Journal of Emerging Science and Engineering
Journal of emerging science and engineering; JESE; emerging science journal;
Journal of Emerging Science and Engineering published under the terms of a Creative Commons Attribution 4.0 International License / CC BY 4.0 This license permits anyone to copy and redistribute this material in any form or format, compose, modify, and make derivative works of this material for any purpose, including commercial purposes, so long as they include credit to the Authors of the original work.
Experimental assessment of domestic biogas production from organic waste through anaerobic digestion in Chad
Environmental degradation and health concerns. In this context, the valorisation of organic waste through anaerobic digestion represents a promising alternative for sustainable household energy production. This study presents an experimental assessment of domestic biogas production from organic waste under local conditions in Chad. A pilot-scale anaerobic digestion system was designed and operated for a period of 30 days. The digester was fed with a mixture of vegetable organic waste and fresh cow dung used as inoculum. Key operational parameters, including temperature and pH, were regularly monitored throughout the digestion process. The system was designed to meet the cooking energy needs of a household of eight persons, and the technical feasibility of biogas production was evaluated. The experimental results showed that biogas production started from the tenth day of fermentation and increased progressively with the hydraulic retention time. The pH remained within a range favourable to methanogenic activity, while temperature variations were compatible with mesophilic digestion conditions. The observed biogas production confirmed the methanogenic potential of the selected organic substrates and demonstrated the suitability of the proposed low-cost digester for domestic energy applications. Biogas volume increases with daily feeding (1/60 of the useful volume) and a retention time of 30 days, reaching a maximum volume of 1,2 m³. This can reduce daily consumption by approximately 0,2 m³ of butane, 1,24 kg of charcoal, and 2,5 kg of firewood.The findings indicate that anaerobic digestion of household organic waste can contribute to sustainable energy supply, waste management improvement and reduction of pressure on forest resources in Chad. This study provides practical evidence supporting the deployment of small-scale biogas systems in similar socio-economic contexts.
Copyright (c) 2026 Abdelhamid Issa Hassane, Bill Vaneck Bôt, Fatimé Nadji Gisele, Doussi Howe Olivier, Ruben Mouangue https://creativecommons.org/licenses/by/4.0
Building institutional resilience to AI-driven misinformation in critical infrastructure: Evidence from the Albanian energy sector
The rapid expansion of generative artificial intelligence has significantly transformed digital information environments, increasing the volume, velocity, and technical sophistication of misinformation affecting critical infrastructure systems. In the energy sector, such disruptions pose measurable risks to regulatory reliability, infrastructure investment, and operational stability, particularly in countries undergoing energy transition and digital modernization. Albania’s developing energy ecosystem provides a relevant empirical context for examining these emerging system-level vulnerabilities. This study analyzes the integration of Business Intelligence (BI), Competitive Intelligence (CI), and AI-based detection systems in strengthening institutional resilience against AI-generated misinformation. A qualitative-dominant mixed-methods case study approach is employed, combining large-scale digital media monitoring, intelligence-cycle modeling, and expert-based validation. The research focuses on a coordinated disinformation campaign targeting the Qeparo Solar Farm project in 2025, using temporal network analysis, content classification, and attribution mapping to evaluate diffusion dynamics and institutional response mechanisms. Results indicate that misinformation propagation followed structured temporal patterns, emotionally optimized framing strategies, and coordinated amplification networks consistent with organized influence operations. Early anomaly detection was achieved through hybrid analytical systems integrating automated machine learning tools with professional assessment. Competitive Intelligence analysis supported probabilistic attribution and risk prioritization, while coordinated governance responses enabled rapid system stabilization and restoration of stakeholder confidence. The study proposes an applied governance-oriented resilience framework integrating BI, CI, and AI detection within a unified institutional monitoring architecture. The findings demonstrate that effective protection of critical infrastructure information systems depends primarily on institutional system design, operational coordination, and analytical capacity, rather than technological deployment alone. This research provides practical guidance for regulators, engineers, and infrastructure managers seeking to enhance digital security, information integrity, and system reliability in AI-driven operational environments
Copyright (c) 2026 Eva Hyna https://creativecommons.org/licenses/by/4.0
Research status and development trends of wind-induced vibration technology for photovoltaic support systems
Against the backdrop of global energy transition, photovoltaic (PV) power generation has witnessed rapid expansion, with China’s newly installed capacity in 2024 accounting for 52.4% of global additions. However, PV support systems face significant wind-induced vibration challenges in complex scenarios. This study systematically reviews advances in wind-induced vibration mitigation technologies for PV supports. First, structural characteristics and failure mechanisms are analyzed for fixed-axis, single-/dual-axis tracking, cable-suspended flexible, and offshore PV support systems. Second, synergistic applications of wind tunnel tests, numerical simulations, and field monitoring are reviewed to reveal nonlinear dynamic mechanisms such as vortex-induced vibration (VIV) and flutter. Third, many important dominant factors, such as aerodynamic parameters, geometric parameters, structural parameters, topographic effects are analyzed in detail. And design strategies such as prestress optimization, damping enhancement, and stiffness assignment are used to mitigate wind-induced vibration response in practice. Current challenges are discussed including unclear dynamic aeroelastic coupling mechanisms, insufficient scaling model similarity, and lack of standards for diverse scenarios. In future, developing high-fidelity multi-physical models, intelligent vibration suppression technologies, and cross-disciplinary frameworks will be emphasized to enhance system robustness and cost-effectiveness under extreme climates, supporting the global scaling of PV deployment.
