nils-herrmann/clean_scirepeval huggingface dataset:
Analyzing and automatically labelling the types of user issues that are raised in mobile app reviews

Mobile app reviews by users contain a wealth of information on the issues that users are experiencing. For example, a review might contain a feature request, a bug report, and/or a privacy complaint. Developers, users and app store owners (e.g. Apple, Blackberry, Google, Microsoft) can benefit from a better understanding of these issues – developers can better understand users’ concerns, app store owners can spot anomalous apps, and users can compare similar apps to decide which ones to download or purchase. However, user reviews are not labelled, e.g. we do not know which types of issues are raised in a review. Hence, one must sift through potentially thousands of reviews with slang and abbreviations to understand the various types of issues. Moreover, the unstructured and informal nature of reviews complicates the automated labelling of such reviews. In this paper, we study the multi-labelled nature of reviews from 20 mobile apps in the Google Play Store and Apple App Store. We find that up to 30 % of the reviews raise various types of issues in a single review (e.g. a review might contain a feature request and a bug report). We then propose an approach that can automatically assign multiple labels to reviews based on the raised issues with a precision of 66 % and recall of 65 %. Finally, we apply our approach to address three proof-of-concept analytics use case scenarios: (i) we compare competing apps to assist developers and users, (ii) we provide an overview of 601,221 reviews from 12,000 apps in the Google Play Store to assist app store owners and developers and (iii) we detect anomalous apps in the Google Play Store to assist app store owners and users.
The construction of next-generation matrices for compartmental epidemic models.

The basic reproduction number (0) is arguably the most important quantity in infectious disease epidemiology. The next-generation matrix (NGM) is the natural basis for the definition and calculation of (0) where finitely many different categories of individuals are recognized. We clear up confusion that has been around in the literature concerning the construction of this matrix, specifically for the most frequently used so-called compartmental models. We present a detailed easy recipe for the construction of the NGM from basic ingredients derived directly from the specifications of the model. We show that two related matrices exist which we define to be the NGM with large domain and the NGM with small domain. The three matrices together reflect the range of possibilities encountered in the literature for the characterization of (0). We show how they are connected and how their construction follows from the basic model ingredients, and establish that they have the same non-zero eigenvalues, the largest of which is the basic reproduction number (0). Although we present formal recipes based on linear algebra, we encourage the construction of the NGM by way of direct epidemiological reasoning, using the clear interpretation of the elements of the NGM and of the model ingredients. We present a selection of examples as a practical guide to our methods. In the appendix we present an elementary but complete proof that (0) defined as the dominant eigenvalue of the NGM for compartmental systems and the Malthusian parameter r, the real-time exponential growth rate in the early phase of an outbreak, are connected by the properties that (0) > 1 if and only if r > 0, and (0) = 1 if and only if r = 0.
Security Analysis of PHP Bytecode Protection Mechanisms

PHP is the most popular scripting language for web applications. Because no native solution to compile or protect PHP scripts exists, PHP applications are usually shipped as plain source code which is easily understood or copied by an adversary. In order to prevent such attacks, commercial products such as ionCube, Zend Guard, and Source Guardian promise a source code protection. In this paper, we analyze the inner working and security of these tools and propose a method to recover the source code by leveraging static and dynamic analysis techniques. We introduce a generic approach for decompilation of obfuscated bytecode and show that it is possible to automatically recover the original source code of protected software. As a result, we discovered previously unknown vulnerabilities and backdoors in 1 million lines of recovered source code of 10 protected applications.
Development and Application of Electrochemical Sensor Based on Molecularly Imprinted Polymer and Carbon Nanotubes for the Determination of Carvedilol

This work describes the preparation of a glassy carbon electrode (GCE) modified with molecularly imprinted polymer (MIP) and multiwalled carbon nanotubes (MWCNTs) for determination of carvedilol (CAR). Electrochemical behavior of CAR on the modified electrode was evaluated using cyclic voltammetry. The best composition was found to be 65% (m/m) of MIP. Under optimized conditions (pH 8.5 in 0.25 mol·L−1 Britton–Robinson buffer and 0.1 mol·L−1 KCl) the voltammetric method showed a linear response for CAR in the range of 50–325 μmol·L−1 (R = 0.9755), with detection and quantification limits of 16.14 μmol·L−1 and 53.8 μmol·L−1, respectively. The developed method was successfully applied for determination of CAR in real samples of pharmaceuticals. The sensor presented good sensitivity, rapid detection of CAR, and quick and easy preparation. Furthermore, the material used as modifier has a simple synthesis and its amount utilized is very small, thus illustrating the economic feasibility of this sensor.
Circular Polarization and Nonreciprocal Propagation in Magnetic Media

