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Abstract Objectives COVID-19 viral pneumonia can result in increased arterial stiffness, along with cardiac and systemic inflammatory responses. This study aimed to investigate the association between arterial stiffness, inflammation severity, and all-cause mortality in patients with COVID-19. Methods In this study, anthropometric data, pneumonia infection severity, and blood tests were analyzed. Arterial stiffness was assessed using the non-invasive assessment indices, including arterial velocity pulse index (AVI) and central arterial pulse pressure (CAPP). Infection volumes and percentages for the whole lungs, most lobes, and most segments were extracted from CT images using artificial intelligence-based quantitative analysis software. The relationship between arterial stiffness, central hemodynamics, and all-cause mortality was investigated. Results In multivariable Cox regression analysis, high CAPP was significantly associated with all-cause mortality (hazard ratio: 0.263, 95% CI, 0.073–0.945, p = 0.041). Whole lung infection percentages were independently associated with high CAPP, with an area under the curve (AUC) of 0.662 and a specificity of 89.09%. Conclusions High CAPP, but not high AVI, demonstrated independent prognostic value for all-cause mortality in patients due to COVID-19 pneumonia infection. Evaluating this parameter could help in risk assessment and improve diagnostic and therapeutic strategies in viral pneumonia infections.

Right ventricular-pulmonary arterial coupling refers to the interaction and functional matching between the right ventricle and the pulmonary artery. When the coupling is disrupted, it can lead to a series of cardiovascular diseases, such as pulmonary hypertension, congenital heart disease, heart failure and so on. Therefore, it is important to evaluate cardiovascular structure and function. Cardiac magnetic resonance has the advantage of multi-parameter, multi-sequence, and high-resolution imaging, which can be used to comprehensively evaluate the cardiovascular system through cardiac magnetic resonance feature tracking technology, cardiac magnetic resonance cine imaging technology, T1 mapping, and T2 mapping imaging, and so on. This review summarizes the application and research progress of cardiac magnetic resonance technology in the assessment of the right ventricle and the pulmonary artery (RV-PA) coupling.

Yuanbaoshancha (YBSC) is characterized as a new wild tea relative morphologically and phytochemically distinguished from the closest wild tea plants Rongjiangcha (Camellia yungkiangensis, RJC) and Tulecha (Camellia costata, TLC). YBSC young leaves contain higher tea polyphenol and theobromine contents but lower caffeine and theanine as compared with RJC, TLC, and other tea landraces and modern cultivars. The major alkaloid detected in YBSC, TLC, and RJC is theobromine while caffeine is a minor; the primary catechins in YBSC leaves are non-galloylated catechins, significantly different from Camellia sinensis and other low-caffeine tea resources. The unique phytochemical profiles featured YBSC black tea with extremely lower caffeine and higher theobromine, as well as unique flavors and health benefits. This botanical characterization of YBSC and two related low-caffeine wild tea resources lays a foundation for future better utilization for the production of a highly valuable natural low-caffeine/high-theobromine tea. Chemical compounds: Caffeine (PubChem CID: 2519); Theobromine (PubChem CID: 5429); Catechins (PubChem CID: 9064); Epigallocatechin gallate (PubChem CID: 65064); Theanine (PubChem CID: 439378); Jasmone (PubChem CID: 1549018); cis-3-Hexenyl hexanoate (PubChem CID: 5352543); Hexyl 2-methylbutanoate (PubChem CID: 24838).

Competition among seaports has been becoming more and more fierce in current times, which has extended to the contest between transportation chains including seaports and their inland ports. Against this background, this paper studies competitive inland port location and pricing problem for an entering seaport under the condition that the incumbent competitive seaport has construct-ed inland transportation chains inside their overlapping hinterland. Specifically, this paper formulates a mixed-integer nonlinear program for the considered problem, in which we take packaged price and service time as influence factors for the inland transportation chains competition and characterize inland ports choice behaviors for shippers based on logit model. Additionally, this paper designs a hybrid heuristic method by integrating a genetic algorithm and an analytical method to solve location and pricing subproblems, respectively. Based on the computational results and sensitivity analysis, this paper provides some valuable suggestions on how to locate in-land ports and make price decisions for the new entering seaport.