Copyright (c) 2026 Jiashun Hu, Wenhua Li, Tao Sun, Mingjie Shi, Fan Yang https://creativecommons.org/licenses/by/4.0
Extracellular polymeric substances from Spirulina sp. for the bioremediation of fishing net–derived microplastics in seawater
The increasing accumulation of plastic waste from fishing nets is primarily driven by the large volume of nets introduced into aquatic systems. Fishing nets are predominantly manufactured from polyethylene, a polymer known for its high resistance to degradation, allowing it to persist in marine environments for hundreds of years. Consequently, discarded or degraded fishing nets represent an ongoing environmental challenge, which is further exacerbated by their fragmentation into microplastics. In response to this issue, this study aims to evaluate the effectiveness of extracellular polymeric substances (EPS) produced by Spirulina sp. for the bioremediation of polyethylene-derived microplastics from fishing nets in seawater. A quasi-experimental design was employed, consisting of control and treatment reactors. EPS was applied at concentrations of 20, 30, and 40 mg in the treatment reactors, while the control reactor received no EPS addition. The remediation process was conducted over treatment periods of 5, 9, and 13 days. Following the treatment, laboratory analyses were performed to assess changes in key water quality parameters, including salinity, dissolved oxygen (DO), pH, total dissolved solids (TDS), chemical oxygen demand (COD), and Spirulina growth rate. In addition, the residual microplastics that were not flocculated were quantified. The results indicated that the presence of microplastics influenced the growth dynamics of Spirulina. Nevertheless, EPS application resulted in a measurable reduction in microplastic mass, with decreases of 5.0 g, 10.1 mg, and 11.6 mg observed in the 20, 30, and 40 mg treatments, respectively. Overall, the findings demonstrate that bioremediation using Spirulina-derived EPS is effective in reducing polyethylene microplastics in seawater. Future studies are recommended to extend the treatment duration, utilize natural seawater under environmentally realistic conditions, and evaluate the broader ecological impacts of EPS-based bioremediation to support its practical application in marine environments.
Copyright (c) 2026 Sri Hapsari Wahyuningtyas, Adian Khoironi, Lilibeth Bucol https://creativecommons.org/licenses/by/4.0
SPIROWPLAST (Spirulina and arrowroot bioplastic): A combination of Spirulina and arrowroot to enhance the tensile strength and durability of bioplastic
Plastic waste that is resistant to natural degradation remains a critical environmental challenge. One promising strategy to address this issue is the development of bioplastics derived from renewable, biodegradable resources. This study investigates the potential of combining Spirulina platensis and arrowroot (Maranta arundinacea) flour to produce bioplastics with improved mechanical, chemical, and biodegradation performance. An experimental approach was employed using four formulations: bioplastics derived solely from S. platensis, solely from arrowroot flour, a composite of S. platensis and arrowroot flour, and a commercial bioplastic (ecoplast) as a positive control. Comprehensive characterization was conducted using Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), X-ray Diffraction (XRD), tensile strength, thickness measurement, and biodegradation tests in accordance with ASTM standards. The results demonstrate that the combined Spirulina–arrowroot formulation exhibits more balanced and superior properties compared to single-component bioplastics. The composite bioplastic achieved a tensile strength of 4.267 MPa and an elongation at break of 105.5%, approaching the performance of commercial bioplastic. FTIR analysis confirmed the presence of key functional groups, including hydroxyl (–OH), carboxyl (–COOH), ester (C–O), and aromatic structures, indicating effective polymer network formation. SEM observations revealed a smoother and denser surface morphology, while XRD analysis indicated a semi-crystalline structure with a crystallinity of 49.6%. All bioplastic samples fully decomposed in composted soil within three days, highlighting their excellent biodegradability. Overall, the combination of Spirulina platensis and arrowroot flour effectively compensates for the limitations of each individual material, yielding a strong, flexible, and rapidly degradable bioplastic. These findings suggest a viable and environmentally friendly alternative to conventional plastics and provide a foundation for the future development of large-scale bioplastic products with properties comparable to commercial materials.
Copyright (c) 2026 Amira Liontina Ichlasia, Zameera Adelia, Roosita Damayanti, Putri Dyah Astari, Wahyu Disky Pratama https://creativecommons.org/licenses/by/4.0
Evaluation of reverse supply chain strategies for end-of-life EV batteries in Vietnam using AHP–TOPSIS
The booming development of electric vehicle (EV) adoption in Vietnam has worsened the problem of end-of-life EV battery management in a sustainable and economically feasible way. Reverse supply chain management (RSCM) plays a critical role in reducing environmental risks, resource dependency, and circular economy goals. However, the choice of suitable reverse supply chain strategies is impaired by several economic, environmental, technical, and policy-related barriers. This study proposes an integrated AHP-TOPSIS framework for the evaluation and prioritization of reverse supply chain alternatives for EV batteries in the Vietnamese context. Ten key barriers were identified, from an extensive literature review and expert consultation by twelve domain specialists. High collection and transportation costs (weight = 0.244) and high recycling and processing expenses (weight = 0.162) were shown to be the most significant barriers when AHP was applied to determine their relative importance. The four options—Direct Recycling, Second-Life Applications, Centralized Recycling, and Decentralized/Hybrid Recycling—were then ranked using TOPSIS. According to the findings, Decentralized/Hybrid Recycling had the highest closeness coefficient, followed by Second-Life Applications, while Direct Recycling had the lowest. The results show how adaptable and localized reverse supply chain topologies can help solve the issue of cost-related barriers. In order to promote sustainable EV battery management in Vietnam, the suggested framework provides policymakers and industry stakeholders with useful insights.
