Environmental Demands Research Articles

Agronomic characteristics, mineral nutrient content, antioxidant capacity, biochemical composition, and fatty acid profile of Iranian pistachio (Pistacia vera L.) cultivars

BackgroundPistachio (Pistacia vera L.) nuts are among the most popular nuts. The pistachio cultivars are tolerant to both drought and salinity, which is why they are extensively grown in the arid, saline, and hot regions of the Middle East, Mediterranean countries, and the United States.ResultsThis study evaluated the agronomic and chemical characteristics of 10 pistachio cultivars (‘Abbasiali’, ‘AhmadAghaei’, ‘Akbari’, ‘Chrook’, ‘Fandoghi’, ‘KalehGhoochi’, ‘Momtaz’, ‘Rezaei’, ‘Sefied’, and ‘Shahpasand’). Total phenolic content, antioxidant capacity, fruit mineral elements, soluble protein content, kernel-oil content, and fatty-acid composition were determined in 60 fruits (20 fruits per replication). Leaf mineral elements were determined in 450 leaves (150 leaves per replication). Significant differences were observed (p < 0.05) among the cultivars, with the coefficient of variation (CV) ranging from 1.03 (unsaturated fatty acids) to 115.16% (early nut splitting). Flower buds varied from 4 (‘AhmadAghaei’) to 7 (‘Momtaz’), and fruit per bunch ranged from 11 (‘Abbasiali’) to 21 (‘Momtaz’). Hull percentage ranged from 36.8 (‘KalehGhoochi’) to 43.1% (‘Chrook’), and nut percentage ranged from 56.3 (‘Chrook’) to 62.4% (‘KalehGhoochi’). Iron content in leaves ranged from 267 (‘Chrook’) to 367 mg/kg (‘Rezaei’), while iron in fruits ranged from 65.72 (‘Fandoghi’) to 81.90 mg/kg (‘Sefied’). Total phenolic content varied from 99.9 (‘Rezaei’) to 184.30 mg/g (‘Fandoghi’), and antioxidant activity ranged from 39.14 (‘Shahpasand’) to 82.89% (‘Sefied’). Oil content ranged from 49.26 (‘Rezaei’) to 67.72% (‘AhmadAghaei’), with oleic acid between 48.4 (‘Rezaei’) and 55.55% (‘KalehGhoochi’). Leaf phosphorus positively correlated with split nut percentage (r = 0.669) and negatively with blank nut percentage (r = -0.734). Fruit potassium strongly correlated with total phenolics (r = 0.917) and oleic acid (r = 0.654). Multiple regression analysis showed that blank nut percentage was negatively correlated with leaf zinc (β = -0.77) and positively with antioxidants (β = 0.77). Early nut splitting showed a negative correlation with antioxidants (β = -0.72). The first three principal components (PC1 = 22.48%, PC2 = 18.15%, PC3 = 15.82%) explained 56.45% of the total variation. Heat map analysis using Ward clustering revealed cultivar groupings based on traits like nutrient content and fatty acid composition.ConclusionsThe findings obtained in this study allow producers to select the most suitable cultivars for obtaining more efficient and high-quality products. Additionally, choosing cultivars based on environmental factors and market demands contributes to the development of more effective production strategies. The ultimate goal is to provide insights that guide the selection of pistachio cultivars optimized for both agricultural sustainability and market-specific requirements.

Advanced Path Planning for UAV Swarms in Smart City Disaster Scenarios Using Hybrid Metaheuristic Algorithms