BackgroundPatients using web-based health care communities for e-consultation services have the option to choose their service providers from an extensive digital market. To stand out in this crowded field, doctors in web-based health care communities often engage in prosocial behaviors, such as proactive and reactive actions, to attract more users. However, the effect of these behaviors on the volume of e-consultations remains unclear and warrants further exploration. ObjectiveThis study investigates the impact of various prosocial behaviors on doctors’ e-consultation volume in web-based health care communities and the moderating effects of doctors’ digital and offline reputations. MethodsA panel data set containing information on 2880 doctors over a 22-month period was obtained from one of the largest web-based health care communities in China. Data analysis was conducted using a 2-way fixed effects model with robust clustered SEs. A series of robustness checks were also performed, including alternative measurements of independent variables and estimation methods. ResultsResults indicated that both types of doctors’ prosocial behaviors, namely, proactive and reactive actions, positively impacted their e-consultation volume. In terms of the moderating effects of external reputation, doctors’ offline professional titles were found to negatively moderate the relationship between their proactive behaviors and their e-consultation volume. However, these titles did not significantly affect the relationship between doctors’ reactive behaviors and their e-consultation volume (P=.45). Additionally, doctors’ digital recommendations from patients negatively moderated both the relationship between doctors’ proactive behaviors and e-consultation volume and the relationship between doctors’ reactive behaviors and e-consultation volume. ConclusionsDrawing upon functional motives theory and social exchange theory, this study categorizes doctors’ prosocial behaviors into proactive and reactive actions. It provides empirical evidence that prosocial behaviors can lead to an increase in e-consultation volume. This study also illuminates the moderating roles doctors’ digital and offline reputations play in the relationships between prosocial behaviors and e-consultation volume.

Summary: Background: Leritrelvir is a novel α-ketoamide based peptidomimetic inhibitor of SARS-CoV-2 main protease. A preclinical study has demonstrated leritrelvir poses similar antiviral activities towards different SARS-CoV-2 variants compared with nirmatrelvir. A phase 2 clinical trial has shown a comparable antiviral efficacy and safety between leritrelvir with and without ritonavir co-administration. This trial aims to test efficacy and safety of leritrelvir monotherapy in adults with mild-to-moderate COVID-19. Methods: This was a randomised, double-blind, placebo-controlled, multicentre phase 3 trial at 29 clinical sites in China. Enrolled patients were from 18 to 75 years old, diagnosed with mild or moderate COVID-19 and not requiring hospitalization. Patients had a positive SARS-CoV-2 nucleic acid test (NAT) and at least one of the COVID-19 symptoms within 48 h before randomization, and the interval between the first positive SARS-CoV-2 NAT and randomization was ≤120 h (5 days). Patients were randomly assigned in a 1:1 ratio to receive a 5-day course of either oral leritrelvir 400 mg TID or placebo. The primary efficacy endpoint was the time from the first dose to sustained clinical recovery of all 11 symptoms (stuffy or runny nose, sore throat, shortness of breath or dyspnea, cough, muscle or body aches, headache, chills, fever ≥37 °C, nausea, vomiting, and diarrhea). The safety endpoint was the incidence of adverse events (AE). Primary and safety analyses were performed in the intention-to-treat (ITT) population. This study is registered with ClinicalTrials.gov, NCT05620160. Findings: Between Nov 12 and Dec 30, 2022 when the zero COVID policy was abolished nationwide, a total of 1359 patients underwent randomization, 680 were assigned to leritrelvir group and 679 to placebo group. The median time to sustained clinical recovery in leritrelvir group was significantly shorter (251.02 h [IQR 188.95–428.68 h]) than that of Placebo (271.33 h [IQR 219.00–529.63 h], P = 0.0022, hazard ratio [HR] 1.20, 95% confidence interval [CI], 1.07–1.35). Further analysis of subgroups for the median time to sustained clinical recovery revealed that (1) subgroup with positive viral nucleic acid tested ≤72 h had a 33.9 h difference in leritrelvir group than that of placebo; (2) the subgroup with baseline viral load >8 log 10 Copies/mL in leritrelvir group had 51.3 h difference than that of placebo. Leritrelvir reduced viral load by 0.82 log10 on day 4 compared to placebo. No participants in either group progressed to severe COVID-19 by day 29. Adverse events were reported in two groups: leritrelvir 315 (46.46%) compared with placebo 292 (43.52%). Treatment-relevant AEs were similar 218 (32.15%) in the leritrelvir group and 186 (27.72%) in placebo. Two cases of COVID-19 pneumonia were reported in placebo group, and one case in leritrelvir group, none of them were considered by the investigators to be leritrelvir related. The most frequently reported AEs (occurring in ≥5% of participants in at least one group) were laboratory finding: hypertriglyceridemia (leritrelvir 79 [11.7%] vs. placebo 70 [10.4%]) and hyperlipidemia (60 [8.8%] vs. 52 [7.7%]); all of them were nonserious. Interpretation: Leritrelvir monotherapy has good efficacy for mild-to-moderate COVID-19 and without serious safety concerns. Funding: This study was funded by the National Multidisciplinary Innovation Team Project of Traditional Chinese Medicine, Guangdong Science and Technology Foundation, Guangzhou Science and Technology Planning Project and R&D Program of Guangzhou Laboratory.

