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Background: Determining the source of infection is significant for the treatment of bloodstream infections (BSI). The gold standard of blood infection detection, blood cultures, have low positive rates to meet clinical needs. In this study, we investigated the ability of hybrid capture-based next generation sequencing technology to detect pathogens in peripheral blood samples collected from patients with suspected BSI. Blood cultures and capture sequencing assays were also analyzed against the final clinical diagnoses. Methods: In this study, peripheral blood samples were collected from patients with fever, chills, and suspected BSI at Jinshazhou Hospital of Guangzhou University of Chinese Medicine from March 2023 to January 2024. All samples were tested by three different technologies: plasma capture sequencing technology, white blood cell capture sequencing technology, and blood culture. Relevant clinical diagnostic information was also collected. The performances of the blood cultures were then compared to those of both plasma capture sequencing technology and white blood cell capture sequencing technology. Results: A total of 98 patients were included in this study. The positive rates of probe capture next generation sequencing (NGS technology) in plasma and white blood cells were 81.63% and 65.31%, respectively, which were both significantly higher than that of the blood culture, which was 21.43% (p < 0.001). Taking blood culture as the standard control, the sensitivity and specificity of plasma capture sequencing were 85.71% and 71.43%, respectively, while the sensitivity and specificity of white blood cell sequencing were 76.19% and 81.82%, respectively. Upon final clinical diagnosis, the clinical agreement rates of the blood cultures, plasma capture sequencing, and white blood cell capture sequencing were 39.80%, 83.67%, and 73.47%, respectively. Conclusion: Our study demonstrates the high accuracy of probe capture sequencing technology compared to blood cultures in the identification of pathogenic microorganisms in BSI upon final clinical diagnosis. Among the different sample types, white blood cell samples had a lower clinical compliance rate compared to plasma samples, possibly due to the higher host rate in cell samples, which impairs the sensitivity of pathogen detection. [ABSTRACT FROM AUTHOR]

Purpose: Low water resource utilization rate, water environment pollution, and water ecology deterioration are unfavorable factors restricting the high-quality development of the Yellow River basin and the coordinated development of the region, and industrial linkage is an important mechanism to promote the regional "pole-diffusion" effect. Currently, the water resource constraints of the Yellow River basin are close to the upper limit; in this context, how to enhance the industrial linkage between regions, promote the coordinated development of resources and economy in the Yellow River basin, and construct new "growth poles" of high-quality development has become an important proposition. Methods: By analyzing the mechanism of water resource constraints affecting industrial linkage and constructing a mediation effect model, we investigate the transmission mechanism of water resource constraints affecting industrial linkage through virtual water trade and optimization of industrial structure. Results: The results show that water resource constraints significantly inhibit the development of industrial linkage in the whole basin, but enhance the development of industrial linkage through the promotion of virtual water trade and optimization of industrial structure; in terms of subregions, there are differences in the mediation effect in the Yellow River basin in the regions with advantages in agriculture and animal husbandry, in the regions with advantages in the energy industry, and in the regions with advantages in the emerging industry and advanced manufacturing industry. Inspiration: This study has several aims: first, the rational use of the virtual water trade model of the Yellow River basin; second, use of the basin as a whole to promote the upgrading of industrial structure; third, the development of water resource rigid constraints in accordance with local conditions to promote the sustainable development of the economy; and fourth, promotion of the construction of the industrial community of the whole basin to realize the synergistic high-quality development of the Yellow River basin. Marginal contribution: In the study of high-quality development in the Yellow River basin, the existing literature focuses on the optimization of the industrial layout and industrial structure based on the theory of resource advantage and industrial division of labor. Based on this, this article analyzes the impact of water resource constraints on the industrial linkage of regions with advantages in agriculture and animal husbandry, energy industry, and emerging industry and advanced manufacturing industry from the perspective of the adaptability of water resources to the layout of productive forces and puts forward the proposal of coordinating the linkage development of industries in the whole river basin, which promotes the research on the relationship between water resources and industries. [ABSTRACT FROM AUTHOR]