In disaster-stricken areas, rapid restoration of communication infrastructure is critical to ensuring effective emergency response and recovery. Swarm UAVs, operating as mobile aerial base stations (MABS), offer a transformative solution for bridging connectivity gaps in environments where the traditional infrastructure has been compromised. This paper presents a novel hybrid path planning approach combining affinity propagation clustering (APC) with genetic algorithms (GA), aimed at maximizing coverage, and ensuring quality of service (QoS) compliance across diverse environmental conditions. Comprehensive simulations conducted in suburban, urban, dense urban, and high-rise urban environments demonstrated the efficacy of the APC-GA approach. The proposed method achieved up to 100% coverage in suburban settings with only eight unmanned aerial vehicle (UAV) swarms, and maintained superior performance in dense and high-rise urban environments, achieving 97% and 93% coverage, respectively, with 10 UAV swarms. The QoS compliance reached 98%, outperforming benchmarks such as GA (94%), PSO (90%), and ACO (88%). The solution exhibited significant stability, maintaining consistently high performance, highlighting its robustness under dynamic disaster scenarios. Mobility model analysis further underscores the adaptability of the proposed approach. The reference point group mobility (RPGM) model consistently achieved higher coverage rates (95%) than the random waypoint model (RWPM) (90%), thereby demonstrating the importance of group-based mobility patterns in enhancing UAV deployment efficiency. The findings reveal that the APC-GA adaptive clustering and path planning mechanisms effectively navigate propagation challenges, interference, and non-line-of-sight (NLOS) conditions, ensuring reliable connectivity in the most demanding environments. This research establishes the APC-GA hybrid as a scalable and QoS-compliant solution for UAV deployment in disaster response scenarios. By dynamically adapting to environmental complexities and user mobility patterns, it advances state-of-the-art emergency communication systems, offering a robust framework for real-world applications in disaster resilience and recovery.

Occupational exposures and coronary heart disease in the Hamburg City Health Study (HCHS) – a cross-sectional study

BackgroundCoronary heart disease (CHD) is the leading cause of death among adults in Germany. There is evidence that occupational exposure to particulate matter, noise, psychosocial stressors, shift work and high physical workload are associated with CHD. The aim of this study is to identify occupations that are associated with CHD and to elaborate on occupational exposures associated with CHD by using the job exposure matrix (JEM) BAuA-JEM ETB 2018 in a German study population.MethodsCross-sectional data from 8,070 participants, members of the first sub-cohort of the Hamburg City Health Study (HCHS), was used. To classify occupations, we rely on standard occupational titles (ISCO-08). The level of exposure is assigned to each job using a JEM. CHD is measured by self-reported diagnosis. Absolute and relative frequencies were calculated. Using logistic regression, the association of CHD and standard occupation titles via ISCO-08 and the association of CHD and occupational exposures via JEM were calculated and adjusted for potentially confounding covariates. Multiple imputations with chained equations (MICEs) were applied for missing values. Sensitivity analyses were performed.ResultsThe CHD prevalence in the study population was 4.6% (95% CI 4.2–5.1). Occupations associated with CHD were Physical and Engineering Science Technicians, Other Health Associate Professionals, General Office Clerks, Secretaries (general), Material Recording and Transport Clerks, Hairdressers, Beauticians and Related Workers, Electronics and Telecommunications Installers and Repairers, Other Craft and Related Workers, Car, Van and Motorcycle Drivers, Mobile Plant Operators and Domestic, Hotel and Office Cleaners and Helpers. Among occupational exposures retrieved from the JEM, Environmental Demands showed an association with CHD in the crude model but not after adjustment. The results remained robust in sensitivity analyses.ConclusionsThis study is the first to assess the association of a wide range of occupations and occupational exposures with CHD in a German study population. We found no association between occupational exposures and CHD after adjustment, but 11 occupations associated with CHD were identified. The results are limited by cross-sectional design, healthy worker effect (HWE), and small group sizes. Further studies with a larger sample and longitudinal design containing data on occupational history, occupational exposures and time of CHD diagnosis are needed.

Research on the Aerodynamics of Electric Vehicles

A major contributing factor to the growing severity of the global warming issue is greenhouse gas emissions, of which carbon dioxide from moving cars makes up a significant amount. Therefore, electric vehicles have become the focus of countries to replace conventional internal combustion engine vehicles due to their low emission characteristics. However, the weight of electric vehicles is increased by their reinforced structures and batteries, which reduces their range. In the short run, it is challenging to lower the weight of electric vehicles greatly because of the constraints of battery technology. Thus, lowering air resistance has emerged as a key strategy for extending the range of electric cars. This paper first analyses the reasons why electric vehicles need better aerodynamic design to increase range, including increased environmental demands, battery technology limitations and the high weight of electric vehicles. Next, the causes of air resistance are explored. Finally, the paper discusses ways to design active aerodynamic components to increase or decrease drag under different operating conditions. For example, a front air dam design can reduce the amount of airflow into the underbody, reducing lift and increasing grip. Variable air dams can optimize aerodynamics by automatically adjusting their position according to speed and driving conditions. In conclusion, the aim of this paper is to find and discover ways to optimize the aerodynamic performance of electric vehicles in order to solve the range problem. This paper provides an important theoretical and practical basis for aerodynamic optimization of electric vehicles

Flexibility in choosing decision policies in gathering discrete evidence over time.

