nils-herrmann/clean_scirepeval huggingface dataset:
Medical Therapies for Adult Chronic Sinusitis: A Systematic Review.

Chronic sinusitis is a common inflammatory condition defined by persistent symptomatic inflammation of the sinonasal cavities lasting longer than 3 months. It accounts for 1% to 2% of total physician encounters and is associated with large health care expenditures. Appropriate use of medical therapies for chronic sinusitis is necessary to optimize patient quality of life (QOL) and daily functioning and minimize the risk of acute inflammatory exacerbations.



To summarize the highest-quality evidence on medical therapies for adult chronic sinusitis and provide an evidence-based approach to assist in optimizing patient care.



A systematic review searched Ovid MEDLINE (1947-January 30, 2015), EMBASE, and Cochrane Databases. The search was limited to randomized clinical trials (RCTs), systematic reviews, and meta-analyses. Evidence was categorized into maintenance and intermittent or rescue therapies and reported based on the presence or absence of nasal polyps.



Twenty-nine studies met inclusion criteria: 12 meta-analyses (>60 RCTs), 13 systematic reviews, and 4 RCTs that were not included in any of the meta-analyses. Saline irrigation improved symptom scores compared with no treatment (standardized mean difference [SMD], 1.42 [95% CI, 1.01 to 1.84]; a positive SMD indicates improvement). Topical corticosteroid therapy improved overall symptom scores (SMD, -0.46 [95% CI, -0.65 to -0.27]; a negative SMD indicates improvement), improved polyp scores (SMD, -0.73 [95% CI, -1.0 to -0.46]; a negative SMD indicates improvement), and reduced polyp recurrence after surgery (relative risk, 0.59 [95% CI, 0.45 to 0.79]). Systemic corticosteroids and oral doxycycline (both for 3 weeks) reduced polyp size compared with placebo for 3 months after treatment (P < .001). Leukotriene antagonists improved nasal symptoms compared with placebo in patients with nasal polyps (P < .01). Macrolide antibiotic for 3 months was associated with improved QOL at a single time point (24 weeks after therapy) compared with placebo for patients without polyps (SMD, -0.43 [95% CI, -0.82 to -0.05]).



Evidence supports daily high-volume saline irrigation with topical corticosteroid therapy as a first-line therapy for chronic sinusitis. A short course of systemic corticosteroids (1-3 weeks), short course of doxycycline (3 weeks), or a leukotriene antagonist may be considered in patients with nasal polyps. A prolonged course (3 months) of macrolide antibiotic may be considered for patients without polyps.
Molecular definitions of autophagy and related processes.

Over the past two decades, the molecular machinery that underlies autophagic responses has been characterized with ever increasing precision in multiple model organisms. Moreover, it has become clear that autophagy and autophagy-related processes have profound implications for human pathophysiology. However, considerable confusion persists about the use of appropriate terms to indicate specific types of autophagy and some components of the autophagy machinery, which may have detrimental effects on the expansion of the field. Driven by the overt recognition of such a potential obstacle, a panel of leading experts in the field attempts here to define several autophagy-related terms based on specific biochemical features. The ultimate objective of this collaborative exchange is to formulate recommendations that facilitate the dissemination of knowledge within and outside the field of autophagy research.
Story Cloze Evaluator: Vector Space Representation Evaluation by Predicting What Happens Next

The main intrinsic evaluation for vector space representation has been focused on textual similarity, where the task is to predict how semantically similar two words or sentences are. We propose a novel framework, Story Cloze Evaluator, for evaluating vector representations which goes beyond textual similarity and captures the notion of predicting what should happen next given a context. This evaluation methodology is simple to run, scalable, reproducible by the community, non-subjective, 100% agreeable by human, and challenging to the state-of-theart models, which makes it a promising new framework for further investment of the representation learning community.
Application impersonation: problems of OAuth and API design in online social networks

