Health-driven mechanism of organic food consumption: A structural equation modelling approach.

The COVID-19 pandemic seriously threatened human survival and development. It has also highlighted the significant correlation between ecological and public health. After three years of the COVID pandemic, Chinese consumers have become more aware of the importance of health. Especially in the Internet era, consumers' purchasing methods and health awareness have been changed. Consumers can buy nutritious and organic foods. To understand the impact of consumer psychology and health beliefs on the willingness to purchase organic food in the post-pandemic period, this study uses organic beef as an example and extracts key variables from three basic theories. The three basic theories include the Health Belief Model (HBM), the Theory of Planned Behavior (TPB), and the Norm Activation Model (NAM), respectively. Specifically, perceived susceptibility and severity are combined to form a health belief variable that can drive organic food purchasing. In contrast, perceived benefit, moral norms, self-efficiency, and controllability are introduced as mediating variables to construct the health driving factors of organic beef purchasing. Structural equation modeling (SEM) and mediation effect tests are used to analyse 539 samples. Meanwhile, paths and mechanisms between health concern and other variables are explored. The results show that health concern is an important driving factor. Health concern can significantly promote the formation of willingness to purchase organic beef. Mediation effect tests suggest that health concern can indirectly affect the willingness to purchase organic beef through perceived benefit, moral norms, and controllability, but the mediation effect of self-efficiency is not significant. This study provides important references for government regulation and certification of organic foods as well as for enterprises'organic food marketing strategies.

METTL14 Suppresses Tumor Stemness and Metastasis of Colon Cancer Cells by Modulating m6A-Modified SCD1.

Colon cancer (CC) is a malignant disease of the digestive tract, and its rising prevalence poses a grave threat to people's health. N6-methyladenosine (m6A) modification is essential for various crucial life processes through modulating gene expression. Methyltransferase-like 14 (METTL14), the m6A methylation transferase core protein, and its aberrant expression is intimately correlated to tumor development. This study was conducted to probe the impacts and specific mechanisms of METTL14 on the biological process of CC. Bioinformatics data disclosed that METTL14 was significantly attenuated in CC. Functional assays were executed to ascertain how METTL14 affected CC tumorigenicity, and METTL14 overexpression caused a notable decline in viability, migration, invasion, and stemness phenotype of CC cells. Then, in-depth mechanistic studies displayed that stearoyl-CoA desaturase 1 (SCD1) was a downstream target gene of METTL14-mediated m6A modification. METTL14 overexpression substantially augmented the m6A modification of SCD1 mRNA and diminished the SCD1 mRNA level. In addition, we revealed that YTHDF2 was the m6A reader to recognize METTL14 m6A-modified SCD1 mRNA and abolish its stability. Finally, we also validated that METTL14 might impede the tumorigenic process of CC through SCD1 mediated Wnt/ß-catenin signaling. Taken together, this study presented that METTL14 performed as a potential therapeutic target in CC with important implications for the prognosis amelioration of CC patients.

α-Amino Radical-Mediated Difunctionalization of Alkenes with Polyhaloalkanes and N-Heteroarenes.

Herein, we report a mild and practical protocol for the α-perchloroalkyl ß-heteroarylation of alkenes using available chloroform as the dichloromethyl source via α-amino radical-mediated halogen-atom transfer. Various substrates are compatible under mild reaction conditions, providing the corresponding products in moderate to good yields. This strategy gives an efficient and convenient method for the introduction of chloroalkyl motifs into N-heteroarenes. The control experiment demonstrates that the α-amino radical generated in situ is a key intermediate in the transformation.

A Two-Workshop Collaborative, Integrated Scheduling Algorithm considering the Prescheduling of the Root-Subtree Processes.

