To achieve the most efficiency in supply chain management, the capability of distribution networks is a key point for the entire supply chain. Stocks are critical for enhancing the efficiency of ...satisfying the demand of retailers in the distribution network. A configuration of a distribution network is consisted of routes and nodes. Each route connects a pair of nodes and each node is denoted as a supplier, a distribution center, or a retailer. For each route, it has a carrier whose available capacity for demand transmission is multi state. Hence, a distribution network is also regarded as a multi state network and such a network is named as a multi state distribution network (MDN) in here. The propose of this paper is to evaluate the system reliability which is defined as the probability that the MDN can meet all retailers’ demand under stocks. In practical, all retailers’ demand should be satisfied by stocks in the distribution centers (DCs) firstly. Therefore flow assignment in MDN model is mainly clarified by the relationship between the demand of retailers, stocks on DCs, and suppliers. The concept of minimal capacity vectors (MCVs) is then proposed and an algorithm is developed to obtaining MCVs for evaluating system reliability.
The primary concern of managers in logistics management is how market demand can be satisfied. The inventory in the transfer center of a distribution network plays a key role in meeting customer ...demands. This study focuses on evaluating the system reliability of a stochastic delivery-flow distribution network (SDDN) with inventory. An SDDN is composed of nodes and routes, where each node denotes a vendor, transfer center, or market and each route connects a pair of nodes. Along each route, there is a carrier whose available capacity is stochastic. Different from previous issues regarding system reliability, this study does not consider the vendor (source) and market (sink) but also the amount of stocks in transfer center is included. If the market demand cannot be met by inventory in transfer center, then vendors must meet the remaining demand to satisfy the market. Therefore an algorithm is developed in terms of minimal paths to evaluate system reliability, which is defined as the probability that the SDDN with stocks can satisfy the market demand from multiple vendors and transfer centers to the market under budget constraints. A numerical example is given to illustrate this proposed algorithm.
Background
There are several studies comparing the difference between adenocarcinoma (AC) and squamous cell carcinoma (SqCC) of lung cancer. However, seldom studies compare the different overall ...survival (OS) between AC and SqCC at same clinical or pathological stage. The aim of the study was to investigate the 5-year OS between AC and SqCC groups.
Methods
Data were obtained from the Taiwan Society of Cancer Registry. There were 48,296 non-small cell lung cancer (NSCLC) patients analyzed between 2009 and 2014 in this retrospective study. We analyzed both the AC and SqCC groups by age, gender, smoking status, Charlson co-morbidity index (CCI) score, clinical TNM stage, pathological stage, tumor location, histologic grade, pleura invasion, performance status, treatment, stage-specific 5-year OS rate in each clinical stage I–IV and causes of death. We used propensity score matching to reduce the bias.
Results
The AC and SqCC groups are significantly different in age, gender, smoking status, CCI score, clinical TNM stage, pathological stage, tumor location, histologic grade, pleura invasion, performance status, treatment, stage-specific 5-year OS rate in each clinical stage and causes of death (
p
< 0.0001). The stage-specific 5-year OS rates between AC and SqCC were 79% vs. 47% in stage I; 50% vs. 32% in stage II; 27% vs. 13% in stage III; 6% vs. 2% in stage IV, respectively (all
p
values < 0.0001).
Conclusions
AC and SqCC have significantly different outcomes in lung cancer. We suggest that these two different cancers should be analyzed separately to provide more precise outcomes in the future.
