LLukas22/scidocs huggingface dataset:
Wormy wood?

Background: Post thrombotic syndrome (PTS) is a burdensome and costly complication of deep venous thrombosis (DVT) that develops in 20–40% of patients within 1–2 years after symptomatic DVT. Affected patients have chronic leg pain and swelling and may develop ulcers. Venous valve disruption from the thrombus itself or thrombus-associated mediators of inflammation is considered to be a key initiating event for the development of venous hypertension that often underlies PTS. As existing treatments for PTS are extremely limited, strategies that focus on preventing the development of PTS in patients with DVT are more likely to be effective and cost-effective in reducing its burden. Elastic compression stockings (ECS) could be helpful in preventing PTS; however, data on their effectiveness are scarce and conflicting. Methods/Design: The SOX Trial is a randomized, allocation concealed, double-blind multicenter clinical trial. The objective of the study is to evaluate ECS to prevent PTS. A total of 800 patients with proximal DVT will be randomized to one of 2 treatment groups: ECS or placebo (inactive) stockings worn on the DVT-affected leg daily for 2 years. The primary outcome is the incidence of PTS during follow-up. Secondary outcomes are severity of PTS, venous thromboembolism (VTE) recurrence, death from VTE, quality of life and cost-effectiveness. Outcomes will be evaluated during 6 clinic visits and 2 telephone follow ups. At baseline, 1 and 6 months, blood samples will be obtained to evaluate the role of inflammatory mediators and genetic markers of thrombophilia in the development of PTS (Bio-SOX substudy). Discussion: The SOX Trial will be the largest study and the first with a placebo control to evaluate the effectiveness of ECS to prevent PTS. It is designed to provide definitive data on the effects of ECS on the occurrence and severity of PTS, as well as DVT recurrence, cost-effectiveness and quality of life. This study will also prospectively evaluate the predictive role of biomarkers that are reflective of putative underlying pathophysiological mechanisms in the development of clinical PTS. As such, our results will impact directly on the care of patients with DVT. Trial Registration: NCT00143598 and ISRCTN71334751 Published: 24 July 2007 BMC Cardiovascular Disorders 2007, 7:21 doi:10.1186/1471-2261-7-21 Received: 14 June 2007 Accepted: 24 July 2007 This article is available from: http://www.biomedcentral.com/1471-2261/7/21 © 2007 Kahn et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Dissociation of glutamate and cortical thickness is restricted to regions subserving trait but not state markers in major depressive disorder.

BACKGROUND
The anterior cingulate cortex (ACC) plays an important role in the neuropathology of major depressive disorder (MDD). So far, the effect of local cortical alteration on metabolites in multiple subdivisions of ACC has not been studied. We aimed to investigate structural and biochemical changes and their relationship in the pregenual ACC (pgACC), dorsal ACC (dACC) in MDD.


METHODS
We obtained magnetic resonance spectroscopy (MRS) in two investigated regions for 24 depressed patients and matched controls. In each region, cortical thickness (CTh) was calculated within a template mask based on its MRS voxel. We investigated neurotransmitter concentrations of Glx, N-acetyl aspartate (NAA), and myo-inositol (m-Ins) in two investigated regions, as well as their relationships with CTh in depressed individuals and healthy controls.


RESULTS
Patients showed significantly lower cortical thickness in dACC compared to controls. Glx in dACC significantly correlated with CTh in healthy controls but not MDD patients, while NAA and CTh in dACC significantly correlated in both groups. A marginal decrease of Glx in pgACC was found in the subgroup of more severely depressive patients, compared to the mildly depressed patients.


LIMITATIONS
Modest sample size and lack of episodes of depression may limit the generalizability of our findings.


CONCLUSION
Our results indicate an abolished CTh-MRS relation in dACC-associated with structural decline-but not in pgACC, where acute MRS alterations prevailed. Our study provides the first evidence of a neurochemical basis explaining some of the inter-individual variability in CTh in MDD.
Using information technology: engagement modes, flow experience, and personality orientations

The engagement mode (EM) model describes how an IT user (subject) engages in an activity with an object in a certain mode. The model specifies five engagement modes (Enjoying/Acceptance, Ambition/Curiosity, Avoidance/Hesitation, Frustration/Anxiety, and Efficiency/Productivity), which are characterized on three dimensions (evaluation of object, locus of control between subject and object, and intrinsic or extrinsic focus of motivation). Using questionnaire data from 290 participants, we extended previous empirical support for the model as well as described the model’s relationship to flow experience. In addition, it was found that autonomy, controlled and impersonal orientation in conjunction with socio-demographic variables differentiated among specific engagement modes and flow experience. We conclude that the EM-model, flow experience, and causality orientation theories provide a uniform framework for understanding how people adapt to information technology. 2004 Elsevier Ltd. All rights reserved.
Home-based asthma education of young low-income children and their families.