With the implementation of the Belt and Road Initiative, the inland ports planning is receiving more and more attention. In this work, we aim to determine the scale and function of different potential inland ports in a certain region while considering the cargo flow allocation schemes for the inland ports and seaports in cross-border trade. Unlike previous studies, we consider the dynamic interaction between local government and manufacturing enterprises in the inland port planning process. Based on this, we formulate a bilevel programming model for the considered inland port planning problem, where the upper-level focuses on the local government and the lower-level concentrates on the manufacturing enterprise. To solve the proposed model, we develop a hybrid heuristic algorithm by combining a genetic algorithm and an exact solution method. Furthermore, we conduct a case study of the inland ports planning for the Huaihai Economic Zone in China to verify the applicability of the proposed model and algorithm. The computational results demonstrate that the proposed optimization approach can effectively increase the cross-border transportation market share of inland ports within a limited investment amount and reduce the competition among these inland ports. Our case study also provides valuable management insights on inland port planning in terms of manufacturing enterprises weights, investment limit amount, scale effect, and cargo value weights.

Inland ports are gaining more and more attention as important hubs for inland cities to promote foreign trade. However, studies on the evaluation of inland ports are lacking. In this work, we aim to construct an index system and propose a multi-criteria group decision-making method to comprehensively evaluate the development of inland ports. Unlike previous studies, using pressure–state–response model as a reference, we built up a demand–risk–power–potential framework for the index system proposed in this study. To determine the different weights for each indicator, which is a typical multi-criteria decision-making problem, we innovatively combined the decision-making trial and evaluation laboratory (DEMATEL) and the Bayesian best–worst method (BBWM) based on their distinct advantages in dealing with data coupling and group decision-making. In addition, this work introduces a case study of inland ports in the Huaihai Economy Zone to validate the efficacy of the proposed evaluation model and method. After calculating and obtaining the comprehensive scores and rankings of each inland port in this case, we compared the evaluation results with those under the BBWM, TOPSIS, and CRITIC methodologies, and found that the results under the DEMATEL–BBWM methodology can provide better differentiation for inland port evaluation results. Moreover, based on the evaluation results, a performance–importance matrix is formulated to identify the areas requiring attention in the development process of each inland port. Subsequently, rational managerial insights are put forward to achieve the sustainable development of inland ports in the Huaihai Economy Zone.

With the outbreak of COVID-19 pandemic, the problem of supply chain emergency scheduling has had a great influence on economic benefits of enterprises. The uncertainty of the COVID-19 pandemic and uncertainty of supply chain have made the problem of emergency scheduling more complicated. In this study, a multiobjective multiperiod mixed-integer programming optimization model was developed, in which two conflicting benefit factors, cost and service level were taken as the optimization target of the model. Cost and service level were normalized, and the weighted sum was taken as the objective function, which transformed the problem into a multiperiod nonlinear one. Two algorithms of Bi-level Modified Hybrid Genetic Algorithm (BMHGA) and Bi-level Hybrid Genetic Algorithm (BHGA) were designed to solve the model. Three emergency strategies have been proposed, including enabling alternative suppliers, repairing failure nodes and enabling internal suppliers’ flexibility. The parameter of disruption scenario and its solution method were designed. Finally, the practicability of the proposed model and algorithm was demonstrated through application to a case study of an electronics supply chain. The results indicated that the optimal solution of two algorithms was between 2%-5%, and BMHGA could obtain a better optimal solution.

