LLukas22/scidocs huggingface dataset:
Oracle SOA Suite for Healthcare Integration Connecting Clinical and Administrative Processes with Service Oriented Architecture

Disclaimer The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle's products remains at the sole discretion of Oracle. Executive Summary One of the biggest IT challenges facing today's health care industry is the difficulty finding reliable, secure, and cost-effective ways to exchange information. Payers and providers need versatile platforms for enterprise-wide information sharing. Clinicians require accurate information to provide quality care to patients while administrators need integrated information for all facets of the business operation. Both sides of the organization must be able to access information from research and development systems, practice management systems, claims systems, financial systems, and many others. Externally, these organizations must share claims data, patient records, pharmaceutical data, lab reports, and diagnostic information among third party entities—all while complying with emerging standards for formatting, processing, and storing electronic health records (EHR). Service-oriented architecture (SOA) enables developers to integrate many types of software applications, databases and computing platforms within a particular health network as well as with community, state, and national health information exchanges. The Oracle SOA Suite for healthcare integration is designed to provide healthcare organizations with comprehensive integration capabilities within a unified middleware platform, as well as with healthcare libraries and templates for streamlining healthcare IT projects. Through the use of Oracle SOA Suite and the Oracle Healthcare Adapter, Oracle helps these organizations to reliably exchange information while adhering to important industry standards and initiatives. As part of the Oracle Fusion Middleware family, these technologies enable healthcare organizations to lower operating costs and accelerate time-to-market by delivering a consistent user interface, security architecture, management console, and monitoring environment. Oracle helps health care organizations to improve information sharing processes—both internally and with business partners—by enabling simple, secure and scalable methods for sending authenticated and encrypted information directly to trusted recipients. Oracle's proven SOA tools reduce costs and minimize complexity by utilizing a secure, flexible, and standards-based middleware platform. Based on popular industry standards, Oracle SOA 2 Oracle SOA Suite for Healthcare Integration Suite for healthcare integration reduces the need for specialized skills and enforces an enterprise-wide view of critical healthcare data. Health plans, health care …
Spanning Tree Methods for Discriminative Training of Dependency Parsers

Untyped dependency parsing can be viewed as the problem of finding maximum spanning trees (MSTs) in directed graphs. Using this representation, the Eisner (1996) parsing algorithm is sufficient for searching the space of projective trees. More importantly, the representation is extended naturally to non-projective parsing using Chu-Liu-Edmonds (Chu and Liu, 1965; Edmonds, 1967) MST algorithm. These efficient parse search methods support large-margin discriminative training methods for learning dependency parsers. We evaluate these methods experimentally on the English and Czech treebanks. Comments University of Pennsylvania Department of Computer and Information Science Technical Report No. MSCIS-06-11. This technical report is available at ScholarlyCommons: http://repository.upenn.edu/cis_reports/55 Spanning Tree Methods for Discriminative Training of Dependency Parsers Ryan McDonald Koby Crammer Fernando Pereira Department of Computer and Information Science University of Pennsylvania Philadelphia, PA, 19107 {ryantm,crammer,pereira}@cis.upenn.edu
Autosomal dominant PIK3R1 mutations cause SHORT syndrome.

PIK3R1 mutations cause syndromic insulin resistance with lipoatrophy. Thauvin-Robinet et al. (2013) The American Journal of Human Genetics 93: 141-149 SHORT syndrome with partial lipodystrophy due to impaired phosphatidylinositol 3 kinase signalling. Chudasama et al. (2013) The American Journal of Human Genetics 93: 150-157 Mutations in PIK3R1 cause SHORT syndrome. Dyment et al. (2013) The American Journal of Human Genetics 93: 158-166.
The High-Dimensional Geometry of Binary Neural Networks

Recent research has shown that one can train a neural network with binary weights and activations at train time by augmenting the weights with a high-precision continuous latent variable that accumulates small changes from stochastic gradient descent. However, there is a dearth of theoretical analysis to explain why we can effectively capture the features in our data with binary weights and activations. Our main result is that the neural networks with binary weights and activations trained using the method of Courbariaux, Hubara et al. (2016) work because of the highdimensional geometry of binary vectors. In particular, the ideal continuous vectors that extract out features in the intermediate representations of these BNNs are wellapproximated by binary vectors in the sense that dot products are approximately preserved. Compared to previous research that demonstrated the viability of such BNNs, our work explains why these BNNs work in terms of the HD geometry. Our theory serves as a foundation for understanding not only BNNs but a variety of methods that seek to compress traditional neural networks. Furthermore, a better understanding of multilayer binary neural networks serves as a starting point for generalizing BNNs to other neural network architectures such as recurrent neural networks.
Challenges and trends in Ambient Assisted Living and intelligent tools for disabled and elderly people

