LLukas22/scidocs huggingface dataset:
Nateglinide alone and in combination with metformin improves glycemic control by reducing mealtime glucose levels in type 2 diabetes.

OBJECTIVE
To evaluate the efficacy and tolerability of nateglinide and metformin alone and in combination in type 2 diabetic patients inadequately controlled by diet, focusing on changes in HbA1c, fasting plasma glucose (FPG), and mealtime glucose excursions.


RESEARCH DESIGN AND METHODS
In this randomized double-blind study, patients with an HbA1c level between 6.8 and 11.0% during a 4-week placebo run-in received 24 weeks' treatment with 120 mg nateglinide before meals (n = 179), 500 mg metformin three times a day (n = 178), combination therapy (n = 172), or placebo (n = 172). HbA1c and FPG were evaluated regularly, and plasma glucose levels were determined after Sustacal challenge at weeks 0, 12, and 24. Hypoglycemia and other adverse events were recorded.


RESULTS
At study end point, HbA1c was reduced from baseline with nateglinide and metformin but was increased with placebo (-0.5, -0.8, and +0.5%, respectively; P < or = 0.0001). Changes in FPG followed the same pattern (-0.7, -1.6, and +0.4 mmol/l; P < or = 0.0001). Combination therapy was additive (HbA1c -1.4% and FPG -2.4 mmol/l; P < or = 0.01 vs. monotherapy). After Sustacal challenge, there was a greater reduction in mealtime glucose with nateglinide monotherapy compared with metformin monotherapy or placebo (adjusted area under the curve [AUC]0-130 min -2.1, -1.1, and -0.6 mmol x h(-1) x l(-1); p < or = 0.0001). An even greater effect was observed with combination therapy (AUC0-130 min -2.5 mmol x h(-1) x l(-1); P < or = 0.0001 vs. metformin and placebo). All regimens were well tolerated.


CONCLUSIONS
Nateglinide and metformin monotherapy each improved overall glycemic control but by different mechanisms. Nateglinide decreased mealtime glucose excursions, whereas metformin primarily affected FPG. In combination, nateglinide and metformin had complementary effects, improving HbA1c, FPG, and postprandial hyperglycemia.
Integrating Classification and Association Rule Mining: A Concept Lattice Framework

Concept lattice is an efficient tool for data analysis. In this paper we show how classification and association rule mining can be unified under concept lattice framework. We present a fast algorithm to extract association and classification rules from concept lattice.
Social Cognition in Schizophrenia: From Social Stimuli Processing to Social Engagement

Social cognition consists of several skills which allow us to interact with other humans. These skills include social stimuli processing, drawing inferences about others' mental states, and engaging in social interactions. In recent years, there has been growing evidence of social cognitive impairments in patients with schizophrenia. Apparently, these impairments are separable from general neurocognitive impairments, such as attention, memory, and executive functioning. Moreover, social cognition seems to be a main determinant of functional outcome and could be used as a guide to elaborate new pharmacological and psychological treatments. However, most of these studies focus on individual mechanisms and observational perspectives; only few of them study schizophrenic patients during interactive situations. We first review evidences of social cognitive impairments both in social stimuli processing and in mental state attribution. We focus on the relationship between these functions and both general cognitive impairments and functional outcome. We next review recent game theory approaches to the study of how social engagement occurs in schizophrenic patients. The advantage of using game theory is that game-oriented tasks can assess social decision making in an interactive everyday situation model. Finally, we review proposed theoretical models used to explain social alterations and their underlying biological mechanisms. Based on interactive studies, we propose a framework which takes into account the dynamic nature of social processes. Thus, understanding social skills as a result of dynamical systems could facilitate the development of both basic research and clinical applications oriented to psychiatric populations.
'Silk Road', the virtual drug marketplace: a single case study of user experiences.

BACKGROUND
The online promotion of 'drug shopping' and user information networks is of increasing public health and law enforcement concern. An online drug marketplace called 'Silk Road' has been operating on the 'Deep Web' since February 2011 and was designed to revolutionise contemporary drug consumerism.


METHODS
A single case study approach explored a 'Silk Road' user's motives for online drug purchasing, experiences of accessing and using the website, drug information sourcing, decision making and purchasing, outcomes and settings for use, and perspectives around security. The participant was recruited following a lengthy relationship building phase on the 'Silk Road' chat forum.


RESULTS
The male participant described his motives, experiences of purchasing processes and drugs used from 'Silk Road'. Consumer experiences on 'Silk Road' were described as 'euphoric' due to the wide choice of drugs available, relatively easy once navigating the Tor Browser (encryption software) and using 'Bitcoins' for transactions, and perceived as safer than negotiating illicit drug markets. Online researching of drug outcomes, particularly for new psychoactive substances was reported. Relationships between vendors and consumers were described as based on cyber levels of trust and professionalism, and supported by 'stealth modes', user feedback and resolution modes. The reality of his drug use was described as covert and solitary with psychonautic characteristics, which contrasted with his membership, participation and feelings of safety within the 'Silk Road' community.


