DCM: D Number Extended Cognitive Map. Application on Location Selection in SCM

Offshore outsourcing is a widely used management technique for performing business functions with the aim of reducing labor and transportation costs. The selection of locations has a significant influence on the supply chain’s resilience and qualities, but the influence of multiple external factors on the supply chain’s performance in local places in a complex and uncertain environment has not been examined. In this study, we investigated the influence of external factors in a highly uncertain and complicated situation in which relationships between external factors and supply chain resilience are complicated. Furthermore, we proposed a novel model to select locations from a comprehensive perspective. Specifically, the fuzzy cognitive map (FCM) is utilized to simulate the dynamic influence process where the adjacency is aggregated by D numbers. The weights of different resilience capabilities are considered from the perspective of maximizing benefits by using the decision-making trial and evaluation laboratory-analytic network processes (DEMATEL-ANP) model. By comparing the distance to the ideal solutions, we selected the best alternative location. Our results differ from the general case, which reveals that the weights of different capabilities influence selections

Text to realistic image generation with attentional concatenation generative adversarial networks.

In this paper, we propose an Attentional Concatenation Generative Adversarial Network (ACGAN) aiming at generating 1024 × 1024 high-resolution images. First, we propose a multilevel cascade structure, for text-to-image synthesis. During training progress, we gradually add new layers and, at the same time, use the results and word vectors from the previous layer as inputs to the next layer to generate high-resolution images with photo-realistic details. Second, the deep attentional multimodal similarity model is introduced into the network, and we match word vectors with images in a common semantic space to compute a fine-grained matching loss for training the generator. In this way, we can pay attention to the fine-grained information of the word level in the semantics. Finally, the measure of diversity is added to the discriminator, which enables the generator to obtain more diverse gradient directions and improve the diversity of generated samples. The experimental results show that the inception scores of the proposed model on the CUB and Oxford-102 datasets have reached 4.48 and 4.16, improved by 2.75% and 6.42% compared to Attentional Generative Adversarial Networks (AttenGAN). The ACGAN model has a better effect on text-generated images, and the resulting image is closer to the real image

Application of Angiotensin Receptor–Neprilysin Inhibitor in Chronic Kidney Disease Patients: Chinese Expert Consensus

Chronic kidney disease (CKD) is a global public health problem, and cardiovascular disease is the most common cause of death in patients with CKD. The incidence and prevalence of cardiovascular events during the early stages of CKD increases significantly with a decline in renal function. More than 50% of dialysis patients die from cardiovascular disease, including coronary heart disease, heart failure, arrhythmia, and sudden cardiac death. Therefore, developing effective methods to control risk factors and improve prognosis is the primary focus during the diagnosis and treatment of CKD. For example, the SPRINT study demonstrated that CKD drugs are effective in reducing cardiovascular and cerebrovascular events by controlling blood pressure. Uncontrolled blood pressure not only increases the risk of these events but also accelerates the progression of CKD. A co-crystal complex of sacubitril, which is a neprilysin inhibitor, and valsartan, which is an angiotensin receptor blockade, has the potential to be widely used against CKD. Sacubitril inhibits neprilysin, which further reduces the degradation of natriuretic peptides and enhances the beneficial effects of the natriuretic peptide system. In contrast, valsartan alone can block the angiotensin II-1 (AT1) receptor and therefore inhibit the renin–angiotensin–aldosterone system. These two components can act synergistically to relax blood vessels, prevent and reverse cardiovascular remodeling, and promote natriuresis. Recent studies have repeatedly confirmed that the first and so far the only angiotensin receptor–neprilysin inhibitor (ARNI) sacubitril/valsartan can reduce blood pressure more effectively than renin–angiotensin system inhibitors and improve the prognosis of heart failure in patients with CKD. Here, we propose clinical recommendations based on an expert consensus to guide ARNI-based therapeutics and reduce the occurrence of cardiovascular events in patients with CKD

Memory

Entry for the 10th Baker & Whitehill Student Artists\u27 Book Contest. Opening Reception Thursday, February 29th, 2024 Fleet Library, Main Reading Room. Juror: Ian Cozzens BArch 05.https://digitalcommons.risd.edu/bookcontest10th2024/1057/thumbnail.jp

Destination Service Encounter Modeling and Relationships with Tourist Satisfaction

