LLukas22/scidocs huggingface dataset:
Efficacy and safety of CH-1504, a metabolically stable antifolate, in patients with active rheumatoid arthritis: results of a phase II multicenter randomized study.

OBJECTIVE
To investigate the potential efficacy, safety, and tolerability of daily use of CH-1504 in patients with active rheumatoid arthritis (RA). US National Institutes of Health database no. NCT00658047.


METHODS
In our phase II randomized double-blind double-dummy study, patients naive to methotrexate (MTX; n = 201) and having moderate to severe RA received either CH-1504 (0.25 mg, 0.5 mg, or 1.0 mg once-daily oral doses) or MTX (titrated to 20.0 mg once-weekly oral doses). All received weekly 10-mg folate supplementation. Efficacy and safety were assessed at 2, 4, 8, and 12 weeks, with a treatment-free followup at 16 weeks. Safety and tolerability were assessed. Primary efficacy endpoint was proportion of patients achieving ACR20 response at Week 12. Secondary endpoints included difference from baseline in the 28-joint Disease Activity Score (DAS28) and individual components of the American College of Rheumatology (ACR) composite index.


RESULTS
Demographic characteristics were similar in all treatment groups: mean age 54.3 ± 11.4 years, female sex 87%, mean baseline DAS28 6.6 ± 0.9. At Week 12, CH-1504 demonstrated comparable efficacy compared to MTX as measured by ACR20, DAS28, and ACR composite core-set measures, including tender and swollen joints. No dose-response relationship was observed. Adverse events across treatment groups were mild. Liver enzyme levels increased from baseline to Week 16 in the MTX group, with qualitatively lesser increases in the CH-1504 groups. Two patients in the MTX group withdrew because of gastrointestinal-related adverse events. CH-1504 appeared safe and well tolerated at all dose levels.


CONCLUSION
CH-1504 has comparable efficacy to MTX and is safe and well tolerated. Metabolically stable antifolates are a promising therapeutic option that warrants further study.
Is high mole count a marker of more than melanoma risk? Eczema diagnosis is associated with melanocytic nevi in children.

BACKGROUND
The number of melanocytic nevi is the best single marker of increased melanoma risk. In a previous study, adults with severe eczema were reported to have significantly fewer nevi than adults without eczema.


OBSERVATIONS
In a nested case-control design within a randomized, controlled interventional trial of additional sun protection vs standard care in 269 children, a history of eczema was reported by the parents of 44 (16%) of the children. More nevi were found in children with a parental report of previous eczema diagnosis than in children without reported eczema (median, 7.5 nevi vs 5.0 nevi; P =.01). Eczema diagnosis was most significantly associated with more melanocytic nevi in children with lightly pigmented skin (8.5 nevi vs 6.0 nevi; P <.001). In multivariate logistical regression analysis, including assessment of hair color, sun protection practices, and study assignment (intervention vs standard care), eczema status remained significantly predictive of nevi number in children (P <.001).


CONCLUSIONS
In contrast to a previous study that associated severe eczema with fewer nevi in adults, in the present study children with a reported history of eczema had more nevi than children without a reported history of eczema.
Constrained Centroidal Voronoi Tessellations for Surfaces

Abstract. Centroidal Voronoi tessellations are useful for subdividing a region in Euclidean space into Voronoi regions whose generators are also the centers of mass, with respect to a prescribed density function, of the regions. Their extensions to general spaces and sets are also available; for example, tessellations of surfaces in a Euclidean space may be considered. In this paper, a precise definition of such constrained centroidal Voronoi tessellations (CCVTs) is given and a number of their properties are derived, including their characterization as minimizers of an “energy.” Deterministic and probabilistic algorithms for the construction of CCVTs are presented and some analytical results for one of the algorithms are given. Computational examples are provided which serve to illustrate the high quality of CCVT point sets. Finally, CCVT point sets are applied to polynomial interpolation and numerical integration on the sphere.
Acute iliofemoral venous thrombosis in patients with atresia of the inferior vena cava can be treated successfully with catheter-directed thrombolysis.

