LLukas22/scidocs huggingface dataset:
RITZ-5: randomized intravenous TeZosentan (an endothelin-A/B antagonist) for the treatment of pulmonary edema: a prospective, multicenter, double-blind, placebo-controlled study.

OBJECTIVES
The objective of this study was to evaluate the addition of intravenous (IV) tezosentan to standard therapy for patients with pulmonary edema.


BACKGROUND
Tezosentan is an IV nonselective endothelin (ET)-1 antagonist that yields favorable hemodynamic effects in patients with acute congestive heart failure (CHF).


METHODS
Pulmonary edema was defined as acute CHF leading to respiratory failure, as evidenced by an oxygen saturation (SO(2)) <90% by pulse oxymeter despite oxygen treatment. All patients received oxygen 8 l/min through a face mask, 3 mg of IV morphine, 80 mg of furosemide, and 1 to 3 mg/h continuous drip isosorbide-dinitrate according to their blood pressure level and were randomized to receive a placebo or tezosentan (50 or 100 mg/h) for up to 24 h.


RESULTS
Eighty-four patients were randomized. The primary end point, the change in SO(2) from baseline to 1 h, was 9.1 +/- 6.3% in the placebo arm versus 7.6 +/- 10% in the tezosentan group (p = NS). The incidence of death, recurrent pulmonary edema, mechanical ventilation, and myocardial infarction during the first 24 h of treatment was 19% in both groups. Reduced baseline SO(2), lower echocardiographic ejection fraction, high baseline mean arterial blood pressure (MAP), and inappropriate vasodilation (MAP reduction at 30 min of <5% or >30%) correlated with worse outcomes. A post-hoc analysis revealed that the outcome of patients who received only 50 mg/h tezosentan was better than patients in the placebo group whereas patients receiving 100 mg/h had the worst outcomes.


CONCLUSIONS
In the present study, tezosentan (an ET-1 antagonist) did not affect the outcome of pulmonary edema, possibly because of the high dose used.
Knowledge Management Process : a theoretical-conceptual research

Resumo: A gestão do Conhecimento (GC) é um tema que vem despertando o interesse de muitos pesquisadores nas últimas décadas, sendo grande parte das contribuições orientadas por etapas, denominadas processo de GC. Por se tratar de um tema abrangente, as publicações sobre o processo de GC apresentam contribuições multidisciplinares e, desta forma, esta pesquisa tem por objetivo conceituar este processo, analisando as principais abordagens que orientam o estudo de cada etapa, e, também, levantar as principais publicações que tratam do tema, classificando‐as quanto à sua área de contribuição. Para alcançar estes objetivos, este artigo é orientado por uma pesquisa teórico‐conceitual, na qual foram estudados 71 artigos. Os resultados desta pesquisa apontam que o processo de GC é constituído de quatro etapas: aquisição, armazenamento, distribuição e utilização do conhecimento. Na fase de aquisição, as temáticas estudadas são aprendizagem organizacional, absorção de conhecimento, processo criativo e transformação do conhecimento. Na fase de armazenamento, as contribuições tratam do indivíduo, organização e tecnologia da informação, enquanto na fase de distribuição os estudos concentram‐se nas temáticas contato social, comunidade de prática e compartilhamento via tecnologia de informação. E, por fim, na fase de utilização, são abordados os temas forma de utilização, capacidade dinâmica e recuperação e transformação do conhecimento. Palavras-chave: Processo de gestão do conhecimento; Aquisição de conhecimento; Armazenamento de conhecimento; Distribuição de conhecimento; Utilização de conhecimento; Pesquisa teórico‐conceitual. Abstract: Knowledge Management (KM) is a subject that has aroused the interest of many researchers in the last decade, being great part of contributions driven by steps, named KM process. Because it is an embracing theme, publications about KM process have multidisciplinary contributions and, thus, this research aims to conceptualize this process, analyzing the main approach that guides the study of each stage, and also, to raise the main publications on the subject, classifying them as to their contribution area. To reach these goals, this article is oriented by a theoretical-conceptual research, in which 71 articles were studied. The results indicate that the KM process consists of four stages: acquisition, storage, distribution, and use of knowledge. In the acquisition phase, the studied themes are organizational learning, knowledge inception, creative process and knowledge transformation. In the storage phase, the contributions deal with a person, an organization and information technology, while in the distribution phase the studies concentrate in social contact themes, practice community and sharing via information technology. And, finally, in the use phase, we address the form of use, dynamic capacity and retrieval and knowledge transformation.
Drought disturbance from climate change: response of United States forests.

