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Climate change, primarily driven by CO2 emissions from energy and non-energy sectors, necessitates effective mitigation strategies. This study develops a stochastic diffusive model to capture the complex dynamics of CO2 concentration, human population growth, and energy production. The objectives are to enhance the predictive accuracy of existing models by incorporating diffusion effects and stochastic variability, offering insights for sustainable environmental policies. A novel numerical scheme, an extension of the Euler-Maruyama algorithm, is proposed to solve stochastic time-dependent partial differential equations governing the model. The scheme's consistency and stability are rigorously analyzed in the mean square sense. Findings reveal that increasing emission rate coefficients in energy and non-energy sectors exacerbates CO2 levels, emphasizing the need for stringent controls. The proposed scheme demonstrates superior accuracy to the non-standard finite difference method, establishing its efficacy in modeling complex environmental processes. This research contributes a robust computational tool to improve existing predictive models, aiding decision-making for long-term ecological sustainability. By addressing uncertainties in the environmental process, the work advances the understanding of interactions between population growth, energy production, and CO2 emissions, offering a significant improvement over the traditional modeling approach. The novelty lies in integrating stochastic dynamics with diffusion to better inform CO2reduction strategies. Doi: 10.28991/ESJ-2025-09-01-012 Full Text: PDF

This work presents a novel perspective towards generating automated multiple-choice questions (MCQs)-a task fundamentally different due to the highly dynamic nature of computer science education, which spans several sub-domains. Taking advantage of Conditional Generative Adversarial Networks (cGANs), our model provides a versatile approach to addressing the need for diversity and context in relevant MCQ generation across proficiency levels, topic areas. Resulting MCQs inspire implementations within a variety of educational environments - from classrooms, to online courses, and finally exams - equipping teachers with an instrument that could be easily adapted based on the specific needs o students. The model is trained on a carefully constructed dataset that includes material from more than 20 subareas in computer science, consisting of materials such as textbooks, online encyclopedias and Q&A websites. Through rigorous evaluation using comprehensive performance metrics, including Question Relevance Score (QRS), Diversity Index (DI), and Difficulty Alignment Accuracy (DAA), we demonstrate the efficacy and robustness of our framework in generating high-quality MCQs. Moreover, we address ethical considerations inherent in AI-driven educational assessment, ensuring fairness, transparency, and accountability in the MCQ generation process. The cGAN architecture facilitates the generation of contextually relevant MCQs across various proficiency levels and subject domains, enhancing the educational assessment process. The comprehensive dataset developed for this study encompasses diverse computer science topics curated from authoritative textbooks, online resources, question banks, and instructor-generated content. Additionally, a user-friendly QT application has been developed, enabling seamless integration of the cGAN model into educational environments. Through rigorous evaluation and ethical considerations, this framework demonstrates its efficacy, ensuring fairness, transparency, and accountability in MCQ generation. This interdisciplinary work represents a significant advancement in computer science education, providing educators with a powerful tool to enhance student engagement and learning outcomes.

Distributed DevOps is a software development methodology that aims to integrate the work of development and operations teams without being bound by geographical constraints. This methodology excels in enhancing collaboration and speeding software development. However, it does suffer from a lack of security, transparency, and traceability, which can result in project delays, a lack of trust between stakeholders, and even project failure. This paper addresses these issues of Distributed DevOps by implementing Blockchain technology. In this paper, we propose a novel framework that leverages blockchain technology to address the challenges faced by Distributed DevOps. Through performance analysis, we demonstrate the effectiveness of our framework in a real-world scenario, highlighting its ability to improve transparency, traceability, and the security of the DevOps pipeline. Our findings underscore the potential of blockchain-empowered solutions in revolutionizing DevOps practices. Furthermore, this research offers a practical framework for organizations seeking to optimize their development processes by integrating blockchain technology.

