Predicting epidemic trends of coronavirus disease 2019 (COVID-19) remains a key public health concern globally today. However, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection rate in previous studies of the transmission dynamics model was mostly a fixed value. Therefore, we proposed a meta-Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) model by adding a time-varying SARS-CoV-2 reinfection rate to the transmission dynamics model to more accurately characterize the changes in the number of infected persons. The time-varying reinfection rate was estimated using random-effect multivariate meta-regression based on published literature reports of SARS-CoV-2 reinfection rates. The meta-SEIRS model was constructed to predict the epidemic trend of COVID-19 from February to December 2023 in Sichuan province. Finally, according to the online questionnaire survey, the SARS-CoV-2 infection rate at the end of December 2022 in Sichuan province was 82.45%. The time-varying effective reproduction number in Sichuan province had two peaks from July to December 2022, with a maximum peak value of about 15. The prediction results based on the meta-SEIRS model showed that the highest peak of the second wave of COVID-19 in Sichuan province would be in late May 2023. The number of new infections per day at the peak would be up to 2.6 million. We constructed a meta-SEIRS model to predict the epidemic trend of COVID-19 in Sichuan province, which was consistent with the trend of SARS-CoV-2 positivity in China. Therefore, a meta-SEIRS model parameterized based on evidence-based data can be more relevant to the actual situation and thus more accurately predict future trends in the number of infections.

We reported on an efficient high-power continuous-wave laser operation on the 3H4 → 3H5 transition of Tm3+ ions in a diffusion-bonded composite YVO4/Tm:GdVO4 crystal. Pumped by a laser diode at 794 nm, a maximum output power of 7.5 W was obtained from a YVO4/Tm:GdVO4 laser at 2.29 μm, corresponding to a slope efficiency of 40.3% and exceeding the Stokes limit. To the best of our knowledge, this result represents the maximum power ever achieved from a Tm laser at 2.3 μm.

Fast radio bursts (FRBs) are millisecond-duration radio waves from the Universe. Even though more than 50 physical models have been proposed, the origin and physical mechanism of FRB emissions are still unknown. The classification of FRBs is one of the primary approaches to understanding their mechanisms, but previous studies classified conventionally using only a few observational parameters, such as fluence and duration, which might be incomplete. To overcome this problem, we use an unsupervised machine-learning model, the Uniform Manifold Approximation and Projection to handle seven parameters simultaneously, including amplitude, linear temporal drift, time duration, central frequency, bandwidth, scaled energy, and fluence. We test the method for homogeneous 977 sub-bursts of FRB 20121102A detected by the Arecibo telescope. Our machine-learning analysis identified five distinct clusters, suggesting the possible existence of multiple different physical mechanisms responsible for the observed FRBs from the FRB 20121102A source. The geometry of the emission region and the propagation effect of FRB signals could also make such distinct clusters. This research will be a benchmark for future FRB classifications when dedicated radio telescopes such as the square kilometer array or Bustling Universe Radio Survey Telescope in Taiwan discover more FRBs than before.

Human alveolar echinococcosis is a hard-to-treat and largely untreated parasitic disease with high associated health care costs. The current antiparasitic treatment for alveolar echinococcosis relies exclusively on albendazole, which does not act parasiticidally and can induce severe adverse effects. Alternative, and most importantly, improved treatment options are urgently required. A drug repurposing strategy identified the approved antimalarial pyronaridine as a promising candidate against Echinococcus multilocularis infections. Following a 30-day oral regimen (80 mg kg−1 day−1), pyronaridine achieved an excellent therapeutic outcome in a clinically relevant hepatic alveolar echinococcosis murine model, showing a significant reduction in both metacestode size (72.0%) and counts (85.2%) compared to unmedicated infected mice, which revealed significantly more potent anti-echinococcal potency than albendazole treatment at an equal dose (metacestode size: 42.3%; counts: 4.1%). The strong parasiticidal activity of pyronaridine was further confirmed by the destructive damage to metacestode tissues observed morphologically. In addition, a screening campaign combined with computational similarity searching against an approved drug library led to the identification of pirenzepine, a gastric acid-inhibiting drug, exhibiting potent parasiticidal activity against protoscoleces and in vitro cultured small cysts, which warranted further in vivo investigation as a promising anti-echinococcal lead compound. Pyronaridine has a known drug profile and a long track record of safety, and its repurposing could translate rapidly to clinical use for human patients with alveolar echinococcosis as an alternative or salvage treatment.