The problem of integrated scheduling of supply chains has a huge impact on operational efficiency and cost effectiveness. Increasing number of the nodes, different time window constraints for customers, and a variety of uncertain scenarios complicate supply chain scheduling. In the study a multi-objective multi-period mixed-integer programming optimization model was developed. We comprehensively considered the effects of demand uncertainty, time window constraints, constraints of node capability, and multi-period and sub-period factors. The conflicting benefit factors, cost and service level are the two optimization objectives. The first objective function aims to minimize the total cost in all periods. The second objective function considers service level by minimizing the material flow of out-of-stock items in all periods to maximize service level. Suppliers’ capacity, selection of suppliers, manufacturers’ productivity, transaction relationship, sub-period time, inventory capacity and lead time for delivery are also considered. Subsequently the total costs and service levels are normalized, whose sum is the objective function. The problem was transformed into a multi-period non-linear optimization problem. An improved mixed Genetic Algorithm was designed to solve the model. Finally, the practicability of the proposed model and algorithm is demonstrated through its application to an electronics supply chain case study. The results indicate that the proposed model and algorithm can provide a promising approach for fulfilling a multi-objective multi period integrated scheduling plan under uncertain demand scenarios.

Objective: To investigate the correlation between the DCE-CT imaging biomarkers and histological biomarkers of tumor angiogenesis in adrenal adenomas and non-adenomas for the enhancement mechanism of DCE-CT. Methods: Forty-two patients with 45 adrenal masses including 27 adenomas and 18 non-adenomas diagnosed pathologically were enrolled in this study. The features of DCE-CT (imaging biomarkers) and tumor angiogenesis (histological biomarkers) in adrenal masses were evaluated, and their correlations were explored. Results: The enhanced features of DCE-CT in adrenal masses were classified: rapid washout group and slow washout group. Type A and C of time density (TD) curves, relative washout rate (Washr) ≥34%, and absolute washout rate (Washa) ≥43% belonged to the rapid group. In contrast, type B, D and E, Washr

Apolipoprotein C1 (APOC1) has been found to play an essential part in proliferation and metastasis of numerous cancers, but related mechanism has not been elucidated, especially its function and role in tumor immunity. Through systematic pan-cancer analysis, we identified that APOC1 was closely associated with the infiltration of various immune cells in multiple cancers. Besides, APOC1 was significantly co-expressed with the immune checkpoints, major histocompatibility complex (MHC) molecules, chemokines and other immune-related genes. Furthermore, single-cell sequencing analysis suggested that the vast majority of APOC1 was expressed in macrophages or tumor-associated macrophages (TAMs). Additionally, the expression of APOC1 was significantly related to the prognosis of different cancers. Since APOC1 was most significantly abnormally expressed in renal cell cancer (RCC), subsequent experiments were carried out in RCC to explore the role of APOC1 in tumor immunity. The expression of APOC1 was significantly elevated in the tumor and serum of RCC patients. Besides, APOC1 was mainly expressed in the macrophage and it was closely related to the immune cell infiltration of RCC. Co-culture with RCC cells could induce the generation of TAMs with M2 phenotype which be blocked by silencing APOC1. The expression of APOC1 was elevated in the M2 or TAMs and APOC1 promoted M2 polarization of macrophages through interacting with CD163 and CD206. Furthermore, macrophages overexpressing APOC1 promoted the metastasis of RCC cells via secreting CCL5. Together, these data indicate that APOC1 is an immunological biomarker which regulates macrophage polarization and promotes tumor metastasis.

The importance of inland ports in promoting current cross-border trade is increasingly recognized. In this work, we aim to design the entire network for the cross-border multimodal container transport system based on inland ports. Unlike previous studies, we consider strong uncertainty in cross-border transportation demand to be caused by a variety of realistic factors such as the global economic situation, trade policies among countries, and global epidemics, etc. To handle the demand uncertainty, we develop an uncertain programming model for the considered cross-border multimodal container transportation network design problem to minimize the expectation of the total costs, including carbon emissions, by imposing two types of chance constraints for capacity limitations. Under mild assumptions, we further convert the proposed uncertain model into its equivalent deterministic one, which can be solved by off-the-shelf solvers such as CPLEX, Gurobi, and Lingo. Finally, we illustrate the applicability of the proposed model by taking the Huaihai Economic Zone-Europe multimodal container transport system as a real-world case study. The computational results provide valuable suggestions and policy guidance regarding four issues: the inland port locations, the transportation route choices, the strategies for reducing the total cost, and the schemes for improving network performance against uncertain demand.

