Annual Production Research Articles

GloRESatE: A dataset for global rainfall erosivity derived from multi-source data

Numerous hydrological applications, such as soil erosion estimation, water resource management, and rain driven damage assessment, demand accurate and reliable rainfall erosivity data. However, the scarcity of gauge rainfall records and the inherent uncertainty in satellite and reanalysis-based rainfall datasets limit rainfall erosivity assessment globally. Here, we present a new global rainfall erosivity dataset (0.1° × 0.1° spatial resolution) integrating satellite (CMORPH and IMERG) and reanalysis (ERA5-Land) derived rainfall erosivity estimates with gauge rainfall erosivity observations collected from approximately 6,200 locations across the globe. We used a machine learning-based Gaussian Process Regression (GPR) model to assimilate multi-source rainfall erosivity estimates alongside geoclimatic covariates to prepare a unified high-resolution mean annual rainfall erosivity product. It has been shown that the proposed rainfall erosivity product performs well during cross-validation with gauge records and inter-comparison with the existing global rainfall erosivity datasets. Furthermore, this dataset offers a new global rainfall erosivity perspective, addressing the limitations of existing datasets and facilitating large-scale hydrological modelling and soil erosion assessments.

Investigating the Structural and Power Performance of a 15 MW Class Wind Energy Generation System under Experimental Wind and Marine Loading

The global transition to renewables in response to climate change has largely been supported by the expansion of wind power capacity and improvements in turbine technology. This is being made possible mainly due to improvements in the design of highly efficient turbines exceeding a 10 MW rated power. Apart from power efficiency, wind turbines must withstand the mechanical stress caused by wind–hydro conditions. Such comprehensive structural analysis has rarely been performed previously, especially for large-scale wind turbines under real environmental conditions. The present work analyzes the energy production and structural performance of an NREL-IEA 15 MW wind turbine using measured wind and hydro data. First of all, an optimum operating range is determined in terms of the wind speed and blade pitch angle to maximize the power coefficient. Then, at this optimum range, a detailed breakdown of the forces and moments acting on different components of the wind turbine is presented. It was found that wind speeds of 9 to 12 m/s are best suited for this wind turbine, as the power coefficient is at its maximum and the mechanical loads on all components are at a minimum. The loads are at a minimum due to the optimized blade pitch angle. The bending force on a monopile foundation (fixed on the seabed) is found to be at a maximum and corresponds to nearly 2000 kN. The maximum blade force is nearly 700 kN, whereas on the tower it is almost 250 kN. The maximum force on the tower occurs at a point which is found to be undersea, whereas above-sea, the maximum force on the tower is nearly 20% less than the undersea maximum force. Finally, seasonal and annual energy production is also estimated using locally measured wind conditions.

Functional Time Series Models for K-Step Prediction of Sugar Production: A Case Study of Eswatini, Kenya, and South Africa

Sugar, produced from cane or beet, is a vital energy source and a globally traded commodity. Most business happens in a futures exchange market where speculators, hedgers, and institutional consumers and producers, make decisions based on their understanding of the future supply and demand situation. Sugar is sometimes bought and sold before the cane or beet is planted. Hence, improving sugar production forecast accuracy is vital to maximize gains and enable effective planning. The study considered the annual sugar production total as a function of the monthly output rather than a scalar quantity and analyzed historical data using three functional time series techniques. In particular, the methods used for k-steps and dynamic updating prediction of sugar production include Local Polynomial Regression (LPR), Ridge Regression (RR), and Penalized Least Squares (PLS). The performance of the three models was compared to that of the automatic ARIMA method using the Mean Squared Error (MSE) and the Mean Absolute Percentage Error (MAPE) measures to establish the suitability of each technique in sugar production forecasting. The LPR, RR, and PLS outperformed the ARIMA method in all three cases. However, the prediction accuracy was lower for highly volatile datasets from countries that overly depend on rainfall for cane development.

