nils-herrmann/clean_scirepeval huggingface dataset:
My expressed breast milk turned pink!

A 28-year-old breastfeeding mother of term-born 3-month old twins contacted the Hospital Lactation consultant for advice. She had expressed milk at 2am and had stored the milk in the fridge. She fed some of that milk to one of the twins at 11am and further milk to both twins at 4pm. All three bottles were left on the bench until the next morning when the mother intended to clean the bottles. She found that the milk residue in all three feeding bottles had turned bright pink and had a strong earthy odour (see Fig. 1). The mother brought one of the bottles containing the bright pink milk with her to the hospital. The mother was in good health, with no symptoms of mastitis and no fever. Both twins were also healthy and continued to feed well and gain weight. What is the cause of the pink milk? (answer on page 82)
Clustering android malware families by http traffic

Due to its popularity and open-source nature, Android is the mobile platform that has been targeted the most by malware that aim to steal personal information or to control the users' devices. More specifically, mobile botnets are malware that allow an attacker to remotely control the victims' devices through different channels like HTTP, thus creating malicious networks of bots. In this paper, we show how it is possible to effectively group mobile botnets families by analyzing the HTTP traffic they generate. To do so, we create malware clusters by looking at specific statistical information that are related to the HTTP traffic. This approach also allows us to extract signatures with which it is possible to precisely detect new malware that belong to the clustered families. Contrarily to x86 malware, we show that using fine-grained HTTP structural features do not increase detection performances. Finally, we point out how the HTTP information flow among mobile bots contains more information when compared to the one generated by desktop ones, allowing for a more precise detection of mobile threats.
Text as Scene: Discourse Deixis and Bridging Relations

This paper presents a new framework, “text as scene”, which lays the foundations for the annotation of two coreferential links: discourse deixis and bridging relations. The incorporation of what we call textual and contextual scenes provides more flexible annotation guidelines, broad type categories being clearly differentiated. Such a framework that is capable of dealing with discourse deixis and bridging relations from a common perspective aims at improving the poor reliability scores obtained by previous annotation schemes, which fail to capture the vague references inherent in both these links. The guidelines presented here complete the annotation scheme designed to enrich the Spanish CESS-ECE corpus with coreference information, thus building the CESS-Ancora corpus.
Transformational leadership and innovative work behavior

The purpose of this paper is to explore the mediating role of psychological empowerment and the moderating role of self-construal (independent and interdependent) on the relationship between transformational leadership and employees’ innovative work behavior (IWB).  A total of 639 followers and 87 leaders filled out questionnaires from cross-industry sample of five most innovative companies of China. Structural equation modeling was used to analyze the relations.  Results revealed that psychological empowerment mediated the relationship between transformational leadership and IWB. The research established that transformational leadership positively influences IWB which includes idea generation as well as idea implementation. The results also showed that the relationship between transformational leadership and IWB was stronger among employees with a higher interdependent self-construal and a lower independent self-construal.  This study adds to IWB literature by empirically testing the moderating role of self-construal and the mediating role of psychological empowerment on transformational leadership-IWB link.
The effect of endodontic solutions on resorcinol-formalin paste in teeth.

This study determined if any of six endodontic solutions would have a softening effect on resorcinol-formalin paste in extracted teeth, and if there were any differences in the solvent action between these solutions. Forty-nine single-rooted extracted teeth were decoronated 2 mm coronal to the CEJ, and the roots sectioned apically to a standard length of 15 mm. Canals were prepared to a 12 mm WL and a uniform size with a #7 Parapost drill. Teeth were then mounted in a cylinder ring with acrylic. The resorcinol-formalin mixture was placed into the canals and was allowed to set for 60 days in a humidor. The solutions tested were 0.9% sodium chloride, 5.25% sodium hypochlorite, chloroform, Endosolv R (Endosolv R), 3% hydrogen peroxide, and 70% isopropyl alcohol. Seven samples per solution were tested and seven samples using water served as controls. One drop of the solution was placed over the set mixture in the canal, and the depth of penetration of a 1.5-mm probe was measured at 2, 5, 10, and 20 min using a dial micrometer gauge. A repeated-measures ANOVA showed a difference in penetration between the solutions at 10 min (p = 0.04) and at 20 min (p = 0.0004). At 20 min, Endosolv R, had significantly greater penetration than 5.25% sodium hypochlorite (p = 0.0033) and chloroform (p = 0.0018); however, it was not significantly better than the control (p = 0.0812). Although Endosolv R, had statistically superior probe penetration at 20 min, the softening effect could not be detected clinically at this time.
The fractional Fourier transform and time-frequency representations

