LLukas22/scidocs huggingface dataset:
Wolf Motor Function Test for characterizing moderate to severe hemiparesis in stroke patients.

OBJECTIVE
To extend the applicability of the Wolf Motor Function Test (WMFT) to describe the residual functional abilities of moderate to severely affected stroke patients.


DESIGN
Data were collected as part of 2 double-blind, sham-controlled, randomized interventional studies: the Transcranial Direct Current Stimulation (tDCS) in Chronic Stroke Recovery and the tDCS Enhanced Stroke Recovery and Cortical Reorganization. Stroke patients were evaluated with the upper extremity Fugl-Meyer (UFM) and the WMFT in the same setting before treatment.


SETTING
University inpatient rehabilitation and outpatient clinic.


PARTICIPANTS
Stroke patients (N=32) with moderate to severe hemiparesis enrolled in the tDCS in Chronic Stroke Recovery and the tDCS Enhanced Stroke Recovery and Cortical Reorganization studies.


INTERVENTIONS
Not applicable.


MAIN OUTCOME MEASURES
WMFT scores were calculated using (1) median performance times and (2) a new calculation using the mean rate of performance. We compared the distribution of values from the 2 methods and examined the WMFT-UFM correlation for the traditional and the new calculation.


RESULTS
WMFT rate values were more evenly distributed across their range than median WMFT time scores. The association between the WMFT rate and UFM was as good as the association between the median WMFT time scores and UFM (Spearman ρ, .84 vs -.79).


CONCLUSIONS
The new WMFT mean rate of performance is valid and a more sensitive measure in describing the functional activities of the moderate to severely affected upper extremity of stroke subjects and avoids the pitfalls of the median WMFT time calculations.
Inheritance and usefulness of AFLP markers in channel catfish (Ictalurus punctatus), blue catfish (I. furcatus), and their F1, F2, and backcross hybrids

Eight primer combinations were used to investigate the application of amplified fragment length polymorphism (AFLP) markers in catfish for genetic analysis. Intraspecific polymorphism was low among channel catfish or blue catfish strains. Interspecific AFLP polymorphism was high between the channel catfish and blue catfish. Each primer combination generated from 70 to more than 200 bands, of which 38.6–75.7% were polymorphic between channel catfish and blue catfish. On average, more than 20 polymorphic bands per primer combination were produced as quality markers suitable for genetic analysis. All AFLP markers were transmitted into channel catfish × blue catfish F1 hybrids, except rare markers that were heterozygous in the parents and therefore were segregating in F1 hybrids. The two reciprocal channel catfish × blue catfish F1 hybrids (channel catfish female × blue catfish male; blue catfish female × channel catfish male) produced identical AFLP profiles. The AFLP markers were inherited and segregated in expected Mendelian ratios. At two loci, E8-b9 and E8-b2, markers were found at significantly lower frequencies than expected with F2 and backcross hybrids which had been selected for increased growth rates. The reproducibility of AFLP was excellent. These characteristics of the catfish AFLP markers make them highly useful for genetic analysis of catfish, especially for construction of genetic linkage and quantitative trait loci maps, and for marker-assisted selection.
News article ranking: leveraging the wisdom of bloggers

Every day, editors rank news articles for placement within t heir newspapers. In this paper, we investigate how news article r anking can be performed automatically. In particular, we inves tigate the blogosphere as a prime source of evidence, on the intuiti on that bloggers, and by extension their blog posts, can indicate in terest in one news article or another. Moreover, we propose to model this automatic news article ranking task as a voting process, whe re each relevant blog post acts as a vote for one or more news articles . W evaluate this approach using the TREC 2009 Blog track top new s story identification task judgments, showing strong perfor mance in comparison to TREC systems, as well as two alternative basel ine rankings. Furthermore, to increase the accuracy of the prop osed approach, we examine temporal re-ranking techniques, corpus cleaning of inappropriate articles and article expansion to coun ter vocabulary mismatch. We conclude that, overall, blog post eviden ce can be a useful indicator to a news editor as to the importance of v arious news stories, and that our approaches for extracting this ev idence are effective. General Terms: Ranking, Information Retrieval, Social networks
Parietal rTMS distorts the mental number line: Simulating ‘spatial’ neglect in healthy subjects