Transient analysis of a near-zero energy building with green hydrogen production integrated with energy storage systems

The current study highlights the potential of hybrid renewable energy systems in mitigating CO2 emissions for a near-zero energy building. A Python-based controller is used to manage the state of charge (SoC) of the lithium-ion battery. Two buildings are considered in the study. Once the SoC in the first building reaches 75 %, the system prevents overcharging and redirects the green electricity towards the hybrid system for hydrogen production. To compare the role of a hybrid system in which a fuel cell is used to supply the required energy for electric load and electrolyzer demand, a diesel generator is considered for the same energy demands. The hybrid system achieves a 56.14 % reduction in diesel fuel consumption, leading to an annual decrease of 33.860 tons of CO2 emissions. Economic analysis reveals that while the cost of the diesel mode is calculated to be 96 % higher than the hybrid mode, the CO2 emissions in the hybrid mode will be 56.14 % lower than the full diesel mode. Additionally, the system's total annual hydrogen production is 7582.74 kg, with a maximum production rate of 15.52 m³/hr at 1.3 bar pressure. Despite higher initial costs, hybrid systems effectively address the challenge of CO2 emissions compared to conventional systems. The results underscore the necessity of hybrid systems for achieving significant reductions in fossil fuel consumption, presenting a sustainable solution for future energy needs.

Assessing a machine learning-based downscaling framework for obtaining 1km daily precipitation from GPM data

Hydro-meteorological monitoring through satellites in arid and semi-arid regions is constrained by the coarse spatial resolution of precipitation data, which impedes detailed analyses. The objective of this study is to evaluate various machine learning techniques for developing a downscaling framework that generates high spatio-temporal resolution precipitation products. Focusing on the Hai River Basin, we evaluated three machine learning approaches—Extreme Gradient Boosting (XGBoost), Random Forest (RF), and Back Propagation (BP) neural networks. These methods integrate environmental variables including land surface temperature (LST), Normalized Difference Vegetation Index (NDVI), Digital Elevation Model (DEM), Precipitable Water Vapor (PWV), and albedo, to downscale the 0.1° spatial resolution Global Precipitation Measurement (GPM) product to a 1 km resolution. We further refined the results with residual correction and calibration using terrestrial rain gauge data. Subsequently, utilizing the 1 km annual precipitation, we employed the moving average window method to derive monthly and daily precipitation. The results demonstrated that the XGBoost method, calibrated with Geographical Difference Analysis (GDA) and Kriging spatial interpolation, proved to be the most accurate, achieving a Mean Absolute Error (MAE) of 58.40 mm for the annual product, representing a 14 % improvement over the original data. The monthly and daily products achieved MAE values of 11.61 mm and 1.79 mm, respectively, thus enhancing spatial resolution while maintaining accuracy comparable to the original product. In the Hai River Basin, key factors including longitude, latitude, DEM, LST_night, and PWV demonstrated greater importance and stability than other factors, thereby enhancing the model's precipitation prediction capabilities. This study provides a comprehensive assessment of the annual, monthly, and daily high-temporal and high-spatial resolution downscaling processes of precipitation, serving as an important reference for hydrology and related fields.

Part-load analysis and preliminary annual simulation of a constant inventory supercritical CO2 power plant for waste heat recovery in cement industry

The present work investigates the part-load performance of a MW-scale sCO2 power plant designed as waste heat recovery unit for an existing cement plant located in Czech Republic, in the framework of the H2020 funded project CO2OLHEAT. The study first presents the selected power plant configuration and then focuses on the evaluation of its part-load operation due to variation of flue gas mass flow rate and temperature. The range of flue gas conditions at the outlet of the upstream process is retrieved from a preliminary statistical analysis of historical trends obtained through the cement plant monitoring. The numerical model developed for this study aims at providing realistic results thanks to the adoption of turbomachinery performance maps provided by the turbomachinery manufacturer of the project. Moreover, heat exchangers have been modelled through a discretized approach which has been validated against manufacturer data, while piping inventory and pressure losses have been assessed through a preliminary sizing that considers the actual distances to be covered in the cement plant. Performance decay is estimated for the whole range of flue gas conditions, reporting the most significant power cycle parameters, and identifying the main causes of efficiency loss. The part-load analysis is carried out considering a constant CO2 inventory, in order to reduce the system complexity and capital cost and simplify plant operation. Results show that the operation entails minor variation of the compressors operative points in the whole range of operating conditions of the cement plant, avoiding the risk of anti-surge bypass activation. Moreover, the plant is able to work close to the nominal thermodynamic cycle efficiency (20.5 %–23.0 %) for most of the year and benefits from part-load operation in terms of overall performance. In the last part of the work, a preliminary techno-economic analysis of the plant is also presented to highlight the potential advantages of sCO2 technology for waste heat recovery applications. The results of the part-load performance of the plant are combined with the flue gases data obtained from the preliminary statistical analysis and the cement plant historical monitoring. An annual electricity production equal to 13′909.7 MWh is obtained, corresponding to 6560 equivalent hours and a system capacity factor of 74.9 %. The investment cost of each CO2OLHEAT plant component is estimated by means of cost correlations obtained from literature and the non-discounted payback time is computed as a function of the electricity selling price. The results show that, even considering electricity prices before 2022, the payback time of the CO2OLHEAT plant is estimated to be lower than 8 years, justifying the industrial interest in the proposed technology.

