nils-herrmann/clean_scirepeval huggingface dataset:
Motors, switches, and contacts in the replisome.

Replisomes are the protein assemblies that replicate DNA. They function as molecular motors to catalyze template-mediated polymerization of nucleotides, unwinding of DNA, the synthesis of RNA primers, and the assembly of proteins on DNA. The replisome of bacteriophage T7 contains a minimum of proteins, thus facilitating its study. This review describes the molecular motors and coordination of their activities, with emphasis on the T7 replisome. Nucleotide selection, movement of the polymerase, binding of the processivity factor, unwinding of DNA, and RNA primer synthesis all require conformational changes and protein contacts. Lagging-strand synthesis is mediated via a replication loop whose formation and resolution is dictated by switches to yield Okazaki fragments of discrete size. Both strands are synthesized at identical rates, controlled by a molecular brake that halts leading-strand synthesis during primer synthesis. The helicase serves as a reservoir for polymerases that can initiate DNA synthesis at the replication fork. We comment on the differences in other systems where applicable.
G-Spotplasty: A New Surgical Plastic Intervention—The Preliminary Study

Ostrzenski’s G-pot anatomical structure discovery has been verified by the anatomy, histology, MRI in vivo, and electrovaginography in vivo studies. The objectives of this scientific-clinical investigation were to develop a new surgical reconstructive intervention (G-spotplasty); to determine the ability of G-spotplasty surgical implementation; to observe for potential complications; and to gather initial information on whether G-spotplasty improves female sexual activity, sexual behaviors, and sexual concerns. A case series study was designed and conducted with 5-year follow-up (October 2013 and October 2017). The rehearsal of new G-spotplasty was performed on fresh female cadavers. Three consecutive live women constituted this clinical study population, and they were subjected to the newly developed G-spotplasty procedure in October 2013. Preoperatively and postoperatively, a validated, self-completion instrument of Sexual Relationships and Activities Questionnaire (SRA-Q) was used to measure female sexual activity, sexual behaviors, and sexual concerns. Three out of twelve women met inclusion criteria and were incorporated into this study. All patients were subjected to G-spotplasty, completed 5-year follow-up, and returned completed SRA-Q in a sealed envelope. New G-spotplasty was successfully implemented without surgical difficulty and without complications. All patients reported re-establishing vaginal orgasms with different degrees of difficulties, observing return of anterior vaginal wall engorgement, and were very pleased with the outcome of G-spotplasty. The G-spotplasty is a simple surgical intervention, easy to implement, and improves sexual activities, sexual behaviors, and sexual concerns. The preliminary results are very promising and paved the way for additional clinical-scientific research. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.
Real-time Personalization using Embeddings for Search Ranking at Airbnb

Search Ranking and Recommendations are fundamental problems of crucial interest to major Internet companies, including web search engines, content publishing websites and marketplaces. However, despite sharing some common characteristics a one-size-fits-all solution does not exist in this space. Given a large difference in content that needs to be ranked, personalized and recommended, each marketplace has a somewhat unique challenge. Correspondingly, at Airbnb, a short-term rental marketplace, search and recommendation problems are quite unique, being a two-sided marketplace in which one needs to optimize for host and guest preferences, in a world where a user rarely consumes the same item twice and one listing can accept only one guest for a certain set of dates. In this paper we describe Listing and User Embedding techniques we developed and deployed for purposes of Real-time Personalization in Search Ranking and Similar Listing Recommendations, two channels that drive 99% of conversions. The embedding models were specifically tailored for Airbnb marketplace, and are able to capture guest's short-term and long-term interests, delivering effective home listing recommendations. We conducted rigorous offline testing of the embedding models, followed by successful online tests before fully deploying them into production.
A study of organic food consumption behavior using the decomposed theory of planned behavior

Organic food is an achievement of agricultural scientific and technological innovations, in order to ensure the application of agricultural science and technology and innovation from organic agricultural producers and participants benefit. This study employed the decomposed theory of planned behavior to analyze the antecedent factors that influence consumer purchase of organic food by deconstruction of the constructs related to attitude, the subjective norm, and the perceived behavioral control. Based on these influencing effects, the study aimed to provide marketing suggestions to popularize organic food. In total, 441 effective questionnaires were collected. The data was analyzed using the structural equation model. The study results indicate that consumers with ethical consciousness will consider environmental protection when they make food purchasing decisions, and have a comparatively positive attitude towards the purchase of organic food. One of the main motives for purchasing organic food is the requirement that food ingredients are safe and natural. Additionally, with respect to external influences, consumers tend to trust information delivered by TV media, experts, and Internet word-of-mouth. Nonetheless, consumers with high or low involvement obviously have significant differences in the relationships between facilitating conditions and perceived behavioral control. Therefore, intensifying the environmental resources of organic food will enhance the purchasing intention of consumers who have low involvement.
A Delicious Recipe Analysis Framework for Exploring Multi-Modal Recipes with Various Attributes