n The polarization of electromagnetic signals is an important feature in the design of modern radar and telecommunications. Standard electromagnetic theory readily shows that a linearly polarized plane wave propagating in free space consists of two equal but counter-rotating components of circular polarization. In magnetized media, these circular modes can be arranged to produce the nonreciprocal propagation effects that are the basic properties of isolator and circulator devices. Independent phase control of right-hand (+) and left-hand (–) circular waves is accomplished by splitting their propagation velocities through differences in the e ± m ± parameter. A phenomenological analysis of the permeability m and permittivity e in dispersive media serves to introduce the corresponding magneticand electric-dipole mechanisms of interaction length with the propagating signal. As an example of permeability dispersion, a Lincoln Laboratory quasi-optical Faradayrotation isolator circulator at 35 GHz (l ~ 1 cm) with a garnet-ferrite rotator element is described. At infrared wavelengths (l = 1.55 mm), where fiber-optic laser sources also require protection by passive isolation of the Faraday-rotation principle, e rather than m provides the dispersion, and the frequency is limited to the quantum energies of the electric-dipole atomic transitions peculiar to the molecular structure of the magnetic garnet. For optimum performance, bismuth additions to the garnet chemical formula are usually necessary. Spectroscopic and molecular theory models developed at Lincoln Laboratory to explain the bismuth effects are reviewed. In a concluding section, proposed advances in present technology are discussed in the context of future radar and telecommunications challenges.
The Nuss Procedure After Breast Augmentation for Female Pectus Excavatum

Pectus excavatum, the most common congenital chest wall malformation, has a higher incidence among men. Since 1987, when Donald Nuss performed his technique for the first time, the minimally invasive approach has become the most widely used technique for treating pectus excavatum. Few reported studies have focused on the repair of female pectus excavatum. Women with pectus excavatum often present with breast asymmetry that may require breast augmentation, either before or after pectus excavatum repair. To the authors’ knowledge, no reports on the Nuss procedure after breast implant surgery have been published. This report describes the case of a 26-year-old woman who underwent minimally invasive repair after breast implant surgery. The authors believe that for women with severe pectus excavatum, the Nuss procedure should be the first choice for surgical correction. Moreover, for breast implant patients, this technique is absolutely feasible without major complications.
Revisiting Single Image Depth Estimation: Toward Higher Resolution Maps With Accurate Object Boundaries

This paper considers the problem of single image depth estimation. The employment of convolutional neural networks (CNNs) has recently brought about significant advancements in the research of this problem. However, most existing methods suffer from loss of spatial resolution in the estimated depth maps; a typical symptom is distorted and blurry reconstruction of object boundaries. In this paper, toward more accurate estimation with a focus on depth maps with higher spatial resolution, we propose two improvements to existing approaches. One is about the strategy of fusing features extracted at different scales, for which we propose an improved network architecture consisting of four modules: an encoder, decoder, multi-scale feature fusion module, and refinement module. The other is about loss functions for measuring inference errors used in training. We show that three loss terms, which measure errors in depth, gradients and surface normals, respectively, contribute to improvement of accuracy in an complementary fashion. Experimental results show that these two improvements enable to attain higher accuracy than the current state-of-the-arts, which is given by finer resolution reconstruction, for example, with small objects and object boundaries.
Nutrition for working and service dogs.

Conformation, genetics, and behavioral drive are the major determinants of success in canine athletes, although controllable variables, such as training and nutrition, play an important role. The scope and breadth of canine athletic events has expanded dramatically in the past 30 years, but with limited research on performance nutrition. There are considerable data examining nutritional physiology in endurance dogs and in sprinting dogs; however, nutritional studies for agility, field trial, and detection are rare. This article highlights basic nutritional physiology and interventions for exercise, and reviews newer investigations regarding aging working and service dogs, and canine detection activities.
Mashup Service Clustering Based on an Integration of Service Content and Network via Exploiting a Two-Level Topic Model