OAuth 2.0 protocol has enjoyed wide adoption by Online Social Network (OSN) providers since its inception. Although the security guideline of OAuth 2.0 is well discussed in RFC6749 and RFC6819, many real-world attacks due to the implementation specifics of OAuth 2.0 in various OSNs have been discovered. To our knowledge, previously discovered loopholes are all based on the misuse of OAuth and many of them rely on provider side or application side vulnerabilities/ faults beyond the scope of the OAuth protocol. It was generally believed that correct use of OAuth 2.0 is secure. In this paper, we show that OAuth 2.0 is intrinsically vulnerable to App impersonation attack due to its provision of multiple authorization flows and token types. We start by reviewing and analyzing the OAuth 2.0 protocol and some common API design problems found in many 1st tiered OSNs. We then propose the App impersonation attack and investigate its impact on 12 major OSN providers. We demonstrate that, App impersonation via OAuth 2.0, when combined with additional API design features/ deficiencies, make large-scale exploit and privacy-leak possible. For example, it becomes possible for an attacker to completely crawl a 200-million-user OSN within just one week and harvest data objects like the status list and friend list which are expected, by its users, to be private among only friends. We also propose fixes that can be readily deployed to tackle the OAuth2.0-based App impersonation problem.
On (4, 2)-Choosable Graphs

A graph G is called (a, b)-choosable if for any list assignment L that assigns to each vertex v a set L(v ) of a permissible colors, there is a b-tuple L-coloring of G. An (a, 1)-choosable graph is also called achoosable. In the pioneering article on list coloring of graphs by Erdős et al. , 2-choosable graphs are characterized. Confirming a special case of a conjecture in , Tuza and Voigt  proved that 2-choosable graphs are (2m, m)-choosable for any positive integer m. On the other hand, Voigt  proved that if m is an odd integer, then these are the only (2m, m)choosable graphs; however, when m is even, there are (2m, m)-choosable graphs that are not 2-choosable. A graph is called 3-choosable-critical if it is not 2-choosable, but all its proper subgraphs are 2-choosable. Voigt conjectured that for every positive integer m, all bipartite 3-choosablecritical graphs are (4m, 2m)-choosable. In this article, we determine which 3-choosable-critical graphs are (4, 2)-choosable, refuting Voigt’s conjecture in the process. Nevertheless, a weaker version of the conjecture is true: we prove that there is an even integer k such that for any positive integer m, every bipartite 3-choosable-critical graph is (2km, km)-choosable. Moving ∗ Contract grant sponsor: CNSF; contract grant number: 11571319.   412 ON (4, 2)-CHOOSABLE GRAPHS 413 beyond 3-choosable-critical graphs, we present an infinite family of non-3choosable-critical graphs that have been shown by computer analysis to be (4, 2)-choosable. This shows that the family of all (4, 2)-choosable graphs has rich structure.
Young adult sequelae of adolescent cannabis use: an integrative analysis.

Debate continues about the consequences of adolescent cannabis use. Existing data are limited in statistical power to examine rarer outcomes and less common, heavier patterns of cannabis use than those already investigated; furthermore, evidence has a piecemeal approach to reporting of young adult sequelae. We aimed to provide a broad picture of the psychosocial sequelae of adolescent cannabis use.



We integrated participant-level data from three large, long-running longitudinal studies from Australia and New Zealand: the Australian Temperament Project, the Christchurch Health and Development Study, and the Victorian Adolescent Health Cohort Study. We investigated the association between the maximum frequency of cannabis use before age 17 years (never, less than monthly, monthly or more, weekly or more, or daily) and seven developmental outcomes assessed up to age 30 years (high-school completion, attainment of university degree, cannabis dependence, use of other illicit drugs, suicide attempt, depression, and welfare dependence). The number of participants varied by outcome (N=2537 to N=3765).