Predicted changes in climate have raised concerns about potential impacts on terrestrial forest ecosystem productivity, biogeochemical cycling, and the availability of water resources. This review summarizes characteristics of drought typical to the major forest regions of the United States, future drought projections, and important features of plant and forest community response to drought. Research needs and strategies for coping with future drought are also discussed. Notwithstanding uncertainties surrounding the magnitude and direction of future climate change, and the net impact on soil water availability to forests, a number of conclusions can be made regarding the sensitivity of forests to future drought. The primary response will be a reduction in net primary production and stand water use, which are driven by reductions in stomatal conductance. Mortality of small stature plants (i.e. seedlings and saplings) is a likely consequence of severe drought. In comparison, deep rooting and substantial reserves of carbohydrates and nutrients make mature trees less susceptible to water limitations caused by severe or prolonged drought. However, severe or prolonged drought may render even mature trees more susceptible to insects or disease. Drought-induced reductions in decomposition rates may cause a buildup of organic material on the forest floor, with ramifications for fire regimes and nutrient cycling. Although early model predictions of climate change impacts suggested extensive forest dieback and species migration, more recent analyses suggest that catastrophic dieback will be a local phenomenon, and changes in forest composition will be a relatively gradual process. Better climate predictions at regional scales, with a higher temporal resolution (months to days), coupled with carefully designed, field-based experiments that incorporate multiple driving variables (e.g. temperature and CO2), will advance our ability to predict the response of different forest regions to climate change.
Has My Algorithm Succeeded? An Evaluator for Human Pose Estimators

Example classifications (test set) [And09] Andriluka et al. Pictorial structures revisited: People detection and articulated pose estimation. In CVPR, 2009 [Eic09] Eichner et al. Articulated Human Pose Estimation and Search in (Almost) Unconstrained Still Images. In IJCV, 2012 [Sap10] Sapp et al. Cascaded models for articulated pose estimation. In ECCV, 2010 [Yan11] Yang and Ramanan. Articulated pose estimation with flexible mixturesof-parts. In CVPR, 2011. References Human Pose Estimation (HPE) Algorithm Input
Appearance-and-Relation Networks for Video Classification

Spatiotemporal feature learning in videos is a fundamental problem in computer vision. This paper presents a new architecture, termed as Appearance-and-Relation Network (ARTNet), to learn video representation in an end-to-end manner. ARTNets are constructed by stacking multiple generic building blocks, called as SMART, whose goal is to simultaneously model appearance and relation from RGB input in a separate and explicit manner. Specifically, SMART blocks decouple the spatiotemporal learning module into an appearance branch for spatial modeling and a relation branch for temporal modeling. The appearance branch is implemented based on the linear combination of pixels or filter responses in each frame, while the relation branch is designed based on the multiplicative interactions between pixels or filter responses across multiple frames. We perform experiments on three action recognition benchmarks: Kinetics, UCF101, and HMDB51, demonstrating that SMART blocks obtain an evident improvement over 3D convolutions for spatiotemporal feature learning. Under the same training setting, ARTNets achieve superior performance on these three datasets to the existing state-of-the-art methods.1
Deep learning in remote sensing: a review