CONCLUSION
'Silk Road' as online drug marketplace presents an interesting displacement away from 'traditional' online and street sources of drug supply. Member support and harm reduction ethos within this virtual community maximises consumer decision-making and positive drug experiences, and minimises potential harms and consumer perceived risks. Future research is necessary to explore experiences and backgrounds of other users.
Firm-Level Corruption in Vietnam

This paper uses a unique panel dataset on firm-level corruption. It contains quantitative information on bribe payments by a sample of formal and informal Vietnamese firms. We show that bribe incidence is highly associated with firm-level differences in (i) visibility, (ii) sunk costs, (iii) ability to pay, and (iv) level of interaction with public officials. Moreover, when informal firms become formal the probability of paying bribes increases. Becoming formal is also associated with a revenue growth premium that is not driven by self-selection of well-performing firms. On average, this premium outweighs the additional bribe cost of formalization. Formalization embodies net benefits in spite of the growth hampering effects of bribes
Highly efficient optical quantum memory with long coherence time in cold atoms

Optical quantum memory is an essential element for long distance quantum communication and photonic quantum computation protocols. The practical implementation of such protocols requires an efficient quantum memory with long coherence time. Beating the no-cloning limit, for example, requires efficiencies above 50%. An ideal optical fibre loop has a loss of 50% in 100 μs, and until now no universal quantum memory has beaten this time-efficiency limit. Here, we report results of a gradient echo memory (GEM) experiment in a cold atomic ensemble with a 1/e coherence time up to 1 ms and maximum efficiency up to 87 ± 2% for short storage times. Our experimental data demonstrates greater than 50% efficiency for storage times up to 0.6 ms. Quantum storage ability is verified beyond the ideal fibre limit using heterodyne tomography of small coherent states.
Augmented Reality Oculus Rift

This paper covers the whole process of developing an Augmented Reality Stereoscopig Render Engine for the Oculus Rift. To capture the real world in form of a camera stream, two cameras with fish-eye lenses had to be installed on the Oculus Rift DK1 hardware. The idea was inspired by Steptoe [1]. After the introduction, a theoretical part covers all the most neccessary elements to achieve an AR System for the Oculus Rift, following the implementation part where the code from the AR Stereo Engine is explained in more detail. A short conclusion section shows some results, reflects some experiences and in the final chapter some future works will be discussed. The project can be accessed via the git repository https: // github. com/ MaXvanHeLL/ ARift. git .
Epidemiological Factors Affecting Low Birth Weight

Birth weight is a reliable index of intra uterine growth retardation (IUGR) and a major factor determining child survival, future physical growth and mental development (1). A multifactorial inter-relationship exists between the environment in which pregnant mothers live and the growth of the fetus (2). This relationship has prompted public health personnel to suggest that birth weight distribution and the proportion of babies born with a low birth weight (LBW) be considered as indicators of socio economic development. LBW is found to be one of the major causes of high mortality and morbidity rates (3). Worldwide, out of 139 million live births, about 23 million infants had low birth weight i.e., birth weight less than 2.5 kg (4). In India, the prevalence of LBW infants is about 33% (5), as compared to 4.5% in industrially developed countries (6). The perinatal mortality among LBW infants is about 8 times higher than that in infants weighing more than 2.5kg (7).
Latent Variable Dialogue Models and their Diversity

We present a dialogue generation model that directly captures the variability in possible responses to a given input, which reduces the ‘boring output’ issue of deterministic dialogue models. Experiments show that our model generates more diverse outputs than baseline models, and also generates more consistently acceptable output than sampling from a deterministic encoder-decoder model.
The Gilbert-Elliott Model for Packet Loss in Real Time Services on the Internet

The estimation of quality for real time services over telecommunication networks requires realistic models in order to generate impairments and failures during transmission. Starting with the classical Gilbert-Elliot model, we derive the second order statistics over arbitrary time scales and fit the parameters to match the packet loss pattern of traffic traces. The results show that simple Markov models are appropriate to capture the observed loss pattern.
Translanguaging in the Bilingual Classroom: A Pedagogy for Learning and Teaching?

This article reports on research that questions commonsense understandings of a bilingual pedagogy predicated on what Cummins (2005, 2008) refers to as the “two solitudes” assumption (2008, p. 65). It sets out to describe a flexible bilingual approach to language teaching and learning in Chinese and Gujarati community language schools in the United Kingdom. We argue for a release from monolingual instructional approaches and advocate teaching bilingual children by means of bilingual instructional strategies, in which two or more languages are used alongside each other. In developing this argument, the article takes a language ecology perspective and seeks to describe the interdependence of skills and knowledge across languages.
Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology.

