Steinernema carpocapsae is an entomopathogenic nematode with established efficacy against various agricultural pests. However, its impact on key lepidopteran pests, including Ostrinia furnacalis, Mythimna separata, and Spodoptera litura, remains underexplored, particularly at the pupal stage. This study evaluates the efficacy of the nematode through a combination of choice-based attraction assays, non-choice infection performance bioassays involving direct application to specific pupal body parts, and assessments of sublethal effects on adult survival and oviposition following pupal-stage exposure. S. carpocapsae exhibited a clear preference for pupae of all three pests over blank controls and for previously infected pupae over healthy pupae. When presented with different pupal genders, S. carpocapsae preferred female M. separata over males but showed no gender preference for O. furnacalis and S. litura. Infection performance varied by body part, with a higher infection performance on the abdomen and thorax compared to the head for O. furnacalis and S. litura, and on the abdomen over the thorax and head for M. separata. Adult survival probability was significantly lower when pupae were infected, and female oviposition was reduced when either member of a mating pair had been infected. These findings highlight the efficacy of S. carpocapsae as a promising biological control agent against these lepidopteran pests, particularly when targeting the pupal stage.

Lagostonema ecasiense is a bursate nematode parasite of Lagostomus maximus in Argentina. New morphological data, geographical distribution, ecological data, molecular characterization and exploratory phylogenetic analysis are provided. The general morphology and measurements agree with the original description with minimal discrepancies. The geographical distribution of Lagostonema is expanded with 3 new provinces and 9 new departments in Argentina. The molecular characterization constitutes the first molecular contribution for the genus Lagostonema. The analysis of genetic distances and phylogenetic exploration allow considering L. ecasiense as a nominal species, confirming its nomenclatural taxonomic identity. Likewise, although morphological studies allow the identification of specimens from all populations as L. ecasiense, molecular studies show a major genetic distance in the population from Santiago del Estero Province concerning the rest of the populations. Consequently, the haplotypes are mentioned as Lagostonema sp. with the possibility that these specimens belong to a new species. This study is valuable because it contributes to the ratification of a nominal species described decades ago, adding new morphological aspects and providing an understanding of their value as a marker of host populations.

Ostrinia furnacalis Guenée (Lepidoptera: Crambidae) is a key lepidopteran pest affecting maize production across Asia. While its general biology has been well studied, the phenomenon of pupal ring formation remains poorly understood. This study examined the factors influencing pupal ring formation under controlled laboratory conditions. Results showed that pupal rings were formed exclusively when larvae were reared on an artificial diet, with no ring formation observed on corn-stalks. Females exhibited a significantly higher tendency to participate in ring formation than males. Additionally, male participation increased proportionally with the number of rings formed, a pattern not observed in females. The size of the rearing arena significantly influenced ring formation, with smaller arenas (6 cm diameter) promoting more frequent pairing, particularly among females. Temperature also played a significant role: lower participation rates were recorded at 22 °C compared to 25 °C and 28 °C, although the number of rings formed did not differ significantly across temperatures. Developmental stage and sex composition further influenced pairing behaviour; pupal rings formed only among individuals of similar maturity, and male participation was significantly reduced in all-male groups compared to mixed-sex groups. These findings suggest that pupal ring formation in O. furnacalis is modulated by dietary substrate, larval sex, environmental conditions, and developmental synchrony, offering new insights into the behavioural ecology of this pest.

