University of Agriculture, Peshawar

The assessment of genotype × environment interactions (GEI) and the trait stability estimation are pivotal in germplasm selection and varietal development. In this study, forty bread wheat (Triticum aestivum L.) advanced lines were subjected to a multi-environmental evaluation across seven different environments to assess their agronomic performances and yield stability under both irrigated and rainfed conditions. The trials were conducted according an RCB Design under 7 different environments in four different locations for two consecutive cropping seasons 2016–2017 and 2017–2018. Results showed high genotypic variation between the studies genotypes with significant effects of environment and GEI for all studied traits. The environment effect was mostly predominant for grain yield and tillers m−2, while GEI effects were predominant for grains spike−2. Clear and predominant genotypic effects were observed for kernel weight. Agronomic performance of different tested genotypes and their stability across all environments were confirmed at a higher dimension using principal component analysis (PCA). The two first components of the PCA (PCA1 and PCA2) explained 57.1

Underwater Wireless Sensor Network (UWSN) accomplishes the consideration of a few scientists and academicians towards itself. Because of the brutality of the climate lies submerged represents various difficulties, i.e., high transmission delay, outstanding piece mistake rate, more expense in usage, sinks development and energy imperatives, unequal surface highlights of an area and low data transfer capacity, and so forth Void opening evasion is compulsory for to motivation behind limiting the utilization of energy and amplifying throughput and region inclusion. In this exploration work, the creator planned plans for void opening shirking initial one is, Avoiding Void Hole Adaptive Hop by Hop Vector-Based Forwarding (AVH-AHH-VBF) in submerged remote sensor organization and a second plan for limiting utilization of energy and expanding the lifetime of the organization, Sink Mobility-Adaptive Hop by Hop Vector-Based Forwarding (SM-AHH-VBF). Reproduction results show that our plans beat contrasted and standard arrangement as far as normal Packet Delivery Ratio (PDR), energy charge. Our reproduction confirms the effectiveness of our proposed procedure AVH-AHH-VBF equivalents to 0.17 and SM-AHH-VBF equivalents to 0.24 regarding normal PDR, AVH-AHH-VBF equivalents to 24j and SM-AHH-VBF equivalents to 5j for the normal energy charge, AVH-AHH-VBF had a tradeoff of 63% in light of considering two jumps and SM-AHH-VBF approaches 20% tradeoff for normal start to finish.

This study presents an integrated Data Envelopment Analysis (DEA) and ensemble learning framework optimized with the Golden Jackal Optimization (GJO) algorithm to evaluate and predict the efficiency of United States information technology firms. Both Constant Returns to Scale and Variable Returns to Scale models were applied to measure firm efficiency and compute scale efficiency, providing a clearer distinction between managerial and scale-related effects. Using data from 3,940 firms over the period 2013 to 2023, a robustness test introducing ±20% random noise to a 10% random sample confirmed that the CCR model achieved stronger stability, with a correlation coefficient of 0.795 compared to 0.773 for the BCC model. Consequently, the CCR results were adopted as the basis for predictive modeling. DEA efficiency scores were predicted using six ensemble learners, including XGBoost, Gradient Boosting Regressor, AdaBoost, Extra Trees Regressor, Random Forest, and LightGBM, with GJO employed for hyperparameter tuning. The Gradient Boosting Regressor optimized with GJO achieved the best predictive performance, accurately reproducing the observed efficiency scores. SHAP and feature importance analyses revealed that Total Equity, Operating Income, and Total Assets were the most influential determinants of efficiency. This research contributes a scalable and interpretable approach to efficiency prediction, offering actionable insights for managers, investors, and policymakers in volatile financial markets.

Tillage and nitrogen (N) management are key drivers of soil fertility and microbial processes in semi-arid agroecosystems. However, their combined long-term effects under the commonly adopted plastic film mulching system remain poorly understood. In this study, plastic film mulching was applied uniformly across all treatments to conserve soil moisture and temperature, reflecting standard agronomic practices in the semi-arid Loess Plateau of China. A multi-year field experiment was conducted to assess four tillage practices (conventional, rotary, no-tillage, and subsoil) combined with two N rates (200 and 300 kg N ha-1). Maize yield, soil properties, and N-cycling functional groups (amoA-AOA, amoA-AOB, nirK, nirS, and nosZ) were analyzed. Results showed that tillage and its interaction with N significantly influenced crop yield, soil fertility, and microbial community composition, whereas N rate alone had minimal effects. Subsoil tillage with 200 kg N ha-1 (T4N2) increased maize yield and biomass by 13.7 % and 13.2 %, respectively, compared with rotary tillage. No-tillage and subsoil tillage with moderate N input improved soil water content (15-20 %), total N (10-12 %), available P (18-20 %), SOC (12-15 %), and the C:N ratio (8-10 %) relative to rotary tillage. These practices enriched beneficial nitrifiers (Nitrosospira) and denitrifiers (Sinorhizobium, Thauera, Pseudomonas), which were positively correlated with nutrient availability and yield. Structural equation modeling revealed that tillage improved soil C and N status, which stimulated denitrifier diversity and indirectly enhanced maize productivity. Overall, conservation tillage with moderate N input under film mulching offers a practical strategy to improve yield, increase N use efficiency, and foster beneficial microbial communities in semi-arid drylands.