Morphological Differentiation, Yield, and Cutting Time of Lolium multiflorum L. under Acid Soil Conditions in Highlands.

Livestock production in the basins of the northern macro-region of Peru has as its primary source pastures of Lolium multiflorum L. 'Cajamarquino ecotype' (ryegrass CE) in monoculture, or in association with white clover Ladino variety, for feeding. The objective of this research work was the morphological characterisation, yield evaluation, and cutting time evaluation of two local genotypes (LM-58 and LM-43) of Lolium multiflorum L. in six locations. An ANOVA was performed to compare fixed effects and interaction. It was determined that the LM-58 genotype is intermediate, growing semi-erect, with a dark green colouring and 0.8 cm broadleaf, and can reach an average stem length of 46 cm, up to 1.6 cm. day-1, achieving fourth-leaf growth at 28 days under appropriate management conditions. Despite the differentiated characteristics, according to BLASTn evaluation, the ITS1 sequences showed a greater than 99.9% similar identification to Lolium multiflorum L., characterising it as such. It was determined that the LM-58 genotype outperforms LM-43, achieving a forage yield of 4.49 Mg. ha-1, a seed production of 259.23 kg. ha-1, and an average of 13.48% crude protein (CP). The best biomass yield (49.10 Mg. ha-1.yr-1) is reached at 60 days; however, at 30 days, there is a high level of CP (14.84%) and there are no differences in the annual protein production at the cutting age of 60 and 45 days. With the results of the present study, LM-58 from a selection and crossbreeding of 680 ryegrass EC accessions emerges as an elite genotype adapted to the conditions of the northern high Andean zone of Peru.

Advancing towards zero emissions: Integrating floating photovoltaic systems in hydroelectric power plant reservoirs

One technological alternative to diversifying the energy matrix and reducing reliance on conventional sources involves integrating floating photovoltaics into hydropower plants. To improve the efficiency and sustainability of electricity production, this combination harnesses the benefits of solar and hydropower, thus contributing to climate change mitigation. This study proposes an assessment of the floating photovoltaics resource in water bodies associated with the 14 most important hydropower plants in Mexico. Using ERA5 reanalysis data and the assumption of a 10% coverage of the area of the water bodies, parameters such as annual energy production, avoided greenhouse gases and water savings were estimated. This was done considering two scenarios of floating photovoltaics power density, a pessimistic 30 W/m2 and an optimistic 125 W/m2. Under the conditions proposed in this work, the results of the optimistic Scenario indicate that an annual energy production of 33.12 TWh could be achieved, avoiding the emission of 14.51 MtCO2e of greenhouse gases and the evaporation of 336.78 hm3 of water.

Anticipatory Technoeconomic Evaluation of Kentucky Bluegrass-Based Perennial Groundcover Implementations in Large-Scale Midwestern US Corn Production Systems

