nils-herrmann/clean_scirepeval huggingface dataset:
Computational complexity: a conceptual perspective written by Oded Goldreich, and published by Cambridge University Press 2008, ISBN 978-0-521-88473-0, 606 pages

Chapters cover topics in areas such as P and NP, space complexity, randomness, computational problems that are (or appear) infeasible to solve, pseudo-random generators, and probabilistic proof systems. The introduction nicely summarizes the material covered in the rest of the book and includes a diagram of dependencies between chapter topics. Initial chapters cover preliminary topics as preparation for the rest of the book. These are more than topical or historical summaries but generally not sufficient to fully prepare the reader for later material. Readers should approach this text already competent at undergraduate-level algorithms in areas such as basic analysis, algorithm strategies, fundamental algorithm techniques, and the basics for determining computability. Elective work in P versus NP or advanced analysis would be valuable but that isn‟t really required.
An implementation of normal distribution based segmentation and entropy controlled features selection for skin lesion detection and classification

Melanoma is the deadliest type of skin cancer with highest mortality rate. However, the annihilation in its early stage implies a high survival rate therefore, it demands early diagnosis. The accustomed diagnosis methods are costly and cumbersome due to the involvement of experienced experts as well as the requirements for the highly equipped environment. The recent advancements in computerized solutions for this diagnosis are highly promising with improved accuracy and efficiency. In this article, a method for the identification and classification of the lesion based on probabilistic distribution and best features selection is proposed. The probabilistic distribution such as normal distribution and uniform distribution are implemented for segmentation of lesion in the dermoscopic images. Then multi-level features are extracted and parallel strategy is performed for fusion. A novel entropy-based method with the combination of Bhattacharyya distance and variance are calculated for the selection of best features. Only selected features are classified using multi-class support vector machine, which is selected as a base classifier. The proposed method is validated on three publicly available datasets such as PH2, ISIC (i.e. ISIC MSK-2 and ISIC UDA), and Combined (ISBI 2016 and ISBI 2017), including multi-resolution RGB images and achieved accuracy of 97.5%, 97.75%, and 93.2%, respectively. The base classifier performs significantly better on proposed features fusion and selection method as compared to other methods in terms of sensitivity, specificity, and accuracy. Furthermore, the presented method achieved satisfactory segmentation results on selected datasets.
Real time cooperative localization for autonomous vehicles

This paper describes a new strategy for real-time cooperative localization of autonomous vehicles. The strategy aims to improve the vehicles localization accuracy and reduce the impact of computing time of multi-sensor data fusion algorithms and vehicle-to-vehicle communication on parallel architectures. The method aims to solve localization issues in a cluster of autonomous vehicles, equipped with low-cost navigation systems in an unknown environment. It stands on multiple forms of the Kalman filter derivatives to estimate the vehicles' nonlinear model vector state, named local fusion node. The vehicles exchange their local state estimate and Covariance Intersection algorithm for merging the local vehicles' state estimate in the second node (named global data fusion node). This strategy simultaneously exploits the proprioceptive and sensors -a Global Positioning System, and a vehicle-to-vehicle transmitter and receiver- and an exteroceptive sensor, range finder, to sense their surroundings for more accurate and reliable collaborative localization.
Visualising software as a particle system

Current metrics-based approaches to visualise unfamiliar software systems face two key limitations: (1) They are limited in terms of the number of dimensions that can be projected, and (2) they use fixed layout algorithms where the resulting positions of entities can be vulnerable to mis-interpretation. In this paper we show how computer games technology can be used to address these problems. We present the PhysVis software exploration system, where software metrics can be variably mapped to parameters of a physical model and displayed via a particle system. Entities can be imbued with attributes such as mass, gravity, and (for relationships) strength or springiness, alongside traditional attributes such as position, colour and size. The resulting visualisation is a dynamic scene; the relative positions of entities are not determined by a fixed layout algorithm, but by intuitive physical notions such as gravity, mass, and drag. The implementation is openly available, and we evaluate it on a selection of visualisation tasks for two openly-available software systems.
Evaluation of a Rapid Molecular Drug-Susceptibility Test for Tuberculosis.