Aiming at the existing two-workshop integrated scheduling algorithm with the same equipment resources, a unified vertical or horizontal scheduling rule is used to sort all processes and ignore the vertical and horizontal characteristics of the associated process position in the process tree, which affects the scheduling results. A two-workshop collaborative, integrated scheduling algorithm considering the prescheduling of the Root-Subtree processes is proposed. The algorithm proposes a process conflict adjustment strategy for the horizontal equipment constraints. The same equipment Root-Subtree processes are sorted and loaded into the corresponding equipment queue through the vertical and horizontal prescheduling method in a single-workshop environment, and it combines with the schedulable process set to dequeue the first process of the queue. To enhance the flexibility of process scheduling, it proposes a process conflict adjustment strategy for the vertical process tree constraints in the two workshops to determine the processing workshop of the processes and the actual start time, which narrows the search comparison for schedulable processes. The example tests show that the algorithm not only excavates and utilizes the effectiveness of the vertical and horizontal characteristics of the process tree, but also considers the process migration time. Therefore, the effect is better and more practical.

Organic acid catalysed Minisci-type arylation of heterocycles with aryl acyl peroxides.

A metal-free method for the Minisci-type arylation of heterocycles with aryl acyl peroxides has been reported. This strategy enables the rapid and simple synthesis of a series of Minisci-type adducts from commercially available starting materials without metal catalysts. A free-radical-pathway mechanism is suggested for this transformation.

Does more stringencies in government policies during pandemic impact stock returns? Fresh evidence from GREF countries, a new emerging green bloc.

In this paper, we investigate the impact of the government economic policies in addition to the more stringent Covid-19 policies on stock index returns of GREF countries, that is, a new economic bloc of 5 countries (Pakistan, Iran, Turkey, Russia, and China) to foster for sustainable development of the region. Using the Panel, ARDL model and data for index returns and economic and Covid-19 control policies for the period March 1, 2020-June 30, 2021, results show that Income support, workplace closure, stringency index, and cancellation of public events have a significant positive impact on the stock index returns over the long run. In contrast, school closure, restriction on public gatherings, and international travel control policies negatively impact stock returns. In comparison, Debt policies, Covid-19 testing policies, health index, and face-covering policies remain insignificant. In the short run, stringent index and face-covering policies remain positively significant. Results of the study suggest significant policy implications that can help reform economic and Covid-19 control policies and promote the region's economic growth over the long-run period.

The role of green innovation and tourism towards carbon neutrality in Thailand: Evidence from bootstrap ADRL approach.

The recent years have been marked by the role of green tech innovation in decreasing carbon emissions worldwide to attain the carbon neutrality target. Despite many studies examining the nexus between the former and energy consumption, tech innovation's effects on CO2 releases have not been extensively researched, and the extant empirical findings are often contradictory. Also, a major concern regarding the available literature is the scarcity of papers that scan the impact of tourism on carbon emissions, even though the industry has a high potential to affect ambient air pollution. In this case, the evidence is mixed, and no consensus among academics on the relationships between the two. Therefore, this study seeks to investigate the relevance of green innovation and tourism in decreasing environmental damage in Thailand based on the bootstrapping ARDL causality model suggested by (McNown et al., 2018). This specification includes a new cointegration feature and conventional ARDL bounds tests, which increases the power of the t- and of the f-test and has several advantages, being more adequate for dynamic models with more than one explanatory variable. Our findings reveal that green innovation and tourism lead to lower environmental damage by reducing CO2 emissions, similar to foreign investments and that green tech innovation improves the environmental quality via lower carbon emissions.

Complex Entropy and Its Application in Decision-Making for Medical Diagnosis.

In decision-making systems, how to measure uncertain information remains an open issue, especially for information processing modeled on complex planes. In this paper, a new complex entropy is proposed to measure the uncertainty of a complex-valued distribution (CvD). The proposed complex entropy is a generalization of Gini entropy that has a powerful capability to measure uncertainty. In particular, when a CvD reduces to a probability distribution, the complex entropy will degrade into Gini entropy. In addition, the properties of complex entropy, including the nonnegativity, maximum and minimum entropies, and boundedness, are analyzed and discussed. Several numerical examples illuminate the superiority of the newly defined complex entropy. Based on the newly defined complex entropy, a multisource information fusion algorithm for decision-making is developed. Finally, we apply the decision-making algorithm in a medical diagnosis problem to validate its practicability.

Assessing the Effect of Bilateral Trade on Health in the Asian Region: Does Digitization Matter?