Perennial groundcover (PGC) has promise as a scalable approach to generating natural resource benefits and sustainable biofuel feedstock while preserving the high yields of annual row crop production. Partnering row crops with temporally and spatially complementary low-growing, shallow-rooted perennials, such as Kentucky bluegrass (KBG) (Poa pratensis L.), is one example of an emerging PGC system. PGC’s ecosystem benefits can only be fully realized if commercial-scale adoption occurs, which hinges on its economic feasibility. This paper utilizes an enterprise budget framework to detail and compare the expected cost and revenue of establishing and maintaining PGC in row crop systems with standard continuous corn (SCC) (Zea mays L.) production, including stover harvest, but excluding economic incentives for ecosystem services. Optimistic and pessimistic assumptions were used, along with Monte Carlo simulation, to characterize the uncertainty in results. In the optimistic stover market scenario, Year 1 net returns for PGC averaged USD 84/ac less than for SCC; Year 2+ net returns averaged USD 83/ac more, meaning that cost parity with SCC occurs by the second PGC system year. Without stover revenue, parity is achieved after five years. These results affirm that PGC’s economic viability is critically impacted by a groundcover’s lifespan, the yield parity with SCC, and the availability of a stover market.

Needle Biomass Turnover Rate in Scots Pine Stands of Different Ages

Understanding needle biomass turnover rates in Scots pine (Pinus sylvestris L.) stands is crucial for modelling forest ecosystem dynamics and nutrient cycling. This study examined needle litterfall and biomass turnover in Scots pine stands of varying ages in temperate forests (western Poland). The research focused on determining how stand age affects needle biomass, litterfall and the associated turnover rates. Data were collected from 20 Scots pine stands aged 26 to 90 years, and needle litterfall was measured and analysed in relation to stand characteristics such as age, density and biomass. The average annual needle litter production of the sampled Scots pine stands was 2008 kg·ha−1·year−1, similar to the values previously reported for this tree species in other temperate forests in Europe. The average needle biomass turnover rate for sampled Scots pine stands was 23.4%. We could not support the hypothesis that this parameter depended on the age of the Scots pine stand. The needle biomass turnover rate showed a positive correlation with crown length and a negative correlation with stand density due to the very weak correlations; however, further research is needed to confirm these relationships. Despite this, the parameter can be used to estimate needle litterfall and can be applicable to conditions corresponding to those of temperate forests in Central and Western Europe. This study also highlights the need for further research on needle biomass turnover in temperate forests to improve the accuracy of carbon and nutrient cycling models. This work contributes to a deeper understanding of the role of needle litterfall in maintaining soil fertility and forest productivity, offering insights into sustainable forest management and conservation strategies.

Green energy and rooftop innovation: Unlocking the carbon reduction potential of photovoltaic-green roofs

As urbanization progresses rapidly, cities encounter significant environmental and energy challenges. Photovoltaic-Green Roof (PV-GR) technology offers an innovative strategy with the potential to alleviate urban carbon emissions and resource scarcity issues. However, the carbon reduction potential of PV-GR technology remains unclear. Hence, this study aims to comprehensively assess the carbon reduction potential of PV-GR. This is achieved by integrating Geographic Information Systems (GIS), lifecycle assessment, the Denitrification-Decomposition Model (DNDC), and solar simulation. Using Fuzhou City as a case study, the research indicates: (1) Fuzhou has approximately 72.9 km2 of rooftops suitable for PV-GR development, with an annual biomass production from herbaceous plants estimated at around 2.958 × 107 kg. The annual electricity production under the baseline scenario reaches 9,678 GWh, satisfying about 17 % of Fuzhou’s annual electricity demand. Moreover, in an optimistic scenario, electricity generation rises to 10,176 GWh, and even in a pessimistic scenario, it could achieve 9,471 GWh. (2) In the baseline scenario, Fuzhou’s PV-GR annual carbon reduction is estimated at 6.678 × 106 t CO2, potentially offsetting about 11.14 % of the city’s annual carbon emissions. In an optimistic scenario, this reduction increases to 7.022 × 106 t CO2, and even in a pessimistic scenario, the reduction remains significant at 6.535 × 106 t CO2. (3) Over a 30-year lifecycle, the carbon emissions from PV-GR are projected to total 3.092 × 107 t CO2, accounting for 51.34 % of Fuzhou’s annual emissions. In an ideal baseline scenario, the net carbon reduction over the lifecycle of PV-GR could total 1.703×108 t CO2, effectively offsetting 282.76 % of Fuzhou’s annual carbon emissions. Additionally, scenario simulations suggest that by 2030, potential electricity generation from PV-GR could increase to between 10,463 GWh and 10,901 GWh, due to changes in power structure and urban expansion. Overall, this study demonstrates that PV-GR holds considerable potential for carbon reduction.