The brain can remarkably adapt its decision-making process to suit the dynamic environment and diverse aims and demands. The brain's flexibility can be classified into three categories: flexibility in choosing solutions, decision policies, and actions. We employ two experiments to explore flexibility in decision policy: a visual object categorization task and an auditory object categorization task. Both tasks required participants to accumulate discrete evidence over time, with the only difference being the sensory state of the stimuli. We aim to investigate how the brain demonstrates flexibility in selecting decision policies in different sensory contexts when the solution and action remain the same. Our results indicate that the decision policy of the brain in integrating information is independent of inter-pulse interval across these two tasks. However, the decision policy based on how the brain ranks the first and second pulse of evidence changes flexibly. We show that the sequence of pulses does not affect the choice accuracy in the auditory mode. However, in the visual mode, the first pulse had the larger leverage on decisions. Our research underscores the importance of incorporating diverse contexts to improve our understanding of the brain's flexibility in real-world decision-making.

Research Agenda for Entrustable Professional Activities Among US Surgical Specialties.

The magnitude of advances in surgical care inspires awe consistent with the impact of these developments on patients' lives. With this comes greater knowledge, new practices, and novel technologies for integration into residency training, making the skillset required of today's residents quite different from those in the past. Competency-based medical education and learner-centered approaches offer innovative and studied methodologies for teaching, learning, and assessment to meet the demands of today's educational environment. The authors provide an overview of competency-based medical education, its association with Accreditation Council for Graduate Medical Education Milestones as a competency framework, a description and outline of the emerging execution of Entrustable Professional Activities in the surgical disciplines, and a research agenda focused on Entrustable Professional Activities for American Board of Surgery certified surgical specialties in the United States. The research agenda includes five domains of inquiry: entrustment and practice readiness; bias and environment; distinguishing features and certification; qualitative feedback; and patient outcomes, and builds upon prior work by ten Cate et al. by expanding upon their organizing framework to also include the element of time. Additionally, the authors provide questions and suggest data integration strategies that might foster a breadth of studies investigating the utility of Entrustable Professional Activities in surgical training. Collectively engaging in such a process of evaluation early in the process of competency-based reform will serve to optimize education, assessment, and ultimately patient care.

Dynamic coupling of qualitative–quantitative models for operation of water resources based on environmental criteria

Concerning issues include the distribution of scarce water resources, the quality of utilized water, environmental repercussions, and regulations for the sustainable use of water resources. In the management of water resources, optimal qualitative–quantitative exploitation of surface water bodies is regarded as a desirable strategy. The Dez River surface water system from the Dez regulatory dam to Band-e-Ghir is selected in the current paper to create a qualitative–quantitative model that can determine the best exploitation strategies. A dynamic linkage between qualitative and quantitative models is built in order to simulate the current exploitation conditions under the umbrella of the best-case scenario. In this coupled system, hydraulic relationships are established between all of the system’s components. The available data are shared between two models in this structure to simulate the qualitative and quantitative effects of surface water. Then, a new structure is produced to derive the best policies for exploiting the dam and the river by connecting the multi-objective particle swarm optimization algorithm with the qualitative–quantitative coupled model body. The monthly river environmental demand is one of the decision variables in the ideal scenario, and the goals include boosting the percentage of supply demands and minimizing the violation of quality standards. The best-case scenario’s implementation increases the likelihood that all plain demands will be met, regardless of priority. Furthermore, in comparison with the reference scenario, the results of the optimal scenario show that not only are the concentrations of contaminants and qualitative parameters increased, but there are also only minimal violations of the quality and pollution standards of the river water in the majority of river points, particularly in the locations of agricultural withdrawals. The findings demonstrate that using the qualitative–quantitative dynamic relationship between water resources and the development of the coupled model using the NSGA-II algorithm allows us to better plan for the appropriate use of existing water resources by taking into account all stakeholders in such a way that, in addition to meeting needs, maintains the river quality close to standard limits throughout the exploitation period. By using this strategy, users will be informed of the negative effects of their actions, as well as the encroachment on river boundaries and associated consequences.