Context: Explore the incentive for farmers to save water by confirming the rights of agricultural water in the Yellow River Basin. Aims: To explore the incentives of water-rights confirmation in agriculture and its transmission mechanism for water conservation among farmers and explore the incentive measures for farmers to save water. Methods: Quantitative research method. Key results: Water-rights confirmation in agriculture influences farmers' willingness to conserve water and the amount of investment in water conservation through security effects, credit effects and transaction effects. Conclusions: The deepening of agricultural water ownership will increase farmers' willingness to save water and their investment amount. Implications: Clarify the transmission mechanism of agricultural water rights for farmers' water saving. On the basis of research data from nine provinces in the Yellow River Basin, this study explored the incentives of water-rights confirmation in agriculture and its transmission mechanism for water conservation among farmers. The research findings indicated that water-rights confirmation in agriculture influences farmers' willingness to conserve water and the amount of investment in water conservation. This article belongs to the collection Ecological Monitoring and Assessment of Freshwater Ecosystems: New Trends and Future Challenges. [ABSTRACT FROM AUTHOR]

This paper enhances the agent model of ordinary individuals by incorporating the roles of places in the transmission, prevention, and control in the process, establishing a fundamental connection between these two types of agents through individual travel rules. The impact of real-world prevention and control measures on regional epidemic transmission is studied based on this model. Firstly, based on the analysis of place elements in typical cases of major infectious diseases, we give the classification of places. Secondly, the resident agent and the place agent are constructed and rules are established to form an agent-based major infectious disease transmission model considering the place. Then, the simulation process is established and an ideal regional environment is constructed to simulate overall changes in major infectious disease scale and spread speed. Additionally, evolutionary simulations are conducted for individual isolation intensity and place control time during emergency management stages to compare infection outcomes, and we analyze different roles and application scenarios of specific prevention and control measures. Finally, simulation results from real major infectious disease cases in Yangzhou, China, validate the effectiveness of this model in predicting major infectious disease development trends as well as evaluating prevention and control measure effects. [ABSTRACT FROM AUTHOR]

Multiple opinions, including many that are negative, are produced in emergency events. These opinions are commonly formed asynchronously based on misinformation. However, most researches on opinion dynamics involving information neglect the asynchronous process of initial opinion formation due to information diffusion. Since online social networks like Sina Weibo act as major avenues for the expression, after analysing online behaviours, an opinion dynamic model is developed with consideration of misinformation diffusion of public opinion. In this model, schemes are developed for opinion interactions in multiple dimensions by introducing characteristics of online communication as another way of opinion interactions besides communication between neighbours. Subsequently, we investigate the impacts of network structure, diffusion rate, repost rate and other factors, which provide insights into understanding online opinion dynamics during emergency events. Furthermore, we conduct simulations to determine the intervention effects of different official responses. Results show that removing comments compulsively exhibits better performance in reducing negative opinion as well as increasing the density of Spreaders. Debunking misinformation by posting early results officially which indicates the probability of the existence of misinformation may lead public opinion in time if it takes a long time to finally confirm the misinformation. [ABSTRACT FROM AUTHOR]

