nils-herrmann/clean_scirepeval huggingface dataset:
Tubular modular permanent-magnet machines equipped with quasi-Halbach magnetized magnets-part I: magnetic field distribution, EMF, and thrust force

This paper describes the analysis, design, and experimental characterization of three-phase tubular modular permanent-magnet machines equipped with quasi-Halbach magnetized magnets. It identifies feasible slot/pole number combinations and discusses their relative merits. It establishes an analytical expression for the open-circuit magnetic field distribution, formulated in the cylindrical coordinate system. The expression has been verified by finite-element analysis. The analytical solution allows the prediction of the thrust force and electromotive force in closed forms, and provides an effective tool for design optimization, as will be described in Part II of the paper.
DIAGNOSING AUTISM: COMPARISON OF THE CHILDHOOD AUTISM RATING SCALE (CARS) AND THE AUTISM DIAGNOSTIC OBSERVATION SCHEDULE (ADOS)

This project sought to determine the utility in using either, or both, of two instruments to diagnose autism, the CARS (Childhood Autism Rating Scale) and the ADOS (Autism Diagnostic Observation Schedule), Modules 1 or 2. Children (n=320) who were seen in the autism diagnostic clinics at the Developmental Disabilities Center of the Kansas University Medical Center, who were under the age of 72 months (6 years), and who had been evaluated with both instruments were chosen as participants in this study. Those children who received the diagnosis of autism after being evaluated numbered 220; 100 received another or no diagnosis. Three levels of data analysis were conducted in this study. The first level included developing itemitem correlation matrices for each instrument that was then compared to those in the original, normed study for internal consistency. Results indicated good internal consistency. At the second level, a factor analysis was conducted on each instrument that resulted in weighted factor scores and a correlation matrix of factors for each instrument. Factor analyses resulted in three factors identified for the CARS, two factors for ADOS, Module 1, and three factors for ADOS, Module 2. These factors are consistent with the criteria currently used for the diagnosis of autism. The third level of analysis utilized chi square and stepwise discriminant analysis to predict group membership (autism or no autism) with each instrument. From these results, it was concluded that both instruments are similar in their ability to diagnose autism, although they may be measuring somewhat different factors. Closer examination revealed that communication difficulty is the factor that most closely distinguished autism for this group of children.
Shared Decision Making for Psychiatric Rehabilitation Services Before Discharge from Psychiatric Hospitals.

Shared decision making (SDM) is an effective health communication model designed to facilitate patient engagement in treatment decision making. In mental health, SDM has been applied and evaluated for medications decision making but less for its contribution to personal recovery and rehabilitation in psychiatric settings. The purpose of this pilot study was to assess the effect of SDM in choosing community psychiatric rehabilitation services before discharge from psychiatric hospitalization. A pre-post non-randomized design with two consecutive inpatient cohorts, SDM intervention (N = 51) and standard care (N = 50), was applied in two psychiatric hospitals in Israel. Participants in the intervention cohort reported greater engagement and knowledge after choosing rehabilitation services and greater services use at 6-to-12-month follow-up than those receiving standard care. No difference was found for rehospitalization rate. Two significant interaction effects indicated greater improvement in personal recovery over time for the SDM cohort. SDM can be applied to psychiatric rehabilitation decision making and can help promote personal recovery as part of the discharge process.
Analysis of a privacy-preserving PCA algorithm using random matrix theory

To generate useful summarization of data while maintaining privacy of sensitive information is a challenging task, especially in the big data era. The privacy-preserving principal component algorithm proposed in  is a promising approach when a low rank data summarization is desired. However, the analysis in  is limited to the case of a single principal component, which makes use of bounds on the vector-valued Bingham distribution in the unit sphere. By exploring the non-commutative structure of data matrices in the full Stiefel manifold, we extend the analysis to an arbitrary number of principal components. Our results are obtained by analyzing the asymptotic behavior of the matrix-variate Bingham distribution using tools from random matrix theory.
Fuzzy Topological Spaces and Fuzzy Compactness

It is the purpose of this paper to go somewhat deeper into the structure of fuzzy topological spaces. In doing so we found we had to alter the definition of a fuzzy topology used up to now. We shall also introduce two functors 3 and i which will allow us to see more clearly the connection between fuzzy topological spaces and topological spaces. Finally we shall introduce the concept of fuzzy compactness as the generalization of compactness in topology. It will be shown in a following publication that contrary to the results obtained up to now, the Tychonoff-product theorem is safeguarded with fuzzy compactness.
Unanswered questions in headache: so what is photophobia, anyway?