Patients with left-sided visuospatial neglect, typically after damage to the right parietal lobe, show a systematic bias towards larger numbers when asked to bisect a numerical interval. This has been taken as further evidence for a spatial representation of numbers, perhaps akin to a mental number line with smaller numbers represented to the left and larger numbers to the right. Previously, contralateral neglect-like symptoms in physical line bisection have been induced in healthy subjects with repetitive transcranial magnetic stimulation (rTMS) over right posterior parietal lobe. Here we used rTMS over parietal and occipital sites in healthy subjects to investigate spatial representations in a number bisection task. Subjects were asked to name the midpoint of numerical intervals without calculating. On control trials subjects' behaviour was similar to performance reported in physical line bisection experiments. Subjects underestimated the midpoint of the numerical interval. Repetitive transcranial magnetic stimulation produced representational neglect-like symptoms in number bisection when applied over right posterior parietal cortex (right PPC). Repetitive TMS over right PPC shifted the perceived midpoint of the numerical interval significantly to the right while occipital TMS had no effect on bisection performance. Our study therefore provides further evidence that subjects use spatial representations, perhaps akin to a mental number line, in basic numerical processing tasks. Furthermore, we showed that the right posterior parietal cortex is crucially involved in spatial representation of numbers.
Real-time multiple vehicle detection and tracking from a moving vehicle

 Abstract. A real-time vision system has been developed that analyzes color videos taken from a forward-looking video camera in a car driving on a highway. The system uses a combination of color, edge, and motion information to recognize and track the road boundaries, lane markings and other vehicles on the road. Cars are recognized by matching templates that are cropped from the input data online and by detecting highway scene features and evaluating how they relate to each other. Cars are also detected by temporal differencing and by tracking motion parameters that are typical for cars. The system recognizes and tracks road boundaries and lane markings using a recursive least-squares filter. Experimental results demonstrate robust, real-time car detection and tracking over thousands of image frames. The data includes video taken under difficult visibility conditions.
Inverse Jiles-Atherton vector hysteresis model

In this paper, we present a new vector hysteresis model, which is derived from the original Jiles-Atherton scalar one. The model presents the magnetic vector induction as the independent variable. A modified Langevin equation is used to represent the anhysteretic vector magnetization, and some model aspects are discussed. A comparison between measured and calculated curves for an anisotropic soft magnetic material is performed to validate the model.
A thermal model for photovoltaic panels under varying atmospheric conditions

The response of the photovoltaic (PV) panel temperature is dynamic with respect to the changes in the incoming solar radiation. During periods of rapidly changing conditions, a steady state model of the operating temperature cannot be justified because the response time of the PV panel temperature becomes significant due to its large thermal mass. Therefore, it is of interest to determine the thermal response time of the PV panel. Previous attempts to determine the thermal response time have used indoor measurements, controlling the wind flow over the surface of the panel with fans or conducting the experiments in darkness to avoid radiative heat loss effects. In real operating conditions, the effective PV panel temperature is subjected to randomly varying ambient temperature and fluctuating wind speeds and directions; parameters that are not replicated in controlled, indoor experiments. A new thermal model is proposed that incorporates atmospheric conditions; effects of PV panel material composition and mounting structure. Experimental results are presented which verify the thermal behaviour of a photovoltaic panel for low to strong winds. 2010 Elsevier Ltd. All rights reserved.
Aripiprazole monotherapy in acute mania: 12-week randomised placebo- and haloperidol-controlled study.

BACKGROUND
Well-tolerated and effective therapies for bipolar mania are required.


AIMS
To evaluate the efficacy and tolerability of aripiprazole as acute and maintenance of effect therapy in patients with bipolar I disorder experiencing manic or mixed episodes.


METHOD
Patients were randomised to double-blind aripiprazole (15 or 30 mg/day; n=167), placebo (n=153) or haloperidol (5-15 mg/day, n=165) for 3 weeks (trial registration NCT00097266). Aripiprazole- and haloperidol-treated patients remained on masked treatment for 9 additional weeks.