The function of aortic heart valves is to prevent regurgitant flow from the aorta into the left ventricle. A higher regurgitant flow is observed in bileaflet mechanical heart valves (BMHVs) compared with bioprosthetic heart valves (BHVs) because of their delayed closure. Here, we investigate this behaviour through fluid–structure interaction simulations of a BMHV compared with a trileaflet mechanical heart valve (TMHV) and a BHV under similar conditions. We find that the TMHV and BHV begin to close during the systolic deceleration, whereas BMHV only begins to close when the flow reverses. We found this to be related to hemodynamics as the TMHV and BHV, when fully opened, generate a central jet-dominant flow, whereas the BMHV generates triple jets with lateral jets being wider than its central jet. The flow deceleration of the central jet during late systole is higher than that of the sinuses, which results in a lower pressure in the central region than the sinuses to drive the leaflets of the TMHV and BHV towards the centre for closure. Conversely, the pressure on the sinus- and central flow-sides of the BMHV leaflets is nearly the same until the end of systole. We, contrary to what classically believed, did not find any evidence of sinus vortices generating high pressure or viscous stresses to initiate valve closure. Overall, the results suggest that the generation of a strong central jet and the direction of the leaflets’ closure towards the centre are the design principles to ensure an early valve closure and minimise regurgitation.

Suicidal and self-harming behaviours present a significant challenge for mental health services. Recent national guidelines advocate abandoning tools based on box-ticking and a move towards a personalised psychosocial assessment. This article examines evidence from theoretical and empirical research in this area and attempts to integrate it by introducing the source–problem–solution–motive (SPSM) model. The model, which builds on the contributions of other suicidologists, specially Jean Baechler, could be used as a framework for the assessment and management of these behaviours. The four stages of the model provide a comprehensive approach that enables an exploration of the internal logic of the behaviour. The model covers ‘because’ and ‘in-order-to’ motives. This allows a personalised approach, but also a structured one that can be taught and generalised.

[We present three articles on Iran in the crosshairs, examining the conflict over Iran in light of moves by the US, UN, Japan, EU and Israel. The central issue concerns the US effort to bring Iran before the UN Security Council for its refusal to terminate the development of its civilian nuclear power program. It is a course that many see as the essential step toward US-directed regime change.

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.

The Asian corn borer, Ostrinia furnacalis (Guenée), emerges as a significant threat to maize cultivation, inflicting substantial damage upon the crops. Particularly, its larval stage represents a critical point characterised by significant economic consequences on maize yield. To manage the infestation of this pest effectively, timely and precise identification of its larval stages is required. Currently, the absence of techniques capable of addressing this urgent need poses a formidable challenge to agricultural practitioners. To mitigate this issue, the current study aims to establish models conducive to the identification of larval stages. Furthermore, this study aims to devise predictive models for estimating larval weights, thereby enhancing the precision and efficacy of pest management strategies. For this, 9 classification and 11 regression models were established using four feature datasets based on the following features geometry, colour, and texture. Effectiveness of the models was determined by comparing metrics such as accuracy, precision, recall, F1-score, coefficient of determination, root mean squared error, mean absolute error, and mean absolute percentage error. Furthermore, Shapley Additive exPlanations analysis was employed to analyse the importance of features. Our results revealed that for instar identification, the DecisionTreeClassifier model exhibited the best performance with an accuracy of 84%. For larval weight, the SupportVectorRegressor model performed best with R2 of 0.9742. Overall, these findings present a novel and accurate approach to identify instar and predict the weight of O. furnacalis larvae, offering valuable insights for the implementation of management strategies against this key pest.

The Asian corn borer (ACB), Ostrinia furnacalis (Guenée, 1854), is a serious pest of several crops, particularly a destructive pest of maize and other cereals throughout most of Asia, including China, the Philippines, Indonesia, Malaysia, Thailand, Sri Lanka, India, Bangladesh, Japan, Korea, Vietnam, Laos, Myanmar, Afghanistan, Pakistan and Cambodia. It has long been known as a pest in South-east Asia and has invaded other parts of Asia, Solomon Islands, parts of Africa and certain regions of Australia and Russia. Consequently, worldwide efforts have been increased to ensure new control strategies for O. furnacalis management. In this article, we provide a comprehensive review of the ACB covering its (i) distribution (geographic range and seasonal variations), (ii) morphology and ecology (taxonomy, life-history, host plants and economic importance) and (iii) management strategies (which include agroecological approaches, mating disruption, integrated genetic approaches, chemical as well as biological control). Furthermore, we conclude this review with recommendations to provide some suggestions for improving eco-friendly pest management strategies to enhance the sustainable management of ACB in infested areas.