nils-herrmann/clean_scirepeval huggingface dataset:
Flooding and Mental Health: A Systematic Mapping Review

Floods are the most common type of global natural disaster. Floods have a negative impact on mental health. Comprehensive evaluation and review of the literature are lacking.



To systematically map and review available scientific evidence on mental health impacts of floods caused by extended periods of heavy rain in river catchments.



We performed a systematic mapping review of published scientific literature in five languages for mixed studies on floods and mental health. PUBMED and Web of Science were searched to identify all relevant articles from 1994 to May 2014 (no restrictions).



The electronic search strategy identified 1331 potentially relevant papers. Finally, 83 papers met the inclusion criteria. Four broad areas are identified: i) the main mental health disorders-post-traumatic stress disorder, depression and anxiety; ii] the factors associated with mental health among those affected by floods; iii) the narratives associated with flooding, which focuses on the long-term impacts of flooding on mental health as a consequence of the secondary stressors; and iv) the management actions identified. The quantitative and qualitative studies have consistent findings. However, very few studies have used mixed methods to quantify the size of the mental health burden as well as exploration of in-depth narratives. Methodological limitations include control of potential confounders and short-term follow up.



Floods following extreme events were excluded from our review.



Although the level of exposure to floods has been systematically associated with mental health problems, the paucity of longitudinal studies and lack of confounding controls precludes strong conclusions.



We recommend that future research in this area include mixed-method studies that are purposefully designed, using more rigorous methods. Studies should also focus on vulnerable groups and include analyses of policy and practical responses.
On winding design of a high performance ferrite motor for traction application

Design of low cost traction motors with ferrite magnets needs to meet challenges such as minimizing the risk of demagnetization, and maximizing the torque and power density, via a suitable choice of rotor and stator winding topology and parameters. With regards to the stator, distributed and concentrated windings may have both advantages and disadvantages when considering manufacturing cost, slot fill factor, the contribution factor of reluctance torque and parasitic effects. Furthermore, the trend toward high speed operation of the traction motors may increase the AC loss effects in the windings, contributing to motor deficiencies and risk of thermal failure. In this paper, the performance of a high speed ferrite motor with a distributed and concentrated wound stator, and with regards to torque and power performance as well AC loss effects is assessed. The dynamic performance of a full scale prototype design based on a distributed aluminum wound stator is presented.
Segmentation of white blood cells and comparison of cell morphology by linear and naïve Bayes classifiers

Blood smear microscopic images are routinely investigated by haematologists to diagnose most blood diseases. However, the task is quite tedious and time consuming. An automatic detection and classification of white blood cells within such images can accelerate the process tremendously. In this paper we propose a system to locate white blood cells within microscopic blood smear images, segment them into nucleus and cytoplasm regions, extract suitable features and finally, classify them into five types: basophil, eosinophil, neutrophil, lymphocyte and monocyte.



Two sets of blood smear images were used in this study's experiments. Dataset 1, collected from Rangsit University, were normal peripheral blood slides under light microscope with 100× magnification; 555 images with 601 white blood cells were captured by a Nikon DS-Fi2 high-definition color camera and saved in JPG format of size 960 × 1,280 pixels at 15 pixels per 1 μm resolution. In dataset 2, 477 cropped white blood cell images were downloaded from CellaVision.com. They are in JPG format of size 360 × 363 pixels. The resolution is estimated to be 10 pixels per 1 μm.



The proposed system comprises a pre-processing step, nucleus segmentation, cell segmentation, feature extraction, feature selection and classification. The main concept of the segmentation algorithm employed uses white blood cell's morphological properties and the calibrated size of a real cell relative to image resolution. The segmentation process combined thresholding, morphological operation and ellipse curve fitting. Consequently, several features were extracted from the segmented nucleus and cytoplasm regions. Prominent features were then chosen by a greedy search algorithm called sequential forward selection. Finally, with a set of selected prominent features, both linear and naïve Bayes classifiers were applied for performance comparison. This system was tested on normal peripheral blood smear slide images from two datasets.



Two sets of comparison were performed: segmentation and classification. The automatically segmented results were compared to the ones obtained manually by a haematologist. It was found that the proposed method is consistent and coherent in both datasets, with dice similarity of 98.9 and 91.6% for average segmented nucleus and cell regions, respectively. Furthermore, the overall correction rate in the classification phase is about 98 and 94% for linear and naïve Bayes models, respectively.



The proposed system, based on normal white blood cell morphology and its characteristics, was applied to two different datasets. The results of the calibrated segmentation process on both datasets are fast, robust, efficient and coherent. Meanwhile, the classification of normal white blood cells into five types shows high sensitivity in both linear and naïve Bayes models, with slightly better results in the linear classifier.
Stigma as related to mental disorders.

