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Frequent disruptions to global supply chains, driven by factors such as trade restrictions and geopolitical conflicts, brought supply chain resilience to the forefront of both academic research and industry practice. Concurrently, the rapid advancement of artificial intelligence (AI) technologies in supply chain management in recent years offers new perspectives for researching resilience. Based on the Organizational Information Processing Theory (OIPT), this study explores the direct and indirect mechanisms through which AI usage impacts supply chain resilience from an information processing perspective. Within the OIPT framework, we develop a theoretical model incorporating AI usage, supply chain resilience, supply chain efficiency, supply chain collaboration, and digital information technology capability. We empirically test the model using survey data collected from 231 Chinese manufacturing senior executives and supply chain managers, employing partial least squares structural equation modeling (PLS-SEM). The findings reveal that AI usage has a significant direct positive effect on supply chain resilience. Additionally, supply chain efficiency and collaboration act as mediators in this relationship. Furthermore, we examined the moderating role of a firm’s digital information technology capability and found that it positively moderates the impact of AI usage on supply chain resilience.

Digital transformation is a critical tool driving enterprises’ innovation capabilities. This study investigates the nexus between the degree of digital transformation and sustainable innovation from dual perspective. It selects 805 listed manufacturing enterprises on the A-share from 2012 to 2021, categorizes sustainability innovation into exploitative sustainability and exploratory sustainability innovations, and empirically examines the impact of digital transformation on these innovation types. The results indicate that the effects of digital transformation on these two sustainability innovation types are significant, showing an inverted U-shaped relationship. The findings hold after robustness testing. Additionally, external resource acquisition and knowledge absorption abilities play an important role in the influence of digital transformation on the two sustainability innovation types. Further analysis reveals the differential moderating effects of the nature of firm ownership and regional resource differences between the east and the west on the above relationships. State-owned enterprises (SOEs), depending on policy support and resource scale advantages, are more strongly facilitated by digital transformation for exploitative sustainable innovation, while non-SOEs are more effective in driving exploratory sustainable innovation through flexible knowledge absorption mechanisms. The marginal effect of digital transformation on sustainable innovation tends to be significantly better in eastern than in western regions owing to the advanced degree of marketization and improved digital infrastructures.

Global riverine nitrous oxide (N 2 O) emissions have increased more than 4-fold in the last century. It has been estimated that the hyporheic zones in small streams alone may contribute approximately 85% of these N 2 O emissions. However, the mechanisms and pathways controlling hyporheic N 2 O production in stream ecosystems remain unknown. Here, we report that ammonia-derived pathways, rather than the nitrate-derived pathways, are the dominant hyporheic N 2 O sources (69.6 ± 2.1%) in agricultural streams around the world. The N 2 O fluxes are mainly in positive correlation with ammonia. The potential N 2 O metabolic pathways of metagenome-assembled genomes (MAGs) provides evidence that nitrifying bacteria contain greater abundances of N 2 O production-related genes than denitrifying bacteria. Taken together, this study highlights the importance of mitigating agriculturally derived ammonium in low-order agricultural streams in controlling N 2 O emissions. Global models of riverine ecosystems need to better represent ammonia-derived pathways for accurately estimating and predicting riverine N 2 O emissions. NH 4 + -derived pathways, rather than NO 3 - -derived pathway, are the dominant hyporheic N 2 O sources in lower-order streams. These findings provide insights into better estimation of N 2 O emissions in global models of riverine ecosystems and emphasize the importance of managing ammonium.

The fulfillment of corporate social responsibility remains crucial for companies to maintain competitiveness in today’s rapidly developing digital landscape. A truly robust corporate social responsibility strategy involves avoiding “doing bad” and actively engaging in “doing good.” This study uses data from 692 A-share listed companies from 2013 to 2021 to analyze the relationship between top management team (TMT) functional experience, executive incentives, and corporate social responsibility behavior. The research suggests that such heterogeneity enhances responsible behaviors and reduces irresponsible behaviors of firms, and functional experience centrality enhances responsible behaviors but does not reduce irresponsible behaviors. By adopting a stakeholder and behavioral segmentation method into the firm’s corporate social responsibility, it was observed that TMT functional experience heterogeneity enhances responsible behaviors of internal stakeholders while reducing irresponsible behaviors of external stakeholders, whereas TMT functional experience centrality primarily enhances responsible behaviors of internal stakeholders. When compensation incentives exceed a certain threshold to align with the expectations of TMT, members can leverage their experience to enhance responsible corporate behavior and reduce irresponsible behaviors. However, equity incentives must be controlled within certain thresholds to effectively harness the heterogeneous functional experience of TMTs and address irresponsible corporate behavior.

Objective To investigate the impact of peritoneal lavage on the incidence of intra-abdominal abscess (IAA) after laparoscopic appendectomy (LA) in adults with perforated appendicitis. Methods Clinical data from adult patients intraoperatively diagnosed with perforated appendicitis and undergoing LA at the Affiliated Hospital of Qingdao University between January 2020 and January 2025 were retrospectively analyzed. Patients were divided into a no-peritoneal lavage group and a peritoneal lavage group based on whether peritoneal lavage was performed. A total of 128 patients were included, comprising 91 in the no-peritoneal lavage group and 37 in the peritoneal lavage group. Patient demographics were collected, and propensity score matching (PSM) was employed to compare clinical data between groups. Results After PSM, patient demographics showed no significant differences, indicating good balance ( P  > 0.05). There were no statistically significant differences between the two groups regarding operative time, postoperative antibiotic duration, postoperative length of stay(LOS), or postoperative IAA incidence ( P  > 0.05). Conclusion Our findings indicate that compared to suction alone, peritoneal lavage did not reduce the incidence of postoperative IAA in adults undergoing LA for acute perforated appendicitis. There is no evidence that patients benefit from lavage. Prospective multicenter randomized controlled trials are warranted.