Abstract Cadmium (Cd) contamination in the environment is widespread, making it crucial to reduce Cd accumulation in cereal crops like wheat. However, strategies that not only mitigate Cd pollution but also address other environmental challenges, such as invasive species management, remain unclear. This study introduces an innovative approach combining molybdenum nanoparticles (Mo NPs, 1 µM) and biochar biofilters derived from the invasive plant Mikania micrantha (IPMM), targeting the biochemical and molecular responses of wheat under Cd stress (100 µM). Our findings showed that this novel combination significantly improved wheat physiological characteristics, growth, root architecture, elemental profile, osmoregulation, carotenoid, chlorophyll, gas exchange, and photosynthetic efficiency. Remarkably, simultaneous supply of IPMM biochar biofilters and Mo NPs substantially modulated the Cd translocation, reducing its accumulation in root (30.54%) and shoot (53.59%). Additionally, this strategy not only preserved mesophyll cell structures and the membrane integrity, but also strengthened and activated the oxidative defense systems through the regulation of genetic expressions. This synergistic approach advances the Cd alleviating techniques and offers a sustainable solution for utilizing invasive plants as a potential resource. By addressing both heavy metal pollution and ecological challenges, it provides a promising solution for safer crop production in Cd-contaminated environments. Graphical Abstract

This paper focus on the application of Physics Informed Neural Network (PINN) for extracting parameters of photovoltaic (PV), wind, and energy storage equipment models. Accurately extracting the parameters of these models is essential for effectively controlling and optimizing the overall stability of Chongqing power system (CPS). Despite numerous algorithms proposed to tackle this issue, accurately and reliably extracting the parameters of these remains a significant challenge. This paper proposed an improved PINN, named Uniform Physics Informed Neural Network (UPINN), with Proximal Policy Optimization (PPO) based reinforcement learning, for extortion of parameters of these models. The PINN difficulty is overcome in UPINN by configuring four strategies: feedback operator, GRU gating mechanisms, transfer operator with historic population, and modification factor with PPO aided reinforcement learning. UPINN models are trained iteratively to maximize parameters and reduce RMSE. UPINN accurately extracts parameters and describes the behavior of PV, wind, and energy storage equipment models as it converges towards optimal solutions through parameter adjustments and RMSE evaluations. The UPINN was implemented for real-time voltage stability monitoring of CPS. The results show that UPINN performs better than other neural network models in respect of accuracy and stability, demonstrating the effectiveness of improved strategies. Moreover, its emphasis the importance of computed and estimated indices obtained through UPINN for predicting voltage collapse occurrences within the system.

Cardiac strangulation from leads of an epicardial pacemaker is a rarely reported life-threatening complication. We report the case of a 72-year-old female with history of supraventricular tachycardia status post sino-atrial node ablation with epicardial pacemaker placement who presented to the outpatient setting with shortness of breath. Heart catheterization was performed which showed elevated right and left heart pressures. Compression involving the mid left anterior descending artery and left circumflex artery was noted from an epicardial lead on coronary angiography consistent with cardiac strangulation. The patient was then referred to cardiothoracic surgery for epicardial pacemaker lead removal. The literature has only reported one other survival case of cardiac strangulation in an adult.

Amid energy crisis, population growth, expanding energy demand, the utilities face limited supply of hydrocarbons due to depletion of available reserves. The future of energy supply quest for sustainable polygeneration system by integrating solar thermal, photovoltaic, wind and geothermal energy. The system is designed to produce multiple energy vectors including electricity, space heating & cooling, hydrogen, oxygen, pure water, domestic hot water, and electric vehicle charging. The key innovation lies in optimal integration of energy conversion devices with a multi-tiered backup system featuring thermal, electric, and pressurized hydrogen storage which provide uninterrupted operation during intermittent weathers. The system is modeled and simulated using TRNSYS® and optimized via GenOpt by applying Hooke-Jeeve's algorithm. The results of optimal system having bore hole depth 100 m, collector area 560 m2, tank volume 15 m3, wind turbine hub height 46 m, PV module area 1.5 m2, electrolyzer electrode area 0.25 m2, fuel cell electrode area 0.01 m2 show that the solar thermal collector achieves a peak efficiency (η) of 74% and a solar fraction (f) of 0.78, delivering 8020 MJ of heat gain annually. The thermally stratified storage tank provides 7105 MJ of heat energy by efficiently utilizing stored energy. Hydrogen production via electrolyzer reaches 54 m³ per day and 12,696 m³ annually, contributing to green energy storage. The wind energy system generates 1000 kWh at 41% efficiency. This study demonstrates the feasibility and performance of a polygeneration system, highlighting the potential of integrated renewable systems to meet diversified energy needs with enhanced storage solutions.