Tourists are in contact with two types of services at destinations: enterprise services offered by tourism enterprises (e.g., hotels, shops, restaurants, etc.) and public services (public transportation, public information, public safety, etc.) provided by the local government. Following Churchill’s (1979) procedures, a model of destination service encounters (DSEs), including four dimensions (i.e.,enterprise personal interaction encounters (EPIEs), enterprise physical environment encounters (EPEEs), public personal interaction encounters (PPIEs), public physical environment encounters (PPEEs), and 10 subdimensions, was constructed. Then, the effects of DSEs on tourist satisfaction (TS) were tested with data collected in Shaoshan Township, China. The results revealed that EPIEs, PPIEs, and PPEEs had significant positive effects on TS. This model promotes the application of service encounter (SE) theory in destination management, and it offers implications for the synergy management of public and private sectors at destinations to improve tourist experiences

Cayley Graphs Defined by Systems of Equations

Let R be a finite ring. In this paper, we mainly explore the conditions to ensure the graph BΓn defined by a system of equations {fi|i=2,…,n} to be a Cayley graph or a Hamiltonian graph. More precisely, we prove that BΓn is a Cayley graph with G=⟨ϕ,A⟩ a group of dihedral type if and only if the system Fn={fi|i=2,…,n} is Cayley graphic of dihedral type in R. As an application, the well-known Lova´sz Conjecture, which states that any finite connected Cayley graph has a Hamilton cycle, holds for the connected BΓn defined by Cayley graphic system Fn of dihedral type in the field GF(pk)

A Model of High-Dimensional Feature Reduction Based on Variable Precision Rough Set and Genetic Algorithm in Medical Image

Aiming at the shortcomings of high feature reduction using traditional rough sets, such as insensitivity with noise data and easy loss of potentially useful information, combining with genetic algorithm, in this paper, a VPRS-GA (Variable Precision Rough Set--Genetic Algorithm) model for high-dimensional feature reduction of medical image is proposed. Firstly, rigid inclusion of the lower approximation is extended to partial inclusion by classification error rate β in the traditional rough set model, and the ability dealing with noise data is improved. Secondly, some factors of feature reduction are considered, such as attribute dependency, attributes reduction length, and gene coding weight. A general framework of fitness function is put forward, and different fitness functions are constructed by using different factors such as weight and classification error rate β. Finally, 98 dimensional features of PET/CT lung tumor ROI are extracted to build decision information table of lung tumor patients. Three kinds of experiments in high-dimensional feature reduction are carried out, using support vector machine to verify the influence of recognition accuracy in different fitness function parameters and classification error rate. Experimental results show that classification accuracy is affected deeply by different weight values under the invariable classification error rate condition and by increasing classification error rate under the invariable weigh value condition. Hence, in order to achieve better recognition accuracy, different problems use suitable parameter combination

Evidential Analytic Hierarchy Process Dependence Assessment Methodology in Human Reliability Analysis

In human reliability analysis, dependence assessment is an important issue in risky large complex systems, such as operation of a nuclear power plant. Many existing methods depend on an expert's judgment, which contributes to the subjectivity and restrictions of results. Recently, a computational method, based on the Dempster–Shafer evidence theory and analytic hierarchy process, has been proposed to handle the dependence in human reliability analysis. The model can deal with uncertainty in an analyst's judgment and reduce the subjectivity in the evaluation process. However, the computation is heavy and complicated to some degree. The most important issue is that the existing method is in a positive aspect, which may cause an underestimation of the risk. In this study, a new evidential analytic hierarchy process dependence assessment methodology, based on the improvement of existing methods, has been proposed, which is expected to be easier and more effective

Cloning and Bioinformatics Analysis of pepck Gene in Vibrio alginolyticus

[Objectives] To clone the pepck gene of Vibrio alginolyticus strain HY9901 and analyze its sequence by bioinformatics. [Methods] According to the complete gene sequence of V. alginolyticus on GenBank, specific primers were designed to amplify the target gene pepck by PCR. The sequence of the pepck gene was analyzed using bioinformatics. The phylogenic tree of pepck gene and the corresponding single-subunit three-dimensional structure were constructed. [Results] The pepck gene of V. alginolyticus strain HY9901 has a full length of 1 629 bp, with theoretical molecular weight of 60.12 kD. The prediction results show that there is no signal peptide or transmembrane region at the N-terminus of the sequence, the amino acid sequence contains 11 phosphorylation sites of casein kinase II. The prediction results of protein subcellular localization indicate that PEPEK protein is localized in the cytoplasm. The protein is stable and hydrophobic. The tertiary structure of the PEPCK protein of V. alginolyticus is similar to that of Vibrio parahaemolyticus. It is predicted that PEPCK has a major functional domain PEPCK_ATP. In the secondary structure, alpha helix, random coil, and extended strand accounted for 21.96%, 52.03% and 26.01%, respectively. The PEPCK homology between V. alginolyticus and Vibrio diabolicus is as high as 99%. [Conclusions] This study lays the foundation for further understanding the function of pepck gene in V. alginolyticus