Copyright (c) 2026 Viet Khai Le, The Anh Le, Quoc Bay Le, Minh Phuong Thai, Nguyen Phuong Lien Le https://creativecommons.org/licenses/by/4.0
A multi-model simulation framework for the 'Sponge Park' concept: achieving urban water-energy nexus sustainability in hyper-arid climates
Urban areas in hyper-arid regions face a dual threat of water scarcity and urban heat islands, exacerbated by conventional infrastructure. This study introduces and evaluates the "Sponge Park" concept—a decentralized, nature-based system of permeable surfaces and subsurface storage—as a replicable model for integrated water management and climate adaptation in arid cities. A novel multi-model computational framework was developed, coupling Computational Fluid Dynamics (CFD) for process-level subsurface hydrology and heat transfer, the EPA HELP model for long-term water balance, and TR-55/HydroCAD for extreme storm event routing. The system, designed for a 13-ha site in Abu Dhabi, integrates high-infiltration silica-sand pavers and breathable aquicludes (APAC). A comprehensive Monte Carlo analysis (n=1,000) quantified uncertainties in key parameters. Simulations under local climatic inputs (80 mm/yr rainfall) project exceptional performance: >93.6 ± 3.8% annual rainfall infiltration, <0.1% runoff for 50 mm/24h storms, and pollutant removal efficiencies of 98.0 ± 2.1% (SS) and 93.9 ± 4.2% (COD). The system harvests 5,240 ± 520 m³/yr of water for reuse. The latent heat flux from evaporation (9.32 ± 0.93 GJ/yr per 1,000 m²) translates to a microclimate cooling of 0.4–0.6 °C. A life-cycle cost analysis confirms economic viability with a net present value of +$0.42 million. The Sponge Park provides a quantitative, policy-ready blueprint for transforming arid cities. It demonstrates a sustainable pathway to achieving water security and climate resilience, directly supporting the UAE's Estidama framework, Net-Zero 2050 goal, and relevant UN Sustainable Development Goals (SDGs). The simulation-based proof-of-concept establishes a new benchmark for sponge city applications in water-stressed regions, with a defined plan for field validation.
Sponge City; Urban Hydrology; Computational Fluid Dynamics (CFD); Nature-Based Solutions; Heat Island Mitigation; Arid Regions; Sustainable Drainage Systems (SuDS); Water-Energy Nexus
Copyright (c) 2026 Firas Fayssal https://creativecommons.org/licenses/by/4.0
Analysis of weather and ship-type effects on fuel efficiency and emissions for green maritime operations
This research is an endeavour to develop an explainable machine learning framework to quantify the combined effect of ship type, fuel type, distance and weather conditions affecting fuel consumption and CO2 emissions for green maritime operations. The data collected from the voyage-level records for various vessel categories was pre-processed and used to train three supervised regression models: Linear Regression, Random Forest, and Extreme Gradient Boosting (XGBoost). The models were tested based on the coefficient of determination (R2) and mean squared error for training and test data sets separately for fuel consumption and CO2 emission. Results show that all models are able to capture the main trends, but the Random Forest was able to provide the most accurate and robust predictions, with values of test R2 exceeding 0.94 and the lowest values of error for both target variables. In order to improve the interpretability, SHapley Additive exPlanations (SHAP) analysis and feature importance measures were used for the Random Forest models. Distance becomes the main factor, whereas ship type, fuel type, and weather variables have a secondary but significant impact on fuel consumption and emissions. The proposed approach offers a transparent and computationally efficient aid for supporting operational optimization, fuel choice evaluation, and policy design in the context of maritime decarbonization.
Copyright (c) 2025 Ngoc Doanh Le, Nguyen Dang Khoa Pham https://creativecommons.org/licenses/by/4.0
Global research trends and hotspots in solar power tower technology: A bibliometric review
Solar Power Towers (SPTs), as a forefront division of Concentrated Solar Power (CSP), have become a promising option for green electricity generation. This paper presents a bibliometric study of global research output in SPTs using data retrieved from the Scopus and Web of Science databases for the period between 2015 and 2024. The 860 documents dataset was mapped using bibliometric tools like VOSviewer and Bibliometrix to examine publication trends, prominent authors, leading institutions, high-output countries, and hot topics of research. The findings illustrate a picture of tremendous growth in publications since 2008 with China, the United States, and Spain as the leading contributors. Heliostat field design, thermal energy storage, receiver efficiency, and system-level optimization are some of the leading research themes. Keyword co-occurrence and co-authorship analysis reveal thematic clustering and changing collaboration patterns, with increasing yet still modest international collaboration. This review presents the current shape and intellectual structure of SPT research, giving a glimpse of its evolutionary trajectory. The findings can help researchers, practitioners, and policymakers identify knowledge gaps and plan future research agendas in the field of solar thermal technologies.
Copyright (c) 2025 Zeshan Aslam, Syed Ihtsham Ul-Haq Gilani, Taib Iskandar Mohamad, Kehinde Temitope Alao https://creativecommons.org/licenses/by/4.0
Risk management in the energy sector: Challenges, strategies, and regulatory frameworks in Western Balkans as Albania case study
The energy sector, characterized by substantial capital investments, long-term projects, volatile commodity prices, and increasing environmental concerns, faces a complex and evolving landscape of risks (Kaarle Parikka, 2024). This article examines the key challenges in effective risk management within this critical sector, ranging from operational disruptions and geopolitical instability to the impacts of the energy transition and climate change. It explores diverse risk management strategies employed by energy companies, including advanced forecasting techniques, hedging instruments, diversification, and robust emergency response plans. Furthermore, the paper analyzes the crucial role of regulatory frameworks at national and international levels in shaping risk management practices and promoting resilience across the energy value chain in Western Balkans having Albania as case study. By synthesizing current trends and best practices, this article provides valuable insights for energy stakeholders seeking to navigate uncertainty and ensure sustainable and secure energy supply.