PURPOSE
To assess the effectiveness and clinical outcomes of catheter-directed thrombolysis in patients with atresia of the inferior vena cava (IVC) and acute iliofemoral deep vein thrombosis (DVT).


MATERIALS AND METHODS
From 2001 to 2009, 11 patients (median age, 32 y) with atresia of the IVC and acute iliofemoral DVT in 13 limbs were admitted for catheter-directed thrombolysis. Through a multiple-side hole catheter inserted in the popliteal vein, continuous pulse-spray infusion of tissue plasminogen activator and heparin was performed. Thrombolysis was terminated when all thrombus was resolved and venous outflow through the paravertebral collateral vessels was achieved. After thrombolysis, all patients received lifelong anticoagulation and compression stockings and were followed up at regular intervals.


RESULTS
Ultrasound or computed tomography revealed absence of the suprarenal segment of the IVC in two patients, and nine were diagnosed with absence of the infrarenal segment of the IVC. Median treatment time was 58 hours (range, 42-95 h). No deaths or serious complications occurred. Overall, complications were observed in four patients, one of whom required blood transfusion. Three patients were diagnosed with thrombophilia. Median follow-up was 37 months (range, 51 d to 96 mo). All patients had patent deep veins and one developed reflux in the popliteal fossa after 4 years. No thromboembolic recurrences were observed during follow-up.


CONCLUSIONS
Catheter-directed thrombolysis of patients with acute iliofemoral DVT and atresia of the IVC is a viable treatment option, as reasonable clinical outcomes can be obtained.
The Effect of Neutral Peritoneal Dialysis Solution with Low Glucose-Degradation-Product on the Fluid Status and Body Composition – A Randomized Control Trial

BACKGROUND
Previous studies report conflicting results on the benefit of peritoneal dialysis (PD) patients treated with low glucose degradation product (GDP) solution. The effects of low GDP solution on body fluid status and arterial pulse wave velocity (PWV) have not been studied.


METHODS
We randomly assigned 68 incident PD patients to low GDP (Intervention Group) or conventional solutions (Control Group); 4 dropped off before they received the assigned treatment. Patients were followed for 52 weeks for changes in ultrafiltration, residual renal function, body fluid status and arterial PWV.


RESULT
After 52 weeks, Intervention Group had higher overhydration (3.1 ± 2.6 vs 1.9 ± 2.2 L, p = 0.045) and extracellular water volume (17.7 ± 3.9 vs 15.8 ± 3.1 L, p = 0.034) than Control Group. There was no significant difference in PWV between groups. There was no significant difference in residual renal function between the Groups. Intervention Group had lower ultrafiltration volume than Control Group at 4 weeks (0.45 ± .0.61 vs 0.90 ± 0.79 L/day, p = 0.013), but the difference became insignificant at later time points. Intervention Group had lower serum CRP levels than Control Group (4.17 ± 0.77 vs 4.91 ± 0.95 mg/dL, p < 0.0001).


CONCLUSION
Incident PD patients treated with low GDP solution have less severe systemic inflammation but trends of less ultrafiltration, and more fluid accumulation. However, the effects on ultrafiltration and fluid accumulation disappear with time. The long term effect of low GDP solution requires further study.


TRIAL REGISTRATION
ClinicalTrials.gov NCT00966615.
Knowledge Management and the Leading IS Journals: An Analysis of Trends and Gaps in Published Research

Knowledge management (KM) is maturing as a research topic, although there is still debate among researchers over what constructs form its basis. Because the topic has received increasing attention in academic journals, it is important for researchers to be aware of the research streams associated with KM. Accordingly, this paper reviews the knowledge management literature published in top-tier journals from 2000 to 2003. These articles are then classified into five constructs from two knowledge management frameworks. The results indicate that the majority of knowledge management research has examined the construct of knowledge transfer and approximately one third of the research is empirical in nature. Trends of published KM research, gaps, and inconsistencies in the examined literature, and areas of potential research are presented.
Unusually large interthalamic adhesion and its clinical importance

