Explore the vast range of titles available.

We present distributions of the zonal-mean temperature and static stability in the Venusian atmosphere obtained from Venus Express and Akatsuki radio occultation profiles penetrating down to an altitude of 40 km. At latitudes equatorward of 75°, static stability derived from the observed temperature profiles is consistent with previous in-situ measurements in that there is a low-stability layer at altitudes of 50–58 km and highly and moderately stratified layers above 58 km and below 50 km, respectively. Meanwhile, at latitudes poleward of 75°, a low-stability layer extends down to 42 km, which has been unreported in analyses of previous measurements. The deep low-stability layer in the polar region cannot be explained by vertical convection in the middle/lower cloud layer, and the present result thus introduces new constraints on the dynamics of the sub-cloud atmosphere. The Venusian atmosphere is in striking contrast to the Earth’s troposphere, which generally has a deeper low-stability layer at low latitudes than at mid- and high latitudes.

Near net shape forging represents a manufacturing philosophy aimed at achieving components that closely approximate their final geometries in the as-forged state. Unlike a specific forging process, it emphasizes minimizing post-forging machining and material waste while enhancing efficiency and cost-effectiveness. The present work focuses on the preform design of commercially pure aluminium for closed-die forging conditions by analyzing its flow in the die cavity using Deform 3D software. The simulations have been conducted using DEFORM 3D V11.2 software to determine the optimal shape and size of the preform, thereby minimizing costly and inefficient shop floor iterations. The fully defined finite element model includes tetrahedral elements, refined contact region mesh, Lagrangian incremental solver, Coulomb friction formulation, and a calibrated nonlinear hardening law. Three preform geometries of equal volume were evaluated to determine the most suitable design for forming a 40 mm sphere. Experiments validated numerical predictions using a closed-die forging setup. Results show strong agreement in material flow, die filling, and energy trends, though quantitative deviations in forging energy (12.8%), ovality (1.9% simulation vs. 3.6% experimental), die-filling completeness (97.4% simulation vs. 95.1% experiment), and volume conservation (< 1% error in both cases) arose due to friction and strain hardening effects. The findings highlight the effectiveness of simulation in refining the forging process, offering practical insights for manufacturing complex components with improved quality and efficiency.

The Litchi stink bug, Tessaratoma javanica (Thunberg) (Hemiptera: Tessaratomidae), is a major insect pest of litchi in India. Insect-associated bacteria play significant roles in their growth and development. We studied the bacterial communities linked to T. javanica using 16 S rRNA amplicon sequencing and predicted the functions of associated bacterial communities. The findings revealed that bacterial communities significantly differ across the developmental stages of T. javanica . The primary bacterial phyla across all developmental stages linked to T. javanica were Proteobacteria, Firmicutes, Bacteroidota, Actinobacteria, Patescibacteria, and Nitrospirota. Class Gammaproteobacteria predominated in first and 4th nymphal instars, and adult females, whereas Bacilli dominated the gut of the 3rd, and 5th nymphal instars of T. javanica . Ligilactobacillus apodemi , Staphylococcus xylosus , and Pseudomonas furukawaii were identified as the predominant bacterial species associated with T. javanica . The peak bacterial diversity was observed in the 5th nymphal instar and the lowest in the 1st nymphal instar. The observed changes between growth and developmental stages indicate that bacterial communities are dynamic and perpetually developing to meet the metabolic functions of T. javanica . Comprehending these interactions will improve our understanding of the ecological relationship with this pest and assists in developing and implementing efficient biological control plans for its management.