Developing ion‐selective membranes with anti‐biofouling property and biocompatibility is highly crucial in harvesting osmotic energy in natural environments and for future biomimetic applications. ...However, the exploration of membranes with these properties in osmotic energy conversion remain largely unaddressed. Herein, a tough zwitterionic gradient double‐network hydrogel membrane (ZGDHM) with excellent biofouling resistance and cytocompatibility for sustainable osmotic energy harvesting is demonstrated. The ZGDHM, composed of negatively charged 2‐acrylamido‐2‐methylpropanesulfonic acid (AMPS) as the first scaffold network and zwitterionic sulfobetaine acrylamide (SBAA) as the second network, is prepared by a two‐step photopolymerization, thus creating continuous gradient double‐network nanoarchitecture and then remarkably enhanced mechanical properties. As verified by the experiments and simulations, the gradient nanoarchitecture endows the hydrogel membrane with apparent ionic diode effect and space‐charge‐governed transport property, thus facilitating directional ion transport. Consequently, the ZGDHM can achieve a power density of 5.44 W m−2 by mixing artificial seawater and river water, surpassing the commercial benchmark. Most importantly, the output power can be promoted to an unprecedented value of 49.6 W m−2 at the mixing of salt‐lake water and river water, nearly doubling up most of the existing nanofluidic membranes. This study paves a new avenue toward developing ultrahigh‐performance osmotic energy harvesters for biomimetic applications.
A tough zwitterionic gradient double‐network hydrogel membrane, with excellent biofouling resistance, cytocompatibility, and high energy conversion efficiency is exploited for sustainable osmotic energy harvesting. Due to the induced ion diode effect, low interfacial ion transport resistance, and space‐charge‐governed transport property from the continuous gradient nanoarchitecture, an amazingly high power density of up to 49.6 W m−2 is achieved.
Coronary risk scores (CRS) including History, Electrocardiogram, Age, Risk Factors, Troponin (HEART) score and Emergency Department Assessment of Chest pain Score (EDACS) can help identify patients ...at low risk of major adverse cardiac events. In the emergency department (ED), there are wide variations in hospital admission rates among patients with chest pain.
This study aimed to evaluate the impact of CRS on the disposition of patients with symptoms suggestive of acute coronary syndrome in the ED.
This retrospective cohort study included 3660 adult patients who presented to the ED with chest pain between January and July in 2019. Study inclusion criteria were age > 18 years and a primary position International Statistical Classification of Diseases and Related Health Problems-10th revision coded diagnosis of angina pectoris (I20.0–I20.9) or chronic ischemic heart disease (I25.0–I25.9) by the treating ED physician. If the treating ED physician completed the electronic structured variables for CRS calculation to assist disposition planning, then the patient would be classified as the CRS group; otherwise, the patient was included in the control group.
Among the 2676 patients, 746 were classified into the CRS group, whereas the other 1930 were classified into the control group. There was no significant difference in sex, age, initial vital signs, and ED length of stay between the two groups. The coronary risk factors were similar between the two groups, except for a higher incidence of smokers in the CRS group (19.6% vs. 16.1%, p = 0.031). Compared with the control group, significantly more patients were discharged (70.1% vs. 64.6%) directly from the ED, while fewer patients who were hospitalized (25.9% vs. 29.7%) or against-advise discharge (AAD) (2.6% vs. 4.0%) in the CRS group. Major adverse cardiac events and mortality at 60 days between the two groups were not significantly different.
A higher ED discharge rate of the group using CRS may indicate that ED physicians have more confidence in discharging low-risk patients based on CRS.
In this study, a fractal absorber was designed to enhance light absorptivity and improve the efficiency of converting solar energy into electricity for a range of solar energy technologies. The ...absorber consisted of multiple layers arranged from bottom to top, and the bottom layer was made of Ti metal, followed by a thin layer of MgF2 atop it. Above the two layers, a structure comprising square pillars formed by three layers of Ti/MgF2/Ti was formed. This pillar was encompassed by a square hollow with cylindrical structures made of Ti material on the exterior. The software utilized for this study was COMSOL Multiphysics® (version 6.0). This study contains an absorption spectrum analysis of the various components of the designed absorber system, confirming the notion that achieving ultra-wideband and perfect absorption resulted from the combination of the various components. A comprehensive analysis was also conducted on the width of the central square pillar, and the analysis results demonstrate the presence of several remarkable optical phenomena within the investigated structure, including propagating surface plasmon resonance, localized surface plasmon resonance, Fabry–Perot cavity resonance, and symmetric coupling plasma modes. The optimal model determined through this software demonstrated that broadband absorption in the range of 276 to 2668 nm, which was in the range of UV-B to near-infrared, exceeded 90.0%. The average absorption rate in the range of 276~2668 nm reached 0.965, with the highest achieving a perfect absorptivity of 99.9%. A comparison between absorption with and without outer cylindrical structures revealed that the resonance effects significantly enhanced absorption efficiency, as evidenced by a comparison of electric field distributions.