Individuals with mental illness receive harsh stigmatization, resulting in decreased life opportunities and a loss of independent functioning over and above the impairments related to mental disorders themselves. We begin our review with a multidisciplinary discussion of mechanisms underlying the strong propensity to devalue individuals displaying both deviant behavior and the label of mental illness. Featured is the high potential for internalization of negative perceptions on the part of those with mental disorders-i.e., self-stigmatization. We next focus on several issues of conceptual and practical relevance: (a) stigma against less severe forms of mental disorder; (b) the role of perceptions of dangerousness related to mental illness; (c) reconciliation of behavioral research with investigations of explicit and implicit attitudes; (d) evolutionary models and their testability; (e) attributional accounts of the causes of mental illness, especially to personal control versus biogenetic factors; and (f) developmental trends regarding stigma processes. We conclude with a brief review of multilevel efforts to overcome mental illness stigma, spanning policy and legislation, alterations in media depictions, changed attitudes and practices among mental health professionals, contact and empathy enhancement, and family and individual treatment.
Systems Biology of Free Radicals and Antioxidants

Oxidative stress is a phenomenon associated with the pathology of several diseases including atherosclerosis, neurodegenerative diseases such as Alzheimer’s and Parkinson’s diseases, cancer, diabetes mellitus, inflammatory diseases, as well as psychiatric disorders or aging process. Oxidative stress is defined as an imbalance between the production of free radicals and reactive metabolites, so called oxidants, and their elimination by protective mechanisms named antioxidative systems. Free radicals and their metabolites prevail over antioxidants. This imbalance leads to damage of important biomolecules and organs with plausible impact on the whole organism. Oxidative and antioxidative processes are associated with electron transfer influencing the redox state of cells and organisms; therefore, oxidative stress is also known as redox stress. At present, the opinion that oxidative stress is not always harmful has been accepted. Depending on its intensity, it can play a role in regulation of other important processes through modulation of signal pathways, influencing synthesis of antioxidant enzymes, repair processes, inflammation, apoptosis and cell proliferation, and thus process of a malignity. Therefore, improper administration of antioxidants can potentially negatively impact biological systems.
A map of abstract relational knowledge in the human hippocampal–entorhinal cortex

The hippocampal-entorhinal system encodes a map of space that guides spatial navigation. Goal-directed behaviour outside of spatial navigation similarly requires a representation of abstract forms of relational knowledge. This information relies on the same neural system, but it is not known whether the organisational principles governing continuous maps may extend to the implicit encoding of discrete, non-spatial graphs. Here, we show that the human hippocampal-entorhinal system can represent relationships between objects using a metric that depends on associative strength. We reconstruct a map-like knowledge structure directly from a hippocampal-entorhinal functional magnetic resonance imaging adaptation signal in a situation where relationships are non-spatial rather than spatial, discrete rather than continuous, and unavailable to conscious awareness. Notably, the measure that best predicted a behavioural signature of implicit knowledge and blood oxygen level-dependent adaptation was a weighted sum of future states, akin to the successor representation that has been proposed to account for place and grid-cell firing patterns.
Real-Time Locating Systems Using Active RFID for Internet of Things

The proliferation of the Internet of Things (IoT) has fostered growing attention to real-time locating systems (RTLSs) using radio frequency identification (RFID) for asset management, which can automatically identify and track physical objects within indoor or confined environments. Various RFID indoor locating systems have been proposed. However, most of them are inappropriate for large-scale IoT applications owing to severe radio multipath, diffraction, and reflection. In this paper, we propose a newly fashioned RTLS using active RFID for the IoT, i.e., iLocate, which locates objects at high levels of accuracy up to 30 cm with ultralong distance transmission. To achieve fine-grained localization accuracy, iLocate presents the concept of virtual reference tags. To overcome signal multipath, iLocate employs a frequency-hopping technique to schedule RFID communication. To support large-scale RFID networks, iLocate leverages the ZigBee. We implement all hardware using 2.45-GHz RFID chips so that each active tag can communicate with readers that are around 1000 m away in a free space. Our empirical study and real project deployment show the superiority of the proposed system with respect to the localization accuracy and the data transmission rate for large-scale active RFID networks.
Graves' Disease Mechanisms: The Role of Stimulating, Blocking, and Cleavage Region TSH Receptor Antibodies.