BACKGROUND
Research literature on problematic smartphone use, or smartphone addiction, has proliferated. However, relationships with existing categories of psychopathology are not well defined. We discuss the concept of problematic smartphone use, including possible causal pathways to such use.


METHOD
We conducted a systematic review of the relationship between problematic use with psychopathology. Using scholarly bibliographic databases, we screened 117 total citations, resulting in 23 peer-reviewer papers examining statistical relations between standardized measures of problematic smartphone use/use severity and the severity of psychopathology.


RESULTS
Most papers examined problematic use in relation to depression, anxiety, chronic stress and/or low self-esteem. Across this literature, without statistically adjusting for other relevant variables, depression severity was consistently related to problematic smartphone use, demonstrating at least medium effect sizes. Anxiety was also consistently related to problem use, but with small effect sizes. Stress was somewhat consistently related, with small to medium effects. Self-esteem was inconsistently related, with small to medium effects when found. Statistically adjusting for other relevant variables yielded similar but somewhat smaller effects.


LIMITATIONS
We only included correlational studies in our systematic review, but address the few relevant experimental studies also.


CONCLUSIONS
We discuss causal explanations for relationships between problem smartphone use and psychopathology.
Signal functions for measuring the ability of health facilities to provide abortion services: an illustrative analysis using a health facility census in Zambia

BACKGROUND
Annually, around 44 million abortions are induced worldwide. Safe termination of pregnancy (TOP) services can reduce maternal mortality, but induced abortion is illegal or severely restricted in many countries. All abortions, particularly unsafe induced abortions, may require post-abortion care (PAC) services to treat complications and prevent future unwanted pregnancy. We used a signal-function approach to look at abortion care services and illustrated its utility with secondary data from Zambia.


METHODS
We refined signal functions for basic and comprehensive TOP and PAC services, including family planning (FP), and assessed functions currently being collected via multi-country facility surveys. We then used the 2005 Zambian Health Facility Census to estimate the proportion of 1369 health facilities that could provide TOP and PAC services under three scenarios. We linked facility and population data, and calculated the proportion of the Zambian population within reach of such services.


RESULTS
Relevant signal functions are already collected in five facility assessment tools. In Zambia, 30 % of facilities could potentially offer basic TOP services, 3.7 % comprehensive TOP services, 2.6 % basic PAC services, and 0.3 % comprehensive PAC services (four facilities). Capability was highest in hospitals, except for FP functions. Nearly two-thirds of Zambians lived within 15 km of a facility theoretically capable of providing basic TOP, and one-third within 15 km of comprehensive TOP services. However, requiring three doctors for non-emergency TOP, as per Zambian law, reduced potential access to TOP services to 30 % of the population. One-quarter lived within 15 km of basic PAC and 13 % of comprehensive PAC services. In a scenario not requiring FP functions, one-half and one-third of the population were within reach of basic and comprehensive PAC respectively. There were huge urban-rural disparities in access to abortion care services. Comprehensive PAC services were virtually unavailable to the rural population.


CONCLUSIONS
Secondary data from facility assessments can highlight gaps in abortion service provision and coverage, but it is necessary to consider TOP and PAC separately. This approach, especially when combined with population data using geographic coordinates, can also be used to model the impact of various policy scenarios on access, such as requiring three medical doctors for non-emergency TOP. Data collection instruments could be improved with minor modifications and used for multi-country comparisons.
Zero-Knowledge Based Identification: From a Theoretical Concept Towards a Practical Token

We overview various attacks on identification systems based on zero-knowledge proofs, and measures to prevent them. We also consider the efficiency of zero-knowledge proofs and overview protocols with a low communication and computation complexity. We conclude that with today's technology it is possible to make identification tokens which are secure and efficient.
Short inversion time on delayed-enhancement magnetic resonance improves diagnostic accuracy in recent-onset heart failure

Background Subendocardial LGE is a marker of ischemic aetiology of left ventricular dysfunction, and of viable myocardium. Using a high relaxivity contrast media such as gadobenate dimeglumine, however, little areas of subendocardial LGE can be masked by the high signal of the blood pool. We halved the optimal TI to null the signal of viable myocardium to obtain LGE images with high signal from viable myocardium, intermediate signal from the blood pool, and no signal from LGE areas, thus enhancing the presence of “hidden areas” subendocardial enhancement.
Circuit-Level Modeling and Detection of Metallic Carbon Nanotube Defects in Carbon Nanotube FETs

Carbon Nanotube Field Effect Transistors (CNTFET) are promising nano-scaled devices for implementing high performance, very dense and low power circuits. The core of a CNTFET is a carbon nanotube. Its conductance property is determined by the so-called chirality of the tube; chirality is difficult to control during manufacturing. This results in conducting (metallic) nanotubes and defective CNTFETs similar to stuck-on (SON or source-drain short) faults, as encountered in classical MOS devices. This paper studies this phenomenon by using layout information and presents modeling and detection methodologies for nano-scaled defects arising from the presence of metallic carbon nanotubes. For CNTFET-based circuits (e.g. intramolecular), these defects are analyzed using a traditional stuck-at fault model. This analysis is applicable to primitive and complex gates. Simulation results are presented for detecting modeled metallic nanotube faults in CNTFETs using a single stuck-at fault test set. A high coverage is achieved (~98%).
Anxiety and depression among medical students: a cross-sectional study.

