An Optimization Model for Ordering and Transporting Raw Materials by Manufacturers Based on Linear Programming

This study applies analytic hierarchy process (A­­­HP), 0-1 integer programming and other systematic programming models, combined with the needs of manufacturers to build a set of mathematical models to help manufacturers select suppliers, control raw material ordering costs, and transporting costs. As the production costs of products is linked to the ordering and transporting of raw materials, manufacturers need to choose suitable raw material suppliers and develop the most economical ordering and transporting schemes with the most negligible loss so as to improve profits and enhance the market competitiveness. Taking a building and decorative plate enterprise as a case, this model shows that AHP can effectively quantify the supplying characteristics of suppliers and obtain a list of high-quality suppliers. LINGO software combined with linear programming can be used to obtain the optimal weekly ordering and transporting schemes, thus reducing the raw material ordering costs and transporting losses. It is shown from the results that the production costs of enterprises from the source can be reduced so as to improve their cost control system. The present study seeks to fill the gap in ordering and transporting raw materials for manufacturers to control production costs. At the same time, this model provides references for producers who have the demand for processing raw materials and play a significant role in controlling production costs

A real-time electricity price decision model for demand side management in wind power heating mode

The problem of wind power curtailment (WPC) during winter heating periods in China’s "Three-North regions" is becoming worse. Wind power heating, though being an effective way to increase wind power consumptions, is constrained by high electric heating costs under a peak-to-valley electricity price pattern. This study develops a real-time price (RTP) decision model which adjusts the time-varying RTPs within an acceptable range of heating users based on the WPC distribution over a particular dispatch day. The lower RTPs accompanying the higher WPC can guide the electric heating user side equipped with regenerative electric boilers (REBs) to actively increase REB imports to absorb additional wind generation. Then, the demand side response using REBs under the RTP scheme is optimized to minimize the total heating cost met by electric heating users while assisting in the large-scale wind generation accommodation. The total heating costs and WPC reductions under different heating scenarios are compared and discussed alongside the effectiveness of the RTP-based demand side management in terms of reducing the WPC and heating costs and increasing the feasibility of wind power heating during winter heating periods

ISA-Net: Improved spatial attention network for PET-CT tumor segmentation

Achieving accurate and automated tumor segmentation plays an important role in both clinical practice and radiomics research. Segmentation in medicine is now often performed manually by experts, which is a laborious, expensive and error-prone task. Manual annotation relies heavily on the experience and knowledge of these experts. In addition, there is much intra- and interobserver variation. Therefore, it is of great significance to develop a method that can automatically segment tumor target regions. In this paper, we propose a deep learning segmentation method based on multimodal positron emission tomography-computed tomography (PET-CT), which combines the high sensitivity of PET and the precise anatomical information of CT. We design an improved spatial attention network(ISA-Net) to increase the accuracy of PET or CT in detecting tumors, which uses multi-scale convolution operation to extract feature information and can highlight the tumor region location information and suppress the non-tumor region location information. In addition, our network uses dual-channel inputs in the coding stage and fuses them in the decoding stage, which can take advantage of the differences and complementarities between PET and CT. We validated the proposed ISA-Net method on two clinical datasets, a soft tissue sarcoma(STS) and a head and neck tumor(HECKTOR) dataset, and compared with other attention methods for tumor segmentation. The DSC score of 0.8378 on STS dataset and 0.8076 on HECKTOR dataset show that ISA-Net method achieves better segmentation performance and has better generalization. Conclusions: The method proposed in this paper is based on multi-modal medical image tumor segmentation, which can effectively utilize the difference and complementarity of different modes. The method can also be applied to other multi-modal data or single-modal data by proper adjustment

Bioengineered MSC-derived exosomes in skin wound repair and regeneration

Refractory skin defects such as pressure ulcers, diabetic ulcers, and vascular ulcers represent a challenge for clinicians and researchers in many aspects. The treatment strategies for wound healing have high cost and limited efficacy. To ease the financial and psychological burden on patients, a more effective therapeutic approach is needed to address the chronic wound. MSC-derived exosomes (MSC-exosomes), the main bioactive extracellular vesicles of the paracrine effect of MSCs, have been proposed as a new potential cell-free approach for wound healing and skin regeneration. The benefits of MSC-exosomes include their ability to promote angiogenesis and cell proliferation, increase collagen production, regulate inflammation, and finally improve tissue regenerative capacity. However, poor targeting and easy removability of MSC-exosomes from the wound are major obstacles to their use in clinical therapy. Thus, the concept of bioengineering technology has been introduced to modify exosomes, enabling higher concentrations and construction of particles of greater stability with specific therapeutic capability. The use of biomaterials to load MSC-exosomes may be a promising strategy to concentrate dose, create the desired therapeutic efficacy, and maintain a sustained release effect. The beneficial role of MSC-exosomes in wound healing is been widely accepted; however, the potential of bioengineering-modified MSC-exosomes remains unclear. In this review, we attempt to summarize the therapeutic applications of modified MSC-exosomes in wound healing and skin regeneration. The challenges and prospects of bioengineered MSC-exosomes are also discussed