We recorded clear and consistent associations and dose-response relations between the frequency of adolescent cannabis use and all adverse young adult outcomes. After covariate adjustment, compared with individuals who had never used cannabis, those who were daily users before age 17 years had clear reductions in the odds of high-school completion (adjusted odds ratio 0·37, 95% CI 0·20-0·66) and degree attainment (0·38, 0·22-0·66), and substantially increased odds of later cannabis dependence (17·95, 9·44-34·12), use of other illicit drugs (7·80, 4·46-13·63), and suicide attempt (6·83, 2·04-22·90).



Adverse sequelae of adolescent cannabis use are wide ranging and extend into young adulthood. Prevention or delay of cannabis use in adolescence is likely to have broad health and social benefits. Efforts to reform cannabis legislation should be carefully assessed to ensure they reduce adolescent cannabis use and prevent potentially adverse developmental effects.



Australian Government National Health and Medical Research Council.
Paleolimnological assessment of human-induced impacts on Walden Pond (Massachusetts, USA) using diatoms and stable isotopes

on Walden Pond (Massachusetts, USA) using diatoms and stable isotopes Dörte Köster,1∗ Reinhard Pienitz,1∗ Brent B. Wolfe,2 Sylvia Barry,3 David R. Foster,3 and Sushil S. Dixit4 Paleolimnology-Paleoecology Laboratory, Centre d’études nordiques, Department of Geography, Université Laval, Québec, Québec, G1K 7P4, Canada Department of Geography and Environmentals Studies, Wilfrid Laurier University, Waterloo, Ontario, N2L 3C5, Canada Harvard University, Harvard Forest, Post Office Box 68, Petersham, Massachusetts, 01366-0068, USA Environment Canada, National Guidelines & Standards Office, 351 St. Joseph Blvd., 8th Floor, Ottawa, Ontario, K1A 0H3, Canada ∗Corresponding authors: E-mail: doerte.koster.1@ulaval.ca,
Information filtering in high velocity text streams using limited memory: an event-driven approach to text stream analysis

This dissertation is concerned with the processing of high velocity text using event processing means. It comprises a scientific approach for combining the area of information filtering and event processing, in order to analyse fast and voluminous streams of text. In order to be able to process text streams within event driven means, an event reference model was developed that allows for the conversion of unstructured or semi-structured text streams into discrete event types on which event processing engines can operate. Additionally, a set of essential reference processes in the domain of information filtering and text stream analysis were described using eventdriven concepts. In a second step, a reference architecture was designed that described essential architectural components required for the design of information filtering and text stream analysis systems in an event-driven manner. Further to this, a set of architectural patterns for building event driven text analysis systems was derived that support the design and implementation of such systems. Subsequently, a prototype was built using the theoretic foundations. This system was initially used to study the effect of sliding window sizes on the properties of dynamic sub-corpora. It could be shown that small sliding window based corpora are similar to larger sliding windows and thus can be used as a resource-saving alternative. Next, a study of several linguistic aspects of text streams was undertaken that showed that event stream summary statistics can provide interesting insights into the characteristics of high velocity text streams. Finally, four essential information filtering and text stream analysis components were studied, viz. filter policies, term weighting, thresholds and query expansion. These were studied using three temporal search profile types and were evaluated using standard performance measures. The goal was to study the efficiency of traditional as well as new algorithms within the given context of high velocity text stream data, in order to provide advise which methods work best. The results of this dissertation are intended to provide software architects and developers with valuable information for the design and implementation of event-driven text stream analysis systems.
On Shannon's Formula and Hartley's Rule: Beyond the Mathematical Coincidence

In the information theory community, the following “historical” statements are generally well accepted: (1) Hartley did put forth his rule twenty years before Shannon; (2) Shannon’s formula as a fundamental tradeoff between transmission rate, bandwidth, and signal-to-noise ratio came out unexpected in 1948; (3) Hartley’s rule is inexact while Shannon’s formula is characteristic of the additive white Gaussian noise channel; (4) Hartley’s rule is an imprecise relation that is not an appropriate formula for the capacity of a communication channel. We show that all these four statements are somewhat wrong. In fact, a careful calculation shows that “Hartley’s rule” in fact coincides with Shannon’s formula. We explain this mathematical coincidence by deriving the necessary and sufficient conditions on an additive noise channel such that its capacity is given by Shannon’s formula and construct a sequence of such channels that makes the link between the uniform (Hartley) and Gaussian (Shannon) channels.
Impact of Cognitive Absorption on Facebook on Students' Achievement