To determine the prevalence of hepatitis B surface antigen (HBsAg), hepatitis B surface antibody (anti-HBs), and hepatitis B core anti-body (anti-HBc) in a representative population in China 14 years after introduction of hepatitis B vaccination of infants. National serosurvey, with participants selected by multi-stage random sampling. Demographics and hepatitis B vaccination history collected by questionnaire and review of vaccination records, and serum tested for HBsAg, antibody to anti-HBc and anti-HBs by ELISA. The weighted prevalences of HBsAg, anti-HBs and anti-HBc for Chinese population aged 1–59 years were 7.2%, 50.1%, 34.1%, respectively. HBsAg prevalence was greatly diminished among those age <15 years compared to that found in the 1992 national serosurvey, and among children age <5 years was only 1.0% (90% reduction). Reduced HBsAg prevalence was strongly associated with vaccination among all age groups. HBsAg risk in adults was associated with male sex, Western region, and certain ethnic groups and occupations while risk in children included birth at home or smaller hospitals, older age, and certain ethnic groups (Zhuang and other). China has already reached the national goal of reducing HBsAg prevalence to less than 1% among children under 5 years and has prevented an estimated 16–20 million HBV carriers through hepatitis B vaccination of infants. Immunization program should be further strengthened to reach those remaining at highest risk.

A new KNN-based lead-free luminescent ceramics, (1- x )(K 0.48 Na 0.52 )Nb 0.96 Sb 0.04 - x (Bi 0.45 Sm 0.05 Na 0.5 )ZrO 3 (KNNS- x BSNZ, 0 ≤ x ≤ 0.05), was designed to further improve the properties, such as piezoelectricity, dielectricity, ferroelectricity, and fluorescence properties. It was found that the R–T phase boundary could be constructed when the ceramics with x = 0.03~0.04, and the two-phase coexistence endowed them with relatively superior properties ( d 33 = 260 pC/N, ε r  = 2185, T C = 250 o C, P r = 21 µC/cm 2 , E c = 15 kV/cm). Meanwhile, the KNNS- x BSNZ ceramics show good photoluminescence characteristics at room temperature, which can achieve the combination of the piezoelectric and luminescent properties. Hence, we believe that this work has important reference value for the popularization of the optoelectronic components and multifunctional applications.

Hydrothermal geothermal energy, as a widely distributed, large reserve and easily exploitable renewable source, can be used for both power generation and building heating. In this study, a numerical simulation of heat extraction performance is conducted based on monitoring well temperature data in a geothermal field in Xiong’an New Area. The effects of the reinjection temperature, injection flow rate, and reinjection rate on the outlet temperature and the reservoir temperature during a long-term operation are analyzed. The results indicate that the lower reinjection temperature can generate a critical disturbance scope for the thermal reservoir during the exploitation process. The impact scope on the thermal reservoir can reach 210.3 m at a reinjection temperature of 25 °C, which is not conducive to maintaining the outlet temperature of production wells in the long-term. The reinjection rate significantly affects both the horizontal and vertical temperature fields of the thermal reservoir. Under reinjection conditions of 30 °C and 40 kg/s, the horizontal and vertical impact scope of the thermal reservoir are 262.3 and 588.5 m, respectively. The reinjection rate is inversely related to the outlet temperature. A decrease from 100% to 70% in the reinjection rate can increase the outlet temperature by 4.21%. However, a decrease in the reinjection rate will lead to a decline in the groundwater level. Therefore, balancing the variation in outlet temperature and groundwater level is crucial in practical engineering.

Contrast-enhanced computed tomography scans (CECT) are routinely used in the evaluation of different clinical scenarios, including the detection and characterization of hepatocellular carcinoma (HCC). Quantitative medical image analysis has been an exponentially growing scientific field. A number of studies reported on the effects of variations in the contrast enhancement phase on the reproducibility of quantitative imaging features extracted from CT scans. The identification and labeling of phase enhancement is a time-consuming task, with a current need for an accurate automated labeling algorithm to identify the enhancement phase of CT scans. In this study, we investigated the ability of machine learning algorithms to label the phases in a dataset of 59 HCC patients scanned with a dynamic contrast-enhanced CT protocol. The ground truth labels were provided by expert radiologists. Regions of interest were defined within the aorta, the portal vein, and the liver. Mean density values were extracted from those regions of interest and used for machine learning modeling. Models were evaluated using accuracy, the area under the curve (AUC), and Matthew’s correlation coefficient (MCC). We tested the algorithms on an external dataset (76 patients). Our results indicate that several supervised learning algorithms (logistic regression, random forest, etc.) performed similarly, and our developed algorithms can accurately classify the phase of contrast enhancement.