Asian corn borer, Ostrinia furnacalis Guenée (Lepidoptera: Crambidae), is a major pest in corn production, and its management remains a significant challenge. Current control methods, which rely heavily on synthetic chemical pesticides, are environmentally detrimental and unsustainable, necessitating the development of eco-friendly alternatives. This study investigates the potential of the entomopathogenic nematode Steinernema carpocapsae as a biological control agent for O. furnacalis pupae, focusing on its infection efficacy and the factors influencing its performance. We conducted a series of laboratory experiments to evaluate the effects of distance, pupal developmental stage, soil depth, and light conditions on nematode attraction, pupal mortality and sublethal impacts on pupal longevity and oviposition. Results demonstrated that S. carpocapsae exhibited the highest attraction to pupae at a 3 cm distance, with infection declining significantly at greater distances. Younger pupae (<12 h old), were more attractive to nematodes than older pupae, and female pupae were preferred over males. Nematode infection was highest on the head and thorax of pupae, with a significant reduction in infection observed after 24 h. Infection caused 100% mortality in pupae within 2 cm soil depth, though efficacy was reduced under light conditions. Sublethal effects included a significant reduction in the longevity of infected adults and a decrease in the number of eggs laid by infected females compared to controls. These findings underscore the potential of S. carpocapsae as an effective biocontrol agent for sustainable pest management in corn production, offering a viable alternative to chemical pesticides.

The oriental armyworm, Mythimna separata (Walker), is a highly migratory pest known for its sudden larval outbreaks, which result in severe crop losses. These unpredictable surges pose significant challenges for timely and accurate monitoring, as conventional methods are labour-intensive and prone to errors. To address these limitations, this study investigates the use of machine learning for automated and precise identification of M. separata larval instars. A total of 1577 larval images representing different instar were analysed for geometric, colour, and texture features. Additionally, larval weight was predicted using 13 regression models. Instar identification was conducted using Support Vector Classifier (SVC), Random Forest, and Multi-Layer Perceptron. Key feature contributing to classification accuracy were subsequently identified through permutation feature importance analysis. The results demonstrated the potential of machine learning for automating instar identification with high efficiency and accuracy. Predicted larval weight emerged as a key feature, significantly enhancing the performance of all identification models. Among the tested approaches, BaggingRegressor exhibited the best performance for larval weight prediction (R2 = 98.20%, RMSE = 0.2313), while SVC achieved the highest instar identification accuracy (94%). Overall, the integration of larval weight with other image-derived features proved to be a highly effective strategy. This study demonstrates the efficacy of machine learning in enhancing pest monitoring systems by providing a scalable and reliable framework for precise pest management. The proposed methodology significantly improves larval instar identification accuracy and efficiency, offering actionable insights for implementing targeted biological and chemical control strategies.

While the innovation behaviors of family firms (FFs) have attracted burgeoning scholarly attention, few studies have investigated how intergenerational succession, one of the most critical aspects of family dynamics changes among FFs, affects innovation behaviors. Based on the socioemotional wealth perspective (SEW), we have introduced a concept of innovation decoupling that refers to the tendency of prioritizing the symbolic disclosures over substantive changes of innovation and proposed that FFs that have experienced intergenerational succession would exhibit a greater extent of innovation decoupling. By tracking a sample of Chinese publicly listed FFs from 2012 to 2021 while applying the machine learning approach, we have confirmed the proposition and further unveiled that such inclination becomes weaker when the focal FF is influenced by the family affective endowment and the successor with ascribed bureaucratic connections. Overall, this study brings new nuances to the knowledge of the innovation behaviors of FFs by highlighting the inter-firm heterogeneities and impacts of family dynamics.

Given the growing trend of using digital platforms for exporters' internationalization, the management of exporters' online internationalization has become a critical issue. However, academic research in this area remains sparse. Specifically, little is known about when and under what conditions exporters may consider discontinuing the use of a digital platform for exporting, i.e., online de-internationalization. This study develops and tests a theoretical framework for these determinants and the contingencies for exporters' online de-internationalization. Specifically, drawing on the de-internationalization literature, we identify sets of internal and external antecedents of exporters' intention to discontinue the use of digital platforms for exporting. Furthermore, we examine the moderating effect of technological opportunism. Based on a unique sample of Chinese exporters registered on Alibaba.com, the world's largest business-to-business platform, the empirical findings support our proposed determinants of online de-internalization. This article ultimately discusses the theoretical and managerial implications.