We depend on exposure to light to guide us, inform us about the outside world, and regulate the biological rhythms in our bodies. We think about turning lights on to improve our lives; however, for some people, exposure to light creates pain and distress that can overwhelm their desire to see. Photophobia is ocular or headache pain caused by normal or dim light. People are symptomatic when irradiance levels inducing pain fall into a range needed for functionality and productivity, making photoallodynia a more accurate term. “Dazzle” is a momentary and normal aversion response to bright lights that subsides within seconds, but photoallodynia only subsides when light exposure is reduced. Milder degrees of sensitivity may manifest as greater perceived comfort in dim illumination. In severe cases, the pain is so debilitating that people are physically and socially isolated into darkness. The suffering and loss of function associated with photoallodynia can be devastating, but it is underappreciated in clinical assessment, treatment, and basic and clinical research. Transient photoallodynia generally improves when the underlying condition resolves, as in association with ocular inflammation, dry eye syndrome and laser-assisted in situ keratomileusis surgery. Migraine-associated light sensitivity can be severe during migraine or mild (and non-clinical) during the interictal period. With so many causes of photoallodynia, a singular underlying mechanism is unlikely, although different etiologies likely have shared and unique components and pathways. Photoallodynia may originate by alteration of a trigeminal nociceptive pathway or possibly through direct retinal projections to higher brain regions involved in pain perception, including but not limited to the periaqueductal gray, the anterior cingulate and somatorsensory cortices, which are collectively termed the “pain matrix.” However, persistent photoallodynia, occurring in a number of ocular and central brain causes, can be remarkably resistant to therapy. The initial light detection that triggers a pain response likely arises through interaction of cone photoreceptors (color and acuity), rod photoreceptors (low light vision), and intrinsically photosensitive retinal ganglion cells (ipRGCs, pupil light reflex and circadian photoentrainment). We can gain clues as to these interactions by examining retinal diseases that cause – or do not cause – photoallodynia.
Energy-Saving Smart Home Based on ZigBee and Fuzzy Neural Network

In this paper, we present a novel smart home system integrating energy efficiency features. The paper firstly introduces the attempt tried by the power system and researchers for home energy-saving. Secondly the paper compares the performance of three kinds of network, and raised timing sleep, routing node rotation mechanism and data compression for ZigBee to conserve energy. Thirdly introduces three main sensors monitored to conserve energy and presents an experiment to find the optimal light intensity for healthy and sustainable lifestyle. Fourthly combines fuzzy neural network for energy-saving and puts forward the design and learning procedure for home controlling. At last it prospects the future research work about smart home visualized by mixed reality to achieve more ideal control.
Evaluation of Cellular Proliferative Activity in Patients with Actinic Cheilitis through Silver-stained Nucleolar Organizer Region Method.

Actinic cheilitis (AC) is a lesion potentially malignant that affects the lips after prolonged exposure to solar ultraviolet (UV) radiation. The present study aimed to assess and describe the proliferative cell activity, using silver-stained nucleolar organizer region (AgNOR) quantification proteins, and to investigate the potential associations between AgNORs and the clinical aspects of AC lesions.  Cases diagnosed with AC were selected and reviewed from Center of Histopathological Diagnosis of the Institute of Biological Sciences, Passo Fundo University, Brazil. Clinical data including clinical presentation of the patients affected with AC were collected. The AgNOR techniques were performed in all recovered cases. The different microscopic areas of interest were printed with magnification of *1000, and in each case, 200 epithelial cell nuclei were randomly selected. The mean quantity in each nucleus for NORs was recorded. One-way analysis of variance was used for statistical analysis.  A total of 22 cases of AC were diagnosed. The patients were aged between 46 and 75 years (mean age: 55 years). Most of the patients affected were males presenting asymptomatic white plaque lesions in the lower lip. The mean value quantified for AgNORs was 2.4 ± 0.63, ranging between 1.49 and 3.82. No statistically significant difference was observed associating the quantity of AgNORs with the clinical aspects collected from the patients (p > 0.05).  The present study reports the lack of association between the proliferative cell activity and the clinical aspects observed in patients affected by AC through the quantification of AgNORs.  Knowing the potential relation between the clinical aspects of AC and the proliferative cell activity quantified by AgNORs could play a significant role toward the early diagnosis of malignant lesions in the clinical practice.  Actinic cheilitis, Proliferative cell activity, Silver-stained nucleolar organizer regions.
Floral morphology as the main driver of flower-feeding insect occurrences in the Paris region

