LLukas22/scidocs huggingface dataset:
STUDENT ENGAGEMENT AND STUDENT LEARNING: Testing the Linkages*

This study examines (1) the extent to which student engagement is associated with experimental and traditional measures of academic performance, (2) whether the relationships between engagement and academic performance are conditional, and (3) whether institutions differ in terms of their ability to convert student engagement into academic performance. The sample consisted of 1058 students at 14 four-year colleges and universities that completed several instruments during 2002. Many measures of student engagement were linked positively with such desirable learning outcomes as critical thinking and grades, although most of the relationships were weak in strength. The results suggest that the lowest-ability students benefit more from engagement than classmates, first-year students and seniors convert different forms of engagement into academic achievement, and certain institutions more effectively convert student engagement into higher performance on critical thinking tests. ................................................................................................ ................................................................................................
Human immunodeficiency virus/acquired immune deficiency syndrome: A survey on the knowledge, attitude, and practice among medical professionals at a tertiary health-care institution in Uttarakhand, India

INTRODUCTION
Health-care professionals are trained health-care providers who occupy a potential vanguard position in human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS) prevention programs and the management of AIDS patients. This study was performed to assess HIV/AIDS-related knowledge, attitude, and practice (KAP) and perceptions among health-care professionals at a tertiary health-care institution in Uttarakhand, India, and to identify the target group where more education on HIV is needed.


MATERIALS AND METHODS
A cross-sectional KAP survey was conducted among five groups comprising consultants, residents, medical students, laboratory technicians, and nurses. Probability proportional to size sampling was used for generating random samples. Data analysis was performed using charts and tables in Microsoft Excel 2016, and statistical analysis was performed using the Statistical Package for the Social Science software version 20.0.


RESULTS
Most participants had incomplete knowledge regarding the various aspects of HIV/AIDS. Attitude in all the study groups was receptive toward people living with HIV/AIDS. Practical application of knowledge was best observed in the clinicians as well as medical students. Poor performance by technicians and nurses was observed in prevention and prophylaxis. All groups were well informed about the National AIDS Control Policy except technicians.


CONCLUSION
Poor knowledge about HIV infection, particularly among the young medical students and paramedics, is evidence of the lacunae in the teaching system, which must be kept in mind while formulating teaching programs. As suggested by the respondents, Information Education Communication activities should be improvised making use of print, electronic, and social media along with interactive awareness sessions, regular continuing medical educations, and seminars to ensure good quality of safe modern medical care.
TOM: Twitter opinion mining framework using hybrid classification scheme

Article history: Received 20 February 2013 Received in revised form 30 July 2013 Accepted 11 September 2013 Available online 21 September 2013
Plasma nutrient biomarkers are associated with waist-to-height ratio in youth with type 1 diabetes.

BACKGROUND
Plasma fatty acids (FAs) and micronutrients have been associated with central obesity in adults; however, previous studies of these associations in adults have yielded mixed results. In addition, no comparable research has been conducted among youth with type 1 diabetes (T1D).


OBJECTIVE
We investigated the cross-sectional and longitudinal associations between plasma nutrient biomarkers and waist-to-height ratio (WHtR) in youth with T1D.


METHODS
These analyses included 1324 youth aged 3-20 y at T1D diagnosis with a baseline visit in the SEARCH (Search for Diabetes in Youth) Study and a subset of 1178 of these youth with a follow-up visit an average of 23 mo (range: 16-40 mo) after their baseline visit. Plasma phospholipid FAs and vitamins were measured, and estimated desaturase activities were calculated at baseline. Anthropometric measurements and diabetes-related assessments were collected at each visit. Multiple linear regression was used to examine the association between plasma nutrient biomarkers and WHtR.