The fractional Fourier transform (FRFT), which is a generalization of the classical Fourier transform, was introduced a number of years ago in the mathematics literature but appears to have remained largely unknown to the signal processing community, to which it may, however, be potentially useful. The FRFT depends on a parameter cy and can be interpreted as a rotation by an angle a in the time-frequency plane. An FRFT with a = n-/2 corresponds to the classical Fourier transform, and an FRFT with Q = 0 corresponds to the identity operator. On the other hand, the angles of successively performed FRFT’s simply add up, as do the angles of successive rotations. The FRFT of a signal can also be interpreted as a decomposition of the signal in terms of chirps. In this paper, we briefly introduce the FRFT and a number of its properties and then present some new results: the interpretation as a rotation in the time-frequency plane, and the FRFT’s relationships with time-frequency representations such as the Wigner distribution, the ambiguity function, the shorttime Fourier transform and the spectrogram. These relationships have a very simple and natural form and support the FRFT’s interpretation as a rotation operator. Examples of FRFT’s of some simple signals are given. An example of the application of the FRFT is also given.
In vivo imaging of early stage apoptosis by measuring real-time caspase-3/7 activation

In vivo imaging of apoptosis in a preclinical setting in anticancer drug development could provide remarkable advantages in terms of translational medicine. So far, several imaging technologies with different probes have been used to achieve this goal. Here we describe a bioluminescence imaging approach that uses a new formulation of Z-DEVD-aminoluciferin, a caspase 3/7 substrate, to monitor in vivo apoptosis in tumor cells engineered to express luciferase. Upon apoptosis induction, Z-DEVD-aminoluciferin is cleaved by caspase 3/7 releasing aminoluciferin that is now free to react with luciferase generating measurable light. Thus, the activation of caspase 3/7 can be measured by quantifying the bioluminescent signal. Using this approach, we have been able to monitor caspase-3 activation and subsequent apoptosis induction after camptothecin and temozolomide treatment on xenograft mouse models of colon cancer and glioblastoma, respectively. Treated mice showed more than 2-fold induction of Z-DEVD-aminoluciferin luminescent signal when compared to the untreated group. Combining D-luciferin that measures the total tumor burden, with Z-DEVD-aminoluciferin that assesses apoptosis induction via caspase activation, we confirmed that it is possible to follow non-invasively tumor growth inhibition and induction of apoptosis after treatment in the same animal over time. Moreover, here we have proved that following early apoptosis induction by caspase 3 activation is a good biomarker that accurately predicts tumor growth inhibition by anti-cancer drugs in engineered colon cancer and glioblastoma cell lines and in their respective mouse xenograft models.
The Impact of the Exploring Computer Science Instructional Model in Chicago Public Schools

As part of the Taste of Computing project, the Exploring Computer Science (ECS) instructional model has been expanded to many high schools in the Chicago Public Schools system. The authors report on initial outcomes showing that students value the ECS course experience, resulting in increased awareness of and interest in the field of computer science. The authors also compare these results by race and gender. The data provide a good basis for exploring the impact of meaningful computer science instruction on students from groups underrepresented in computing; of several hundred students surveyed, nearly half were female, and over half were Hispanic or African American.
Socioeconomic status and obesity.