To investigate the associations between dietary patterns and biological aging, identify the most recommended dietary pattern for coping with biological aging and explore the potential mediating role of gut microbiota in less-developed ethnic minority regions (LEMRs). This prospective cohort study included 8288 participants aged 30-79 years from the China Multi-Ethnic Cohort study (CMEC). Anthropometric measurements and clinical biomarkers were utilized to construct biological age based on Klemera and Doubal’s method (KDM-BA) and KDM-BA acceleration (KDM-AA). Dietary information was obtained through the baseline food frequency questionnaire (FFQ). Six dietary patterns were constructed: plant-based diet index (PDI), healthful plant-based diet index (hPDI), unhealthful plant-based diet index (uPDI), healthy diet score (HDS), Dietary Approaches to Stop Hypertension (DASH), and alternative Mediterranean diets (aMED). Follow-up adjusted for baseline analysis were employed to assess the associations between dietary patterns and KDM-AA. Additionally, quantile G-computation was utilized to evaluate the significant beneficial and harmful food groups. In the subsample of 764 participants with gut microbiota data obtained through 16S rRNA gene sequencing, we used causal mediation model to explore the mediating role of gut microbiota in the associations between dietary patterns and KDM-AA. The results showed that all dietary patterns were associated with KDM-AA. Transitioning from non-compliance to compliance, DASH exhibited the strongest negative association with KDM-AA [β = -0.91, 95%CI (-1.19, -0.63)]. The component analyses revealed that tea and soybean products were the significant beneficial food groups, while salt, preserved vegetables, red and processed meats were identified as the major harmful food groups. In mediation analysis, the decreased abundance of Synergistetes phylum and Pyramidobacter genus possibly mediated the negative associations between plant-based diets and KDM-AA (5.61%-9.19%). Overall, healthy dietary patterns, especially DASH, are negatively associated with biological aging in LEMRs. The Synergistetes and Pyramidobacter may mediate the associations between plant-based diets and biological aging. Developing appropriate strategies may promote healthy aging in LEMRs.

As a required sample preparation method for 14C graphite, the Zn-Fe reduction method has been widely used in various laboratories. However, there is still insufficient research to improve the efficiency of graphite synthesis, reduce modern carbon contamination, and test other condition methodologies at Guangxi Normal University (GXNU). In this work, the experimental parameters, such as the reduction temperature, reaction time, reagent dose, Fe powder pretreatment, and other factors, in the Zn-Fe flame sealing reduction method for 14C graphite samples were explored and determined. The background induced by the sample preparation process was (2.06 ± 0.55) × 10–15, while the 12C– beam current were better than 40μA. The results provide essential instructions for preparing 14C graphite of ∼1 mg at the GXNU lab and technical support for the development of 14C dating and tracing, contributing to biology and environmental science.

A new vacuum line to extract CO2 from carbonate and dissolved inorganic carbon (DIC) in water was established at Guangxi Normal University. The vacuum line consisted of two main components: a CO2 bubble circulation region and a CO2 purification collection region, both of which were made of quartz glass and metal pipelines. To validate its reliability, a series of carbonate samples were prepared using this system. The total recovery rate of CO2 extraction and graphitization exceeded 80%. Furthermore, the carbon content in calcium carbonate exhibited a linear relationship with the CO2 pressure within the system, demonstrating its stability and reliability. The system was also employed to prepare and analyze various samples, including calcium carbonate blanks, foraminiferal, shell, groundwater, and subsurface oil-water samples. The accelerator mass spectrometry (AMS) results indicated that the average beam current for 12C- in the samples exceeded 40 μA. Additionally, the contamination introduced during the liquid sample preparation process was approximately (1.77 ± 0.57) × 10−14. Overall, the graphitized preparation system for carbonate and DIC in water exhibited high efficiency and recovery, meeting the requirements for samples dating back to approximately 30,000 years.

This study proposes a novel super-resolution (or SR) framework for generating high-resolution turbulent boundary layer (TBL) flow from low-resolution inputs. The framework combines a super-resolution generative adversarial neural network (SRGAN) with down-sampling modules (DMs), integrating the residual of the continuity equation into the loss function. The DMs selectively filter out components with excessive energy dissipation in low-resolution fields prior to the super-resolution process. The framework iteratively applies the SRGAN and DM procedure to fully capture the energy cascade of multi-scale flow structures, collectively termed the SRGAN-based energy cascade reconstruction framework (EC-SRGAN). Despite being trained solely on turbulent channel flow data (via ‘zero-shot transfer’), EC-SRGAN exhibits remarkable generalization in predicting TBL small-scale velocity fields, accurately reproducing wavenumber spectra compared to direct numerical simulation (DNS) results. Furthermore, a super-resolution core is trained at a specific super-resolution ratio. By leveraging this pretrained super-resolution core, EC-SRGAN efficiently reconstructs TBL fields at multiple super-resolution ratios from various levels of low-resolution inputs, showcasing strong flexibility. By learning turbulent scale invariance, EC-SRGAN demonstrates robustness across different TBL datasets. These results underscore the potential of EC-SRGAN for generating and predicting wall turbulence with high flexibility, offering promising applications in addressing diverse TBL-related challenges.