In this review article, we present some challenges and opportunities in Ambient Assisted Living (AAL) for disabled and elderly people addressing various state of the art and recent approaches particularly in artificial intelligence, biomedical engineering, and body sensor networking.
Definition of a online to offline (O2O) system to support the individualized management and treatment strategies for overall asthma control

Asthma is one of the most prevalent non-communicable diseases worldwide. It creates substantial health and economic burden to patients, and affects their families. This paper presents an online to offline (O2O) system to support the treatment and management of asthma, based on individualized strategies for the overall asthma control. It uses Information and Communication Technologies (ICTs) to create an asthma care system that provides the online virtual service and offline real service to support patients and medicals in the improvement of the treatment outcome.
Identification of Klebsiella capsule synthesis loci from whole genome data

Klebsiella pneumoniae is a growing cause of healthcare-associated infections for which multi-drug resistance is a concern. Its polysaccharide capsule is a major virulence determinant and epidemiological marker. However, little is known about capsule epidemiology since serological typing is not widely accessible and many isolates are serologically non-typeable. Molecular typing techniques provide useful insights, but existing methods fail to take full advantage of the information in whole genome sequences. We investigated the diversity of the capsule synthesis loci (K-loci) among 2503 K. pneumoniae genomes. We incorporated analyses of full-length K-locus nucleotide sequences and also clustered protein-encoding sequences to identify, annotate and compare K-locus structures. We propose a standardized nomenclature for K-loci and present a curated reference database. A total of 134 distinct K-loci were identified, including 31 novel types. Comparative analyses indicated 508 unique protein-encoding gene clusters that appear to reassort via homologous recombination. Extensive intra- and inter-locus nucleotide diversity was detected among the wzi and wzc genes, indicating that current molecular typing schemes based on these genes are inadequate. As a solution, we introduce Kaptive, a novel software tool that automates the process of identifying K-loci based on full locus information extracted from whole genome sequences (https://github.com/katholt/Kaptive). This work highlights the extensive diversity of Klebsiella K-loci and the proteins that they encode. The nomenclature, reference database and novel typing method presented here will become essential resources for genomic surveillance and epidemiological investigations of this pathogen.
The Tiling of the Hyperbolic 4D Space by the 120-cell is Combinatoric

The splitting method was defined by the author in [Margenstern 2002a, Margenstern 2002d]. It is at the basis of the notion of combinatoric tilings. As a consequence of this notion, there is a recurrence sequence which allows us to compute the number of tiles which are at a fixed distance from a given tile. A polynomial is attached to the sequence as well as a language which can be used for implementing cellular automata on the tiling. The goal of this paper is to prove that the tiling of hyperbolic 4D space is combinatoric. We give here the corresponding polynomial and, as the first consequence, the language of the splitting is not regular, as it is the case in the tiling of hyperbolic 3D space by rectangular dodecahedra which is also combinatoric.
Color Constancy, Intrinsic Images, and Shape Estimation

We present SIRFS (shape, illumination, and reflectance from shading), the first unified model for recovering shape, chromatic illumination, and reflectance from a single image. Our model is an extension of our previous work [1], which addressed the achromatic version of this problem. Dealing with color requires a modified problem formulation, novel priors on reflectance and illumination, and a new optimization scheme for dealing with the resulting inference problem. Our approach outperforms all previously published algorithms for intrinsic image decomposition and shape-from-shading on the MIT intrinsic images dataset [1, 2] and on our own “naturally” illuminated version of that dataset.
Evaluation of torsional oscillations in paper machine sections

Torsional oscillations greatly affect performance and determine the bandwidth (BW) and damping of speed loops. Backlash due to gear reducers can also contribute to the triggering of oscillations, especially when the drive runs at very low load torque. This paper presents a detailed evaluation of these effects in typical electromechanical drive trains applied to paper machine sections. The cases evaluated consider torsional oscillations in two-mass and three-mass systems, and the effect of shaft diameter and length on the resonant frequencies of three typical paper machine sections. Time-domain response plots are evaluated to show the effect of speed response overshoot, reducer backlash, and step or ramp speed commands. Based on these results, mechanical design guidelines are given for the most significant drive train components in order to minimize torsional oscillations of the speed-controlled drive system.
What determines health-related quality of life among people living with HIV: an updated review of the literature

BACKGROUND
As infection with the Human Immunodeficiency Virus (HIV) has evolved to a chronic disease, perceived health-related quality of life (HRQoL) is becoming a prominent and important patient-reported outcome measure in HIV care. Literature discusses different factors influencing HRQoL in this population, however, currently no consensus exists about the main determinants. In this review a clear, up-to-date overview of the determinants influencing HRQOL among people living with HIV is provided.