Phytomass carbon pools of Koivulambisuo mire system (South Karelia)

Koivulambisuo mire system (61,80º N, 33,56º E, middle taiga subzone) has a complex structure of vegetation cover, includes south karelian variant of aapa mires, raised bogs, transitional herb-sphagnum fens and forested sites of different trophic levels.The study was carried out within the framework of the National system for monitoring carbon pools and greenhouse gas fluxes in Russia. Phytomass and carbon pools were determined for three types of mire sites: aapa, ridge-hollow sphagnum bog and oligotrophic pine-dwarf shrub-cotton grass-sphagnum. On each type of mire sites, 3 sample plots 50x50 m in size were set up, with 8–12 sampling points on each. Tree stand estimated by total count and basic measurements of all standing trees on plots, production of needles and branches by model tree method. The above-ground vascular plants phytomass material was collected by the cutting method, mosses and underground phytomass by monoliths method, the production of sphagnum mosses by annual increment method. Aapa mire extremely poorly afforested, to the least extent among the studied sites, due to strong watering and poor development of strings. The total carbon pool in a forest stand is only 0.01 tC/ha. The carbon pool in the above-ground phytomass of aapa complexes is also minimal – 2.56 tC/ha. It is mainly provided by sphagnum mosses, while herbs and shrubs contain half as much carbon in total. Living underground phytomass deposits 21.56 tC/ha (89% of the total phytomass). Such a high carbon sequestration by living underground plant organs is a feature of aapa sites and is associated with favorable regime of water movement. Some overestimation is also possible due to the difficulty of separating living and dead tightly intertwined roots. The mortmass of a 40 cm surface layer of peat soil contains 38.71 tC/ha, most of it in the sphagnum remains. The annual ground cover production of aapa is minimal: 1.55 tC/ha, which is caused by the development of extensive flarks with sparse vegetation cover. Unlike other sites, the role of vascular plants is higher here (0.68 tC/ha) due to the predominance of herbaceous plants in cover. The afforestation degree of ridge-hollow bogs varies; the living forest stand of the most afforested sites is contains 0.31 tC/ha, while in the other two, more watered sites, the pool is less than 0.02 tC/ha. The average carbon stock in a tree stand is 0.11 tC/ha. The carbon pool in the ground cover of the ridge-hollow bogs is maximum among the studied mire sites (4.25 tC/ha), the main share in it is sphagnum mosses (3.52 tC/ha), while grasses and shrubs 0.73 tC/ha. Living underground phytomass deposits 8.62 tC/ha (66% of the total phytomass).The mortmass of a 40 cm surface layer of peat soil contains, on average, 61.77 tC/ha, most of it in the sphagnum remains. In cotton grass-sphagnum hollows the stock reaches 80.09 tC/ha due to dense cotton grass tussocks. The above-ground vascular plants annual production is 0.48 tC/ha (the minimum among the studied mire site types) and 1.56 tC/ha by mosses. Pine-dwarf shrub-cotton grass-sphagnum plots have the most developed forest stands among the studied mire sites. The average tree height here is 1-2 m, individual trees reach a 5-6 m. The carbon pool in the living tree stand is 2.92 tC/ha, in dead wood – 1.66 tC/ha. Accordingly, the forest stand contribution to the total living phytomass carbon stock is maximum here and equal to moss stock. In the ground cover is deposited 4.46 tC/ha, besides sphagnum mosses (2.9 tC/ha), a significant stock in dwarf shrubs (1.11 tC/ha). Living underground phytomass deposits 9.04 tC/ha (56% of the total phytomass). The mortmass of a 40 cm surface layer of peat soil contains 63.43 tC/ha. The total contribution of pine needles and branches to the annual production is 0.04 tC/ha. The above-ground phytomass here also demonstrates the maximum annual production – 2.21 tC/ha per year, mainly provided by sphagnum mosses (1.64 tC/ha). In general, the main living phytomass carbon pools of mire sites are concentrated in the underground parts of vascular plants. The ground cover main stock is in sphagnum mosses. Significant carbon stock in the tree stands only has pine-cotton grass-dwarf shrub-sphagnum sites, where it equal to the carbon stock of mosses. In all types of sites, carbon pool in the mortmass of the upper 40 cm of the deposit are noticeably higher than the total reserves in living phytomass. The main part of the mortmass consists of the sphagnum mosses remains. Mosses are also characterized by the largest primary annual production of carbon.