Copyright (c) 2025 Eva Hyna, Eli Vyshka https://creativecommons.org/licenses/by/4.0
Effect of ambient temperature variance on power output of wind turbine and mitigation strategy
Many challenges have been found in the operation of wind turbine under varying weather conditions, which demands novel strategies to address these issues. As far as we know, the variation of weather parameters is crucial for wind turbine operators to monitor the operation of wind turbines and adjust parameters of generator to ensure safe and efficient operation. This study aims to explore the effect of ambient temperature variation on wind turbine parameters including rotational speed, output power and pitch angle, using 10-minute measurement data for temperature ranges from -5oC to +20oC. By understanding such effects, researches can develop a control strategy to minimize their effect and improve the performance of wind turbines by increasing power production and reducing unnecessary loads and control actions. In this research, the mitigation method was developed within the control system to correct the parameters of wind turbine according to ambient temperature variation, offering a more practical strategy for wind turbines that currently in use. The simulation studies were carried out using Matlab/Simulink® software, and the results revealed that the output power of the wind turbine rose by 5.71% compared to standard strategy after mitigation method was implemented.
Copyright (c) 2025 Nyam Jargalsaikhan, Sergelen Byambaa, Baigali Erdenebat, Nomuulin Batjargal, Munkhjargal Sukhbaatar https://creativecommons.org/licenses/by/4.0
From pond to polymer: A concise review on algae-derived plastics
Algae-derived plastics signify a revolutionary advancement in the pursuit of sustainable materials, providing a renewable and environmentally benign substitute for conventional petroleum-based polymers. This review explores the most recent advancements in algae cultivation, polymerization methodologies, and synthetic biology that have elevated algae-based bioplastics to a position of prominence. It emphasizes the distinctive characteristics of algal biopolymers, their capacity to sequester carbon, and their various applications, encompassing packaging and 3D printing. Nonetheless, the pathway from aquatic environments to polymeric substances is laden with obstacles, including elevated production costs, challenges related to scalability, and regulatory impediments. Through the analysis of case studies, market dynamics, and burgeoning research, this paper highlights the pivotal importance of algae-derived plastics in fulfilling circular economy objectives and mitigating plastic pollution. The review culminates with an appeal for international collaboration, policy advocacy, and sustained investment in algae bioplastics to realize their complete potential as a fundamental element of sustainable development.
Copyright (c) 2026 Akash Phillip, Tushar Chauhan, Shravan Kumar, Bagepalli Srinivas Ashok Kumar https://creativecommons.org/licenses/by/4.0
Enhancing renewable energy integration through energy storage and smart grid innovations: A systematic review
This study presents a systematic review of advancements in energy storage technologies and intelligent grid management systems and evaluates their combined role in enhancing the reliability, efficiency, and integration of renewable energy sources. A comprehensive search across major databases identified 170 records, of which nine studies met PRISMA-based inclusion criteria after rigorous screening. The findings indicate that energy storage technologies, particularly lithium-ion batteries, pumped hydro storage, and emerging hybrid systems, significantly improve grid stability by mitigating renewable intermittency, supporting load balancing, and optimizing charge–discharge cycles through advanced scheduling techniques. Parallel innovations in smart grid technologies, including advanced metering infrastructure, demand response mechanisms, enhanced forecasting tools, and communication-enabled automation, strengthen real-time system flexibility and reduce operational stress associated with fluctuating renewable output. Integrated approaches, especially Virtual Power Plants that aggregate distributed energy resources, demonstrate superior performance by enabling coordinated dispatch, improving system resilience, and supporting higher levels of renewable penetration. Despite these benefits, challenges such as high capital costs, uneven technological readiness, regulatory gaps, and cybersecurity vulnerabilities persist. Overall, the review underscores that the convergence of advanced storage technologies with digitally optimized grid architectures is essential to achieving stable, efficient, and low-carbon electricity systems capable of supporting global decarbonization goals.
Renewable Energy, Energy Storage Systems (ESS)
Copyright (c) 2025 Kaseem A. Obakhume, Faith F. Opatola https://creativecommons.org/licenses/by/4.0
Design a PID controller based on grey wolf optimization algorithm for single-area load frequency control
This article, focuses on the load frequency control (LFC) of a single-area system with a grey wolf optimization metaheuristic approach. This approach is applied to optimize the PID controller parameters for the effective operation of the system. The grey wolf Algorithm (GWO) has been utilized to optimize the controller’s parameters and minimize the error. SIMULINK Model is used to simulate the Single-area load frequency control (SALFC) with GWO to mitigate the error and frequency fluctuations. The integral time absolute error (ITAE) has been considered as an objective function for optimal search of PID parameters. The frequency performance of the system has been observed without a controller, or any other methods in literature and with the proposed grey wolf optimization (GWO). The simulation response shows in terms of rise time, settling time, and peak time. The performance of the power system has been compared with other approaches namely Particle Swarm Optimization (PSO), and Firefly Algorithm (FFA). The Proposed optimization technique provides a much better response than other strategies.
Copyright (c) 2024 Priyanka Jangid, Vishal Nagar, Aditya Sharma, Sonam Nagar, D. K. Palwalia https://creativecommons.org/licenses/by/4.0
Optimizing circular economy practices in Nigerian construction: Effective strategies for waste reduction and resource efficiency
This study explores the current state of circular economy (CE) practices in the Nigerian construction industry, identifying key challenges and opportunities for their implementation. Utilizing a mixed-methods approach, data were collected from 200 survey participants and 20 key informants through structured surveys and semi-structured interviews. The quantitative data were analyzed using descriptive and inferential statistics, including regression and factor analysis, to uncover the relationships between variables and the underlying dimensions of barriers to CE adoption. The findings reveal that while there is a moderate level of awareness and implementation of CE practices, such as waste segregation and the use of recycled materials, these practices are not yet widespread. Major barriers identified include lack of awareness, high implementation costs, and insufficient regulatory support. Specifically, 75% of respondents cited lack of awareness as a significant barrier, and 80% identified high costs as a deterrent. Regression analysis indicated that awareness level, regulatory support, and company size positively influence CE practice adoption, while perceived cost has a negative impact. The study also highlights positive perceptions towards CE practices among industry professionals, with 85% of respondents recognizing their importance for the future of the construction industry. Factor analysis revealed three main dimensions of barriers: financial, awareness and education, and regulatory and policy barriers. Based on these findings, the study recommends targeted educational programs to increase awareness, financial incentives to mitigate cost barriers, and stronger regulatory frameworks to enforce sustainable practices..