METHODS
All studies published before July 2013 that identified determinants of HRQoL among people living with HIV in high-income countries, were considered in this narrative review. PubMed, Web of Science and The Cochrane Library were consulted using the keywords 'determinants', 'quality of life', 'HIV' and 'AIDS'. To be included, studies should have reported overall health and/or physical/mental health scores on a validated instrument and performed multivariable regression analyses to identify determinants that independently influence perceived HRQoL.


RESULTS
In total, 49 studies were included for further analysis and they used a variety of HRQoL instruments: Medical Outcomes Study Short Form-36 or variants, Medical Outcomes Study-HIV, HIV Cost and Services Utilization Study measure, Multidimensional Quality of Life Questionnaire, HIV targeted quality of life instrument, Functional Assessment of Human Immunodeficiency Virus Infection, HIV Overview of Problems Evaluation System, EuroQol, Fanning Quality of Life scale, Health Index and PROQOL-HIV. In this review, the discussed determinants were thematically divided into socio-demographic, clinical, psychological and behavioural factors. Employment, immunological status, presence of symptoms, depression, social support and adherence to antiretroviral therapy were most frequently and consistently reported to be associated with HRQoL among people living with HIV.


CONCLUSIONS
HRQoL among people living with HIV is influenced by several determinants. These determinants independently, but simultaneously impact perceived HRQoL. Most HRQoL instruments do not capture all key determinants. We recommend that the choice for an instrument should depend on the purpose of the HRQoL assessment.
Intermediation and electronic markets: aggregation and pricing in Internet commerce

The Internet continues to grow as a medium to support commerce. Economic analysis of Internet commerce is still in a nascent stage while Internet technology and use has rapidly advanced. The result is an Internet marketplace brimming with entrepreneurs and major corporations experimenting with business strategies and technology advances even though the economics of Internet commerce is not well understood. This thesis responds to this need by exploring how the Internet reduces the market friction common in physical commerce. The intermediaries who help reduce market friction in physical markets may be eliminated, when suppliers and consumers increasingly rely on the Internet as a transaction medium. An intermediary in any market may reduce transaction costs by performing four roles: aggregation, pricing, search, and trust. The intermediary roles of aggregation and pricing may provide little or no value as the Internet becomes the medium for commerce because the technology, not the intermediary, reduces transaction costs. This thesis examines the possible elimination of aggregation and pricing intermediaries in Internet commerce. It does so by extending the theory of the economics of intermediation and electronic markets; developing a methodology for the analysis of Internet price competition; analyzing exploratory empirical data of the book, compact disc, and software markets to test a subset of this theory; and exploring the public policy implications of Internet price discrimination. The approach is interdisciplinary because this thesis integrates the technology, policy, and economics that underpin the role of aggregation and pricing intermediaries in Internet commerce. The thesis shows that Internet commerce may not reduce market friction because prices are higher when consumers buy homogeneous products on the Internet, and price dispersion for homogenous products among Internet retailers is greater than the price dispersion among physical retailers. Internet retailers—even those selling homogenous goods—can develop pricing strategies to differentiate themselves from their competitors and to price discriminate. The ability for the Internet to become a medium for price discrimination is an area that requires the attention of public policy makers. While self-regulation of Internet price discrimination may be the most appropriate policy, monitoring by the United States government through the Federal Trade Commission and international organizations such as the World Trade Organization helps establish a trusted transaction environment for future Internet commerce growth. Thesis Committee: Lee W. McKnight Lecturer, Technology and Policy Program Erik Brynjolfsson Associate Professor, MIT Sloan School of Management David D. Clark Senior Research Scientist, Laboratory for Computer Science
Fuzzy PI Controller for BLDC motors Considering Variable Sampling Effect

Variable sampling is important issue for the motor drives with low resolution position sensors. We present the fuzzy PI (proportional and integral) controller for brushless dc (BLDC) motors considering variable sampling effect in this paper, and this controller uses three fuzzy logics and three PI controllers to achieve variable sampling control. Therefore, the simple structure of the fuzzy PI controller for BLDC motors considering variable sampling effect is not only implemented and understood easily, but also robust in variable speed control system.
Grid-connected Photovoltaic System with Maximum Power Point Tracking using Self-Organizing Fuzzy Logic Controller

This paper presents the design of a controller for the maximum power point tracking of a grid-connected photovoltaic energy conversion system. A boost converter is used in the system to deliver the output from the solar array to DC-AC inverter, and feed the power into the AC grid. A self-organizing fuzzy logic controller is introduced for the tracking algorithm. The duty ratio for the operation of the boost converter is optimally adjusted in such a way that the maximum power point, which normally varies according to the environment, can be achieved. We demonstrate via the simulation results that our proposed technique outperforms over the conventional fuzzy logic controller in terms of tracking speed and transient response. Furthermore, the algorithm implementation can be done using a look-up table, hence a high- performance, cost-effective real-time maximum power point tracking can be simply realized.
Effect of Fly Ash and Farm Yard Manure on Soil Properties and Yield of Rice Grown on an Inceptisol

