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Data-driven decision-making (DDDM) has become integral to managerial and organizational processes in the era of digitalization and internationalization. This study explores the impact of DDDM on international firm performance. Leveraging AI language models, specifically BERT and ChatGLM2-6B, to quantify DDDM, we find that DDDM positively impacts international firm performance. To uncover the mechanisms underlying this correlation, we develop a framework explaining how DDDM creates sustainable value for firms, thereby enhancing international firm performance across four dimensions: pollution prevention (current internal), green innovation (future internal), sustainability information disclosure (current external), and sustainability vision co-creation (future external). Additionally, this study reveals that the positive impact of DDDM on international firm performance is amplified by higher market competition, greater foreign shareholding, and state ownership.

The carbon atom provides the backbone for the complex organic chemistry composing the building blocks of life. The physics of the carbon nucleus in its predominant isotope, 12 C, is similarly full of multifaceted complexity. Here we provide a model-independent density map of the geometry of the nuclear states of 12 C using the ab initio framework of nuclear lattice effective field theory. We find that the well-known but enigmatic Hoyle state is composed of a “bent-arm” or obtuse triangular arrangement of alpha clusters. We identify all of the low-lying nuclear states of 12 C as having an intrinsic shape composed of three alpha clusters forming either an equilateral triangle or an obtuse triangle. The states with the equilateral triangle formation also have a dual description in terms of particle-hole excitations in the mean-field picture. Carbon ( 12 C) nucleus has interesting characteristics including the existence of the Hoyle state. Here the authors discuss the structure of the nuclear states of 12 C by using nuclear lattice effective field theory.

Electrochemical hydrogen evolution reaction in neutral media is listed as the most difficult challenges of energy catalysis due to the sluggish kinetics. Herein, the Ir-H x WO 3 catalyst is readily synthesized and exhibits enhanced performance for neutral hydrogen evolution reaction. H x WO 3 support is functioned as proton sponge to create a local acid-like microenvironment around Ir metal sites by spontaneous injection of protons to WO 3 , as evidenced by spectroscopy and electrochemical analysis. Rationalize revitalized lattice-hydrogen species located in the interface are coupled with H ad atoms on metallic Ir surfaces via thermodynamically favorable Volmer-Tafel steps, and thereby a fast kinetics. Elaborated Ir-H x WO 3 demonstrates acid-like activity with a low overpotential of 20 mV at 10 mA cm −2 and low Tafel slope of 28 mV dec −1 , which are even comparable to those in acidic environment. The concept exemplified in this work offer the possibilities for tailoring local reaction microenvironment to regulate catalytic activity and pathway. The development of neutral hydrogen evolution catalysts is challenging due to their sluggish kinetics. Here the authors report H x WO 3 support which acts as proton sponge to create a local acid-like microenvironment around Ir sites, realizing acid-like hydrogen evolution rate in neutral media.

Small nucleolar RNAs (snoRNAs), a type of non-coding RNA, are widely present in the nucleoli of eukaryotic cells and play an important role in rRNA modification. With the recent increase in research on snoRNAs, new evidence has emerged indicating that snoRNAs also participate in tRNA and mRNA modification. Studies suggest that numerous snoRNAs, including tumor-promoting and tumor-suppressing snoRNAs, are not only dysregulated in tumors but also show associations with clinical prognosis. In this review, we summarize the reported functions of snoRNAs and the possible mechanisms underlying their role in tumorigenesis and cancer development to guide the snoRNA-based clinical diagnosis and treatment of cancer in the future.

We give an overview of the work done during the past ten years on the Casimir interaction in electronic topological materials, our focus being solids, which possess surface or bulk electronic band structures with nontrivial topologies, which can be evinced through optical properties that are characterizable in terms of nonzero topological invariants. The examples we review are three-dimensional magnetic topological insulators, two-dimensional Chern insulators, graphene monolayers exhibiting the relativistic quantum Hall effect, and time reversal symmetry-broken Weyl semimetals, which are fascinating systems in the context of Casimir physics. Firstly, this is for the reason that they possess electromagnetic properties characterizable by axial vectors (because of time reversal symmetry breaking), and, depending on the mutual orientation of a pair of such axial vectors, two systems can experience a repulsive Casimir–Lifshitz force, even though they may be dielectrically identical. Secondly, the repulsion thus generated is potentially robust against weak disorder, as such repulsion is associated with the Hall conductivity that is topologically protected in the zero-frequency limit. Finally, the far-field low-temperature behavior of the Casimir force of such systems can provide signatures of topological quantization.