Photosynthesis, crop health and dry matter partitioning are among the most important factors influencing crop productivity and quality. Identifying variation in these parameters may help discover the plausible causes for crop productivity differences under various management practices and cropping systems. Thus, a 2-year (2019–2020) study was undertaken to investigate how far the integrated crop management (ICM) modules and cropping systems affect maize physiology, photosynthetic characteristics, crop vigour and productivity in a holistic manner. The treatments included nine main-plot ICM treatments [ICM 1 to ICM 4 – conventional tillage (CT)-based; ICM 5 to ICM 8 – conservation agriculture (CA)-based; ICM 9 – organic agriculture (OA)-based] and two cropping systems, viz ., maize–wheat and maize + blackgram–wheat in subplots. The CA-based ICM module, ICM 7 resulted in significant ( p < 0.05) improvements in the physiological parameters, viz ., photosynthetic rate (42.56 μ mol CO 2 m –2 sec –1 ), transpiration rate (9.88 m mol H 2 O m –2 sec –1 ) and net assimilation rate (NAR) (2.81 mg cm –2 day –1 ), crop vigour [NDVI (0.78), chlorophyll content (53.0)], dry matter partitioning toward grain and finally increased maize crop productivity (6.66 t ha –1 ) by 13.4–14.2 and 27.3–28.0% over CT- and OA-based modules. For maize equivalent grain yield (MEGY), the ICM modules followed the trend as ICM 7 > ICM 8 > ICM 5 > ICM 6 > ICM 3 > ICM 4 > ICM 1 > ICM 2 > ICM 9 . Multivariate and PCA analyses also revealed a positive correlation between physiological parameters, barring NAR and both grain and stover yields. Our study proposes an explanation for improved productivity of blackgram-intercropped maize under CA-based ICM management through significant improvements in physiological and photosynthetic characteristics and crop vigour. Overall, the CA-based ICM module ICM 7 coupled with the maize + blackgram intercropping system could be suggested for wider adoption to enhance the maize production in semiarid regions of India and similar agroecologies across the globe.

The capacity to comprehend and communicate with others via language is one of the most valuable human abilities. We are well-trained in our experience reading awareness of different emotions since they play a vital part in communication. Contrary to popular belief, emotion recognition is a challenging task for computers or robots due to the subjective nature of human mood. This research proposes a framework for acknowledging the passionate sections of conversation, independent of the semantic content, via the recognition of discourse feelings. To categorize the emotional content of audio files, this article employs deep learning techniques such as convolutional neural networks (CNNs) and long short-term memories (LSTMs). In order to make sound information as helpful as possible for future use, models using Mel-frequency cepstral coefficients (MFCCs) were created. It was tested using RAVDESS and TESS datasets and found that the CNN had a 97.1% accuracy rate.

Drought is a global phenomenon affecting plant growth and productivity, the severity of which has impacts around the whole world. A number of approaches, such as agronomic, conventional breeding, and genetic engineering, are followed to increase drought resilience; however, they are often time consuming and non-sustainable. Plant growth-promoting microorganisms are used worldwide to mitigate drought stress in crop plants. These microorganisms exhibit multifarious traits, which not only help in improving plant and soil health, but also demonstrate capabilities in ameliorating drought stress. The present review highlights various adaptive strategies shown by these microbes in improving drought resilience, such as modulation of various growth hormones and osmoprotectant levels, modification of root morphology, exopolysaccharide production, and prevention of oxidative damage. Gene expression patterns providing an adaptive edge for further amelioration of drought stress have also been studied in detail. Furthermore, the practical applications of these microorganisms in soil are highlighted, emphasizing their potential to increase crop productivity without compromising long-term soil health. This review provides a comprehensive coverage of plant growth-promoting microorganisms-mediated drought mitigation strategies, insights into gene expression patterns, and practical applications, while also guiding future research directions.

