nils-herrmann/clean_scirepeval huggingface dataset:
Effect of Single and Contiguous Teeth Extractions on Alveolar Bone Remodeling : A Study in Dogscid

Tooth extraction is associated with dimensional changes in the alveolar ridge. The aim was to examine the effect of single versus contiguous teeth extractions on the alveolar ridge remodeling.  Five female beagle dogs were randomly divided into three groups on the basis of location (anterior or posterior) and number of teeth extracted – exctraction socket classification: group 1 (one dog): single-tooth extraction; group 2 (two dogs): extraction of two teeth; and group 3 (two dogs): extraction of three teeth in four anterior sites and four posterior sites in both jaws. The dogs were sacrificed after 4 months. Sagittal sectioning of each extraction site was performed and evaluated using microcomputed tomography.  Buccolingual or palatal bone loss was observed 4 months after extraction in all three groups. The mean of the alveolar ridge width loss in group 1 (single-tooth extraction) was significantly less than those in groups 2 and 3 (p < .001) (multiple teeth extraction). Three-teeth extraction (group 3) had significantly more alveolar bone loss than two-teeth extraction (group 2) (p < .001). The three-teeth extraction group in the upper and lower showed more obvious resorption on the palatal/lingual side especially in the lower group posterior locations.  Contiguous teeth extraction caused significantly more alveolar ridge bone loss as compared with when a single tooth is extracted.
An Intelligent Teaching Assistant System for Logic

This paper presents the Logic-ITA, an Intelligent Teaching Assistant system for the teaching/learning of propositional logic. Intelligent Teaching Assistant Systems are dedicated both to learners and teachers. The system embeds three tools: the Logic Tutor, the LT-Configurator and the LT-Analyser. The Logic Tutor is an intelligent tutoring system destined to the students. The other two tools are dedicated to the teacher. The LT-Configurator manages teaching configuration settings and material. The LT-Analyser is for monitoring the class’ progress and collect data.
Local Word Vectors Guide Keyphrase Extraction

Word vector representation techniques, built on word-word co-occurrence statistics, often provide representations that decode the differences in meaning between various words. This significant fact is a powerful tool that can be exploited to a great deal of natural language processing tasks. In this work, we propose a simple and efficient unsupervised approach for keyphrase extraction, called Reference Vector Algorithm (RVA) which utilizes a local word vector representation by applying the GloVe method in the context of one scientific publication at a time. Then, the mean word vector (reference vector) of the article’s abstract guides the candidate keywords’ selection process, using the cosine similarity. The experimental results that emerged through a thorough evaluation process show that our method outperforms the state-of-the-art methods by providing high quality keyphrases in most cases, proposing in this way an additional mode for the exploitation of GloVe word vectors.
Carbon monoxide has anti-inflammatory effects involving the mitogen-activated protein kinase pathway

The stress-inducible protein heme oxygenase-1 provides protection against oxidative stress. The anti-inflammatory properties of heme oxygenase-1 may serve as a basis for this cytoprotection. We demonstrate here that carbon monoxide, a by-product of heme catabolism by heme oxygenase, mediates potent anti-inflammatory effects. Both in vivo and in vitro, carbon monoxide at low concentrations differentially and selectively inhibited the expression of lipopolysaccharide-induced pro-inflammatory cytokines tumor necrosis factor-α, interleukin-1β, and macrophage inflammatory protein-1β and increased the lipopolysaccharide-induced expression of the anti-inflammatory cytokine interleukin-10. Carbon monoxide mediated these anti-inflammatory effects not through a guanylyl cyclase–cGMP or nitric oxide pathway, but instead through a pathway involving the mitogen-activated protein kinases. These data indicate the possibility that carbon monoxide may have an important protective function in inflammatory disease states and thus has potential therapeutic uses.
Fighting Food Loss and Food Waste in Japan