RESULTS
In cross-sectional analysis, plasma palmitic acid (P = 0.004), dihomo-γ-linolenic acid (DGLA; P = 0.017) and Δ6 desaturase (D6D; P = 0.006) were positively correlated with WHtR after adjustment of confounders. Oleic acid (OA; P = 0.002), linoleic acid (LA; P = 0.015), Δ9 desaturase 18 (D9D-18; P = 0.027), and vitamin D (P < 0.0001) were negatively correlated with WHtR after adjustment. Weight status was an effect modifier (P < 0.05). In normal-weight youth, vitamin D (P = 0.003) was negatively associated with WHtR. In obese youth, stearic acid (P = 0.037), DGLA (P < 0.0001), and D6D (P < 0.0001) were positively associated and OA (P = 0.0008), D9D-18 (P = 0.0006), and vitamin D (P < 0.0001) were negatively associated with WHtR. In longitudinal analysis, baseline linoleic acid (P = 0.018), n-6:n-3 (ω-3:ω-6) FA ratio (P = 0.029), vitamin D (P = 0.003), and vitamin E (P < 0.0001) were negatively correlated with WHtR at follow-up only in obese participants.


CONCLUSIONS
In T1D youth, plasma FAs and vitamins are associated with WHtR and are modified by weight status. These associations are particularly marked in obese youth.
Chapter 2. Map-reduce and the New Software Stack 2.2.7 Exercises for Section 2.2

one becomes available. The Master must also inform each Reduce task that the location of its input from that Map task has changed. Dealing with a failure at the node of a Reduce worker is simpler. The Master simply sets the status of its currently executing Reduce tasks to idle. These will be rescheduled on another reduce worker later. Exercise 2.2.1 : Suppose we execute the word-count map-reduce program described in this section on a large repository such as a copy of the Web. We shall use 100 Map tasks and some number of Reduce tasks. (a) Suppose we do not use a combiner at the Map tasks. Do you expect there to be significant skew in the times taken by the various reducers to process their value list? Why or why not? (b) If we combine the reducers into a small number of Reduce tasks, say 10 tasks, at random, do you expect the skew to be significant? What if we instead combine the reducers into 10,000 Reduce tasks? ! (c) Suppose we do use a combiner at the 100 Map tasks. Do you expect skew to be significant? Why or why not? 2.3 Algorithms Using Map-Reduce Map-reduce is not a solution to every problem, not even every problem that profitably can use many compute nodes operating in parallel. As we mentioned in Section 2.1.2, the entire distributed-file-system milieu makes sense only when files are very large and are rarely updated in place. Thus, we would not expect to use either a DFS or an implementation of map-reduce for managing on-line retail sales, even though a large on-line retailer such as Amazon.com uses thousands of compute nodes when processing requests over the Web. The reason is that the principal operations on Amazon data involve responding to searches for products, recording sales, and so on, processes that involve relatively little calculation and that change the database. 2 On the other hand, Amazon might use map-reduce to perform certain analytic queries on large amounts of data, such as finding for each user those users whose buying patterns were most similar. The original purpose for which the Google implementation of map-reduce was created was to execute very large matrix-vector multiplications as are needed in the calculation of PageRank (See Chapter 5). We shall see that matrix-vector and matrix-matrix calculations fit nicely into the map-reduce 2 Remember that even looking at a product …
The heterogeneous effects of training incidence and duration on labor market transitions

This paper estimates the impact of training incidence and duration on employment transitions accounting for the endogeneity of program participation and duration. We specify a very flexible bivariate random effects probit model for employment and training participation and we use Bayesian Markov Chain Monte Carlo (MCMC) techniques for estimation. We develop a simulation approach that uses the estimated coefficients and individual specific effects from the MCMC iterations to calculate the posterior distributions of different treatment effects of interest. Our estimation results imply positive effects of training on the employment probability of the treated, lying between 12 and 21 percentage points ten quarters after program start. The effects are higher for women than for men and higher in West Germany than in East Germany. Further, we find that the effect of training versus waiting underestimates the effect of training versus no training in the medium and long run by a third. Finally, our results show that longer planned enrolment lengths of three and four quarters as opposed to just two quarters lead to an increase in employment rates in the medium and long run by four to eleven percentage points.
Hazard avoidance for high-speed mobile robots in rough terrain

