Acta Geophysica最新文献_第3页

Advancing Symptom Science Through Symptom Cluster Research: Expert Panel Proceedings and Recommendations. 通过症状群研究推进症状科学：专家组会议记录和建议。

IF 9.9 4区地球科学

Acta Geophysica Pub Date : 2017-01-24 Print Date: 2017-04-01 DOI: 10.1093/jnci/djw253

Christine Miaskowski, Andrea Barsevick, Ann Berger, Rocco Casagrande, Patricia A Grady, Paul Jacobsen, Jean Kutner, Donald Patrick, Lani Zimmerman, Canhua Xiao, Martha Matocha, Sue Marden

{"title":"Advancing Symptom Science Through Symptom Cluster Research: Expert Panel Proceedings and Recommendations.","authors":"Christine Miaskowski, Andrea Barsevick, Ann Berger, Rocco Casagrande, Patricia A Grady, Paul Jacobsen, Jean Kutner, Donald Patrick, Lani Zimmerman, Canhua Xiao, Martha Matocha, Sue Marden","doi":"10.1093/jnci/djw253","DOIUrl":"10.1093/jnci/djw253","url":null,"abstract":"<p><p>An overview of proceedings, findings, and recommendations from the workshop on \"Advancing Symptom Science Through Symptom Cluster Research\" sponsored by the National Institute of Nursing Research (NINR) and the Office of Rare Diseases Research, National Center for Advancing Translational Sciences, is presented. This workshop engaged an expert panel in an evidenced-based discussion regarding the state of the science of symptom clusters in chronic conditions including cancer and other rare diseases. An interdisciplinary working group from the extramural research community representing nursing, medicine, oncology, psychology, and bioinformatics was convened at the National Institutes of Health. Based on expertise, members were divided into teams to address key areas: defining characteristics of symptom clusters, priority symptom clusters and underlying mechanisms, measurement issues, targeted interventions, and new analytic strategies. For each area, the evidence was synthesized, limitations and gaps identified, and recommendations for future research delineated. The majority of findings in each area were from studies of oncology patients. However, increasing evidence suggests that symptom clusters occur in patients with other chronic conditions (eg, pulmonary, cardiac, and end-stage renal disease). Nonetheless, symptom cluster research is extremely limited and scientists are just beginning to understand how to investigate symptom clusters by developing frameworks and new methods and approaches. With a focus on personalized care, an understanding of individual susceptibility to symptoms and whether a \"driving\" symptom exists that triggers other symptoms in the cluster is needed. Also, research aimed at identifying the mechanisms that underlie symptom clusters is essential to developing targeted interventions.</p>","PeriodicalId":50898,"journal":{"name":"Acta Geophysica","volume":"56 1","pages":""},"PeriodicalIF":9.9,"publicationDate":"2017-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5939621/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90844634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improved Data Preprocessing Algorithm for Time-Domain Induced Polarization Method with Digital Notch Filter 改进的数字陷波滤波器时域诱导偏振法数据预处理算法

IF 2.3 4区地球科学

Acta Geophysica Pub Date : 2016-12-28 DOI: 10.1515/acgeo-2016-0015

Shuang-Chao Ge, M. Deng, Kai Chen, Bin Li, Yuan Li

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引用次数: 5

Oil Formation Volume Factor Determination Through a Fused Intelligence 基于融合智能的储层体积因子确定

IF 2.3 4区地球科学

Acta Geophysica Pub Date : 2016-12-28 DOI: 10.1515/acgeo-2016-0099

A. Gholami

{"title":"Oil Formation Volume Factor Determination Through a Fused Intelligence","authors":"A. Gholami","doi":"10.1515/acgeo-2016-0099","DOIUrl":"https://doi.org/10.1515/acgeo-2016-0099","url":null,"abstract":"Volume change of oil between reservoir condition and standard surface condition is called oil formation volume factor (FVF), which is very time, cost and labor intensive to determine. This study proposes an accurate, rapid and cost-effective approach for determining FVF from reservoir temperature, dissolved gas oil ratio, and specific gravity of both oil and dissolved gas. Firstly, structural risk minimization (SRM) principle of support vector regression (SVR) was employed to construct a robust model for estimating FVF from the aforementioned inputs. Subsequently, an alternating conditional expectation (ACE) was used for approximating optimal transformations of input/output data to a higher correlated data and consequently developing a sophisticated model between transformed data. Eventually, a committee machine with SVR and ACE was constructed through the use of hybrid genetic algorithm-pattern search (GA-PS). Committee machine integrates ACE and SVR models in an optimal linear combination such that makes benefit of both methods. A group of 342 data points was used for model development and a group of 219 data points was used for blind testing the constructed model. Results indicated that the committee machine performed better than individual models.","PeriodicalId":50898,"journal":{"name":"Acta Geophysica","volume":"64 1","pages":"2510-2529"},"PeriodicalIF":2.3,"publicationDate":"2016-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/acgeo-2016-0099","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67091769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Variations of Strength, Resistivity and Thermal Parameters of Clay after High Temperature Treatment 高温处理后粘土强度、电阻率及热参数的变化

IF 2.3 4区地球科学

Acta Geophysica Pub Date : 2016-12-28 DOI: 10.1515/acgeo-2016-0090

Qiang Sun, Weiqiang Zhang, Yuliang Zhang, Lining Yang

引用次数: 9

Shear Wave Velocity Estimates through Combined Use of Passive Techniques in a Tectonically Active Area 在构造活动区联合使用被动技术估算横波速度

IF 2.3 4区地球科学

Acta Geophysica Pub Date : 2016-12-28 DOI: 10.1515/acgeo-2016-0086

R. Biswas, S. Baruah

引用次数: 9

The Relationship of Stratospheric QBO with the Difference of Measured and Calculated NmF2 平流层QBO与实测与计算NmF2差的关系