Transforming dementia research into practice: a multiple case study of academic research utilization strategies in Dutch Alzheimer Centres.

Non-pharmacological dementia research products, such as social and behavioural interventions, are generated in traditional university settings. These often experience challenges to impact practices that they were developed for. The Netherlands established five specialized academic health science centres, referred to as Alzheimer Centres, to structurally coordinate and facilitate the utilization of dementia research knowledge. This study leverages implementation science to systematically explore the research utilization strategies used by academic researchers from each Alzheimer Centre, on the basis of the "knowledge-to-action" (KTA) framework that includes knowledge creation, adaptation, dissemination and implementation. Individual semi-structured qualitative interviews were conducted with 29 respondents across the five Alzheimer Centres in the Netherlands. Participants were selected through purposive (snowball) sampling. Interviews were conducted in-person and virtually through Microsoft Teams, and all were audio-recorded and transcribed verbatim. Data analysis was guided by the dimensions of the KTA framework. There was a high variation in the strategies used across the five Alzheimer Centres to bring non-pharmacological dementia research into practice. Selected strategies in each Centre were influenced by the typology of research products produced and the Centres' organizational heritage. The knowledge creation and adaptation phases were mainly facilitated by funders' guidance towards research impact and research product co-creation with patients and implementing organizations. Dissemination and implementation phases were often facilitated through utilizing support from university-based technology transfer offices to facilitate implementation and valorization and establishing and strategically leveraging formal infrastructure, such as public-private partnerships and professional collaborative networks. Successful research utilization requires evolving researcher competencies to meet environmental demands and facilitating co-creation with research end-users and implementing partners. Understanding external determinants influencing research utilization in the Dutch dementia research ecosystem is crucial for capacity-building and aligning cross-sector agendas. The KTA framework appears to reveal the intricacies of research utilization, guiding future studies to explore strategies employed across various contexts.

Artificial Intelligence Based Hybrid ASFO-ESVM for Load Demand Prediction in Micro Grid Energy Management

Predicting load demand is relevant when used in microgrid energy management systems to address issues such as nonlinear and dynamic consumption data. In this research, the author presents a fusion of Adaptive Sunflower Optimization (ASFO) and Enhanced Support Vector Machine (ESVM) methods to predict the load demand in micro grid environment. The ASFO algorithm enhances the efficiency of the ESVM through a fine-tuning meta-heuristic algorithm based on the sunflower natural organisms. This integration of ASFO and ESVM eliminates many of the drawbacks associated with the basic performance of the task, namely low speed of convergence, overtraining, and the presence of local minima in choosing the parameters. Some of the general parameters used in training and validating the model include load and meteorological data features involving, weather, temporal, load histories are the main contributors in the analysis. Comparisons with other ML algorithm ‘shave been made in respect of relative performance against established methods, such as Random Forest (RF) and Particle Swarm Optimization based with ESVM (PSO-ESVM). The findings infer that lower values of Mean Absolute Percentage Error (MAPE) and Symmetric Mean Absolute Percentage Error (SMAPE) and higher consistency index (d) are yielded by the proposed hybrid ASFO-ESVM model. For instance, even on working days of the week, the precision of the load forecasts was higher with the hybrid model than with the other options. The outcomes do prove that the proposed ASFO-ESVM model is very reliable and precise in its concerning aspect of load demand forecasting as it can be seen in the results obtained for different situations. Relatively, this work estimates a cost effective and feasible method for micro grid energy predictions which can enhance decisions in matters concerning power production, distribution, and control of energy. The study shows how these techniques are relevant towards the complexity and dynamism of the contemporary energy systems.

A review on WO3 photocatalysis used for wastewater treatment and pesticide degradation.

