We present an experimental study of proton acceleration driven by femtosecond multi-PW lasers of three different prepulse parameters with the peak laser intensity of 1.2 × 1021 W/cm2 irradiating micrometre-thick metal foils. For 4-μm-thick copper foils, the highest-energy proton beam of 58.9 MeV is generated with the moderate-contrast laser, while the low-contrast or high-contrast lasers result in the lower proton cutoff energies. The one-dimensional hydrodynamic and two-dimensional particle-in-cell simulations indicate that the front preplasma of foils induced by the laser prepulse can enhance electron acceleration and in turn improve proton acceleration, while the rear preplasma will weaken the sheath field and be unfavourable for accelerating ions. For the case of the moderate contrast, the scale length of the front preplasma is long enough to generate high-temperature electrons compared to the high-contrast case, and the scale length of the rear preplasma is so short that the sheath field still remains strong compared with the low-contrast case, which is advantageous for generating high-energy protons. Meanwhile, a concrete map is theoretically given for accelerating higher-energy protons. This work extends the concept of the prepulse effect on target normal sheath acceleration (TNSA) to a wider range of laser parameters (multi-PW, 1021 W/cm2), representing an important step towards potential applications of TNSA-driven proton sources, especially considering that PW and even 10 PW laser facilities exist all around the world.

To determine values for the digestible indispensable amino acid score (DIAAS), it is recommended that ileal amino acid (AA) digestibility values obtained in growing pigs are used to characterise protein quality in different foods. Therefore, an experiment was conducted to determine the standardised ileal digestibility (SID) of AA in eight energy ingredients (barley, sorghum, wheat, brown rice, rice bran, wheat bran, cassava and paddy rice) fed to pigs, where SID values in pigs can be used to calculate approximate DIAAS values in humans. Among the data obtained for all energy ingredients, significant variations (P < 0·01) in CP and AA composition were observed. Rice bran and wheat bran had the highest CP (16·43 % and 18·16 %, respectively) and DIAAS scores of 81–88 for adult, qualifying as ‘good’ protein sources (> 75). Cassava, with the lowest CP (2·74 %), was limited by sulphur amino acid (54). Lysine (Lys) was the first-limiting AA in barley (74), sorghum (51) and wheat (49), with SID values lowest in wheat (71·04 %). Brown rice and paddy rice showed higher SIDLys (87·51 % and 78·13 %, respectively). These findings highlight the potential of bran-based ingredients and Lys fortification to improve protein quality in grain-dependent diets, providing the scientific basis to combat protein malnutrition.

Recently, increasing numbers of nonprofit studies have used experiments to understand individuals’ charitable giving decisions. One significant gap between experimental settings and the real world is the way in which individuals earn the incomes that they use for charitable donations. This study examined the relationship between individuals’ income sources and their charitable giving decisions. To do so, we conducted a laboratory experiment with 188 college students and asked them to donate with windfall money or with money earned from a real task, respectively. The findings showed that participants donated more to charities if their funds derived from windfall gains. Implications for conducting experiments and motivating donors are also discussed.

While existing literature has conceptualized the multiple, complex ways in which NGOs might relate to the state, it has paid limited attention to how NGO–government collaboration leads to NGO policy influence. This study examines small, indigenous grassroots NGOs and their interactions with the local state in China. Using a grounded theory approach, we find that the aspiration for both NGOs and the local state is to establish reciprocal engagement, which consists of three dimensions—proximity and communication, mutual support, and joint action. We explain how reciprocal engagement might lead to NGO policy influence: (a) shaping government departments’ internal work methods, (b) facilitating policy implementation, and (c) influencing policy revision. We further define the boundary conditions for the reciprocal engagement and policy influence framework by examining how regions, administrative agencies, and evolving political climate affect the engagement–influence relationship. Our study provides a more nuanced understanding of the dynamics of NGO–government relations in China and of non-contentious methods of policy influence from the grassroots.

To advance the understanding of how e-government resources drive e-participation, the current research conducts a meta-analysis on the relationship above from the perspective of citizen experience. This meta-analysis synthesizes 517 effect sizes from 126 empirical studies to examine how e-government resources influence citizens’ e-participation intention. The findings highlight several key variables that moderate this effect. Specifically: (1) From the perspective of the experience channel, e-government resources are more effective in facilitating citizen e-participation intention when delivered through social (vs. official) channels. (2) From the perspective of the experience affair, e-government resources exert a stronger impact on citizen e-participation intention when targeting specific (vs. general) public affairs and when focusing on regional (vs. national) government affairs. (3) From the perspective of the experience environment, the effect of e-government resources on e-participation intention is stronger in developing (vs. developed) countries. Based on these findings, this study offers implications for governments and researchers and suggests directions for future research.

