The present study investigates the benefit of joint decision making regarding whole blood collection and platelet production at a blood center. We consider a blood center that faces two types of platelet demands, differing in their freshness requirements and shortage penalty costs. We fully characterize the structure of the optimal policy regarding whole blood collection, platelet production, and inventory issuing, rationing and disposal. We find that the optimal platelet production quantity in each period is nonincreasing in the inventory levels of platelets and whole blood but that interestingly, the optimal blood collection effort may increase with the on‐hand platelet inventory level. We demonstrate with a real dataset that joint decision making leads to significant cost savings compared with separate decision making. The benefit is mainly derived from reduced blood collection and platelet production, better utilization of the collected whole blood, and reduced platelet shortage. For practical implementation, we develop a lookahead heuristic, which is shown to be very effective by numerical experiments.

Eutrophic coastal regions are highly productive and greatly influenced by human activities. Primary production supporting the coastal ecosystems is supposed to be affected by progressive ocean acidification driven by increasing CO2 emissions. In order to investigate the effects of high pCO2 (HC) on eutrophic plankton community structure and ecological functions, we employed 9 mesocosms and carried out an experiment under ambient (∼410 ppmv) and future high (1000 ppmv) atmospheric pCO2 conditions, using in situ plankton community in Wuyuan Bay, East China Sea. Our results showed that HC along with natural seawater temperature rise significantly boosted biomass of diatoms with decreased abundance of dinoflagellates in the late stage of the experiment, demonstrating that HC repressed the succession from diatoms to dinoflagellates, a phenomenon observed during algal blooms in the East China Sea. HC did not significantly influence the primary production or biogenic silica contents of the phytoplankton assemblages. However, the HC treatments increased the abundance of viruses and heterotrophic bacteria, reflecting a refueling of nutrients for phytoplankton growth from virus-mediated cell lysis and bacterial degradation of organic matters. Conclusively, our results suggest that increasing CO2 concentrations can modulate plankton structure including the succession of phytoplankton community and the abundance of viruses and bacteria in eutrophic coastal waters, which may lead to altered biogeochemical cycles of carbon and nutrients.

Manufacturing servitization has become a major trend in industry that is implemented by so called integrated production and service systems (IPSSs) to offer not only products but also their associated services. In this study, we explore the capacity allocation policy for an IPSS that consists of a manufacturing facility and a service center. The IPSS serves two classes of customers, each demanding a specific product produced at the manufacturing facility and, subsequently, the associated service offered by the service center. We formulate this problem of resource allocation as a Markov decision process. Our analysis suggests that it is optimal to serve the customer with the larger cost saving rate and slower service rate, where the cost saving rate equals service rate times the sum of holding cost and waiting cost. Then we explore production control policies coupled with optimal service ones. We demonstrate that, with light service traffic, the system under the optimal production policy becomes similar to a make‐to‐stock system. Such a system can effectively hedge the system uncertainty. Therefore, the optimal production policy for the IPSS is also a hedging point policy. Under this policy, switching and idling curves split the state space into three regions: one without any production, the two others for production of two type products, respectively. We also discuss the optimal control policies of the two extensions of the IPSS (one with multiple types of product and customers, and the other with a single product and two classes of customers) and find that the characters of the optimal production and service policy still hold. Finally, we develop three heuristic integrated scheduling policies. Numerical experiments show that one is very effective.

W e consider a periodic-review perishable inventory system with multiple demand classes, each characterized by a different lost-sales cost and the least freshness requirement. Demands of different classes in the same period could be correlated, while demands across periods are independent but not necessarily identical. In each period, the firm jointly makes the decisions regarding demand fulfillment, production/ordering, and disposal. The objective is to minimize the total discounted expected cost over the entire planning horizon including linear ordering cost, inventory holding/lostsales cost, expiration cost, and disposal cost. By establishing new properties of multimodularity, we explore some monotonicity and bounded sensitivity properties of the optimal policies. The optimality analysis enables us to propose a novel approximation approach, called adaptive approximation approach, which can be recursively calculated through a singledimension dynamic program. Numerical studies demonstrate that our proposed approximation approach is nearly optimal with the average optimality gap 0.30% and significantly outperforms the existing heuristics in the literature.