Abstract. Unmanned ground vehicles have important applications in high speed, rough terrain scenarios. In these scenarios unexpected and dangerous situations can occur that require rapid hazard avoidance maneuvers. At high speeds, there is limited time to perform navigation and hazard avoidance calculations based on detailed vehicle and terrain models. This paper presents a method for high speed hazard avoidance based on the “trajectory space,” which is a compact model-based representation of a robot’s dynamic performance limits in rough, natural terrain. Simulation and experimental results on a small gasoline-powered unmanned ground vehicle demonstrate the method’s effectiveness on sloped and rough terrain.
Learning Answer-Entailing Structures for Machine Comprehension

Understanding open-domain text is one of the primary challenges in NLP. Machine comprehension evaluates the system’s ability to understand text through a series of question-answering tasks on short pieces of text such that the correct answer can be found only in the given text. For this task, we posit that there is a hidden (latent) structure that explains the relation between the question, correct answer, and text. We call this the answer-entailing structure; given the structure, the correctness of the answer is evident. Since the structure is latent, it must be inferred. We present a unified max-margin framework that learns to find these hidden structures (given a corpus of question-answer pairs), and uses what it learns to answer machine comprehension questions on novel texts. We extend this framework to incorporate multi-task learning on the different subtasks that are required to perform machine comprehension. Evaluation on a publicly available dataset shows that our framework outperforms various IR and neuralnetwork baselines, achieving an overall accuracy of 67.8% (vs. 59.9%, the best previously-published result.)
Ambulatory medical care utilization estimates for 2005.

OBJECTIVE
This report presents statistics on ambulatory care visits to physician offices, hospital outpatient departments (OPDs), and hospital emergency departments (EDs) in the United States in 2005. Ambulatory medical care utilization is described in terms of patient, practice, facility, and visit characteristics.


METHODS
Data from the 2005 National Ambulatory Medical Care Survey (NAMCS) and the National Hospital Ambulatory Medical Care Survey (NHAMCS) were combined to produce averaged annual estimates of ambulatory medical care utilization.


RESULTS
Patients in the United States made an estimated 1.2 billion visits to physician offices and hospital OPDs and EDs, a rate of 4.0 visits per person annually. Between 1995 and 2005, population visit rates increased by about 20% in primary care offices, surgical care offices, and OPDs; 37% in medical specialty offices; and 7% in EDs. The aging of the population has contributed to increased volume of visits because older patients have higher visit rates. Visits by patients 40-59 years of age represented about 28.5 percent in 2005, compared with 23.9 percent in 1995. Black persons had higher visit rates than white persons to hospital OPDs and EDs, but lower visit rates to office-based primary care and to surgical and medical specialists. In the ED, the visit rate for patients with no insurance was about twice that of those with private insurance; whereas for all types of office-based care, the visit rates were higher for privately insured persons than for uninsured persons. About 29.4 percent of all ambulatory care visits were for chronic diseases and 25.2 percent were for preventive care, including checkups, prenatal care, and postsurgical care. The leading treatment provided at ambulatory care visits was medicinal with 71.3 percent of all visits having one or more medications prescribed, up by 10% since 1995 when encounters with drug therapy represented 64.9 percent of all visits. In 2005, 2.4 billion medications were prescribed or administered at these visits.
Two Asymmetrically Mirrored Gap-Coupled Loop Antennas as a Compact Building Block for Eight-Antenna MIMO Array in the Future Smartphone