RESULTS
Mean change in Young Mania Rating Scale Total score (primary end-point) at week 3 was significantly greater with aripiprazole (-12.0; P<0.05) and haloperidol (-12.8; P<0.01) than with placebo (-9.7). Improvements were maintained to week 12 for aripiprazole (-17.2) and haloperidol (-17.8). Aripiprazole was well tolerated. Extrapyramidal adverse events were more frequent with haloperidol than aripiprazole (53.3% v. 23.5%).


CONCLUSIONS
Clinical improvements with aripiprazole were sustained to week 12. Aripiprazole was generally well tolerated.
A review of level-set methods and some recent applications

We review some of the recent advances in level-set methods and their applications. In particular, we discuss how to impose boundary conditions at irregular domains and free boundaries, as well as the extension of level-set methods to adaptive Cartesian grids and parallel architectures. Illustrative applications are taken from the physical and life sciences. Fast sweeping methods are briefly discussed.
Who is accessing public-sector anti-retroviral treatment in the Free State, South Africa? An exploratory study of the first three years of programme implementation

BACKGROUND
Although South Africa has the largest public-sector anti-retroviral treatment (ART) programme in the world, anti-retroviral coverage in adults was only 40.2% in 2008. However, longitudinal studies of who is accessing the South African public-sector ART programme are scarce. This study therefore had one main research question: who is accessing public-sector ART in the Free State Province, South Africa? The study aimed to extend the current literature by investigating, in a quantitative manner and using a longitudinal study design, the participants enrolled in the public-sector ART programme in the period 2004-2006 in the Free State Province of South Africa.


METHODS
Differences in the demographic (age, sex, population group and marital status) socio-economic (education, income, neo-material indicators), geographic (travel costs, relocation for ART), and medical characteristics (CD4, viral load, time since first diagnosis, treatment status) among 912 patients enrolled in the Free State public-sector ART programme between 2004 and 2006 were assessed with one-way analysis of variance, Bonferroni post-hoc analysis, and cross tabulations with the chi square test.


RESULTS
The patients accessing treatment tended to be female (71.1%) and unemployed (83.4%). However, although relatively poor, those most likely to access ART services were not the most impoverished patients. The proportion of female patients increased (P < 0.05) and their socio-economic situation improved between 2004 and 2006 (P < 0.05). The increasing mean transport cost (P < 0.05) to visit the facility is worrying, because this cost is an important barrier to ART uptake and adherence. Encouragingly, the study results revealed that the interval between the first HIV-positive diagnosis and ART initiation decreased steadily over time (P < 0.05). This was also reflected in the increasing baseline CD4 cell count at ART initiation (P < 0.05).


CONCLUSIONS
Our analysis showed significant changes in the demographic, socio-economic, geographic, and medical characteristics of the patients during the first three years of the programme. Knowledge of the characteristics of these patients can assist policy makers in developing measures to retain them in care. The information reported here can also be usefully applied to target patient groups that are currently not reached in the implementation of the ART programme.
Zygapophysial joint blocks in chronic low back pain: a test of Revel's model as a screening test

BACKGROUND
Only controlled blocks are capable of confirming the zygapophysial joints (ZJ) as the pain generator in LBP patients. However, previous workers have found that a cluster of clinical signs ("Revel's criteria"), may be valuable in predicting the results of an initial screening ZJ block. It was suggested that these clinical findings are unsuitable for diagnosis, but may be of value in selecting patients for diagnostic blocks of the lumbar ZJ's. To constitute evidence in favour of a clinical management strategy, these results need confirmation. This study evaluates the utility of 'Revel's criteria' as a screening tool for selection of chronic low back pain patients for controlled ZJ diagnostic blocks.


METHODS
This study utilized a prospective blinded concurrent reference standard related validity design. Consecutive chronic LBP patients completed pain drawings, psychosocial distress and disability questionnaires, received a clinical examination and lumbar zygapophysial blocks. Two reference standards were evaluated simultaneously: 1. 75% reduction of pain on a visual analogue scale (replication of previous work), and 2. abolition of the dominant or primary pain. Using "Revel's criteria" as predictors, logistic regression analyses were used to test the model. Estimates of sensitivity, specificity, predictive values and likelihood ratios for selected variables were calculated for the two proposed clinical strategies.