Corrosion is a major cause of economic failures and environmental concerns in industries. This study evaluated the corrosion rates of mild steel (MS), stainless steel (SS), aluminium (Al), and copper (Cu) in sodium silicate using potentiodynamic polarisation (PDP) and electrochemical impedance spectroscopy (EIS) at temperatures of 25, 50, and 70 degrees C. Corroded metal samples at 25 degrees C were characterised using X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS). The PDP results revealed that SS had the lowest corrosion rates (CR) of 0.0002 mm/y at 25 degrees C and 0.0085 mm/y at 70 degrees C, while also maintaining a moderate CR of 0.0018 mm/y at 50 degrees C, indicating superior corrosion resistance. MS recorded the lowest CR (0.0007 mm/y) at 50 degrees C. Most corroded materials in NaSiO3 at 25, 50 and 70 degrees C was Al with CR of 0.1245, 0.138 and 3.2817 mm/y. Corrosion rates and current densities (icorr) for all metals increased with temperature. The EIS analysis supported the PDP findings. XRD identified FeMnSiO4 as dominant phase in MS, phases of FeSiO3 and FeSi4O6 in SS, Al2O3 and aluminium complexations discovered on Al while Cu8H6O27Si8 was corrosion product on Cu. SEM analysis showed micrographs in SS having denser and more compact corrosion layer than that of MS, dimple-like spots were discovered on micrographs of Al while Cu surface was almost unaffected. In conclusion, stainless steel is suitable for both low and high-temperature applications in sodium silicate environments though mild steel is more appropriate for medium temperatures application. La corrosion est une cause majeure d'& eacute;checs & eacute;conomiques et de pr & eacute;occupations environnementales dans les industries. Cette & eacute;tude a & eacute;valu & eacute; les taux de corrosion de l'acier doux (MS), de l'acier inoxydable (SS), de l'aluminium (Al) et du cuivre (Cu) dans le silicate de sodium en utilisant la polarisation potentiodynamique (PDP) et la spectroscopie d'imp & eacute;dance & eacute;lectrochimique (EIS) & agrave; des temp & eacute;ratures de 25, 50 et 70 degrees C. On a caract & eacute;ris & eacute; les & eacute;chantillons m & eacute;talliques corrod & eacute;s & agrave; 25 degrees C & agrave; l'aide de la diffraction des rayons X (DRX), de la microscopie & eacute;lectronique & agrave; balayage (MEB) et de la spectroscopie & agrave; dispersion d'& eacute;nergie (EDS). Les r & eacute;sultats de la PDP ont r & eacute;v & eacute;l & eacute; que SS pr & eacute;sentait les plus faibles taux de corrosion (CR), soit 0.0002 mm/an & agrave; 25 degrees C et 0.0085 mm/an & agrave; 70 degrees C, tout en maintenant & eacute;galement un CR mod & eacute;r & eacute; de 0.0018 mm/an & agrave; 50 degrees C, indiquant une r & eacute;sistance & agrave; la corrosion sup & eacute;rieure. Le MS a enregistr & eacute; le plus faible CR (0.0007 mm/an) & agrave; 50 degrees C. La plupart des mat & eacute;riaux corrod & eacute;s dans le NaSiO3 & agrave; 25, 50 et 70 degrees C & eacute;taient de l'Al avec un CR de 0.1245, 0.138 et 3.2817 mm/an. Les taux de corrosion et les densit & eacute;s de courant (icorr) pour tous les m & eacute;taux augmentaient avec la temp & eacute;rature. L'analyse d'EIS a confirm & eacute; les r & eacute;sultats de la PDP. La DRX a identifi & eacute; FeMnSiO4 comme phase dominante dans le MS, des phases de FeSiO3 et de FeSi4O6 dans le SS, Al2O3 et des complexations d'aluminium ont & eacute;t & eacute; d & eacute;couvertes sur l'Al tandis que Cu8H6O27Si8 & eacute;tait un produit de corrosion sur le Cu. L'analyse de MEB a montr & eacute; que les micrographies dans le SS pr & eacute;sentaient une couche de corrosion plus dense et plus compacte que celle de MS; on a d & eacute;couvert des taches en forme de fossettes sur les micrographies d'Al tandis que la surface de cuivre n'& eacute;tait presque pas affect & eacute;e. En conclusion, l'acier inoxydable convient aux applications & agrave; basse et & agrave; haute temp & eacute;rature dans des environnements de silicate de sodium, bien que l'acier doux convienne mieux pour les applications & agrave; temp & eacute;ratures moyennes.