nils-herrmann/clean_scirepeval huggingface dataset:
The unified theory of acceptance and use of technology (UTAUT): a literature review

The purpose of this paper is to perform a systematic review of articles that have used the unified theory of acceptance and use of technology (UTAUT).  The results produced in this research are based on the literature analysis of 174 existing articles on the UTAUT model. This has been performed by collecting data including demographic details, methodological details, limitations, and significance of relationships between the constructs from the available articles based on the UTAUT.  The findings were categorised by dividing the articles that used the UTAUT model into types of information systems used, research approach and methods employed, and tools and techniques implemented to analyse results. We also perform the weight analysis of variables and found that performance expectancy and behavioural intention qualified for the best predictor category. The research also analysed and presented the limitations of existing studies.  The search activities were centered on occurrences of keywords to avoid tracing a large number of publications where these keywords might have been used as casual words in the main text. However, we acknowledge that there may be a number of studies, which lack keywords in the title, but still focus upon UTAUT in some form.  This is the first research of its type, which has extensively examined the literature on the UTAUT and provided the researchers with the accumulative knowledge about the model.
Pair correlation function characteristics of nearly jammed disordered and ordered hard-sphere packings.

We study the approach to jamming in hard-sphere packings and, in particular, the pair correlation function g(2) (r) around contact, both theoretically and computationally. Our computational data unambiguously separate the narrowing delta -function contribution to g(2) due to emerging interparticle contacts from the background contribution due to near contacts. The data also show with unprecedented accuracy that disordered hard-sphere packings are strictly isostatic: i.e., the number of exact contacts in the jamming limit is exactly equal to the number of degrees of freedom, once rattlers are removed. For such isostatic packings, we derive a theoretical connection between the probability distribution of interparticle forces P(f) (f) , which we measure computationally, and the contact contribution to g(2) . We verify this relation for computationally generated isostatic packings that are representative of the maximally random jammed state. We clearly observe a maximum in P(f) and a nonzero probability of zero force, shedding light on long-standing questions in the granular-media literature. We computationally observe an unusual power-law divergence in the near-contact contribution to g(2) , persistent even in the jamming limit, with exponent -0.4 clearly distinguishable from previously proposed inverse-square-root divergence. Additionally, we present high-quality numerical data on the two discontinuities in the split-second peak of g(2) and use a shared-neighbor analysis of the graph representing the contact network to study the local particle clusters responsible for the peculiar features. Finally, we present the computational data on the contact contribution to g(2) for vacancy-diluted fcc crystal packings and also investigate partially crystallized packings along the transition from maximally disordered to fully ordered packings. We find that the contact network remains isostatic even when ordering is present. Unlike previous studies, we find that ordering has a significant impact on the shape of P(f) for small forces.
Matching HTML Tables to DBpedia

Millions of HTML tables containing structured data can be found on the Web. With their wide coverage, these tables are potentially very useful for filling missing values and extending cross-domain knowledge bases such as DBpedia, YAGO, or the Google Knowledge Graph. As a prerequisite for being able to use table data for knowledge base extension, the HTML tables need to be matched with the knowledge base, meaning that correspondences between table rows/columns and entities/schema elements of the knowledge base need to be found. This paper presents the T2D gold standard for measuring and comparing the performance of HTML table to knowledge base matching systems. T2D consists of 8 700 schema-level and 26 100 entity-level correspondences between the WebDataCommons Web Tables Corpus and the DBpedia knowledge base. In contrast related work on HTML table to knowledge base matching, the Web Tables Corpus (147 million tables), the knowledge base, as well as the gold standard are publicly available. The gold standard is used afterward to evaluate the performance of T2K Match, an iterative matching method which combines schema and instance matching. T2K Match is designed for the use case of matching large quantities of mostly small and narrow HTML tables against large cross-domain knowledge bases. The evaluation using the T2D gold standard shows that T2K Match discovers table-to-class correspondences with a precision of 94%, row-to-entity correspondences with a precision of 90%, and column-to-property correspondences with a precision of 77%.
Artificial immune recognition systems in medical diagnosis

Medical diagnosis is an exciting are of research and many researchers have been working on the application of Artificial Intelligence techniques to develop disease recognition systems. They are analysing currently available information and also biochemical data collecting from clinical laboratories and experts for identifying pathological status of the patient. During the process of diagnosis, the clinical data so obtained from several sources must be inferred and classified into a particular pathology. Computer aided diagnosis tools designed based on biologically inspired methods such as artificial neural/immune networks can be employed to improve the regular diagnostic process and to avoid misdiagnosis. In this paper pre-processing and classification techniques are used to train the system. Artificial immune recognition method is used for pre-processing and KNN classifier is used for classification. The system is tested with some sample data and obtained the results. The system is validated with annotated data.
Perspectives on human population structure at the cusp of the sequencing era.