Estimated economic costs of dental implants among older South Korean adults, 2015-2018.

Dental implants are a considerable financial burden for elderly people and their caregivers. This study aimed to calculate the estimated economic costs of dental implants on the Korean older population. The economic costs of dental implants for adults aged 75 years and older were estimated from a societal perspective, considering both direct and indirect expenditures. We used data from the Korean National Health Insurance Service for the period 2015-2018 to estimate the medical costs. Noninsured medical costs were estimated from research on medical expenses by the National Health Insurance Review and Assessment Service. Indirect costs related to transportation fees and time loss were obtained. The Cochran Armitage trend test was performed to examine the trend of the economic burden of dental implants. The estimated economic costs showed from 2015 to 2018 (total costs: $26.54-55.66 million, total costs after discount: $17.11-39.56 million). Direct costs, including insured and noninsured medical costs, represented from $25.81 to $47.03 million. Indirect costs, including transportation and time costs, ranged from $0.73 to $1.63 million. The impact of the total dental implant costs was 0.0018%-0.0034% of the Korean annual gross domestic product and 1.03%-1.59% of the annual total costs of dental care benefits. The estimated economic burden of dental implants significantly increased from 2015 to 2018 in older South Korean adults. These results will provide a foundation and guidance for further health economic studies on the burden of dental implants in the elderly population.

Modelling and optimization of concentrated solar power using response surface methodology: A comparative study of air, water, and hybrid cooling techniques

This research introduces a novel approach specifically designed to improve the design of Concentrated Solar Power plants utilizing the Response Surface Methodology. The objective of the suggested methodology is to enhance energy production efficiency by simultaneously minimizing the levelized cost of electricity and the land footprint associated with the power plant while comparing three different cooling techniques: air, water, and hybrid. Two software tools, System Advisor Model and Design-Expert, are employed to validate the primary model, evaluate the responses, generate the predictive models, and verify the results. The configuration of a Concentrated Solar Power plant is influenced by four main factors: the size of the solar field (solar multiple), row spacing, number of solar assemblies per loop, and size of thermal energy storage. In this study, these factors are varied within the following ranges: solar multiple from 1 to 5, row spacing from 10 to 30 m, number of solar assemblies from 4 to 10 per loop, and thermal energy storage from 5 to 15 h. The generated predictive models demonstrated very high accuracy, particularly for the annual energy production, with an error ranging between 0.2% and 1.5%. The findings showed that the hybrid cooling system is the most cost-effective cooling technique and has the highest energy output compared to the evaporative and air-cooling methods. When optimizing the required area of the hybrid cooled plant with a reduction of 47.44%, the analysis indicated a minimal decrease in energy output of 3.61% and a slight increase in the levelized cost of electricity by 0.95%. According to the results, the effect of area on the annual energy production and levelized cost of electricity is significant below the optimal area, while this effect becomes minor at higher values.

Adoption of Coffee Technologies: A Multivariate Probit Model

The sector of agriculture in Ethiopia is a source of livelihood for over 80% population residing in rural areas. It contributes about 50% to the national value of production. The country has huge potential to increase coffee production as it endowed with suitable elevation, temperature, and soil fertility, indigenous quality plantation materials, and sufficient rainfall in coffee growing belts of the country. Adoption of improved coffee varieties and recommended coffee management practice together have a significant effect on annual coffee production. The study was aimed to see the adoption rate and intensity of coffee technologies which are improved coffee Varity and coffee management practice, determinant of adoption of coffee technologies in Jima zone south western Ethiopia. A total of 196 sampled households from three woreda in the zone and 430 plots of 196 farmers household is considered in the survey. The study develops a multivariate probit model econometric model of farmers' choice of combination of coffee technologies. And two primary results were found. First, adoption rate and intensity of Improved coffee variety is greater than adoption of coffee management practice. Secondly adoption of coffee technologies determined by many institutional, resource and other related factor. This implies that policy makers and other stakeholders promoting a combination of technologies can enhance coffee yield through reducing production costs and decreasing coffee vulnerability to disease.

