nils-herrmann/clean_scirepeval huggingface dataset:
Can perceived risks affect the relationship of switching costs and customer loyalty in e-commerce?

The purpose of this paper is to verify the relationship between switching costs and customer loyalty in e-commerce.  The study conducted an empirical research. A total of 425 online shopping customers were invited from northeastern USA as samples.  The findings show that switching costs positively influence customer loyalty. In addition, perceived risks will affect the relationship of switching costs and customer loyalty. For customers with low perceived risks, switching costs are also positively associated with customer loyalty. However, for customers with high perceived risks, the relationship of switching costs and customer loyalty is weak or negative.  One limitation is that mostly students were selected in the sample. The insights of this study can further validate the previous studies about the relationship of switching costs and customer loyalty, and suggest that perceived risks can be a moderating factor affecting this relationship.  The study suggests that the practitioners should further understand the relationship among switching costs, perceived risks and customer loyalty for their customers.  The paper contributes to the knowledge of perceived risks and how switching costs affect customer loyalty, particularly in e-commerce.
Prevalence of rheumatic heart disease in children and young adults in Nicaragua.

Rheumatic heart disease (RHD) results in morbidity and mortality that is disproportionate among individuals in developing countries compared to those living in economically developed countries. The global burden of disease is uncertain because most previous studies to determine the prevalence of RHD in children relied on clinical screening criteria that lacked the sensitivity to detect most cases. The present study was performed to determine the prevalence of RHD in children and young adults in León, Nicaragua, an area previously thought to have a high prevalence of RHD. This was an observational study of 3,150 children aged 5 to 15 years and 489 adults aged 20 to 35 years randomly selected from urban and rural areas of León. Cardiopulmonary examinations and Doppler echocardiographic studies were performed on all subjects. Doppler echocardiographic diagnosis of RHD was based on predefined consensus criteria that were developed by a working group of the World Health Organization and the National Institutes of Health. The overall prevalence of RHD in children was 48 in 1,000 (95% confidence interval 35 in 1,000 to 60 in 1,000). The prevalence in urban children was 34 in 1,000, and in rural children it was 80 in 1,000. Using more stringent Doppler echocardiographic criteria designed to diagnose definite RHD in adults, the prevalence was 22 in 1,000 (95% confidence interval 8 in 1,000 to 37 in 1,000). In conclusion, the prevalence of RHD among children and adults in this economically disadvantaged population far exceeds previously predicted rates. The findings underscore the potential health and economic burden of acute rheumatic fever and RHD and support the need for more effective measures of prevention, which may include safe, effective, and affordable vaccines to prevent the streptococcal infections that trigger the disease.
Chemical Boltzmann Machines

How smart can a micron-sized bag of chemicals be? How can an artificial or real cell make inferences about its environment? From which kinds of probability distributions can chemical reaction networks sample? We begin tackling these questions by showing four ways in which a stochastic chemical reaction network can implement a Boltzmann machine, a stochastic neural network model that can generate a wide range of probability distributions and compute conditional probabilities. The resulting models, and the associated theorems, provide a road map for constructing chemical reaction networks that exploit their native stochasticity as a computational resource. Finally, to show the potential of our models, we simulate a chemical Boltzmann machine to classify and generate MNIST digits in-silico.
Anatomy and clinical significance of the maxillary nerve: a literature review.

The aim of this paper was to summarise the anatomical knowledge on the subject of the maxillary nerve and its branches, and to show the clinical usefulness of such information in producing anaesthesia in the region of the maxilla.



A literature search was performed in Pubmed, Scopus, Web of Science and Google Scholar databases, including studies published up to June 2014, with no lower data limit.