This is the pre-acceptance version, to read the final version please go to IEEE Geoscience and Remote Sensing Magazine on IEEE XPlore. Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields. Shall we embrace deep learning as the key to all? Or, should we resist a “black-box” solution? There are controversial opinions in the remote sensing community. In this article, we analyze the challenges of using deep learning for remote sensing data analysis, review the recent advances, and provide resources to make deep learning in remote sensing ridiculously simple to start with. More importantly, we advocate remote sensing scientists to bring their expertise into deep learning, and use it as an implicit general model to tackle unprecedented large-scale influential challenges, such as climate change and urbanization. X. Zhu and L. Mou are with the Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany and with Signal Processing in Earth Observation (SiPEO), Technical University of Munich (TUM), Germany, E-mails: xiao.zhu@dlr.de; lichao.mou@dlr.de. D. Tuia was with the Department of Geography, University of Zurich, Switzerland. He is now with the Laboratory of GeoInformation Science and Remote Sensing, Wageningen University of Research, the Netherlands. E-mail: devis.tuia@wur.nl. G.-S Xia and L. Zhang are with the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University. E-mail:guisong.xia@whu.edu.cn; zlp62@whu.edu.cn. F. Xu is with the Key Laboratory for Information Science of Electromagnetic Waves (MoE), Fudan Univeristy. E-mail: fengxu@fudan.edu.cn. F. Fraundorfer is with the Institute of Computer Graphics and Vision, TU Graz, Austria and with the Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany. E-mail: fraundorfer@icg.tugraz.at. The work of X. Zhu and L. Mou are supported by the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (grant agreement No [ERC-2016-StG-714087], Acronym: So2Sat), Helmholtz Association under the framework of the Young Investigators Group “SiPEO” (VH-NG-1018, www.sipeo.bgu.tum.de) and China Scholarship Council. The work of D. Tuia is supported by the Swiss National Science Foundation (SNSF) under the project NO. PP0P2 150593. The work of G.-S. Xia and L. Zhang are supported by the National Natural Science Foundation of China (NSFC) projects with grant No. 41501462 and No. 41431175. The work of F. Xu are supported by the National Natural Science Foundation of China (NSFC) projects with grant No. 61571134. October 12, 2017 DRAFT ar X iv :1 71 0. 03 95 9v 1 [ cs .C V ] 1 1 O ct 2 01 7 IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, IN PRESS. 2
Generalized 2D principal component analysis for face image representation and recognition

In the tasks of image representation, recognition and retrieval, a 2D image is usually transformed into a 1D long vector and modelled as a point in a high-dimensional vector space. This vector-space model brings up much convenience and many advantages. However, it also leads to some problems such as the Curse of Dimensionality dilemma and Small Sample Size problem, and thus produces us a series of challenges, for example, how to deal with the problem of numerical instability in image recognition, how to improve the accuracy and meantime to lower down the computational complexity and storage requirement in image retrieval, and how to enhance the image quality and meanwhile to reduce the transmission time in image transmission, etc. In this paper, these problems are solved, to some extent, by the proposed Generalized 2D Principal Component Analysis (G2DPCA). G2DPCA overcomes the limitations of the recently proposed 2DPCA (Yang et al., 2004) from the following aspects: (1) the essence of 2DPCA is clarified and the theoretical proof why 2DPCA is better than Principal Component Analysis (PCA) is given; (2) 2DPCA often needs much more coefficients than PCA in representing an image. In this work, a Bilateral-projection-based 2DPCA (B2DPCA) is proposed to remedy this drawback; (3) a Kernel-based 2DPCA (K2DPCA) scheme is developed and the relationship between K2DPCA and KPCA (Scholkopf et al., 1998) is explored. Experimental results in face image representation and recognition show the excellent performance of G2DPCA.
Reverse ontology matching