Introduction Interthalamic adhesion is a structure that connects the medial surfaces of the two thalami. It crosses the cavity of the third ventricle. It is roughly about 1 cm in diameter and is made up of nerve cell bodies and a few nerve fibers. Exact function of the adhesion is not known as its absence has not caused any functional deficits. It is absent in about 20% of the cases. When enlarged, it may cause hindrance to the flow of cerebrospinal fluid. We saw an unusually large interthalamic adhesion and the same is being reported here. Case Report During regular dissections for undergraduate medical students at Melaka Manipal Medical College (Manipal Campus) we found an unusually large interthalamic adhesion (Figure 1). The variation was found in a male cadaver aged approximately 70 years. The interthalamic adhesion was coma shaped in sectional view and was about 3 cm in anteroposterior diameter. It connected most of the area on the medial surfaces of the two thalami. The cavity of the third ventricle was confined to the part below the hypothalamic sulcus. All the parts of the body and brain were normal other than the large size of the interthalamic adhesion. Discussion Interthalamic adhesion is a variable structure and it may be totally absent [1]. In the past, several studies have been conducted on the variations of thalamus and interthalamic Satheesha NAYAK B. [1] Soumya KV [2]
A Sequential Learning Approach for Single Hidden Layer Neural Networks

A sequential orthogonal approach to the building and training of single hidden layer neural networks is presented in this paper. In the proposed method, hidden neurons are added one at a time. The procedure starts with a single hidden neuron and sequentially increases the number of hidden neurons until the model error is sufficiently small. When adding a neuron, the new information introduced by this neuron is caused by that part of its output vector which is orthogonal to the space spanned by the output vectors of previously added hidden neurons. The classical Gram-Schmidt orthogonalization method is used at each step to form a set of orthogonal bases for the space spanned by the output vectors of hidden neurons. Hidden layer weights are found through optimization while output layer weights are obtained from the least-squares regression. Using the proposed technique, it is possible to determine the necessary number of hidden neurons required. A regularization factor is also incorporated into the sequential orthogonal training algorithm to improve the network generalization capability. An additional advantage of this method is that it can be used to build and train neural networks with mixed types of hidden neurons and thus to develop hybrid models. By using mixed types of neurons, it is found that more accurate neural network models, with a smaller number of hidden neurons than seen in conventional networks, can be developed. The proposed sequential orthogonal training method was successfully applied to three non-linear modelling examples.
A Taxonomy and Survey of Cloud Computing Systems

The computational world is becoming very large and complex. Cloud Computing has emerged as a popular computing model to support processing large volumetric data using clusters of commodity computers. According to J.Dean and S. Ghemawat [1], Google currently processes over 20 terabytes of raw web data. It's some fascinating, large-scale processing of data that makes your head spin and appreciate the years of distributed computing fine-tuning applied to today's large problems. The evolution of cloud computing can handle such massive data as per on demand service. Nowadays the computational world is opting for pay-for-use models and Hype and discussion aside, there remains no concrete definition of cloud computing. In this paper, we first develop a comprehensive taxonomy for describing cloud computing architecture. Then we use this taxonomy to survey several existing cloud computing services developed by various projects world-wide such as Google, force.com, Amazon. We use the taxonomy and survey results not only to identify similarities and differences of the architectural approaches of cloud computing, but also to identify areas requiring further research.
Data Distillation for Controlling Specificity in Dialogue Generation

People speak at different levels of specificity in different situations.1 A conversational agent should have this ability and know when to be specific and when to be general. We propose an approach that gives a neural network–based conversational agent this ability. Our approach involves alternating between data distillation and model training : removing training examples that are closest to the responses most commonly produced by the model trained from the last round and then retrain the model on the remaining dataset. Dialogue generation models trained with different degrees of data distillation manifest different levels of specificity. We then train a reinforcement learning system for selecting among this pool of generation models, to choose the best level of specificity for a given input. Compared to the original generative model trained without distillation, the proposed system is capable of generating more interesting and higher-quality responses, in addition to appropriately adjusting specificity depending on the context. Our research constitutes a specific case of a broader approach involving training multiple subsystems from a single dataset distinguished by differences in a specific property one wishes to model. We show that from such a set of subsystems, one can use reinforcement learning to build a system that tailors its output to different input contexts at test time. Depending on their knowledge, interlocutors, mood, etc.
Modeling industrial energy demand in Greece using cointegration techniques