African swine fever (ASF) is a highly contagious animal disease caused by African swine fever virus (ASFV). It is listed by the World Organization for Animal Health (WOAH) as an animal disease subject to statutory reporting. ASFV, a large, enveloped double-stranded DNA virus with high genomic complexity, exhibits a case fatality rate of up to 100%, posing a significant threat to the global pig industry and food safety. To date, the absence of a safe commercial ASFV vaccine primarily stems from challenges in identifying immunogenic viral antigens, insufficient characterization of ASFV pathogenesis, and limited understanding of the virus’s immune evasion mechanisms. Here, we review the pathogenic characteristics (morphological structure, clinical symptoms, and epidemiological characteristics), molecular biological characteristics, and infection mechanism of ASFV, as well as the immune response mechanism, vaccine research, and the latest information on ASFV in other areas. This review will be in favour of understanding the current state of knowledge of ASF and developing effective vaccines to control this disease.

Fully resolving turbulent flows remains challenging due to a turbulent systems’ multiscale complexity. Existing data-driven approaches typically demand expensive retraining for each flow scenario and struggle to generalize beyond their training conditions. Leveraging the universality of small-scale turbulent motions (Kolmogorov’s K41 theory), we propose a scale-oriented zonal generative adversarial network (SoZoGAN) framework for high-fidelity, zero-shot turbulence generation across diverse domains. Unlike conventional methods, SoZoGAN is trained exclusively on a single dataset of moderate-Reynolds-number homogeneous isotropic turbulence (HIT). The framework employs a zonal decomposition strategy, partitioning turbulent snapshots into subdomains based on scale-sensitive physical quantities. Within each subdomain, turbulence is synthesized using scale-indexed models pretrained solely on the HIT database. A SoZoGAN demonstrates high accuracy, cross-domain generalizability and robustness in zero-shot super-resolution of unsteady flows, as validated on untrained HIT, turbulent boundary layer and channel flow. Its strong generalization, demonstrated for homogeneous and inhomogeneous turbulence cases, suggests potential applicability to a wider range of industrial and natural turbulent flows. The scale-oriented zonal framework is architecture-agnostic, readily extending beyond generative adversarial networks to other deep learning models.

This study reports potassium (K) isotope compositions of diamondiferous kimberlites. Altered kimberlite samples exhibit δ41K values ranging from −1.293 ± 0.052 (2SD) to −0.114 ± 0.029 ‰, showing covariations with chemical indicators of alteration. This is consistent with the geochemical dynamics of K isotopes in hydrothermal fluid-related processes. In contrast, pristine kimberlite samples display restricted K isotope compositions, with δ41K values between −0.494 ± 0.057 and −0.270 ± 0.048 ‰. Notably, the δ41K values of these pristine kimberlite samples correlate well with K2O and Rb contents, suggesting that approximately ∼0.2 ‰ of K isotope fractionation is induced by phlogopite crystallization, as indicated by quantitative modelling. The estimated δ41K values of −0.458 ‰ for the primary kimberlite melt and of −0.414 ‰ for the kimberlite source imply a potential link to the bulk silicate Earth. These new measurements, along with literature data from various rocks, indicate that the K isotope composition in the deep mantle (>150 km) is more homogenous than in shallow regions, likely reflecting the efficiency of convection flow and K behaviour during subduction. In addition, the K isotope data reveal temporal variations in mantle-derived magmas from the Palaeozoic to the Cenozoic, highlighting the geological history and lithospheric destruction of the North China Craton. This study underscores the significance of K isotopes in enhancing our understanding of mantle dynamics, crustal recycling and the geochemical evolution of the Earth’s interior.