Driven by China’s booming natural gas consumption market, LNG (Liquified Natural Gas) shipping import has grown rapidly. To facilitate scientific and efficient decision making on LNG shipping fleet deployment and the development of the LNG shipping industry, this article proposes an optimization model to minimize annual fleet operating costs, including voyage cost, running cost, and capital cost. Under the consideration of the mixed factors of self-owned and time charter vessels, epidemic prevention and control, port congestion, transportation time cost, and evaporation loss, as well as navigation security and emergency situations, the validity and optimality of the model are demonstrated by the empirical example and the cost comparison between the conventional and optimized solution. The results show that this optimization model can reduce the total cost by 9.87%. Then, through sensitivity analysis, various significant factors affecting the operating costs of LNG shipping enterprises and their degrees of influence are determined. Based on the analysis of the relevant causes, some actionable countermeasures are recommended, including establishing a shipping price reciprocity mechanism and full chain investment planning, optimizing the inbound link to reduce invalid berthing time, strengthening the construction competitiveness and economy of scale of larger LNG ships, and building a combined dual resource pool transportation mode. This paper contributes to improving transregional maritime energy transport and management capacity, while further enhancing the energy security and development of port cities and their economic hinterlands.

Dendritic cells (DCs) are the most potent antigen-presenting cells. Upon maturation, DCs express costimulatory molecules and migrate to the lymph nodes to present antigens to T cells. The actin cytoskeleton plays key roles in multiple aspects of DC functions. However, little is known about the mechanisms and identities of actin-binding proteins that control DC maturation and maturation-associated functional changes. Tropomodulin1 (Tmod1), an actin-capping protein, controls actin depolymerization and nucleation. We found that Tmod1 was expressed in bone marrow-derived immature DCs and was significantly upregulated upon lipopolysaccharide (LPS)-induced DC maturation. By characterizing LPS-induced mature DCs (mDCs) from Tmod1 knockout mice, we found that compared with Tmod1+/+ mDCs, Tmod1-deficient mDCs exhibited lower surface expression of costimulatory molecules and chemokine receptors and reduced secretion of inflammatory cytokines, suggesting that Tmod1 deficiency retarded DC maturation. Tmod1-deficient mDCs also showed impaired random and chemotactic migration, deteriorated T-cell stimulatory ability, and reduced F-actin content and cell stiffness. Furthermore, Tmod1-deficient mDCs secreted high levels of IFN-β and IL-10 and induced immune tolerance in an experimental autoimmune encephalomyelitis (EAE) mouse model. Mechanistically, Tmod1 deficiency affected TLR4 signaling transduction, resulting in the decreased activity of MyD88-dependent NFκB and MAPK pathways but the increased activity of the TRIF/IRF3 pathway. Rescue with exogenous Tmod1 reversed the effect of Tmod1 deficiency on TLR4 signaling. Therefore, Tmod1 is critical in regulating DC maturation and immune functions by regulating TLR4 signaling and the actin cytoskeleton. Tmod1 may be a potential target for modulating DC functions, a strategy that would be beneficial for immunotherapy for several diseases.

BACKGROUND:Constructing a medical image feature database according to the category of disease can achieve a quick retrieval of images with similar pathological features. Therefore, this approach has important application values in the fields such as auxiliary diagnosis, teaching, research, and telemedicine. METHODS:Based on the deep convolutional neural network, an image classifier applicable to brain disease was designed to distinguish between the image features of the different brain diseases with similar anatomical structures. Through the extraction and analysis of visual features, the images were labelled with the corresponding semantic features of a specific disease category, which can establish an association between the visual features of brain images and the semantic features of the category of disease which will permit to construct a disease category feature database of brain images. RESULTS:Based on the similarity measurement and the matching strategy of high-dimensional visual feature, a high-precision retrieval of brain image with semantics category was achieved, and the constructed disease category feature database of brain image was tested and evaluated through large numbers of pathological image retrieval experiments, the accuracy and the effectiveness of the proposed approach was verified. CONCLUSION:The disease category feature database of brain image constructed by the proposed approach achieved a quick and effective retrieval of images with similar pathological features, which is beneficial to the categorization and analysis of intractable brain diseases. This provides an effective application tool such as case-based image data management, evidence-based medicine and clinical decision support.

