Explore the vast range of titles available.

Doctoral education, a key component of higher education in the United States, is performing well. It educates future professors, researchers, innovators, and entrepreneurs. It attracts students and scholars from all over the world and is being emulated globally. This success, however, should not engender complacency. A Data-Based Assessment of Research-Doctorate Programs in the United States provides an unparalleled dataset that can be used to assess the quality and effectiveness of doctoral programs based on measures important to faculty, students, administrators, funders, and other stakeholders. This report features analysis of selected findings across six broad fields: agricultural sciences, biological and health sciences, engineering, physical and mathematical sciences, social and behavioral sciences, and humanities, as well as a discussion of trends in doctoral education since the last assessment in 1995, and suggested uses of the data. It also includes a detailed explanation of the methodology used to collect data and calculate ranges of illustrative rankings.

Objective based county-level AGD evaluation index system was established. A typical agricultural county of Quzhou County in the North China Plain was use as a representative study. Unbalanced development was revealed as well as large gaps relative to targets. Spearman rank correlation analysis revealed more synergistic effect than trade-off effect. Trade-off existed between eco-environment and both food production and socioeconomic dimensions. Agriculture green development (AGD) has become an unavoidable choice to address the unique national circumstances of China. This study established a county-level AGD evaluation index system, comprised three dimensions, food production, ecological environment and socioeconomic development, using 20 indicators. The assessment delved into historical trend and current situation, utilizing Spearman rank correlation analysis to analyze trade-off and synergy relationships, using Quzhou County, Hebei Province as a case study. The main findings were in four areas. Firstly, the index for AGD in Quzhou County increased by 58.9% from 1978 to 2019. The major contribution were the social economy (65.8%) and food production (53.5%), whereas the ecological environment was found to have had a negative impact. Secondly, in 2019, the AGD index was only 56.4, indicating substantial potential for improvement relative to the target value. A notable difference in scores existed between the three dimensions, with the order being ecological environment (66.3) > food production (61.7) > socioeconomic (41.3). Also, 90% of the indicators did not reach the target value. Thirdly, relationship analysis of the indicators revealed that the synergistic effect exceeded the trade-off effect. Specifically, 46.3% of the indicators had no significant relationship, 35.3% had a synergistic relationship, and 18.4% had a trade-off relationship. Finally, interdimensional indicator relationships exhibited a trade-off effect between the ecological environment and both food production and socioeconomic dimensions. However, a positive trend of synergy between production and ecology has emerged since 2015. In conclusion, the quantitative evaluation index system exposed the unbalanced development and significant potential relative to the target value of AGD in Quzhou County, despite notable progress.

This book presents a systematic review on traditional Arab herbal medicine including historical background, medical innovations introduced by Arab physicians, common roots of Arab medicine and western medicine, methodology of drug discovery and therapy in Arabic and Islamic medicine, a state-of-the-art description of traditional Arab herbal.

The American Time Use Survey (ATUS), conducted by the Bureau of Labor Statistics, included a subjective well-being (SWB) module in 2010 and 2012. The module, funded by the National Institute on Aging (NIA), is being considered for inclusion in the ATUS for 2013. The National Research Council was asked to evaluate measures of self-reported well-being and offer guidance about their adoption in official government surveys. The charge for the study included an interim report to consider the usefulness of the ATUS SWB module, specifically the value of continuing it for at least one more wave. Among the key points raised in this report are the value, methodological benefits, and cost and effects on the ATUS and new opportunities. Research on subjective or self-reported well-being has been ongoing for several decades, with the past few years seeing an increased interest by some countries in using SWB measures to evaluate government policies and provide a broader assessment of the health of a society than is provided by such standard economic measures as gross domestic product. NIA asked the panel to prepare an interim report on the usefulness of the SWB module of the ATUS, with a view as to the utility of continuing the module in 2013. The Subjective Well-Being Module of the American Time Use Survey is intended to fulfill only one narrow aspect of the panel's broader task. It provides an overview of the ATUS and the SWB module, a brief discussion of research applications to date, and a preliminary assessment of the value of SWB module data. The panel's final report will address issues of whether research has advanced to the point that SWB measures-and which kinds of measures-should be regularly included in major surveys of official statistical agencies to help inform government economic and social policies.

The purpose of economic evaluation is to inform decisions intended to improve healthcare. The new edition of Methods for the Economic Evaluation of Health Care Programmes equips the reader with the essential hands-on experience to undertake evaluations, providing a 'tool kit' based on the authors own experience of undertaking economic evaluations.

ObjectivesTo explore the relationship between the imaging manifestations and clinical classification of COVID-19.MethodsWe conducted a retrospective single-center study on patients with COVID-19 from Jan. 18, 2020 to Feb. 7, 2020 in Zhuhai, China. Patients were divided into 3 types based on Chinese guideline: mild (patients with minimal symptoms and negative CT findings), common, and severe-critical (patients with positive CT findings and different extent of clinical manifestations). CT visual quantitative evaluation was based on summing up the acute lung inflammatory lesions involving each lobe, which was scored as 0 (0%), 1 (1–25%), 2 (26–50%), 3 (51–75%), or 4 (76–100%), respectively. The total severity score (TSS) was reached by summing the five lobe scores. The consistency of two observers was evaluated. The TSS was compared with the clinical classification. ROC was used to test the diagnosis ability of TSS for severe-critical type.ResultsThis study included 78 patients, 38 males and 40 females. There were 24 mild (30.8%), 46 common (59.0%), and 8 severe-critical (10.2%) cases, respectively. The median TSS of severe-critical-type group was significantly higher than common type (p < 0.001). The ICC value of the two observers was 0.976 (95% CI 0.962–0.985). ROC analysis showed the area under the curve (AUC) of TSS for diagnosing severe-critical type was 0.918. The TSS cutoff of 7.5 had 82.6% sensitivity and 100% specificity.ConclusionsThe proportion of clinical mild-type patients with COVID-19 was relatively high; CT was not suitable for independent screening tool. The CT visual quantitative analysis has high consistency and can reflect the clinical classification of COVID-19.Key Points• CT visual quantitative evaluation has high consistency (ICC value of 0.976) among the observers. The median TSS of severe-critical type group was significantly higher than common type (p < 0.001).• ROC analysis showed the area under the curve (AUC) of TSS for diagnosing severe-critical type was 0.918 (95% CI 0.843–0.994). The TSS cutoff of 7.5 had 82.6% sensitivity and 100% specificity.• The proportion of confirmed COVID-19 patients with normal chest CT was relatively high (30.8%); CT was not a suitable screening modality