The selection and evaluation of fresh food suppliers is the primary problem for supermarkets. This problem is solved by a new multiattribute group decision‐making method with multigranular unbalanced hesitant fuzzy linguistic term set, which is based on prospect theory and evidential theory. Then, a novel supermarket fresh food supplier evaluation index is constructed with 5 elements and 15 indicators. To get the reasonable weights, best–worst method, criteria importance through intercriteria correlation method, and game theory are applied. Moreover, three methods are compared to prove our proposed method's validity and superiority. Finally, this paper offers analysis and suggestions based on the results from strategy level and statics level, respectively. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to investigate the expression levels of plasma miR-30a-5p, miR-101-3p, miR-140-3p and miR-141-3p and their relationship to dexmedetomidine efficacy and adverse effects in pediatric patients. Methods: The expression levels of miR-30a-5p, miR-101-3p, miR-140-3p and miR-141-3p were measured by qRT-PCR in plasma of 133 pediatric patients receiving dexmedetomidine for preoperative sedation. We analyzed the relationship between miRNA abundance and dexmedetomidine response, including sedative effect and adverse effects, and assessed the predictive power of miRNAs for drug response. Results: Among 133 pediatric patients, 111 patients were dexmedetomidine responders (UMSS ≥ 2) and 22 patients were non-responders (UMSS < 2). We observed higher expression levels of miR-101-3p and miR-140-3p in dexmedetomidine responders compared with non-responders (P < 0.05, P < 0.0001). In contrast, there was no significant difference in the expression levels of miR-30a-5p and miR-141-3p between responders and non-responders (P > 0.05). The plasma levels of miR-101-3p and miR-30a-5p were markedly downregulated in patients who experienced hypotension and bradycardia, respectively (P < 0.05). MiR-101-3p and miR-140-3p demonstrated a potential discriminatory ability between dexmedetomidine responders and non-responders, with AUC of 0.64 (P < 0.05) and 0.77 (P < 0.0001), respectively. The AUC of miR-101-3p in distinguishing patients without hypotension was 0.63 (P < 0.05). The AUC of miR-30a-5p in distinguishing patients without bradycardia was 0.74 (P < 0.05). Conclusion: Our study demonstrated that circulating miR-101-3p, miR-140-3p and miR-30a-5p might be used as a blood-based marker for dexmedetomidine efficacy and safety in pediatric patients. [ABSTRACT FROM AUTHOR]

Massive open online courses (MOOCs) are very popular in China, and it is very important to evaluate and improve them. In this paper, a new evaluation method for MOOCs based on multi‐attribute group decision‐making is proposed. First, an evaluation index system of MOOCs is constructed, which contains six elements and 16 indicators, and multigranular unbalanced hesitant fuzzy linguistic term set (MGUHFLTS) is adopted to describe these indicators. Then based on MGUHFLTS, the aggregation operators are developed, including the multigranularity unbalanced hesitant fuzzy linguistic weighted averaging operator and the multigranularity unbalanced hesitant fuzzy linguistic order weighted averaging operator, moreover, a novel multi‐attributive border approximation area comparison model based on MGUHFLTS is proposed. This model is testified validity and superiority by comparison with other three methods and is applied in evaluation of MOOCs. After ranking five MOOCs, each indicator is analyzed to show how they influenced each element and suggestions are given. [ABSTRACT FROM AUTHOR]

T-spherical fuzzy numbers (FNs), which add an abstinence degree based on membership and non-membership degrees, can express neutral information conveniently and have a considerable large range of information expression. The normal FNs (NFNs) are very available to characterize normal distribution phenomenon widely existing in social life. In this paper, we first define the normal T-SFNs (NT-SFNs) which can combine the advantages of T-SFNs and NFNs. Then, we define their operational laws, score value, and accuracy value. By considering the interrelationship among multi-input parameters, we propose the Maclaurin symmetric mean operator with NT-SFNs (NT-SFMSM) and its weighted form (NT-SFWMSM). Furthermore, we study some characteristics and special cases of them. Based on the NT-SFWMSM operator, we put forward a novel multi-attribute decision-making (MADM) approach. Finally, some numerical examples are conducted to prove that the proposed approach is valid and superior to some other existing methods. [ABSTRACT FROM AUTHOR]