Fluoroquinolones and second-line injectable drugs are the backbone of treatment regimens for multidrug-resistant tuberculosis, and resistance to these drugs defines extensively drug-resistant tuberculosis. We assessed the accuracy of an automated, cartridge-based molecular assay for the detection, directly from sputum specimens, of Mycobacterium tuberculosis with resistance to fluoroquinolones, aminoglycosides, and isoniazid.



We conducted a prospective diagnostic accuracy study to compare the investigational assay against phenotypic drug-susceptibility testing and DNA sequencing among adults in China and South Korea who had symptoms of tuberculosis. The Xpert MTB/RIF assay and sputum culture were performed. M. tuberculosis isolates underwent phenotypic drug-susceptibility testing and DNA sequencing of the genes katG, gyrA, gyrB, and rrs and of the eis and inhA promoter regions.



Among the 308 participants who were culture-positive for M. tuberculosis, when phenotypic drug-susceptibility testing was used as the reference standard, the sensitivities of the investigational assay for detecting resistance were 83.3% for isoniazid (95% confidence interval [CI], 77.1 to 88.5), 88.4% for ofloxacin (95% CI, 80.2 to 94.1), 87.6% for moxifloxacin at a critical concentration of 0.5 μg per milliliter (95% CI, 79.0 to 93.7), 96.2% for moxifloxacin at a critical concentration of 2.0 μg per milliliter (95% CI, 87.0 to 99.5), 71.4% for kanamycin (95% CI, 56.7 to 83.4), and 70.7% for amikacin (95% CI, 54.5 to 83.9). The specificity of the assay for the detection of phenotypic resistance was 94.3% or greater for all drugs except moxifloxacin at a critical concentration of 2.0 μg per milliliter (specificity, 84.0% [95% CI, 78.9 to 88.3]). When DNA sequencing was used as the reference standard, the sensitivities of the investigational assay for detecting mutations associated with resistance were 98.1% for isoniazid (95% CI, 94.4 to 99.6), 95.8% for fluoroquinolones (95% CI, 89.6 to 98.8), 92.7% for kanamycin (95% CI, 80.1 to 98.5), and 96.8% for amikacin (95% CI, 83.3 to 99.9), and the specificity for all drugs was 99.6% (95% CI, 97.9 to 100) or greater.



This investigational assay accurately detected M. tuberculosis mutations associated with resistance to isoniazid, fluoroquinolones, and aminoglycosides and holds promise as a rapid point-of-care test to guide therapeutic decisions for patients with tuberculosis. (Funded by the National Institute of Allergy and Infectious Diseases, National Institutes of Health, and the Ministry of Science and Technology of China; ClinicalTrials.gov number, NCT02251327 .).
Social, proximal and conditioned threat

Responding to threats in the environment is crucial for survival. Certain types of threat produce defensive responses without necessitating previous experience and are considered innate, whereas other threats are learned by experiencing aversive consequences. Two important innate threats are whether an encountered stimulus is a member of the same species (social threat) and whether a stimulus suddenly appears proximal to the body (proximal threat). These threats are manifested early in human development and robustly elicit defensive responses. Learned threat, on the other hand, enables adaptation to threats in the environment throughout the life span. A well-studied form of learned threat is fear conditioning, during which a neutral stimulus acquires the ability to eliciting defensive responses through pairings with an aversive stimulus. If innate threats can facilitate fear conditioning, and whether different types of innate threats can enhance each other, is largely unknown. We developed an immersive virtual reality paradigm to test how innate social and proximal threats are related to each other and how they influence conditioned fear. Skin conductance responses were used to index the autonomic component of the defensive response. We found that social threat modulates proximal threat, but that neither proximal nor social threat modulates conditioned fear. Our results suggest that distinct processes regulate autonomic activity in response to proximal and social threat on the one hand, and conditioned fear on the other.
Multi-domain evaluation framework for named entity recognition tools