Inadequate nutrient management is one of the major challenges for sustainable soybean production in semi-arid climatic conditions. Hence, a 3-year (2015–2017) field experiment was conducted to assess the effect of foliar application of macro- and micronutrients on the growth, productivity, and profitability of soybean. Eight foliar nutrient sprays at the pod initiation stage—water spray (WS), 2% urea solution, 2% di-ammonium phosphate solution (DAP2%), 0.5% muriate of potash solution (MOP0.5%), 2% solution of 19:19:19 nitrogen phosphorus and potassium (NPK2%), and a 0.5% solution each of molybdenum (Mo0.5%), boron (B0.5%), chelated-zinc (Zn 0.5%) and no-foliar nutrition (NFN)—were compared with a basal-applied recommended dose of fertilizers (RDF: 30 kg N, 75 kg P, and 40 kg K ha−1) in a randomized block design (RBD), replicated three times. Foliar-applied chelated Zn@0.5% (Zn0.5%) at the pod initiation stage resulted in more pods per plants. In addition to Zn0.5%, urea2%, NPK2%, and B0.5% significantly improved the pods per plant over treatment by no-foliar nutrition (NFN). The RDF-supplied soybean subsequently sprayed with Zn0.5% produced the highest seed yield, which was 18.5–37.8% higher than that of NFN treatment Yield improvement due to the application of B0.5%, DAP2%, and urea2% varied between 19.2–23.7, 16.6–20.4 and 18.6–20%, respectively. Foliar nutrition showed the largest net returns from Zn0.5%. The water-use efficiency (WUE) and production efficiency increased by 18.4–37.6 and 34.9–37.5%, respectively, due to Zn0.5% over the efficiencies from NFN treatment. Monetary efficiency (ME) gains due to Zn0.5% were 24% higher, while ME efficiency gains due to urea2%, NPK2%, and B0.5% varied between 15–16%. Thus, this study suggested that the foliar application of 0.5% Zn and B, urea, NPK fertilizer, and DAP at 2%, along with RDF. is a profitable nutrient management option for quality soybean production in a semiarid region. However, nutrient partitioning, changes in soil chemical and biological indicators, and environmental aspects need critical examination in future studies.

Deficiency of Zn in human diet is an emerging health issue in many developing countries across the globe. Agronomic Zn biofortification using diverse Zn fertilization options is being advised for enhancing Zn concentration in the edible portion of rice.A field study was carried out to find out the Zn fertilization effects on biofortification of basmati rice and nutrient use efficiencies in the Himalayan foothills region. Amongst the Zn nutrition treatments, 4.0% Zn-coated urea (ZnCU) + 0.2% Zn foliar spray (FS) using ZnSO4·7H2O recorded the highest grain (3.46 t/ha) and straw (7.93 t/ha) yield of basmati rice. On average, the rice productivity increase due to ZnCU application was ~25.4% over Commercial Urea. Likewise, the same Zn fertilization treatment also resulted in the maximum Zn (35.93 and 81.64 mg/kg) and N (1.19 and 0.45%) concentration in grain and straw of rice, respectively. Moreover, N use efficiency (NUE) was also highest when ZnCU was applied at 4.0% (ZnSO4·7H2O) in comparison to soil application. From the grain quality viewpoint, Zn ferti-fortification had significant effect on elongation ratio and protein concentration of grain only and respective Zn fertilization treatment recorded highest quality parameters 1.90 and 7.44%, respectively. Therefore, ZnCU would be an important low-cost and useful strategy for enhancing yield, NUE and biofortification, and also in minimizing the Zn malnutrition related challenges in human diet in many developing economies.

Maize is an economically important cereal crop, whose adaptability to a variety of agroecological zones and uses as a food, feed, and input in various industries has ensured its global importance. In this study, the implications of the raised bed planting (RBP) system on smallholder maize farming in Bihar, India, for four consecutive Rabi seasons were evaluated from 2020–2021 to 2023–2024. The research focuses on key parameters such as productivity, profitability, water use efficiency (WUE), and nutrient use efficiency (NUE) to present a sustainable alternative to traditional flatbed planting systems. Maize yield at RBP ranged from 9.28 to 10.53 t ha −1 , significantly higher than the range of 5.70 to 8.29 t ha −1 for flatbed (FB). The raised bed planting (RBP) system was more profitable as well, where net return increased by 20% compared to the FB system. WUE was 35% better in the RBP system, and NUE (grain yield per unit of applied N) was 25% better than FB systems. RBP enhances water and nutrient (nitrogen, phosphorus, and potassium) use efficiency, boosting productivity and profitability.