The objective of this review was to update Sobal and Stunkard's exhaustive review of the literature on the relation between socioeconomic status (SES) and obesity (. Diverse research databases (including CINAHL, ERIC, MEDLINE, and Social Science Abstracts) were comprehensively searched during the years 1988-2004 inclusive, using "obesity," "socioeconomic status," and synonyms as search terms. A total of 333 published studies, representing 1,914 primarily cross-sectional associations, were included in the review. The overall pattern of results, for both men and women, was of an increasing proportion of positive associations and a decreasing proportion of negative associations as one moved from countries with high levels of socioeconomic development to countries with medium and low levels of development. Findings varied by SES indicator; for example, negative associations (lower SES associated with larger body size) for women in highly developed countries were most common with education and occupation, while positive associations for women in medium- and low-development countries were most common with income and material possessions. Patterns for women in higher- versus lower-development countries were generally less striking than those observed by Sobal and Stunkard; this finding is interpreted in light of trends related to globalization. Results underscore a view of obesity as a social phenomenon, for which appropriate action includes targeting both economic and sociocultural factors.
Learning with Hypergraphs: Clustering, Classification, and Embedding

We usually endow the investigated objects with pairwise relationships, which can be illustrated as graphs. In many real-world problems, however, relationships among the objects of our interest are more complex than pairwise. Naively squeezing the complex relationships into pairwise ones will inevitably lead to loss of information which can be expected valuable for our learning tasks however. Therefore we consider using hypergraphs instead to completely represent complex relationships among the objects of our interest, and thus the problem of learning with hypergraphs arises. Our main contribution in this paper is to generalize the powerful methodology of spectral clustering which originally operates on undirected graphs to hypergraphs, and further develop algorithms for hypergraph embedding and transductive classification on the basis of the spectral hypergraph clustering approach. Our experiments on a number of benchmarks showed the advantages of hypergraphs over usual graphs.
Shortest path problem considering on-time arrival probability Yu (

This paper studies the problem of finding a priori shortest paths to guarantee a given likelihood of arriving on-time in a stochastic network. Such ‘‘reliable” paths help travelers better plan their trips to prepare for the risk of running late in the face of stochastic travel times. Optimal solutions to the problem can be obtained from local-reliable paths, which are a set of non-dominated paths under first-order stochastic dominance. We show that Bellman’s principle of optimality can be applied to construct local-reliable paths. Acyclicity of local-reliable paths is established and used for proving finite convergence of solution procedures. The connection between the a priori path problem and the corresponding adaptive routing problem is also revealed. A label-correcting algorithm is proposed and its complexity is analyzed. A pseudo-polynomial approximation is proposed based on extreme-dominance. An extension that allows travel time distribution functions to vary over time is also discussed. We show that the time-dependent problem is decomposable with respect to arrival times and therefore can be solved as easily as its static counterpart. Numerical results are provided using typical transportation networks.
Molecular characterization of two opecoelid trematodes from fishes in the Gulf of Mexico, with a description of a new species of Helicometra

The plagioporine opecoelids Helicometra fasciata (Rudolphi, 1819) Odhner, 1902, and Macvicaria crassigula (Linton, 1910) Bartoli, Bray, and Gibson, 1989 have been reported from fishes in expansive geographic regions, disjointed from their type localities. New material of M. crassigula was collected from near its type locality as well as specimens resembling Helicometra fasciata sensu lato from three triglids in the Gulf of Mexico. Comparisons of the ribosomal DNA (rDNA) sequences, comprising the partial 18S rDNA, internal transcribed spacer region (= ITS1, 5.8S, and ITS2), and partial 28S rDNA gene, from M. crassigula and Helicometra fasciata sensu lato in the Gulf of Mexico were made with sequences deposited in GenBank from those species from the Mediterranean Sea. Results reveal that M. crassigula sensu stricto from the Gulf of Mexico is distinct from the two cryptic species of M. crassigula sensu lato from the Mediterranean Sea and Helicometra fasciata sensu lato in this study differs from H. fasciata sequences from the Mediterranean Sea, thus Helicometra manteri sp. nov. is described.
" Sam " Neurofeedback in Der Kinder-und Jugendpsychiatrie Göttingen Englisch: Attention-deficit Hyperactivity Disorder (adhd)