Circular Economy, Nigerian Construction Industry, Sustainable Practices, Waste Management, Recycled Materials, Barriers to Implementation, Awareness, Regulatory Support, Financial Incentives.
Copyright (c) 2024 Hyginus C.O. Unegbu, Danjuma S. Yawas, B Dan-asabe, A.A. Alabi https://creativecommons.org/licenses/by/4.0
The impact of the Russia-Ukraine war on the Russian supply chain
The Ukraine and Russia war has damaged the worldwide supply chains during the war, several countries imposed dozens of sanctions worldwide which crippled the supply chain of Russia to a great extent. In many nations, bans were also imposed on industrial products, fossil fuels, raw materials, and grains. In this regard, the authors have analysed how the war between Ukraine and Russia has affected the supply chain of Russia, and that analysis is presented in this dissertation. The findings presented by this research have indicated that finished goods, fuels, and energy shortages have augmented inflation. The war affected the routes of transport which in turn impacted the goods and logistics of the commodities by Russia. Due to war, Europe has taken the step to welcome the Russians leaving their country. The sanctions imposed have adversely affected the Russian imports from Europe and exports to Europe. However, European countries such as Poland, Germany, and Finland imported natural gas from Russia and the imports of fossil fuels were increased by nations like Turkey, China, and India. In this way, Russia's earnings from its sales of fossil fuels rose. Unfortunately, everything gets costly because the cost of transport increased, and worldwide prices of energy elevated. Intense inflation was led by this war.
Supply Chain; Russia-Ukraine war; sanctions; logistics; disruptions; export; import; material shortage; disrupted logistics; inflation; global supply chain.
Copyright (c) 2024 Neha Bargujara, Muhammad Ahmed Kalwar, Ioannis Dermitzakis, Asif Nawaz Wassan https://creativecommons.org/licenses/by/4.0
The laboratory study of P441 oil samples separation by using super absorbent polymer from the waste diapers
The waste diapers, the second largest waste source after plastic, pose environmental challenges due to their slow degradation of 25-50 years. Reprocessing diaper waste, including utilizing Super Absorbent Polymer (SAP), is crucial. SAP's high absorption capacity aids in research for separating crude oil from water, particularly relevant for Indonesian oil wells with aging infrastructure. Emulsions in crude oil, stabilized by natural chemicals, require demulsification to prevent production issues, underscoring the importance of efficient water-oil separation methods. The research experimentally compares oil-in-water emulsion separation using SAP with and without SAP. The study utilizes waste-based ingredients like used diapers, and tests involve centrifuge processes at varying temperatures. SAP's osmotic properties enable high water absorption, impacting demulsification efficiency. This study investigates the impact of temperature on emulsion separation between water and crude oil. Testing at 26°C and 40°C reveals accelerated separation at higher temperatures due to reduced crude oil viscosity. Waste-containing tubes demonstrate better separation, with SAP absorbing water, enhancing separation efficiency. Increasing centrifuge speed and temperature improve oil-water separation, showcasing SAP's effectiveness in waste management processes. Research findings on crude oil-water separation using diaper waste conclude that demulsification is faster at 40°C due to decreased viscosity; with SAP waste, volumes of water are more efficient at 40°C; SAP's hydrophilic nature traps water in the gel network; SAP enhances separation effectiveness compared to non-SAP methods in saline solutions.
Copyright (c) 2025 Prayang Sunny Yulia, Aditya Yoga Pratama, Samsol Samsol, Ridha Husla, Widia Yanti https://creativecommons.org/licenses/by/4.0
Study of decision support for the installation of photovoltaic systems coupled to the electricity grid: Mali’s case study
As the world's energy shortages worsen, countries are starting to exploit renewable energies for which solar power becomes the first choice. Considering the insufficiency of hydraulic and thermal resources in Mali, the hybrid system photovoltaic coupled at the grid is necessary and natural. The present study aims to increase the contribution of renewable energy sources to the national electricity production of Mali, and to pave the way for a good supply of electricity, ensuring the sustainable development of the economy and society of Mali. A preliminary analysis defines the technical, economic and environmental conditions for the implementation of 36 MW solar power plants at four points of Mali's energy interconnection network (Fana Kayes, Kita and Ségou). It can be a first contribution to demonstrating the feasibility of an integrated and self-sufficient energy model in this country. The power of 36 MW is compatible with the capacity of the interconnected network of Mali to absorb the electrical energy produced. For the location of the sites, several criteria have been taken into account for a definitive implementation (local climate conditions, proximity to the interconnected network, source of cooling water, social and environmental impact of the project). The results of the different simulations have shown that the installation of a solar system of 36 MW will be more beneficial in the cities of Ségou and Fana, less beneficial in the city of Kita compared to the two previous cities.
