Exploring the factors inducing contractors’ unethical behavior: Case of China

The construction industry is experiencing more serious ethical problems than ever before. The objectives of this study are to (1) identify the inducers of individuals’ unethical behavior in contractors’ organizations in the Chinese construction industry; and (2) investigate the interrelationships among these inducers. Based on a literature review and interviews, 18 factors inducing unethical behavior were identified, and a questionnaire survey was performed, which garnered 129 responses. The results showed that 13 inducers were significantly important, and that “cost pressures,” “inadequate sanctions,” and “absence of ethics systems” were the top three inducers of unethical behavior. Additionally, the 18 inducers were categorized into 5 underlying groupings: culture-related inducers; policy environment; project pressures; individual traits; and organizational climate. Further analysis results indicated that culture-related inducers indirectly influence organizational climate through their direct impact on policy environment, project pressures, and individual traits. The proposed framework describing the inducers and the intergrouping relationships provides an understanding of the formation mechanism of contractors’ unethical behavior

Risk paths in international construction projects: Case study from Chinese contractors

Contracting in overseas construction markets involves not only the typical risks at home, but also the complex and diverse risks peculiar to international transactions. In addition, international construction project risks are highly interdependent. The objectives of this study are to (1) explore the risk paths in the international construction projects performed by Chinese contractors, and (2) examine the risk effects on the objectives of these projects. To achieve the research objectives, a total of 60 risks were identified from literature review and a questionnaire survey was conducted with 104 professionals from Chinese international contractors. Adopting the structural equation modeling technique, this study proposed a networking of 20 significant risk paths. Specifically, host government–related risk, contractor’s lack of experience, and contractors’ lack of managerial skills had significant effect on project cost, quality, and schedule objectives, respectively. Moreover, host government–related risk affected project cost performance indirectly through resource price fluctuation, and contractors’ lack of managerial skills affects project schedule objective indirectly through decrease in productivity. This study contributes to the literature because it is different from most of the previous studies, which depended on separate risk categories and generic checklists but failed to explore the potential interrelationships among risks in international construction projects. Additionally, the identification of risk path scenarios enables practitioners to gain a better understanding of the sources and impact areas of risks, and to better deal with the risks, thereby contributing to the practice

Summarizing source code through heterogeneous feature fusion and extraction

Code summarization, which seeks to automatically produce a succinct natural-language description to summarize the functionality of source code, plays an essential role in maintaining the software. Currently, plentiful approaches have been proposed to first encode the source code based on its Abstract Syntax Tree (AST), and then decode it into a textual summary. However, most existing works interpret the AST-based syntax structure as a homogeneous graph, without discriminating the different relations between graph nodes (e.g., the parent–child and sibling relations) in a heterogeneous way. To mitigate this issue, this paper proposes HETCOS to extract the syntactic and sequential features of source code by exploring its inherent heterogeneity for code summarization. Specifically, we first build a Heterogeneous Code Graph (HCG) that fuses the syntax structure and code sequence with eight types of edges/relations designed between graph nodes. Moreover, we present a heterogeneous graph neural network for capturing the diverse relations in HCG. The represented HCG is then fed into a Transformer decoder, followed by a multi-head attention-based copying mechanism to support high-quality summary generation. Extensive experiments on the major Java and Python datasets illustrate the superiority of our approach over sixteen state-of-the-art baselines. To promote reproducibility studies, we make the implementation of HETCOS publicly accessible at https://github.com/GJCEXP/HETCOS.</p

Measuring Sustainable Intensification Using Satellite Remote Sensing Data

Farm-level sustainable intensification metrics are needed to evaluate farm performance and support policy-making processes aimed at enhancing sustainable production. Farm-level sustainable intensification metrics require environmental impacts associated with agricultural production to be accounted for. However, it is common that such indicators are not available. We show how satellite-based remote sensing information can be used in combination with farm efficiency analysis to obtain a sustainable intensification (SI) indicator, which can serve as a sustainability benchmarking tool for farmers and policy makers. We obtained an SI indicator for 114 maize farms in Yangxin County, located in the Shandong Province in China, by combining information on maize output and inputs with satellite information on the leaf area index (from which a nitrogen environmental damage indicator is derived) into a farm technical efficiency analysis using a stochastic frontier approach. We compare farm-level efficiency scores between models that incorporate environmental damage indicators based on satellite-based remote sensing information and models that do not account for environmental impact. The results demonstrate that (a) satellite-based information can be used to account for environmental impacts associated with agriculture production and (b) how the environmental impact metrics derived from satellite-based information combined with farm efficiency analysis can be used to obtain a farm-level sustainable intensification indicator. The approach can be used to obtain tools for farmers and policy makers aiming at improving SI

Improved reinforcement learning-based real-time energy scheduling for prosumer with elastic loads in smart grid