In order to improve the utilization rate of spectroscopic data and texture information, this study proposes a method for optimal selection of spectrum and texture features based on automatic subspace division and rough set theory. This method takes advantage of rough set reduct ideology in order to realize the reduction of different types of ground object spectral features on the basis of the conventional subspace division method. In using this method, the primary spectral band based on spectral information can be determined. Then, the grey-level co-occurrence matrix method can be used to calculate the texture information of the primary spectral band and determine the reduction and optimization in order to obtain the final band based on the spectrum and texture information. Verification of this method is made by using CASI data of Heihe Region, China, and AVIRIS data of the Indiana Region, USA, and also using Support Vector Machine (SVM) classification of the original spectral, primary spectral, and final bands. The results indicate the following. (1) The method for optimal selection of the critical spectral band and texture band, based on the rough set theory, can efficiently improve the classification accuracy of high-spatial resolution remote-sensing images. However, the effects for the low-spatial resolution images are minimal. (2) For high-spatial-resolution remote-sensing images, such as roads, trenches, buildings, and other types of object with obvious textural features, the addition of image texture information can increase the degree of distinction of these different types and thereby improve the classification accuracy. However, the addition of the textural information for some objects with similar texture features will cause misclassification and reduce the classification accuracy for these types of images.(3) This method can realize the optimal selection of spectrum and texture bands of a hyperspectral image and has a certain universality. Also, the texture information will be richer and this method will be more practical through increasing the spatial resolution of images.

No abstract

In the context of global warming, changes in phytoplankton-associated bacterial communities have the potential to change biogeochemical cycling and food webs in marine ecosystems. Skeletonema is a cosmopolitan diatom genus in coastal waters worldwide. Here, we grew a Skeletonema strain with its native bacterial assemblage at different temperatures and examined cell concentrations of Skeletonema sp. and free-living bacteria, dissolved organic carbon (DOC) concentrations of cultures, and the community structure of both free-living and attached bacteria at different culture stages. The results showed that elevated temperature increased the specific growth rates of both Skeletonema and free-living bacteria. Different growth stages had a more pronounced effect on community structure compared with temperatures and different physical states of bacteria. The effects of temperature on the structure of the free-living bacterial community were more pronounced compared with diatom-attached bacteria. Carbon metabolism genes and those for some specific amino acid pathways were found to be positively correlated with elevated temperature, which may have profound implications on the oceanic carbon cycle and the marine microbial loop. Network analysis revealed evidence of enhanced cooperation with an increase in positive interactions among different bacteria at elevated temperature. This may help the whole community to overcome the stress of elevated temperature. We speculate that different bacterial species may build more integrated networks with a modified functional profile of the whole community to cope with elevated temperature. This study contributes to an improved understanding of the response of diatom-associated bacterial communities to elevated temperature.

The detection of different thickness of spilled oil film is internationally recognized as one of the difficult problems. Hyperspectral remote sensing data can provide continuous spectrum, and be beneficial for the identification of oil film. The traditional detection method failed to make full use of different spectral characteristics of the oil film, so is unable to improving the identification precision of them. By deep digging the time-frequency information based on the wavelet transform, we can enhance the difference of the spectral characteristic between thick and thin oil film, so that we can find sensitive wavelength location of them. High frequency coefficient of wavelet transformation is able to indicating the sensitive spectral range of different thickness of oil film, and low frequency coefficient information is available for eliminating the noise of the image, consequently, enhancing the contrast between the categories. Based on this, this paper proposed a new method for classification of the various thickness of oil film based on wavelet transform spectrum information. Firstly, we extracted the sensitive wave bands of different thickness of oil film based on the analysis of the singularity of the high frequency wavelet coefficient curve. Secondly, we regenerated the new low-frequency wavelet coefficients image of sensitive bands which are regarded as sensitive bands in term of the analysis on the high frequency wavelet coefficients curve. Finally, we conducted the classification of the different thickness of oil spill film based on the new low-frequency wavelet coefficients image. The experiment has gotten good effect with Hyperspectral data obtained airborne from oil spill accident happening