The rapid growth in the number and diversity of Mashup services, coupled with the myriad of functionally similar Mashup services, makes it difficult to find suitable Mashup services to develop Mashup-based software applications due to an unprecedentedly large number of choices of Mashup services. Even if the existing latent factor based methods show significant improvements in Mashup service clustering and discovery, it is still challenging to find Mashup services with high accuracy due to overlooking of relationships among Mashup services. The relationships among Mashup services actually can be exploited in mining latent functional factors to improve the accuracy of clustering and discovery. In this paper, we propose a Mashup service clustering method based on an integration of service content and network via exploiting a two-level topic model. This method, firstly designs a two-level topic model to mine latent topics for representing functional features of Mashup services. Secondly, it uses two different random walk processes to derive and incorporate the topic distribution of Mashup services at service network level into the topic distribution of Mashup services at the service content level. Thirdly, K-means and Agnes algorithm are used to perform Mashup service clustering based on latent topics' similarity. Finally, we conduct a comprehensive evaluation to measure performance of our method. Compared with other existing clustering approaches, experimental results show that our approach achieves a significant improvement in terms of precision, recall, purity and entropy.
A deeper look into the complex relationship between social media use and academic outcomes and attitudes

The use of social media is prevalent among college students, and it is important to understand how social media use may impact students' attitudes and behaviour. Prior studies have shown negative outcomes of social media use, but researchers have not fully discovered or fully understand the processes and implications of these negative effects. This research provides additional scientific knowledge by focussing on mediators of social media use and controlling for key confounding variables.  Surveys that captured social media use, various attitudes about academics and life, and personal characteristics were completed by 234 undergraduate students at a large U.S. university. Analysis. We used covariance-based structural equation modelling to analyse the response data.  Results indicated that after controlling for self-regulation, social media use was negatively associated with academic self-efficacy and academic performance. Additionally, academic self-efficacy mediated the negative relationship between social media use and satisfaction with life.  There are negative relationships between social media use and academic performance, as well as with academic self-efficacy beliefs. Academic self-efficacy beliefs mediate the negative relationship between social media use and satisfaction with life. These relationships are present even when controlling for individuals' levels of self-regulation.
Effect of Tuned Parameters on a LSA MCQ Answering Model

This article presents the current state of a work in progress, whose objective is to better understand the effects of factors that significantly influence the performance of latent semantic analysis (LSA). A difficult task, which consisted of answering (French) biology multiple choice questions, was used to test the semantic properties of the truncated singular space and to study the relative influence of the main parameters. A dedicated software was designed to fine-tune the LSA semantic space for the multiple choice questions task. With optimal parameters, the performances of our simple model were quite surprisingly equal or superior to those of seventh- and eighth-grade students. This indicates that semantic spaces were quite good despite their low dimensions and the small sizes of the training data sets. In addition, we present an original entropy global weighting of the answers' terms for each of the multiple choice questions, which was necessary to achieve the model's success.
Risk of development of abdominal aortic aneurysm and dissection of thoracic aorta in a postpartum woman with Marfan's syndrome.

A 24-year-old pregnant woman with Marfan's syndrome delivered by cesarean section during the 38th week of gestation. Although aortic root dilatation did not increase during pregnancy, three months after delivery, the patient noticed a pulsatile abdominal mass. Aortic aneurysm was diagnosed and surgical replacement of the infrarenal abdominal aorta to the common iliac arteries and reconstruction of the inferior mesenteric artery were performed. Moreover, the patient subsequently developed a Stanford type B thoracic aortic dissection, even after more than four months of beta-blockade.
Behavior-based steering control for four wheel independent steering vehicle

This paper proposed a behavior-based steering controller for four wheel independent steering vehicle. The proposed controller acts as virtual linkages among each wheel to minimize wheel slip resulted by the misalignment of the orientations of wheels effectively. As there is no trajectory planning needed in the control algorithm, the proposed controller is especially suitable for non-autonomous vehicle which the driving path cannot be pre-determined. Numerical simulations to examine the performance of the proposed controller are implemented. Results show the effectiveness and robustness of the proposed behavior-based controller.
Aspect Ranking: Identifying Important Product Aspects from Online Consumer Reviews

In this paper, we dedicate to the topic of aspect ranking, which aims to automatically identify important product aspects from online consumer reviews. The important aspects are identified according to two observations: (a) the important aspects of a product are usually commented by a large number of consumers; and (b) consumers’ opinions on the important aspects greatly influence their overall opinions on the product. In particular, given consumer reviews of a product, we first identify the product aspects by a shallow dependency parser and determine consumers’ opinions on these aspects via a sentiment classifier. We then develop an aspect ranking algorithm to identify the important aspects by simultaneously considering the aspect frequency and the influence of consumers’ opinions given to each aspect on their overall opinions. The experimental results on 11 popular products in four domains demonstrate the effectiveness of our approach. We further apply the aspect ranking results to the application of documentlevel sentiment classification, and improve the performance significantly.
Final Collapse of the Neyman-Pearson Decision Theoretic Framework and Rise of the neoFisherian