Ontology Matching aims to find the semantic correspondences between ontologies that belong to a single domain but that have been developed separately. However, there are still some problem areas to be solved, because experts are still needed to supervise the matching processes and an efficient way to reuse the alignments has not yet been found. We propose a novel technique named Reverse Ontology Matching, which aims to find the matching functions that were used in the original process. The use of these functions is very useful for aspects such as modeling behavior from experts, performing matching-by-example, reverse engineering existing ontology matching tools or compressing ontology alignment repositories. Moreover, the results obtained from a widely used benchmark dataset provide evidence of the effectiveness of this approach.
PowerCore: a program applying the advanced M strategy with a heuristic search for establishing core sets

MOTIVATION
Core sets are necessary to ensure that access to useful alleles or characteristics retained in genebanks is guaranteed. We have successfully developed a computational tool named 'PowerCore' that aims to support the development of core sets by reducing the redundancy of useful alleles and thus enhancing their richness.


RESULTS
The program, using a new approach completely different from any other previous methodologies, selects entries of core sets by the advanced M (maximization) strategy implemented through a modified heuristic algorithm. The developed core set has been validated to retain all characteristics for qualitative traits and all classes for quantitative ones. PowerCore effectively selected the accessions with higher diversity representing the entire coverage of variables and gave a 100% reproducible list of entries whenever repeated.


AVAILABILITY
PowerCore software uses the .NET Framework Version 1.1 environment which is freely available for the MS Windows platform. The files can be downloaded from http://genebank.rda.go.kr/powercore/. The distribution of the package includes executable programs, sample data and a user manual.
Efficacy and Safety of Zhuanggu Joint Capsules in Combination with Celecoxib in Knee Osteoarthritis: A Multi-center, Randomized, Double-blind, Double-dummy, and Parallel Controlled Trial

BACKGROUND
Knee osteoarthritis (KOA) is a chronic joint disease that manifests as knee pain as well as different degrees of lower limb swelling, stiffness, and movement disorders. The therapeutic goal is to alleviate or eliminate pain, correct deformities, improve or restore joint functions, and improve the quality of life. This study aimed to evaluate the efficacy and safety of Zhuanggu joint capsules combined with celecoxib and the benefit of treatment with Zhuanggu alone for KOA.


METHODS
This multi-center, randomized, double-blind, double-dummy, parallel controlled trial, started from December 2011 to May 2014, was carried out in 6 cities, including Beijing, Shanghai, Chongqing, Changchun, Chengdu, and Nanjing. A total of 432 patients with KOA were divided into three groups (144 cases in each group). The groups were treated, respectively, with Zhuanggu joint capsules combined with celecoxib capsule simulants, Zhuanggu joint capsules combined with celecoxib capsules, and celecoxib capsules combined with Zhuanggu joint capsule simulants for 4 weeks consecutively. The improvement of Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index and the decreased rates in each dimension of WOMAC were evaluated before and after the treatment. Intergroup and intragroup comparisons of quantitative indices were performed. Statistically significant differences were evaluated with pairwise comparisons using Chi-square test (or Fisher's exact test) and an inspection level of α = 0.0167.


RESULTS
Four weeks after treatment, the total efficacies of Zhuanggu group, combination group, and celecoxib group were 65%, 80%, and 64%, respectively, with statistically significant differences among the three groups (P = 0.005). Intergroup pairwise comparisons showed that the total efficacy of the combination group was significantly higher than that of the Zhuanggu (P = 0.005) and celecoxib (P = 0.003) groups. The difference between the latter two groups was not statistically significant (P > 0.0167). Four weeks after discontinuation, the efficacies of the three groups were 78%, 95%, and 65%, respectively, with statistically significant differences (P < 0.0001). Intergroup pairwise comparisons revealed that the efficacy of the combination group was significantly better than that of the Zhuanggu and the celecoxib groups (P < 0.0001). The difference between the latter two groups was not statistically significant (P > 0.0167). The incidences of adverse events in Zhuanggu group, combination group, and celecoxib group were 8.5%, 8.5%, and 11.1%, respectively, with insignificant differences (P > 0.05).


