LLukas22/scidocs huggingface dataset:
Physicians' beliefs about conscience in medicine: a national survey.

PURPOSE
To explore physicians' beliefs about whether physicians sometimes have a professional obligation to provide medical services even if doing so goes against their conscience, and to examine associations between physicians' opinions and their religious and ethical commitments.


METHOD
A survey was mailed in 2007 to a stratified random sample of 1,000 U.S. primary care physicians, selected from the American Medical Association Physician Masterfile. Participants were classified into three groups according to agreement or disagreement with two statements: "A physician should never do what he or she believes is morally wrong, no matter what experts say," and "Sometimes physicians have a professional ethical obligation to provide medical services even if they personally believe it would be morally wrong to do so."


RESULTS
The response rate was 51% (446/879 delivered questionnaires). Forty-two percent and 22% believed they are never and sometimes, respectively, obligated to do what they personally believe is wrong, and 36% agreed with both statements. Physicians who are more religious are more likely to believe that physicians are never obligated to do what they believe is wrong (58% and 31% of those with high and low intrinsic religiosity, respectively; multivariate odds ratio, 2.9; 95% CI, 1.2-7.2). Those with moral objections to any of three controversial practices were more likely to hold that physicians should never do what they believe is wrong.


CONCLUSION
A substantial minority of physicians do not believe there is ever a professional obligation to do something they personally believe is wrong.
Successful overweight prevention in adolescents by increasing physical activity: a 4-year randomized controlled intervention

Background:Population-based studies directed at promoting physical activity in youth have shown limited success in obesity prevention.Objective:To assess whether an intervention integrating environmental changes to induce sustained changes in physical activity, prevents overweight in adolescents.Design:Four-year randomized trial started in 2002 in eight middle schools of Eastern France. The intervention, randomized at school level, was designed to promote physical activity by changing attitudes through debates and attractive activities, and by providing social support and environmental changes encouraging physical activity.Subjects:Nine hundred and fifty four 12-year-old six-graders.Measurements:Body mass index (BMI), body composition, physical activity by questionnaire, plasma lipids and glucose, insulin resistance.Results:Intervention students had a lower increase in BMI (P=0.01) and age- and gender-adjusted BMI (P<0.02) over time than controls. The differences across groups of the age- and gender-adjusted BMI changes (95% confidence interval (CI)) were −0.29 (−0.51; −0.07) kg/m2 at 3 years, −0.25 (−0.51; 0.01) kg/m2 at 4 years. An interaction with baseline weight status was noted. The intervention had a significant effect throughout the study in initially non-overweight adolescents (−0.36 (−0.60;−0.11) kg/m2 for adjusted BMI at 4 years), corresponding to a lower increase in fat mass index (P<0.001). In initially overweight adolescents, the differences observed across groups at 2 years (–0.40 (−0.94; 0.13) kg/m2 for adjusted BMI) did not persist over time. At 4 years, 4.2% of the initially non-overweight adolescents were overweight in the intervention schools, 9.8% in the controls (odds ratio=0.41 (0.22; 0.75); P<0.01). Independent of initial weight status, compared with controls, intervention adolescents had an increase in supervised physical activity (P<0.0001), a decrease of TV/video viewing (P<0.01) and an increase of high-density cholesterol concentrations (P<0.0001).Conclusion:Enhancing physical activity with a multilevel program prevents excessive weight gain in non-overweight adolescents. Our study provides evidence that prevention of obesity in youth is feasible.
Poseidon: A System Architecture for Efficient GPU-based Deep Learning on Multiple Machines

Deep learning models, which learn high-level feature representations from raw data, have become popular for machine learning and artificial intelligence tasks that involve images, audio, and other forms of complex data. A number of software “frameworks” have been developed to expedite the process of designing and training deep neural networks, such as Caffe [11], Torch [4], and Theano [1]. Currently, these frameworks can harness multiple GPUs on the same machine, but are unable to use GPUs that are distributed across multiple machines; because even average-sized deep networks can take days to train on a single GPU when faced with 100s of GBs to TBs of data, distributed GPUs present a prime opportunity for scaling up deep learning. However, the limited inter-machine bandwidth available on commodity Ethernet networks presents a bottleneck to distributed GPU training, and prevents its trivial realization. To investigate how existing software frameworks can be adapted to efficiently support distributed GPUs, we propose Poseidon, a scalable system architecture for distributed inter-machine communication in existing deep learning frameworks. In order to assess Poseidon’s effectiveness, we integrate Poseidon into the Caffe [11] framework and evaluate its performance at training convolutional neural networks for object recognition in images. Poseidon features three key contributions that improve the training speed of deep neural networks on clusters: (i) a three-level hybrid architecture that allows Poseidon to support both CPU-only clusters as well as GPU-equipped clusters, (ii) a distributed wait-free backpropagation (DWBP) algorithm to improve GPU utilization and to balance communication, and (iii) a dedicated structure-aware communication protocol (SACP) to minimize communication overheads. We empirically show that Poseidon converges to the same objective value as a single machine, and achieves state-of-the-art training speedup across multiple models and well-established datasets, using a commodity GPU cluster of 8 nodes (e.g. 4.5× speedup on AlexNet, 4× on GoogLeNet, 4× on CIFAR-10). On the much larger ImageNet 22K dataset, Poseidon with 8 nodes achieves better speedup and competitive accuracy to recent CPU-based distributed deep learning systems such as Adam [2] and Le et al. [16], which use 10s to 1000s of nodes.
The economics of food choice behavior: why poverty and obesity are linked.