We investigate the statistical properties of kinetic and thermal dissipation rates in two-dimensional/three-dimensional vertical convection of liquid metal ($Pr = 0.032$) within a square cavity. Two situations are specifically discussed: (i) classical vertical convection with no external forces and (ii) vertical magnetoconvection with a horizontal magnetic field. Through an analysis of dissipation fields and a reasonable approximation of buoyancy potential energy sourced from vertical heat flux, the issue of the ‘non-closure of the dissipation balance relation’, which has hindered the application of the GL theory in vertical convection, is partially resolved. The resulting asymptotic power laws are consistent with existing laminar scaling theories and even show certain advantages in validating simulations with large Prandtl number ($Pr$). Additionally, a full-parameter model and prefactors applicable to low-$Pr$ fluids are provided. The extension to magnetoconvection naturally introduces the approximate expression for total buoyancy potential energy and necessitates adjustments to the contributions of kinetic dissipation in both the bulk and boundary layer. The flow dimensionality and boundary layer thickness are key considerations in this analysis. The comprehension of Joule dissipation has been updated: the Lorentz force generates positive dissipation in the bulk by suppressing convection, while in the Hartmann layer, shaping the exponential boundary layer requires the fluid to perform positive work to accelerate, leading to negative dissipation. Finally, the proposed transport equations for magnetoconvection are supported by current direct numerical simulation (DNS) and literature data, and the applicability of the model is discussed.

On both global and local levels, one can observe a trend toward the adoption of algorithmic regulation in the public sector, with the Chinese social credit system (SCS) serving as a prominent and controversial example of this phenomenon. Within the SCS framework, cities play a pivotal role in its development and implementation, both as evaluators of individuals and enterprises and as subjects of evaluation themselves. This study engages in a comparative analysis of SCS scoring mechanisms for individuals and enterprises across diverse Chinese cities while also scrutinizing the scoring system applied to cities themselves. We investigate the extent of algorithmic regulation exercised through the SCS, elucidating its operational dynamics at the city level in China and assessing its interventionism, especially concerning the involvement of algorithms. Furthermore, we discuss ethical concerns surrounding the SCS’s implementation, particularly regarding transparency and fairness. By addressing these issues, this article contributes to two research domains: algorithmic regulation and discourse surrounding the SCS, offering valuable insights into the ongoing utilization of algorithmic regulation to tackle governance and societal challenges.

In 2023 the Supreme Court of Mauritius cited human rights and public health arguments to strike down a colonial-era law criminalizing consensual same-sex sex. The parliament of Singapore recently did the same through legislative means. Are these aberrations or a shifting global consensus? This article documents a remarkable shift international legal shift regarding LGBTQ+ sexuality. Analysis of laws from 194 countries across multiple years demonstrates a clear, ongoing trend toward decriminalization globally. Where most countries criminalized same-sex sexuality in the 1980s, now two-thirds of countries do not criminalize under law. Additionally, 28 criminalizing countries in 2024 demonstrate a de facto policy of non-enforcement, a milestone towards legal change that all of the countries that have fully decriminalized since 2017 have taken. This has important public health effects, with health law lessons for an era of multiple pandemics. But amidst this trend, the reverse is occurring in some countries, with a counter-trend toward deeper, harsher criminalization of LGBTQ+ sexuality. Case studies of Angola, Singapore, India, Botswana, Mauritius, Cook Islands, Gabon, and Antigua and Barbuda show many politically- and legally-viable pathways to decriminalization and highlight actors in the executive, legislative, and judicial arenas of government and civil society engaged in legal change.