In the great expansion of the social networking activity, young people are the main users whose choices have vast influence. This study uses the flow theory to gauge the impact of Facebook usage on Tunisian students' achievements, with the presumption that the high usage level might reduce students' scholar achievements. The research design suggests that this impact would vary among students with different interests for the university and multitasking capabilities. Facebook usage would develop students' satisfaction with friends and family, which could enhance their academic performance. Analyses from 161 Tunisian students show that Facebook usage does not affect significantly students' academic performance and their satisfaction with the family, whereas it decreases their actual satisfaction with friends. Yet, a high level of satisfaction of the student with his family continues to enhance his academic performance. Overall, though, Facebook usage appears to do not have a significant effect on undergraduate students' academic performance. However, this interdependency is significantly moderated by the student's interest for the university and his multitasking capabilities. Students with multitasking skills and students with initial interest for the university might experience a positive effect of Facebook usage on their studies, as they keep control over their activity and make it a beneficial leisure activity. However, students who do not have these characteristics tend to not have any significant effect. Results help to understand the psychological attitude and consequent behavior of the youths on this platform. Implications, limitations, and further research directions are offered.
Mandolin: A Knowledge Discovery Framework for the Web of Data

Markov Logic Networks join probabilistic modeling with first-order logic and have been shown to integrate well with the Semantic Web foundations. While several approaches have been devised to tackle the subproblems of rule mining, grounding, and inference, no comprehensive workflow has been proposed so far. In this paper, we fill this gap by introducing a framework called MANDOLIN, which implements a workflow for knowledge discovery specifically on RDF datasets. Our framework imports knowledge from referenced graphs, creates similarity relationships among similar literals, and relies on state-of-the-art techniques for rule mining, grounding, and inference computation. We show that our best configuration scales well and achieves at least comparable results with respect to other statistical-relational-learning algorithms on link prediction.
Dissipative fault-tolerant control for T-S fuzzy descriptor systems

This paper focuses on the robust dissipative fault-tolerant control problem for one kind of Takagi-Sugeno (T-S) fuzzy descriptor system with actuator failures. The solvable conditions of the robust dissipative fault-tolerant controller are given by using of the Lyapunov theory, Lagrange interpolation polynomial theory, etc. These solvable conditions not only make the closed loop system dissipative, but also integral for the actuator failure situation. The dissipative fault-tolerant controller design methods are given by the aid of the linear matrix inequality toolbox, the function of randomly generated matrix, loop statement, and numerical solution, etc. Thus, simulation process is fully intelligent and efficient. At the same time, the design methods are also obtained for the passive and H∞ fault-tolerant controllers. This explains the fact that the dissipative control unifies H∞ control and passive control. Finally, we give example that illustrates our results.
Scoping rules on a platter: a framework for understanding and specifying name binding

We present a simple and generic way to reason about name binding. Name binding is an essential component of every nontrivial programming language, matching uses of names, references, with the things that they name, declarations, based on scoping rules defined by the language. The definition of name binding is often entangled with the language-specific details, which makes abstract and comparative analysis of competing designs challenging. We present a framework that allows to abstract the fundamental notions of references, declarations, and scopes, and to express scoping rules in terms of four scope combinators and three properties of a specific programming language encapsulated in a concept named Language. Using this framework, we clarify complex scoping rules like argument-dependent lookup in C++, investigate the implications of the concepts feature for C++, and introduce a novel scoping rule named weak hiding. In an ideal world, specifications could be formulated based on our framework, and compilers could use such formulation to unambiguously implement name binding. While our examples are primarily centered around C++ and lexical scoping, our framework has applications in other languages and dynamic scoping.
Approximation Algorithms for Directed Multi-Multiway Cut and Directed Multicut Problems