OBJECTIVE
To determine the prevalence of anxiety and depression among medical students at Nishtar Medical College, Multan.


METHODS
A cross-sectional study was carried out at Nishtar Medical College, Multan in 2008. The questionnaire was administered to 815 medical students who had spent more than 6 months in college and had no self reported physical illness. They were present at the time of distribution of the questionnaires and consented. Prevalence of anxiety and depression was assessed using a structured validated questionnaire, the Aga Khan University Anxiety and Depression Scale with a cut-off score of 19. Data Analysis was done using SPSS v. 14.


RESULTS
Out of 815 students, 482 completed the questionnaire with a response rate of 59.14%. The mean age of students was 20.66 +/- 1.8 years. A high prevalence of anxiety and depression (43.89%) was found amongst medical students. Prevalence of anxiety and depression among students of first, second, third, fourth and final years was 45.86%, 52.58%, 47.14%, 28.75% and 45.10% respectively. Female students were found to be more depressed than male students (OR = 2.05, 95% CI = 1.42-2.95, p = 0.0001). There was a significant association between the prevalence of anxiety and depression and the respective year of medical college (p = 0.0276). It was seen that age, marital status, locality and total family income did not significantly affect the prevalence of anxiety and depression.


CONCLUSIONS
The results showed that medical students constitute a vulnerable group that has a high prevalence of psychiatric morbidity comprising of anxiety and depression.
Use of sputum eosinophil counts to guide management in children with severe asthma.

BACKGROUND
Previous studies in adults with asthma incorporating the control of sputum eosinophils into management strategies have shown significant reductions in exacerbations. A study was undertaken to investigate whether this strategy would be successful in children with severe asthma.


METHODS
55 children (7-17 years) with severe asthma were randomised to either a conventional symptom-based management strategy or to an inflammation-based strategy (principally sputum eosinophils). Children were seen 3-monthly over a 1-year period.


RESULTS
The annual rate of total and major exacerbations (courses of oral corticosteroids) was non-significantly lower in the inflammatory management group compared with the symptom management group (3.6 vs. 4.8, incident rate ratio (IRR) 0.75, 95% CI 0.54 to 1.04, p=0.082; and 1.9 vs. 2.7 IRR 0.73, 95% CI 0.42 to 1.28, p=0.274 for total and major exacerbations, respectively). Significantly fewer subjects in the inflammatory management group experienced an exacerbation within 28 days of a study visit. There were small non-significant differences in measures of asthma control (symptom-free days and short-acting β agonist use) favouring the inflammatory management group. There was no significant difference in the inhaled corticosteroid dose prescribed over the course of the study.


CONCLUSION
Incorporating the control of sputum eosinophils into the management algorithm did not significantly reduce overall exacerbations or improve asthma control. Exacerbations were reduced in the short term, suggesting that more frequent measurements would be needed for a clinically useful effect and that controlling inflammation may have a role to play in subgroups of children with severe asthma.
Competence and impact of tools for BPR

Software tools for Business Process Reengineering (BPR) promise to reduce cost and improve quality of projects. This paper discusses the contribution of BPR tools in BPR projects and identi®es critical factors for their success. A model was built based on previous research on tool success. The analysis of empirical data shows that BPR tools are related to effectiveness rather than ef®ciency of the projects. Process visualization and process analysis features are key to BPR tool competence. Also success factors for BPR tools are different from those for CASE tools. # 1999 Elsevier Science B.V. All rights reserved.
The Ecological Approach to Text Visualization

This article presents both theoretical and technical bases on which to build a ‘‘science of text visualization.’’ These conceptually produce ‘‘the ecological approach,’’ which is rooted in ecological and evolutionary psychology. The basic idea is that humans are genetically selected from their species history to perceptually interpret certain informational aspects of natural environments. If information from text documents is visually spatialized in a manner conformal with these predilections, its meaningful interpretation to the user of a text visualization system becomes relatively intuitive and accurate. The SPIRE text visualization system, which images information from free text documents as natural terrains, serves as an example of the ‘‘ecological approach’’ in its visual metaphor, its text analysis, and its spatializing procedures.