We present a high-power mid-infrared single-frequency pulsed fiber laser (SFPFL) with a tunable wavelength range from 2712.3 to 2793.2 nm. The single-frequency operation is achieved through a compound cavity design that incorporates a germanium etalon and a diffraction grating, resulting in an exceptionally narrow seed linewidth of approximately 780 kHz. Employing a master oscillator power amplifier configuration, we attain a maximum average output power of 2.6 W at 2789.4 nm, with a pulse repetition rate of 173 kHz, a pulse energy of 15 μJ and a narrow linewidth of approximately 850 kHz. This achievement underscores the potential of the mid-infrared SFPFL system for applications requiring high coherence and high power, such as high-resolution molecular spectroscopy, precision chemical identification and nonlinear frequency conversion.

Double-zero-event studies (DZS) pose a challenge for accurately estimating the overall treatment effect in meta-analysis (MA). Current approaches, such as continuity correction or omission of DZS, are commonly employed, yet these ad hoc methods can yield biased conclusions. Although the standard bivariate generalized linear mixed model (BGLMM) can accommodate DZS, it fails to address the potential systemic differences between DZS and other studies. In this article, we propose a zero-inflated bivariate generalized linear mixed model (ZIBGLMM) to tackle this issue. This two-component finite mixture model includes zero inflation for a subpopulation with negligible or extremely low risk. We develop both frequentist and Bayesian versions of ZIBGLMM and examine its performance in estimating risk ratios against the BGLMM and conventional two-stage MA that excludes DZS. Through extensive simulation studies and real-world MA case studies, we demonstrate that ZIBGLMM outperforms the BGLMM and conventional two-stage MA that excludes DZS in estimating the true effect size with substantially less bias and comparable coverage probability.

Matching-adjusted indirect comparison (MAIC) has been increasingly applied in health technology assessments (HTA). By reweighting subjects from a trial with individual participant data (IPD) to match the summary statistics of covariates in another trial with aggregate data (AgD), MAIC enables a comparison of the interventions for the AgD trial population. However, when there are imbalances in effect modifiers with different magnitudes of modification across treatments, contradictory conclusions may arise if MAIC is performed with the IPD and AgD swapped between trials. This can lead to the “MAIC paradox,” where different entities reach opposing conclusions about which treatment is more effective, despite analyzing the same data. In this paper, we use synthetic data to illustrate this paradox and emphasize the importance of clearly defining the target population in HTA submissions. Additionally, we recommend making de-identified IPD available to HTA agencies, enabling further indirect comparisons that better reflect the overall population represented by both IPD and AgD trials, as well as other relevant target populations for policy decisions. This would help ensure more accurate and consistent assessments of comparative effectiveness.

Network meta-analysis (NMA), also known as mixed treatment comparison meta-analysis or multiple treatments meta-analysis, extends conventional pairwise meta-analysis by simultaneously synthesizing multiple interventions in a single integrated analysis. Despite the growing popularity of NMA within comparative effectiveness research, it comes with potential challenges. For example, within-study correlations among treatment comparisons are rarely reported in the published literature. Yet, these correlations are pivotal for valid statistical inference. As demonstrated in earlier studies, ignoring these correlations can inflate mean squared errors of the resulting point estimates and lead to inaccurate standard error estimates. This article introduces a composite likelihood-based approach that ensures accurate statistical inference without requiring knowledge of the within-study correlations. The proposed method is computationally robust and efficient, with substantially reduced computational time compared to the state-of-the-science methods implemented in R packages. The proposed method was evaluated through extensive simulations and applied to two important applications including an NMA comparing interventions for primary open-angle glaucoma, and another comparing treatments for chronic prostatitis and chronic pelvic pain syndrome.

With the evolution of the Web and development of web-based search engines, online searching has become a common method for obtaining information. Given this popularity, the question arises as to how much time people save by using search engines for their information needs compared to offline sources, as well as how online searching affects both search experiences and search outcomes. Using a random sample of queries from a major search engine and a sample of reference questions from the Internet Public Library (IPL), we conduct a real-effort experiment to compare online and offline search experiences and outcomes. We find that participants are significantly more likely to find an answer on the Web (100 %), compared to offline searching (between 87 % and 90 %). Restricting our analysis to the set of questions in which participants find answers in both treatments, a Web search takes on average 7 (9) minutes, whereas the corresponding offline search takes 22 (19) minutes for a search-engine (IPL) question. Furthermore, while raters judge library sources to be significantly more trustworthy and authoritative than the corresponding Web sources, they judge Web sources as significantly more relevant. Balancing all factors, we find that the overall source quality is not significantly different between the two treatments for the set of search-engine questions. However, for IPL questions, we find that non-Web sources are judged to have significantly higher overall quality than the corresponding Web sources. In comparison, for factual questions, Web search results are significantly more likely to be correct (66 % vs. 43 %). Lastly, post-search questionnaires reveal that participants find online searching more enjoyable than offline searching.