Cathodic cage plasma nitriding (CCPN) is a proficient and cost-effective technique for surface modification of metallic samples that has been in use for the last two decades. The effectiveness of CCPN depends upon different controlled parameters. The main objective of the current study was to investigate the effect of temperature on CCPN performance. Copper (Cu) samples were nitrided at various temperatures (100–400 °C) for a fixed time of 4 h. The treated samples were investigated using a micro-hardness tester, x-ray diffraction, scanning electron microscopy, energy-dispersive x-ray spectroscopy, ball-on-disc wear tester, and potentiodynamic polarization. An improvement in hardness, wear resistance, and corrosion resistance has been reported with an increase in temperature. The treated samples possessed aluminum nitride (AlN), copper(I) nitride (Cu3N), copper(I) azide (CuN3), copper(II) azide (CuN6), and AlCu4 phases with intensity increasing with temperature. The current study clarified the reactivity of the CCPN system on treated samples in a broad manner. Untreated samples have shown abrasive wear at low temperatures, whereas adhesive wear is the predominant mechanism at high temperatures. At high temperatures, a low friction coefficient has been achieved due to smoother surfaces. Nitrided samples have shown an overall increased corrosion resistance with an increase in temperature.

Molybdenum (Mo) deficiency is a global problem in acidic soils, limiting plant growth, development, and nutrient availability. To address this, we carried out a field study with two treatments, i.e., Mo applied (+Mo) and without Mo (−Mo) treatment to explore the effects of Mo application on crop growth and development, microbial diversity, and metabolite variations in maize and soybean cropping systems. Our results indicated that the nutrient availability (N, P, K) was higher under Mo supply leading to improved biological yield and nutrient uptake efficiency in both crops. Microbial community analysis revealed that Proteobacteria and Acidobacteria were the dominant phyla in Mo treated (+Mo) soils for both maize and soybean. Both these phyla accounted together 39.43% and 57.74% in −Mo and +Mo, respectively, in soybean rhizosphere soil, while they accounted for 44.51% and 46.64% in maize rhizosphere soil. This indicates more variations among the treatments in soybean soil compared to maize soil. At a lower taxonomic level, the diverse responses of the genera indicated the specific bacterial community adaptations to fertilization. Candidatus Koribacter and Kaistobacter were commonly significantly higher in both crops under Mo-applied conditions in both cropping systems. These taxa, sharing similar functions, could serve as potential markers for nutrient availability and soil fertility. Metabolite profiling revealed 8 and 10 significantly differential metabolites in maize and soybean, respectively, under +Mo treatment, highlighting the critical role of Mo in metabolite variation. Overall, these findings emphasize the importance of Mo in shaping soil microbial diversity by altering metabolite composition, which in turn may enhance the nutrient availability, nutrient uptake, and plant performance.

The agricultural sector is vulnerable to climate change (CC). Various climate-related extremes, such as droughts, heat waves, unpredictable rainfall patterns, storms, floods, and an increase in insect pests, have adversely affected farmers' livelihoods. Climate forecasts indicate a significant increase in temperatures and more inconsistent, extreme rainfall, obfuscating the prediction of extreme weather events. The IPCC projects that by the end of the 21st century, temperatures in Thailand will rise by 0.95 ​°C–3.23 ​°C. This study aims to review the current understanding of CC's impact on the agricultural sector and evaluate the adaptation measures being employed in Thailand. Farmers have begun adopting adaptive measures such as alternative farming techniques, crop diversification, and water management strategies to mitigate climate risks and maintain productivity. However, limited resources, knowledge gaps, and insufficient government support hinder widespread adoption. Targeted interventions and policy support are essential for enhancing adaptive capacity and resilience. The impacts on crop water requirements and livelihoods reveal vulnerabilities due to extreme weather events. Rain-fed agriculture faces significant yield declines and reduced crop water productivity, exacerbating economic impacts on rural households and leading to food insecurity and financial instability. Effective adaptation requires enhanced water management, sustainable practices, and improved institutional support. Community engagement and participatory approaches are vital for building resilience against CC impacts. Comprehensive, region-specific, and long-term studies are crucial for developing robust adaptive strategies.

