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Soil sickness a severe problem in tobacco production, leading to soil-borne diseases and reduce in tobacco yield. This occurs as a result of the interaction between root exudates and rhizosphere microorganisms, which is however, little studied until now. By combining the field investigation and pot experiment, we found the output yield consistently decreased during the first 10 years of continuous cropping in a tobacco field, but increased at the 15th year (15Y). The root exudate and rhizosphere bacterial community was further analyzed to reveal the underlying mechanism of the suppressive soil formation. Root exudate of 15Y tobacco enriched in amino acids and derivatives, while depleted in the typical autotoxins including phenolic acids and alkaloids. This was correlated to the low microbial diversity in 15Y, but also the changes in community composition and topological properties of the co-occurrence network. Especially, the reduced autotoxins were associated with low Actinobacteria abundance, low network complexity and high network modularity, which significantly correlated with the recovered output yield in 15Y. This study revealed the coevolution of rhizosphere microbiota and root exudate as the soil domesticated by continuous cropping of tobacco, and indicated a potential role of the autotoxins and theirs effect on the microbial community in the formation of suppressive soil. [ABSTRACT FROM AUTHOR]

Purpose: The mineralization rate of soil carbon (C) and nitrogen (N) is important for determining soil C storage as well as nutrient supply and retention. Soil C and N decomposition processes are microbially driven and are therefore expected to be influenced by the balance between soil resource availability and microbial resource demand. However, we lack understanding of how the microbial uptake and mineralization of soil C and N is affected by different levels of fertilization and crop rotation patterns in agricultural systems. Materials and methods: Soils from a field experiment including five levels of N fertilization (0 kg N ha−1 (control, 0), 84 kg N ha−1 (low N application), 95 kg N ha−1 (moderate N application), 105 kg N ha−1 (conventional N application) and 115.5 kg N ha−1 (high N application)) were used to determine soil C and N mineralization and retention, in either a tobacco plantation either under tobacco monoculture or tobacco-maize rotation. Results and discussion: Nitrogen fertilizer application increased net N mineralization (40–307%), net nitrification (150–400%), microbial NUE (131–373%) and CUE (16–57%) but decreased respiration (11–42%) in monoculture system, due to the significant higher DOC concentration and microbial C limitation. However, N fertilizer application increased net N mineralization (67–400%), net nitrification (50–544%), and microbial NUE (84–438%) but reduced microbial respiration (56–71%) and CUE (8–39%) in rotation system, due to the lower microbial activity caused by significant higher microbial C and N limitation and poorer C quality. Therefore, fertilization aggravated microbial resource limitation and lowered quality indicated by elemental stoichiometry in rotation system, leading to decoupling of microbial respiration and metabolism. Conclusions: Together, our results suggest that elemental stoichiometry and enzyme activities can be used to predict soil C and N cycling under different agricultural management practices. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, understanding the effects of location information of patients has significant theoretical and practical implications for public crisis management and health communication. Based on fear appeal theories, this research proposed a chain reaction model that links physical distance to the nearest patients, which is informed by the location information of patients, citizens' anxiety, attention to information and preventive behaviors. To test the hypothesized model, we conducted a study during the COVID-19 outbreak in mainland China in March 2020. The survey of 2061 people from 244 cities across 30 provinces showed that physical distance to confirmed cases has a significant influence on citizens' anxiety, which in turn can improve their preventive behaviors through the mediating factor of attention to information. In addition, this research also revealed the twofold effects of vertical collectivism as a personality trait on anxiety. These findings will provide support to help governments take actions to reduce citizens' anxiety and promote preventive behaviors. [ABSTRACT FROM AUTHOR]

Environmental sustainability is an important strategy for firms to expand market reach and space in pursuit of profitable growth. In the context of internationalization, environment information disclosure (EID) is considered an environmental signal released by a firm to external stakeholders. Using a sample of Chinese construction firms listed in the global Engineering News-Record (ENR), two periods, from 2008 to 2014 and 2015 to 2019, were set up from the perspective of the EID guideline changes. The regression results illustrate a negative relationship between EID and financial performance in the first period. The moderating effect of internationalization on the relationship between EID and financial performance changes from negative to positive over time. Quantile regressions further reveal how EID and internationalization affect firms at different levels of financial performance. This study proposed a periodic contingency perspective to reconcile the changes in the influence of EID on financial performance within the context of internationalization. [ABSTRACT FROM AUTHOR]