OBJECTIVE
To conduct a controlled trial of a home-based education program for low-income caregivers of young children with asthma.


METHODS
Participants were randomized to treatment-eight weekly asthma education sessions adapted from the Wee Wheezers program (n = 49)-or usual care (n = 46). Baseline and 3- and 12-month follow-up data were gathered from caregivers and from children's medical records.


RESULTS
Treatment was associated with less bother from asthma symptoms, more symptom-free days, and better caregiver quality of life at follow-up for children 1-3, but not those 4-6, years of age. Treatment and control groups did not differ in caregiver asthma management behavior or children's acute care utilization.


CONCLUSIONS
This home-based asthma education program was most effective with younger children; perhaps their caregivers were more motivated to learn about asthma management. Targeting psychosocial factors associated with asthma morbidity might also enhance the efficacy of asthma education for these families.
Design of a new counter-balancing stackable mechanism

This paper describes design and application of a novel counter-balancing stackable parallel mechanism. The stackable mechanism is designed by combining a five-bar and a couple of parallelograms. This design allows a compact design and wide workspace as compared to prior parallel type counter-balancing mechanisms. A linear geometry of this mechanism guarantees static balancing in the whole workspace. This mechanism was successfully applied to otologic.
Soluble corn fiber increases bone calcium retention in postmenopausal women in a dose-dependent manner: a randomized crossover trial.

BACKGROUND
Dietary soluble corn fiber (SCF) significantly improves calcium absorption in adolescents and the bone strength and architecture in rodent models.


OBJECTIVE
In this study, we aimed to determine the skeletal benefits of SCF in postmenopausal women.


DESIGN
We used our novel technology of determining bone calcium retention by following the urinary appearance of (41)Ca, a rare long-lived radioisotope, from prelabeled bone to rapidly and sensitively evaluate the effectiveness of SCF in reducing bone loss. A randomized-order, crossover, double-blinded trial was performed in 14 healthy postmenopausal women to compare doses of 0, 10, and 20 g fiber from SCF/d for 50 d.


RESULTS
A dose-response effect was shown with 10 and 20 g fiber from SCF/d, whereby bone calcium retention was improved by 4.8% (P < 0.05) and 7% (P < 0.04), respectively. The bone turnover biomarkers N-terminal telopeptide and osteocalcin were not changed by the interventions; however, a significant increase in bone-specific alkaline phosphatase, which is a bone-formation marker, was detected between 0 and 20 g fiber from SCF/d (8%; P = 0.035).


CONCLUSION
Daily SCF consumption significantly increased bone calcium retention in postmenopausal women, which improved the bone calcium balance by an estimated 50 mg/d. This study was registered at clinicaltrials.gov as NCT02416947.
Long Distance Effects in Mixed Electromagnetic-Gravitational Scattering

Using the methods of effective field theory we examine long range effects in mixed electromagnetic-gravitational scattering. Recent calculations which have yielded differing results for such effects are examined and corrected. We consider various spin configurations of the scattered particles and find that universality with respect to spindependence is obtained in agreement with expectations.
Sentiment Analysis Using Deep Learning Techniques: A Review

The World Wide Web such as social networks, forums, review sites and blogs generate enormous heaps of data in the form of users views, emotions, opinions and arguments about different social events, products, brands, and politics. Sentiments of users that are expressed on the web has great influence on the readers, product vendors and politicians. The unstructured form of data from the social media is needed to be analyzed and well-structured and for this purpose, sentiment analysis has recognized significant attention. Sentiment analysis is referred as text organization that is used to classify the expressed mind-set or feelings in different manners such as negative, positive, favorable, unfavorable, thumbs up, thumbs down, etc. The challenge for sentiment analysis is lack of sufficient labeled data in the field of Natural Language Processing (NLP). And to solve this issue, the sentiment analysis and deep learning techniques have been merged because deep learning models are effective due to their automatic learning capability. This Review Paper highlights latest studies regarding the implementation of deep learning models such as deep neural networks, convolutional neural networks and many more for solving different problems of sentiment analysis such as sentiment classification, cross lingual problems, textual and visual analysis and product review analysis, etc. Keywords—Sentiment analysis; recurrent neural network; deep neural network; convolutional neural network; recursive neural network; deep belief network
Working Memory Dimensions as Differential Predictors of the Speed and Error Aspect of Multitasking Performance