A recurrent theme of the literature and wider public discourse is that trade and digitization are good for health as it promotes economic prosperity. The present study investigates the impact of trade and digitization on health in 12 selected Asian economies for the period 1991-2019. The study applied FMOLS and DOLS approaches for confirming the panel and economy-wise findings. The core findings of the panel FMOLS confirm the significant negative impact of trade and digitization on mortality rate, and trade and digitization have significantly positively contributed to life expectancy in selected Asian countries in the long run. The study deduces some imperative policy implications related to trade, digitization, and health, specifically for Asian economies.

Multistage implementation framework for smart supply chain management under industry 4.0.

The true potential of the industry 4.0, which is a byproduct of the fourth industrial revolution, cannot be actually realized. This is, of course true, until the smart factories in the supply chains get connected to each other, with their systems and the machines linked to a common networking system. The last few years have experienced an increase in the adoption and acceptance of the industry 4.0's components. However, the next stage of smart factories, which will be the smart supply chains, is still in its period of infancy. Moreover, there is a simultaneous need to maintain a focus on the supply chain level implementation of the concept that industry 4.0 puts forth. This is important in order to gain the end to end benefits, while also avoiding the organization to organization compatibility issues that may follow later on. When considering this concept, limited research exists on the issues related to the implementation of industry 4.0, at the supply chain level. Hence, keeping in mind this lack of literature and research available, on a phenomenon that will define the future of business and industry, this study uses an exploratory approach to capture the implementation of industry 4.0 concepts across multiple tiers of the supply chain. Based on this research, the study proposes a multistage implementation framework that highlights the organizational enablers such as culture, cross-functional approach, and the continuous improvement activities. Furthermore, it also highlights the staged implementation of the advanced tools, starting from the focal organization with the subsequent integration with the partner organizations.

Weaving public health and safety nets to respond the COVID-19 pandemic.

How do governments take strategic actions in weaving public health and safety nets to respond to the COVID-19 pandemic? Embracing Moore's strategic action framework, this study investigates how municipal governments can configure authorizing environment-operational capacity-public value attributes to weave public health and safety nets, in order to prevent and control the public health and safety emergency. Leveraging fuzzy-set Qualitative Comparative Analysis (fsQCA) with a sample of 323 Chinese cities, we identify a distinctive taxonomy of four equally effective configurations of urban actions in blocking COVID-19 transmission: social reassurance, proactive defence, decisive resiliency, and strengthened coercion. Overall, this study provides a novel insight of public health and safety management into battles against COVID-19 in human society.

Methylene Blue Dye Photocatalytic Degradation over Synthesised Fe3O4/AC/TiO2 Nano-Catalyst: Degradation and Reusability Studies.

In this study, activated carbon (AC) from coconut shell, as a widely available agricultural waste, was synthesised in a simple one-step procedure and used to produce a magnetic Fe3O4/AC/TiO2 nano-catalyst for the degradation of methylene blue (MB) dye under UV light. Scanning electron microscopy revealed that TiO2 nanoparticles, with an average particle size of 45 to 62 nm, covered the surface of the AC porous structure without a reunion of its structure, which according to the TGA results enhanced the stability of the photocatalyst at high temperatures. The photocatalytic activities of synthesised AC, commercial TiO2, Fe3O4/AC, and Fe3O4/AC/TiO2 were compared, with Fe3O4/AC/TiO2 (1:2) exhibiting the highest catalytic activity (98%). Furthermore, evaluation of the recovery and reusability of the photocatalysts after treatment revealed that seven treatment cycles were possible without a significant reduction in the removal efficiency.

Fiscal Expenditures on Science and Technology and Environmental Pollution: Evidence from China.