As the development and extension of hesitant fuzzy linguistic term sets (HFLTSs), free double hierarchy hesitant fuzzy linguistic term sets (FDHHFLTSs) can describe the evaluation information in more detail. In addition, in practical multiple attribute decision-making (MADM) problems, priority relations and interaction relations usually exist among attributes, and the prioritized interactive Choquet (PIC) operator based on generalized prioritized measure-guided aggregation (GPMGA) operator and Choquet integral (CI) operator is an effective tool for dealing with decision-making problems with priority relations and interaction relations. Under the above contexts, we improve the PIC operator and propose the FDHHFLPIC operator which can aggregate the evaluation information under free double hesitant fuzzy linguistic environment and take both priority and interaction relations into account. Furthermore, we propose an approach based on the FDHHFLPIC operators to address the real MADM problem, and the proposed method considering the different relations between attributes in decision-making process. Finally, two numerical examples are given to demonstrate the effectiveness and advantages of the proposed method which can consider priority relations and interaction relations under the FDHHFLTSs. [ABSTRACT FROM AUTHOR]

A rapid and effective analytical method for determination of pydiflumetofen residues in some foods of plant and animal origin (grapes, tomatoes, wheat, pork, milk, and eggs) was developed using a modified QuEChERS (quick, easy, cheap, effective, rugged, and safe) sample preparation procedure followed by ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). Acetonitrile was served as the extraction solvent, and an octadecylsilane-dispersive solid-phase extraction (C18-dSPE) was used to cleanup the analyte, and then detected by UPLC-MS/MS. Pydiflumetofen was eluted within 3.0 min from the HSS T3 chromatography column connected to an electrospray ionization source in positive mode. The linearity of the method was excellent (R2 ≥ 0.992) in the pydiflumetofen concentration range of 10-1000 μg kg−1. The recoveries of spiked pydiflumetofen (10, 100, and 1000 μg kg−1) from the matrices were satisfactory, being between 72.0 and 110.3%, and all with relative standard deviation values of < 15.1%. The limit of quantification for pydiflumetofen was 10 μg kg−1. This study provides a method for the routine monitoring of pydiflumetofen. [ABSTRACT FROM AUTHOR]

We have developed a rapid, multi-compound analytical method for measuring residues of the pesticides thiamethoxam and its metabolite, clothianidin; fipronil and its three metabolites, fipronil sulfone, fipronil sulfide, and fipronil desulfinyl; and pyraclostrobin in unprocessed foods (rice, corn, cucumbers, tomatoes, apples, and bananas) by ultra-performance liquid chromatography coupled to tandem mass spectrometry. Acetonitrile was used as the extraction solvent, and an octadecylsilane-dispersive SPE was used to clean up the analytes, which were then separated through a UPLC HSS T3 column connected to a tandem mass spectrometer via an electrospray ionisation source. The linearity of this method for the target analytes was excellent (R2 ≥0.990) in the concentration range of 5–1000 μg kg–1. The average recoveries of the seven compounds at concentrations of 10, 100, and 1000 μg kg–1from six spiked matrix samples ranged from 73.6 to 110.6%, all with RSD values of ≤19.7%. The limit of quantification was 10 μg kg–1. The method validated the effectiveness of the method for routine monitoring the residue of these pesticides and their metabolites in foods. [ABSTRACT FROM PUBLISHER]

Comprehensive risk evaluation of urban areas is important for disaster prevention and mitigation. Since disaster scenarios of urban areas are diverse and complex, the data are generally inadequate for understanding the absolute risk of disaster loss posed by any specific hazard or multi-hazards but adequate for identifying areas that are at relatively higher risk levels to some extent. Therefore, this paper focuses on modeling relative risk assessment for urban disaster loss. Based on disaster system theory, elements at risk and hazard-formative environments were determined as the crucial components to reflect risk discrepancies of different urban areas facing similar hazards. Furthermore, the critical path of interactions between components within the disaster system was constructed by introducing exposure and sensitivity as filtering processes. On this basis, a relative risk model for urban disaster loss assessment was constructed and applied to cities in Liaoning Province as an illustration. In addition, the results were represented and analyzed from multi-dimensions. A test for the uncertainties of the results indicates that this model shows a strong applicability for urban disaster loss relative risk assessment on the premise of accurate data concerning elements at risk and hazard-formative environments. [ABSTRACT FROM AUTHOR]