A field experiment was conducted in a fine loamy mixed hyperthermic Typic Haplustept soil during rabi, 2004-05 to study the effect of fly ash and FYM on physico-chemical properties and available nutrient status. The test crop was rice var. Tella Hamsa. The grain and straw yield of rice was significantly increased with fly ash, FYM and their interactions. The highest grain (5.84 t ha-1) and straw yield (7.87 t ha-1) were recorded by combined application of fly ash @ 10 t ha-1 and FYM @ 10 t ha-1 which was on par with fly ash @ 15 t ha-1 along with FYM @10 t ha1. Among the different combinations, application of fly ash @ 15 t ha-1 + FYM @ 10 t ha-1 (FA15 FYM10) recorded the highest available N (224.6 kg ha -1), P (24.6 kg ha-1), K (366.7 kg ha-1), S (8.80 mg kg-1), Fe (10.62 mg kg-1) and Zn (0.95 mg kg-1) contents after harvest of rice crop, which were on par with FA10 FYM10. The available Mn content was highest in FA10 FYM10 (6.69 mg kg-1). The available Cu content was not significantly influenced by fly ash levels; however, it was significantly higher in FYM treated plots. Application FA10 FYM10 has resulted in the build up of available nutrients (N-5.8 %), (P-64.5 %), (K – 103.3 %), (S – 2.8 %), (Fe – 22.2 %), (Mn – 23.3%), (Cu – 156.9 %) in post harvest soils except Zn (-10.5%) when compared to their initial status.
Sprouty-2 Controls c-Met Expression and Metastatic Potential of Colon Cancer Cells: Sprouty/c-Met Upregulation in Human Colonic Adenocarcinomas

Sprouty negatively regulates receptor tyrosine kinase signals by inhibiting Ras/extracellular signal-regulated kinase (ERK) pathways. Sprouty is downregulated in breast, prostate and liver cancers and appears to function as a tumor suppressor. The role of sprouty in colonic neoplasia, however, has not been investigated. Sprouty-2 protein and mRNA transcripts were significantly upregulated in human colonic adenocarcinomas. Strikingly, the c-Met receptor was also upregulated in tumors with increased sprouty-2. To delineate a potential causal relationship between sprouty-2 and c-Met, K-ras mutant HCT-116 colon cancer cells were transduced with purified TAT-sprouty-2 protein or stably transfected with full-length human sprouty-2 gene. Sprouty-2 upregulation significantly increased cell proliferation by accelerating cell cycle transition. Sprouty-2 transfectants showed strong upregulation of c-Met protein and mRNA transcripts and hepatocyte growth factor-stimulated ERK and Akt phosphorylation and enhanced cell migration and invasion. In contrast, knockdown of c-Met by small interfering RNA (siRNA) significantly decreased cell proliferation, migration and invasion in sprouty-2 transfectants. Further, knockdown of sprouty-2 by siRNA in parental HT-29 and LS-174T colon cancer cells also decreased cell invasion. Sprouty-2 transfectants formed significantly larger tumor xenografts and showed increased proliferation and angiogenesis and suppressed apoptosis. Sprouty-2 tumors metastasized to the liver from cecal orthotopic implants, suggesting that sprouty-2 might also enhance metastatic signals. Thus, in colon cancer sprouty functions as an oncogene and its effects are mediated in part by c-Met upregulation.
An Architecture and a Domain Ontology for Personalized Multi-agent e-Learning Systems

Semantic web and intelligent agents are main technologies to implement personalization for e-learning systems. Ontology is the key concept in semantic web, and it plays an important role in knowledge representation, sharing of didactic material and content personalization. Furthermore, ontologies are machine-readable. Therefore they are faster and more convenient to query and retrieval educational material with the Semantic Web services. Intelligent agents can provide the learners with personal assistants to carry out learning activities according to their learning styles and their knowledge levels. In this paper, we present the architecture of a multi-agent e-learning system that supports pre-defining students' learning styles and re-estimating them during the course for a better personalization. We also present a domain ontology that is suitable for adaptive e-learning environments. The ontology describes learning material that composes a course as well as describes learners and their learning styles.
Multilingual document recognition research and its application in China

This paper demonstrates the research work on multilingual document recognition technology and its application in China, which is useful for building multilingual digital library. The multilingual OCR (optical character recognition) key technologies and general system framework are summarized based on the previous research work for Chinese, Japanese, Korean, English, and recent research advancement for Tibetan, Uighur, Kazakh, Kirghiz, Arabic, and Mongolian. The key technologies include statistical character recognition, structural analysis for similar character discrimination, character segmentation, script identification, post-processing. Application of multilingual document recognition system in digital library and Web site content construction will benefit people using various languages to retrieve knowledge