The maxillary nerve (V2) is the middle sized branch of the trigeminal nerve - the largest of the cranial nerves. The V2 is a purely sensory nerve supplying the maxillary teeth and gingiva, the adjoining part of the cheek, hard and soft palate mucosa, pharynx, nose, dura mater, skin of temple, face, lower eyelid and conjunctiva, upper lip, labial glands, oral mucosa, mucosa of the maxillary sinus, as well as the mobile part of the nasal septum. The branches of the maxillary nerve can be divided into four groups depending on the place of origin i.e. in the cranium, in the sphenopalatine fossa, in the infraorbital canal, and on the face.



This review summarises the data on the anatomy and variations of the maxillary nerve and its branches. A thorough understanding of the anatomy will allow for careful planning and execution of anaesthesiological and surgical procedures involving the maxillary nerve and its branches.
Cancer Statistics, 2017.

Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States in the current year and compiles the most recent data on cancer incidence, mortality, and survival. Incidence data were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data were collected by the National Center for Health Statistics. In 2017, 1,688,780 new cancer cases and 600,920 cancer deaths are projected to occur in the United States. For all sites combined, the cancer incidence rate is 20% higher in men than in women, while the cancer death rate is 40% higher. However, sex disparities vary by cancer type. For example, thyroid cancer incidence rates are 3-fold higher in women than in men (21 vs 7 per 100,000 population), despite equivalent death rates (0.5 per 100,000 population), largely reflecting sex differences in the "epidemic of diagnosis." Over the past decade of available data, the overall cancer incidence rate (2004-2013) was stable in women and declined by approximately 2% annually in men, while the cancer death rate (2005-2014) declined by about 1.5% annually in both men and women. From 1991 to 2014, the overall cancer death rate dropped 25%, translating to approximately 2,143,200 fewer cancer deaths than would have been expected if death rates had remained at their peak. Although the cancer death rate was 15% higher in blacks than in whites in 2014, increasing access to care as a result of the Patient Protection and Affordable Care Act may expedite the narrowing racial gap; from 2010 to 2015, the proportion of blacks who were uninsured halved, from 21% to 11%, as it did for Hispanics (31% to 16%). Gains in coverage for traditionally underserved Americans will facilitate the broader application of existing cancer control knowledge across every segment of the population.
Distributed Training Strategies for the Structured Perceptron

Perceptron training is widely applied in the natural language processing community for learning complex structured models. Like all structured prediction learning frameworks, the structured perceptron can be costly to train as training complexity is proportional to inference, which is frequently non-linear in example sequence length. In this paper we investigate distributed training strategies for the structured perceptron as a means to reduce training times when computing clusters are available. We look at two strategies and provide convergence bounds for a particular mode of distributed structured perceptron training based on iterative parameter mixing (or averaging). We present experiments on two structured prediction problems – namedentity recognition and dependency parsing – to highlight the efficiency of this method.
Towards Scalable Multiprocessor Virtual Machines

A multiprocessor virtual machine benefits its guest operating system in supporting scalable job throughput and request latency—useful properties in server consolidation where servers require several of the system processors for steady state or to handle load bursts. Typical operating systems, optimized for multiprocessor systems in their use of spin-locks for critical sections, can defeat flexible virtual machine scheduling due to lock-holder preemption and misbalanced load. The virtual machine must assist the guest operating system to avoid lock-holder preemption and to schedule jobs with knowledge of asymmetric processor allocation. We want to support a virtual machine environment with flexible scheduling policies, while maximizing guest performance. This paper presents solutions to avoid lock-holder preemption for both fully virtualized and paravirtualized environments. Experiments show that we can nearly eliminate the effects of lock-holder preemption. Furthermore, the paper presents a scheduler feedback mechanism that despite the presence of asymmetric processor allocation achieves optimal and fair load balancing in the guest operating system.
Fever of unknown origin: prospective comparison of [18F]FDG imaging with a double-head coincidence camera and gallium-67 citrate SPET