This paper attempts to shed light on the determinants of industrial energy demand in Greece. For this purpose we used cointegration analysis in order to capture short-run and long-run elasticities for oil and electricity industrial demand, respectively. The sample spans the period 1970–2004. From the empirical analysis and the Johansen’s maximum likelihood procedure we found cointegration for oil and electricity demand. The results suggest that industrial energy demand is inelastic both in the short and the long run, while electricity and oil are substitutes. Also, oil and electricity prices are weakly exogenous both in the short and the long run. r 2007 Elsevier Ltd. All rights reserved.
Effect of Vitamin C Supplementation on Serum Uric Acid in Patients Undergoing Hemodialysis

Introduction. Clinical studies of recent years have shown that hyperuricemia is associated with poor outcomes such as cardiovascular mortality and dialysis inadequacy in patients undergoing hemodialysis. Our study investigated the effect of vitamin C supplementation on serum uric acid levels in hemodialysis patients. Materials and Methods. This randomized placebo-controlled trial was conducted on 172 hemodialysis patients. They were randomly divided into the intervention group, to receive 250 mg of vitamin C, three times per week, for 8 weeks, and control groups 1 and 2, to receive placebo injection (saline) and no intervention, respectively. Serum levels of uric acid and creatinine were measured at the start of the study and also after 8 weeks. Results. The mean of serum levels of uric acid was 6.02 ± 1.08 mg/ dL (reference range, 2.6 mg/dL to 6 mg/dL). Nearly, half of the patients (46.7%) had a serum level of uric acid greater than 6 mg/ dL. The median baseline serum levels of uric acid were 6.2 mg/ dL, 5.9 mg/dL, and 6 mg/dL in the intervention, control 1, and control 2 groups, respectively (P = .19). After 2 months, median levels reduced significantly in the vitamin C group to 5.8 mg/ dL as compared to 6.4 mg/dL and 6.3 mg/dL in control groups (P = .02). The mean serum creatinine level had no significant changes during the study. Conclusions. Our results demonstrated the existence of a significant negative relationship between vitamin C and serum uric acid levels. Detailed investigations with larger sample sizes and longer-term use of vitamin C are recommended.
Control theoretic approach to tracking radar: First step towards cognition

Article history: Available online xxxx
ANOMALY DETECTION OF ATTACKS (ADA) ON DNN CLASSIFIERS AT TEST TIME

A significant threat to wide deployment of machine learning-based classifiers is adversarial learning attacks, especially at test-time. Recently there has been significant development in defending against such attacks. Several such works seek to robustify the classifier to make "correct" decisions on perturbed patterns. We argue it is often operationally more important to detect the attack, rather than to "correctly classify" in the face of it (Classification can proceed if no attack is detected). We hypothesize that, even if human-imperceptible, adversarial perturbations are machine-detectable. We propose a purely unsupervised anomaly detector (AD), based on suitable (null hypothesis) density models for the different layers of a deep neural net and a novel decision statistic built upon the Kullback-Leibler divergence. This paper addresses: 1) when is it appropriate to aim to "correctly classify" a perturbed pattern?; 2) What is a good AD detection statistic, one which exploits all likely sources of anomalousness associated with a test-time attack? 3) Where in a deep neural net (DNN) (in an early layer, a middle layer, or at the penultimate layer) will the most anomalous signature manifest? Tested on MNIST and CIFAR-10 image databases under three prominent attack strategies, our approach outperforms previous detection methods, achieving strong ROC AUC detection accuracy on two attacks and substantially better accuracy than previously reported on the third (strongest) attack.
Recommender System Framework Using Clustering and Collaborative Filtering