Japan discards approximately 18 million tonnes of food annually, an amount that accounts for 40% of national food production. In recent years, a number of measures have been adopted at the institutional level to tackle this issue, showing increasing commitment of the government and other organizations. Along with the aim of environmental sustainability, food waste recycling, food loss prevention and consumer awareness raising in Japan are clearly pursuing another common objective. Although food loss and waste problems have been publicly acknowledged only very recently, strong implications arise from the economic and cultural history of the Japanese food system. Specific national concerns over food security have accompanied the formulation of current national strategies whose underlying causes and objectives add a unique facet to Japan’s efforts with respect to those of other developed countries’. Fighting Food Loss and Food Waste in Japan
Linguistically Regularized LSTMs for Sentiment Classification

This paper deals with sentence-level sentiment classification. Though a variety of neural network models have been proposed recently, however, previous models either depend on expensive phrase-level annotation, most of which has remarkably degraded performance when trained with only sentence-level annotation; or do not fully employ linguistic resources (e.g., sentiment lexicons, negation words, intensity words). In this paper, we propose simple models trained with sentence-level annotation, but also attempt to model the linguistic role of sentiment lexicons, negation words, and intensity words. Results show that our models are able to capture the linguistic role of sentiment words, negation words, and intensity words in sentiment expression.
Data-driven serverless functions for object storage

Traditionally, active storage techniques have been proposed to move computation tasks to storage nodes in order to exploit data locality. However, we argue in this paper that active storage is ill-suited for cloud storage for two reasons: 1. Lack of elasticity: Computing can only scale out with the number of storage nodes; and 2.  Sharing compute resources can produce interferences in the storage system. Serverless computing is now emerging as a promising alternative for ensuring painless scalability, and also, for simplifying the development of disaggregated computing tasks.
 Here we present an innovative data-driven serverless computing middleware for object storage. It is a lightweight compute solution that allows users to create small, stateless functions that intercept and operate on data flows in a scalable manner without the need to manage a server or a runtime environment. We demonstrate through different use cases how our solution scales with minimal overhead, while getting rid of the resource contention problems incurred by active storage tasks.
Prefrontal space ratio in second- and third-trimester screening for trisomy 21.

To evaluate the prefrontal space ratio (PFSR) in second- and third-trimester euploid fetuses and fetuses with trisomy 21.



This was a retrospective study utilizing stored mid-sagittal two-dimensional images of second- and third-trimester fetal faces that were recorded during prenatal ultrasound examinations at the Department of Prenatal Medicine at the University of Tuebingen, Germany and at a private center for prenatal medicine in Nuremberg, Germany. For the normal range, 279 euploid pregnancies between 15 and 40 weeks' gestation were included. The results were compared with 91 cases with trisomy 21 between 15 and 40 weeks. For the ratio measurement, a line was drawn between the leading edge of the mandible and the maxilla (MM line) and extended in front of the forehead. The ratio of the distance between the leading edge of the skull and the leading edge of the skin (d1) to the distance between the skin and the point where the MM line was intercepted (d2) was calculated. The PFSR was determined by dividing d2 by d1.



In the euploid and trisomy 21 groups, the median gestational age at the time of ultrasound examination was 21.1 (range, 15.0-40.0) and 21.4 (range, 15.0-40.3) weeks, respectively. Multiple regression analysis showed that PFSR was independent of maternal and gestational age. In the euploid group, the mean PFSR was 0.97 ± 0.29. In fetuses with trisomy 21, the mean PFSR was 0.2 ± 0.38 (P < 0.0001). The PFSR was below the 5(th) centile in 14 (5.0%) euploid fetuses and in 72 (79.1%) fetuses with trisomy 21.