Extracting structured information from unstructured text is important for the qualitative data analysis. D31X X Leveraging NLP techniques for qualitative data analysis will effectively accelerate the annotation process, allow for large-scale analysis and provide more insights into the text to improve the performance. The first step for gaining insights from the text is Named Entity Recognition (NER). A significant challenge that directly impacts the performance of the NER process is the domain diversity in qualitative data. The represented text varies according to its domain in many aspects including taxonomies, length, formality and format. In this paper we discuss and analyse the performance of state-of-the-art tools across domains to elaborate their robustness and reliability. In order to do that, we developed a standard, expandable and flexible framework to analyse and test tools performance using corpora representing text across various domains. We performed extensive analysis and comparison of tools across various domains and from various perspectives. The resulting comparison and analysis are of significant importance for providing a holistic illustration of the state-of-the-art tools. 2016
Homogeneous Emission Line Broadening in the Organo Lead Halide Perovskite CH3NH3PbI3-xClx.

The organic-inorganic hybrid perovskites methylammonium lead iodide (CH3NH3PbI3) and the partially chlorine-substituted mixed halide CH3NH3PbI3-xClx emit strong and broad photoluminescence (PL) around their band gap energy of ∼1.6 eV. However, the nature of the radiative decay channels behind the observed emission and, in particular, the spectral broadening mechanisms are still unclear. Here we investigate these processes for high-quality vapor-deposited films of CH3NH3PbI3-xClx using time- and excitation-energy dependent photoluminescence spectroscopy. We show that the PL spectrum is homogenously broadened with a line width of 103 meV most likely as a consequence of phonon coupling effects. Further analysis reveals that defects or trap states play a minor role in radiative decay channels. In terms of possible lasing applications, the emission spectrum of the perovskite is sufficiently broad to have potential for amplification of light pulses below 100 fs pulse duration.
Aggregated QoS Mapping Framework for Relative Service Differentiation-Aware Video Streaming

This research investigates the Quality of Service (QoS) interaction at the edge of differentiated service (DiffServ) domain, denoted by video gateway (VG). VG is responsible for coordinating the QoS mapping between video applications and DiffServ enabled network. To accomplish the goal of achieving economical and high-quality end-to-end video streaming, which utilizes its awareness of relative service differentiation, the proposed QoS control framework includes the following three components: 1) the relative priority based indexing and categorization of streaming video content at sender, 2) the differentiated QoS levels with load variation in DiffServ networks, and 3) the feedforward and feedback mechanisms assisting QoS mapping of categorized index to DS level at the proposed VG. Especially, we focus on building a framework for dynamic QoS mapping, which intends to overcome both the QoS demand variations of CM applications (e.g., varying priorities from aggregated/categorized packets) and the QoS supply variations of DiffServ network (e.g., varying loss/delay due to fluctuating network loads). Thus, with the proposed QoS controls in both feedforward and feedback fashion, enhanced quality provisioning for CM applications (especially video streaming) is investigated under the given pricing model (e.g., DS level differentiated price/packet).
Boosting with structural sparsity

We derive generalizations of AdaBoost and related gradient-based coordinate descent methods that incorporate sparsity-promoting penalties for the norm of the predictor that is being learned. The end result is a family of coordinate descent algorithms that integrate forward feature induction and back-pruning through regularization and give an automatic stopping criterion for feature induction. We study penalties based on the l1, l2, and l∞ norms of the predictor and introduce mixed-norm penalties that build upon the initial penalties. The mixed-norm regularizers facilitate structural sparsity in parameter space, which is a useful property in multiclass prediction and other related tasks. We report empirical results that demonstrate the power of our approach in building accurate and structurally sparse models.
Use of Foley catheter to examine estrogenized hymens for evidence of sexual abuse.