Gallium-67 citrate is currently considered as the tracer of first choice in the diagnostic workup of fever of unknown origin (FUO). Fluorine-18 2'-deoxy-2-fluoro-D-glucose (FDG) has been shown to accumulate in malignant tumours but also in inflammatory processes. The aim of this study was to prospectively evaluate FDG imaging with a double-head coincidence camera (DHCC) in patients with FUO in comparison with planar and single-photon emission tomography (SPET) 67Ga citrate scanning. Twenty FUO patients underwent FDG imaging with a DHCC which included transaxial and longitudinal whole-body tomography. In 18 of these subjects, 67Ga citrate whole-body and SPET imaging was performed. The 67Ga citrate and FDG images were interpreted by two investigators, both blinded to the results of other diagnostic modalities. Forty percent (8/20) of the patients had infection, 25% (5/20) had auto-immune diseases, 10% (2/20) had neoplasms and 15% (3/20) had other diseases. Fever remained unexplained in 10% (2/20) of the patients. Of the 20 patients studied, FDG imaging was positive and essentially contributed to the final diagnosis in 11 (55%). The sensitivity of transaxial FDG tomography in detecting the focus of fever was 84% and the specificity, 86%. Positive and negative predictive values were 92% and 75%, respectively. If the analysis was restricted to the 18 patients who were investigated both with 67Ga citrate and FDG, sensitivity was 81% and specificity, 86%. Positive and negative predictive values were 90% and 75%, respectively. The diagnostic accuracy of whole-body FDG tomography (again restricted to the aforementioned 18 patients) was lower (sensitivity, 36%; specificity, 86%; positive and negative predictive values, 80% and 46%, respectively). 67Ga citrate SPET yielded a sensitivity of 67% in detecting the focus of fever and a specificity of 78%. Positive and negative predictive values were 75% and 70%, respectively. A low sensitivity (45%), but combined with a high specificity (100%), was found in planar 67Ga imaging. Positive and negative predictive values were 100% and 54%, respectively. It is concluded that in the context of FUO, transaxial FDG tomography performed with a DHCC is superior to 67Ga citrate SPET. This seems to be the consequence of superior tracer kinetics of FDG compared with those of 67Ga citrate and of a better spatial resolution of a DHCC system compared with SPET imaging. In patients with FUO, FDG imaging with either dedicated PET or DHCC should be considered the procedure of choice.
Infection Control in Retreatment Cases: In Vivo Antibacterial Effects of 2 Instrumentation Systems.

This in vivo study compared the antibacterial effects of 2 instrumentation systems in root canal-treated teeth with apical periodontitis.



Forty-eight teeth with a single root and a single canal showing post-treatment apical periodontitis were selected for this study. For retreatment, teeth were randomly divided into 2 groups according to the instrumentation system used: Self-Adjusting File (SAF; ReDent-Nova, Ra'anana, Israel) and Twisted File Adaptive (TFA; SybronEndo, Orange, CA). In both groups, 2.5% sodium hypochlorite was the irrigant. Bacteriological samples were taken before (S1) and after chemomechanical preparation (S2). In the TFA group, passive ultrasonic irrigation (PUI) was performed after instrumentation, and samples were also taken after this supplementary step (S2b). DNA was extracted from the clinical samples and subjected to quantitative real-time polymerase chain reaction to evaluate the levels of total bacteria, streptococci, and Enterococcus faecalis. Statistical analyses from quantitative real-time polymerase chain reaction data were performed within groups using the Wilcoxon matched pairs test and between groups using the Mann-Whitney U test and the Fisher exact test with the significance level set at P < .05.



Bacteria were detected in S1 samples from 43 teeth, which were then included in the antibacterial experiment. Both SAF and TFA instrumentation protocols showed a highly significant intracanal bacterial reduction (P < .001). Intergroup quantitative comparisons disclosed no significant differences between TFA with or without PUI and SAF (P > .05). PUI did not result in significant improvement in disinfection (P > .05).