The potential threshold for dietary energy intake (DEI) that might prevent protein-energy wasting (PEW) in chronic kidney disease (CKD) is uncertain. The subjects were non-dialysis CKD patients aged ≥ 14 years who were hospitalised from September 2019 to July 2022. PEW was measured by subjective global assessment. DEI and dietary protein intake (DPI) were obtained by 3-d diet recalls. Patients were divided into adequate DEI group and inadequate DEI group according to DEI ≥ 30 or < 30 kcal/kg/d. Logistic regression analysis and restricted cubic spline were used in this study. We enrolled 409 patients, with 53·8 % had hypertension and 18·6 % had diabetes. The DEI and DPI were 27·63 (sd 5·79) kcal/kg/d and 1·00 (0·90, 1·20) g/kg/d, respectively. 69·2 % of participants are in the inadequate DEI group. Malnutrition occurred in 18·6 % of patients. Comparing with patients in the adequate DEI group, those in the inadequate DEI group had significantly lower total lymphocyte count, serum cholesterol and LDL-cholesterol and a higher prevalence of PEW. For every 1 kcal/kg/d increase in DEI, the incidence of PEW was reduced by 12·0 % (OR: 0·880, 95 % CI: 0·830, 0·933, P < 0·001). There was a nonlinear curve relationship between DEI and PEW (overall P < 0·001), and DEI ≥ 27·6 kcal/kg/d may have a preventive effect on PEW in CKD. Low DPI was also significantly associated with malnutrition, but not when DEI was adequate. Decreased energy intake may be a more important factor of PEW in CKD than protein intake.

Dengue fever is a viral disease caused by one of four dengue stereotypes (Flavivirus: Flaviviridae) that are primarily transmitted by Aedes albopictus (Skuse) and Aedes aegypti (L.). To safeguard public health, it is crucial to conduct surveys that examine the factors favouring the presence of these species. Our study surveyed 42 councils across four towns within the Bhakkar district of Punjab Province, by inspecting man-made or natural habitats containing standing water. First, door-to-door surveillance teams from the district health department were assigned to each council to surveillance Aedes species and dengue cases. Second, data collection through surveillance efforts, and validation procedures were implemented, and the verified data was uploaded onto the Dengue Tracking System by Third Party Validation teams. Third, data were analysed to identify factors influencing dengue fever cases. The findings demonstrated the following: (1) Predominantly, instances were discerned among individuals who had a documented history of having travelled beyond the confines of the province. (2) Containers associated with evaporative air coolers and tyre shops were responsible for approximately 30% of the Aedes developmental sites. (4) Variability in temperature was responsible for approximately 45% of the observed differences in the quantity of recorded Aedes mosquito developmental sites. (5) Implementation of dengue prevention initiatives precipitated a 50% reduction in Aedes-positive containers, alongside a notable 70% decline in reported cases of dengue fever during the period spanning 2019 to 2020, while the majority of reported cases were of external origin. Aedes control measures substantially curtailed mosquito populations and lowered vector-virus interactions. Notably, local dengue transmission was eliminated through advanced and effective Aedes control efforts, emphasising the need for persistent surveillance and eradication of larval habitats in affected regions.

The absorption and distribution of radiocarbon-labeled urea at the ultratrace level were investigated with a 14C-AMS biotracer method. The radiopharmaceutical concentrations in the plasma, heart, liver, spleen, lung, kidney, stomach, brain, bladder, muscle, testis, and fat of rats after oral administration of 14C urea at ultratrace doses were determined by AMS, and the concentration-time curves in plasma and tissues and pharmacokinetic distribution data were obtained. This study provides an analytical method for the pharmacokinetic parameters and tissue distribution of exogenous urea in rats at ultratrace doses and explores the feasibility of evaluation and long-term tracking of ultratrace doses of drugs with AMS.