Human groups show structured levels of genetic similarity as a consequence of factors such as geographical subdivision and genetic drift. Surveying this structure gives us a scientific perspective on human origins, sheds light on evolutionary processes that shape both human adaptation and disease, and is integral to effectively carrying out the mission of global medical genetics and personalized medicine. Surveys of population structure have been ongoing for decades, but in the past three years, single-nucleotide-polymorphism (SNP) array technology has provided unprecedented detail on human population structure at global and regional scales. These studies have confirmed well-known relationships between distantly related populations and uncovered previously unresolvable relationships among closely related human groups. SNPs represent the first dense genome-wide markers, and as such, their analysis has raised many challenges and insights relevant to the study of population genetics with whole-genome sequences. Here we draw on the lessons from these studies to anticipate the directions that will be most fruitful to pursue during the emerging whole-genome sequencing era.
Online Trust Production: Interactions among Trust Building Mechanisms

Lack of trust has been identified as a major obstacle to the adoption of online shopping. However, there is paucity of research that investigates the effectiveness of various trust building mechanisms, especially the interactions amongst these mechanisms. In this study, three trust building mechanisms (i.e., third-party certification, reputation, and return policy) were examined. Scenario survey method was used for data collection. 463 usable questionnaires were collected from respondents with diverse backgrounds. Regression results show that all three trust building mechanisms have significant positive effects on trust in the online vendor. Their effects are not simple ones; the different trust building mechanisms interact with one another to produce an overall effect on the level of trust. These results have both theoretical and practical implications.
A Transportation $$L^p$$ L p Distance for Signal Analysis

Transport-based distances, such as the Wasserstein distance and earth mover’s distance, have been shown to be an effective tool in signal and image analysis. The success of transport-based distances is in part due to their Lagrangian nature which allows it to capture the important variations in many signal classes. However, these distances require the signal to be non-negative and normalised. Furthermore, the signals are considered as measures and compared by redistributing (transporting) them, which does not directly take into account the signal intensity. Here, we study a transport-based distance, called the $$TL^p$$ T L p distance, that combines Lagrangian and intensity modelling and is directly applicable to general, non-positive and multichannelled signals. The distance can be computed by existing numerical methods. We give an overview of the basic properties of this distance and applications to classification, with multichannelled non-positive one-dimensional signals and two-dimensional images, and colour transfer.
Design Patterns: Abstraction and Reuse of Object-Oriented Design

We propose design patterns as a new mechanism for expressing object-oriented design experience. Design patterns identify, name, and abstract common themes in objectoriented design. They capture the intent behind a design by identifying objects, their collaborations, and the distribution of responsibilities. Design patterns play many roles in the object-oriented development process: they provide a common vocabulary for design, they reduce system complexity by naming and de ning abstractions, they constitute a base of experience for building reusable software, and they act as building blocks from which more complex designs can be built. Design patterns can be considered reusable micro-architectures that contribute to an overall system architecture. We describe how to express and organize design patterns and introduce a catalog of design patterns. We also describe our experience in applying design patterns to the design of object-oriented systems.
Fitted Learning: Models with Awareness of their Limits

Though deep learning has pushed the boundaries of classification forward, in recent years hints of the limits of standard classification have begun to emerge. Problems such as fooling, adding new classes over time, and the need to retrain learning models only for small changes to the original problem all point to a potential shortcoming in the classic classification regime, where a comprehensive a priori knowledge of the possible classes or concepts is critical. Without such knowledge, classifiers misjudge the limits of their knowledge and overgeneralization therefore becomes a serious obstacle to consistent performance. In response to these challenges, this paper extends the classic regime by reframing classification instead with the assumption that concepts present in the training set are only a sample of the hypothetical final set of concepts. To bring learning models into this new paradigm, a novel elaboration of standard architectures called the competitive overcomplete output layer (COOL) neural network is introduced. Experiments demonstrate the effectiveness of COOL by applying it to fooling, separable concept learning, one-class neural networks, and standard classification benchmarks. The results suggest that, unlike conventional classifiers, the amount of generalization in COOL networks can be tuned to match the problem.
Path-based depth-first search for strong and biconnected components