Remote sensing is a useful tool for monitoring spatio-temporal variations of crop morphological and physiological status and supporting practices in precision farming. In comparison with multispectral imaging, hyperspectral imaging is a more advanced technique that is capable of acquiring a detailed spectral response of target features. Due to limited accessibility outside of the scientific community, hyperspectral images have not been widely used in precision agriculture. In recent years, different mini-sized and low-cost airborne hyperspectral sensors (e.g., Headwall Micro-Hyperspec, Cubert UHD 185-Firefly) have been developed, and advanced spaceborne hyperspectral sensors have also been or will be launched (e.g., PRISMA, DESIS, EnMAP, HyspIRI). Hyperspectral imaging is becoming more widely available to agricultural applications. Meanwhile, the acquisition, processing, and analysis of hyperspectral imagery still remain a challenging research topic (e.g., large data volume, high data dimensionality, and complex information analysis). It is hence beneficial to conduct a thorough and in-depth review of the hyperspectral imaging technology (e.g., different platforms and sensors), methods available for processing and analyzing hyperspectral information, and recent advances of hyperspectral imaging in agricultural applications. Publications over the past 30 years in hyperspectral imaging technology and applications in agriculture were thus reviewed. The imaging platforms and sensors, together with analytic methods used in the literature, were discussed. Performances of hyperspectral imaging for different applications (e.g., crop biophysical and biochemical properties’ mapping, soil characteristics, and crop classification) were also evaluated. This review is intended to assist agricultural researchers and practitioners to better understand the strengths and limitations of hyperspectral imaging to agricultural applications and promote the adoption of this valuable technology. Recommendations for future hyperspectral imaging research for precision agriculture are also presented.

Oral administration of resveratrol is able to ameliorate the progression of diabetic nephropathy (DN); however, its mechanisms of action remain unclear. Recent evidence suggested that the gut microbiota is involved in the metabolism therapeutics. In the current study, we sought to determine whether the anti-DN effects of resveratrol are mediated through modulation of the gut microbiota using the genetic db/db mouse model of DN. We demonstrate that resveratrol treatment of db/db mice relieves a series of clinical indicators of DN. We then show that resveratrol improves intestinal barrier function and ameliorates intestinal permeability and inflammation. The composition of the gut microbiome was significantly altered in db/db mice compared to control db/m mice. Dysbiosis in db/db mice characterized by low abundance levels of Bacteroides , Alistipes , Rikenella , Odoribacter , Parabacteroides , and Alloprevotella genera were reversed by resveratrol treatment, suggesting a potential role for the microbiome in DN progression. Furthermore, fecal microbiota transplantation, derived from healthy resveratrol-treated db/m mice, was sufficient to antagonize the renal dysfunction, rebalance the gut microbiome and improve intestinal permeability and inflammation in recipient db/db mice. These results indicate that resveratrol-mediated changes in the gut microbiome may play an important role in the mechanism of action of resveratrol, which provides supporting evidence for the gut–kidney axis in DN.

Quantum Monte Carlo (QMC) is a family of powerful tools for addressing quantum many-body problems. However, its applications are often plagued by the fermionic sign problem. A promising strategy is to simulate an interaction without sign problem as the zeroth order and treat the other pieces as perturbations. According to this scheme, we construct precision nuclear chiral forces on the lattice and make perturbative calculations around a sign-problem-free interaction respecting the Wigner-SU4 symmetry. We employ the recently developed perturbative QMC (ptQMC) method to calculate the perturbative energies up to the second order. This work presents the first ptQMC calculations for two-body next-to-next-to-next-to leading order ( N 3 LO) chiral forces and elucidates how the hierarchical nature of the chiral interactions helps organize and simplify the ptQMC calculations. We benchmark the algorithm for the deuteron, where exact solutions serve as rigorous reference points. We also reproduce the famous Tjon line by correlating the perturbative 4 He binding energies with the non-perturbative 3 H binding energies. These comprehensive demonstrations underscore the efficacy of ptQMC in resolving high-fidelity nuclear interactions, establishing its potential as a robust tool for ab initio nuclear structure studies.

Constant water circulation between land, ocean and atmosphere contains great and sustainable energy, which has been successfully employed to generate electricity by the burgeoning water-enabled electric generator. However, water in various forms (e.g. liquid, moisture) is inevitably discharged after one-time use in current single-stage water-enabled electric generators, resulting in the huge waste of inherent energy within water circulation. Herein, a multistage coupling water-enabled electric generator is proposed, which utilizes the internal liquid flow and subsequently generated moisture to produce electricity synchronously, achieving a maximum output power density of ~92 mW m −2 (~11 W m −3 ). Furthermore, a distributary design for internal water in different forms enables the integration of water-flow-enabled and moisture-diffusion-enabled electricity generation layers into mc-WEG by a “flexible building blocks” strategy. Through a three-stage adjustment process encompassing size control, space optimization, and large-scale integration, the multistage coupling water-enabled electric generator realizes the customized electricity output for diverse electronics. Twenty-two units connected in series can deliver ~10 V and ~280 μA, which can directly lighten a table lamp for 30 min without aforehand capacitor charging. In addition, multistage coupling water-enabled electric generators exhibit excellent flexibility and environmental adaptability, providing a way for the development of water-enabled electric generators. Liquid water or moisture discharge is a significant source of energy waste in current single-stage water-enabled electric generators. Here, authors propose a modular multistage coupling device that integrates internal liquid water flow and subsequently generated moisture to optimize energy harvesting at all stages.

A heterodinuclear MgCo catalyst has been shown to be highly active for the copolymerization of CO2 and epoxides under low (atmospheric) CO2 pressures. Its performance arises from the intramolecular synergy between the two metals, which adopt distinct roles and mediate each other’s reactivity during catalysis.