Photocatalytic processes offer promising solutions for environmental remediation and clean energy production, yet their efficiency under visible light remains a significant challenge. Here, we report a novel silver-graphene (Ag-G) modified TiO2 (Ag-G-TiO2) nanocomposite photocatalyst that demonstrates remarkably enhanced photocatalytic activity for both dye wastewater degradation and hydrogen production under visible and UV light irradiation. Through comprehensive characterization and performance analysis, we reveal that the Ag-G modification narrows the TiO2 bandgap from 3.12 eV to 1.79 eV, enabling efficient visible light absorption. The nanocomposite achieves a peak hydrogen production rate of 191 μmolesg-1h-1 in deionized water dye solution under visible light, significantly outperforming unmodified TiO2. Intriguingly, we observe an inverse relationship between dye degradation efficiency and hydrogen production rates in dye solutions with tap water versus deionized water, highlighting the critical role of water composition in photocatalytic processes. Our findings demonstrate sustained hydrogen production under visible light and rapid initial rates under UV irradiation, underscoring the versatility of Ag-G-TiO2 catalyst. This work not only advances our understanding of fundamental photocatalytic mechanisms but also presents a promising material for solar-driven environmental and energy applications, potentially contributing to the global transition towards sustainable technologies.

The achievement of size uniformity and monodispersity in perovskite quantum dots (QDs) requires the implementation of precise temperature control and the establishment of optimal reaction conditions. Nevertheless, the accurate control of a range of reaction variables represents a considerable challenge. This study addresses the aforementioned challenge by employing manganese (Mn) doping to achieve size uniformity in CsPbBr₃ perovskite QDs without the necessity for precise control of the reaction conditions. By optimizing the Mn:Pb ratio, it is possible to successfully dope CsPbBr₃ QDs with appropriate concentrations of Mn²⁺ and achieve a uniform size distribution. The spectroscopic measurements on single QDs indicate that the appropriate Mn²⁺ concentrations can result in a narrower spectral linewidth, a longer photoluminescence (PL) lifetime, and a reduced biexciton Auger recombination rate, thus positively affecting the PL properties. This study not only simplifies the size control of perovskite QDs, but also demonstrates the potential of Mn-doped CsPbBr₃ QDs for narrow linewidth light-emitting diode applications.

In recent years, machine learning (ML) techniques have emerged as an efficient and effective technology within the petroleum industry. This paper focuses on the current application of ML in enhanced oil recovery (EOR) through CO2 injection, which exhibits promising economic and environmental benefits of climate-change mitigation strategy. Our comprehensive review explores the diverse use cases of ML techniques in CO2-EOR, including aspects such as minimum miscible pressure (MMP) prediction, well location optimization, oil production and recovery factor prediction, multi-objective optimization, Pressure-Volume-Temperature (PVT) properties estimation, Water Alternating Gas (WAG) analysis, and CO2-foam EOR, from 101 reviewed papers. In this comprehensive review, we catalog relative information, including the input parameters, objectives, data sources, train/test/validate information, results, evaluation, and rating score for each area based on criteria such as data quality, ML building process, and analysis of results. We also briefly summarized the benefits and limitations of ML methods in petroleum industry applications. Our detailed and extensive study could serve as an invaluable reference for employing ML techniques in the petroleum industry. Based on the review, we found that ML techniques offer great potential in solving problems in the majority of CO2-EOR areas involving prediction and regression. With the generation of massive amounts of data in the everyday oil and gas industry, machine learning techniques can provide efficient and reliable preliminary results for the industry.

Abstract Introduction: Despite the determination to succeed in eliminating neglected tropical diseases, these have been increasing within certain endemicities, particularly in depriving region. Objective: This study aimed to assess the relative burden of neglected tropical diseases in rural and urban slum settings in Eastern Ethiopia. Methods: A comparative cross-sectional study was conducted from February 25 to April 30, 2024 with a multistage random sampling technique used. A survey tool with the integration of the spectrum was employed. Data were entered using Epi-Data version 3.1 and analyzed using STATA 16. Descriptive statistics and multivariable logistic regression analysis was used to identify the risk factors and the level for statistical significance was declared at p-value < 0.05 with 95 % CI. Result: The response rate was 93 % and the mean age of house heads was 31.6 (Range; 18. 63) with 5.7 average family size. The overall prevalence of NTDs among study participants was 22.6 % (95% CI; 20.2, 25.2); urban slum it was 15 % (95% CI; 12.2, 18.4) while it was 29.8 % (95% CI; 26, 33.9) in rural. Though there is no statistically significant difference, the relative prevalence of NTDs in rural to urban was two. The multivariable analysis provided that the risk factors associated with NTDs were government employment (AOR: 12.5 (1.17, 132.4)), good income (AOR: 0.13 (.03, 0.57)), Child playing with soil (AOR: 5.8 (1.52, 22.0)); child hand washing at critical times ( AOR: 11.2 (1.7, 74.9)), presence of flies in the child faces (AOR: 20.3 (4.7, 88.6)) and type of drinking water sources (AOR: 0.11 (0.02, 0.73)). Conclusion: the burden of NTDs was moderate in the study area dominated by STH, Trachoma, and scabies. Socio economic and WASH factors were found to be associated with NTDs. Collaborated efforts among stakeholders are crucial to prevent and control NTDs.