Both instrumentation systems/treatment protocols were highly effective in significantly reducing the intracanal bacterial counts. No significant difference was observed between the 2 systems in disinfecting the canals of teeth with post-treatment apical periodontitis.
A New Urban Ecology Modeling human communities as integral parts of ecosystems poses special problems for the development and testing of ecological theory

The science of ecology was born from the expansive curiosity of the biologists of the late 19th century, who wished to understand the distribution, abundance and interactions of the earth's organisms. Why do we have so many species, and why not more, they asked--and what causes them to be distributed as they are? What are the characteristics of a biological community that cause it to recover in a particular way after a disturbance?
Building Scene Models by Completing and Hallucinating Depth and Semantics

In this document, we first provide mathematical details regarding our optimization of the visible and hidden layers. In particular, we discuss the derivation of K−1 in Section 1.3 and provide the proximal operators for the hidden layer in Section 2. We further give the detailed derivation of the proximal operators for the hidden layer as an example in Section 2.1. A similar derivation can be used for the other proximal operators. We finally provide some additional details about our experiments.
A new TCP/AQM for Stable Operation in Fast Networks

This paper is aimed at designing a congestion control system that scales gracefully with network capacity, providing high utilization, low queueing delay, dynamic stability, and fairness among users. In earlier work we had developed fluid-level control laws that achieve the first three objectives for arbitrary networks and delays, but were forced to constrain the resource allocation policy. In this paper we extend the theory to include dynamics at TCP sources, preserving the earlier features at fast time-scales, but permitting sources to match their steady-state preferences, provided a bound on round-trip-times is known. We develop two packet-level implementations of this protocol, using (i) ECN marking, and (ii) queueing delay, as means of communicating the congestion measure from links to sources. We discuss parameter choices and demonstrate using ns-2 simulations the stability of the protocol and its equilibrium features in terms of utilization, queueing and fairness. We also demonstrate the scalability of these features to increases in capacity, delay, and load, in comparison with other deployed and proposed protocols.
An open-source radio coverage prediction tool

The cellular concept applied in mobile communication systems enables significant increase of overall system capacity, but requires careful radio network planning and dimensioning. Wireless and mobile network operators typically rely on various commercial radio network planning and dimensioning tools, which incorporate different radio signal propagation models. In this paper we present the use of open-source Geographical Resources Analysis Support System (GRASS) for the calculation of radio signal coverage. We developed GRASS modules for radio coverage prediction for a number of different radio channel models, with antenna radiation patterns given in the standard MSI format. The results are stored in a data base (e.g. MySQL, PostgreSQL) for further processing and in a simplified form as a bit-map file for displaying in GRASS. The accuracy of prediction was confirmed by comparison with results obtained by a dedicated professional prediction tool as well as with measurement results.  network planning tool, open-source, GRASS GIS, path loss, raster, clutter, radio signal coverage
Effect of Photo-Fenton Bleaching on Tetracycline-stained Dentin in vitro.

Tetracycline-stained tooth structure is difficult to bleach using nightguard tray methods. The possible benefits of in-office light-accelerated bleaching systems based on the photo-Fenton reaction are of interest as possible adjunctive treatments. This study was a proof of concept for possible benefits of this approach, using dentine slabs from human tooth roots stained in a reproducible manner with the tetracycline antibiotic demeclocycline hydrochloride.



Color changes overtime in tetra-cycline stained roots from single rooted teeth treated using gel (Zoom! WhiteSpeed(®)) alone, blue LED light alone, or gel plus light in combination were tracked using standardized digital photography. Controls received no treatment. Changes in color channel data were tracked overtime, for each treatment group (N = 20 per group).



Dentin was lighter after bleaching, with significant improvements in the dentin color for the blue channel (yellow shade) followed by the green channel and luminosity. The greatest changes occurred with gel activated by light (p < 0.0001), which was superior to effects seen with gel alone. Use of the light alone did not significantly alter shade.