Copyright (c) 2024 Amadou Fousseyni Toure, Fadaba Danioko, Badié Diourte, Nouhoum Keita https://creativecommons.org/licenses/by/4.0
Significance of Balanites aegyptiaca (L.) as Molluscicide against Bulinus wrighti (Mandahl, 1965) snails: A review of concepts
The objective of this paper is to bring a conceptual review of schistosomiasis and application of Balanites aegyptiaca in controlling the host (Bulinus wrighti) of the disease. The snail host (Bulinus wrighti) serve as the host that transmits schistosomiasis disease to humans; therefore, for effective management it shall be controlled. Whereas, schistosomiasis is mostly due to the parasites, S. haematobium, S.japonicum, S. mekongi, and S. intercalatum. Those parasites deposit their eggs in freshwater environment that tend to further develop in snail. Snail shed numerous cercariae that under opportunity invade the human body (for example, farmers, fishers, swimmers, etc). In the human body, the schistosomule is made from the cercariae; thereof allowed to be transported to various body parts (such as liver, messentric veins) depending on the specific parasite involved. Thereafter, eggs are formed and definitive host reactions are elicited in form of clinical portends (such as cough, fever, abdominal pain, fatigue, skin symptoms) in respective of the parasite species. In Africa, millions of individuals are infected, and millions are at risk. To prevent the disease, natural or synthetic mollusucicides could be applied to kill the snail. Natural products such as Balanites aegyptiaca are proven with good virtues to act as mollusucicides. B. aegyptiaca in its various parts contain active compounds such as saponins, tannins, alkaloids, terpenoids, flavonoids, etc that might be responsible for the activities of the plant. Therefore, it is relevant to advocate for natural-bases products such as B.aegyptiaca for prevention of schistosomiasis due to accessibility, cheapness, effectiveness, poverty, and culture-based traditions.
Copyright (c) 2023 Yalli Abu Abdulkarim https://creativecommons.org/licenses/by/4.0
Potential of cassava peel collected from Bauchi (Nigeria) as culture media for growing specific fungi
The objective of this paper is to assess the potential of using cassava peel for A. niger and penicillium growth using standard methods and chemicals of analytical grade. The result of the study indicates that, the peel is rich in proximate contents as the analyzed cassava peel is composed of 8.70% moisture, 4.89% crude protein, 6.9.00% carbohydrates, 4.00 % fat content, 8.93% ash, and 8.75% fibre. Considering the observed morphological and physical characteristics of the test fungi; therewith, A. niger, and penicillium were present. There is indication that, the two utilized media (control and formulated media) are in support of the two microbes growth and depicted positive results of degradation, as well as fermentation ability on the cassava peels. The enriched cassava agar supports higher growth of the two analyzed microbes (viz, A. niger, and penicillium). There was significant difference pertaining the colonies number made on the formulated media (cassava peel agar, and enriched cassava agar). Potato dextrose agar (PDA) shows lower colony count amounting to 3.4 0.1 CFU/ml for A. niger, and amounting to 3.3 0.2 CFU/ml for penicillium. Cassava peel agar (CPA) possessed 6.5 0.5 CFU/ml mean colony count (MCC) for A. niger, and 5.6 0.1 CFU/ml for penicillium. Enriched cassava agar media (ECA) had highest MCC as 7.8 0.1 CFU/ml with respect to A. niger, and 7.3 0.6 CFU/ml pertaining penicillium. Utilization of cassava peel as substrate due to its contents of nutrients that can meet the nutritional requirement of fungi growth is a better move. The peel may be considered as substitute and alternative substrate for producing culture media to cultivate fungi and consequently reducing pollution.
Copyright (c) 2024 Yusuf Yahaya Miya, Thomas Murma Butuwo, Jamil Hassan Abdulkareem https://creativecommons.org/licenses/by/4.0
An insight from homogeneity testing of long-term rainfall datasets over East Java, Indonesia
Robust, reliable, and trustworthy ground observation datasets are the preliminary requirement for assessing the impact of climate change over regions. Principal testing to assess the quality of ground observation rely on the missing data and homogeneity result. The study used 40 years of monthly rainfall documented from different topographical features in the monsoonal region of East Java, Indonesia. The test included annual rainfall, early rainy season (October-November-December), and primary rain season (January-February-March). The homogeneity of rainfall determined by absolute technique: Pettitt’s test, the Standard Normal Homogeneity Test, the Buishand Rank Test, and the von Neumann Ratio. Among the time series, October-November-December observation results in better homogeneity. However, the rainfall datasets during primary rainy season showed the worst homogeneity. By performing annual and seasonal homogeneity test from 67 rainfall stations: 5 stations out of data length required, 5% stations ‘rejected’, 11% ‘suspect’, 11% ‘doubtful’, and 73% were ‘trusted’. Therefore, a total of 45 stations can be used as metadata for relative comparison and 7 stations can be considered to be useful for analysis despite ‘doubtful’. The remaining 10 stations need careful consideration to be used for future water management. Change point detected particularly between the year of 1997 through 2000. Pettitt’s test has outstanding results in the case of extreme climatic anomaly, but less sensitive of continuous abrupt change. The von Neumann test could detect abnormal data, but was not suitable for datasets containing few extreme values. The insights from homogeneity testing were: a) it is important to remove any outliers in the datasets before conducting homogeneity testing, b) both parametric and nonparametric homogeneity tests should be performed, and c) comparisons should be made with surrounding rainfall stations. Comparison with trusted long-term rainfall data is valuable for stations labeled as ‘doubtful’ or ‘suspect’ to mitigate false detections in individual homogeneity tests. The identified ‘useful’ rainfall data can then serve as reference stations for relative homogeneity tests. These findings suggest that reference stations should be assessed within similar rainfall zones.