As information and communication technology evolves and expands, business and markets are linked to form a complex international network, thus generating plenty of cross-border trading activities in the supply chain network. Through the observations from a typical cross-border supply chain network, this paper introduces the fuzzy reliability-oriented 2-hub center problem with cluster-based policy, which is a special case of the well-studied hub location problem (HLP). This problem differs from the classical HLP in the sense that (i) the hub-and-spoke (H&S) network is grouped into two clusters in advance based on their cross-border geographic features, and (ii) a fuzzy reliability optimization approach based on the possibility measure is developed. The proposed problem is first modeled through a mixed-integer nonlinear programming (MINLP) formulation that maximizes the reliability of the entire cross-border supply chain network. Then, some linearization techniques are implemented to derive a linear model, which can be efficiently solved by exact algorithms run by CPLEX for only small instances. To counteract the difficulty for solving the proposed problem in realistic-sized instances, a tabu search (TS) algorithm with two types of move operators (called “Swap I” and “Swap II”) is further developed. Finally, a series of numerical experiments based on the Turkish network and randomly generated large-scale datasets are set up to verify the applicability of the proposed model as well as the superiority of the TS algorithm compared to the CPLEX.

Polygonatum kingianum Collett & Hemsl is one of the famous traditional Chinese herbs with satisfactory therapeutic effects on invigorating Qi, nourishing Yin and moistening lungs, in which steroidal saponins are one class of important active substances. The main purpose is to determine the optimal extraction technology of steroidal saponins and evaluate the quality of P. kingianum planted in five different areas. The optimal ultrasonic-assisted extraction (UAE) technology was established by using single-factor experiments and the response surface methodology (RSM), and the determination method of high-performance liquid chromatography (HPLC) for dioscin and diosgenin, two primary types of acid-hydrolyzed steroidal saponins, was constructed with good linear range and precision. The results showed that UAE was an efficient extraction method for steroidal saponins, and the extraction yield was significantly affected by the liquid-solid ratio. The optimal extraction technology was generated following a liquid-solid ratio of 10:1 (mL/g), an ethanol concentration of 85% (v/v), an extraction time of 75 min, an extraction temperature of 50 °C and three extractions, of which these parameters were in line with the predicted values calculated by RSM. Considering only dioscin and diosgenin, the quality of P. kingianum planted at five sample plots presented non-significant difference. However, the content of diosgenin in Pingbian Prefecture (PB) was higher than that of the other four areas with a value of 0.46 mg/g. Taken together, the optimal UAE technology for P. kingianum steroidal saponins was determined via RSM. The quality evaluation revealed that there was a non-significant difference among P. kingianum planted in different areas based on the contents of the sum of dioscin and diosgenin. This work has important reference value for the exploitation and utilization of P. kingianum.

Abstract While natural killer (NK) cell‐based adoptive transfer immunotherapy (ATI) provides only modest clinical success in cancer patients. This study was hypothesized that MRI‐guided transcatheter intra‐hepatic arterial (IHA) infusion permits local delivery to liver tumors to improve outcomes during NK‐based ATI in a rat model of hepatocellular carcinoma (HCC). Mouse NK cells were labeled with clinically applicable iron nanocomplexes. Twenty rat HCC models were assigned to three groups: transcatheter IHA saline infusion as the control group, transcatheter IHA NK infusion group, and intravenous (IV) NK infusion group. MRI studies were performed at baseline and at 24 h, 48 h, and 8 days postinfusion. There was a significant difference in tumor R2* values between baseline and 24 h following the selective transcatheter IHA NK delivery to the tumors (P = 0.039) when compared to IV NK infusion (P = 0.803). At 8 days postinfusion, there were significant differences in tumor volumes between the control, IV, and IHA NK infusion groups (control vs. IV, P = 0.196; control vs. IHA, P