This paper presents a novel way to analyze unsteady flow and heat transfer in Magnetohydrodynamic Tangent-Hyperbolic Fluid (MHD-THF) flow over a stretching sheet that uses Recurrent Neural Networks (RNNs) optimized with the Levenberg-Marquardt Algorithm (LMA). The controlling PDEs are similarly converted into nonlinear ordinary differential equations (ODEs), and reference data is generated using the Adam-Bashforth numerical solver. The reference dataset, divided into 70 % training, 15 % testing, and 15 % validation sets, which was separated into three distinct cases for each scenario, was trained, tested, and validated using MATLAB's RNN-LMA technique. The absolute error for each scenario of model instance is approximately 10−06, 10−05, 10−07, 10−05, and 10−08. The numerical solutions for the nonlinear fluid dynamics system were considered to reduce mean square error. The stochastic technique's reliability and competency are demonstrated using comparison configurations of MSE, error histograms, correlation, and regression. A graphical assessment of the model shows that power-law index, unsteadiness, Hartmann number, and Weissenberg number decrease velocity profiles. Meanwhile, the temperature profile reveals an increase with the Eckert number and unsteadiness, whereas the Prandtl number has the reverse impact. This study illustrates the potential of RNN-LMA techniques to handle complicated fluid dynamics problems with more accuracy and efficiency.

This study aims to d an efficient computational scheme for solving partial differential equations involving fuzzy parameters in boundary layer flow. Specifically, we propose a modified exponential integrator method to handle the challenges of variable viscosity and thermal conductivity in flow over flat and oscillatory sheets. This work aims to enhance accuracy and stability in simulating fluid flows under uncertainty. The proposed explicit scheme operates on two-time levels with compact spatial discretization. The stability and convergence of the proposed scheme are also provided for scalar and system of partial differential equations. Results show that the scheme provides better accuracy than existing first- and second-order methods, especially for specific time steps. Additionally, the method effectively handles fuzzy Hartmann number, Eckert number, and reaction rate parameters, reflecting uncertainties in material properties. The proposed method significantly improves the precision of fluid simulations with complex parameters.

Innovation in the Information and Communication Technology (ICT) sector is critical for organizational growth and societal sustainability. However, the innovation capabilities of developing countries, particularly in the ICT sector, remain underexplored. This study is aimed at assessing the perceptions of senior leadership within Pakistan’s ICT sector to identify the factors contributing to the limited scope of innovation. Through qualitative interviews with senior leaders from various ICT organizations, this research explores their views on the definition, types, and driving factors of innovation. Most interview participants reported that the major type of innovation practiced at the ICT sector of Pakistan is “product,” the level is “partial replication,” and the major driving source is “factors external to the organization.” Based on these insights, we developed an innovation readiness framework (IRF) to help organizations enhance their innovation capacity. IRF is expected to provide actionable strategies for organizations to assess their current innovation practices, identify gaps, and adopt a structured approach to enhance both product development and operational processes. By addressing sector-specific challenges such as limited resources and regulatory barriers, the IRF is aimed at empowering organizations to move from replication to more original, impactful innovations. Hence, implementing this framework is expected to improve the sector’s competitiveness, drive sustainable growth, and contribute meaningfully to societal advancement by aligning with broader development goals.

Enhancement in the visible light absorption and efficient interfacial charge transfer is crucial for optimizing photocatalytic efficiency in the degradation of pollutants such as methyl orange (MO) and formaldehyde. This study focuses on the properties of a TiO2/C/g-C3N4 hybrid efficient photocatalyst, which is developed using an air calcination method to deposit graphitic nitride (g-C3N4) onto a carbon-modified TiO2 surface. The characterization techniques, including high-resolution transmission electron Microscopy (HRTEM), X-ray diffraction (XRD), Raman spectroscopy, thermogravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS), were used to provide a comprehensive understanding of the material’s structural, morphological, thermal, and chemical properties. This hybrid catalyst is specifically engineered for the efficient decomposition of methyl orange (MO) and formaldehyde, demonstrating a significant increase in photocatalytic activity. The TiO2/C/g-C3N4 photocatalyst also exhibits an enhanced specific surface area of 181.2 m2/g, which facilitates increased physical adsorption and photo-catalytic active sites. Experimental results confirm that this catalyst effectively adsorbs MO physically even in the dark without degradation. Combining physical and photo-catalytic functions, this catalyst degrades 94 % of MO within 180 min with the initial concentration 0.2 mol/L of MO, and achieves almost 100 % decolorization of MO under visible light irradiation. Notably, the catalyst retains its high activity after 4 cycles of MO degradation, underscoring its durability and consistent performance. Additionally, the hybrid catalyst features a staggered type-II energy level configuration, which effectively enhances charge separation and boosts photocatalytic efficacy. The incorporation of an ultrafine carbon layer further augments electron mobility towards the surface, crucial for effective catalytic reactions. This study paves the way for future development of highly efficient photocatalytic materials for environmental purification.