Obesity in the United States does not affect all segments of the population equally. It is more prevalent in deprived neighborhoods and among groups with lower education and incomes. Inequitable access to healthy foods is one mechanism by which socioeconomic factors can influence food choice behaviors, overall diet quality, and bodyweight. Having a supermarket in the immediate neighborhood has been linked to better diets and to lower obesity rates. However, the affordability of healthy foods may have more of an impact on food patterns than does distance to the nearest store. Grains, added sugars, and added fats are inexpensive, good-tasting, and convenient. Their consumption has been linked to lower quality diets, lower diet costs, and lower socioeconomic status. By contrast, the recommended healthier diets not only cost more but were consumed by more affluent groups. New techniques of spatial analysis are a promising approach to mapping obesity rates and linking them with measures of socioeconomic status based on diverse social and economic aspects of the built environment. Low residential property values predicted bodyweights of women better than did either education or incomes. Shopping in low-cost supermarkets was another powerful predictor of bodyweight. Bodyweight gain may be best predicted not by any one nutrient, food or beverage but by low diet cost. Higher obesity rates in poor neighborhoods may be the toxic consequence of economic insecurity. Alleviating poverty may be the best, if not the only, way to stop the obesity epidemic.
eGovernment as a Carrier of Context

.................................................................................................................1 A. THE DIFFUSION OF eGOVERNMENT ............................................................2 B. eGOVERNMENT IN CONTEXT .........................................................................3 B1. eGOVERNMENT DESIGNERS .................................................................................6 B2. IMPLICATIONS OF DESIGN-USE MISMATCH: CONTEXTUAL COLLISION..............10 C. ANALYSIS AND IMPLICATIONS....................................................................12 C1. IMPLICATIONS FOR POLICY AND FOR RESEARCH ................................................18 REFERENCES .............................................................................................................19 eGovernment as a Carrier of Context
Software Engineering: An Idea Whose Time Has Come and Gone?

Certain principles long considered fundamental to software engineering are examined and found wanting.
Student design - Efficiency Comparison Between Highly Efficient Class-F and Inverse Class-F Power Amplifiers

The purpose of this note is to provide a clear quantitative explanation of the better efficiency and a design guide for optimizing the output power or efficiency of inverse class-F amplifiers (Woo, et. al., 2006). For this purpose, the efficiency equations of the inverse class-F and conventional class-F amplifiers are derived using ideal time-domain waveforms. Then, analytic comparisons are carried out using these equations under the condition that the fundamental output power of both amplifiers are identical, near where maximum power added efficiency (PAE) is produced. The analysis results clearly show why the inverse class-F amplifier has higher efficiency than the class-F amplifier. We have designed and implemented several inverse class-F amplifiers at 1 GHz to confirm these results
Essential Cognitive Therapy

An Outline of Cognitive Therapy. Assessment and Socialization Into ct. Eliciting and Examining Negative Automatic Thoughts. Homework. Identifying and Examining Underlying Assumptions and Core Beliefs. Tackling Client and therapist Difficulties With CT.
Gaussian Process Latent Variable Models for Human Pose Estimation

We describe a method for recovering 3D human body pose from silhouettes. Our model is based on learning a latent space using the Gaussian Process Latent Variable Model (GP-LVM) [1] encapsulating both pose and silhouette features Our method is generative, this allows us to model the ambiguities of a silhouette representation in a principled way. We learn a dynamical model over the latent space which allows us to disambiguate between ambiguous silhouettes by temporal consistency. The model has only two free parameters and has several advantages over both regression approaches and other generative methods. In addition to the application shown in this paper the suggested model is easily extended to multiple observation spaces without constraints on type.
3D-IC thermo-compression collective bonding process using high temperature stage