Recent update on cerebral sparganosis: A bibliometric analysis and scientific mapping.

Human sparganosis, a parasitic infection prevalent in Asia, can progress to cerebral sparganosis, a severe condition with significant neurological symptoms. Diagnosis and treatment are challenging due to its clinical similarity to other infections, highlighting the need for improved detection and management strategies. The aim of this study was to observe research trends, key contributors, gaps in the existing knowledge, diagnosis challenges, effective treatment options, and prevention strategies, providing recommendations for future research directions and clinical practice improvements on cerebral sparganosis. A bibliometric analysis was conducted by extracting 139 documents from the Scopus database in June 2024. The retrieved data were analyzed using the R package's Bibliometrix (Biblioshiny) and VOSviewer. Spanning 97 different sources, the research exhibited an annual growth rate of 2.5%. Annual scientific production revealed fluctuating research activity with peaks in 2010 and 2011 and notable citation peaks in 1996 and 2005, indicating pivotal studies that significantly influenced subsequent research. Early studies focused on diagnosis and specific parasites, while recent studies (2010-2024) have increasingly addressed clinical outcomes, treatment strategies, and advanced diagnostic techniques. Trends revealed a shift towards clinical and diagnostic advancements, with recent emphasis on diagnostic imaging, immunoassays, and the relationship between cerebral sparganosis and brain tumors. In conclusion, the studies on cerebral sparganosis underscore the potential for enhancing clinical practice by improving diagnostic accuracy, informing treatment decisions, and implementing targeted screening efforts based on epidemiology and risk factors. Recommendation to further study needs to notify the cerebral sparganosis in high-risk countries with similar socioeconomic and cultural characteristics to endemic regions, including Indonesia.

Enhancing the commercial viability of commercial algal bioethanol production: The role of technological advancements

Malaysia's economic growth relies on depletable fossil fuels that raise atmospheric CO2. Accordingly, researchers search for sustainable fuels that sequester significant levels of CO2. Chlorella vulgaris meets these criteria, but high production costs hamper its adoption. The hypothesis is that technological advances improve the commercial viability of algal bioethanol. A large-scale agricultural model is modified to study algal cultivation. Algal bioethanol becomes competitive if algal producers experience an annual 2 % harvest yield gain or a 3 % annual production cost reduction. Algal bioethanol is predicted to produce 4249.21 megalitres in 2059 for harvest yield gains. It sequesters 9.72 megatons of CO2-equivalent tailpipe emissions and 12.78 megatons of flue gas in 2059. Meanwhile, production cost reductions yield 1607.61 megalitres in 2064. It sequesters 3.68 megatons of CO2-equivalent tailpipe emissions and 10.68 megatons of flue gas in 2059. Thus, the hypothesis is supported that technological advancements improve the commercial viability of algal bioethanol.

FLUID FLOW MODEL BASED ON THE ANALYSIS OF WATER INJECTION DATA IN THE TURONIAN RESERVOIR OF THE LIAWENDA FIELD, OFFSHORE COASTAL BASIN OF D.R. CONGO

Arranged the hydrocarbons in an oil reservoir require several techniques for their exploitation. The Liawenda field, discovered in December 1971 following the drilling of the Liawenda-01 exploration well, has a total of 186 wells with an annual production of 3,009,553 barrels. Having started production several years ago, the field has used the water injection technique following a drop in pressure. Despite this recourse to water injection methods, production from the Liawenda field is not always satisfactory. Knowledge of fluid flow inside an oil reservoir is important because it enables us to estimate certain useful parameters that can determine fluid movements in order to identify the causes of excessive water production. Thus, the present paper deals with water injection data in order to understand fluid movements in the Turonian reservoir of the Liawenda Field: - What is the fluid movement like in the Turonian reservoir of the Liawenda Field? - How does water move in relation to oil? - What are the efficiencies of fluid movement within the Liawenda Field? - What is the speed and travel time of the fluids in this reservoir? - How mobile are fluids?

