Inherent mechanism of digital technology application empowered corporate green innovation: Based on resource allocation perspective.

Confronted with the treacherous digital wave and the aggressive environmental challenges, digital technology and green innovation are becoming critical tools for corporations to secure a sustainable advantage. The significance of identifying the role of digital technology application on corporate green innovation has been widely debated in the extant literature. Nevertheless, few researchers have investigated the inherent mechanism between them from the resource allocation perspective. From this research gap, we construct a theoretical model of the inherent mechanism by which digital technology application affects corporate green innovation, validate it using listed corporations in China from 2011 to 2020, and further investigate the differences in their inherent mechanism triggered by property rights and industry competition. We found that digital technology application is effective in promoting corporate green innovation. Stronger green innovation effect of digital technology application in state-owned corporations and those in highly competitive industries. The inherent mechanism between them manifest in optimizing the allocation of conventional labor, expanding the scale of non-conventional labor, and enhancing investment in R&D and digital infrastructure capital. We further explored that the impact of applying digital technology to optimize conventional labor allocation, expand non-conventional labor scale, and enhance investment in R&D and digital infrastructure capital is stronger for corporations in highly competitive industries than those in lowly competitive industries. The difference is that the role of the digital technology application in boosting capital investment in R&D does not differ across corporations with different property rights. Findings provide theoretical and empirical evidence on effectively developing the digital technology application's green innovative effects.

The effects of digital technology application and supply chain management on corporate circular economy: A dynamic capability view.

Developing circular economy capability has emerged as an effective response to environmental pressures on firms. The proliferation of digital technology has created uncertainty in developing corporate circular economy capability. Although research has begun to focus on the impact of digital technology application on corporate circular economy capability, empirical evidence remains absent. Simultaneously, few studies have concerned corporate circular economy capability obtained from supply chain management. The answer to the correlation between digital technology application, supply chain management, and circular economy capability is unavailable in current research. Based on a dynamic capability view, we investigate how digital technology application affects corporate circular economy capability through supply chain management regarding supply chain risk management, collaboration, and integration. This underlying mechanism was verified with 486 Chinese-listed industrial firms and the mediating model. The findings demonstrate that digital technology application and supply chain management significantly affect corporate circular economy capability. The mediating channel whereby the digital technology application provides circular economy capability can facilitate the positive impact of supply chain risk management and collaboration while undermining the adverse effects of supply chain integration. These mediating channels differentiate in heterogeneous growth firms and are more pronounced in low-growth groups. It presents an opportunity to use digital technology to reinforce the positive impact of supply chain risk management and collaboration and mitigate the negative effect of supply chain integration on circular economy capability.

Nitric oxide synthase and reduced arterial tone contribute to arteriovenous malformation.

Mechanisms underlying arteriovenous malformations (AVMs) are poorly understood. Using mice with endothelial cell (EC) expression of constitutively active Notch4 (Notch4*EC), we show decreased arteriolar tone in vivo during brain AVM initiation. Reduced vascular tone is a primary effect of Notch4*EC, as isolated pial arteries from asymptomatic mice exhibited reduced pressure-induced arterial tone ex vivo. The nitric oxide (NO) synthase (NOS) inhibitor NG-nitro-l-arginine (L-NNA) corrected vascular tone defects in both assays. L-NNA treatment or endothelial NOS (eNOS) gene deletion, either globally or specifically in ECs, attenuated AVM initiation, assessed by decreased AVM diameter and delayed time to moribund. Administering nitroxide antioxidant 4-hydroxy-2,2,6,6-tetramethylpiperidine-1-oxyl also attenuated AVM initiation. Increased NOS-dependent production of hydrogen peroxide, but not NO, superoxide, or peroxynitrite was detected in isolated Notch4*EC brain vessels during AVM initiation. Our data suggest that eNOS is involved in Notch4*EC-mediated AVM formation by up-regulating hydrogen peroxide and reducing vascular tone, thereby permitting AVM initiation and progression.

Mitochondrial dysfunction reactivates α-fetoprotein expression that drives copper-dependent immunosuppression in mitochondrial disease models.