Studying the driving factors of environmental pollution is of great importance for China. Previous literature mainly focused on the cause of national aggregate emission changes. However, research about the effect of fiscal expenditures on science and technology (FESTs) on environmental pollution is rare. Considering the large gap among cities in China, it is necessary to investigate whether and how FESTs affect environmental pollution among cities. We adopted three kinds of typical environmental pollutants including sulfur dioxide (SO2) emissions, wastewater emission, and atmospheric particulate matter less than 2.5 micrometers in diameter (PM2.5). Using the data of 260 prefecture-level cities over ten years in China, we found that FESTs play a significantly positive role in reducing sulfur dioxide (SO2) emissions and PM2.5 concentrations, but fail to alleviate wastewater emissions. Specifically, for every 1% increase in FESTs, SO2 emissions were reduced by 5.317% and PM2.5 concentrations were reduced by 5.329%. Furthermore, we found that FESTs reduced environmental pollution by impeding fixed asset investments and by promoting research and development activities (R&D). Moreover, the impacts of FESTs on environmental pollution varied across regions and sub-periods. Our results are robust to a series of additional checks, including alternative econometric specifications, generalized method of moments (GMM) analysis and overcoming potential endogeneity with an instrumental variable. Our findings confirm that government efforts can be effective on pollution control in China. Hence, all governments should pay more attention to FESTs for sustainable development and environmental quality improvements.

Valuation Impacts of Environmental Protection Taxes and Regulatory Costs in Heavy-Polluting Industries.

In 2016, the issue of the Environmental Protection Tax Law indicated the enhancement of environmental protection in China. This study examines the market reaction to firms in heavy-polluting industries, and the effects of external legal institutional quality and internal environmental disclosure on firm value around the passage of Environmental Protection Tax Law. Using an event study approach coupled with ordinary least square regressions, the researchers find a significantly negative market reaction to firms in heavy-polluting industries, but this negative reaction varies depending on the expected increase in future regulatory costs. Specifically, the above negative reaction is stronger when the firm reveals that itself or its subsidiary belongs to heavy-polluting industry, however it would be mitigated when a firm is in a region with better quality of legal institutions or discloses environmental improvement activities. Overall, the results are consistent with the market perceiving that the environmental protection tax law enacted would increase regulatory costs for firms in heavy-polluting industries, and also show the higher-quality regional legal institutions and more efforts on environmental protection could relieve the market's pessimism caused by uncertainty.

Response to the COVID-19 Epidemic: The Chinese Experience and Implications for Other Countries.

The ongoing outbreak of the novel coronavirus disease (COVID-19) that occurred in China is rapidly spreading globally. China's bond and strict containment measures have been proved (in practice) to significantly reduce the spread of the epidemic. This was obtained through the use of emergency control measures in the epidemic areas and the integration of resources from multiple systems, including business, community, technology, education, and transportation, across the country. In order to better understand how China has managed to reduce the public health and economic impacts of the COVID-19 epidemic, this editorial systematically reviews the specific measures for infection prevention and control of the disease. The best practices for COVID-19 eradication in China provide evidence-based strategies that could be replicated in other countries.

Training Convolutional Neural Networks withMulti-Size Images and Triplet Loss for RemoteSensing Scene Classification.

Many remote sensing scene classification algorithms improve their classification accuracyby additional modules, which increases the parameters and computing overhead of the model atthe inference stage. In this paper, we explore how to improve the classification accuracy of themodel without adding modules at the inference stage. First, we propose a network trainingstrategy of training with multi-size images. Then, we introduce more supervision information bytriplet loss and design a branch for the triplet loss. In addition, dropout is introduced between thefeature extractor and the classifier to avoid over-fitting. These modules only work at the trainingstage and will not bring about the increase in model parameters at the inference stage. We useResnet18 as the baseline and add the three modules to the baseline. We perform experiments onthree datasets: AID, NWPU-RESISC45, and OPTIMAL. Experimental results show that our modelcombined with the three modules is more competitive than many existing classification algorithms.In addition, ablation experiments on OPTIMAL show that dropout, triplet loss, and training withmulti-size images improve the overall accuracy of the model on the test set by 0.53%, 0.38%, and0.7%, respectively. The combination of the three modules improves the overall accuracy of themodel by 1.61%. It can be seen that the three modules can improve the classification accuracy of themodel without increasing model parameters at the inference stage, and training with multi-sizeimages brings a greater gain in accuracy than the other two modules, but the combination of thethree modules will be better.

Effects of Codonopis bulleynana forest ex diels on Deferribacteres in constipation predominant intestine tumor: Differential analysis.