Copyright (c) 2024 Heri Mulyanti, Istadi, Rahmat Gernowo https://creativecommons.org/licenses/by/4.0
Review of micronutrients in Sokoto, Nigeria: Insufficiency and effects on brain (Nervous system) functioning
In humans, micronutrients are special nutrients that are supposed to be obtained from diets in small amounts to aid body functioning, growth, and development. Micronutrients deficiency results due to low dietary nutrients intake and is currently a worldwide threat that affects humans in various ways, including learning or brain functioning. Sokoto State Nigeria due to its peculiarities such as arid land, poverty, poor education, single-diet nutrition, etc. should be of great risk of micronutrients deficiencies. The objective of this review paper is concerned about micronutrients deficiencies with regards to Sokoto State Nigeria and consequences on brain function. Micronutrients prevalence in Sokoto Nigeria, micronutrients in foods, insufficiency of nutrients in soil, consequences of excess micronutrients, micronutrients deficiencies, causes, etc. were described. Multifold approach to this myriad task should be put forward and tackled head-on; otherwise, the society (Sokoto) will languish continuously with maternal and child mortalities, abnormalities, mental derangements, aa well as poor productivity..
Copyright (c) 2024 Yusuf Sarkingobir https://creativecommons.org/licenses/by/4.0
Modeling a storage tank of carbon capture technology in a power plant in southern Iraq
The IEA's special study on CO2 collection, usage, and storage, released in 2020, estimates global CO2 capacity for storage to be among 8,000 and 55,000 gigatons. One of the most significant issues in introducing carbon into the energy market is improving carbon storage and developing more efficient distribution systems to increase the quantity of carbon that is held as liquid while decreasing storage pressure. The goal of this work is to investigate the efficiency of adsorption-based carbon-storing units from a "systems" perspective. The finite element approach, utilized in COMSOL Multi-physics™, is used to create an appropriate two-dimensional axisymmetric geometrical structure that balances energy, mass, and momentum based on thermodynamic extinction rules. We examine charging and discharging the storage unit with a rated pressure of 9 MPa and an initial temperature of 302 K.The storage tank is chilled using ice water. The research findings demonstrate that both simulated fluctuations in pressure and temperature during storage operations are extremely valuable. At the conclusion of charge time, the temperatures in the tank's center region are greater than those at the entry and along the wall, but at the end of discharge time, they are lower. The velocities are highest near the entry and progressively diminish throughout the tank's axis. As a result, even the lowest possible number (8,000 Gt) substantially surpasses the 100 Gt of CO2 required to be stored by 2055 under the "sustainable development" scenario. The IEA analysis also states that the land potential exceeds the offshore potential. Land-based storage capacity is estimated to be between 6,000 and 42,000 Gt, while offshore capacity is estimated to be between 2,000 and 13,000 Gt, assuming only sites less than 300 kilometers from the coast, at depths less than 300 meters, and outside the Arctic and Antarctic zones. Development of a prediction model to improve knowledge of a novel CO2 adsorbent during the adsorbent-desorption cycle, taking into account all transport events. Validation of the model against published data for H2 storage. Predicting pressure and temperature dispersion at various storage tank sites.
Copyright (c) 2024 Mustafa M. Mansour, Alaa M. Lafta, Haider Sami Salman, Sarah R. Nashee, Ahmed J. Shkarah https://creativecommons.org/licenses/by/4.0
Performance evaluation of off-grid solar systems for critical medical instruments in remote regions
In areas with limited access to electricity or during power outages, ensuring continuous and reliable use of grid-powered electrical instruments is challenging, especially in remote emergency centers. A stable source of electricity is crucial to prevent disruptions in power supply, as they can lead to severe medical complications, jeopardize patient well-being, and even result in fatal incidents. To address this issue, integrating renewable electricity sources such as off-grid solar systems into existing power supply infrastructure can be a viable solution. Recent studies suggest that off-grid solar systems can be reliable and sustainable options for powering medical facilities, particularly in areas lacking uninterrupted grid connectivity. Therefore, this research aims to evaluate the feasibility, benefits, and challenges of integrating off-grid power to support critical medical instruments. Based on an extensive literature review, interviews with experts, and surveys among relevant users, this study finds that the system has the capability to maintain a consistent, dependable power supply, even during adverse weather conditions. Cost and feasibility are highlighted as paramount considerations, based on surveys and focus group results. The study concludes that off-grid solar systems offer an economical, low-maintenance, and environmentally sustainable alternative for remote medical facilities. Finally, this study proposes recommendations to optimize critical device performance during power outages and improve overall system functionality and efficiency.
Copyright (c) 2024 Saba Shadvar, Anisur Rahman https://creativecommons.org/licenses/by/4.0
Soft computing-based modelling and optimization of NOx emission from a variable compression ratio diesel engine
Machine learning method and statistical method used for model prediction and optimization of third generation biodiesel-diesel blend powered variable compression engine High R2 values of 0.9998 and 0.9994 were observed in the training and testing phase of the model, respectively, indicating that The results confirm the robustness of the forecasting system. It was shown that the model accuracy means squared errors remained low at 0.0002 and 0.0014. These results were then confirmed by desirability-based optimization, which succeeded in achieving the values of the set parameters It should be noted that the compression ratio (CR), fuel injection pressure, and engine load were optimized to meet the defined parameters, resulting in a NOx emissions reduction as 222.8 ppm. The research illustrates the efficacy of desirability-based optimization in attaining targeted performance targets across important engine parameters whilst also reducing the impact on the environment.