Through the rapid expansion worldwide of impervious areas and habitat fragmentation, urbanization has strong consequences that must be understood to efficiently manage biodiversity. We studied the effects of urbanization on flower-feeding insects by using data from a citizen science program in the Parisian region. We analysed the occurrence of insects from 46 different families on flowers of different morphologies, using landscape indices in buffer areas from a 100-m to a 4000-m radius around 1194 sampled sites. Our aims were to determine (i) how the proportion of impervious area around sampled sites affected the occurrence of flower-feeding insect families and at which landscape scales impervious area calculations best predicted these occurrences; (ii) the effect of corolla shape variables on insect family occurrences. Twenty-one families were negatively impacted by increasing proportion of impervious areas (urbanophobic) and 3 were positively impacted (urbanophilic). Urbanophobic families were most affected by the proportion of impervious areas when it was estimated within buffers of 200-m to 1400-m radii, depending on the family. Notable losses of urbanophobic families were detected at less than 50% of impervious areas, which highlights the threat to the diversity of flower-feeding insects posed by urban sprawl. Corolla shape variables were the variables most often significantly implicated in the occurrence of insect families. Urbanophobic families were negatively affected by the tubular shape of flowers, and tubular corollas were found more often in urbanized areas. These results suggest that flora management might be a key component for the conservation of insect diversity in cities.
Burst photography for high dynamic range and low-light imaging on mobile cameras

Cell phone cameras have small apertures, which limits the number of photons they can gather, leading to noisy images in low light. They also have small sensor pixels, which limits the number of electrons each pixel can store, leading to limited dynamic range. We describe a computational photography pipeline that captures, aligns, and merges a burst of frames to reduce noise and increase dynamic range. Our system has several key features that help make it robust and efficient. First, we do not use bracketed exposures. Instead, we capture frames of constant exposure, which makes alignment more robust, and we set this exposure low enough to avoid blowing out highlights. The resulting merged image has clean shadows and high bit depth, allowing us to apply standard HDR tone mapping methods. Second, we begin from Bayer raw frames rather than the demosaicked RGB (or YUV) frames produced by hardware Image Signal Processors (ISPs) common on mobile platforms. This gives us more bits per pixel and allows us to circumvent the ISP's unwanted tone mapping and spatial denoising. Third, we use a novel FFT-based alignment algorithm and a hybrid 2D/3D Wiener filter to denoise and merge the frames in a burst. Our implementation is built atop Android's Camera2 API, which provides per-frame camera control and access to raw imagery, and is written in the Halide domain-specific language (DSL). It runs in 4 seconds on device (for a 12 Mpix image), requires no user intervention, and ships on several mass-produced cell phones.
Simulation and Analysis of Random Decision Errors in Clocked Comparators

Clocked comparators have found widespread use in noise sensitive applications including analog-to-digital converters, wireline receivers, and memory bit-line detectors. However, their nonlinear, time-varying dynamics resulting in discrete output levels have discouraged the use of traditional linear time-invariant (LTI) small-signal analysis and noise simulation techniques. This paper describes a linear, time-varying (LTV) model of clock comparators that can accurately predict the decision error probability without resorting to more general stochastic system models. The LTV analysis framework in conjunction with the linear, periodically time-varying (LPTV) simulation algorithms available from RF circuit simulators can provide insights into the intrinsic sampling and decision operations of clock comparators and the major contribution sources to random decision errors. Two comparators are simulated and compared with laboratory measurements. A 90-nm CMOS comparator is measured to have an equivalent input-referred random noise of 0.73 mVrms for dc inputs, matching simulation results with a short channel excess noise factor ¿ = 2.
Color-SURF: A surf descriptor with local kernel color histograms

SIFT (Scale Invariant Feature Transform) is an important local invariant feature descriptor. Since its expensive computation, SURF (Speeded-Up Robust Features) is proposed. Both of them are designed mainly for gray images. However, color provides valuable information in object description and matching tasks. To overcome the drawback and to increase the descriptor's distinctiveness, this paper presents a novel feature descriptor which combines local kernel color histograms and Haar wavelet responses to construct the feature vector. So the descriptor is a two elements vector. In image matching process, SURF descriptor is first compared, then the unmatched points are computed by Bhattacharyya distance between their local kernel color histograms. Extensive experimental evaluations show that the method has better robustness than the original SURF. The ratio of correct matches is increased by about 8.9% in the given dataset.
Foggy: A Framework for Continuous Automated IoT Application Deployment in Fog Computing

Traditional Cloud model is not designed to handle latency-sensitive Internet of Things applications. The new trend consists on moving data to be processed close to where it was generated. To this end, Fog Computing paradigm suggests using the compute and storage power of network elements. In such environments, intelligent and scalable orchestration of thousands of heterogeneous devices in complex environments is critical for IoT Service providers. In this vision paper, we present a framework, called Foggy, that facilitates dynamic resource provisioning and automated application deployment in Fog Computing architectures. We analyze several applications and identify their requirements that need to be taken intoconsideration in our design of the Foggy framework. We implemented a proof of concept of a simple IoT application continuous deployment using Raspberry Pi boards.
Silk Server - Adding missing Links while consuming Linked Data