RESULTS
Earlier results were not replicated. Sensitivity of "Revel's criteria" was low sensitivity (<17%), and specificity high (approximately 90%). Absence of pain with cough or sneeze just reached significance (p = 0.05) within one model.


CONCLUSIONS
"Revel's criteria" are unsuitable as a clinical screening test to select chronic LBP patients for initial ZJ blocks. However, the criteria may have use in identifying a small subset (11%) of patients likely to respond to the initial block (specificity 93%).
Map-Reduce for Machine Learning on Multicore

We are at the beginning of the multicore era. Computers will have increasingly many cores (processors), but there is still no good programming framework for these architectures, and thus no simple and unified way for machine learning to take advantage of the potential speed up. In this paper, we develop a broadly applicable parallel programming method, one that is easily applied to manydifferent learning algorithms. Our work is in distinct contrast to the tradition in machine learning of designing (often ingenious) ways to speed up a singlealgorithm at a time. Specifically, we show that algorithms that fit the Statistical Query model [15] can be written in a certain “summation form,” which allows them to be easily parallelized on multicore computers. We adapt Google’s map-reduce [7] paradigm to demonstrate this parallel speed up technique on a variety of learning algorithms including locally weighted linear regression (LWLR), k-means, logistic regression (LR), naive Bayes (NB), SVM, ICA, PCA, gaussian discriminant analysis (GDA), EM, and backpropagation (NN). Our experimental results show basically linear speedup with an increasing number of processors.
A novel multilevel inverter topology with no clamping diodes and flying capacitors

To decrease the number of clamping diodes and flying capacitors in multilevel inverters, a novel multilevel inverter topology with no clamping diodes and flying capacitors is proposed in the paper. The topology structure, operating principle, balance of the DC link capacitor voltages, and comparisons with the conventional multilevel topologies will be discussed. The number of power switching devices needed is same as the conventional multilevel inverters, i.e. 2(M-1) for an M-level single-phase inverter. With no clamping diodes and flying capacitors, the reliability is improved and the costs are saved. But two of the switching devices will block double of one DC link capacitor voltages at some voltage levels. So this novel topology is more suitable for medium voltage applications with low THD requirements. By using the method of hybrid clamped, the DC link capacitors can be balanced with easy control. Its validity is confirmed by simulations and experiments based on a five level inverter.
High resolution microendoscopy for classification of colorectal polyps.

BACKGROUND AND STUDY AIMS
It can be difficult to distinguish adenomas from benign polyps during routine colonoscopy. High resolution microendoscopy (HRME) is a novel method for imaging colorectal mucosa with subcellular detail. HRME criteria for the classification of colorectal neoplasia have not been previously described. Study goals were to develop criteria to characterize HRME images of colorectal mucosa (normal, hyperplastic polyps, adenomas, cancer) and to determine the accuracy and interobserver variability for the discrimination of neoplastic from non-neoplastic polyps when these criteria were applied by novice and expert microendoscopists.


METHODS
Two expert pathologists created consensus HRME image criteria using images from 68 patients with polyps who had undergone colonoscopy plus HRME. Using these criteria, HRME expert and novice microendoscopists were shown a set of training images and then tested to determine accuracy and interobserver variability.


RESULTS
Expert microendoscopists identified neoplasia with sensitivity, specificity, and accuracy of 67 % (95 % confidence interval [CI] 58 % - 75 %), 97 % (94 % - 100 %), and 87 %, respectively. Nonexperts achieved sensitivity, specificity, and accuracy of 73 % (66 % - 80 %), 91 % (80 % - 100 %), and 85 %, respectively. Overall, neoplasia were identified with sensitivity 70 % (65 % - 76 %), specificity 94 % (87 % - 100 %), and accuracy 85 %. Kappa values were: experts 0.86; nonexperts 0.72; and overall 0.78.