The immunologic processes involved in Graves' disease (GD) have one unique characteristic--the autoantibodies to the TSH receptor (TSHR)--which have both linear and conformational epitopes. Three types of TSHR antibodies (stimulating, blocking, and cleavage) with different functional capabilities have been described in GD patients, which induce different signaling effects varying from thyroid cell proliferation to thyroid cell death. The establishment of animal models of GD by TSHR antibody transfer or by immunization with TSHR antigen has confirmed its pathogenic role and, therefore, GD is the result of a breakdown in TSHR tolerance. Here we review some of the characteristics of TSHR antibodies with a special emphasis on new developments in our understanding of what were previously called "neutral" antibodies and which we now characterize as autoantibodies to the "cleavage" region of the TSHR ectodomain.
A Cognitive Model for the Representation and Acquisition of Verb Selectional Preferences

We present a cognitive model of inducing verb selectional preferences from individual verb usages. The selectional preferences for each verb argument are represented as a probability distribution over the set of semantic properties that the argument can possess—asemantic profile . The semantic profiles yield verb-specific conceptualizations of the arguments associated with a syntactic position. The proposed model can learn appropriate verb profiles from a small set of noisy training data, and can use them in simulating human plausibility judgments and analyzing implicit object alternation.
Thehumanamygdala insocial judgment

giving a statistic image for each contrast. P values for activations in the amygdala were corrected for the volume of brain analysed (specified as a sphere with radius 8 mm) 29. Anatomical localization for the group mean-condition-specific activations are reported in standard space 28. In all cases, the localization of the group mean activations was confirmed by registration with the subject's own MRIs. In an initial conditioning phase immediately before scanning, subjects viewed a sequence of greyscale images of four faces taken from a standard set of pictures of facial affect 30. Images of a single face were presented on a computer monitor screen for 75 ms at intervals of 15–25 s (mean 20 s). Each of the four faces was shown six times in a pseudorandom order. Two of the faces had angry expressions (A1 and A2), the other two being neutral (N1 and N2). One of the angry faces (CS+) was always followed by a 1-s 100-dB burst of white noise. In half of the subjects A1 was the CS+ face; in the other half, A2 was used. None of the other faces was ever paired with the noise. Before each of the 12 scanning windows, which occurred at 8-min intervals, a shortened conditioning sequence was played consisting of three repetitions of the four faces. During the 90-s scanning window, which seamlessly followed the conditioning phase, 12 pairs of faces, consisting of a target and mask, were shown at 5-s intervals. The target face was presented for 30 ms and was immediately followed by the masking face for 45 ms . These stimulus parameters remained constant throughout all scans and effectively prevented any reportable awareness of the target face (which might be a neutral face or an angry face). There were four different conditions , masked conditioned, non-masked conditioned, masked unconditioned, and non-masked unconditioned. Throughout the experiment, subjects performed the same explicit task, which was to detect any occurrence, however fleeting, of the angry faces. Immediately before the first conditioning sequence, subjects were shown the two angry faces and were instructed, for each stimulus presentation, to press a response button with the index finger of the right hand if one the angry faces appeared, or another button with the middle finger of the right hand if they did not see either of the angry faces. Throughout the acquisition and extinction phases, subjects' SCRs were monitored to …
An Evaluation of the Use of Atmospheric and BRDF Correction to Standardize Landsat Data

Normalizing for atmospheric and land surface bidirectional reflectance distribution function (BRDF) effects is essential in satellite data processing. It is important both for a single scene when the combination of land covers, sun, and view angles create anisotropy and for multiple scenes in which the sun angle changes. As a consequence, it is important for inter-sensor calibration and comparison. Procedures based on physics-based models have been applied successfully with the Moderate Resolution Imaging Spectroradiometer (MODIS) data. For Landsat and other higher resolution data, similar options exist. However, the estimation of BRDF models using internal fitting is not available due to the smaller variation of view and solar angles and infrequent revisits. In this paper, we explore the potential for developing operational procedures to correct Landsat data using coupled physics-based atmospheric and BRDF models. The process was realized using BRDF shape functions derived from MODIS with the MODTRAN 4 radiative transfer model. The atmospheric and BRDF correction algorithm was tested for reflectance factor estimation using Landsat data for two sites with different land covers in Australia. The Landsat reflectance values had a good agreement with ground based spectroradiometer measurements. In addition, overlapping images from adjacent paths in Queensland, Australia, were also used to validate the BRDF correction. The results clearly show that the algorithm can remove most of the BRDF effect without empirical adjustment. The comparison between normalized Landsat and MODIS reflectance factor also shows a good relationship, indicating that cross calibration between the two sensors is achievable.
Learning a strategy for adapting a program analysis via bayesian optimisation