Die Aufmerksamkeitsdefizit-/Hyperaktivitätsstörung (ADHS) 1 ist eine der häufigsten psychiatrischen Störungen des Kindes-und Jugendalters. Die betroffenen Kinder zeigen als wesentliche Kennzeichen (unterschiedlicher Ausprägung)-einen Mangel an Konzentration und Ausdauer und eine Tendenz, von einer Tätigkeit zu einer anderen zu wechseln, ohne etwas zu Ende zu bringen (Unaufmerksamkeit),-einen deutlichen Mangel an kognitiver und emotionaler Impulskontrolle (Impulsivität) und / oder-eine überschießende allgemein erhöhte motorische Aktivität (Hyperaktivität/motorische Unruhe).
Exploration in Gradient-Based Reinforcement Learning

Gradient-based policy search is an alternative to value-function-based methods for reinforcement learning in non-Markovian domains. One apparent drawback of policy search is its requirement that all actions be \on-policy"; that is, that there be no explicit exploration. In this paper, we provide a method for using importance sampling to allow any well-behaved directed exploration policy during learning. We show both theoretically and experimentally that using this method can achieve dramatic performance improvements. During this work, Nicolas Meuleau was at the MIT Arti cial Intelligence laboratory, supported in part by a research grant from NTT; Leonid Peshkin by grants from NSF and NTT; and Kee-Eung Kim in part by AFOSR/RLF 30602-95-1-0020.
1 Planar Inter Digital Capacitors on Printed Circuit

Coplanar wave guide (CPW) inter digital capacitor (IDC) configurations on printed circuit board (PCB) and parametric variations over frequency are studied by simulation using ADS Momentum. The structures are fabricated in printed circuit board using PCB fabrication techniques. The scattering parameters of the structure are measured using vector network analyzer (VNA). The capacitance is estimated in both case using an approximate circuit model and simulation. A Comparative study of the simulation performance with measured results conducted.
Cumulative mortality of Aedes aegypti larvae treated with compounds

To evaluate the larvicidal activity of Azadirachta indica, Melaleuca alternifolia, carapa guianensis essential oils and fermented extract of Carica papaya against Aedes aegypti (Linnaeus, 1762) (Diptera: Culicidae).  The larvicide test was performed in triplicate with 300 larvae for each experimental group using the third larval stage, which were exposed for 24h. The groups were: positive control with industrial larvicide (BTI) in concentrations of 0.37 ppm (PC1) and 0.06 ppm (PC2); treated with compounds of essential oils and fermented extract, 50.0% concentration (G1); treated with compounds of essential oils and fermented extract, 25.0% concentration (G2); treated with compounds of essential oils and fermented extract, 12.5% concentration (G3); and negative control group using water (NC1) and using dimethyl (NC2). The larvae were monitored every 60 min using direct visualization.  No mortality occurred in experimental groups NC1 and NC2 in the 24h exposure period, whereas there was 100% mortality in the PC1 and PC2 groups compared to NC1 and NC2. Mortality rates of 65.0%, 50.0% and 78.0% were observed in the groups G1, G2 and G3 respectively, compared with NC1 and NC2.  The association between three essential oils from Azadirachta indica, Melaleuca alternifolia, Carapa guianensis and fermented extract of Carica papaya was efficient at all concentrations. Therefore, it can be used in Aedes aegypti Liverpool third larvae stage control programs.
Learning via human feedback in continuous state and action spaces