Root-knot nematode disease is a catastrophic soil-borne disease in tobacco production. The regulation of natural microbial communities is considered a good disease management approach to suppress the incidence of soilborne diseases. In this study, the effects of tobacco (Nicotiana tabacum L.)-marigold (Tagetes erecta L.) rotation on the diversity and structure of soil microbial communities in continuously cropped tobacco fields were analyzed to manage this devastating pathogen. The results showed that the soil bacterial OTUs increased after marigold rotation and that the bacterial Shannon, ACE, Chao1 index, and fungal Shannon index were higher in the tobacco-marigold rotation fields than in the continuously cropped tobacco fields by 3.98%, 10.37%, 5.46%, and 3.43%, respectively. After marigold rotation, the relative abundances of Actinobacteria, Acidobacteria, and Ascomycota increased by 28.62%, 107.50%, and 57.44%, respectively, and the proportion of beneficial bacterial genera such as Nocardioides, Gemmatimonas, and Bradyrhizobium increased. In addition, our results also showed that rotation of marigold could effectively reduce the incidence of root-knot nematodes in the next crop of tobacco. These results indicate that marigold rotation had a positive effect on the soil microecological environment of continuously cropped tobacco fields, reducing the obstacles to continuous cropping of tobacco. [ABSTRACT FROM AUTHOR]

One of the most important activities in any organization is the identification and selection of the right supplier. The responsible organizations determine the performance of their potential suppliers based on the attributes that are aligned with their sustainable development goals. Data regarding these attributes can be qualitative and/or quantitative, and not every supplier selection methodology can handle them simultaneously. Data envelopment analysis (DEA) is an influential methodology for measuring the suppliers' performance, especially when there are more than one input and/or output. However, the original DEA model cannot consider human judgment during evaluation. In this regard, the current study proposes a novel methodology with the aid of the Ordinal Priority Approach (OPA) of multiple attributes decision-making and the DEA. The proposed method, the DEA-OPA model, truly enjoys the advantages of both DEA and OPA models, making it more powerful than the original DEA for performance measurement. The proposed model was compared with the original DEA and OPA then retested through incomplete data when the experts lack enough knowledge about inputs and outputs. Finally, a pilot application has been executed in the paper industry, and comprehensive sensitivity analysis has been performed to illustrate the feasibility of the proposed model. The findings are of significant importance to responsible enterprises and organizational decision-makers. [ABSTRACT FROM AUTHOR]

Despite many studies on the influence of cropping practices on soil microbial community structure, little is known about ecological patterns of rare and abundant microbial communities in response to different tobacco cropping systems. Here, using the high-throughput sequencing technique, we investigated the impacts of two different cropping systems on soil biochemical properties and the microbial community composition of abundant and rare taxa and its driving factors in continuous and rotational tobacco cropping systems in the mountain lands of Yunnan, China. Our results showed that distinct co-occurrence patterns and driving forces for abundant and rare taxa across the different cropping systems. The abundant taxa were mainly constrained by stochastic processes in both cropping systems. In contrast, rare taxa in continuous cropping fields were mainly influenced by environmental perturbation (cropping practice), while governed by deterministic processes under rotational cropping. The α-diversity indices of rare taxa tended to be higher than those of the abundant ones in the two cropping systems. Furthermore, the network topologies of rare taxa were more complex than those of the abundant taxa in the two cropping systems. These results highlight that rare taxa rather than abundant ones play important roles in maintaining ecosystem diversity and sustaining the stability of ecosystem functions, especially in continuous cropping systems. [ABSTRACT FROM AUTHOR]