The application and progress of tissue engineering and biomaterial scaffolds for total auricular reconstruction in microtia

Microtia is a congenital deformity of the ear with an incidence of about 0.8–4.2 per 10,000 births. Total auricular reconstruction is the preferred treatment of microtia at present, and one of the core technologies is the preparation of cartilage scaffolds. Autologous costal cartilage is recognized as the best material source for constructing scaffold platforms. However, costal cartilage harvest can lead to donor-site injuries such as pneumothorax, postoperative pain, chest wall scar and deformity. Therefore, with the need of alternative to autologous cartilage, in vitro and in vivo studies of biomaterial scaffolds and cartilage tissue engineering have gradually become novel research hot points in auricular reconstruction research. Tissue-engineered cartilage possesses obvious advantages including non-rejection, minimally invasive or non-invasive, the potential of large-scale production to ensure sufficient donors and controllable morphology. Exploration and advancements of tissue-engineered cartilaginous framework are also emerging in aspects including three-dimensional biomaterial scaffolds, acquisition of seed cells and chondrocytes, 3D printing techniques, inducing factors for chondrogenesis and so on, which has greatly promoted the research process of biomaterial substitute. This review discussed the development, current application and research progress of cartilage tissue engineering in auricular reconstruction, particularly the usage and creation of biomaterial scaffolds. The development and selection of various types of seed cells and inducing factors to stimulate chondrogenic differentiation in auricular cartilage were also highlighted. There are still confronted challenges before the clinical application becomes widely available for patients, and its long-term effect remains to be evaluated. We hope to provide guidance for future research directions of biomaterials as an alternative to autologous cartilage in ear reconstruction, and finally benefit the transformation and clinical application of cartilage tissue engineering and biomaterials in microtia treatment

Effect of storage time on the silage quality and microbial community of mixed maize and faba bean in the Qinghai-Tibet Plateau

Tibetan Plateau is facing serious shortage of forage in winter and spring season due to its special geographical location. Utilization of forages is useful to alleviate the forage shortage in winter and spring season. Consequently, the current study was aimed to evaluate the influence of storage time on the silage quality and microbial community of the maize (Zea mays L.) and faba bean (Vicia faba L.) mixed silage at Qinghai-Tibet Plateau. Maize and faba bean were ensiled with a fresh weight ratio of 7:3, followed by 30, 60, 90, and 120 days of ensiling. The results showed the pH value of mixed silage was below 4.2 at all fermentation days. The LA (lactic acid) content slightly fluctuated with the extension of fermentation time, with 33.76 g/kg DM at 90 days of ensiling. The AA (acetic acid) and NH3-N/TN (ammonium nitrogen/total nitrogen) contents increased with the extension of fermentation time and no significantly different between 90 and 120 days. The CP (crude protein) and WSC (water soluble carbohydrate) contents of mixed silage decreased significantly (P < 0.05) with ensiling time, but the WSC content remained stable at 90 days. The Proteobacteria was the predominant phyla in fresh maize and faba bean, and Pseudomonas and Sphingomonas were the predominant genera. After ensiling, Lactobacillus was the prevalent genus at all ensiling days. The relative abundance of Lactococcus increased rapidly at 90 days of ensiling until 120 days of fermentation. Overall, the storage time significant influenced the silage fermentation quality, nutrient content, and microbial environment, and it remained stable for 90 days of ensiling at Qinghai-Tibet Plateau. Therefore, the recommended storage time of forage is 90 days in Qinghai-Tibet Plateau and other cool areas

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Significantly Enhanced Electrical Performances of Eco-Friendly Dielectric Liquids for Harsh Conditions with Fullerene

The eco-friendly vegetable liquid is increasingly used because of the growing demand for environmentally friendly dielectric liquid. A vegetable liquid/fullerene nanofluid was fabricated via ultrasonic processing with good dispersion of the fullerene nanoparticles. It was observed that a small amount of fullerene (~100 mg/L) can significantly improve the electrical properties of vegetable insulating liquid (dissipation factor decreased by 20.1%, volume resistivity increased by 23.3%, and Alternating Current (AC) dielectric breakdown strength increased by 8.6%). Meanwhile, the trace amount of fullerene is also able to improve the electrical performances (i.e., dissipation factor and electrical resistivity) of the vegetable nanofluid under harsh conditions of long-term thermal aging compared with the blank contrast. The reduced acid values (25%) and dissolved decomposition gases (58.2% for hydrogen) in the aged vegetable nanofluid indicate the inhibition of molecule decomposition of vegetable liquid with fullerene. The improved electrical performances and thermal resistance of the vegetable nanofluid contribute to the electron affinity of fullerene proved by calculation of electron density distribution on the surface. The thermogravimetric analysis of the nanofluid under different atmospheres interprets that the oxygen absorbed inevitably in the fullerene contributes to the performance deterioration of the nanofluids during the initial aging. This work provides a potential method towards eco-friendly dielectric liquid with great electrical performances for harsh environments