Human beings have developed a diverse food culture. Many factors like ingredients, visual appearance, courses (e.g., breakfast and lunch), flavor and geographical regions affect our food perception and choice. In this work, we focus on multi-dimensional food analysis based on these food factors to benefit various applications like summary and recommendation. For that solution, we propose a delicious recipe analysis framework to incorporate various types of continuous and discrete attribute features and multi-modal information from recipes. First, we develop a Multi-Attribute Theme Modeling (MATM) method, which can incorporate arbitrary types of attribute features to jointly model them and the textual content. We then utilize a multi-modal embedding method to build the correlation between the learned textual theme features from MATM and visual features from the deep learning network. By learning attribute-theme relations and multi-modal correlation, we are able to fulfill different applications, including (1) flavor analysis and comparison for better understanding the flavor patterns from different dimensions, such as the region and course, (2) region-oriented multi-dimensional food summary with both multi-modal and multi-attribute information and (3) multi-attribute oriented recipe recommendation. Furthermore, our proposed framework is flexible and enables easy incorporation of arbitrary types of attributes and modalities. Qualitative and quantitative evaluation results have validated the effectiveness of the proposed method and framework on the collected Yummly dataset.
Common errors of reasoning in child protection work.

Repeated public inquiries into child abuse tragedies in Britain demonstrate the level of public concern about the services designed to protect children. These inquiries identify faults in professionals' practice but the similarities in their findings indicate that they are having insufficient impact on improving practice. This study is based on the hypothesis that the recurrent errors may be explicable as examples of the typical errors of human reasoning identified by psychological research.



The sample comprised all child abuse inquiry reports published in Britain between 1973 and 1994 (45 in total). Using a content analysis and a framework derived from psychological research on reasoning, a study was made of the reasoning of the professionals involved and the findings of the inquiries.



It was found that professionals based assessments of risk on a narrow range of evidence. It was biased towards the information readily available to them, overlooking significant data known to other professionals. The range was also biased towards the more memorable data, that is, towards evidence that was vivid, concrete, arousing emotion and either the first or last information received. The evidence was also often faulty, due, in the main, to biased or dishonest reporting or errors in communication. A critical attitude to evidence was found to correlate with whether or not the new information supported the existing view of the family. A major problem was that professionals were slow to revise their judgements despite a mounting body of evidence against them.



Errors in professional reasoning in child protection work are not random but predictable on the basis of research on how people intuitively simplify reasoning processes in making complex judgements. These errors can be reduced if people are aware of them and strive consciously to avoid them. Aids to reasoning need to be developed that recognize the central role of intuitive reasoning but offer methods for checking intuitive judgements more rigorously and systematically.
A Portable , Extensible and Efficient Implementation of Proactor Pattern

The Proactor pattern  describes how to structure applications and systems that effectively utilize asynchronous mechanisms supported by operating systems. When an application invokes an asynchronous operation, the OS performs the operation on behalf of the application. This allows the application to have multiple operations running simultaneously without requiring the application to have a corresponding number of threads. Therefore, the Proactor pattern simplifies concurrent programming and improves performance by requiring fewer threads and leveraging OS support for asynchronous operations. The Adaptive Communications Environment (ACE)  has implemented a Proactor framework that encapsulates I/O Completion Ports of Windows NT operating system. This ACE Proactor abstraction provides an OO interface to the standard C APIs supported by Windows NT. We ported this Proactor framework to Unix platforms that support POSIX4 asynchronous I/O calls and real-time signals. This paper describes the design and implementation of this new Portable Proactor framework and explains how the design and the implementation have been made so that the framework can be extensible, scalable and efficient. We explain how our design took care of keeping the old interfaces of the framework intact, still making the design highly extensible and efficient. The source code for this implementation can be acquired from the ACE website at www.cs.wustl.edu/ schmidt/ACE.html . 1 The Proactor Pattern
BUE ACE 1 Sustainable Vital Technologies in Engineering & Informatics 8-10 Nov 2016 Internet of Things – A Complete Solution for Aviation ' s Predictive Maintenance