The complex process of wound healing depends on the coordinated interaction between various immunological and biological systems, which can be aided by technology. This present review provides a ...broad overview of the medical applications of piezoelectric and triboelectric nanogenerators, focusing on their role in the development of wound healing technology. Based on the finding that the damaged epithelial layer of the wound generates an endogenous bioelectric field to regulate the wound healing process, development of technological device for providing an exogenous electric field has therefore been paid attention. Authors of this review focus on the design and application of piezoelectric and triboelectric materials to manufacture self-powered nanogenerators, and conclude with an outlook on the current challenges and future potential in meeting medical needs and commercialization.
In the intelligent traffic system, real-time and accurate detections of vehicles in images and video data are very important and challenging work. Especially in situations with complex scenes, ...different models, and high density, it is difficult to accurately locate and classify these vehicles during traffic flows. Therefore, we propose a single-stage deep neural network YOLOv3-DL, which is based on the Tensorflow framework to improve this problem. The network structure is optimized by introducing the idea of spatial pyramid pooling, then the loss function is redefined, and a weight regularization method is introduced, for that, the real-time detections and statistics of traffic flows can be implemented effectively. The optimization algorithm we use is the DL-CAR data set for end-to-end network training and experiments with data sets under different scenarios and weathers. The analyses of experimental data show that the optimized algorithm can improve the vehicles’ detection accuracy on the test set by 3.86%. Experiments on test sets in different environments have improved the detection accuracy rate by 4.53%, indicating that the algorithm has high robustness. At the same time, the detection accuracy and speed of the investigated algorithm are higher than other algorithms, indicating that the algorithm has higher detection performance.
In this paper, a modern computer network, cloud-based network, which comprises internet of things (IoT), edge servers, and cloud servers for data transmission, is investigated and evaluated. A ...cloud-based network is modeled as a graph having a set of nodes and a set of links. Each link represents a transmission route, and each node represents a device, such as an IoT device, edge server, and cloud server. In practical, a transmission route comprises several physical lines or virtual channels. Each physical line (virtual channel) may provide a capacity or may fail to imply several and stochastic states. Such a cloud-based network is called a stochastic flow cloud-based network (SCN) herein. System reliability for an SCN is then evaluated. It is defined as the probability of the data being successfully transmitted through the SCN under edge server capacity and budget constraints. The SCN is modeled firstly in order to elucidate the flow relationship among the whole system; capacity limitation of the edge servers and costs of data transmission/process are also considered. Subsequently, we conclude an algorithm to evaluate system reliability. Supervisors can manage the SCN based on system reliability which presents the system capability with capacity and budget consideration.
Real-time identification of irrigation water pollution sources and pathways (PSP) is crucial to ensure both environmental and food safety. This study uses an integrated framework based on the ...Internet of Things (IoT) and the blockchain technology that incorporates a directed acyclic graph (DAG)-configured wireless sensor network (WSN), and GIS tools for real-time water pollution source tracing. Water quality sensors were installed at monitoring stations in irrigation channel systems within the study area. Irrigation water quality data were delivered to databases via the WSN and IoT technologies. Blockchain and GIS tools were used to trace pollution at mapped irrigation units and to spatially identify upstream polluted units at irrigation intakes. A Water Quality Analysis Simulation Program (WASP) model was then used to simulate water quality by using backward propagation and identify potential pollution sources. We applied a “backward pollution source tracing” (BPST) process to successfully and rapidly identify electrical conductivity (EC) and copper (Cu2+) polluted sources and pathways in upstream irrigation water. With the BPST process, the WASP model effectively simulated EC and Cu2+ concentration data to identify likely EC and Cu2+ pollution sources. The study framework is the first application of blockchain technology for effective real-time water quality monitoring and rapid multiple PSPs identification. The pollution event data associated with the PSP are immutable.
PDF