The rapid growth in the global population has led to increased environmental pollution and energy demands, exacerbating the issue of environmental contamination. This contamination is significantly impacted by various types of pesticides found in water sources, which pose serious health risks to humans, animals, and aquatic ecosystems. In response, extensive research into water treatment technologies has been conducted, focusing on efficient methods to remove these pollutants, with advanced oxidation processes and the utilization of tungsten trioxide (WO3) as a photocatalyst showing promising results. This paper aims to review WO3-based photocatalytic processes for pesticide degradation, highlighting the potential of modified WO3 structures to improve photocatalytic efficiency and address current environmental challenges. Different WO3 synthesis routes and methods for modification have been discussed. The synthesis of WO3-based photocatalysts encompasses various methods that significantly affect their morphologies, sizes, structures, and thus catalytic performance, cost-effectiveness, and environmental sustainability. Techniques like hydrothermal, solvothermal, co-precipitation, sol-gel, and green synthesis and physical deposition techniques are elaborated, highlighting their unique advantages in producing nanostructures with desired physical and chemical properties. Moreover, enhancement methods aimed at optimizing the photocatalytic activity of WO3 under visible light for pollutant degradation have been discussed. Evaluation of WO3-based photocatalytic systems for pesticide treatment, emphasizing the effectiveness of various catalysts in degrading pesticides including organochlorines, organophosphorus, and chloropyridines have been conducted.

THE HIGHLY EFFICIENT BiOCl/KBiO3 p-n HETEROJUNCTION PHOTO-CATALYSTS UNDER VISIBLE LIGHT IRRADIATION

BiOCl/KBiO3 p-n heterostructures with hierarchical mesoporous architectures were successfully synthesized via a facile in situ method. The X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and scanning electron microscope (SEM) results indicate the formation of heterojunctions between BiOCl and KBiO3. The photocatalytic performance of the as-prepared samples was investigated by the degradation of dye Rhodamine B (RhB) under visible light irradiation. BiOCl/KBiO3 composite has never been used to photodegrade the RhB which is a common dye and very difficult to degrade. The results demonstrated that KBiO3 combined with proper amount of BiOCl nanosheets exhibited high efficiency in the photocatalytic process, and BiOCl/KBiO3 with the molar ratio of 70/30 demonstrated the highest photocatalytic activity due to its large surface area, excellent charge separation characteristics and the suppressed recombination of electron-hole pairs. The results of active species detection reveal that the superoxide radical anions (O2-), hydroxyl free radicals (·OH), photogenerated holes (h+) and photogenerated electrons (e-) reactive species work together for the photocatalytic degradation of RhB. A possible and new mechanism of photocatalysis that differs from other teams was also explored and proposed. The present study will benefit the development of the new p-n heterojunction photocatalysts and would be of great importance to meet ever-increasing environmental demands in the future.

A Game-Theoretic Approach for User-Centric AP Selection in Cell-Free Massive MIMO under Dynamic User Demand Environment

A Game-Theoretic Approach for User-Centric AP Selection in Cell-Free Massive MIMO under Dynamic User Demand Environment

Encouraging Community Empowerment and Local Economic In-dependence in Villages through Sustainable Economic Develop-ment Techniques

With an emphasis on local economic independence and community empowerment, this publication examines sustainable economic development tactics in villages. The purpose of this study is to present an integrated and comprehensive picture of sustainable village economic development. The researchers assessed economic development initiatives in several community areas in Indonesia, using qualitative descriptive methods. The study findings suggest that a comprehensive and integrated approach that considers the economic, social, cultural, and environmental demands of the local population is necessary for sustainable economic development in villages. To achieve local economic independence, community empowerment through active community involvement in the formulation and implementation of economic development programs is essential. The authors of this article suggest a sustainable economic development plan for villages that is based on the ideas of community empowerment and participation. Leveraging local resources, strengthening organizations and cooperatives, empowering women and youth, developing small and medium enterprises and the agricultural sector, and implementing sustainable environmental management are all part of this plan. In conclusion, a comprehensive and integrated approach that emphasizes local economic independence and community empowerment can lead to sustainable economic development in villages. Such a plan can improve the welfare of village communities and encourage sustainable economic growth.