The PFSR is a simple and effective marker in second- and third-trimester screening for trisomy 21.
Mining information from credit card time series for timelier fraud detection

As e-commerce sales continue to grow, the associated online fraud remains an attractive source of revenue for fraudsters. These fraudulent activities impose a considerable financial loss to merchants, making online fraud detection a necessity. The problem of fraud detection is concerned with not only capturing the fraudulent activities, but also capturing them as quickly as possible. This timeliness is crucial to decrease financial losses. In this research, a profiling method has been proposed for credit card fraud detection. The focus is on fraud cases which cannot be detected at the transaction level. In the proposed method the patterns inherent in the time series of aggregated daily amounts spent on an individual credit card account has been extracted. These patterns have been used to shorten the time between when a fraud occurs and when it is finally detected, which resulted in timelier fraud detection, improved detection rate and less financial loss.
A Molecular Phylogeny of Living Primates

Comparative genomic analyses of primates offer considerable potential to define and understand the processes that mold, shape, and transform the human genome. However, primate taxonomy is both complex and controversial, with marginal unifying consensus of the evolutionary hierarchy of extant primate species. Here we provide new genomic sequence (~8 Mb) from 186 primates representing 61 (~90%) of the described genera, and we include outgroup species from Dermoptera, Scandentia, and Lagomorpha. The resultant phylogeny is exceptionally robust and illuminates events in primate evolution from ancient to recent, clarifying numerous taxonomic controversies and providing new data on human evolution. Ongoing speciation, reticulate evolution, ancient relic lineages, unequal rates of evolution, and disparate distributions of insertions/deletions among the reconstructed primate lineages are uncovered. Our resolution of the primate phylogeny provides an essential evolutionary framework with far-reaching applications including: human selection and adaptation, global emergence of zoonotic diseases, mammalian comparative genomics, primate taxonomy, and conservation of endangered species.
INTERGROUP relations.

INDIVIDUAL PROCESSES IN INTERGROUP BEHAVIOR ................................ 3 From Individual to Group Impressions ...................................................................... 3 GROUP MEMBERSHIP AND INTERGROUP BEHAVIOR .................................. 7 The Scope and Range of Ethnocentrism .................................................................... 8 The Development of Ethnocentrism .......................................................................... 9 Intergroup Conflict and Competition ........................................................................ 12 Interpersonal and intergroup behavior ........................................................................ 13 Intergroup conflict and group cohesion ........................................................................ 15 Power and status in intergroup behavior ...................................................................... 16 Social Categorization and Intergroup Behavior ........................................................ 20 Social categorization: cognitions, values, and groups ...................................................... 20 Social categorization a d intergroup discrimination ...................................................... 23 Social identity and social comparison .......................................................................... 24 THE REDUCTION FINTERGROUP DISCRIMINATION ................................ 27 Intergroup Cooperation and Superordinate Goals " 28 Intergroup Contact. .... ................................................................................................ 28 Multigroup Membership and "lndividualizat~’on" of the Outgroup .......................... 29 SUMMARY .................................................................................................................... 30
THEORY BUILDING FROM CASES : OPPORTUNITIES AND CHALLENGES

ion (i.e., probes) that was more accurate than the individual instantiations (e.g., alliances, exploratory products). Multiple cases also enable broader exploration of research questions and theoretical elaboration. For example, Brown and Eisenhardt (1998) added successful and unsuccessful turnaround cases that enabled them to add further longitudinal elements to their theory. Because case numbers are typically small, a few additional cases can significantly affect the quality of the emergent theory. For example, adding three cases to a single-case study is modest in terms of numbers, but offers four times the analytic power. Thus, theory building from multiple cases typically yields more robust, generalizable, and testable theory than single-case research. But although multiple cases are likely to result in better theory, theoretical sampling is more complicated. The choice is based less on the uniqueness of a given case, and more on the contribution to theory development within the set of cases. That is, multiple cases are chosen for theoretical reasons such as replication, extension of theory, contrary replication, and elimination of alternative explanations (Yin, 1994). For example, Graebner and Eisenhardt (2004) studied acquisition from the seller perspective by examining three replicated cases in which the executives sold their companies, a contrary replication in which executives could have sold their companies but did not, and then further cases in different industries that explored industrylevel explanations. A particularly important theoretical sampling approach is “polar types,” in which a researcher samples extreme (e.g., very high and very low performing) cases in order to more easily observe contrasting patterns in the data. Although such an approach can surprise reviewers because the resulting theory is so consistently supported by the empirical evidence, this sampling leads to very clear pattern recognition of the central constructs, relationships, and logic of the focal phenomenon. 2007 27 Eisenhardt and Graebner
Infrastructure, programs, and policies to increase bicycling: an international review.