Supply risk can have a negative impact on a manufacturer’s performance. Backup sourcing is one of the most commonly used strategies to mitigate the adverse consequences of supply risks. In this paper, we study a procurement strategy with backup sourcing when a manufacturer faces stochastic supply risk and demand. The optimal decisions of the players involved are investigated theoretically using the game theoretic framework, and the impacts of the key parameters, such as wholesale prices and the risk probability, are assessed numerically under supply information symmetry and asymmetry. The results illustrate that the reservation price provided by the backup supplier varies greatly under different information-sharing conditions. Reservation quantity is negatively correlated with the reservation price, which is affected by the risk probability, wholesale prices, and marginal cost of the backup supplier. We also show that given the same wholesale prices, the potential supply risk has a substantial impact on the manufacturer’s expected profit, and the performance of the manufacturer under asymmetrical supply information is not always better than that under symmetrical information. In addition, we also discuss the impact of wholesale prices on reservation price and participants’ profits based on numerical examples. The research enriches the understanding of a procurement strategy under stochastic supply risk, and the conclusions have certain management significance.

Manufacturers add online direct channels that inevitably engage in channel competition with offline retail channels. Since price is an important factor in consumers' choice of purchasing channel, pricing strategy has become a popular topic for research on dual-channel competition and coordination. In contrast to previous research on pricing strategies based on the full rationality of members, we focus on the impact of retailers' fairness concerns on pricing strategies. In this study, the hybrid dual-channel supply chain consists of one manufacturer with a direct channel who acts as the leader and a retailer who acts as the follower. First, we use the Stackelberg game approach to determine the equilibrium pricing strategy for a fair caring retailer. Simultaneously, we consider a centralized dual-channel supply chain as the benchmark for a comparative analysis of the efficiency of a decentralized supply chain. Furthermore, we study pricing strategies when the retailer has fairness concerns and determine the complete equilibrium solutions for different ranges of the parameters representing cross-price sensitivity and fairness. Finally, through numerical experiments, the pricing strategies, the profit and utility of the manufacturer and retailer, and the channel efficiency of the supply chain are compared and analysed for two scenarios. We find that fairness concerns reduce the manufacturer's profits, while for the most part, the retailers’ profit can be improved; however, the supply chain cannot achieve complete coordination.

With the deepening of the research on supply chain management, scholars have increasingly begun to investigate the impact of fairness on a supply chain, and many conclusions suggest that a simple wholesale price can coordinate a supply chain under specific conditions. However, the corresponding analysis and other optimization mechanisms that affect the situation in which the channel cannot be coordinated are either omitted or given little attention. In this paper, we constructed a dyadic supply chain with a single manufacturer and a single retailer; the manufacturer acts as a selfish leader, and the retailer acts as a follower with fairness concerns and sales efforts. For this setting, we derived the equilibrium strategy solution for a wholesale price contract and cost sharing of effort (CS-E) contract offered by the manufacturer, and the results indicated that both contracts achieved channel coordination with different requirements. Further, the profit of the manufacturer and the sales effort of the retailer under CS-E contracts were never less than those for the wholesale price contract, and there was an interval during which the retailer's profit and utility and supply chain efficiency were better than those under the wholesale price contract. In addition, we described situations in which a CS-E contract is unnecessary. These results should be a useful reference for managerial decisions and organizations.

This study proposes a mathematical model of clustered multi-temperature joint distribution in fuzzy environment. In this model, a Z-shaped function is used to depict customer satisfaction. For the imprecise model, triangular fuzzy numbers are used to represent travel times. By redefining the movement procedure of fireflies, two versions of discrete firefly algorithms are developed, which differ in the population initialization strategy. Finally, experiments are carried out and computational results are reported to confirm the effectiveness of the proposed algorithms.

This paper proposes a reliable facility location design model under imperfect information with site-dependent disruptions; i.e., each facility is subject to a unique disruption probability that varies across the space. In the imperfect information contexts, customers adopt a realistic "trial-and-error" strategy to visit facilities; i.e., they visit a number of pre-assigned facilities sequentially until they arrive at the first operational facility or give up looking for the service. This proposed model aims to balance initial facility investment and expected long-term operational cost by finding the optimal facility locations. A nonlinear integer programming model is proposed to describe this problem. We apply a linearization technique to reduce the difficulty of solving the proposed model. A number of problem instances are studied to illustrate the performance of the proposed model. The results indicate that our proposed model can reveal a number of interesting insights into the facility location design with site-dependent disruptions, including the benefit of backup facilities and system robustness against variation of the loss-of-service penalty.