Human–machine compatibility and collaborative control for stroke patients utilizing lower limb rehabilitation robots have attracted considerable research attention. As a highly human–machine-coupled system, ensuring adequate compliance and safety is fundamental to efficient and comfortable rehabilitation. Therefore, this paper first quantifies human–machine contact interactions, proposes a human–machine coupling dynamics modeling method, and identifies the robot’s dynamic inertia parameters and human lower limb parameters. Second, a dual closed-loop controller for the rehabilitation robot is designed. Based on the bottom position control, an adaptive admittance control algorithm is proposed that employs the root-mean-square propagation (RMSprop) algorithm to tune the adaptive gain. In rehabilitation training, the controller can adaptively adjust the admittance parameters according to the human–machine interaction force to achieve responsiveness to the dynamic changes of the human–machine system. The experimental results of the control system show that the human–machine cooperative control performance is significantly improved, the maximum joint angle error is reduced by more than 40.9%, and the maximum human–machine interaction force is reduced by more than 19.4%.

Objectives: Data on primary care antibiotic prescription practices for children in Southeast Asia, which are essential for policy, quality improvement and patient safety, are lacking. We aimed to describe this gap and to benchmark prescription practices against international standards. Methods: Antibiotic prescriptions for children (age <18 years) who visited six public primary care clinics in Singapore between 2018 and 2021 were extracted and categorized according to the World Health Organization Access, Watch, Reserve (WHO AWaRe) classification. Quality indicators from the European Surveillance of Antimicrobial Consumption Network (ESAC- Net) and National Institute for Health and Care Excellence (NICE) guidelines were used as a measure of appropriateness of antibiotic prescribing. Descriptive statistics and T-test was used to compare prescription rates pre- and post-COVID-19 pandemic. Results: 19,325 and 20,692 oral and topical antibiotics were prescribed for 831,669 visits, with a prescription rate of 2.3% and 2.5% respectively. Mean antibiotic prescriptions fell significantly post-pandemic (2020–2021), compared to pre-pandemic numbers (1062.8 to 604.5 prescriptions per month) (p <0.001). The majority (95.8%) of prescriptions belonged to the Access group. Watch group antibiotics constituted 6.1% of the total antibiotics prescribed for respiratory conditions (n = 562). While prescriptions were low (4.1%) and well within EASC-Net quality indicator limits of 0-20% for respiratory infections, prescriptions for otitis media were significantly high (56.6%). Approximately 1 in 2 children received antibiotics as recommended by NICE guidelines for both respiratory infections (n=4,622, 51.5%) and otitis media (n=204, 51.8%). Conclusions: Primary care antibiotic prescriptions for children in Singapore decreased post- COVID-19. However, high rates of otitis media prescriptions and only 50% appropriateness for respiratory infections and otitis media emphasize the need for targeted improvements in these areas.

Contact tracing is an effective public health policy to put the fast-spreading epidemic under control. The government tracks the contacts of confirmed SARS-CoV-2 cases, recommends testing, encourages self-quarantine, and monitors symptoms of contacts. In developing and less-developed countries with limited resources for widespread SARS-CoV-2 testing, it remains essential to identify and quarantine positive contacts to control outbreaks. Therefore, analysing recall and precision when implementing testing policies for these contacts is necessary. We analysed a contact tracing dataset from a cohort of 827 index patients infected with SARS-CoV-2 and their 14814 close contacts from Jan 2020 to July 2020 in a province in eastern China. We constructed a network from the data and used a Graph Convolutional Network to predict each contact’s infection status. To the best of our knowledge, this is the first method to use population-based contact tracing data for predicting the infection status using graph neural networks. Despite limited information, our model achieves competitive Area Under the Receiver Operating Characteristic Curve (ROC AUC) compared to hospital-onset scenarios. Based on the risk scores, we propose several contact testing policy adaptations that balance resource efficiency and effective pandemic control.

Determining whether cryptic remnant animal populations survive within specific landscapes is a conservation challenge and may require multiple types of information. Hainan Island, China, has lost most of its large mammal fauna, with no recent evidence for persistence of large carnivores. We conducted a survey of local ecological knowledge in communities around seven protected areas in 2015, collecting sighting reports of the Asiatic black bear Ursus thibetanus. Respondents living near Wuzhishan National Nature Reserve reported the highest number of dated sightings as well as the most recent sightings. In follow-up interviews, wildlife rangers at Wuzhishan reported recent signs of bears and local hunting, and a possible bear photograph was taken inside the Reserve in 2017. Characteristic bear signs, including fresh diagnostic claw marks on trees, were detected at Wuzhishan in 2021, confirming bear presence. Wuzhishan is the last area in Hainan where large herbivores and carnivores survive, and where local conservation efforts still have the potential to maintain functional forest ecosystems that support megafaunal assemblages.