This proof of concept study demonstrates that bleaching using the photo-Fenton chemistry is capable of lightening tetracycline-stained dentine. Further investigation of the use of this method for treating tetracycline-stained teeth in clinical settings appears warranted.



Because tetracycline staining may respond to bleaching treatments based on the photo-Fenton reaction, systems, such as Zoom! WhiteSpeed, may have benefits as adjuncts to home bleaching for patients with tetracycline-staining.
Hexagonal hexapod robot foot-modeled dynamics simulation analysis

In this paper, to solve the problems of hexapod robot's foot frequent collisions with hard ground impact and other issues, we establish the foot-modeled and its parameters identification in the geological environment, and compile Fortran language which is based on the foot-modeled with the secondary development program by the ADAMS dynamic link and the overall hexagonal hexapod robot dynamics simulates in co-simulation of MATLAB and ADAMS. Through the analysis of the simulation results, the correctness and universality of the foot-modeled and the geological environment is verified.
A hybrid multi-objective evolutionary algorithm using an inverse neural network for aircraft control system design

This study introduces a hybrid multi-objective evolutionary algorithm (MOEA) for the optimization of aircraft control system design. The strategy suggested is composed mainly of two stages. The first stage consists of training an artificial neural network (ANN) with objective values as inputs and decision variables as outputs to model an approximation of the inverse of the objective function used. The second stage consists of a local improvement phase in objective space preserving objectives relationships, and a mapping process to decision variables using the trained ANN. Both the hybrid MOEA and the original MOEA were applied to an aircraft control system design application for assessment
Zirconia-Prefabricated Crowns for Pediatric Patients With Primary Dentition: Technique and Cementation for Esthetic Outcomes.

Traditionally, many clinicians tend to forego esthetic considerations when full-coverage restorations are indicated for pediatric patients with primary dentitions. However, the availability of new zirconia pediatric crowns and reliable techniques for cementation makes esthetic outcomes practical and consistent when restoring primary dentition. Two cases are described: a 3-year-old boy who presented with severe early childhood caries affecting both anterior and posterior teeth, and a 6-year-old boy who presented with extensive caries of his primary posterior dentition, including a molar requiring full coverage. The parents of both boys were concerned about esthetics, and the extent of decay indicated the need for full-coverage restorations. This led to the boys receiving treatment using a restorative procedure in which the carious teeth were prepared for and restored with esthetic tooth-colored zirconia crowns. In both cases, comfortable function and pleasing esthetics were achieved.
MINE: Mutual Information Neural Estimation

We argue that the estimation of mutual information between high dimensional continuous random variables can be achieved by gradient descent over neural networks. We present a Mutual Information Neural Estimator (MINE) that is linearly scalable in dimensionality as well as in sample size, trainable through back-prop, and strongly consistent. We present a handful of applications on which MINE can be used to minimize or maximize mutual information. We apply MINE to improve adversarially trained generative models. We also use MINE to implement the Information Bottleneck, applying it to supervised classification; our results demonstrate substantial improvement in flexibility and performance in these settings.
Compression of facial images using the K-SVD algorithm

The use of sparse representations in signal and image processing is gradually increasing in the past several years. Obtaining an overcomplete dictionary from a set of signals allows us to represent them as a sparse linear combination of dictionary atoms. Pursuit algorithms are then used for signal decomposition. A recent work introduced the K-SVD algorithm, which is a novel method for training overcomplete dictionaries that lead to sparse signal representation. In this work we propose a new method for compressing facial images, based on the K-SVD algorithm. We train K-SVD dictionaries for predefined image patches, and compress each new image according to these dictionaries. The encoding is based on sparse coding of each image patch using the relevant trained dictionary, and the decoding is a simple reconstruction of the patches by linear combination of atoms. An essential pre-process stage for this method is an image alignment procedure, where several facial features are detected and geometrically warped into a canonical spatial location. We present this new method, analyze its results and compare it to several competing compression techniques.