Hazard Assessment for Manufacture of Combustible Cartridge Cases using Picrite

A systematic study of the effect of impact, friction, flame and electric spark sensitivity was carried out on the samples combustible cartridge case (CCC) withdrawn at different stages of manufacture. These are Stage I dried felted CCC; stage II-CCC from stage III Coated with nitrocellulose coating. based on the results obtained from various experiments, the CCC can be classified for handling storage and transportation as Group 3, for safety distance category as UN 1.3 and for fire fighting as class 2. further it is concluded from hazard analysis study that the CCCs are safe to handle but these should be protected from naked flame

The Effects of Vision Impairment on Balance in Athletes and Non-Athletes

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Commission des Communautes Europeennes: Groupe du Porte-Parole = Commission of European Communities: Spokesman Group. Spokesman Service Note to National Offices Bio No. (81) 276, 8 July 1981

This paper presents a novel approach for multi-lingual sentiment classification in short texts. This is a challenging task as the amount of training data in languages other than English is very limited. Previously proposed multi-lingual approaches typically require to establish a correspondence to English for which powerful classifiers are already available. In contrast, our method does not require such supervision. We leverage large amounts of weakly-supervised data in various languages to train a multi-layer convolutional network and demonstrate the importance of using pre-training of such networks. We thoroughly evaluate our approach on various multi-lingual datasets, including the recent SemEval-2016 sentiment prediction benchmark (Task 4), where we achieved state-of-the-art performance. We also compare the performance of our model trained individually for each language to a variant trained for all languages at once. We show that the latter model reaches slightly worse – but still acceptable – performance when compared to the single language model, while benefiting from better generalization properties across languages

SentiBench - a benchmark comparison of state-of-the-practice sentiment analysis methods

In the last few years thousands of scientific papers have investigated sentiment analysis, several startups that measure opinions on real data have emerged and a number of innovative products related to this theme have been developed. There are multiple methods for measuring sentiments, including lexical-based and supervised machine learning methods. Despite the vast interest on the theme and wide popularity of some methods, it is unclear which one is better for identifying the polarity (i.e., positive or negative) of a message. Accordingly, there is a strong need to conduct a thorough apple-to-apple comparison of sentiment analysis methods, \textit{as they are used in practice}, across multiple datasets originated from different data sources. Such a comparison is key for understanding the potential limitations, advantages, and disadvantages of popular methods. This article aims at filling this gap by presenting a benchmark comparison of twenty-four popular sentiment analysis methods (which we call the state-of-the-practice methods). Our evaluation is based on a benchmark of eighteen labeled datasets, covering messages posted on social networks, movie and product reviews, as well as opinions and comments in news articles. Our results highlight the extent to which the prediction performance of these methods varies considerably across datasets. Aiming at boosting the development of this research area, we open the methods' codes and datasets used in this article, deploying them in a benchmark system, which provides an open API for accessing and comparing sentence-level sentiment analysis methods

Changes in the Frontotemporal Cortex and Cognitive Correlates in First-Episode Psychosis

Background: Loss of cortical volume in frontotemporal regions has been reported in patients with schizophrenia and their relatives. Cortical area and thickness are determined by different genetic processes, and measuring these parameters separately may clarify disturbances in corticogenesis relevant to schizophrenia. Our study also explored clinical and cognitive correlates of these parameters.Methods: Thirty-seven patients with first-episode psychosis (34 schizophrenia, 3 schizoaffective disorder) and 38 healthy control subjects matched for age and sex took part in the study. Imaging was performed on an magnetic resonance imaging 1.5-T scanner. Area and thickness of the frontotemporal cortex were measured using a surface-based morphometry method (Freesurfer). All subjects underwent neuropsychologic testing that included measures of premorbid and current IQ, working and verbal memory, and executive function.Results: Reductions in cortical area, more marked in the temporal cortex, were present in patients. Overall frontotemporal cortical thickness did not differ between groups, although regional thinning of the right superior temporal region was observed in patients. There was a significant association of both premorbid IQ and IQ at disease onset with area, but not thickness, of the frontotemporal cortex, and working memory span was associated with area of the frontal cortex. These associations remained significant when only patients with schizophrenia were considered.Conclusions: Our results suggest an early disruption of corticogenesis in schizophrenia, although the effect of subsequent environmental factors cannot be excluded. In addition, cortical abnormalities are subject to regional variations and differ from those present in neurodegenerative diseases

White matter microstructural perturbations after total sleep deprivation in depression

BackgroundTotal sleep deprivation (TSD) transiently reverses depressive symptoms in a majority of patients with depression. How TSD modulates diffusion tensor imaging (DTI) measures of white matter (WM) microstructure, which may be linked with TSD’s rapid antidepressant effects, remains uncharacterized.MethodsPatients with depression (N = 48, mean age = 33, 26 women) completed diffusion-weighted imaging and Hamilton Depression Rating (HDRS) and rumination scales before and after >24 h of TSD. Healthy controls (HC) (N = 53, 23 women) completed the same assessments at baseline, and after receiving TSD in a subset of HCs (N = 15). Tract based spatial statistics (TBSS) investigated voxelwise changes in fractional anisotropy (FA) across major WM pathways pre-to-post TSD in patients and HCs and between patients and HCs at baseline. Post hoc analyses tested for TSD effects for other diffusion metrics, and the relationships between change in diffusion measures with change in mood and rumination symptoms.ResultsSignificant improvements in mood and rumination occurred in patients with depression (both p < 0.001), but not in HCs following TSD. Patients showed significant (p < 0.05, corrected) decreases in FA values in multiple WM tracts, including the body of the corpus callosum and anterior corona radiata post-TSD. Significant voxel-level changes in FA were not observed in HCs who received TSD (p > 0.05). However, differential effects of TSD between HCs and patients were found in the superior corona radiata, frontal WM and the posterior thalamic radiation (p < 0.05, corrected). A significant (p < 0.05) association between change in FA and axial diffusivity within the right superior corona radiata and improvement in rumination was found post-TSD in patients.ConclusionTotal sleep deprivation leads to rapid microstructural changes in WM pathways in patients with depression that are distinct from WM changes associated with TSD observed in HCs. WM tracts including the superior corona radiata and posterior thalamic radiation could be potential biomarkers of the rapid therapeutic effects of TSD. Changes in superior corona radiata FA, in particular, may relate to improvements in maladaptive rumination