In this paper, we present approximation algorithms for the directed multi-multiway cut and directed multicut problems. The so called region growing paradigm  is modified and used for these two cut problems on directed graphs By this paradigm, we give for each problem an approximation algorithm such that both algorithms have an approximate factor. The work previously done on these problems need to solve k linear programming, whereas our algorithms require only one linear programming for obtaining a good approximate factor.
Acupuncture and Meditation for Military Veterans: First Steps of Quality Management and Future Program Development

Veterans of all war eras have a high rate of chronic disease, mental health disorders, and chronic multi-symptom illnesses (CMI).(1-3) Many veterans report symptoms that affect multiple biological systems as opposed to isolated disease states. Standard medical treatments often target isolated disease states such as headaches, insomnia, or back pain and at times may miss the more complex, multisystem dysfunction that has been documented in the veteran population. Research has shown that veterans have complex symptomatology involving physical, cognitive, psychological, and behavioral disturbances, such as difficult to diagnose pain patterns, irritable bowel syndrome, chronic fatigue, anxiety, depression, sleep disturbance, or neurocognitive dysfunction.(2-4) Meditation and acupuncture are each broad-spectrum treatments designed to target multiple biological systems simultaneously, and thus, may be well suited for these complex chronic illnesses. The emerging literature indicates that complementary and integrative medicine (CIM) approaches augment standard medical treatments to enhance positive outcomes for those with chronic disease, mental health disorders, and CMI.(5-12.
Internet of Things for Disaster Management: State-of-the-Art and Prospects

Disastrous events are cordially involved with the momentum of nature. As such mishaps have been showing off own mastery, situations have gone beyond the control of human resistive mechanisms far ago. Fortunately, several technologies are in service to gain affirmative knowledge and analysis of a disaster’s occurrence. Recently, Internet of Things (IoT) paradigm has opened a promising door toward catering of multitude problems related to agriculture, industry, security, and medicine due to its attractive features, such as heterogeneity, interoperability, light-weight, and flexibility. This paper surveys existing approaches to encounter the relevant issues with disasters, such as early warning, notification, data analytics, knowledge aggregation, remote monitoring, real-time analytics, and victim localization. Simultaneous interventions with IoT are also given utmost importance while presenting these facts. A comprehensive discussion on the state-of-the-art scenarios to handle disastrous events is presented. Furthermore, IoT-supported protocols and market-ready deployable products are summarized to address these issues. Finally, this survey highlights open challenges and research trends in IoT-enabled disaster management systems.
Networks of spiking neurons can emulate arbitrary Hopfield nets in temporal coding

A theoretical model for analogue computation in networks of spiking neurons with temporal coding is introduced and tested through simulations in GENESIS. It turns out that the use of multiple synapses yields very noise robust mechanisms for analogue computations via the timing of single spikes in networks of detailed compartmental neuron models. In this way, one arrives at a method for emulating arbitrary Hopfield nets with spiking neurons in temporal coding, yielding new models for associative recall of spatio-temporal firing patterns. We also show that it suffices to store these patterns in the efficacies of excitatory synapses. A correspondinglayered architecture yields a refinement of the synfire-chain model that can assume a fairly large set of different stable firing patterns for different inputs.
Sensorless Field Oriented Control ( FOC ) of an AC Induction Motor ( ACIM ) Using Field Weakening

The utilization of an AC induction motor (ACIM) ranges from consumer to automotive applications, with a variety of power and sizes. From the multitude of possible applications, some require the achievement of high speed while having a high torque value only at low speeds. Two applications needing this requirement are washing machines in consumer applications and traction in powertrain applications. These requirements impose a certain type of approach for induction motor control, which is known as “field weakening.”