CONCLUSIONS
Using the new criteria, observers achieved high specificity and substantial interobserver agreement for distinguishing benign polyps from neoplasia. Increased expertise in HRME imaging improves accuracy. This low-cost microendoscopic platform may be an alternative to confocal microendoscopy in lower-resource or community-based settings.
Articulated part-based model for joint object detection and pose estimation

Despite recent successes, pose estimators are still somewhat fragile, and they frequently rely on a precise knowledge of the location of the object. Unfortunately, articulated objects are also very difficult to detect. Knowledge about the articulated nature of these objects, however, can substantially contribute to the task of finding them in an image. It is somewhat surprising, that these two tasks are usually treated entirely separately. In this paper, we propose an Articulated Part-based Model (APM) for jointly detecting objects and estimating their poses. APM recursively represents an object as a collection of parts at multiple levels of detail, from coarse-to-fine, where parts at every level are connected to a coarser level through a parent-child relationship (Fig. 1(b)-Horizontal). Parts are further grouped into part-types (e.g., left-facing head, long stretching arm, etc) so as to model appearance variations (Fig. 1(b)-Vertical). By having the ability to share appearance models of part types and by decomposing complex poses into parent-child pairwise relationships, APM strikes a good balance between model complexity and model richness. Extensive quantitative and qualitative experiment results on public datasets show that APM outperforms state-of-the-art methods. We also show results on PASCAL 2007 - cats and dogs - two highly challenging articulated object categories.
From random walks to distances on unweighted graphs

The spatial graph model depends on the following latent quantities: • p(x): latent probability density in compact connected smooth domain D ⊂ Rd; •Xn = {x1, . . . , xn}: coordinate points drawn i.i.d. from p(x); • εn(xi) : Xn → R>0: local scale function (may depend on Xn); • h : R≥0 → [0, 1]: connectivity kernel with h(x) = 0 for x > 1, h(1) > 0, and h left-continuous at 1. Definition 1: Spatial graph The spatial graph Gn corresponding to εn and h is the random graph with: • vertex set Xn; • a directed edge from xi to xj with probability h(|xi − xj|εn(xi)).
On the Learnability of Fully-Connected Neural Networks

Despite the empirical success of deep neural networks, there is limited theoretical understanding of the learnability of these models with respect to polynomial-time algorithms. In this paper, we characterize the learnability of fullyconnected neural networks via both positive and negative results. We focus on `1-regularized networks, where the `1-norm of the incoming weights of every neuron is assumed to be bounded by a constant B > 0. Our first result shows that such networks are properly learnable in poly(n, d, exp(1/ )) time, where n and d are the sample size and the input dimension, and > 0 is the gap to optimality. The bound is achieved by repeatedly sampling over a low-dimensional manifold so as to ensure approximate optimality, but avoids the exp(d) cost of exhaustively searching over the parameter space. We also establish a hardness result showing that the exponential dependence on 1/ is unavoidable unless RP = NP. Our second result shows that the exponential dependence on 1/ can be avoided by exploiting the underlying structure of the data distribution. In particular, if the positive and negative examples can be separated with margin γ > 0 by an unknown neural network, then the network can be learned in poly(n, d, 1/ ) time. The bound is achieved by an ensemble method which uses the first algorithm as a weak learner. We further show that the separability assumption can be weakened to tolerate noisy labels. Finally, we show that the exponential dependence on 1/γ is unimprovable under a certain cryptographic assumption. Proceedings of the 20 International Conference on Artificial Intelligence and Statistics (AISTATS) 2017, Fort Lauderdale, Florida, USA. JMLR: W&CP volume 54. Copyright 2017 by the author(s).
Response Surface Model Building and Multidisciplinary Optimization Using D-Optimal Designs

This paper discusses response surface methods for approximation model building and multidisciplinary design optimization. The response surface methods discussed are central composite designs, Bayesian methods and Doptimal designs. An over-determined D-optimal design is applied to a configuration design and optimization study of a wing-body, launch vehicle. Results suggest that over determined Doptimal designs may provide an efficient approach for approximation model building and for multidisciplinary design optimization.