Signaling circuits crucial to systemic physiology are widespread, yet uncovering their molecular underpinnings remains a barrier to understanding the etiology of many metabolic disorders. Here, we identified a copper-linked signaling circuit activated by disruption of mitochondrial function in the murine liver or heart that resulted in atrophy of the spleen and thymus and caused a peripheral white blood cell deficiency. We demonstrated that the leukopenia was caused by α-fetoprotein, which required copper and the cell surface receptor CCR5 to promote white blood cell death. We further showed that α-fetoprotein expression was upregulated in several cell types upon inhibition of oxidative phosphorylation. Collectively, our data argue that α-fetoprotein may be secreted by bioenergetically stressed tissue to suppress the immune system, an effect that may explain the recurrent or chronic infections that are observed in a subset of mitochondrial diseases or in other disorders with secondary mitochondrial dysfunction.

Robust optimization model of anti-epidemic supply chain under technological innovation: learning from COVID-19.

The anti-epidemic supply chain plays an important role in the prevention and control of the COVID-19 pandemic. Prior research has focused on studying the facility location, inventory management, and route optimization of the supply chain by using certain parameters and models. Nevertheless, uncertainty, as a vital influence factor, greatly affects the supply chain. As such, the uncertainty that comes with technological innovation has a heightened influence on the supply chain. Few studies have explicitly investigated the influence of technological innovation on the anti-epidemic supply chain under the COVID-19 pandemic. Hence, the current research aims to investigate the influences of the uncertainty caused by technological innovation on the supply chain from demand and supply, shortage penalty, and budget. This paper presents a three-level model of the anti-epidemic supply chain under technological innovation and employs an interval data robust optimization to tackle the uncertainties of the model. The findings are obtained as follows. Firstly, the shortage penalty will increase the costs of the objective function but effectively improve demand satisfaction. Secondly, if the shortage penalty is sufficiently large, the minimum demand satisfaction rate can ensure a fair distribution of materials among the affected areas. Thirdly, technological innovation can reduce costs. The technological innovation related to the transportation costs of the anti-epidemic material distribution center has a greater influence on the optimal value. Meanwhile, the technological innovation related to the transportation costs of the supplier has the least influence. Fourthly, both supply and demand uncertainty can influence costs, but demand uncertainty has a greater influence. Fifthly, the multi-scenario budgeting approach can decrease the calculation complexity. These findings provide theoretical support for anti-epidemic dispatchers to adjust the conservativeness of uncertain parameters under the influence of technological innovation.

Effect of Chinese pilots carbon emission trading scheme on enterprises' total factor productivity: The moderating role of government participation and carbon trading market efficiency.

Based on the tightening regulation of carbon emissions, China has launched the pilot carbon emission trading scheme (CETS) since 2013. There is growing empirical evidence of the actual effect of CETS to promote enterprises' productivity which is characterized by total factor productivity (TFP). However, most studies ignored the further analysis of influence mechanisms. This paper aims to explore the impact of CETS on the TFP of enterprises and discuss the mediating role of government participation and carbon trading market efficiency. Using data from A-share listed enterprises from CETS-covered enterprises, this paper employed a combination of the propensity score matching (PSM) and difference-in-differences (DID) strategies and found that the CETS has a statistically significant positive impact on the TFP of enterprises, and the positive effect has been maintained for six years since its inception. The moderation analysis indicated that: (1) two dimensions of government participation in terms of the market incentive and government supervision significantly moderate the positive impact of CETS on TFP of enterprises; (2) two dimensions of carbon trading market efficiency in terms of the market scale and liquidity significantly moderates the positive impact of CETS on TFP of enterprises. In light of Chinese pilots CETS policy, the study highlights the important moderating roles of government participation and high carbon trading market efficiency on enterprise's TFP.

Oral Elesclomol Treatment Alleviates Copper Deficiency in Animal Models.

Copper (Cu) is an essential trace element for key biochemical reactions. Dietary or genetic copper deficiencies are associated with anemia, cardiomyopathy, and neurodegeneration. The essential requirement for copper in humans is illustrated by Menkes disease, a fatal neurodegenerative disorder of early childhood caused by mutations in the ATP7A copper transporter. Recent groundbreaking studies have demonstrated that a copper delivery small molecule compound, elesclomol (ES), is able to substantially ameliorate pathology and lethality in a mouse model of Menkes disease when injected as an ES-Cu2+ complex. It is well appreciated that drugs administered through oral means are more convenient with better efficacy than injection methods. Here we show, using genetic models of copper-deficient C. elegans and mice, that dietary ES supplementation fully rescues copper deficiency phenotypes. Worms lacking either the homolog of the CTR1 copper importer or the ATP7 copper exporter showed normal development when fed ES. Oral gavage with ES rescued intestine-specific Ctr1 knockout mice from early postnatal lethality without additional copper supplementation. Our findings reveal that ES facilitates copper delivery from dietary sources independent of the intestinal copper transporter CTR1 and provide insight into oral administration of ES as an optimal therapeutic for Menkes disease and possibly other disorders of copper insufficiency.