Wheat and maize are two major food crops in China. Conventional fertilizer recommendations result in higher than necessary costs to farmers and increased environmental pollution. It is essential to quantitatively estimate optimal fertilizer requirements to alleviate the problems of the two crops in China. The QUEFTS (QUantitative Evaluation of the Fertility of Tropical Soils) model was used to estimate region-specific nitrogen (N), phosphorus (P) and potassium (K) requirements as well as fertilizer applications needed to realize target yields of wheat and maize. Data of field experiments with different fertilization treatments of various regions in China during the years of 1985-1995 were used to calibrate the QUEFTS model for both wheat and maize. Minimum and maximum internal nutrient efficiencies (kg grain kg-¹) for the model were estimated at N (25 and 56), P (171 and 367), K (24 and 67) for wheat, and N (21 and 64), P (126 and 384), K (20 and 90) for maize. The model suggested a linear increase of grain yields for scenarios with nutrient contents of 24.6, 3.7 and 23.0 kg N, P and K per 1000 kg of wheat grain and 25.8, 4.3 and 23.1 kg N, P and K per 1000 kg of maize grain. These results suggest that the average N: P: K ratio in the plant dry matter is about 6.7: 1: 6.2 for wheat and 6.0: 1: 5.4 for maize. Relationships between internal N, P and K levels and soil properties were established and relationships between the recovery efficiencies of applied fertilizer - N, P and K were found. Running the calibrated QUEFTS model with observed field data produced a good fit between predicted and observed data. It was concluded that the calibrated QUEFTS model could be a useful tool for improving fertilizer recommendations for wheat and maize in China.

Health literacy-the ability for individuals to obtain, process, and understand basic health information and services to facilitate appropriate health decisions-is increasingly recognized as an important facet of health care and health outcomes. Although research on health literacy has grown tremendously in the past decade, there is no widely agreed-upon framework for health literacy as a determinant of health outcomes. Most instruments focus on assessing an individual's health literacy, yet the scope of health literacy reaches far beyond an individual's skills and abilities. Health literacy occurs in the context of the health care system, and therefore measures of health literacy must also assess the demands and complexities of the health care systems with which patients interact. For example, measures are needed to determine how well the system has been organized so that it can be navigated by individuals with different levels of health literacy and how well health organizations are doing at making health information understandable and actionable. To examine what is known about measures of health literacy, the Institute of Medicine convened a workshop. The workshop, summarized in this volume, reviews the current status of measures of health literacy, including those used in the health care setting; discusses possible surrogate measures that might be used to assess health literacy; and explores ways in which health literacy measures can be used to assess patient-centered approaches to care.

This book focuses on new small molecule approaches to combat viral infections. The chapters describe the discovery and development from bench through the clinic of relatively recently-approved antiviral drugs and compounds in advanced clinical development. Organized by a virus (such as HIV, HCV, RSV, influenza, HBV and CMV) and written by top academic and industrial authorities in the field, the book provides a unique opportunity to study, understand and apply discovery and development principles and learning without the need for an individual to research, analyze and synthesize all immense sourcing references.  Topics showcase challenges and solutions of issues encountered, offering tremendous experience accumulated over many years of research that will be particularly useful to basic and bench scientists as well as clinicians as they continue discovering and developing new drugs and therapies.

ObjectivesEvaluation of imaging performance across dual-energy CT (DECT) platforms, including dual-layer CT (DLCT), rapid-kVp-switching CT (KVSCT) and dual-source CT (DSCT).MethodsA semi-anthropomorphic abdomen phantom was imaged on these DECT systems. Scans were repeated three times for CTDIvol levels of 10 mGy, 20 mGy, 30 mGy and different fat-simulating extension rings. Over the available range of virtual-monoenergetic images (VMI), noise as well as quantitative accuracy of hounsfield units (HU) and iodine concentrations were evaluated.ResultsFor all VMI levels, HU values could be determined with high accuracy compared to theoretical values. For KVSCT and DSCT, a noise increase was observed towards lower VMI levels. A patient-size dependent increase in the uncertainty of quantitative iodine concentrations is observed for all platforms. For a medium patient size the iodine concentration root-mean-square deviation at 20 mGy is 0.17 mg/ml (DLCT), 0.30 mg/ml (KVSCT) and 0.77mg/ml (DSCT).ConclusionNoticeable performance differences are observed between investigated DECT systems. Iodine concentrations and VMI HUs are accurately determined across all DECT systems. KVSCT and DLCT deliver slightly more accurate iodine concentration values than DSCT for investigated scenarios. In DLCT, low-noise and high-image contrast at low VMI levels may help to increase diagnostic information in abdominal CT.Key Points• Current dual-energy CT platforms provide accurate, reliable quantitative information.• Dual-energy CT cross-platform evaluation revealed noticeable performance differences between different systems.• Dual-layer CT offers constant noise levels over the complete energy range.