Collaborative filtering is becoming greatly popular as it contributes in reducing information overload. Collaborative filtering based recommender system focuses on predicting new items of interest for a user based on correlations computed between that user and other users. In this paper we propose a framework based on, application of data partitioning/clustering algorithm on ratings dataset followed by collaborative filtering for developing a Movie Recommender System. The proposed system reduces the computation time considerably and increases the prediction accuracy.
Anomaly detection in vessel tracks using Bayesian networks

Article history: Available online 2 April 2013
Semi Automatic Development of FarsNet ; The Persian WordNet

This paper describes the development process of FarsNet; a lexical ontology for the Persian language. FarsNet is designed to contain a Persian WordNet with about 10000 synsets in its first phase and grow to cover verbs' argument structures and their selectional restrictions in its second phase. In this paper we discuss the semi-automatic approach to create the first phase: the Persian WordNet.
PERIODIC ORBIT THEORY INCLUDING SPIN DEGREES OF FREEDOM

We summarize recent developments of the semiclassical description of shell effects in finite fermion systems with explicit inclusion of spin degrees of freedom, in particluar in the presence of spin-orbit interactions. We present a new approach that makes use of spin coherent states and a correspondingly enlarged classical phase space. Taking suitable limits, we can recover some of the earlier approaches. Applications to some model systems are presented.
MPC-MPI: An MPI Implementation Reducing the Overall Memory Consumption

Message-Passing Interface (MPI) has become a standard for parallel applications in high-performance computing. Within a shared address space, MPI implementations benefit from the global memory to speed-up intra-node communications while the underlying network protocol is exploited to communicate between nodes. But, it requires the allocation of additional buffers leading to a memory-consumption overhead. This may become an issue on future clusters with reduced memory amount per core. In this article, we propose an MPI implementation upon the MPC framework called MPC-MPI reducing the overall memory footprint. We obtained up to 47% of memory gain on benchmarks and a real-world application.
Individualised homeopathy as an adjunct in the treatment of childhood asthma: a randomised placebo controlled trial.

BACKGROUND
Homeopathy is frequently used to treat asthma in children. In the common classical form of homeopathy, prescriptions are individualised for each patient. There has been no rigorous investigation into this form of treatment for asthma.


METHODS
In a randomised, double blind, placebo controlled trial the effects of individualised homeopathic remedies were compared with placebo medication in 96 children with mild to moderate asthma as an adjunct to conventional treatment. The main outcome measure was the active quality of living subscale of the Childhood Asthma Questionnaire administered at baseline and follow up at 12 months. Other outcome measures included other subscales of the same questionnaire, peak flow rates, use of medication, symptom scores, days off school, asthma events, global assessment of change, and adverse reactions.


RESULTS
There were no clinically relevant or statistically significant changes in the active quality of life score. Other subscales, notably those measuring severity, indicated relative improvements but the sizes of the effects were small. There were no differences between the groups for other measures.


CONCLUSIONS
This study provides no evidence that adjunctive homeopathic remedies, as prescribed by experienced homeopathic practitioners, are superior to placebo in improving the quality of life of children with mild to moderate asthma in addition to conventional treatment in primary care.
Groupoid cocycles and derivations

This is a study of derivations constructed from conditionally negative type functions on groupoids which illustrates Sauvageot's theory of non-commutative Dirichlet forms.
Learning to Learn

Connectionist networks that have learned one task can be reused on related tasks in a process that is called "transfer". This paper surveys recent work on transfer. A number of distinctions between kinds of transfer are identified, and future directions for research are explored. The study of transfer has a long history in cognitive science. Discoveries about transfer in human cognition can inform applied efforts. Advances in applications can also inform cognitive studies.
Structure de la region d'Ijibiten (feuille El Gleitat, E d'Akjoujt, Mauritanie occidentale)

Folds, overthrusts, four units, Precambrian basement rocks, sedimentary cover of Paleozoic age, Reg unit overthrust, and the epimetamorphic formations