Being able to work on several tasks at the same time (multitasking) is an important performance aspect of many jobs. Recent research findings pointed out the important role of working memory for multitasking performance in general. To understand more about the role of working memory in predicting the speed and the error aspect of multitasking performance, this research was based on a newly developed and well-elaborated multidimensional model of working memory (Oberauer, Süß, Wilhelm, & Wittmann, 2003). Its 3 dimensions are storage in the context of processing, coordination, and supervision. In addition, attention and reasoning were controlled when predicting multitasking speed and error. A multitasking scenario, a battery of working memory tests, a battery of reasoning tests, and 2 attention tests were administered to 135 participants. As expected working memory was the best predictor of multitasking performance, followed by reasoning and attention. Working memory components showed a differential validity when predicting multitasking speed and multitasking error: Multitasking speed was predicted mainly by coordination, and HUMAN PERFORMANCE, 19(3), 253–275 Copyright © 2006, Lawrence Erlbaum Associates, Inc.
Tandem HMM with convolutional neural network for handwritten word recognition

In this paper, we investigate the combination of hidden Markov models and convolutional neural networks for handwritten word recognition. The convolutional neural networks have been successfully applied to various computer vision tasks, including handwritten character recognition. In this work, we show that they can replace Gaussian mixtures to compute emission probabilities in hidden Markov models (hybrid combination), or serve as feature extractor for a standard Gaussian HMM system (tandem combination). The proposed systems outperform a basic HMM based on either decorrelated pixels or handcrafted features. We validated the approach on two publicly available databases, and we report up to 60% (Rimes) and 35% (IAM) relative improvement compared to a Gaussian HMM based on pixel values. The final systems give comparable results to recurrent neural networks, which are the best systems since 2009.
3D object class detection in the wild

Object class detection has been a synonym for 2D bounding box localization for the longest time, fueled by the success of powerful statistical learning techniques, combined with robust image representations. Only recently, there has been a growing interest in revisiting the promise of computer vision from the early days: to precisely delineate the contents of a visual scene, object by object, in 3D. In this paper, we draw from recent advances in object detection and 2D-3D object lifting in order to design an object class detector that is particularly tailored towards 3D object class detection. Our 3D object class detection method consists of several stages gradually enriching the object detection output with object viewpoint, keypoints and 3D shape estimates. Following careful design, in each stage it constantly improves the performance and achieves state-of-the-art performance in simultaneous 2D bounding box and viewpoint estimation on the challenging Pascal3D+ [50] dataset.
The potential of 4D sonography in the assessment of fetal neurobehavior--multicentric study in high-risk pregnancies.

OBJECTIVE
An evolving challenge for obstetrician is to better define normal and abnormal fetal neurological function in utero in order to better predict antenatally which fetuses are at risk for adverse neurological outcome.


PATIENTS AND METHODS
Prenatal neurological assessment in high-risk fetuses using four-dimensional ultrasound applying the recently developed Kurjak antenatal neurodevelopmental test (KANET). Postnatal neurological assessment was performed using Amiel Tison's neurological assessment at term (ATNAT) for all live-borns and general movement (GM) assessment for those with borderline and abnormal ATNAT.


RESULTS
Inclusion criteria were met by 288 pregnant women in four centers of whom 266 gave birth to a live-born baby. It was revealed that 234 fetuses were neurologically normal, 7 abnormal and 25 borderline. Out of 7 abnormal fetuses ATNAT was borderline in 5 and abnormal in 2, whereas GM assessment was abnormal in 5 and definitely abnormal in 2. Out of 25 KANET borderline fetuses, ATNAT was normal in 7, borderline in 17 and abnormal in 1, whereas the GM assessment was as follows: normal optimal in 4, normal suboptimal in 20, and abnormal in 1. In summary, out of 32 borderline and abnormal fetuses ATNAT was normal in 7, borderline in 22 and abnormal in 3; GM assessment was normal optimal in 4, normal suboptimal in 20, abnormal in 6 and definitely abnormal in 2.


CONCLUSION
The sonographic test requires further studies before being recommended for wider clinical practice.
Anatomic single- and double-bundle anterior cruciate ligament reconstruction flowchart.

Anatomy is the foundation of orthopaedic surgery, and the advancing knowledge of the anterior cruciate ligament (ACL) anatomy has led to the development of improved modern reconstruction techniques that approach the anatomy of the native ACL. Current literature on the anatomy of the ACL and its reconstruction techniques, as well as our surgical experience, was used to develop a flowchart that can aid the surgeon in performing anatomic ACL reconstruction. We define anatomic ACL reconstruction as the functional restoration of the ACL to its native dimensions, collagen orientation, and insertion sites. A guideline was written to accompany this flowchart with more detailed information on anatomic ACL reconstruction and its pitfalls, all accompanied by relevant literature and helpful figures. Although there is still much to learn about anatomic ACL reconstruction methods, we believe this is a helpful document for surgeons. We continue to modify the flowchart as more information about the anatomy of the ACL, and how to more closely reproduce it, becomes available.
A 312-MHz 16-Mb random-cycle embedded DRAM macro with a power-down data retention mode for mobile applications