A compact two-antenna building block for forming the multiple-input multiple-output (MIMO) array in the mobile device such as the smartphone is presented. The building block has a planar structure of small size <inline-formula> <tex-math notation="LaTeX">$7 \times 10$ </tex-math></inline-formula> mm<sup>2</sup> (about <inline-formula> <tex-math notation="LaTeX">$0.08\lambda \times 0.12\lambda$ </tex-math></inline-formula>) for operating at 3.5-GHz band (3.4–3.6 GHz), which is the recently identified frequency spectrum in World Radiocommunication Conference 2015 for future broadband mobile services. The building block is formed by two gap-coupled loop antennas having asymmetrically mirrored (AM) structures with respect to the system ground plane of the smartphone. The two AM antennas show good isolation thereof and their envelope correlation coefficient is much less than 0.1 in the operating band, showing very good independence of the two antennas in their far-field radiation characteristics. By using four such building blocks, an eight-antenna MIMO array at 3.5-GHz band in the smartphone is easily implemented. The channel capacity of the eight-antenna MIMO array in an <inline-formula> <tex-math notation="LaTeX">$8 \times 8$ </tex-math></inline-formula> MIMO system is calculated to be about 36 b/s/Hz with 20-dB signal-to-noise ratio. The measured channel capacity obtained using an <inline-formula> <tex-math notation="LaTeX">$8 \times 8$ </tex-math></inline-formula> MIMO measurement setup is also presented, which generally agrees with the calculated results. The obtained eight-antenna MIMO array is promising for future or fifth-generation smartphone applications.
Reasons for participating and genetic information needs among racially and ethnically diverse biobank participants: a focus group study

In order for DNA biobanks to be a valuable reservoir of genetic information, large numbers of participants from all racial and ethnic backgrounds need to be recruited. This study explored reasons for participating in a new biobank among primarily Hispanic and African American individuals, as well as their general attitudes towards genetic research, and their views on obtaining genetic tests. Focus groups were conducted with Mount Sinai Biobank participants recruited from predominantly lower income, minority communities. The topic guide included questions on The Mount Sinai Biobank, genetic research, and genetic testing. All focus groups were audio recorded, transcribed, and analyzed using thematic analysis. The six focus groups comprised 43 participants: 39 females and four males, aged 27–76 years, with a median household income category of $20,000–$39,999. Twenty-one participants were Hispanic, 20 African American, one Asian, and one White. Participants’ reasons for participating in the biobank included altruism, personal and family benefit, and general curiosity. Although there was evidence of conflation between genetic research and genetic testing, most participants held positive views of genetic research and expressed interest in receiving personal genetic test results. Participants wanted to learn more about genetic research and suggested various venues such as health fairs for disseminating information. Participation in biobanks by racial and ethnic minorities is apparently driven by altruism, and desire for personal or collective health benefits. Participants had generally positive attitudes, limited understanding of genetics and genetic research, and made useful suggestions regarding information dissemination mechanisms.
Paxos made live: an engineering perspective

We describe our experience in building a fault-tolerant data-base using the Paxos consensus algorithm. Despite the existing literature in the field, building such a database proved to be non-trivial. We describe selected algorithmic and engineering problems encountered, and the solutions we found for them. Our measurements indicate that we have built a competitive system.
A Mobile Cloud-Based Parkinson’s Disease Assessment System for Home-Based Monitoring

BACKGROUND
Parkinson's disease (PD) is the most prevalent movement disorder of the central nervous system, and affects more than 6.3 million people in the world. The characteristic motor features include tremor, bradykinesia, rigidity, and impaired postural stability. Current therapy based on augmentation or replacement of dopamine is designed to improve patients' motor performance but often leads to levodopa-induced adverse effects, such as dyskinesia and motor fluctuation. Clinicians must regularly monitor patients in order to identify these effects and other declines in motor function as soon as possible. Current clinical assessment for Parkinson's is subjective and mostly conducted by brief observations made during patient visits. Changes in patients' motor function between visits are hard to track and clinicians are not able to make the most informed decisions about the course of therapy without frequent visits. Frequent clinic visits increase the physical and economic burden on patients and their families.