Hand, foot, and mouth disease (HFMD) shows spatiotemporal heterogeneity in China. A spatiotemporal filtering model was constructed and applied to HFMD data to explore the underlying spatiotemporal structure of the disease and determine the impact of different spatiotemporal weight matrices on the results. HFMD cases and covariate data in East China were collected between 2009 and 2015. The different spatiotemporal weight matrices formed by Rook, K-nearest neighbour (KNN; K = 1), distance, and second-order spatial weight matrices (SO-SWM) with first-order temporal weight matrices in contemporaneous and lagged forms were decomposed, and spatiotemporal filtering model was constructed by selecting eigenvectors according to MC and the AIC. We used MI, standard deviation of the regression coefficients, and five indices (AIC, BIC, DIC, R2, and MSE) to compare the spatiotemporal filtering model with a Bayesian spatiotemporal model. The eigenvectors effectively removed spatial correlation in the model residuals (Moran’s I < 0.2, p > 0.05). The Bayesian spatiotemporal model’s Rook weight matrix outperformed others. The spatiotemporal filtering model with SO-SWM was superior, as shown by lower AIC (92,029.60), BIC (92,681.20), and MSE (418,022.7) values, and higher R2 (0.56) value. All spatiotemporal contemporaneous structures outperformed the lagged structures. Additionally, eigenvector maps from the Rook and SO-SWM closely resembled incidence patterns of HFMD.

Manned lunar landers must ensure astronaut safety while enhancing payload capacity. Due to traditional landers being weak in high-impact energy absorb and heavy payload capacity, a Starship-type manned lunar lander is proposed in this paper. Firstly, a comprehensive analysis was conducted on the traditional cantilever beam cushioning mechanism for manned lander. Subsequently, a 26-ton manned lander and its landing mechanism were designed, and a rigid-flexible coupling dynamic analysis was performed on the compression process of the primary and auxiliary legs. Secondly, the landing performance of the proposed Starship-type manned lunar lander was compared with the traditional 14-ton manned lander in multiple landing conditions. The results indicate that under normal conditions, the largest acceleration of the proposed 26-ton Starship-type manned lander decreases more than 13.1%. It enables a significant increase in payload capacity while mitigating impact loads under various landing conditions.

Exposure to adversity during the perinatal period has been associated with cognitive difficulties in children. Given the role of the nucleus accumbens (NAcc) in attention and impulsivity, we examined whether NAcc volume at age six mediates the relations between pre- and postnatal adversity and subsequent attention problems in offspring. 306 pregnant women were recruited as part of the Growing Up in Singapore Towards Healthy Outcomes Study. Psychosocial stress was assessed during pregnancy and across the first 5 years postpartum. At six years of age, children underwent structural MRI and, at age seven years, mothers reported on their children’s attention problems. Separate factor analyses conducted on measures of pre- and postnatal adversity each yielded two latent factors: maternal mental health and socioeconomic status. Both pre- and postnatal maternal mental health predicted children’s attention difficulties. Further, NAcc volume mediated the relation between prenatal, but not postnatal, maternal mental health and children’s attention problems. These findings suggest that the NAcc is particularly vulnerable to prenatal maternal mental health challenges and contributes to offspring attention problems. Characterizing the temporal sensitivity of neurobiological structures to adversity will help to elucidate mechanisms linking environmental exposures and behavior, facilitating the development of neuroscience-informed interventions for childhood difficulties.

The impact of long-term nocturnal warming on soil aggregate stability and carbon (C) and nitrogen (N) sequestration was examined in agricultural fields. Employing a passive warming system, the nighttime warming experiment involved two treatments: a control check (CK) and a nighttime warming treatment (WT), spanning the entire growth seasons of wheat from 2013 to 2021. The annual average temperature increase ranged from 0.3 to 1.3°C, with an average increment of 0.71°C over the eight years. Both dry and wet sieving methods showed that nighttime warming reduced the proportion of macroaggregates and increased microaggregates compared to CK, thereby diminishing soil aggregate (SA) stability. While nighttime warming had the potential to elevate the concentrations and contents of soil organic carbon (SOC) and total nitrogen (TN), significant effects were only observed in the concentrations and contribution rates of SOC and TN. The C/N ratios across different particle sizes within SA were not significantly affected by nighttime warming. Additionally, no significant correlation was found between the SOC/TN contents and contribution rates and the stability of SA. These results suggest that eight years of nighttime warming could undermine the stability of SA, yet it did not impact the pools of N and C in the agricultural lands of central China.