To assess existing research on the effects of various interventions on levels of bicycling. Interventions include infrastructure (e.g., bike lanes and parking), integration with public transport, education and marketing programs, bicycle access programs, and legal issues.



A comprehensive search of peer-reviewed and non-reviewed research identified 139 studies. Study methodologies varied considerably in type and quality, with few meeting rigorous standards. Secondary data were gathered for 14 case study cities that adopted multiple interventions.



Many studies show positive associations between specific interventions and levels of bicycling. The 14 case studies show that almost all cities adopting comprehensive packages of interventions experienced large increases in the number of bicycle trips and share of people bicycling.



Most of the evidence examined in this review supports the crucial role of public policy in encouraging bicycling. Substantial increases in bicycling require an integrated package of many different, complementary interventions, including infrastructure provision and pro-bicycle programs, supportive land use planning, and restrictions on car use.
Network Transplanting

This paper focuses on a new task, i.e. transplanting a category-and-task-specific neural network to a generic, modular network without strong supervision. We design an functionally interpretable structure for the generic network. Like building LEGO blocks, we teach the generic network a new category by directly transplanting the module corresponding to the category from a pre-trained network with a few or even without sample annotations. Our method incrementally adds new categories to the generic network but does not affect representations of existing categories. In this way, our method breaks the typical bottleneck of learning a net for massive tasks and categories, i.e. the requirement of collecting samples for all tasks and categories at the same time before the learning begins. Thus, we use a new distillation algorithm, namely back-distillation, to overcome specific challenges of network transplanting. Our method without training samples even outperformed the baseline with 100 training samples.
Mission-centricity in cyber security: Architecting cyber attack resilient missions

Until recently the information technology (IT)-centricity was the prevailing paradigm in cyber security that was organized around confidentiality, integrity and availability of IT assets. Despite of its widespread usage, the weakness of IT-centric cyber security became increasingly obvious with the deployment of very large IT infrastructures and introduction of highly mobile tactical missions where the IT-centric cyber security was not able to take into account the dynamics of time and space bound behavior of missions and changes in their operational context. In this paper we will show that the move from IT-centricity towards to the notion of cyber attack resilient missions opens new opportunities in achieving the completion of mission goals even if the IT assets and services that are supporting the missions are under cyber attacks. The paper discusses several fundamental architectural principles of achieving cyber attack resilience of missions, including mission-centricity, survivability through adaptation, synergistic mission C2 and mission cyber security management, and the real-time temporal execution of the mission tasks. In order to achieve the overall system resilience and survivability under a cyber attack, both, the missions and the IT infrastructure are considered as two interacting adaptable multi-agent systems. While the paper is mostly concerned with the architectural principles of achieving cyber attack resilient missions, several models and algorithms that support resilience of missions are discussed in fairly detailed manner.
Idioms : A View from Cognitive Semantics