Corporate carbon disclosure, financing structure, and total factor productivity: evidence from Chinese heavy polluting enterprises.

Low-carbon economy has become the current global economic development trend, and corporate carbon disclosure has attracted more and more attention from scholars and investors. This study creatively explores the mechanism of corporate carbon disclosure on total factor productivity with financing structure as a mediating variable. The content analysis method is employed to assess carbon disclosure that is suitable for Chinese enterprises. Through the mediating effect model and Sobel test, the internal mechanism of carbon disclosure affecting total factor productivity is analyzed, with Chinese heavy polluting enterprises from 2015 to 2018 as research samples. The results show that, firstly, carbon disclosure has a positive effect on the improvement of total factor productivity. The effect of monetary carbon disclosure on the improvement of total factor productivity is higher than that of non-monetary carbon disclosure. Secondly, the financing structure has a mediating effect between carbon disclosure and total factor profductivity, and the mediating effect of internal financing capabilities is better than those of external financing costs. Finally, external financing costs and internal financing capabilities have mediating effects in both heterogeneous carbon disclosure and total factor productivity. The mediating effect of internal financing capabilities is significantly higher than the mediating effect of external financing costs. The effect of monetary carbon disclosure on total factor productivity indirectly through internal financing capabilities is higher than that of non-monetary carbon disclosure.

Heat-response patterns of the heat shock transcription factor family in advanced development stages of wheat (Triticum aestivum L.) and thermotolerance-regulation by TaHsfA2-10.

BACKGROUND: Heat shock transcription factors (Hsfs) are present in majority of plants and play central roles in thermotolerance, transgenerational thermomemory, and many other stress responses. Our previous paper identified at least 82 Hsf members in a genome-wide study on wheat (Triticum aestivum L.). In this study, we analyzed the Hsf expression profiles in the advanced development stages of wheat, isolated the markedly heat-responsive gene TaHsfA2-10 (GenBank accession number MK922287), and characterized this gene and its role in thermotolerance regulation in seedlings of Arabidopsis thaliana (L. Heynh.). RESULTS: In the advanced development stages, wheat Hsf family transcription profiles exhibit different expression patterns and varying heat-responses in leaves and roots, and Hsfs are constitutively expressed to different degrees under the normal growth conditions. Overall, the majority of group A and B Hsfs are expressed in leaves while group C Hsfs are expressed at higher levels in roots. The expression of a few Hsf genes could not be detected. Heat shock (HS) caused upregulation about a quarter of genes in leaves and roots, while a number of genes were downregulated in response to HS. The highly heat-responsive gene TaHsfA2-10 was isolated through homeologous cloning. qRT-PCR revealed that TaHsfA2-10 is expressed in a wide range of tissues and organs of different development stages of wheat under the normal growth conditions. Compared to non-stress treatment, TaHsfA2-10 was highly upregulated in response to HS, H2O2, and salicylic acid (SA), and was downregulated by abscisic acid (ABA) treatment in two-leaf-old seedlings. Transient transfection of tobacco epidermal cells revealed subcellular localization of TaHsfA2-10 in the nucleus under the normal growth conditions. Phenotypic observation indicated that TaHsfA2-10 could improve both basal thermotolerance and acquired thermotolerance of transgenic Arabidopsis thaliana seedlings and rescue the thermotolerance defect of the T-DNA insertion mutant athsfa2 during HS. Compared to wild type (WT) seedlings, the TaHsfA2-10-overexpressing lines displayed both higher chlorophyll contents and higher survival rates. Yeast one-hybrid assay results revealed that TaHsfA2-10 had transactivation activity. The expression levels of thermotolerance-related AtHsps in the TaHsfA2-10 transgeinc Arabidopsis thaliana were higher than those in WT after HS. CONCLUSIONS: Wheat Hsf family members exhibit diversification and specificity of transcription expression patterns in advanced development stages under the normal conditions and after HS. As a markedly responsive transcriptional factor to HS, SA and H2O2, TaHsfA2-10 involves in thermotolerance regulation of plants through binding to the HS responsive element in promoter domain of relative Hsps and upregulating the expression of Hsp genes.

