766 resultados para hybride value-added chain
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A value-added extruded fish product was prepared with corn flour (80%) and fish (sciaenid) powder (20%), using a twin-screw extruder. The effect of different parameters like moisture, temperature, fish powder concentration, speed of the extruder and die-diameter on expansion ratio and crisp texture were studied. The storage characteristics of the final product were studied using three different types of packaging under nitrogen flushing. The study revealed that aluminum foil is the best packaging material to keep the product acceptable for more than three months.
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In the Philippines at present, milkfish farming in ponds includes a wide range of intensities, systems and practices. To make aquaculture possible, ecosystems are used as sources of energy and resources and as sinks for wastes. The growth of aquaculture is limited by the life-support functions of the ecosystem, and sustainability depends on matching the farming techniques with the processes and functions of the ecosystems, for example, by recycling some degraded resources. The fish farm has many interactions with the external environment. Serious environmental problems may be avoided if high-intensity farms are properly planned in the first place, at the farm level and at the level of the coastal zone where it can be integrated with other uses by other sectors. It is believed that the key to immediate success in the mass production of milkfish for local consumption and for export of value-added forms may be in semi-intensive farming at target yields of 3 tons per ha per year, double the current national average. Intensive milkfish farming will be limited by environmental, resource and market constraints. Integrated intensive farming systems are the appropriate long-term response to the triple needs of the next century: more food, more income, and more jobs for more people, all from less land, less resources, and less non-renewable energy.
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随着电子技术和计算机技术的不断发展,工业生产过程的控制系统正在向着智能化、数字化和网络化的方向发展。传统的集散控制方式和计算机分层控制方式已经开始让位于智能终端与网络结合的总线网络控制方式。当今,在工厂中过程控制环境下的分布式自动化系统变得越来越复杂,尤其系统内部的各设备之间需要快速交换大量的信息,以便实现对被控系统更为精确的控制和提供一些辅助的评价函数。这就意味着要不断增加带宽和提高通信速率以满足网络通信的需要。在现有的多种可利用网络设备中,CAN总线以其清晰的定义、极高的可靠性及其独特的设计,被认为是最能有效地解决这一问题的途径之一。而且市场上基于通信技术的产品中,就实时性考虑,由于CAN总线采用的非表意性的通信方式,因此其结构更为简单,实时性更好。基于此背景,我们以CAN总线作为通信媒介,将分布于各控制现场的传感器、执行器和控制器有序地连接起来,构成了一个基于CAN总线的分布式局域网络控制系统。本文首先介绍了基于CAN总线的分布式数据采集与控制系统的总体结构。然后从硬件方面描述了基于CAN总线的通信协议转换单元、数据采集单元和输出控制单元的功能、硬件配置及各单元功能的具体实现过程,给出了各单元的性能指标。软件方面,以C语言作为平台,开发了基于CAN总线的上位计算机管理与监控软件,实现了对整个网络设备的系统管理和系统控制功能。对于该总线系统,作者运用了PID控制和模糊控制算法实现了对水箱液位的控制,达到了理想的效果。基于CAN总线的控制系统很好地解决了集散控制系统难以解决的难题,模糊控制的应用能很好地把总线控制系统应用到具有非线性、大时滞和难于获得精确模型的控制系统中。
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1999
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BACKGROUND: Diagnostic imaging represents the fastest growing segment of costs in the US health system. This study investigated the cost-effectiveness of alternative diagnostic approaches to meniscus tears of the knee, a highly prevalent disease that traditionally relies on MRI as part of the diagnostic strategy. PURPOSE: To identify the most efficient strategy for the diagnosis of meniscus tears. STUDY DESIGN: Economic and decision analysis; Level of evidence, 1. METHODS: A simple-decision model run as a cost-utility analysis was constructed to assess the value added by MRI in various combinations with patient history and physical examination (H&P). The model examined traumatic and degenerative tears in 2 distinct settings: primary care and orthopaedic sports medicine clinic. Strategies were compared using the incremental cost-effectiveness ratio (ICER). RESULTS: In both practice settings, H&P alone was widely preferred for degenerative meniscus tears. Performing MRI to confirm a positive H&P was preferred for traumatic tears in both practice settings, with a willingness to pay of less than US$50,000 per quality-adjusted life-year. Performing an MRI for all patients was not preferred in any reasonable clinical scenario. The prevalence of a meniscus tear in a clinician's patient population was influential. For traumatic tears, MRI to confirm a positive H&P was preferred when prevalence was less than 46.7%, with H&P preferred above that. For degenerative tears, H&P was preferred until the prevalence reaches 74.2%, and then MRI to confirm a negative was the preferred strategy. In both settings, MRI to confirm positive physical examination led to more than a 10-fold lower rate of unnecessary surgeries than did any other strategy, while MRI to confirm negative physical examination led to a 2.08 and 2.26 higher rate than H&P alone in primary care and orthopaedic clinics, respectively. CONCLUSION: For all practitioners, H&P is the preferred strategy for the suspected degenerative meniscus tear. An MRI to confirm a positive H&P is preferred for traumatic tears for all practitioners. Consideration should be given to implementing alternative diagnostic strategies as well as enhancing provider education in physical examination skills to improve the reliability of H&P as a diagnostic test. CLINICAL RELEVANCE: Alternative diagnostic strategies that do not include the use of MRI may result in decreased health care costs without harm to the patient and could possibly reduce unnecessary procedures.