According to the most common definition, idioms are linguistic expressions whose overall meaning cannot be predicted from the meanings of the constituent parts Although we agree with the traditional view that there is no complete predictability, we suggest that there is a great deal of systematic conceptual motivation for the meaning of most idioms Since most idioms are based on conceptual metaphors and metonymies, systematic motivation arises from sets of 'conceptual mappings or correspondences' that obtain between a source and a target domain in the sense of Lakoff and Koiecses (1987) We distinguish among three aspects of idiomatic meaning First, the general meaning of idioms appears to be determined by the particular 'source domains' that apply to a particular target domain Second, more specific aspects ot idiomatic meaning are provided by the 'ontological mapping that applies to a given idiomatic expression Third, connotative aspects ot idiomatic meaning can be accounted for by 'epistemic correspondences' Finally, we also present an informal experimental study the results of which show that the cognitive semantic view can facilitate the learning of idioms for non-native speakers
Metaphor Clusters , Metaphor Chains : Analyzing the Multifunctionality of Metaphor in Text

This paper applies Halliday's (1994) theory of the interpersonal, ideational and textual meta-functions of language to conceptual metaphor. Starting from the observation that metaphoric expressions tend to be organized in chains across texts, the question is raised what functions those expressions serve in different parts of a text as well as in relation to each other. The empirical part of the article consists of the sample analysis of a business magazine text on marketing. This analysis is two-fold, integrating computer-assisted quantitative investigation with qualitative research into the organization and multifunctionality of metaphoric chains as well as the cognitive scenarios evolving from those chains. The paper closes by summarizing the main insights along the lines of the three Hallidayan meta-functions of conceptual metaphor and suggesting functional analysis of metaphor at levels beyond that of text. Im vorliegenden Artikel wird Hallidays (1994) Theorie der interpersonellen, ideellen und textuellen Metafunktion von Sprache auf das Gebiet der konzeptuellen Metapher angewandt. Ausgehend von der Beobachtung, dass metaphorische Ausdrücke oft in textumspannenden Ketten angeordnet sind, wird der Frage nachgegangen, welche Funktionen diese Ausdrücke in verschiedenen Teilen eines Textes und in Bezug aufeinander erfüllen. Der empirische Teil der Arbeit besteht aus der exemplarischen Analyse eines Artikels aus einem Wirtschaftsmagazin zum Thema Marketing. Diese Analysis gliedert sich in zwei Teile und verbindet computergestütze quantitative Forschung mit einer qualitativen Untersuchung der Anordnung und Multifunktionalität von Metaphernketten sowie der kognitiven Szenarien, die aus diesen Ketten entstehen. Der Aufsatz schließt mit einer Zusammenfassung der wesentlichen Ergebnisse im Licht der Hallidayschen Metafunktionen konzeptueller Metaphern und gibt einen Ausblick auf eine funktionale Metaphernanalyse, die über die rein textuelle Ebene hinausgeht.
Simple and Effective Semi-Supervised Question Answering

Recent success of deep learning models for the task of extractive Question Answering (QA) is hinged on the availability of large annotated corpora. However, large domain specific annotated corpora are limited and expensive to construct. In this work, we envision a system where the end user specifies a set of base documents and only a few labelled examples. Our system exploits the document structure to create cloze-style questions from these base documents; pre-trains a powerful neural network on the cloze style questions; and further finetunes the model on the labeled examples. We evaluate our proposed system across three diverse datasets from different domains, and find it to be highly effective with very little labeled data. We attain more than 50% F1 score on SQuAD and TriviaQA with less than a thousand labelled examples. We are also releasing a set of 3.2M cloze-style questions for practitioners to use while building QA systems1.
Optimal Load Shedding Using an Ensemble of Artificial Neural Networks

Optimal load shedding is a very critical issue in power systems. It plays a vital role, especially in third world countries. A sudden increase in load can affect the important parameters of the power system like voltage, frequency and phase angle. This paper presents a case study of Pakistan’s power system, where the generated power, the load demand, frequency deviation and load shedding during a 24-hour period have been provided. An artificial neural network ensemble is aimed for optimal load shedding. The objective of this paper is to maintain power system frequency stability by shedding an accurate amount of load. Due to its fast convergence and improved generalization ability, the proposed algorithm helps to deal with load shedding in an efficient manner.