Copyright (c) 2024 Prabhu Paramasivama, Khatir Naima, Marek Dzida https://creativecommons.org/licenses/by/4.0
Investigations on co-gasification and combustion characteristics of coal biomass blend as an alternative transport fuel for tri-cycles
Kenya discovered huge deposit of lignite-coal, better utilized through co-gasification to produce syngas, a clean and environmental friendly fuel, with easier application in engines. Blends of Mui-basin coal (MBC), Prosporis juliflora(PJ), Hyphanae compressa(HC) and rice husk(RH) were co-fired with resultant upgraded-syngas operating tricycle engine. Analyzed upgraded-syngas reported improved yields on combustible gases and Hydrogen/Carbon-monoxide ratio (low rank to moderate). Calorific values reported 3.2-11.2% increase. At half-load and relative to neat diesel (ND), peak-pressure improved by 31.6%(MBC-PJ), 24.0%(MBC-HC) and 14.6%(MBC-RH). Additionally, peak-pressure increases as load increases and shifts to the right of top-dead-centre with reported increase of 13.1%MBC-PJ, 15.4%MBC-HC, 18.3 % MBC-RH and 16.5 % for ND. Moreover, Net heat release rate (NHRR) in J/degree increased rapidly at 15-25oafter/TDC for all loads and also increased as the load increased with values of 33.4(HC), 26.8(ND), 28.8(RH) and 37.8(PJ) at no load and 35(HC), 27.8(ND), 30(RH), and 38.9(PJ) at full load condition. The optimal approach for sustainably utilization of MBC is through the novel fuel, in which MBC-PJ ranks the best followed by MBC-HC and lastly MBC-RH.
Copyright (c) 2024 Benson Kariuki, Paul Njogu, Joseph Kamau, Robert Kinyua, Reiner Malessa, Sameer Bachani https://creativecommons.org/licenses/by/4.0
Theoretical and simulation of central elliptical hole with rectangular plate
A study on design engineering components with slot, notches is very important, because there is a stress increases/failure region area, where the force/stress is concentrating more and more. The elastic stress concentration mainly depends on the mode of loading, materials, and geometry of the design engineering components. The design engineers, academicians, and researchers concentrated and focused on fail-safe design and safe life design. A Plate is considered with different slots, such as circular and elliptical. The main objective of this study is to find out the stress concentration factor in plates with various cutout shapes. This concept is used in design components/structures, for finding the elastic stress concentration. The methods compared are tabulated with their findings. Singularities of the circular hole and elliptical hole in rectangular plates are considered in the present study. The finite Element Method (FEM) was used for fine mesh and ANSYS WORKBENCH software was used for extracting the results and results were validated by analytical or experimental methods.
Copyright (c) 2024 M Sivaramakrishnaiah, S.N. Pradeepkumar Reddy, P. Madhu Raghava, B.V. Amaranathareddy https://creativecommons.org/licenses/by/4.0
Analysis of the surface roughness of 3D-printed occlusal splints fabricated using biocompatible resins
Nowadays, in order to promote innovation and sustainable product design and manufacturing of occlusal splints, the dental profession requires significant upgrades in the form of novel materials and cutting-edge manufacturing technologies. Researchers and Industry frontrunners are constantly challenged to improve the properties of splint developed using three dimensional scanning and resin printing to meet consumer demand, as the ability of dental practitioners to take accurate impressions remains a major obstacle in dental laboratories. The proposed study outlines a digital manufacturing process for occlusal splints created with three-dimensional scanning and resin printing. The study also analysed the occlusal splints in terms of geometrical preciseness and surface roughness along with the costs involved during 3D printing a resin-based occlusal splint. Occlusal splints were created by scanning impressions made on a typodont model and then designing them in 3D modelling software. The splints were developed in MIMICS and 3D printed to a thickness of 10 microns using Rigid white methacryalate based resin material on a 3D systems DLP Figure IV standalone resin 3D printer to create a biocompatible occlusal splint. Splint tooth height was determined for geometric analysis. Surface roughness of splintwas measured using SURFCOM surface roughness tester. Resins used in 3D printing were proven to produce geometrically precise splints, the study showed. In conclusion, UV curable resin-based occlusal splints that have been 3D printed and cured are recommended for patient usage due to their increased accuracy and the ability to save processing time.
Copyright (c) 2024 Sumit Gahletia, Ashish Kaushik, Ramesh Kumar Garg https://creativecommons.org/licenses/by/4.0
Shrimp and fish underwater image classification using features extraction and machine learning
Shrimp cultivation is one type of cultivation that has a significant impact on the social status of coastal communities. Shrimp farming traditionally faces several challenges, including water pollution, imbalances in temperature, feed, media, and costs. Monitoring the condition of shrimp in the cultivation environment is very necessary to determine the condition of shrimp in the water. Classification of shrimp and fish is the first step in monitoring the condition of shrimp underwater. This research proposes the development of a method for classifying shrimp and fish underwater using feature extraction and machine learning. The flow of this research is: (1) preparing data from ROI detection results, (2) extraction process of morphometric characteristics P and T, (3) calculating the value of morphometric characteristics P and T, (4) data breakdown for training data and testing data, (5) Model creation process, data training and data testing using SVM, RF, DT, and KNN, (6) Evaluation of classification results using a confusion matrix. From this research, it was found that the Random Forest method obtained the highest accuracy, namely 0.93. From this matrix, the values ​​obtained are True Positive = 349, False Positive = 28, True Negative = 223, False Negative = 0.
Copyright (c) 2024 Arif Setiawan, Hadiyanto Hadiyanto, Catur Edi Widodo https://creativecommons.org/licenses/by/4.0
Hyperparameter optimization for hourly PM2.5 pollutant prediction
Air pollution, particularly the presence of Particulate Matter (PM) 2.5, poses significant health risks to humans, with industrial growth and urban vehicle emissions being major contributors. This study utilizes machine learning techniques, specifically K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) algorithms, to predict PM2.5 levels. A dataset from Kaggle consisting of PM2.5 and other pollutant parameters is preprocessed and split into training and testing sets. The models are trained, evaluated, and compared using Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) metrics. Additionally, hyperparameters are applied to optimize the models. Results show that SVM with hyperparameters performs better, indicating its potential for accurate air quality prediction. These findings can aid policymakers in implementing effective pollution control strategies.
Copyright (c) 2024 Aziz, H. Hadiyanto https://creativecommons.org/licenses/by/4.0