Language control in the bilingual brain has remained in the limelight of research over the past decades. However, the mechanisms underlying bilingual language control may be more intricate than typically assumed due to the hierarchical nature of language. This study aimed to investigate the dynamics of bilingual language control at the phonetic level. Participants, who were speakers of Chinese, English and German, named the letters of the alphabet in English (L2) or German (L3) following an alternating language-switching paradigm. Two sets of letters were selected, differing in the phonological similarity of their pronunciation across the two languages, thereby allowing the exploration of cross-language phonological influences. Each participant completed two sessions of letter-naming tasks. In one session, seven phonologically similar letters were randomly repeated either in single-language blocks or in alternate-language blocks. In the other session, seven phonologically dissimilar letters were similarly manipulated. The results indicated local inhibition, reflected by switch costs and global inhibition, reflected by mixing costs. Reversed language dominance, another indicator of global inhibition, was not observed. However, there was a tendency for larger global inhibition to be applied to the more dominant language. Moreover, there was significantly faster naming for phonologically similar letters compared to dissimilar ones, suggesting a facilitation effect for both English and German, irrespective of whether letter naming occurred in single- or alternate-language blocks. These findings provided evidence for the role of inhibitory and facilitative mechanisms at the phonetic level, suggesting language-specific control in the bilingual brain and underscoring the complexity and dynamics of managing language control across multiple levels of processing.

Compacted bentonite, used as an engineering barrier for permanent containment of high-level radioactive waste, is susceptible to mineral evolution resulting in compromise of the expected barrier performance due to alkaline–thermal chemical interaction in the near-field. To elucidate the mineral-evolution mechanisms within bentonite and the transformation of the nuclide adsorption properties during that period, experimental evolution of bentonite was conducted in a NaOH solution with a pH of 14 at temperatures ranging from 60 to 120°C. The results showed that temperature significantly affects the stability of minerals in bentonite under alkali conditions. The dissolution rate of fine-grained cristobalite in bentonite exceeds that of smectite, with the phase-transition products of smectite being temperature-dependent. As the temperature rises, smectite experiences a three-stage transformation: initially, at 60°C, the lattice structure thins due to the collapse of the octahedral sheets; at 80°C, the lattice disintegrates and reorganizes into a loose framework akin to albite; and by 100°C, it further reorganizes into a denser framework resembling analcime. The adsorption properties of bentonite exhibit a peak inflection point at 80°C, where the dissolution of the smectite lattice eliminates interlayer pores and exposes numerous polar or negatively charged sites which results in a decrease in specific surface area and an increase in cation exchange capacity and adsorption capacity of Eu3+. This research provides insights into the intricate evolution of bentonite minerals and the associated changes in radionuclide adsorption capacity, contributing to a better understanding of the stability of bentonite barriers and the effective long-term containment of nuclear waste.

The inverse dynamics model of an industrial robot can predict and control the robot’s motion and torque output, improving its motion accuracy, efficiency, and adaptability. However, the existing inverse rigid body dynamics models still have some unmodelled residuals, and their calculation results differ significantly from the actual industrial robot conditions. The bootstrap aggregating (bagging) algorithm is combined with a long short-term memory network, the linear layer is introduced as the network optimization layer, and a compensation method of hybrid inverse dynamics model for robots based on the BLL residual prediction algorithm is proposed to meet the above needs. The BLL residual prediction algorithm framework is presented. Based on the rigid body inverse dynamics of the Newton–Euler method, the BLL residual prediction network is used to perform error compensation on the inverse dynamics model of the Franka robot. The experimental results show that the hybrid inverse dynamics model based on the BLL residual prediction algorithm can reduce the average residuals of the robot joint torque from 0.5651 N·m to 0.1096 N·m, which improves the accuracy of the inverse dynamics model compared with those of the rigid body inverse dynamics model. This study lays the foundation for performing more accurate operation tasks using industrial robots.