Strength characteristics and prediction model of solidified municipal sludge reinforced by dredged silt combined with sodium silicate and polyurethane

The treatment and resource utilization of municipal sludge and dredged silt have been rendered urgent by the acceleration of urbanization and stricter environmental protection demands. An effective solution was developed to address the challenges of poor mechanical properties and the difficulty in directly using cement-based materials for municipal sludge treatment. The utilization of dredged silt with high water content served as the foundational skeleton material. Appropriate proportion (0.5:1.0) of sodium silicate, which accelerates cement hardening, and polyurethane, which facilitates chemical bond cooperation, was combined to form SP material, partially replacing cement. Unconfined compressive strength (UCS) tests were subsequently conducted on the solidified municipal sludge. These tests aimed to investigate the influence of the dredged silt mixing ratio, initial water content of dredged silt, and the SP mixing ratio on the strength of the solidified municipal sludge. Furthermore, a strength prediction model was established for solidified municipal sludge, taking into consideration the mixing ratios of dredged silt and SP. The research findings indicate that dredged silt can serve as a skeleton structure for solidified municipal sludge. The UCS of the solidified municipal sludge increases with the increase in the dredged silt mixing ratio, and reaches a maximum value at mixing ratio of 1.0. SP materials can partially replace cement, the appropriate proportion of SP and cement can synergistically improve the strength of solidified municipal sludge, and the optimal SP mixing ratio is 50%. Furthermore, the strength prediction model constructed with independent variables such as dredged silt mixing ratio, curing age, water-to-cement ratio, and SP mixing ratio demonstrates better predictability for the strength development of solidified municipal sludge.

Development e-worksheet using PjBL on environmental pollution to enhance environmental literacy of tenth grade high school

The increasing environmental issues demand environmental literacy among the younger generation. 21st-century learning with PjBL-based worksheet can make the learning process more interactive, contextual, and focused on solving real-world problems. This research aims to:(1) produce an E-worksheet with the PjBL model on environmental pollution that is feasible as a learning model for 10th grade high school; (2) produce an E-worksheet with the PjBL model on environmental pollution that is practically for biological teachers and 10th grade high school; (3) produce an E-worksheet with the PjBL model on environmental pollution that is effective in improving environmental literacy for 10th grade high school. This research uses the R&amp;D mode, specifically the 4D model. The research instruments included interview sheets, practitioner assessment questionnaires, material and media validation sheets, and multiple-choice and descriptive test sheets. Based on the data obtained: (1) The E-worksheet with the PjBL model on the topic of environmental pollution is valid according to material and media experts, scoring in the "very good" category; (2) The E-worksheet is practical based on teacher assessment and student responses with scores included in the “very good” category ; (3) The research results indicate that the N-gain for cognitive domain environmental literacy is (&lt;g&gt; = 0.43) and for the affective domain is (&lt;g&gt; = 0.63), which are categorized as moderate. Based on this, it can be concluded that the Electronic Worksheets (E-worksheet) with the PjBL model is feasible and practical and can enhance the environmental literacy of class X SMA students.

Lying as a compensatory mechanism in adolescents with intellectual disabilities

The purpose of this study was to determine how adolescents with intellectual disabilities use lying as a compensatory mechanism. We were particularly interested in observing how these adolescents’ resort to lying as a social facilitation mechanism. The study involved 33 adolescents with intellectual disabilities aged between 14 and 18 years (M = 15.88, SD = 1.45), of whom 24 were boys (72.7%) and 9 were girls (27.3%). The results showed that adolescents with intellectual disabilities use lying as a compensatory mechanism to cope with the social challenges they face. These perspectives offer practical implications for supporting adolescents with intellectual disabilities in navigating social environments, meeting relational needs, and adapting to the demands of an ever-changing environment.

Bridging the urban-rural information gap: A case study of digital rural construction in Yunnan Province

As one of the key initiatives promoted by the Chinese government, precision poverty alleviation aims to lift information-blocked areas out of poverty and ensure their sustainable economic development. Yunnan Province, characterized by its combination of old, young, border, and poor areas, is the province with the most diverse types of poverty, the widest poverty coverage, and the deepest poverty levels in the country. Yunnan has carried out anti-poverty work in tandem with the national efforts for 42 years in a planned and organized manner, ultimately achieving the goal of zero absolute poverty. In this process, digital rural development has played a very important role. Based on the current experience of digital construction in developed regions, completing regional digitalization requires meeting the needs of information resources, information environment, and information supply and demand. Through keyword search, text analysis, and field visits, we summarized the factors considered by local governments in policy formulation. We also attempted to map out the path for rural governments to build digital villages. With the ultimate goal of bridging the urban-rural gap, the study of digital rural development in Yunnan will provide an effective case.