The University of South Carolina has been involved in research for the US military for helicopters and rotary aircraft for over 18 years. Majority of this work has been focused on optimizing aircraft uptime and flight readiness by leveraging condition-based maintenance (CBM), more commonly known as predictive maintenance (PM). This type of maintenance differs from other classical styles (reactive and preventive) in that it has a high reliability and a low cost. The foundation of PM in any application is data collection and storage. It begins with applying tools such as natural language processing (NLP) to historical maintenance records to determine the most critical components on the aircraft. Data mining of previously collected sensor data is then used to establish the most reliable types of condition indicators (CIs) that monitor the critical components. These thresholds from the CIs can be modified over time as more data is collected. Once a data collection scheme is in place, prognostics can be used to determine the remaining useful life of a component. Using this process, along with an optimized maintenance schedule through the maintenance steering group (MSG-3) program, helps to eliminate unnecessary maintenance actions on the aircraft, as well as, reduce the inventory of components needed for the aircraft to operate. After this maintenance scheme has been set up, the Internet of Things (IoT) can be leveraged to allow the entire process to operate within a single environment. This further develops the solution, and allows actions to be executed more quickly than if they were performed individually. The expected benefits and future development of these practices will never come to fruition unless personnel are properly educated and trained. Developing a culture of predictive maintenance practices in an aviation environment is necessary to ensure success of this solution.  Selection and/or peer-review under responsibility of Global Science and Technology Forum Pte Ltd
Formalizing Schoenberg’s Fundamentals of Musical Composition through Petri Nets

The formalization of musical composition rules is a topic that has been studied for a long time. It can lead to a better understanding of the underlying processes, and provide a useful tool for musicologist to aid and speed up the analysis process. In our attempt we introduce Schoenberg’s rules from Fundamentals of Musical Composition using a specialized version of Petri nets, called Music Petri nets. Petri nets are a formal tool for studying systems that are concurrent, asynchronous, distributed, parallel, nondeterministic, and/or stochastic. We present some examples highlighting how multiple approaches to the analysis task can find counterparts in specific instances of PNs.
Novel High Step-Up DC–DC Converter With Coupled-Inductor and Switched-Capacitor Techniques

A novel high step-up dc-dc converter with coupled-inductor and switched-capacitor techniques is proposed in this paper. The capacitors are charged in parallel and are discharged in series by the coupled inductor, stacking on the output capacitor. Thus, the proposed converter can achieve high step-up voltage gain with appropriate duty ratio. Besides, the voltage spike on the main switch can be clamped. Therefore, low on-state resistance RDS(ON) of the main switch can be adopted to reduce the conduction loss. The efficiency can be improved. The operating principle and steady-state analyses are discussed in detail. Finally, a prototype circuit with 24-V input voltage, 400-V output voltage, and 200-W output power is implemented in the laboratory. Experiment results confirm the analysis and advantages of the proposed converter.
Narrow-Size Multiband Inverted-F Antenna

We present a narrow-size multiband inverted-F antenna (IFA), which can easily fit inside the housing of display units of ultra-slim laptops. The narrowness of the antenna is achieved by allowing some of its metallic parts to extend over the sidewalls of the dielectric substrate. The antenna is aimed to operate in all the allocated WiFi and WiMAX frequency bands while providing near-omnidirectional coverage in the horizontal plane. The multiband performance of the proposed antenna and its omnidirectionality are validated by measurements.
What can comparative studies of placental structure tell us?--A review.

The diversity of placental structures in Eutherian mammals is such that drawing generalizations from the definitive forms is problematic. There are always areas of reduced interhaemal distance whether the placenta is epitheliochorial, synepitheliochorial, endotheliochorial or haemochorial. However, the thinning may be achieved by different means. The presence of a haemophagous area as an iron transport facilitator is generally associated with endotheliochorial placentae but is also found in sheep and goats (synepitheliochorial) and in tenrecs and hyaenas (haemochorial). Although similar chorioallantoic placentae are found within families, structure begins to diverge at the ordinal level and there is little correlation at the supraordinal level of phylogeny. Differences in formation and function of the yolk sac provide additional variation. There would appear to be considerable adaptive pressure for development or retention of the haemochorial type of chorioallantoic placenta. This type of placenta has several possible drawbacks including more ready passage of fetal cells to the maternal organism and, should the haemochorial condition be achieved early, oxidative stress. At any rate no animal larger than the human and gorilla has this type of placenta. The endotheliochorial condition is found in animals as large as the bears, manatee and elephants. In addition to the ungulates, the epitheliochorial condition is present in the largest animals with the longest gestation periods, the whales. Considering the length of time since the early stages of mammalian evolution, it is probable that few unmodified structural features are present in any currently surviving mammal. Nevertheless, more complete studies of divergent types of mammalian placenta should help our understanding of mammalian interrelationships as well as placental function.
Bayesian Learning for Spatial Filtering in an EEG-Based Brain–Computer Interface