This essay grew out of an examination of one-tailed significance testing. One-tailed tests were little advocated by the founders of modern statistics but are widely used and recommended nowadays in the biological, behavioral and social sciences. The high frequency of their use in ecology and animal behavior and their logical indefensibil-ity have been documented in a companion review paper. In the present one, we trace the roots of this problem and counter some attacks on significance testing in general. Roots include: the early but irrational dichotomization of the P scale and adoption of the 'significant/non-significant' terminology; the mistaken notion that a high P value is evidence favoring the null hypothesis over the alternative hypothesis; and confusion over the distinction between statistical and research hypotheses. Resultant widespread misuse and misinterpretation of significance tests have also led to other problems, such as unjustifiable demands that reporting of P values be disallowed or greatly reduced and that reporting of confidence intervals and standardized effect sizes be required in their place. Our analysis of these matters thus leads us to a recommendation that for standard types of significance assessment the paleoFisherian and Neyman-Pearsonian paradigms be replaced by a neoFisherian one. The essence of the latter is that a critical α (probability of type I error) is not specified, the terms 'significant' and 'non-significant' are abandoned, that high P values lead only to suspended judgments, and that the so-called " three-valued logic " of Cox, Kaiser, Tukey, Tryon and Harris is adopted explicitly. Confidence intervals and bands, power analyses, and severity curves remain useful adjuncts in particular situations. Analyses conducted under this paradigm we term neoFisherian significance assessments (NFSA). Their role is assessment of the existence, sign and magnitude of statistical effects. The common label of null hypothesis significance tests (NHST) is retained for paleoFisherian and Neyman-Pearsonian approaches and their hybrids. The original Neyman-Pearson framework has no utility outside quality control type applications. Some advocates of Bayesian, likelihood and information-theoretic approaches to model selection have argued that P values and NFSAs are of little or no value, but those arguments do not withstand critical review. Champions of Bayesian methods in particular continue to overstate their value and relevance. 312 Hurlbert & Lombardi •  A quantity of data … is to be replaced by relatively few quantities which shall …
Heteronuclear Micro-Helmholtz Coil Facilitates µm-Range Spatial and Sub-Hz Spectral Resolution NMR of nL-Volume Samples on Customisable Microfluidic Chips

We present a completely revised generation of a modular micro-NMR detector, featuring an active sample volume of ∼ 100 nL, and an improvement of 87% in probe efficiency. The detector is capable of rapidly screening different samples using exchangeable, application-specific, MEMS-fabricated, microfluidic sample containers. In contrast to our previous design, the sample holder chips can be simply sealed with adhesive tape, with excellent adhesion due to the smooth surfaces surrounding the fluidic ports, and so withstand pressures of ∼2.5 bar, while simultaneously enabling high spectral resolution up to 0.62 Hz for H2O, due to its optimised geometry. We have additionally reworked the coil design and fabrication processes, replacing liquid photoresists by dry film stock, whose final thickness does not depend on accurate volume dispensing or precise levelling during curing. We further introduced mechanical alignment structures to avoid time-intensive optical alignment of the chip stacks during assembly, while we exchanged the laser-cut, PMMA spacers by diced glass spacers, which are not susceptible to melting during cutting. Doing so led to an overall simplification of the entire fabrication chain, while simultaneously increasing the yield, due to an improved uniformity of thickness of the individual layers, and in addition, due to more accurate vertical positioning of the wirebonded coils, now delimited by a post base plateau. We demonstrate the capability of the design by acquiring a 1H spectrum of ∼ 11 nmol sucrose dissolved in D2O, where we achieved a linewidth of 1.25 Hz for the TSP reference peak. Chemical shift imaging experiments were further recorded from voxel volumes of only ∼ 1.5 nL, which corresponded to amounts of just 1.5 nmol per voxel for a 1 M concentration. To extend the micro-detector to other nuclei of interest, we have implemented a trap circuit, enabling heteronuclear spectroscopy, demonstrated by two 1H/13C 2D HSQC experiments.
Supporting the Externalisation of Thinking in Criminal Intelligence Analysis

At the end of the criminal intelligence analysis process there are relatively well established and understood approaches to explicit externalisation and representation of thought that include theories of argumentation, narrative and hybrid approaches that include both of these. However the focus of this paper is on the little understood area of how to support users in the process of arriving at such representations from an initial starting point where little is given. The work is based on theoretical considerations and some initial studies with end users. In focusing on process we discuss the requirements of fluidity and rigor and how to gain traction in investigations, the processes of thinking involved including abductive, deductive and inductive reasoning, how users may use thematic sorting in early stages of investigation and how tactile reasoning may be used to externalize and facilitate reasoning in a productive way. In the conclusion section we discuss the issues raised in this work and directions for future work.