As one of the methods to stack the 3D-IC fast, the collective bonding process using TCB (thermo-compression bonder) attracts attention [1-3]. In the collective bonding process, we can improve the throughput considerably by postbonding the multilayered pre-bonded chips at a time. However, when the number of the stacked chips increased, we found that the temperature difference between the upper layer and lower layer became large and the good solder connection was not obtained in all the layer in conventional TCB. Therefore, we reported that the collective bonding could be realized by using the heat insulation stage which can prevent an outflow of the heat from the bonding head [1]. By using the heat insulation stage, we could reduce the temperature difference to less than 10oC for four layers, but it was necessary to reduce temperature difference more, depending on the kind of NCF. Besides, it was difficult to reduce difference of temperature when, for example, the number of the stacked chips increased more than eight layers. In this presentation, we report about new collective bonding process that is able to reduce the temperature difference by using high temperature backup stage. We could enable the high temperature process of the stage by using the wafer-handling mechanism which lifts a substrate from the stage every one bonding cycle.
Single stage inverter for PV applications with One Cycle Sampling technique in the MPPT algorithm

This paper introduces a single-stage, single-phase, inverter, for maximum efficient photovoltaic grid connection. The inverter is based in a full-bridge converter where a few diodes and one inductor have been added to enable single stage operation. The new topology provides an additional buck-boost converter function at the bridge level in order to extract the maximum power from photovoltaic (PV) panel. Non linear control is used to regulate the sinusoidal current injected in the grid and the PV voltage, so that maximum power point tracker, MPPT, is obtained. The new MPPT algorithm uses one cycle sampling technique to obtain the average value of the voltage and current in the panel with a small time delay. This technique eliminates errors introduced in the MPPT calculation, due to the switching ripple. The proposed algorithm also allows the operation of the control circuit at a lower frequency than the high switching frequency of the bridge converter transistors.
Current developments in interim transport (storage) media in dentistry: an update

Healing following avulsion and replantation is dependent on the extent of pulpal and periodontal ligament (PDL) tissue damage. Therefore, immediate replantation is the recommended treatment of choice for an avulsed permanent tooth. To achieve a more favourable prognosis following tooth replantation, use of an appropriate interim transport medium is usually advocated. Numerous studies have researched and advocated the use of media like saliva, milk, Hank's Balanced Salt Solution (HBSS) and ViaSpan. However, current research has indicated the use of few newer media as promising interim transport media for an avulsed tooth. This review summarises the current developments regarding the introduction of newer interim transport media for the treatment of avulsed teeth.
A review of ethnicity, health and nutrition-related diseases in relation to migration in the United Kingdom.

OBJECTIVES
To identify lessons from and gaps in research on diet-disease links among former migrants in the United Kingdom (UK).


RESULTS
Migrant status and self-identified ethnicity do not match so these terms mask differences in social, nutritional and health status within and between population groups. Some former migrants differ in causes of death from the general population, e.g.: fewer coronary heart disease deaths among Caribbean-born; fewer cancer deaths among Caribbean, South Asian- and East African-born adults. Irish- and Scottish-born have higher mortality from all causes. Experience of risk factors differ also, e.g.: higher prevalences of hypertension and diabetes in Caribbean- and South Asian-born adults than representative samples of the general population; obesity and raised waist-hip circumference ratios in South Asian, African-Caribbean and some Irish-born adults. Former migrants experience long-term disadvantage, associated with more self-defined illness and lower reported physical activity. Nutrient intake data from the few, recent, small-scale studies must be interpreted with caution due to methodological diversity. However, second generation offspring of former migrants appear to adopt British dietary patterns, increasing fat and reducing vegetable, fruit and pulse consumption compared with first generation migrants.


CONCLUSIONS
There is insufficient evidence on why some former migrants but not others experience lower specific mortality than the general population. Dietary intake variations provide important clues particularly when examined by age and migration status. Majority ethnic and younger migrant groups could raise and sustain high fruit and vegetable intakes but lower proportions of fat, by adopting many dietary practices from older migrants. Objective measures of physical activity and longitudinal studies of diets among different ethnic groups are needed to explain diversity in health outcomes and provide for evidence-based action.
Unemployment and Labor Market Rigidities : Europe versus North America

H ere is the received wisdom. The European job market is rigid and inflexible. Result: high unemployment. The North American job market is dynamic and flexible. Result: low unemployment. So Europeans had better do something about their labor markets unless they want permanent double digit unemployment. In fact, this is not totally wrong. There are features of the labor markets in some European countries that help sustain high levels of unemployment. Some of these features can be thought of as rigidities. However, there are many other so-called rigidities that do not cause high unemployment and, indeed, may serve a useful purpose. So it is important to know which features of the labor market cause high unemployment and which do not. This is the subject of what follows.
[PENS (papular epidermal nevus with "skyline" basal cell layer)].

BACKGROUND
PENS is a rare neuro-cutaneous syndrome that has been recently described. It involves one or more congenital epidermal hamartomas of the papular epidermal nevus with "skyline" basal cell layer type (PENS) as well as non-specific neurological anomalies. Herein, we describe an original case in which the epidermal hamartomas are associated with autism spectrum disorder (ASD).