As a complicated micro-ecosystem, gut microbes are closely related to metabolic disease, immune disease and tumor (such as constipation. Long-term constipation would cause intestinal mucosal injury, enteritis, ileus, etc., thus inducing intestine cancer). In this research, intestine cancer model group and Codonopsis foetens treatment group were successfully constructed, and the variation of intestinal microbes were analyzed by 16S rRNA sequence. Results showed that there were changes in bacteria abundance of Firmicutes, Bacteroidetes, Proteobacteria, Deferribacteres, Tenericutes, and Actinobacteria, etc. Codonopsis foetens could directly or indirectly affect the growth and metabolism of Deferribacteres by altering the nutritional ingredient and pH value of intestine "medium", thus affecting the occurrence and development of intestinal microbes.

Correlation between SOX2 and Survivin clinical features in patients with salivary adenoid cystic carcinoma.

OBJECTIVE: In this study, expression of cancer stem cells (CSCs)-related factor-Sex-determining region of Y chromosome-related high-mobility-group box 2 (SOX2) and anti-apoptotic specific factor- Survivin in salivary adenoid cystic carcinoma (SACC) was detected to provide important clues for effective SACC prevention and treatment by combining clinical pathological parameters analysis. METHODS: Paraffin and fresh specimens were collected from SACC patients who underwent surgery at the Oral and Maxillofacial Surgery Department of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital. The experimental group was designed as SACC tissue, and the control group normal paracancerous normal gland tissue. (1) SOX2 and Survivin expression were detected using immunohistochemistry and analyzed by comnining clinical pathological parameter analysis. (2) mRNA and protein expression levels of SOX2 and Survivin were detected using RT-PCR, Western Blot. RESULTS: 1. Immunohistochemistry: (1) SOX2 was mainly expressed on the nucleus. The SOX2 positive rate was 28.57% in clinical stage I-II, and 76.92% in stage III-IV. (2) Survivin was mainly expressed in the cytoplasm. The Survivin positive rate was 61.90% in clinical stage I-II, and 76.92% in stage III-IV. (3) There was a clear correlation between SOX2 and Survivin. 2. RT-PCR and Western Blot: The mRNA and protein expression levels of SOX2 and Survivin were significantly higher in the experimental group than in the control group (P < 0.01). CONCLUSION: (1) The mRNA and protein expression level of SOX2 and Survivin was significantly higher in SACC tissues than in paracancerous normal salivary gland tissues, indicating that both of the two are tissue-specific and may become SACC oncogenes. (2) SOX2 and Survivin are significantly correlated in expression, which may coorinatively participate in SACC incidence and development.

Tensile stress distribution in maxillary central incisors restored with cast-made and prefabricated dental posts

AIM: To analyze and compare the tensile stress distribution in endodontically treated teeth restored with cast-made (Ni-Cr and gold) and prefabricated (titanium and glass fibre) dental posts. METHODOLOGY: Four threedimensional finite element (FE) models of a maxillary central incisor restored with Ni-Cr cast-made (Model Ni-Cr), gold cast-made (Model GO), prefabricated titanium (Model TI) and prefabricated glass fibre (Model FP) posts were constructed. An oblique loading of 100N was applied to each three-dimensional model. Tensile stress distribution within the root dentine and at the post and surrounding structure interfaces were analysed. RESULTS: In all the FE models studied, a higher magnitude of tensile stresses was observed on the palatal aspect of the cervical dentin as compared to the labial aspect and progressively decreases from the outer to the inner part of the root. The gold cast-made and glass fibre post models showed significantly less tensile stress concentration in the post-core component than the other experimental models. The maximum tensile stress was seen on the palatal aspect of the Ni-Cr compared to other posts. The higher magnitude interfacial tensile stress concentration was observed in a pulpless tooth restored with a Ni-Cr cast-made post, followed by titanium and gold castmade posts, respectively. However, the minimum interfacial tensile stress was noticed in a pulpless tooth restored with a glass fibre post. CONCLUSION: Glass fibre posts tend to transfer tensile stress more homogenously within the tooth and at interfaces than the other types of investigated posts.