The Web of Linked Data is built upon the idea that data items on the Web are connected by RDF links. Sadly, the reality on the Web shows that Linked Data sources set some RDF links pointing at data items in related data sources, but they clearly do not set RDF links to all data sources that provide related data. In this paper, we present Silk Server, an identity resolution component, which can be used within Linked Data application architectures to augment Web data with additional RDF links. Silk Server is designed to be used with an incoming stream of RDF instances, produced for example by a Linked Data crawler. Silk Server matches the RDF descriptions of incoming instances against a local set of known instances and discovers missing links between them. Based on this assessment, an application can store data about newly discovered instances in its repository or fuse data that is already known about an entity with additional data about the entity from the Web. Afterwards, we report on the results of an experiment in which Silk Server was used to generate RDF links between authors and publications from the Semantic Web Dog Food Corpus and a stream of FOAF profiles that were crawled from the Web.
A 55dB SNR with 240Hz frame scan rate mutual capacitor 30×24 touch-screen panel read-out IC using code-division multiple sensing technique

Capacitive touch-screen technology introduces new concepts to user interfaces, such as multi-touch, pinch zoom-in/out gestures, thus expanding the smartphone market. However, capacitive touch-screen technology still suffers from performance degradation like a low frame scan rate and poor accuracy, etc. One of the key performance factors is the immunity to external noise, which intrudes randomly into the touch-screen system. HUM, display noise, and SMPS are such noise sources. The main electrical power source produces HUM, one of the most important sources of noise, which has a 50 or 60Hz component. Display noise is emitted when an LCD or OLED is driven by the internal timing controller, which generates the driving signal in the tens of kHz range. The touch performance of On-Cell or In-Cell touch displays is seriously affected by this kind of noise, because the distance between the display pixel layer and the capacitive touchscreen panel is getting smaller. SMPS is another noise source that ranges up to 300kHz. The charger for a smart-phone, the USB port in a computer, a tri-phosphor fluorescent light bulb are all examples of sources of SMPS. There have been many attempts to remove such noise. Amplitude modulation with frequency hopping is proposed in . However, when the noise environment changes, this method needs recalibration, resulting in non-constant touch response time. Another method tries to filter the noise from the display , but it does not remove other noise sources like HUM or SMPS.
Pathways of clathrin-independent endocytosis

There are numerous ways that endocytic cargo molecules may be internalized from the surface of eukaryotic cells. In addition to the classical clathrin-dependent mechanism of endocytosis, several pathways that do not use a clathrin coat are emerging. These pathways transport a diverse array of cargoes and are sometimes hijacked by bacteria and viruses to gain access to the host cell. Here, we review our current understanding of various clathrin-independent mechanisms of endocytosis and propose a classification scheme to help organize the data in this complex and evolving field.
Perfusion CT in acute stroke: a comprehensive analysis of infarct and penumbra.

To perform a large-scale systematic comparison of the accuracy of all commonly used perfusion computed tomography (CT) data postprocessing methods in the definition of infarct core and penumbra in acute stroke.



The collection of data for this study was approved by the institutional ethics committee, and all patients gave informed consent. Three hundred fourteen patients with hemispheric ischemia underwent perfusion CT within 6 hours of stroke symptom onset and magnetic resonance (MR) imaging at 24 hours. CT perfusion maps were generated by using six different postprocessing methods. Pixel-based analysis was used to calculate sensitivity and specificity of different perfusion CT thresholds for the penumbra and infarct core with each postprocessing method, and receiver operator characteristic (ROC) curves were plotted. Area under the ROC curve (AUC) analysis was used to define the optimum threshold.



Delay-corrected singular value deconvolution (SVD) with a delay time of more than 2 seconds most accurately defined the penumbra (AUC = 0.86, P = .046, mean volume difference between acute perfusion CT and 24-hour diffusion-weighted MR imaging = 1.7 mL). A double core threshold with a delay time of more than 2 seconds and cerebral blood flow less than 40% provided the most accurate definition of the infarct core (AUC = 0.86, P = .038). The other SVD measures (block circulant, nondelay corrected) were more accurate than non-SVD methods.



This study has shown that there is marked variability in penumbra and infarct prediction among various deconvolution techniques and highlights the need for standardization of perfusion CT in stroke.



http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12120971/-/DC1.
Forest fire monitoring, detection and decision making systems by wireless sensor network

Wireless Sensor Networks (WSNs) can be used for many applications, such as industrial automatic control, remote environmental monitoring and target tracking. The similar system is promising applications in forest fires can make a real-time monitoring and detection. Wireless sensor network consists of numerous small nodes in most situations, which small nodes are deployed in remote and inaccessible hostile environments or over large geographical areas. The large number of small nodes sense environmental changes and report them to cluster head node over network architect, which the deployment and maintenance should be easy and scalable. A new approach for forest fire monitoring and detection was present in this paper, which it is by using data aggregation in wireless sensor network. The proposed approach can provide faster and efficiently reaction to forest fires while consuming economically WSN's energy, which has been validated and evaluated in extensive simulation experiments.