OBJECTIVE
In this project, we sought to design, develop, and evaluate a prototype mobile cloud-based mHealth app, "PD Dr", which collects quantitative and objective information about PD and would enable home-based assessment and monitoring of major PD symptoms.


METHODS
We designed and developed a mobile app on the Android platform to collect PD-related motion data using the smartphone 3D accelerometer and to send the data to a cloud service for storage, data processing, and PD symptoms severity estimation. To evaluate this system, data from the system were collected from 40 patients with PD and compared with experts' rating on standardized rating scales.


RESULTS
The evaluation showed that PD Dr could effectively capture important motion features that differentiate PD severity and identify critical symptoms. For hand resting tremor detection, the sensitivity was .77 and accuracy was .82. For gait difficulty detection, the sensitivity was .89 and accuracy was .81. In PD severity estimation, the captured motion features also demonstrated strong correlation with PD severity stage, hand resting tremor severity, and gait difficulty. The system is simple to use, user friendly, and economically affordable.


CONCLUSIONS
The key contribution of this study was building a mobile PD assessment and monitoring system to extend current PD assessment based in the clinic setting to the home-based environment. The results of this study proved feasibility and a promising future for utilizing mobile technology in PD management.
Effects of exogenous methyl jasmonate in elicited anthocyanin-producing cell cultures of ohelo (Vaccinium phalae)

Elicitation of anthocyanin-producing cells of ohelo (Vaccinium pahalae) by both biotic (purified β-glucan and chitosan) and abiotic [sodium ferric ethylenediamine di-(o-hydroxyphenylacetate) FeEDDHA, and CuSO4] elicitors resulted in significant enhancement of anthocyanin accumulation. Anthocyanin production increased up to 1.8 and 1.5-fold over the control in the presence of abiotic elicitors (90 µM FeEDDHA and 20 µM CuSO4, respectively), and increased 1.9 and 1.6-fold in the presence of biotic elicitors (10 mg L−1 β-glucan and 100 mg L−1 chitosan). Maximum anthocyanin production with the two most effective elicitors was achieved when cultures were treated on Day 3 (β-glucan) or Day 0 (FeEDDHA) after the initiation of fresh cell cultures. A concentration-dependent response was exhibited by cultures treated with exogenous methyl jasmonate (MJ). The addition of 0.5 µM MJ alone provoked a 2–3-fold increase in anthocyanin production over that of the control; however, no additive effect on anthocyanin production was observed in any treatments which combined MJ and β-glucan or FeEDDHA. Conditioning of the cells with a preculture in either MJ, β-glucan, or FeEDDHA similarly did not enhance anthocyanin production. Inoculation of cultures elicited by MJ or β-glucan with ibuprofen, a reported inhibitor of jasmonate biosynthesis, dramatically stimulated, rather than inhibited, anthocyanin production, resulting in levels of accumulation beyond any of the tested elicitor combinations. Hypotheses for the observed influence of ibuprofen in this system are discussed.
The haptic display of complex graphical environments

Force feedback coupled with visual display allows people to interact intuitively with complex virtual environments. For this synergy of haptics and graphics to flourish, however, haptic systems must be capable of modeling environments with the same richness, complexity and interactivity that can be found in existing graphic systems. To help meet this challenge, we have developed a haptic rendering system that allows f r the efficient tactile display of graphical information. The system uses a common high-level framework to model contact constraints, surface shading, friction and tex ture. The multilevel control system also helps ensure that the haptic device will remain stable even as the limits of the renderer’s capabilities are reached. CR
Machine Learning for Dental Image Analysis

In order to study the application of artificial intelligence (AI) to dental imaging, we applied AI technology to classify a set of panoramic radiographs using (a) a convolutional neural network (CNN) which is a form of an artificial neural network (ANN), (b) representative image cognition algorithms that implement scale-invariant feature transform (SIFT), and (c) histogram of oriented gradients (HOG).