CONCLUSIONS
Zhuanggu joint capsules alone or combined with celecoxib showed clinical efficacy in the treatment of KOA. The safety of Zhuanggu joint capsules alone or combined with celecoxib was acceptable.


TRIAL REGISTRATION
Chinese Clinical Trial Registry, ChiCTR-IPR-15007267; http://www.medresman.org/uc/project/projectedit.aspx?proj=1364.
Square Root SAM: Simultaneous Localization and Mapping via Square Root Information Smoothing

Solving the SLAM (simultaneous localization and mapping) problem is one way to enable a robot to explore, map, and navigate in a previously unknown environment. Smoothing approaches have been investigated as a viable alternative to extended Kalman filter (EKF)based solutions to the problem. In particular, approaches have been looked at that factorize either the associated information matrix or the measurement Jacobian into square root form. Such techniques have several significant advantages over the EKF: they are faster yet exact; they can be used in either batch or incremental mode; are better equipped to deal with non-linear process and measurement models; and yield the entire robot trajectory, at lower cost for a large class of SLAM problems. In addition, in an indirect but dramatic way, column ordering heuristics automaticallyexploit the locality inherent in the geographic nature of the SLAM problem. This paper presents the theory underlying these methods, along with an interpretation of factorization in terms of the graphical model associated with the SLAM problem. Both simulation results and actual SLAM experiments in large-scale environments are presented that underscore the potential of these methods as an alternative to EKF-based approaches. KEY WORDS—mobile robots, SLAM, graphical models
An efficient closed-form approach to the design of linear-phase FIR digital filters with variable-bandwidth characteristics

This paper deals with the design of variable-bandwidth linear-phase FIR digital filters. Such filters are implemented as a linear combination of fixed-coefficient linear-phase filters and the variable bandwidth characteristics are provided by a tuning parameter embedded in the filter structure. These filters are designed in a least-square sense by formulating an error function reflecting the difference between the desired variable bandwidth filter and the practical filter represented as a linear combination of fixed-coefficient filters in a quadratic form. The filter coefficients are obtained by solving a system of linear equations comprising of a block-symmetric positive-definite matrix in which each block is a Toeplitz-plus-Hankel matrix. Consequently, a significant reduction in computational complexity can be achieved in obtaining the entries of this matrix. Moreover, closed-form expressions are provided for both the block-symmetric matrix as well as the vector involved in the system of linear equations. r 2005 Elsevier B.V. All rights reserved.
Nd:YAG Laser Treatment of Keloids and Hypertrophic Scars

Pathological cutaneous scars such as keloids and hypertrophic scars (HSs) are characterized by a diffuse redness that is caused by the overgrowth of capillary vessels due to chronic inflammation. Our group has been using long-pulsed, 1064-nm Nd:YAG laser in noncontact mode with low fluence and a submillisecond pulse duration to treat keloids and hypertrophic scars since 2006 with satisfactory results. The present study examined the efficacy of this approach in 22 Japanese patients with keloids (n = 16) or hypertrophic scars (n = 6) who were treated every 3 to 4 weeks. Treatment settings were as follows: 5 mm spot size diameter; 14 J/cm(2) energy density; 300 μs exposure time per pulse; and 10 Hz repetition rate. The responses of the pathological scars to the treatment were assessed by measuring their erythema, hypertrophy, hardness, itching, and pain or tenderness. Moreover, skin samples from 3 volunteer patients were subjected to histological evaluation and 5 patients underwent thermography during therapy. The average total scar assessment score dropped from 9.86 to 6.34. Hematoxylin and eosin staining and Elastica Masson-Goldner staining showed that laser treatment structurally changed the tissue collagen. This influence reached a depth of 0.5 to 1 mm. Electron microscopy revealed plasma protein leakage, proteoglycan particles, and a change in the collagen fiber fascicles. Further analyses revealed that noncontact mode Nd:YAG laser treatment is highly effective for keloids and hypertrophic scars regardless of patient age, the origin and multiplicity of scarring, the location of the scar(s), or the tension on the scar.