The unprecedented outbreak of COVID-19 has left many multinational enterprises facing extremely severe supply disruptions. Besides considering triple-bottom-line requirements, managers now also have ...to consider supply disruption due to the pandemic more seriously. However, existing research does not take these two key objectives into account simultaneously. To bridge this research gap, based on the characteristics of COVID-19 and similar global emergency events, this article proposes a model that aims to solve the problem of sustainable supplier selection and order allocation considering supply disruption in the COVID-19 era. It does so by using a multi-stage multi-objective optimization model applied to the different stages of development and spread of the pandemic. Then, a novel nRa-NSGA-II algorithm is proposed to solve the high-dimensional multi-objective optimization model. The applicability and effectiveness of the proposed model is illustrated in a well-known multinational producer of shortwave therapeutic instruments.
The purpose of this study is to examine how the emotion regulation strategy, cognitive reappraisal, affects the association between perceived stress and anxiety symptoms in COVID-19 isolated people. ...Data for this cross-sectional study come from a community-based online survey of COVID-19 isolated people (
N
= 328), who are not infected with the 2019-nCoV virus. We applied correlation and moderating effect for data analysis and found that cognitive reappraisal negatively moderated the relationship between perceived stress and anxiety symptoms. These results give us a new perspective on understanding the relationship between anxiety symptoms and perceived stress by clarifying the protective function of cognitive reappraisal. It buffers the induced negative emotion when COVID-19 isolated people perceive overpressure, and thus instigates future research into targeted clinical interventions, which aim to cultivate cognitive reappraisal skills for those isolated people in the face of stressful events or crisis events.
Although the formation of metal-carbon σ bonds is a fundamental principle in organometallic chemistry, the direct bonding of one organic molecule with one metal center to generate more than two ...metal-carbon σ bonds remains a challenge. Herein, we report an aromaticity-driven method whereby multiyne chains are used to construct three metal-carbon σ bonds in a one-pot reaction under mild conditions. In this method, multiyne chains act as ligand precursors capable of chelating an osmium center to yield planar metallapolycycles, which exhibit aromaticity and good stability. The direct assembly of various multiyne chains with commercially available metal complexes or even simple metal salts provides a convenient and efficient strategy for constructing all carbon-ligated chelates on the gram scale.
Diet can not only provide nutrition for intestinal microbiota, it can also remodel them. However, is unclear whether and how diet affects the spread of antibiotic resistance genes (ARGs) in the ...intestinal microbiota. Therefore, we employed selected high-sugar, high-fat, high-protein, and normal diets to explore the effect. The results showed that high-sugar, high-fat, and high-protein diets promoted the amplification and transfer of exogenous ARGs among intestinal microbiota, and up-regulated the expression of trfAp and trbBp while significantly altered the intestinal microbiota and its metabolites. Inflammation-related products were strongly correlated with the spread of ARGs, suggesting the intestinal microenvironment after diet remodeling might be conducive to the spreading of ARGs. This may be attributed to changes in bacterial membrane permeability, the SOS response, and bacterial composition and diversity caused by diet-induced inflammation. In addition, acceptor bacteria (zygotes) screened by flow cytometry were mostly Proteobacteria, Firmicutes and Actinobacteria, and most were derived from dominant intestinal bacteria remodeled by diet, indicating that the transfer of ARGs was closely linked to diet, and had some selectivity. Metagenomic results showed that the gut resistance genome could be affected not only by diet, but by exogenous antibiotic resistant bacteria (ARB). Many ARG markers coincided with bacterial markers in diet groups. Therefore, dominant bacteria in different diets are important hosts of ARGs in specific dietary environments, but the many pathogenic bacteria present may cause serious harm to human health.
An unhealthy diet has been linked to increased incidence of chronic diseases. To investigate the relationship between diet and intestinal inflammation, mice in two experimental groups were fed on a ...high-fat diet or high-fructose diet, respectively. The result showed that the defecation volume of the experimental groups was significantly reduced compared with that of the control group, and the levels of pro-inflammatory cytokines (interleukin (IL)-1β and IL-6) and IgG in serum were increased significantly. In addition, inflammatory cell infiltration was observed in intestinal tissue, indicating that a high-fructose or high-fat diet can lead to constipation and inflammation. Further analysis showed that the microbial composition of the experimental groups changed significantly, including a decrease of the
Bacteroidetes/Firmicutes
ratio and increased levels of
Bacteroides
,
Akkermansia
,
Lactobacillus
, and
Ruminococcus
, which might be associated with inflammation. The results of pro-inflammatory metabolites analysis showed that the levels of arachidonic acid, stearic acid, and indoxylsulfuric acid were significantly increased in the experimental groups, which were related significantly to
Bacteroides
,
Enterococcus
, and
Akkermansia
. Meanwhile, the content of 5-hydroxytryptamine (5-HT) was significantly decreased, which might cause constipation by reducing intestinal peristalsis. Moreover, transplantation of fecal bacteria from inflammatory mice caused constipation and inflammation in normal mice, which could be relieved by feeding a normal diet. The results of the present study indicated that changes in intestinal microbiota and microbial metabolites may underlie chronic intestinal inflammation and constipation caused by high-fructose and high-fat diets.
Forest fires present a significant challenge to ecosystems, particularly due to factors like tree cover that complicate fire detection tasks. While fire detection technologies, like YOLO, are widely ...used in forest protection, capturing diverse and complex flame features remains challenging. Therefore, we propose an enhanced YOLOv8 multiscale forest fire detection method. This involves adjusting the network structure and integrating Deformable Convolution and SCConv modules to better adapt to forest fire complexities. Additionally, we introduce the Coordinate Attention mechanism in the Detection module to more effectively capture feature information and enhance model accuracy. We adopt the WIoU v3 loss function and implement a dynamically non-monotonic mechanism to optimize gradient allocation strategies. Our experimental results demonstrate that our model achieves a mAP of 90.02%, approximately 5.9% higher than the baseline YOLOv8 network. This method significantly improves forest fire detection accuracy, reduces False Positive rates, and demonstrates excellent applicability in real forest fire scenarios.