Spatial filtering for EEG feature extraction and classification is an important tool in brain-computer interface. However, there is generally no established theory that links spatial filtering directly to Bayes classification error. To address this issue, this paper proposes and studies a Bayesian analysis theory for spatial filtering in relation to Bayes error. Following the maximum entropy principle, we introduce a gamma probability model for describing single-trial EEG power features. We then formulate and analyze the theoretical relationship between Bayes classification error and the so-called Rayleigh quotient, which is a function of spatial filters and basically measures the ratio in power features between two classes. This paper also reports our extensive study that examines the theory and its use in classification, using three publicly available EEG data sets and state-of-the-art spatial filtering techniques and various classifiers. Specifically, we validate the positive relationship between Bayes error and Rayleigh quotient in real EEG power features. Finally, we demonstrate that the Bayes error can be practically reduced by applying a new spatial filter with lower Rayleigh quotient.
Journal of Theoretical and Applied Information Technology

Research on software architecture from different perspectives has been done for several years. However, Architectural Knowledge (AK), a relatively new field, has gained its increasing interest among the community. On this regard, various topics devoted to architectural knowledge, such as reusing, sharing, managing, and communicating are being studied. Among them, AK sharing brings new effective challenges and issues not present when studying other topics in architectural knowledge. Therefore, this paper surveys the current researches on AK sharing (pertaining to software architecture), the approaches, models that are being proposed, and issues that arise when sharing different AKs by different parties. By making survey on AK sharing approaches, a better understanding of these approaches and issues related in this area is provided so that it can be a penetrative resource for a fast training and educating in this area of SE. In addition, conclusion about current state of research in this area and future trends for AK sharing is identified.
A master-slave synchronization model for enhanced servo clock design

Slave servo clocks have an essential role in hardware and software synchronization techniques based on Precision Time Protocol (PTP). The objective of servo clocks is to remove the drift between slave and master nodes, while keeping the output timing jitter within given uncertainty boundaries. Up to now, no univocal criteria exist for servo clock design. In fact, the relationship between controller design, performances and uncertainty sources is quite evanescent. In this paper, we propose a quite simple, but exhaustive linear model, which is expected to be used in the design of enhanced servo clock architectures.
Influence of Tactical and Situational Variables on Offensive Sequences During Elite Football Matches.

Sarmento, H, Figueiredo, A, Lago-Peñas, C, Milanovic, Z, Barbosa, A, Tadeu, P, and Bradley, PS. Influence of tactical and situational variables on offensive sequences during elite football matches.  2331-2339, 2018-This study examined the influence of tactical and situational variables on offensive sequences during elite football matches. A sample of 68 games and 1,694 offensive sequences from the Spanish La Liga, Italian Serie A, German Bundesliga, English Premier League, and Champions League were analyzed using χ and logistic regression analyses. Results revealed that counterattacks (odds ratio [OR] = 1.44; 95% confidence interval [CI]: 1.13-1.83; p < 0.01) and fast attacks (OR = 1.43; 95% CI: 1.11-1.85; p < 0.01) increased the success of an offensive sequence by 40% compared with positional attacks. The chance of an offensive sequence ending effectively in games from the Spanish, Italian, and English Leagues were higher than that in the Champions League. Offensive sequences that started in the preoffensive or offensive zones were more successful than those started in the defensive zones. An increase of 1 second in the offensive sequence duration and an extra pass resulted in a decrease of 2% (OR = 0.98; 95% CI: 0.98-0.99; p < 0.001) and 7% (OR = 0.93; 95% CI: 0.91-0.96; p < 0.001), respectively, in the probability of its success. These findings could assist coaches in designing specific training situations that improve the effectiveness of the offensive process.
Long-term study of safe Internet use of young children

The Internet is an evolving medium that continuously presents new functionalities. Accordingly, also children's Internet usage changes continuously. This requires being vigilant about related Internet risk behavior and safe Internet use. The present article presents a structured overview of Internet risks and summarizes approaches to foster safe Internet behavior. Based on a long-term cross-sectional study, Internet usage of young children has been researched. The focus is on contact risks and content risks. Based on the analysis of survey data from 10000 children, trends in their (un)safe An Unsafe Internet Usage Index (UIUI) is calculated. The average results point at a rather low level of unsafe Internet usage. But these average results hide between-subject differences and a number of children clearly reflects higher levels of unsafe Internet usage. Also, no consistent reduction in unsafe Internet behavior is being observed over the years. Parental and teacher control seem to decrease, and hardly seem to impact the level of unsafe Internet behavior. Considering a number of limitations of the present study, directions for future research are discussed.