Land use and land cover (LULC) changes are significantly impacting the natural environment. Human activities and population growth are negatively impacting the natural environment. This negative impact directly relates to climate change, sustainable agriculture, inflation, and food security at local and global levels. Remote sensing and GIS tools can provide valuable information about change detection. This study examines the correlation between population growth rate and LULC dynamics in three districts of South Punjab, Pakistan—Multan, Bahawalpur, and Dera Ghazi Khan—over a 30-year period from 2003 to 2033. Landsat 7, Landsat 8, and Sentinel-2 satellite imagery within the Google Earth Engine (GEE) cloud platform was utilized to create 2003, 2013, and 2023 LULC maps via supervised classification with a random forest (RF) classifier, which is a subset of artificial intelligence (AI). This study achieved over 90% overall accuracy and a kappa value of 0.9 for the classified LULC maps. LULC was classified into built-up, vegetation, water, and barren classes in Multan and Bahawalpur, with an additional “rock” class included for Dera Ghazi Khan due to its unique topography. LULC maps (2003, 2013, and 2023) were prepared and validated using Google Earth Engine. Future predictions for 2033 were generated using the MOLUSCE model in QGIS. The results for Multan indicated substantial urban expansion as built-up areas increased from 8.36% in 2003 to 25.56% in 2033, with vegetation and barren areas displaying decreasing trends from 82.96% to 70% and 7.95% to 3.5%, respectively. Moreover, areas containing water fluctuated and ultimately changed from 0.73% in 2003 to 0.9% in 2033. In Bahawalpur, built-up areas grew from 1.33% in 2003 to 5.80% in 2033, while barren areas decreased from 79.13% to 74.31%. Dera Ghazi Khan expressed significant increases in built-up and vegetation areas from 2003 to 2033 as 2.29% to 12.21% and 22.53% to 44.72%, respectively, alongside reductions in barren and rock areas from 32.82% to 10.83% and 41.23% to 31.2%, respectively. Population projections using a compound growth model for each district emphasize the demographic impact on LULC changes. These results and findings focus on the need for policies to manage unplanned urban sprawl and focus on environmentally sustainable practices. This study provides critical awareness to policy makers and urban planners aiming to balance urban growth with environmental sustainability.

Molybdenum (Mo) deficiency is a global problem in acidic soils, limiting plant growth, development, and nutrient availability. To address this, we carried out a field study with two treatments, i.e., Mo applied (+Mo) and without Mo (−Mo) treatment to explore the effects of Mo application on crop growth and development, microbial diversity, and metabolite variations in maize and soybean cropping systems. Our results indicated that the nutrient availability (N, P, K) was higher under Mo supply leading to improved biological yield and nutrient uptake efficiency in both crops. Microbial community analysis revealed that Proteobacteria and Acidobacteria were the dominant phyla in Mo treated (+Mo) soils for both maize and soybean. Both these phyla accounted together 39.43% and 57.74% in −Mo and +Mo, respectively, in soybean rhizosphere soil, while they accounted for 44.51% and 46.64% in maize rhizosphere soil. This indicates more variations among the treatments in soybean soil compared to maize soil. At a lower taxonomic level, the diverse responses of the genera indicated the specific bacterial community adaptations to fertilization. Candidatus Koribacter and Kaistobacter were commonly significantly higher in both crops under Mo-applied conditions in both cropping systems. These taxa, sharing similar functions, could serve as potential markers for nutrient availability and soil fertility. Metabolite profiling revealed 8 and 10 significantly differential metabolites in maize and soybean, respectively, under +Mo treatment, highlighting the critical role of Mo in metabolite variation. Overall, these findings emphasize the importance of Mo in shaping soil microbial diversity by altering metabolite composition, which in turn may enhance the nutrient availability, nutrient uptake, and plant performance. [ABSTRACT FROM AUTHOR]