Elesclomol alleviates Menkes pathology and mortality by escorting Cu to cuproenzymes in mice.

Loss-of-function mutations in the copper (Cu) transporter ATP7A cause Menkes disease. Menkes is an infantile, fatal, hereditary copper-deficiency disorder that is characterized by progressive neurological injury culminating in death, typically by 3 years of age. Severe copper deficiency leads to multiple pathologies, including impaired energy generation caused by cytochrome c oxidase dysfunction in the mitochondria. Here we report that the small molecule elesclomol escorted copper to the mitochondria and increased cytochrome c oxidase levels in the brain. Through this mechanism, elesclomol prevented detrimental neurodegenerative changes and improved the survival of the mottled-brindled mouse-a murine model of severe Menkes disease. Thus, elesclomol holds promise for the treatment of Menkes and associated disorders of hereditary copper deficiency.

CHCA-1 is a copper-regulated CTR1 homolog required for normal development, copper accumulation, and copper-sensing behavior in Caenorhabditis elegans.

Copper plays key roles in catalytic and regulatory biochemical reactions essential for normal growth, development, and health. Dietary copper deficiencies or mutations in copper homeostasis genes can lead to abnormal musculoskeletal development, cognitive disorders, and poor growth. In yeast and mammals, copper is acquired through the activities of the CTR1 family of high-affinity copper transporters. However, the mechanisms of systemic responses to dietary or tissue-specific copper deficiency remain unclear. Here, taking advantage of the animal model Caenorhabditis elegans for studying whole-body copper homeostasis, we investigated the role of a C. elegans CTR1 homolog, CHCA-1, in copper acquisition and in worm growth, development, and behavior. Using sequence homology searches, we identified 10 potential orthologs to mammalian CTR1 Among these genes, we found that chca-1, which is transcriptionally up-regulated in the intestine and hypodermis of C. elegans during copper deficiency, is required for normal growth, reproduction, and maintenance of systemic copper balance under copper deprivation. The intestinal copper transporter CUA-1 normally traffics to endosomes to sequester excess copper, and we found here that loss of chca-1 caused CUA-1 to mislocalize to the basolateral membrane under copper overload conditions. Moreover, animals lacking chca-1 exhibited significantly reduced copper avoidance behavior in response to toxic copper conditions compared with WT worms. These results establish that CHCA-1-mediated copper acquisition in C. elegans is crucial for normal growth, development, and copper-sensing behavior.

An Efficient Method of Sharing Mass Spatio-Temporal Trajectory Data Based on Cloudera Impala for Traffic Distribution Mapping in an Urban City.

The efficient sharing of spatio-temporal trajectory data is important to understand traffic congestion in mass data. However, the data volumes of bus networks in urban cities are growing rapidly, reaching daily volumes of one hundred million datapoints. Accessing and retrieving mass spatio-temporal trajectory data in any field is hard and inefficient due to limited computational capabilities and incomplete data organization mechanisms. Therefore, we propose an optimized and efficient spatio-temporal trajectory data retrieval method based on the Cloudera Impala query engine, called ESTRI, to enhance the efficiency of mass data sharing. As an excellent query tool for mass data, Impala can be applied for mass spatio-temporal trajectory data sharing. In ESTRI we extend the spatio-temporal trajectory data retrieval function of Impala and design a suitable data partitioning method. In our experiments, the Taiyuan BeiDou (BD) bus network is selected, containing 2300 buses with BD positioning sensors, producing 20 million records every day, resulting in two difficulties as described in the Introduction section. In addition, ESTRI and MongoDB are applied in experiments. The experiments show that ESTRI achieves the most efficient data retrieval compared to retrieval using MongoDB for data volumes of fifty million, one hundred million, one hundred and fifty million, and two hundred million. The performance of ESTRI is approximately seven times higher than that of MongoDB. The experiments show that ESTRI is an effective method for retrieving mass spatio-temporal trajectory data. Finally, bus distribution mapping in Taiyuan city is achieved, describing the buses density in different regions at different times throughout the day, which can be applied in future studies of transport, such as traffic scheduling, traffic planning and traffic behavior management in intelligent public transportation systems.