This paper explores the use of inkjet-printing technology for transparent transmitarrays, presenting a viable alternative to traditional copper microwire counterparts. The study focuses on achieving high-gain performance crucial for wireless communication systems, with a particular emphasis on the fifth-generation (5G) millimeter-wave communication. Transparent transmitarrays leverage transparent conducting films and conductive mesh structures, overcoming opacity limitations and seamlessly integrating with urban architecture. In this paper, the inkjet-printing process is detailed for fabricating transmitarray apertures, highlighting the flexibility and precision in depositing nanosilver particles onto a glass substrate. The design intricacies involve optimizing feeding characteristics, determining unit cell structures, and constructing transmitarrays of various sizes. To validate the proposed technique, three different apertures (15 × 15, 20 × 20, and 25 × 25 unit cells) are constructed. The antenna performances are evaluated in terms of reflection coefficients, radiation efficiency, realized gain, and patterns, demonstrating the effectiveness of inkjet-printed transmitarrays. Comparative analysis with copper microwire counterparts is also conducted, validating the inkjet-printing technology for similar gain performance with added advantages of flexibility, compatibility with transparent substrates, and cost-effective manufacturing.

Gut microbiome changed dramatically during pregnancy and played important roles in metabolic status and reproductive endocrinology in mammals. However, investigating the functional microbiota and metabolites to improve the reproductive performance and understanding the host–microbiota interaction are still arduous tasks. This study aims to reveal the dominant strains and metabolites that improve the reproductive performance. We analyzed the fecal microbiota composition and metabolic status of higher yield Chinese pig breed Meishan (MS) sows and lower yield but widespread raised hybrid pig breed Landrace × Yorkshire (L × Y) sows on days 28 and 100 of gestation. Results showed that MS sows had higher litter sizes and steroid hormone level but lower short-chain fatty acid level in feces. Fecal metabolomic analysis revealed that MS sows showed a different metabolic status compared with L × Y sows both at early and late pregnancy, which enriched with phenylpropanoid biosynthesis, bile secretion, steroid hormone biosynthesis, and plant secondary metabolite biosynthesis. In addition, 16S rDNA and internal transcribed spacer sequencing indicated that MS sows showed different structures of microbiota community and exhibited an increased bacterial α-diversity but non-differential fungal α-diversity than L × Y sows. Moreover, we found that the litter sizes and bacteria including Sphaerochaeta, Solibacillus, Oscillospira, Escherichia–Shigella, Prevotellaceae_UCG-001, dgA-11_gut_group, and Bacteroides, as well as fungi including Penicillium, Fusarium, Microascus, Elutherascus, and Heydenia both have positive association to the significant metabolites at the early pregnancy. Our findings revealed significant correlation between reproductive performance and gut microbiome and provided microbial and metabolic perspective to improve litter sizes and steroid hormones of sows.

China faces challenges in meeting the World Health Organization (WHO)’s target of reducing hepatitis B virus (HBV) infections by 95% using 2015 as the baseline. Using Global Burden of Disease (GBD) 2019 data, joinpoint regression models were used to analyse the temporal trends in the crude incidence rates (CIRs) and age-standardized incidence rates (ASIRs) of acute HBV (AHBV) infections in China from 1990 to 2019. The age–period–cohort model was used to estimate the effects of age, period, and birth cohort on AHBV infection risk, while the Bayesian age–period–cohort (BAPC) model was applied to predict the annual number and ASIRs of AHBV infections in China through 2030. The joinpoint regression model revealed that CIRs and ASIRs decreased from 1990 to 2019, with a faster decline occurring among males and females younger than 20 years. According to the age–period–cohort model, age effects showed a steep increase followed by a gradual decline, whereas period effects showed a linear decline, and cohort effects showed a gradual rise followed by a rapid decline. The number of cases of AHBV infections in China was predicted to decline until 2030, but it is unlikely to meet the WHO’s target. These findings provide scientific support and guidance for hepatitis B prevention and control.

We construct an autoregressive moving average (ARMA) model consisting of the history and random effects for the streamwise velocity fluctuation in boundary-layer turbulence. The distance to the wall and the boundary-layer thickness determine the time step and the order of the ARMA model, respectively. Based on the autocorrelation's analytical expression of the ARMA model, we obtain a global analytical expression for the second-order structure function, which asymptotically captures the inertial, dynamic and large-scale ranges. Specifically, the exponential autocorrelation of the ARMA model arises from the autoregressive coefficients and is modified to logarithmic behaviour by the moving-average coefficients. The asymptotic expressions enable us to determine model coefficients by existing parameters, such as the Kolmogorov and the Townsend–Perry constants. A consequent double-log expression for the characteristic length scale is derived and is justified by direct numerical simulation data with $Re_\tau \approx 5200$ and field-measured neutral atmospheric surface layer data with $Re_\tau \sim O(10^6)$ from the Qingtu Lake Observation Array site. This relation is robust because it applies to $Re_\tau$ from $O(10^4)$ to $O(10^6)$, and even when the statistics of natural ASL deviate from those of canonical boundary-layer turbulence, e.g. in the case of imbalance in energy production and dissipation, and when the Townsend–Perry constant deviates from traditional values.