Cadmium (Cd) contamination in the environment is widespread, making it crucial to reduce Cd accumulation in cereal crops like wheat. However, strategies that not only mitigate Cd pollution but also address other environmental challenges, such as invasive species management, remain unclear. This study introduces an innovative approach combining molybdenum nanoparticles (Mo NPs, 1 µM) and biochar biofilters derived from the invasive plant Mikania micrantha (IPMM), targeting the biochemical and molecular responses of wheat under Cd stress (100 µM). Our findings showed that this novel combination significantly improved wheat physiological characteristics, growth, root architecture, elemental profile, osmoregulation, carotenoid, chlorophyll, gas exchange, and photosynthetic efficiency. Remarkably, simultaneous supply of IPMM biochar biofilters and Mo NPs substantially modulated the Cd translocation, reducing its accumulation in root (30.54%) and shoot (53.59%). Additionally, this strategy not only preserved mesophyll cell structures and the membrane integrity, but also strengthened and activated the oxidative defense systems through the regulation of genetic expressions. This synergistic approach advances the Cd alleviating techniques and offers a sustainable solution for utilizing invasive plants as a potential resource. By addressing both heavy metal pollution and ecological challenges, it provides a promising solution for safer crop production in Cd-contaminated environments. Highlights: IPMM biochar biofilter along with Mo NPs supply improved the membrane integrity and osmoregulation under Cd stress. IPMM biochar biofilter and Mo NPs played a protective role in oxidative defense system through regulating the genetic expressions under Cd toxicity. IPMM biochar biofilter together with Mo NPs improved the elemental profile and minimized the nutrient reductions in roots and shoots. IPMM biochar biofilter and Mo NPs preserved the ultrastructure of leaf and root architecture. IPMM biochar biofilter together with Mo NPs could be use as safeguard under HMs toxic conditions. [ABSTRACT FROM AUTHOR]

An ideal microwave absorption material involves multilevel precise regulation and construction at multiple scales, which remains a great challenge. For the first time, we develop a host–guest self-assembling strategy via the entrapment of fullerene C60 molecule guest in a zeolitic imidazolate framework-67 (ZIF-67) host to design the hierarchical structure for a high-performance microwave absorber covering the molecular scale, nanoscale, and microscale synergistic effects. Typically, the two-dimensional orientation growth of microscale ZIF-67 precursors in solution is achieved by introducing C60 molecules. After the accurate pyrolysis process, Co nanoparticles derived from C60@ZIF-67 are embedded into ultrathin carbon flake (CF) substrates, favoring uniformity, size diminishment, and surface stability. These as-synthesized uniformly dispersed C60/Co/CF composites possess advantages of dual dielectric and magnetic loss functions, exhibiting the great microwave absorption properties with a minimum reflection loss of −58.03 dB and the effective absorption bandwidth of 5.94 GHz. This proposed host–guest self-assembling strategy has great potential for the synthesis of other metal–organic framework materials in the field of microwave absorption. [ABSTRACT FROM AUTHOR]

Rectal cancer's prevalence increases with an aging population, disproportionately affecting the elderly. The suitability of surgical interventions for this demographic is contentious due to underrepresentation during surgery. This study examines the practicality of utilizing Da Vinci surgery for rectal cancer patients who are 70 years and older. Information was gathered from PubMed, Embase, Scopus and the Cochrane Library, with a focus on English-language publications. Statistical analysis was performed using RevMan 5.4, presenting outcomes for categorical variables in risk ratios. Out of 890 patients across 5 studies, 240 were categorized as elderly, while 650 fell into the younger age group. Notable distinctions were noted in harvested lymph nodes, BMI, and postoperative outcomes, whereas factors like the length of hospital stay, Clavien–Dindo classification, and radial resection margin did not display significance. Although age increases postoperative risk, evidence emphasizes frailty, not age alone, as the primary determining factor. [ABSTRACT FROM AUTHOR]

Innovation in the Information and Communication Technology (ICT) sector is critical for organizational growth and societal sustainability. However, the innovation capabilities of developing countries, particularly in the ICT sector, remain underexplored. This study is aimed at assessing the perceptions of senior leadership within Pakistan's ICT sector to identify the factors contributing to the limited scope of innovation. Through qualitative interviews with senior leaders from various ICT organizations, this research explores their views on the definition, types, and driving factors of innovation. Most interview participants reported that the major type of innovation practiced at the ICT sector of Pakistan is "product," the level is "partial replication," and the major driving source is "factors external to the organization." Based on these insights, we developed an innovation readiness framework (IRF) to help organizations enhance their innovation capacity. IRF is expected to provide actionable strategies for organizations to assess their current innovation practices, identify gaps, and adopt a structured approach to enhance both product development and operational processes. By addressing sector‐specific challenges such as limited resources and regulatory barriers, the IRF is aimed at empowering organizations to move from replication to more original, impactful innovations. Hence, implementing this framework is expected to improve the sector's competitiveness, drive sustainable growth, and contribute meaningfully to societal advancement by aligning with broader development goals. [ABSTRACT FROM AUTHOR]