An embedded DRAM macro with a self-adjustable timing control (STC) scheme, a negative edge transmission scheme (NET), and a power-down data retention (PDDR) mode is developed. A 13.98-mm/sup 2/ 16-Mb embedded DRAM macro is fabricated in 0.13 /spl mu/m logic-based embedded DRAM process. Co-salicide word lines and MIM capacitors are used for high-speed array operation. The delay timing variation of 36 % for an RC delay can be reduced to 3.8% by using the STC scheme. The NET scheme transfers array control signals to local array blocks with high accuracy. Thereby, the test chip achieves 1.2-V 312-MHz random cycle operation even in the low-power process. 73-/spl mu/W data retention power is realized by using the PDDR mode, which is 5% of conventional schemes.
Relationships Among Spirituality, Religious Practices, Personality Factors, and Health for Five Different Faith Traditions

To determine: (1) differences in spirituality, religiosity, personality, and health for different faith traditions; and (2) the relative degree to which demographic, spiritual, religious, and personality variables simultaneously predict health outcomes for different faith traditions. Cross-sectional analysis of 160 individuals from five different faith traditions including Buddhists (40), Catholics (41), Jews (22), Muslims (26), and Protestants (31). Brief multidimensional measure of religiousness/spirituality (BMMRS; Fetzer in Multidimensional measurement of religiousness/spirituality for use in health research, Fetzer Institute, Kalamazoo, 1999); NEO-five factor inventory (NEO-FFI; in Revised NEO personality inventory (NEO PI-R) and the NEO-five factor inventory (NEO-FFI) professional manual, Psychological Assessment Resources, Odessa, Costa and McCrae 1992); Medical outcomes scale-short form (SF-36; in SF-36 physical and mental health summary scores: A user’s manual, The Health Institute, New England Medical Center, Boston, Ware et al. 1994). (1) ANOVAs indicated that there were no significant group differences in health status, but that there were group differences in spirituality and religiosity. (2) Pearson’s correlations for the entire sample indicated that better mental health is significantly related to increased spirituality, increased positive personality traits (i.e., extraversion) and decreased personality traits (i.e., neuroticism and conscientiousness). In addition, spirituality is positively correlated with positive personality traits (i.e., extraversion) and negatively with negative personality traits (i.e., neuroticism). (3) Hierarchical regressions indicated that personality predicted a greater proportion of unique variance in health outcomes than spiritual variables. Different faith traditions have similar health status, but differ in terms of spiritual, religious, and personality factors. For all faith traditions, the presence of positive and absence of negative personality traits are primary predictors of positive health (and primarily mental health). Spiritual variables, other than forgiveness, add little to the prediction of unique variance in physical or mental health after considering personality. Spirituality can be conceptualized as a characterological aspect of personality or a distinct construct, but spiritual interventions should continue to be used in clinical practice and investigated in health research.
Proactive CSR : An Empirical Analysis of the Role of its Economic , Social and Environmental Dimensions on the Association between Capabilities and Performance

Proactive corporate social responsibility (CSR) involves business practices adopted voluntarily by firms that go beyond regulatory requirements in order to actively support sustainable economic, social and environmental development, and thereby contribute broadly and positively to society. This empirical study examines the role of the economic, social and environmental dimensions of proactive CSR on the association between three specific capabilities – shared vision, stakeholder management and strategic proactivity – and financial performance in small and medium enterprises (SMEs). Using quantitative data collected from a sample of 171 Australian SMEs in the machinery and equipment manufacturing sector and employing structural equation modelling, we find that the adoption of practices in each CSR dimension by SMEs is influenced slightly differently by each capability, and affects financial performance differentially. The study also demonstrates the importance of the interaction between the three dimensions of proactive CSR in positively moderating the deployment of each individual CSR dimension to generate financial performance. Paying primary attention to the economic dimension of proactive CSR, and selectively focusing on social and environmental elements of proactive CSR that drive and support the economic dimension, are of key importance to sustainable long-term financial success for SMEs.
The interactions between attrition, abrasion and erosion in tooth wear.

Tooth wear is the result of three processes: abrasion (wear produced by interaction between teeth and other materials), attrition (wear through tooth-tooth contact) and erosion (dissolution of hard tissue by acidic substances). A further process (abfraction) might potentiate wear by abrasion and/or erosion. Knowledge of these tooth wear processes and their interactions is reviewed. Both clinical and experimental observations show that individual wear mechanisms rarely act alone but interact with each other. The most important interaction is the potentiation of abrasion by erosive damage to the dental hard tissues. This interaction seems to be the major factor in occlusal and cervical wear. The available evidence is insufficient to establish whether abfraction is an important contributor to tooth wear in vivo. Saliva can modulate erosive/abrasive tooth wear, especially through formation of pellicle, but cannot prevent it.