Depth-first search, as developed by Tarjan and coauthors, is a fundamental technique of efficient algorithm design for graphs . This note presents depth-first search algorithms for two basic problems, strong and biconnected components. Previous algorithms either compute auxiliary quantities based on the depth-first search tree (e.g., LOWPOINT values) or require two passes. We present one-pass algorithms that only maintain a representation of the depth-first search path. This gives a simplified view of depth-first search without sacrificing efficiency. In greater detail, most depth-first search algorithms (e.g., [23,10,11]) compute so-called LOWPOINT values that are defined in terms of the depth-first search tree. Because of the success of this method LOWPOINT values have become almost synonymous with depth-first search. LOWPOINT values are regarded as crucial in the strong and biconnected component algorithms, e.g., [14, pp. 94, 514]. Tarjan’s LOWPOINT method for strong components is presented in texts [1, 7,14,16,17,21]. The strong component algorithm of Kosaraju and Sharir [22] is often viewed as conceptu-
Transitive Text Mining for Information Extraction and Hypothesis Generation

Transitive text mining-also named Swanson Linking (SL) after its primary and principal researcher-tries to establish meaningful links between literature sets which are virtually disjoint in the sense that each does not mention the main concept of the other. If successful, SL may give rise to the development of new hypotheses. In this communication we describe our approach to transitive text mining which employs co-occurrence analysis of the medical subject headings (MeSH), the descriptors assigned to papers indexed in PubMed. In addition , we will outline the current state of our web-based information system which will enable our users to perform literature-driven hypothesis building on their own.
Why Are Indian Children So Short? The Role of Birth Order and Son Preference.

Child stunting in India exceeds that in poorer regions like sub-Saharan Africa. Data on over 168,000 children show that, relative to Africa, India's height disadvantage increases sharply with birth order. We posit that India’s steep birth order gradient is due to favoritism toward eldest sons, which affects parents' fertility decisions and resource allocation across children. We show that, within India, the gradient is steeper for high-son-preference regions and religions. The gradient also varies with sibling gender as predicted. A back-of-the-envelope calculation suggests that India's steeper birth order gradient can explain over one-half of the India-Africa gap in average child height.
Synergistic Effect of Silver Nanoparticles with Neomycin or Gentamicin Antibiotics on Mastitis-Causing Staphylococcus aureus

Mastitis is one of the most costly diseases in dairy cows, which greatly decreases milk production. Use of antibiotics in cattle leads to antibiotic-resistance of mastitis-causing bacteria. The present study aimed to investigate synergistic effect of silver nanoparticles (AgNPs) with neomycin or gentamicin antibiotic on mastitis-causing Staphylococcus aureus.  In this study, 46 samples of milk were taken from the cows with clinical and subclinical mastitis during the august-October 2015 sampling period. In addition to biochemical tests, nuc gene amplification by PCR was used to identify strains of Staphylococcus aureus. Disk diffusion test and microdilution were performed to determine minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). Fractional Inhibitory Concentration (FIC) index was calculated to determine the interaction between a combination of AgNPs and each one of the antibiotics.  Twenty strains of Staphylococcus aureus were isolated from 46 milk samples and were confirmed by PCR. Based on disk diffusion test, 35%, 10% and 55% of the strains were respectively susceptible, moderately susceptible and resistant to gentamicin. In addition, 35%, 15% and 50% of the strains were respectively susceptible, moderately susceptible and resistant to neomycin. According to FIC index, gentamicin antibiotic and AgNPs had synergistic effects in 50% of the strains. Furthermore, neomycin antibiotic and AgNPs had synergistic effects in 45% of the strains.  It could be concluded that a combination of AgNPs with either gentamicin or neomycin showed synergistic antibacterial properties in Staphylococcus aureus isolates from mastitis. In addition, some hypotheses were proposed to explain antimicrobial mechanism of the combination.
PISCES: A Programmable, Protocol-Independent Software Switch

Hypervisors use software switches to steer packets to and from virtual machines (VMs). These switches frequently need upgrading and customization—to support new protocol headers or encapsulations for tunneling and overlays, to improve measurement and debugging features, and even to add middlebox-like functions. Software switches are typically based on a large body of code, including kernel code, and changing the switch is a formidable undertaking requiring domain mastery of network protocol design and developing, testing, and maintaining a large, complex codebase. Changing how a software switch forwards packets should not require intimate knowledge of its implementation. Instead, it should be possible to specify how packets are processed and forwarded in a high-level domain-specific language (DSL) such as P4, and compiled to run on a software switch. We present PISCES, a software switch derived from Open vSwitch (OVS), a hard-wired hypervisor switch, whose behavior is customized using P4. PISCES is not hard-wired to specific protocols; this independence makes it easy to add new features. We also show how the compiler can analyze the high-level specification to optimize forwarding performance. Our evaluation shows that PISCES performs comparably to OVS and that PISCES programs are about 40 times shorter than equivalent changes to OVS source code.
Carbapenem-Resistant Enterobacteriaceae: A Strategic Roadmap for Infection Control.