In this study, we investigate the dynamic energy-scheduling problem of a prosumer (producer/consumer) with an energy storage device (EDS) and elastic loads. The goal is to develop efficient real-time scheduling strategies for prosumers, and to minimise their total long-term costs (i.e. cost of energy purchased from the external grid and depreciation cost of the EDS). The challenges are twofold: the uncertainty of the energy output of the prosumer and the time-coupling constraints of the EDS and elastic loads. To address these challenges, we first describe the dynamic energy-scheduling problem as a Markov decision process. Then, an approximate state dual-agent Q-learning algorithm is proposed to solve the optimal dynamic scheduling problem by improving the model-free reinforcement learning(RL) method. Compared with the traditional RL method, the proposed algorithm reduces the system-state dimensions and exhibits improved performance. The proposed algorithm can only be assisted by mutual interactions between the environment with a reward feedback mechanism to dynamically respond to uncertain changes in the environments, without modelling or predicting the system environments. Finally, extensive empirical evaluations using real-world traces are conducted to study the effectiveness of the proposed algorithm. The results show that the proposed algorithm can reduce the total cost of the prosumer by up to 6.3%, 11.7% and 22.4% compared with the traditional RL method, Lyapunov optimisation and greedy algorithm, respectively

Designing a Secure Blockchain-Based Supply Chain Management Framework

Supply chain management (SCM) faces a critical security issue because of the asymmetry of information delivered to various parties in the ecosystem and the lack of corresponding supervision. In response, we propose the use of blockchain technology to address the SCM security issues and put forward a blockchain-based SCM framework. We apply design science paradigm to guide the blockchain-based SCM framework development and implementation of a proof-of-concept prototype. We use Hyperledger Fabric and Composer to develop the prototype artifact. Performance evaluation results issued from Hyperledger Caliper prove the superiority and robustness of the proposed blockchain-based framework in terms of security and efficiency requirements, and performance metrics including throughput and latency. Also, the evaluation results show that the IT artifact is stable, and the high stability can reduce the risks of system vulnerabilities and breakdown

Comparative non-targeted metabolomic analysis reveals insights into the mechanism of rice yellowing

Yellowing of rice during storage is a highly concerned issue for managing rice quality whereas the yellowing mechanism is not clearly elucidated so far. Thus, the comparative untargeted metabolomic analysis was performed in this study. The results revealed that glycolysis pathway and tricarboxylic acid cycle (TCA) were significantly enhanced in yellowed rice, indicating the activated energy metabolism was trigged during the yellowing process. In addition, the increased aromatic compounds (4-hydroxycinnamic acid and benzoic acid) and their precursors (phenylalanine, tyrosine) suggested the activation of shikimate-phenylpropanoid biosynthesis in yellowed rice, which is an antioxidant defense related pathway. In particular, the pathways involved in the metabolism of glutamate and arginine also significantly altered in yellowed rice. Therefore, the enriched pathways of increased amino acids, sugars, sugar alcohols, and intermediates of the TCA cycle during yellowing process are proposed to be associated with the response of heat and dry induced by the yellowing process. © 2019 Elsevier Lt

The Gene Ontology Differs in Bursa of Fabricius Between Two Breeds of Ducks Post Hatching by Enriching the Differentially Expressed Genes

<div><p>ABSTRACT The bursa of Fabricius (BF) is the central humoral immune organ unique to birds. The present study investigated the possible difference on a molecular level between two duck breeds. The digital gene expression profiling (DGE) technology was used to enrich the differentially expressed genes (DEGs) in BF between the Jianchang and Nonghua-P strains of ducks. DGE data identified 195 DEGs in the bursa. Gene Ontology (GO) analysis suggested that DEGs were mainly enriched in the metabolic pathways and ribosome components. Pathways analysis identified the spliceosome, RNA transport, RNA degradation process, Jak-STAT signaling pathway, TNF signaling pathway and B cell receptor signaling pathway. The results indicated that the main difference in the BF between the two duck strains was in the capabilities of protein formation and B cell development. These data have revealed the main divergence in the BF on a molecular level between genetically different duck breeds and may help to perform molecular breeding programs in poultry in the future.</p></div

Citrate esterification of debranched waxy maize starch: Structural, physicochemical and amylolysis properties

Considering that the content of resistant starch (RS) in original starch is very low, chemical modification is one of choices to increase RS level for enhancing its application. The current study applied debranched waxy maize starch (DBS) to produce a citrate-esterified debranched starch (CADS) and investigated impact of the modification on RS formation. Native starch was also citrate esterified without debranching treatment as the control (CANS). Physicochemical and digestion properties of each sample were characterized, and the results indicated an absorption at 1724 cm −1 in FTIR spectrum was determined in either CADS or CANS, indicating the occurrence of the esterification. Debranching of starch molecules led to a higher degree of substitution (DS) of 0.793 for CADS than CANS. Furthermore, re-association of debranched starch achieved a B type crystalline pattern rather than an A type from its native starch granules. Esterification greatly destroyed crystalline regions until completely disappeared in CADS. The loss of crystalline region was highly consistent with the absence of endothermic peak both in CADS and CANS as revealed by DSC. Hydrolysis rate and digestibility of each sample followed the order: native starch > DBS > CANS > CADS, which may indicate that the introduction of the citric anhydride onto the starch molecules led to an increased space steric hindrance that delayed the enzyme contacting within glucosidic bonds. It could be the first report to prepare a citrate-esterified debranched starch with a higher resistance to amylolysis, and the current investigation may highlight a potent to produce a starch derivative with a higher RS content. © 2020 Elsevier Lt

Co3Se4 quantum dots encapsulated with nitrogen-doped porous nanocarbon as ultrastable electrode material for water-based all-solid asymmetric supercapacitors

Co3Se4 quantum dots encapsulated with nitrogen-doped porous nanocarbon as ultrastable electrode material for water-based all-solid asymmetric supercapacitor