We perform the first mapping of the ideological positions of European parties using generative Artificial Intelligence (AI) as a “zero-shot” learner. We ask OpenAI’s Generative Pre-trained Transformer 3.5 (GPT-3.5) to identify the more “right-wing” option across all possible duplets of European parties at a given point in time, solely based on their names and country of origin, and combine this information via a Bradley–Terry model to create an ideological ranking. A cross-validation employing widely-used expert-, manifesto- and poll-based estimates reveals that the ideological scores produced by Large Language Models (LLMs) closely map those obtained through the expert-based evaluation, i.e., CHES. Given the high cost of scaling parties via trained coders, and the scarcity of expert data before the 1990s, our finding that generative AI produces estimates of comparable quality to CHES supports its usage in political science on the grounds of replicability, agility, and affordability.

Objectives/Goals: Engaging interest holders in research is increasingly common, and guidelines include creating engagement plans. A detailed plan may be especially helpful when researchers perceive engagement as difficult or less relevant. We tested whether a study’s translational stage or an investigator’s years of research experience affect their perceptions. Methods/Study Population: Since 2019, the Tufts Clinical and Translational Science Institute Pilot Studies Program required applicants to submit plans to engage interest holders. Applicants in three cohorts responded to a survey about this requirement, including perceived difficulty developing an engagement plan, perceived relevance of engagement, and self-reported years of research experience (≤5, 6–10, and ≥10 years). Two raters assigned translational stage(s) of proposed studies: T0 (basic science), T.5 (pre-clinical to initial human studies), and T1 through T4. Separate analyses were conducted when multistage studies were coded as the earliest vs. latest stage and for individual stage vs. groups of stages (T0/T.5/T1 vs. T2/T3/T4). The Fisher’s exact statistical test was used to assess associations between variables. Results/Anticipated Results: Analyses included 67 participants. Developing an engagement plan was perceived as more difficult for studies at earlier translational stages when those studies were coded as the earliest applicable stage. This significant association held both when stages were grouped as T0/T.5/T1 and T2/T3/T4 (P  =  .03) and when analyzed as a single stage (P  =  .01); however, when studies were coded as the latest applicable stage, there were no significant associations. Similarly, when multistage studies were coded as the earliest applicable stage, engagement was perceived as less relevant for early-stage studies when grouped (P  =  .04), but not for individual stages or when studies were coded as the latest applicable stage. No significant association between years of research experience and perceived difficulty was identified. Discussion/Significance of Impact: Results show that investigators conducting early-stage research perceive more difficulty engaging interest holders, aligning with prior qualitative studies. These investigators may need more evidence of the value added to early-stage studies, targeted and practical training, and funder requirements to establish a culture of engagement.

Objectives/Goals: Sexual minority populations (SMPs), including lesbian, gay, and bisexual groups, disproportionately encounter discriminatory experiences due to bi/homonegativity and systemic inequities across various social domains. We aim to understand how the neighborhood-level stressors and resilience sources differed across specific groups in SMPs. Methods/Study Population: Utilizing the NIH All of Us’ cloud-based platform, we selected cohorts self-identifying as gay (n  =  9,454), bisexual (n  =  15,284), lesbian (n = 5267), or straight (n  =  349,748). We explored multiple key measures of neighborhood-level stressors (e.g., neighborhood disorder, neighborhood cohesion, and environment index) and resilience sources (e.g., neighbor cohesion, social support), and other factors (e.g., food insecurity, housing insecurity, and housing instability) by their sexual orientations using analysis of variance or Chi-square analyses. Results/Anticipated Results: Our sample comprised 60.8% females and 37.5% males identifying as non-binary or transgender, with an average age of 55.6 years (SD  =  17.1). The racial composition was 56.0% White, 19.4% Black, 18.7% Hispanic, and 5.9% others (e.g., Asian, multiracial). Compared to straight individuals, SMPs reported high neighborhood stressors (e.g., disorder, worse environment) but lower neighborhood-level resilience sources (e.g., social support, cohesion). In addition, bisexual groups reported highest prevalence of housing insecurity (6.7% vs. 2.3%), housing instability (36.0% vs. 19.6%), and food insecurity (26.57% vs. 12.21%). Discussion/Significance of Impact: SMPs, particularly bisexual individuals, face greater neighborhood stressors and fewer resilience sources than their straight counterparts. These findings call for targeted interventions to address these disparities and promote health equity, using large-scale datasets to inform community-based solutions.