The intuitionistic linguistic variables are easier to describe the fuzzy information which widely exists in the real world, and Bonferroni mean can capture the interrelationship of the individual arguments.However, the traditional Bonferronimean can only process the crisp number. In this paper, we will extend Bonferroni mean to the intuitionistic linguistic environment and propose a multiple attribute decisionmakingmethodwith intuitionistic linguistic information based on the extended Bonferroni mean which can consider the interrelationship of the attributes. Firstly, score function and accuracy function of intuitionistic linguistic numbers are introduced. Then, an intuitionistic linguistic Bonferroni mean (ILBM) operator and an intuitionistic linguistic weighted Bonferroni mean (ILWBM) operator are developed, and some desirable characteristics of them are studied. At the same time, some special cases with respect to the parameters p and q in Bonferroni are analyzed. Based on the ILWBM operator, the approach to multiple attribute decision making with intuitionistic linguistic information is proposed. Finally, an illustrative example is given to verify the developed approach and to demonstrate its effectiveness. [ABSTRACT FROM AUTHOR]

Link prediction in complex networks has attracted much attention recently. Many local similarity measures based on the measurements of node similarity have been proposed. Among these local similarity indices, the neighborhood-based indices Common Neighbors (CN), Adamic-Adar (AA) and Resource Allocation (RA) index perform best. It is found that the node similarity indices required only information on the nearest neighbors are assigned high scores and have very low computational complexity. In this paper, a new index based on the contribution of common neighbor nodes to edges is proposed and shown to have competitively good or even better prediction than other neighborhood-based indices especially for the network with low clustering coefficient with its high efficiency and simplicity. [ABSTRACT FROM AUTHOR]

How to evaluate the importance of nodes in networks and detect the centrality has become a vital problem in improving the efficiency of telecommunication and making a disease immunity strategy. We consider the mechanisms of real networks, and define a cost function to describe different hierarchies of networks to measure node importance. This method takes up a node’s regional influence as well as its global influence to evaluate its importance. The results of simulation prove that this method is proper to describe effectively and detect node discrepancies in a network. [ABSTRACT FROM AUTHOR]

The catalytic cracking raw oil was treated with microwave digestion process to be dissolved in water solution. And iron, copper ,nickel and Vanadium in the solution were determined by atomic absorption spectrometry. The interference of coexisting elements was measured and then eliminated by the addition of lanthanum -- based inhibitor. The results of a precision experiment showed that the recovery of various element was 96% --105% and the relative standard deviation (RSD) was less than 5%. [ABSTRACT FROM AUTHOR]

The intuitionistic linguistic variables are easier to describe the fuzzy information which widely exists in the real world, and Bonferroni mean can capture the interrelationship of the individual arguments. However, the traditional Bonferroni mean can only process the crisp number. In this paper, we will extend Bonferroni mean to the intuitionistic linguistic environment and propose a multiple attribute decision making method with intuitionistic linguistic information based on the extended Bonferroni mean which can consider the interrelationship of the attributes. Firstly, score function and accuracy function of intuitionistic linguistic numbers are introduced. Then, an intuitionistic linguistic Bonferroni mean (ILBM) operator and an intuitionistic linguistic weighted Bonferroni mean (ILWBM) operator are developed, and some desirable characteristics of them are studied. At the same time, some special cases with respect to the parameters p and q in Bonferroni are analyzed. Based on the ILWBM operator, the approach to multiple attribute decision making with intuitionistic linguistic information is proposed. Finally, an illustrative example is given to verify the developed approach and to demonstrate its effectiveness. [ABSTRACT FROM AUTHOR]