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This article examines the socio-economic evolution of the social economy sector in the Basque Country during the 2008-2014 period of economic crisis. Data have been obtained within a framework of collaboration between university, Basque Government and private sector of the social economy. The results suggest that such entities have evolved better, both in terms of number of enterprises and employment, than the general economy of the Basque Country, while the context of public policies aimed at social economy has worsened over the years. However, in economic terms (measured through the Gross Value Added generated), they have not been able to cope with the crisis in equal conditions to the general economy. The main contribution of this research lies in that, unlike similar studies, it discusses the evolution of the whole sector of the social economy, taking as reference a broad period of the current economic crisis.
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Organometallic hydrogen transfer and dehydrogenation provide straightforward atom efficient routes from alcohols to a variety of chemical products. The potential of these reactions to enable the conversion of biomass to value added chemicals is discussed, with reference to the products that can be prepared from aliphatic alcohols in good isolated yield.
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Many international business (IB) studies have used foreign direct investment (FDI) stocks to measure the aggregate value-adding activity of multinational enterprises (MNE) affiliates in host countries. We argue that FDI stocks are a biased measure of that activity, because the degree to which they overestimate or underestimate affiliate activity varies systematically with host-country characteristics. First, most FDI into countries that serve as tax havens generate no actual productive activity; thus FDI stocks in such countries overestimate affiliate activity. Second, FDI stocks do not include locally raised external funds, funds widely used in countries with well-developed financial markets or volatile exchange rates, resulting in an underestimation of affiliate activity in such countries. Finally, the extent to which FDI translates into affiliate activity increases with affiliate labor productivity, so in countries where labor is more productive, FDI stocks also result in an underestimation of affiliate activity. We test these hypotheses by first regressing affiliate value-added and affiliate sales on FDI stocks to calculate a country-specific mismatch, and then by regressing this mismatch on a host country's tax haven status, level of financial market development, exchange rate volatility, and affiliate labor productivity. All hypotheses are supported, implying that FDI stocks are a biased measure of MNE affiliate activity, and hence that the results of FDI-data-based studies of such activity need to be reconsidered. [ABSTRACT FROM AUTHOR]
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Increasingly infrastructure providers are supplying the cloud marketplace with storage and on-demand compute resources to host cloud applications. From an application user's point of view, it is desirable to identify the most appropriate set of available resources on which to execute an application. Resource choice can be complex and may involve comparing available hardware specifications, operating systems, value-added services, such as network configuration or data replication, and operating costs, such as hosting cost and data throughput. Providers' cost models often change and new commodity cost models, such as spot pricing, have been introduced to offer significant savings. In this paper, a software abstraction layer is used to discover infrastructure resources for a particular application, across multiple providers, by using a two-phase constraints-based approach. In the first phase, a set of possible infrastructure resources are identified for a given application. In the second phase, a heuristic is used to select the most appropriate resources from the initial set. For some applications a cost-based heuristic is most appropriate; for others a performance-based heuristic may be used. A financial services application and a high performance computing application are used to illustrate the execution of the proposed resource discovery mechanism. The experimental result shows the proposed model could dynamically select an appropriate set of resouces that match the application's requirements.