Building a cost-effective static analyser for real-world programs is still regarded an art. One key contributor to this grim reputation is the difficulty in balancing the cost and the precision of an analyser. An ideal analyser should be adaptive to a given analysis task, and avoid using techniques that unnecessarily improve precision and increase analysis cost. However, achieving this ideal is highly nontrivial, and it requires a large amount of engineering efforts. In this paper we present a new approach for building an adaptive static analyser. In our approach, the analyser includes a sophisticated parameterised strategy that decides, for each part of a given program, whether to apply a precision-improving technique to that part or not. We present a method for learning a good parameter for such a strategy from an existing codebase via Bayesian optimisation. The learnt strategy is then used for new, unseen programs. Using our approach, we developed partially flow- and context-sensitive variants of a realistic C static analyser. The experimental results demonstrate that using Bayesian optimisation is crucial for learning from an existing codebase. Also, they show that among all program queries that require flow- or context-sensitivity, our partially flow- and context-sensitive analysis answers the 75% of them, while increasing the analysis cost only by 3.3x of the baseline flow- and context-insensitive analysis, rather than 40x or more of the fully sensitive version.
Best practice guidelines on first-line laboratory testing for porphyria.

The porphyrias are disorders of haem biosynthesis which present with acute neurovisceral attacks or disorders of sun-exposed skin. Acute attacks occur mainly in adults and comprise severe abdominal pain, nausea, vomiting, autonomic disturbance, central nervous system involvement and peripheral motor neuropathy. Cutaneous porphyrias can be acute or chronic presenting at various ages. Timely diagnosis depends on clinical suspicion leading to referral of appropriate samples for screening by reliable biochemical methods. All samples should be protected from light. Investigation for an acute attack: • Porphobilinogen (PBG) quantitation in a random urine sample collected during symptoms. Urine concentration must be assessed by measuring creatinine, and a repeat requested if urine creatinine <2 mmol/L. • Urgent porphobilinogen testing should be available within 24 h of sample receipt at the local laboratory. Urine porphyrin excretion (TUP) should subsequently be measured on this urine. • Urine porphobilinogen should be measured using a validated quantitative ion-exchange resin-based method or LC-MS. • Increased urine porphobilinogen excretion requires confirmatory testing and clinical advice from the National Acute Porphyria Service. • Identification of individual acute porphyrias requires analysis of urine, plasma and faecal porphyrins. Investigation for cutaneous porphyria: • An EDTA blood sample for plasma porphyrin fluorescence emission spectroscopy and random urine sample for TUP. • Whole blood for porphyrin analysis is essential to identify protoporphyria. • Faeces need only be collected, if first-line tests are positive or if clinical symptoms persist. Investigation for latent porphyria or family history: • Contact a specialist porphyria laboratory for advice. Clinical, family details are usually required.
Hierarchical digital modulation classification using cumulants

A simple method, based on elementary fourth-order cumulants, is proposed for the classification of digital modulation schemes. These statistics are natural in this setting as they characterize the shape of the distribution of the noisy baseband I and Q samples. It is shown that cumulant-based classification is particularly effective when used in a hierarchical scheme, enabling separation into subclasses at low signal-to-noise ratio with small sample size. Thus, the method can be used as a preliminary classifier if desired. Computational complexity is order N , whereN is the number of complex baseband data samples. This method is robust in the presence of carrier phase and frequency offsets and can be implemented recursively. Theoretical arguments are verified via extensive simulations and comparisons with existing approaches.
Para 'Normal' Activity: On the Distribution of Average Ratings

In this paper we study the distribution of average user rating of entities in three different domains: restaurants, movies, and products. We find that the distribution is heavily skewed, closely resembling a log-normal in all the cases. In contrast, the distribution of average critic rating is much closer to a normal distribution. We propose user selection bias as the underlying behavioral phenomenon causing this disparity in the two distributions. We show that selection bias can indeed lead to a skew in the distribution of user ratings even when we assume the quality of entities are normally distributed. Finally, we apply these insights to the problem of predicting the overall rating of an entity given its few initial ratings, and obtain a simple method that outperforms strong baselines.
Mechanisms of Ammonia-Induced Astrocyte Swelling

Astrocyte swelling represents the major factor responsible for the brain edema associated with fulminant hepatic failure (FHF). The edema may be of such magnitude as to increase intracranial pressure leading to brain herniation and death. Of the various agents implicated in the generation of astrocyte swelling, ammonia has had the greatest amount of experimental support. This article reviews mechanisms of ammonia neurotoxicity that contribute to astrocyte swelling. These include oxidative stress and the mitochondrial permeability transition (MPT). The involvement of glutamine in the production of cell swelling will be highlighted. Evidence will be provided that glutamine induces oxidative stress as well as the MPT, and that these events are critical in the development of astrocyte swelling in hyperammonemia.