An examination technique for the collection of evidence to document physical findings of sexual abuse of children uses a Foley catheter in older girls with estrogenized hymens. The inflated balloon in the distal vaginal vault puts pressure on the hymen, effectively stretching it out and allowing for a more accurate view of the hymen edges. This report demonstrates the results in 2 of 17 adolescent girls who underwent the Foley catheter stretch technique. Patient 1 was a 13-year-old girl who gave a statement of repeated sexual abuse, including penile penetration by an adult male. Patient 2 was a 12-year-old girl who disclosed a single episode of sexual assault 1 year previously. After careful examination, a Foley catheter (14 Fr) was inserted through the hymen orifice and inflated using 40 ml of air. Gentle pulling toward the orifice resulted in stretching of the hymenal tissues over the balloon surface of the catheter. After photodocumentation of the anatomy of the hymen edges, the balloon was deflated and removed.
Diversity of wild bees supports pollination services in an urbanized landscape

Plantings in residential neighborhoods can support wild pollinators. However, it is unknown how effectively wild pollinators maintain pollination services in small, urban gardens with diverse floral resources. We used a ‘mobile garden’ experimental design, whereby potted plants of cucumber, eggplant, and purple coneflower were brought to 30 residential yards in Chicago, IL, USA, to enable direct assessment of pollination services provided by wild pollinator communities. We measured fruit and seed set and investigated the effect of within-yard characteristics and adjacent floral resources on plant pollination. Increased pollinator visitation and taxonomic richness generally led to increases in fruit and seed set for all focal plants. Furthermore, fruit and seed set were correlated across the three species, suggesting that pollination services vary across the landscape in ways that are consistent among different plant species. Plant species varied in terms of which pollinator groups provided the most visits and benefit for pollination. Cucumber pollination was linked to visitation by small sweat bees (Lasioglossum spp.), whereas eggplant pollination was linked to visits by bumble bees. Purple coneflower was visited by the most diverse group of pollinators and, perhaps due to this phenomenon, was more effectively pollinated in florally-rich gardens. Our results demonstrate how a diversity of wild bees supports pollination of multiple plant species, highlighting the importance of pollinator conservation within cities. Non-crop resources should continue to be planted in urban gardens, as these resources have a neutral and potentially positive effect on crop pollination.
Enhanced vector field visualization via Lagrangian accumulation

In this paper, we revisit the Lagrangian accumulation process that aggregates the local attribute information along integral curves for vector field visualization. Similar to the previous work, we adopt the notation of the Lagrangian accumulation field or A field for the representation of the accumulation results. In contrast to the previous work, we provide a more in-depth discussion on the properties of A fields and the meaning of the patterns exhibiting in A fields. In particular, we revisit the discontinuity in the A fields and provide a thorough explanation of its relation to the flow structure and the additional information of the flow that it may reveal. In addition, other remaining questions about the A field, such as its sensitivity to the selection of integration time, are also addressed. Based on these new insights, we demonstrate a number of enhanced flow visualizations aided by the accumulation framework and the A fields, including a new A field guided ribbon placement, a A field guided stream surface seeding and the visualization of particle-based flow data. To further demonstrate the generality of the accumulation framework, we extend it to the non-integral geometric curves (i.e. streak lines), which enables us to reveal information of the flow behavior other than those revealed by the integral curves. Finally, we introduce the Eulerian accumulation, which can reveal different flow behavior information from those revealed by the Lagrangian accumulation. In summary, we believe the Lagrangian accumulation and the resulting A fields offer a valuable way for the exploration of flow behaviors in addition to the current state-of-the-art techniques.
Superior Mesenteric Artery Syndrome Associated with Rapid Weight Loss Attributed to Amphetamine Abuse