The egg parasitoid Anastatus japonicus is a key natural enemy in the biological control of various agricultural and forestry pests. It is particularly used against the brown marmorated stink bug Halyomorpha halys and the emerging defoliator pest Caligula japonica in East Asia. It has been proved that the eggs of Antheraea pernyi can be used as a factitious host for the mass production of A. japonicus. This study systematically documented the parasitic behaviour and developmental morphology exhibited by A. japonicus on the eggs of A. pernyi. The parasitic behaviour of A. japonicus encompassed ten steps including searching, antennation, locating, digging, probing, detecting, oviposition, host-feeding, grooming, and resting. Oviposition, in particular, was observed to occur in three stages, with the parasitoids releasing eggs during the second stage when the body remained relatively static. Among all the steps of parasitic behaviour, probing accounted for the longest time, constituting 33.1% of the whole time. It was followed by digging (19.3%), oviposition (18.5%), antennation (9.6%), detecting (7.4%), and the remaining steps, each occupying less than 5.0% of the total event time. The pre-emergence of adult A. japonicus involves four stages: egg (0 to 2nd day), larva (3rd to 9th day), pre-pupa (10th to 13th day), pupa (14th to 22nd day), and subsequent development into an adult. Typically, it takes 25.60 ± 0.30 days to develop from an egg to an adult at 25℃. This information increases the understanding of the biology of A. japonicus and may provide a reference for optimising reproductive devices.

MicroRNAs (miRNAs) play important roles in regulating salt tolerance in Dongxiang wild rice (DXWR, Oryza rufipogon Griff.). The development of salt-responsive miRNA-simple sequence repeat (SSR) markers will significantly bolster research on DXWR, providing novel tools for exploring salt-tolerant genetic resources and advancing the development of salt-tolerant rice varieties. In the present study, a total of 137 miRNA-SSR markers were successfully developed, specifically derived from miRNAs responsive to salt stress in DXWR. Subsequently, a subset of 20 markers was randomly selected for validation across three distinct DXWR populations, along with 35 modern rice varieties. Notably, 13 of these markers exhibited remarkable polymorphism. The polymorphic markers collectively amplified 52 SSR loci, averaging four alleles per locus. The polymorphism information content values associated with these loci spanned from 0.23 to 0.70, with a mean value of 0.49. Particularly noteworthy is the miR162a-SSR marker, which demonstrated distinct allelic patterns and holds potential as a diagnostic marker for discriminating the salt-tolerant rice varieties from the non-tolerant varieties. This study provides a valuable tool for genetic analysis and precision breeding, facilitating the identification and utilization of valuable salt-tolerant genetic resources.

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.

As a member of the Scathophagidae family, Scathophaga stercoraria (S. stercoraria) is widely distributed globally and is closely associated with animal feces. It is also a species of great interest to many scientific studies. However, its phylogenetic relationships are poorly understood. In this study, S. stercoraria was found in plateau pikas for the first time. The potential cause of its presence in the plateau pikas was discussed and it was speculated that the presence of S. stercoraria was related to the yak feces. In addition, 2 nuclear genes (18SrDNA and 28SrDNA), 1 mitochondrial gene (COI), and the complete mitochondrial genome of S. stercoraria were sequenced. Phylogenetic trees constructed based on 13 Protein coding genes (13PCGs), 18S and 28S rDNA showed that S. stercoraria is closely related to the Calliphoridae family; phylogenetic results based on COI suggest that within the family Scathophagidae, S. stercoraria is more closely related to the genus Leptopa, Micropselapha, Parallelomma and Americina. Divergence times estimated using the COI gene suggest that the divergence formation of the genus Scathophaga is closely related to changes in biogeographic scenarios and potentially driven by a combination of uplift of the Qinghai-Tibetan Plateau (QTP) and dramatic climate changes. These results provide valuable information for further studies on the phylogeny and differentiation of the Scathophaga genus in the future.

China is still among the 30 high-burden tuberculosis (TB) countries in the world. Few studies have described the spatial epidemiological characteristics of pulmonary TB (PTB) in Jiangsu Province. The registered incidence data of PTB patients in 95 counties of Jiangsu Province from 2011 to 2021 were collected from the Tuberculosis Management Information System. Three-dimensional spatial trends, spatial autocorrelation, and spatial–temporal scan analysis were conducted to explore the spatial clustering pattern of PTB. From 2011 to 2021, a total of 347,495 newly diagnosed PTB cases were registered. The registered incidence rate of PTB decreased from 49.78/100,000 in 2011 to 26.49/100,000 in 2021, exhibiting a steady downward trend (χ2 = 414.22, P < 0.001). The average annual registered incidence rate of PTB was higher in the central and northern regions. Moran’s I indices of the registered incidence of PTB were all >0 (P< 0.05) except in 2016, indicating a positive spatial correlation overall. Local autocorrelation analysis showed that ‘high–high’ clusters were mainly distributed in northern Jiangsu, and ‘low–low’ clusters were mainly concentrated in southern Jiangsu. The results of this study assist in identifying settings and locations of high TB risk and inform policy-making for PTB control and prevention.