Construction 4.0 has become a buzzword since the penetration of building information modeling (BIM), cyber-physical systems, and digital and computing technologies into the construction industry. Among emerging technologies, distributed ledger technology (DLT), or blockchain, is a powerful business enhancer whose potential can disrupt projects, AEC (architecture, engineering, and construction) firms, and construction supply chain, and in a broader sense, the whole construction industry. This technology has not reached the plateau of productivity due to several barriers and challenges. Previous studies have started to investigate the barriers to implementing DLT in various sectors and segmentations. However, we still need further surveys in the construction industry. This study evaluates the applicability of identified challenges and barriers based on a sustainability perspective. Precisely, we will answer which challenges need to be addressed for the sustainability of the construction industry. To meet the research objective, the ordinal priority approach (OPA) in multiple attributes decision-making (MADM) was utilized. This novel method determines the weight of sustainability attributes and barriers simultaneously. The results show that DLT implementation needs (i) infrastructure for data management, (ii) advanced applications and archetypes, and (iii) customers' demand, interest, and tendency, and (iv) taxation and reporting. Solving high-ranked challenges is the key to social sustainability from the aspects of "supply chain management and procurement"; "transparency, anti-corruption, and anti-counterfeiting"; and "fair operation and honest competition." [ABSTRACT FROM AUTHOR]

The most important problems that occur during the extraction of knowledge from data streams are related to the properties characterizing "BigData," namely high speed of information flow (velocity), variety of used forms, variability of data and diversity of information accuracy diagnosis methods (veracity). The use of online or sequential learning methods offers a specialized solution for solving real-time data processing problems. Data are provided without a clear knowledge of their particular inherent characteristics. Conventional approaches focus on applying heuristic or logical analysis rules. They fail to effectively handle new patterns (produced as a function of time) and to consider the dynamic change rate of their characteristics. In most cases, these methods approximate, by creating general rather than clear imprints of knowledge, which is hidden in the flows. Moreover, their function requires significant computational resources. This paper introduces (to the best of our knowledge, for the first time in the literature) the implementation of a specialized online reservoir computing architecture for smart city infrastructure protection which has low requirements in computing resources; it is efficient and suitable for real-time data flow analysis. More specifically, it describes the development of an echo state network, comprised of analog neurons with sparse random connections at the input levels and at the dynamical reservoir. Its training at the output level is performed with the recursive least square method. A complex data set was selected for the testing of the proposed model, which fully simulates the digital attacks that can be faced by the mechatronic equipment used in smart water supply networks located in the front end of the smart cities. [ABSTRACT FROM AUTHOR]

Nowadays, with the development of information management infrastructures in organizations and the improvement of the data storage process, managers are looking for appropriate decision-making methods based on large volumes of data. Therefore, it is crucial to choose the right approach to make the right decisions based on the volume of available data. The present study seeks to provide a comprehensive framework for the decision-making process using big data, even when it is incomplete. The framework of multiple criteria decision making (MCDM) consists of criteria and alternatives, whereas in real-world cases, decision-makers may face several criteria and alternatives. In this study, the Principal Component Analysis (PCA) approach was selected for the criteria clustering. Later, the K-means algorithm is used to cluster the alternatives, which estimates the optimal number of clusters using the Elbow method. The Fuzzy TOPSIS (TOPSIS-F) and Ordinal Priority Approach (OPA) have been used to rank clusters. Ultimately, the best alternative in the top cluster has been identified with the aid of the OPA, which has a unique function to solve MCDM problems with incomplete data. For evaluating the performance of the proposed approach, first, a pilot testing has been executed on a real-world case, and then a practical study was conducted at a refinery equipment manufacturing company with a project-oriented organizational structure. The approach is flexible, interactive, intelligent, and integrative, and significantly reduces the time and computation costs for the decision-makers. The results confirmed the soundness of the proposed approach, which can be used by managers of different companies with confidence. [ABSTRACT FROM AUTHOR]