Superior mesenteric artery (SMA) syndrome arises from a reduction in the angle formed between the SMA and the aorta, thereby compressing the third portion of the duodenum. This phenomenon may be caused by a number of factors, one of which being acute weight loss. We report a case of a female patient presenting with abdominal pain and vomiting who developed superior mesenteric artery (SMA) syndrome as a result of rapid weight loss, thought to be secondary to amphetamine abuse. This association can often be overlooked and, to our knowledge, has not been previously reported.
A Hand Gesture Recognition Framework and Wearable Gesture-Based Interaction Prototype for Mobile Devices

An algorithmic framework is proposed to process acceleration and surface electromyographic (SEMG) signals for gesture recognition. It includes a novel segmentation scheme, a score-based sensor fusion scheme, and two new features. A Bayes linear classifier and an improved dynamic time-warping algorithm are utilized in the framework. In addition, a prototype system, including a wearable gesture sensing device (embedded with a three-axis accelerometer and four SEMG sensors) and an application program with the proposed algorithmic framework for a mobile phone, is developed to realize gesture-based real-time interaction. With the device worn on the forearm, the user is able to manipulate a mobile phone using 19 predefined gestures or even personalized ones. Results suggest that the developed prototype responded to each gesture instruction within 300 ms on the mobile phone, with the average accuracy of 95.0% in user-dependent testing and 89.6% in user-independent testing. Such performance during the interaction testing, along with positive user experience questionnaire feedback, demonstrates the utility of the framework.
Study of Mobile Payments System

Mobile payment is the killer application in mobile commerce. We classify the payment methods according to several standards, analyze and point out the merits and drawbacks of each method. To enable future applications and technologies handle mobile payment, we provide a general layered framework and a new process for mobile payment. The framework is composed of load-bearing layer, network interface and core application platform layer, business layer, and decision-making layer. And it can be extended and improved by the developers. Then a pre-pay and account-based payment process is described. Our method has the advantages of low cost and technical requirement, high scalability and security.
Robot-Audition-based Human-Machine Interface for a Car

This paper describes a Robot-Audition based Car Human Machine Interface (RA-CHMI). A RA-CHMI, like a car navigation system, has difficulty dealing with voice commands, since there are many noise sources in a car, including road noise, air-conditioner, music, and passengers. Microphone array processing developed in robot audition, may overcome this problem. Robot audition techniques, including sound source localization, Voice Activity Detection (VAD), sound source separation, and barge-in-able processing, were introduced by considering the characteristics of RA-CHMI. Automatic Speech Recognition (ASR), based on a Deep Neural Network (DNN), improved recognition performance and robustness in a noisy environment. In addition, as an integrated framework, HARK-Dialog was developed to build a multi-party and multi-modal dialog system, enabling the seamless use of cloud and local services with pluggable modular architecture. The constructed multi-party and multimodal RA-CHMI system did not require a push-to-talk button, nor did it require reducing the audio volume or air-conditioner when issuing speech commands. It could also control a four-DOF robot agent to make the system's responses more understandable. The proposed RA-CHMI was validated by evaluating essential techniques in the system, such as VAD and DNN-ASR, using real speech data recorded during driving. The entire design of the RA-CHMI system, including the system response time and the proper use of cloud/local services, are also discussed.
Polymer Composite and Nanocomposite Dielectric Materials for Pulse Power Energy Storage †

This review summarizes the current state of polymer composites used as dielectric materials for energy storage. The particular focus is on materials: polymers serving as the matrix, inorganic fillers used to increase the effective dielectric constant, and various recent investigations of functionalization of metal oxide fillers to improve compatibility with polymers. We review the recent literature focused on the dielectric characterization of composites, specifically the measurement of dielectric permittivity and breakdown field strength. Special attention is given to the analysis of the energy density of polymer composite materials and how the functionalization of the inorganic filler affects the energy density of polymer composite dielectric materials.