The incidence of carbapenem-resistant Enterobacteriaceae (CRE) has increased worldwide with great regional variability. Infections caused by these organisms are associated with crude mortality rates of up to 70%. The spread of CRE in healthcare settings is both an important medical problem and a major global public health threat. All countries are at risk of falling victim to the emergence of CRE; therefore, a preparedness plan is required to avoid the catastrophic natural course of this epidemic. Proactive and adequate preventive measures locally, regionally, and nationally are required to contain the spread of these bacteria. The keys to success in preventing the establishment of CRE endemicity in a region are early detection through targeted laboratory protocols and containment of spread through comprehensive infection control measures. This guideline provides a strategic roadmap for infection control measures based on the best available evidence and expert opinion, to enable preparation of a multifaceted preparedness plan to abort epidemics of CRE.  Control Hosp Epidemiol 2017;38:580-594.
Bracing following correction of idiopathic clubfoot using the Ponseti method.

The Ponseti method for the management of idiopathic clubfoot has recently experienced a rise in popularity, with several centers reporting excellent outcomes. The challenge in achieving a successful outcome with this method lies not in correcting deformity but in preventing relapse. The most common cause of relapse is failure to adhere to the prescribed postcorrective bracing regimen. Socioeconomic status, cultural factors, and physician-parent communication may influence parental compliance with bracing. New, more user-friendly braces have been introduced in the hope of improving the rate of compliance. Strategies that may be helpful in promoting adherence include educating the family at the outset about the importance of bracing, encouraging calls and visits to discuss problems, providing clear written instructions, avoiding or promptly addressing skin problems, and refraining from criticism of the family when noncompliance is evident. A strong physician-family partnership and consideration of underlying cognitive, socioeconomic, and cultural issues may lead to improved adherence to postcorrective bracing protocols and better patient outcomes.
To Join or Not to Join?: Thinking Twice about Joins before Feature Selection

Closer integration of machine learning (ML) with data processing is a booming area in both the data management industry and academia. Almost all ML toolkits assume that the input is a single table, but many datasets are not stored as single tables due to normalization. Thus, analysts often perform key-foreign key joins to obtain features from all base tables and apply a feature selection method, either explicitly or implicitly, with the aim of improving accuracy. In this work, we show that the features brought in by such joins can often be ignored without affecting ML accuracy significantly, i.e., we can "avoid joins safely." We identify the core technical issue that could cause accuracy to decrease in some cases and analyze this issue theoretically. Using simulations, we validate our analysis and measure the effects of various properties of normalized data on accuracy. We apply our analysis to design easy-to-understand decision rules to predict when it is safe to avoid joins in order to help analysts exploit this runtime-accuracy trade-off. Experiments with multiple real normalized datasets show that our rules are able to accurately predict when joins can be avoided safely, and in some cases, this led to significant reductions in the runtime of some popular feature selection methods.
The ecology, epidemiology and virulence of Enterococcus.

Enterococci are Gram-positive, catalase-negative, non-spore-forming, facultative anaerobic bacteria, which usually inhabit the alimentary tract of humans in addition to being isolated from environmental and animal sources. They are able to survive a range of stresses and hostile environments, including those of extreme temperature (5-65 degrees C), pH (4.5-10.0) and high NaCl concentration, enabling them to colonize a wide range of niches. Virulence factors of enterococci include the extracellular protein Esp and aggregation substances (Agg), both of which aid in colonization of the host. The nosocomial pathogenicity of enterococci has emerged in recent years, as well as increasing resistance to glycopeptide antibiotics. Understanding the ecology, epidemiology and virulence of Enterococcus species is important for limiting urinary tract infections, hepatobiliary sepsis, endocarditis, surgical wound infection, bacteraemia and neonatal sepsis, and also stemming the further development of antibiotic resistance.