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•A novel CQDs/PbBiO2Cl composite photocatalyst was prepared via an efficient process.•The as-prepared PbBiO2Cl nanosheet was firstly reported•The composite photocatalyst exhibited ...excellent photocatalytic activities towards three different types of contaminants, including tetracycline hydrochloride, ciprofloxacin and bisphenol A.•This work provided new insights for designing hybrid composite photocatalysts for water environment purification.
Novel carbon quantum dots (CQDs) modified PbBiO2Cl nanosheets, 0D/2D hybird photocatalyst has been firstly prepared via the reactive ionic liquid 1-hexadecyl-3 methylimidazolium chlorine assisted facile solvothermal approach. PbBiO2Cl nanosheets were designed to shorten the migration distance from bulk phase to the surface for the charge carriers, while CQDs was introduced to accelerate the transfer of surface charge carriers as well as activate molecular oxygen. Various techniques were conducted to explore structures, morphologies, optical and electrochemical properties of the as-prepared materials. Furthermore, the photocatalytic performance of CQDs/PbBiO2Cl materials were appraised via the photodegradation of antibiotic agent ciprofloxacin (CIP), tetracycline (TC) and endocrine disrupter bisphenol A (BPA) under visible light irradiation. The results demonstrated that the photocatalytic activities of CQDs modified PbBiO2Cl materials has a significantly enhancement compared to pure PbBiO2Cl nanosheets and the 3 wt% CQDs/PbBiO2Cl material displays the highest performance. In addition, electron spin resonance (ESR) experiments and radicals quenching experiments were employed to prove that the superoxide radicals and holes were the main active species during the photocatalytic process. Based on the above results, a possible photocatalytic mechanism was put forward. This research aims to develop more hybrid photocatalysts and hope to make progress in environmental remediation.
Aquatic vegetation is an important component of aquatic ecosystems; therefore, the classification and mapping of aquatic vegetation is an important aspect of lake management. Currently, the decision ...tree (DT) classification method based on spectral indices has been widely used in the extraction of aquatic vegetation data, but the disadvantage of this method is that it is difficult to fix the threshold value, which, in turn, affects the automatic classification effect. In this study, Sentinel-2 MSI data were used to produce a sample set (about 930 samples) of aquatic vegetation in four inland lakes (Lake Taihu, Lake Caohai, Lake Honghu, and Lake Dongtinghu) using the visual interpretation method, including emergent, floating-leaved, and submerged vegetation. Based on this sample set, a DL model (Res-U-Net) was used to train an automatic aquatic vegetation extraction model. The DL model achieved a higher overall accuracy, relevant error, and kappa coefficient (90%, 8.18%, and 0.86, respectively) compared to the DT method (79%, 23.07%, and 0.77) and random forest (78%,10.62% and 0.77) when utilizing visual interpretation results as the ground truth. When utilizing measured point data as the ground truth, the DL model exhibited accuracies of 59%, 78%, and 91% for submerged, floating-leaved, and emergent vegetation, respectively. In addition, the model still maintains good recognition in the presence of clouds with the influence of water bloom. When applying the model to Lake Honghu from January 2017 to October 2023, the obtained temporal variation patterns in the aquatic vegetation were consistent with other studies. The study in this paper shows that the proposed DL model has good application potential for extracting aquatic vegetation data.
The localization of sensing nodes is most pronounced in the application of wireless sensor networks. To address this issue, a node localization algorithm called the DMA is proposed in this paper. ...This algorithm identifies the node position by using the estimation matrix and distance matrix together with the optimized linear transforming function. With the integration of GA, the position of the node can be accurately determined. The conducted simulation outcomes and the corresponding analysis verify the high accuracy and low energy consumption of the proposed algorithm, which can outperform other widely used approaches. This study designs and deploys the proposed algorithm and shows its sensor node localization theory, which makes it a promising basis for the realization of positioning in WSNs.
Dysregulation of the gut microbiota by environmental factors is associated with a variety of autoimmune and immune-mediated diseases. In addition, naturally-occurring extracellular antibiotic ...resistance genes (eARGs) might directly enter the gut via the food chain. However, following gut microbiota exposure to eARGs, the ecological processes shaping the microbiota community assembly, as well as the interplay between the microbiota composition, metabolic function, and the immune responses, are not well understood. Increasing focus on the One Health approach has led to an urgent need to investigate the direct health damage caused by eARGs. Herein, we reveal the significant influence of eARGs on microbiota communities, strongly driven by stochastic processes. How eARGs-stimulate variations in the composition and metabolomic function of the gut microbiota led to cytokine responses in mice of different age and sex were investigated. The results revealed that cytokines were significantly associated with immunomodulatory microbes, metabolites, and ARGs biomarkers. Cytokine production was associated with specific metabolic pathways (arachidonic acid and tryptophan metabolic pathways), as confirmed by ex vivo cytokine responses and recovery experiments in vivo. Furthermore, the gut microbial profile could be applied to accurately predict the degree of intestinal inflammation ascribed to the eARGs (area under the curve = 0.9616). The present study provided a comprehensive understanding of the influence of an eARGs on immune responses and intestinal barrier damage, shedding light on the interplay between eARGs, microbial, metabolites, and the gut antibiotic resistome in modulating the human immune system.
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