The emergence of unisexual flower is an important event during plant evolution. The molecular mechanism underlying the formation of unisexual flowers remains unclear in dioecious spinach. In this study, we identified the spinach MALE STERILITY1 gene, SpMS1 , which serves as a masculine factor to regulate male fertility and sex reversion. Silencing SpMS1 led to stamen sterility in male flowers and the development of masculine traits in female flowers. Overexpression of SpMS1 in wild-type Arabidopsis resulted in sterile stamens and irregular pollen exine. Notably, ectopic expression of SpMS1 in Arabidopsis ms1 mutants restored pollen viability and flower fertility. Furthermore, our findings demonstrate that SpMS1 interacts with MADS-box transcription factor SpAP1 to regulate unisexual flower development. Thus, SpMS1 exhibits a conserved function in pollen fertility akin to bisexual flowers, while also acting as a key regulator of unisexual flower development in spinach. This study sheds light on the mechanism of sex differentiation in dioecious plants and also provides valuable insights for manipulating male sterility in plant breeding programs. [ABSTRACT FROM AUTHOR]

Perovskite materials' exceptional physical properties and adjustable crystal forms have sparked the curiosity of many researchers in solid-state chemistry and materials science. In order to fully understand the complex properties of the well-known CaJO3 (J = Mn, Ru) perovskite compounds, this study employs an advanced theoretical first-principle method. The research reveals fascinating insights into structural, electrical, magnetic, optical, and elastic properties. The stability and distortion of perovskites' crystal structures are measured by the Goldschmidt's tolerance factor (τ), which is 0.98 for CaMnO3 and 0.94 for CaRuO3. This clearly indicates that CaJO3 (J = Mn, Ru) are stable perovskites. We specifically identify the metallic character of CaRuO3 and the half-metallic behavior of CaMnO3, both exhibiting distinct electronic band structures with applications in optoelectronics and spintronics. An integer value of magnetic moments of selected compounds results in ferromagnetic behavior. Our elastic analysis of these compounds also reveals ductile and anisotropic elastic characteristics, which provide insight into their mechanical stability and adaptability. These compounds indicate ionic bonding, which makes them more appealing for use in particular applications. To summarize, CaJO3 (J = Mn, Ru) perovskites are materials that show great promise and have wide applications in modern electronic and memory systems. They are also an interesting focus area in the constantly changing field of materials research. [ABSTRACT FROM AUTHOR]

The highly perishable nature of Rubus berries, particularly their susceptibility to water loss and earlier senescence, significantly limits their shelf life. In this study, we investigated the mechanistic role of modified atmosphere packaging (MAP) on the physiochemical quality, phenolic metabolism, and antioxidant potential of blackberries and raspberries during cold storage (2 ± 1 °C) for 12 and 10 days, respectively. Modified atmosphere (MA)-packed Rubus berries exhibited higher total phenolics accompanied by higher activities of shikimate dehydrogenase, and phenylalanine ammonia-lyase. Furthermore, MA-packed Rubus berries demonstrated lower hydrogen peroxide by maintaining higher catalase activity and delayed lipid peroxidation during the entire period of cold storage. Relatively higher levels of glutathione and ascorbic acid as well as the activities of enzymes involved in the ascorbate-glutathione cycle in MA-packed Rubus berries were also observed. Conversely, MAP reduced the respiration rate and weight loss while maintaining higher postharvest quality attributes in raspberries and blackberries than control fruit. In conclusion, MAP is an effective method for extending the cold storage life and maintaining the quality of Rubus berries. [ABSTRACT FROM AUTHOR]

This study examines the flow behavior as well as the cuttings transport of non-Newtonian drilling fluid in the geometry of an eccentric annulus, accounting for what impacts drill pipe rotation might have on fluid velocity, as well as annular eccentricity on axial and tangential distributions of velocity. A two-phase Eulerian–Eulerian model was developed by using computational fluid dynamics to simulate drilling fluid flow and cuttings transport. The kinetic theory of granular flow was used to study the dynamics and interactions of cuttings transport. Non-Newtonian fluid properties were modeled using power law and Bingham plastic formulations. The simulation results demonstrated a marked improvement in efficiency, as much as 45%, in transport by increasing the fluid inlet velocity from 0.54 m/s to 2.76 m/s, reducing the amount of particle accumulation and changing axial and tangential velocity profiles dramatically, particularly at narrow annular gaps. At a 300 rpm rotation, the drill pipe brought on a spiral flow pattern, which penetrated tangential velocities in the narrow gap that had increased transport efficiency to almost 30% more. Shear-thinning behavior characterizes fluid of which the viscosity, at nearly 50% that of the central core low-shear regions, was closer to the wall high-shear regions. Fluid velocity and drill pipe rotation play a crucial role in optimizing cuttings transport. Higher fluid velocities with controlled drill pipe rotation enhance cuttings removal and prevent particle build-up, thereby giving very useful guidance on how to clean the wellbore efficiently in drilling operations. [ABSTRACT FROM AUTHOR]