This paper considers the problem of extending Training an Agent Manually via Evaluative Reinforcement (TAMER) in continuous state and action spaces. Investigative research using the TAMER framework enables a non-technical human to train an agent through a natural form of human feedback (negative or positive). The advantages of TAMER have been shown on tasks of training agents by only human feedback or combining human feedback with environment rewards. However, these methods are originally designed for discrete state-action, or continuous state-discrete action problems. This paper proposes an extension of TAMER to allow both continuous states and actions, called ACTAMER. The new framework utilizes any general function approximation of a human trainer’s feedback signal. Moreover, a combined capability of ACTAMER and reinforcement learning is also investigated and evaluated. The combination of human feedback and reinforcement learning is studied in both settings: sequential and simultaneous. Our experimental results demonstrate the proposed method successfully allowing a human to train an agent in two continuous state-action domains: Mountain Car and Cart-pole (balancing).
Online detection of freezing of gait with smartphones and machine learning techniques

Freezing of gait (FoG) is a common gait deficit in advanced Parkinson's disease (PD). FoG events are associated with falls, interfere with daily life activities and impair quality of life. FoG is often resistant to pharmacologic treatment; therefore effective non-pharmacologic assistance is needed. We propose a wearable assistant, composed of a smartphone and wearable accelerometers, for online detection of FoG. The system is based on machine learning techniques for automatic detection of FoG episodes. When FoG is detected, the assistant provides rhythmic auditory cueing or vibrotactile feedback that stimulates the patient to resume walking. We tested our solution on more than 8h of recorded lab data from PD patients that experience FoG in daily life. We characterize the system performance on user-dependent and user-independent experiments, with respect to different machine learning algorithms, sensor placement and preprocessing window size. The final system was able to detect FoG events with an average sensitivity and specificity of more than 95%, and mean detection latency of 0.34s in user-dependent settings.
An HCI View of Configuration Problems

In recent years, configuration problems have drawn tremendous attention because of their increasing prevalence and their big impact on system availability. We believe that man y of these problems are attributable to today’s configuration interfaces that have not evolved to accommodate the enormous shift of the system administrator group. Plain text files, as thede factoconfiguration interfaces, assume administrators’ understanding of the system under configuration. They ask administrators to directly edit the corresponding entries with little guidance or assistance. However, this assumption no longer holds for today’s administrator group which has expanded greatly to include nonand semi-professional admin istrators. In this paper, we provide an HCI view of today’s configuration problems, and articulate system configuratio n as a new HCI problem. Moreover, we present the top obstacles to correctly and efficiently configuring software syste ms, and most importantly their implications on the design and implementation of new-generation configuration interface s.
Powertrace : Network-level Power Profiling for Low-power Wireless Networks

Low-power wireless networks are quickly becoming a critical part of our everyday infrastructure. Power consumption is a critical concern, but power measurement and estimation is a challenge. We present Powertrace, which to the best of our knowledge is the first system for network-level power profiling of low-power wireless systems. Powertrace uses power state tracking to estimate system power consumption and a structure called energy capsules to attribute energy consumption to activities such as packet transmissions and receptions. With Powertrace, the power consumption of a system can be broken down into individual activities which allows us to answer questions such as “How much energy is spent forwarding packets for node X?”, “How much energy is spent on control traffic and how much on critical data?”, and “How much energy does application X account for?”. Experiments show that Powertrace is accurate to 94% of the energy consumption of a device. To demonstrate the usefulness of Powertrace, we use it to experimentally analyze the power behavior of the proposed IETF standard IPv6 RPL routing protocol and a sensor network data collection protocol. Through using Powertrace, we find the highest power consumers and are able to reduce the power consumption of data collection with 24%. It is our hope that Powertrace will help the community to make empirical energy evaluation a widely used tool in the low-power wireless research community toolbox.
TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow

We introduce TensorFlow Agents, an efficient infrastructure paradigm for building parallel reinforcement learning algorithms in TensorFlow. We simulate multiple environments in parallel, and group them to perform the neural network computation on a batch rather than individual observations. This allows the TensorFlow execution engine to parallelize computation, without the need for manual synchronization. Environments are stepped in separate Python processes to progress them in parallel without interference of the global interpreter lock. As part of this project, we introduce BatchPPO, an efficient implementation of the proximal policy optimization algorithm. By open sourcing TensorFlow Agents, we hope to provide a flexible starting point for future projects that accelerates future research in the field.