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In this paper we use new, detailed, and comprehensive linked firm-transaction data to measure the domestic content and technology intensity of Chinese exports over the period 2000–2007. We evaluate the extent of value-added in China’s exports, using a modification of a method proposed by Hummels et al. (2001) which takes into account the prevalence of processing firms. In addition, we provide new estimates of the skill-and technology-intensity of China’s exports. Our estimates of value-added suggest that the domestic content of China’s exports increased from only 53% to about 60% over the period 2003–2006. Our cross-firm analysis reveals that processing exporters have value-added shares approximately 50% lower than non-processing exporters, even after accounting for ownership, location, and industry. We also show that Chinese exports have become increasingly sophisticated, largely driven by skill and technology improvement within industries.
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This collection offers a diachronic analytical study of new and alternative social movements in Spain from the democratic transition to the first decade of the 21st century, paying attention to anti-war mobilizations and the use of new technologies as a mobilizing resource. New and alternative social movements are studied through the prism of identified linkages among the left, movement identities and global processes in the Spanish context. Weight is given to certain important historical aspects, like Spain’s relatively recent authoritarian past, and certain value-added factors, such as the weak associationalism and materialism exhibited by the Spanish public. These are complemented by exploring insights offered by key theoretical approaches on social movements (political opportunities structures, resource mobilization). The volume covers established social movement cases (gender, peace, environmental movements) as well as those with a more explicit connection to the current context of global contestation (squatters’ and anti-globalization movements).
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Reducing wafer metrology continues to be a major target in semiconductor manufacturing efficiency initiatives due to it being a high cost, non-value added operation that impacts on cycle-time and throughput. However, metrology cannot be eliminated completely given the important role it plays in process monitoring and advanced process control. To achieve the required manufacturing precision, measurements are typically taken at multiple sites across a wafer. The selection of these sites is usually based on a priori knowledge of wafer failure patterns and spatial variability with additional sites added over time in response to process issues. As a result, it is often the case that in mature processes significant redundancy can exist in wafer measurement plans. This paper proposes a novel methodology based on Forward Selection Component Analysis (FSCA) for analyzing historical metrology data in order to determine the minimum set of wafer sites needed for process monitoring. The paper also introduces a virtual metrology (VM) based approach for reconstructing the complete wafer profile from the optimal sites identified by FSCA. The proposed methodology is tested and validated on a wafer manufacturing metrology dataset. © 2012 IEEE.
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Increasingly semiconductor manufacturers are exploring opportunities for virtual metrology (VM) enabled process monitoring and control as a means of reducing non-value added metrology and achieving ever more demanding wafer fabrication tolerances. However, developing robust, reliable and interpretable VM models can be very challenging due to the highly correlated input space often associated with the underpinning data sets. A particularly pertinent example is etch rate prediction of plasma etch processes from multichannel optical emission spectroscopy data. This paper proposes a novel input-clustering based forward stepwise regression methodology for VM model building in such highly correlated input spaces. Max Separation Clustering (MSC) is employed as a pre-processing step to identify a reduced srt of well-conditioned, representative variables that can then be used as inputs to state-of-the-art model building techniques such as Forward Selection Regression (FSR), Ridge regression, LASSO and Forward Selection Ridge Regression (FCRR). The methodology is validated on a benchmark semiconductor plasma etch dataset and the results obtained are compared with those achieved when the state-of-art approaches are applied directly to the data without the MSC pre-processing step. Significant performance improvements are observed when MSC is combined with FSR (13%) and FSRR (8.5%), but not with Ridge Regression (-1%) or LASSO (-32%). The optimal VM results are obtained using the MSC-FSR and MSC-FSRR generated models. © 2012 IEEE.
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Over recent years, ionic liquids have emerged as a class of novel fluids that have inspired the development of a number of new products and processes. The ability to design these materials with specific functionalities and properties means that they are highly relevant to the growing philosophy of chemical-product design. This is particularly appropriate in the context of a chemical industry that is becoming increasingly focussed on small-volume, high-value added products with relatively short times to market. To support such product and process development, a number of tools can be utilised. A key requirement is that the tool can predict the physical properties and activity coefficients of multi-component mixtures and, if required, model the process in which the materials will be used. Multi-scale simulations that span density functional theory (DFT) to process-engineering computations can address the relevant time and length scales and have increased in usage with the availability of cheap and powerful computers. Herein we will discuss the area of engineering calculations relating to the design of ionic liquid processes, that is, the computational tools that bridge this gap and allow for process simulation tools to utilise and assist in the design of ionic liquids. It will be shown that, at present, it is possible to use available tools to estimate many important properties of ionic liquids and mixtures containing them with a sufficient level of accuracy for preliminary design and selection.