The Global ECT-MRI Research Collaboration (GEMRIC): Establishing a multi-site investigation of the neural mechanisms underlying response to electroconvulsive therapy.

Major depression, currently the world's primary cause of disability, leads to profound personal suffering and increased risk of suicide. Unfortunately, the success of antidepressant treatment varies amongst individuals and can take weeks to months in those who respond. Electroconvulsive therapy (ECT), generally prescribed for the most severely depressed and when standard treatments fail, produces a more rapid response and remains the most effective intervention for severe depression. Exploring the neurobiological effects of ECT is thus an ideal approach to better understand the mechanisms of successful therapeutic response. Though several recent neuroimaging studies show structural and functional changes associated with ECT, not all brain changes associate with clinical outcome. Larger studies that can address individual differences in clinical and treatment parameters may better target biological factors relating to or predictive of ECT-related therapeutic response. We have thus formed the Global ECT-MRI Research Collaboration (GEMRIC) that aims to combine longitudinal neuroimaging as well as clinical, behavioral and other physiological data across multiple independent sites. Here, we summarize the ECT sample characteristics from currently participating sites, and the common data-repository and standardized image analysis pipeline developed for this initiative. This includes data harmonization across sites and MRI platforms, and a method for obtaining unbiased estimates of structural change based on longitudinal measurements with serial MRI scans. The optimized analysis pipeline, together with the large and heterogeneous combined GEMRIC dataset, will provide new opportunities to elucidate the mechanisms of ECT response and the factors mediating and predictive of clinical outcomes, which may ultimately lead to more effective personalized treatment approaches

Major Superficial White Matter Abnormalities in Huntington's Disease

Background: The late myelinating superficial white matter at the juncture of the cortical gray and white matter comprising the intracortical myelin and short-range association fibers has not received attention in Huntington's disease. It is an area of the brain that is late myelinating and is sensitive to both normal aging and neurodegenerative disease effects. Therefore, it may be sensitive to Huntington's disease processes. Methods: Structural MRI data from 25 Pre-symptomatic subjects, 24 Huntington's disease patients and 49 healthy controls was run through a cortical pattern-matching program. The surface corresponding to the white matter directly below the cortical gray matter was then extracted. Individual subject's Diffusion Tensor Imaging (DTI) data was aligned to their structural MRI data. Diffusivity values along the white matter surface were then sampled at each vertex point. DTI measures with high spatial resolution across the superficial white matter surface were then analyzed with the General Linear Model to test for the effects of disease. Results: There was an overall increase in the axial and radial diffusivity across much of the superficial white matter (p < 0.001) in Pre-symptomatic subjects compared to controls. In Huntington's disease patients increased diffusivity covered essentially the whole brain (p < 0.001). Changes are correlated with genotype (CAG repeat number) and disease burden (p < 0.001). Conclusions: This study showed broad abnormalities in superficial white matter even before symptoms are present in Huntington's disease. Since, the superficial white matter has a unique microstructure and function these abnormalities suggest it plays an important role in the disease

Volume changes and brain-behavior relationships in white matter and subcortical gray matter in children with prenatal alcohol exposure: Volume Changes and Brain-Behavior in Children with PAE

Children with prenatal alcohol exposure (PAE) may have cognitive, behavioral and brain abnormalities. Here, we compare rates of white matter and subcortical gray matter volume change in PAE and control children, and examine relationships between annual volume change and arithmetic ability, behavior, and executive function. Participants (n=75 PAE/64 control; age: 7.1–15.9 years) each received two structural magnetic resonance scans, ~2 years apart. Assessments included Wechsler Intelligence Scale for Children (WISC-IV), the Child Behavior Checklist (CBCL) and the Behavior Rating Inventory of Executive Function (BRIEF). Subcortical white and gray volumes were extracted for each hemisphere. Group volume differences were tested using false discovery rate (FDR, q<0.05). Analyses examined group-by-age interactions and group-score interactions for correlations between change in volume and raw behavioral scores. Results showed that subjects with PAE had smaller volumes than control subjects across the brain. Significant group-score interactions were found in temporal and parietal regions for WISC arithmetic scores and in frontal and parietal regions for behavioral measures. Poorer cognitive/ behavioral outcomes were associated with larger volume increases in PAE, while control subjects generally showed no significant correlations. In contrast with previous results demonstrating different trajectories of cortical volume change in PAE, our results show similar rates of subcortical volume growth in subjects with PAE and control subjects. We also demonstrate abnormal brain-behavior relationships in subjects with PAE, suggesting different use of brain resources. Our results are encouraging in that, due to the stable volume differences, there may be an extended window of opportunity for intervention in children with PAE