAR and the coming RADARSAT-2 and ALOS/ PALSAR mission will also provide ScanSAR imaging modes. This thesis provides a complete description of interferometric burst-mode and ScanSAR signal characteristics, algorithms for interferometric processing, and options for the efficient utilisation of the wide-swath data. In the course of the examinations the following problems are addressed: derivation of burst-mode interferogram expectation values, coherence, and power spectral densities; relationship of interferogram spectrum and coherence; revision of standard assumptions in SAR interferometry; Doppler centroid estimation, azimuth scanning pattern synchronisation; common band filtering and resampling in the presence of high squint; beam alignment, timing and baseline optimisation, interferogram formation, and selection of a suitable processing concept for ScanSAR data. A new fast time-variant interpolator for burstmode data is introduced and tested. Several processing options are described that exploit the flexibility of burst-mode and ScanSAR data. From the two basic processing options available (single burst and multiple coherent burst), a third, hybrid processing options was synthesised that makes efficient use of the burst-mode and ScanSAR data properties. A prototype of this processor was implemented and tested using a RADARSAT-1 ScanSAR Narrow data set. In this way, RADARSAT-1 repeat-pass ScanSAR interferometry is demonstrated. The generated digital elevation model (DEM) has quality better than DTED-1. Moreover, after interferometric processing the ScanSAR interferogram resembles a coarse resolution stripmap interferogram and, hence, possibly all applications of SAR interferometry may benefit from ScanSAR data. In particular, the data is favourable for those applications gaining from the wide swath extend and the fast revisit times or from the increase in information as for the alternating polarisation mode.
Status quo and challenge of mental health in China

Objective:This article aims to describe methodology and prevalence of mental disorder under the current status of mental health service in the new century,and to explore impact factors of prevalence of mental disorder for decreasing disease burden of mental disorder.Method:Large scale epidemiological studies on mental disorders were reviewed and the results of prevalence studies were summarized in the past decades.Results:There were different prevalence rates of mental disorders using different methodology in different regions.Needs of mental health service had increased,but resources and models of mental health services had not met the needs.Conclusions:There are challenges of improving methodology and reforming model of service in China.In order to reduce disease burden of mental disorder,mental health promotion should be advanced.
Cardio vascular outcomes trials (CVOTS) with anti-hyperglycemic agents: demystifying statistical complexities

There is an explosion of cardiovascular outcome trials (CVOTs) in the last decade or so. Each of these studies generated more questions than providing clinically useful answers. The specific aims of the study were blurred by a lot of attention directed towards secondary end points sometimes diverting our attention from the primary hypothesis being tested. One of the principle reasons behind this phenomenon has been our poor understanding of statistical analysis. This drawback resulted in a nonsystematic approach to analyzing the CV outcome trial and the resulting confusion. It is after a very long time that endocrinologists and diabetologists have found some meaning to managing diabetes after UKPDS helped us in becoming one. Instead of basking in the glory of the new found treasure and taking it forwards with intense vigor we saw our fraternity going into a shell. Criticism of the data is important as it helps in improving the trial designs further in the long run. However this should not shift our focus away from the robust positive findings at hand. This review attempts at demystifying certain aspects of statistical analysis frequently encountered in CV outcome trial and develop a personal understanding on the same instead of depending on conflicting interpretations floated at different continuing medical educations (CMEs) and Diabetes Congresses.
Monopulse radar tracking using an adaptive interacting multiple-model method with extended Kalman filters

In this paper we investigate an adaptive interacting multiple model (AIMM) tracker using the extended Kalman filter. This adaptive algorithm is based on the interacting multiple model (IMM) tracking technique with the addition of an adaptive acceleration model to track behavior that falls in between the fixed model dynamics. In previous research, we found that the adaptive model matches more closely the true system dynamics when the target kinematics lie in between the fixed models, thus improving the overall performance of the tracking system. We also showed that the AIMM outperforms other existing adaptive approaches while reducing computational complexity. In this paper, we further investigate these superior qualities of the AIMM by considering a more realistic radar-tracking scenario where monopulse radar range, azimuth, and elevation measurements are processed using extended Kalman filters in the AIMM. Here a more complex 3D simulation is implemented instead of the simplified 2D problem considered in our previous research. Again, the result how that the AIMM outperforms the classical IMM when the target is maneuvering.