In the management of intermodal transportation, incentive contract design problem has significant impacts on the benefit of a multimodal transport operator (MTO). In this paper, we analyze a typical water-rail-road (WRR) intermodal transportation that is composed of three serial transportation stages: water, rail and road. In particular, the entire transportation process is planned, organized, and funded by an MTO that outsources the transportation task at each stage to independent carriers (subcontracts). Due to the variability of transportation conditions, the travel time of each transportation stage depending on the respective carrier’s effort level is unknown (asymmetric information) and characterized as an uncertain variable via the experts’ estimations. Considering the decentralized decision-making process, we interpret the incentive contract design problem for the WRR intermodal transportation as a Stackelberg game in which the risk-neutral MTO serves as the leader and the risk-averse carriers serve as the followers. Within the framework of uncertainty theory, we formulate an uncertain bi-level programming model for the incentive contract design problem under expectation and entropy decision criteria. Subsequently, we provide the analytical results of the proposed model and analyze the optimal time-based incentive contracts by developing a hybrid solution method which combines a decomposition approach and an iterative algorithm. Finally, we give a simulation example to investigate the impact of asymmetric information on the optimal time-based incentive contracts and to identify the value of information for WRR intermodal transportation.

The membrane skeleton of mature erythrocyte is formed during erythroid differentiation. Fluid shear stress is one of the main factors that promote embryonic hematopoiesis, however, its effects on erythroid differentiation and cytoskeleton remodeling are unclear. Erythrocyte tropomodulin of 41 kDa (E-Tmod41) caps the pointed end of actin filament (F-actin) and is critical for the formation of hexagonal topology of erythrocyte membrane skeleton. Our study focused on the regulation of E-Tmod41 and its role in F-actin cytoskeleton remodeling during erythroid differentiation induced by fluid shear stress. Mouse erythroleukemia (MEL) cells and embryonic erythroblasts were subjected to fluid shear stress (5 dyn/cm2) and erythroid differentiation was induced in both cells. F-actin content and E-Tmod41 expression were significantly increased in MEL cells after shearing. E-Tmod41 overexpression resulted in a significant increase in F-actin content, while the knockdown of E-Tmod41 generated the opposite result. An E-Tmod 3'UTR targeting miRNA, miR-23b-3p, was found suppressed by shear stress. When miR-23b-3p level was overexpressed / inhibited, both E-Tmod41 protein level and F-actin content were reduced / augmented. Furthermore, among the two alternative promoters of E-Tmod, PE0 (upstream of exon 0), which mainly drives the expression of E-Tmod41, was found activated by shear stress. In conclusion, our results suggest that fluid shear stress could induce erythroid differentiation and F-actin cytoskeleton remodeling. It upregulates E-Tmod41 expression through miR-23b-3p suppression and PE0 promoter activation, which, in turn, contributes to F-actin cytoskeleton remodeling.

We evaluated the correlation between computed tomography (CT) perfusion parameters and markers of angiogenesis in adrenal adenomas and non-adenomas to determine if perfusion CT can be used to distinguish between them. Thirty-four patients with pathologically-confirmed adrenal tumors (17 adenomas, 17 non-adenomas) received CT perfusion imaging before surgery. CT perfusion parameters (blood flow [BF], blood volume [BV], mean transit time [MTT], and permeability surface area product [PS]) were calculated. Tumor tissue sections were examined with immunohistochemical methods for vascular endothelial growth factor (VEGF) expression and microvessel density (MVD). The mean age of the 34 patients was 43 years. The median BV was significantly higher in adenomas than in non-adenomas [12.3 ml/100 g, inter-quartile range (IQR): 10.4 to 16.5 ml/100 g vs. 8.8 ml/100 g, IQR: 3.3 to 9.4 ml/100 g, p=0.001]. Differences in BF, MTT, and PS parameter values between adenomas and non-adenomas were not significant (p>0.05). The mean MVD was significantly higher in adenomas compared to non-adenomas (98.5 ± 28.5 vs. 53.5 ± 27.0, p