Accurate evaluation of project performance is one of the biggest concerns of project-oriented organizations, and project managers are always looking for suitable tools and techniques to monitor and control the project activities. For a long time, the earned value management system is helping project managers in achieving this objective. However, its predominant focus on project cost and other limitations paved the way for the development of the earned duration management (EDM) system. The EDM system examines the performance of a project in term of time and can also measure the effectiveness of the project schedule at different stages. Since, in real-life, projects are frequently surrounded by uncertainties, the EDM system was extended to fuzzy EDM to make project performance evaluation more realistic but at the expense of increased computational costs and assumptions. Grey system theory is a promising soft computing approach for situations involving uncertainties and can be employed with the least possible information and assumptions. Unlike the fuzzy set theory, it does not require a membership function, thus facilitating data processing. By benefiting from these advantages, the current study aims to propose grey earned duration management (EDM-G) system and compares it with fuzzy EDM and the original EDM systems. The results suggest, the EDM-G system is a convenient and reliable system while it does not require sophisticated computations, large datasets, and membership functions. Finally, its execution on a real-life industrial case study confirmed its validity and reliability, even when multiple experts are involved in performance measurement. [ABSTRACT FROM AUTHOR]

This study assessed the relationships between maternal systemic lupus erythematosus (SLE) or rheumatoid arthritis (RA) and risk for autism spectrum disorders (ASDs) in offspring. Seven observational studies, including 25,005 ASD cases and 4,543,321 participants, were included for meta-analysis. Pooled results by using random-effects models suggested that maternal RA was associated with an increased risk for ASDs [odds ratio (OR) 1.39, 95% confidence interval (CI) 1.16–1.67], while maternal SLE was associated with an increased risk for ASDs only in western population (OR 1.91, 95% CI 1.02–3.57). Further study is warranted to confirm these results. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the possible genetic effect of sequence variations in TWIST1 on the pathogenesis of ventricular septal defect in humans. We examined the coding region of TWIST1 in a cohort of 196 Chinese people with non-syndromic ventricular septal defect patients and 200 healthy individuals as the controls. We identified two novel potential disease-associated mutations, NM_000474.3:c.247G>A (G83S) and NM_000474.3:c.283A>G (S95G). Both of them were identified for the first time and were not observed in the 200 controls without congenital heart disease. Using a dual-luciferase reporter assay, we showed that both of the mutations significantly down-regulated the repressive effect of TWIST1 on the E- cadherin promoter. Furthermore, a mammalian two-hybrid assay showed that both of the mutations significantly affected the interaction between TWIST1 and KAT2B. New mutations in the transcription factor TWIST1 that affect protein function were identified in 1.0 % (2/196) of Chinese patients with ventricular septal defect. Our data show, for the first time, that TWIST1 has a potential causative effect on the development of ventricular septal defect. [ABSTRACT FROM AUTHOR]

Aims: Metallothioneins are cysteine-rich, metal-binding proteins, but their exact functions are not fully understood. In this study, we isolated two metallothionein genes, BcMT1 and BcMT2 from Brassica campestris to increase our understanding of metal tolerance mechanisms in Brassica plants. Methods: Semi-quantitative RT-PCR was used to analyze expression of the two BcMTs genes. BcMT1 and BcMT2 were ectopically expressed in Arabidopsis thaliana. Quantitative real-time RT-PCR and GUS-staining method were used to select transgenic Arabidopsis plants. Cd and Cu concentrations were analyzed by flame atomic absorption spectrometry. Histochemical detection of HO and O were conducted by 3,3-diaminobenzidine and nitroblue tetrazoliu-staining methods. Results: BcMT1 is expressed predominantly in roots, whereas BcMT2 is expressed mainly in leaves of B. campestris. Expression of BcMT1 was induced by both Cd and Cu, but expression of BcMT2 was enhanced only by Cd. Ectopic expression of BcMT1 and BcMT2 in Arabidopsis thaliana enhanced the tolerance to Cd and Cu and increased the Cu concentration in the shoots of the transgenic plants. Transgenic Arabidopsis accumulated less reactive oxygen species (ROS) than wild-type plants. Conclusions: BcMT1 and BcMT2 increased Cd and Cu tolerance in transgenic Arabidopsis, and decreased production of Cd- and Cu-induced ROS, thereby protecting plants from oxidative damage. [ABSTRACT FROM AUTHOR]