Spatial heterogeneity determines the gastrointestinal microbiome signatures and ecological processes that govern bacterial community assembly in sheep.

Sheep's gastrointestinal tract harbors a diverse microbial community crucial for immune system balance, nutrient digestion, and overall health. We explored the microbial community composition, community types (enterotypes), bacterial interactions, and ecological processes in 10 gastrointestinal regions of 36 six-month-old Hu sheep raised under same diets and environmental conditions. Our findings revealed a unique U-shaped pattern of bacterial diversity from the rumen to the rectum, with the lowest diversity in the jejunum. The composition and enterotypes of bacterial communities varied spatially along the gastrointestinal tract, primarily categorized into three distinct groups. The rumen exhibited the highest abundance of bacterial taxa, unique taxa, and unique functions, while the enterotypes in the three regions of the large intestine were consistent. We explored the assembly processes of bacterial communities, elucidating how they find their ecological niches based on their characteristics and environmental demands. The assembly processes in the four-chambered stomach and small intestine resembled random selection, where bacterial positioning depended on luck and chance, while in the large intestine, it appeared more deterministic, with specific bacteria likely selected based on their unique skills and environmental requirements. This study enhances our understanding of microbial coexistence and interactions in complex ecosystems, with implications for improving animal productivity, disease treatment, and the development of novel microbial formulations.

Automating Data Pipelines with AI for Scalable, Real-Time Process Optimization in the Cloud

Modern data processing environments demand efficient, scalable solutions for handling massive data streams in real-time, yet traditional Extract, Transform, Load (ETL) pipelines face significant limitations in processing speed and adaptability. This article presents an AI-Enhanced Cloud Data Pipeline (AECDP) framework that combines Deep Learning-based Stream Processing (DLSP) with Adaptive Resource Management (ARM) for real-time data optimization. The framework introduces novel algorithms for stream processing, resource allocation, and quality assurance, including the Adaptive Stream Processing Algorithm (ASPA) and Anomaly Detection and Correction (ADC) system. The implementation utilizes a multi-cloud architecture with containerized microservices, enabling independent scaling and maintenance of pipeline components. Experimental results demonstrate the framework's effectiveness across various industry applications, including e-commerce, financial services, and manufacturing sectors. The system achieves consistent sub-second latency for real-time processing, linear throughput scaling, and optimal resource utilization across cloud instances. Additionally, the framework incorporates advanced security features and automated quality monitoring systems, ensuring robust and reliable data processing. The AECDP framework represents a significant advancement in data pipeline automation, providing organizations with a comprehensive solution for managing complex data processing requirements while maintaining high performance and reliability standards.

Conducive conditions for curriculum practice in teaching accounting at a rural school in the KwaZulu-Natal

The education landscape constantly evolves and brings new challenges and opportunities in teaching practices, particularly in specialised subjects such as accounting. The curriculum's adequacy and delivery significantly influence learners' preparedness for professional pathways and academic advancements. This paper presents a theoretical overview of the conditions conducive to practical curriculum practice in accounting instruction. Building on a synthesis of educational theories and empirical studies, we posit that a multidimensional approach incorporating pedagogical, contextual, technological, and evaluative components is necessary to align accounting education with the demands of the contemporary business environment. In recent years, discourse on teachers’ content knowledge, pedagogy knowledge, and pedagogical content knowledge and their influence on learners’ learning outcomes has garnered increasing attention from various stakeholders in the education sector. The theoretical framework we propose aims to support teachers and curriculum developers in fostering educational experiences that enhance learners' engagement and understanding and in applying accounting principles in a multifaceted world. Key to this framework is the integration of technology in pedagogy, the responsiveness of curriculum content to market needs, the adoption of diverse and inclusive teaching methods, and a continuous feedback mechanism to refine teaching strategies. This overview serves as a guide for promising practices and a catalyst for further research on optimising accounting education in a rapidly changing economic landscape.