PATIENTS AND METHODS
A 6-year-old boy with a previous history of severe ASD was referred to us for asymptomatic pigmented congenital plaques on the forehead and occipital region. Clinical examination revealed a light brown verrucous mediofrontal plaque in the form of an inverted comma with a flat striated surface comprising coalescent polygonal papules, and a clinically similar round occipital plaque. Repeated biopsies revealed the presence of acanthotic epidermis covered with orthokeratotic hyperkeratosis with occasionally broadened epidermal crests and basal hyperpigmentation, pointing towards an anatomoclinical diagnosis of PENS.


DISCUSSION
A diagnosis of PENS hamartoma was made on the basis of the clinical characteristics and histopathological analysis of the skin lesions. This condition is defined clinically as coalescent polygonal papules with a flat or rough surface, a round or comma-like shape and light brown coloring. Histopathological examination showed the presence of a regular palisade "skyline" arrangement of basal cell epidermal nuclei which, while apparently pathognomonic, is neither a constant feature nor essential for diagnosis. Association of a PENS hamartoma and neurological disorders allows classification of PENS as a new keratinocytic epidermal hamartoma syndrome. The early neurological signs, of varying severity, are non-specific and include psychomotor retardation, learning difficulties, dyslexia, hyperactivity, attention deficit disorder and epilepsy. There have been no reports hitherto of the presence of ASD as observed in the case we present.


CONCLUSION
This new case report of PENS confirms the autonomous nature of this neuro-cutaneous disorder associated with keratinocytic epidermal hamartoma syndromes.
Stiffness distribution control - locomotion of closed link robot with mechanical softness

This paper proposes a new method of locomotion control, named "stiffness distribution control (SDC)", to realize various locomotion of a closed link robot with mechanical softness. SDC directly defines the reference stiffness coefficient at each hinge by SDC string which represents the distribution of the stiffness. This simple method does not need costly calculation at all and thus is suitable for controlling closed link robots. We build "BIYOn" as the prototype of closed link robots, the variable stiffness hinge (VSH) of which is newly designed. SDC is experimented on BIYOn and then it's found that SDC is effective in a controlling locomotion in practice. We also develop a systematic optimization method of stiffness distribution composed of two-stage approach and succeed in optimization to obtain a fast and smooth rolling motion and a sudden stopping motion
Generative NeuroEvolution for Deep Learning

An important goal for the machine learning (ML) community is to create approaches that can learn solutions with human-level capability. One domain where humans have held a significant advantage is visual processing. A significant approach to addressing this gap has been machine learning approaches that are inspired from the natural systems, such as artificial neural networks (ANNs), evolutionary computation (EC), and generative and developmental systems (GDS). Research into deep learning has demonstrated that such architectures can achieve performance competitive with humans on some visual tasks; however, these systems have been primarily trained through supervised and unsupervised learning algorithms. Alternatively, research is showing that evolution may have a significant role in the development of visual systems. Thus this paper investigates the role neuro-evolution (NE) can take in deep learning. In particular, the Hypercubebased NeuroEvolution of Augmenting Topologies is a NE approach that can effectively learn large neural structures by training an indirect encoding that compresses the ANN weight pattern as a function of geometry. The results show that HyperNEAT struggles with performing image classification by itself, but can be effective in training a feature extractor that other ML approaches can learn from. Thus NeuroEvolution combined with other ML methods provides an intriguing area of research that can replicate the processes in nature.
Chemical Derivatization for the Analysis of Drugs by GC-MS-A Conceptual Review

Drugs are often chemically derivatized prior to their GC-MS analysis for the following reasons: (a) to bring the analytes to the chemical forms that are more compatible to the chromatographic environment; (b) to create a separation mechanism or to maximize resolution efficiency; (c) to improve detection or structural elucidation effectiveness; or (d) to make use of the analytes’ specific structural features for analyticl needs. Analytes that are strongly acidic, basic or with functional groups, that may not vaporize or may interact with (irreversibly or reversibly) silanol groups or contaminating compounds present in the chromatographic system, can be more effectively analyzed after chemical derivatization. Enantiomers can be chromatographically resolved by achiral columns after being converted into diastereomers using chiral reagents; derivatization may also bring the retention time of the targeted analytes to a more desirable range. Introduction of certain elements or groups through chemical derivatization may enhance the detector’s response or generate mass spectra helpful to the elucidation of the analytes’ structural features. In conclusion, commonly used derivatization reagents for silylation, acylation, and alkylation are summarized along with comments on some practical considerations.
Feature weighting in content based recommendation system using social network analysis

We propose a hybridization of collaborative filtering and content based recommendation system. Attributes used for content based recommendations are assigned weights depending on their importance to users. The weight values are estimated from a set of linear regression equations obtained from a social network graph which captures human judgment about similarity of items.