Impact Assessment of Integrated Pest Management Technology on Kharif Paddy Cultivation in Vidarbha Region of Maharashtra, India

The Eastern Vidarbha region consist of Bhandara, Gondia, Gadchiroli and Chandrapur and some part of the Nagpur district is famous for specialized farming and paddy as major crop. The total area in Maharashtra state was 15.53 lakh hectares with annual production 34.81 lakh tons of rice (Anonymous 2023-24). About 80.00 per cent gross cropped area in this region is under paddy. IPM has been proved to be a cost minimization technique. Losses in Paddy yield the tune 10 to 25 per cent occurs due to attack of insect pest and disease. Being the topic of such high importance from cultivators point of view, the research topic has been selected i.e. Impact Assessment of Integrated Pest Management technology on Kharif Paddy cultivation in Vidarbha region of Maharashtra State its economic investigation in different level of adoption of IPM technologies. The study was carried out with the main goals of determining the extent to which recommended technology has been adopted in Kharif paddy production by using principle component analysis approach and for develop the composite index, examining the input utilization of Kharif paddy at varying levels of IPM adoption, and workout cost effectiveness and profitability of kharif paddy at different level of adoption of IPM technology. The study was conducted in the districts of Gadchiroli in the Vidarbha region of Maharashtra State, India. Three tahasil, Gadchiroli, Chamorshi and Dhanora were chosen from these districts, and a total of 120 farmers were selected from seven villages, namely Gadchiroli, Indala, Hirapur, Chamorshi, Krishna Nagar, Heti, Kanartola. The primary data, which cover the years 2023–2024. Total 120 farmers, 25 farmers were classified as high adopters, 76 farmers were classified as medium adopters, and 19 farmers were classified as low adopters. As a result of input usage, the group with a high adoption level utilized the most human labour. Farmyard manure is used most in the high adopter group (49.87 quintal per hectare), followed by low adopters (31.73 qtl/ha) and medium adopters (34.45 qtl/ha) because the farmers can apply only owned farm FYM. The reasons of lower used of FYM, due to shortage of cattle’s population. The reasons of low adopter, high expenditure of Integrated pest management components was the 89.00 per cent farmers can use chemically control that means 2 to 3 spraying was use in kharif paddy in low adopter group. The B:C ratio at Cost ‘A1’ was 1.79, 1.85 and 1.92 in low, medium and high adopters, respectively, while B:C ration at Cost ‘C2’ for low, medium, high adopter were 1.12,1.19,1.25 respectively. The results concluded that the low adopters group are not making more profit. It indicates that, as adoption of technology increases the yield level of crop and so that the net returns also increases. The reduction in per quintal production cost at Cost ‘C2’ over low adopter group were Rs. 188.06/-. Paddy productivity has been reported increased by 19.84 per cent with the reduction in the cost of Rs. 7375.89 in high level of adoption of Integrated Pest Management Technology. The findings of the present study with regards to overall adoption of integrated pest management practices of paddy by paddy growers were observe for wide adoption of IPM technology in Kharif Paddy, Government should take initiative for production of bio-agents and available the pheromane trap and yellow sticky trap through establishing unit in Government Agricultural Offices and Krishi Vigyan Kendra and encourage the rural youth for establishing Units at taluka level.

Analysing the prospects of grid-connected green hydrogen production in predominantly fossil-based countries – A case study of South Africa

Importing substantial amount of green hydrogen from countries like South Africa, which have abundant solar and wind potentials to replace fossil fuels, has attracted interest in developed regions. This study analyses South African strategies for improving and decarbonizing the power sector while also producing hydrogen for export. These strategies include the Integrated Resource Plan, the Transmission Development Plan, Just Energy Transition and Hydrogen Society Roadmap for grid connected hydrogen production in 2030. Results based on an hourly resolution optimisation in Plexos indicate that annual grid-connected hydrogen production of 500 kt can lead to a 20–25% increase in the cost of electricity in scenarios with lower renewable energy penetration due to South African emission constraints by 2030. While the price of electricity is still in acceptable range, and the price of hydrogen can be competitive on the international market (2–3 USD/kgH2 for production), the emission factor of this hydrogen is higher than the one of grey hydrogen, ranging from 13 to 24 kgCO2/kgh2. When attempting to reach emission factors based on EU directives, the three policy roadmaps become unfeasible and free capacity expansion results in significant sixteen-fold increase of wind and seven-fold increase in solar installations compared to 2023 levels by 2030 in South Africa.