The effects of preharvest methyl jasmonate (MeJA) spray application on the physicochemical quality, metabolism of phenolics, and cell wall components in raspberries were investigated during a 10-day cold storage period. MeJA spray reduced firmness loss, decay incidence, and weight loss, while maintained higher levels of soluble solids content, ascorbic acid, anthocyanins and flavonoids in raspberries. Furthermore, MeJA application resulted in increased total pectin and protopectin levels, as well as lowered water-soluble pectin, and activities of pectin methyl esterase, polygalacturonase and cellulase enzymes. Additionally, MeJA treatment upregulated the phenylpropanoid pathway, leading to higher endogenous phenolics and activities of phenylalanine-ammonia lyase and shikimate dehydrogenase. In conclusion, preharvest MeJA spray application could be adopted to enhance the storage potential of cold-stored raspberries for 10 days by maintaining higher firmness, assuring better physicochemical quality, and increasing phenolic metabolism, while reducing cell wall hydrolysis. • • Preharvest MeJA treatment improves physicochemical quality and storage life. • • MeJA treatment upregulates phenolic metabolism and antioxidant capacity. • • MeJA delays cell wall polysaccharides hydrolysis and activities of hydrolases. • • Preharvest MeJA has the potential to maintain postharvest quality of raspberries. [ABSTRACT FROM AUTHOR]

Environmental exposure to heavy metals, particularly lead (Pb) and nickel (Ni), is implicated in chronic metabolic diseases, including diabetes mellitus (DM). This cross-sectional study assessed the Pb and Ni levels in groundwater using ICP-OES and urine samples collected from 2688 participants using ICP-MS. We aimed to establish the associations between Pb and Ni exposure and risk factors for DM and metabolic disorders. Groundwater analysis revealed the elevated levels of total dissolved solids, electrical conductivity, hardness, turbidity, Ni, and Pb, exceeding the WHO guidelines. The mean concentration of Pb in groundwater samples of study area was 0.025 mg/L which was higher than the WHO permissible limit of 0.01 mg/L. Similarly the mean concentration of Ni in groundwater samples of study area was 0.038 mg/L which was also higher than the WHO permissible limit of 0.02 mg/L. In human study, participants, categorized into Pb-detected and Ni-detected groups, exhibited significantly higher Pb and Ni levels and non-exposed non-diabetic groups. Ni-detected diabetics showed elevated Ni levels compared to non-exposed non-diabetics. Similarly, Pb-detected diabetics showed elevated Pb levels compared to non-exposed non-diabetics. These findings suggest a potential contribution of Pb and Ni exposure to DM development. The study also identified associations between heavy metal exposure and disruptions in various biomarkers related to DM, lipid profile, inflammation, oxidative stress, liver function, and kidney function. Pb-detected diabetics demonstrated elevated levels of glycemic index biomarkers, including fasting blood glucose (P

The highly perishable nature of Rubus berries, particularly their susceptibility to water loss and earlier senescence, significantly limits their shelf life. In this study, we investigated the mechanistic role of modified atmosphere packaging (MAP) on the physiochemical quality, phenolic metabolism, and antioxidant potential of blackberries and raspberries during cold storage (2 ± 1 °C) for 12 and 10 days, respectively. Modified atmosphere (MA)-packed Rubus berries exhibited higher total phenolics accompanied by higher activities of shikimate dehydrogenase, and phenylalanine ammonia-lyase. Furthermore, MA-packed Rubus berries demonstrated lower hydrogen peroxide by maintaining higher catalase activity and delayed lipid peroxidation during the entire period of cold storage. Relatively higher levels of glutathione and ascorbic acid as well as the activities of enzymes involved in the ascorbate-glutathione cycle in MA-packed Rubus berries were also observed. Conversely, MAP reduced the respiration rate and weight loss while maintaining higher postharvest quality attributes in raspberries and blackberries than control fruit. In conclusion, MAP is an effective method for extending the cold storage life and maintaining the quality of Rubus berries.