Amazon tropical forest is actually subject to strong deforestation, generally originated from illegal logging, resulting in ecological, environmental and economic problems. Aiming stop deforestation and timber commercialization of illegal logging of tropical forest, new laws has been introduced in many countries. Here we investigated the utility of DNA fingerprinting of nuclear and cytoplasmatic SNPs to timber tracking the intensive logged and commercialized of the Amazonian Neotropical tree Jacaranda copaia. Samples of 832 individuals from 43 populations from Bolivia, Brazil, French Guiana, and Peru were used to investigate the power of 113 nuclear SNPs, 11 CpSNPs, and four MtSNP loci to determine the country and population origin. The genetic differentiation among all populations and contries was high (0.233–0.942), specialy for CpMtSNP (generally>0.6) loci, and there is a strong isolation by distance pathern among populations, favoring the group or individual samples tracking to correct site. For self-assignment tests, we were able to 100% correct determine country and population origin of all samples using all SNPs. Our results show that the use of 128 SNP markers is suitable to correct determination of country and population site of J. copaia timber origin and very useful tool for customs and local and international policies.

Tropical cyclones (TC) are dangerous weather events and accurate monitoring and forecasting can provide significant early warning to reduce loss of life and property. However, the study of tropical cyclone intensity remains challenging, both in terms of theory and forecasting. ERA5 reanalysis is benchmark data set for tropical cyclone studies, yet the maximum wind speed error is very large (68 kts) and still 19 kts after simple linear correction even in the better sampled North Atlantic. Here, we develop an adaptive learning approach to correct the intensity in the ERA5 reanalysis, by optimising the inputs to overcome the problems because of the poor data quality and updating the features to improve the generalisability of the deep learning-based model. Specifically, we use TC knowledge to increase the representativeness of the inputs so that the general features can be learned with deep neural networks in the sample space, and then use domain adaptation to update the general features from the known domain with historical storms to the specific features for the unknown domain of new storms. This approach can reduce the error to only 6 kts which is within the uncertainty of the best track data in IBTrACS in the North Atlantic. The method may have wide applicability, such as extending it to the correction of intensity estimation from satellite imagery and intensity prediction from dynamical models.

Super Typhoon Saola came very close to Hong Kong on 1 and 2 September 2023, necessitating the issuance of No. 10 hurricane signal, the highest tropical cyclone warning signal, in Hong Kong. While there were widespread damages in Hong Kong, no people were killed in the event with effective early warning. It is rare that a super typhoon came very close to Hong Kong and this paper is the first part in the series of the documentation of Saola to summarize the interesting observations of Saola near Hong Kong for future reference by weather forecasters, including sur-face observations, upper air observations, microburst alert from weather radars, and turbulence intensity based on spectral width measurement of radars.

Cashew (Anacardium occidentale) processing generates a by-product (CB) with potential for health benefits and could be a favorable ingredient to be added to a probiotic food matrix. This study aimed to assess the functional attributes of CB in fermented milk with a probiotic and a starter culture using in vitro- gastrointestinal conditions. Using a standardized fermentability assay, two strains more adapted to the dehydrated CB were chosen and applied in: Test Formulation (TF, with CB) and Control Formulation (CF, without CB). TF and CF were fermented by the probiotic strain Lacticaseibacillus paracasei subsp. paracasei F19® and the starter Streptococcus thermophilus ST-M6®. During a 28-day refrigerated (6-8 °C) shelf-life study, both strains used in CF and TF were resistant and maintained a population above 8.0 log CFU/mL in the fermented milk. TF had significant increase in total phenolic compounds and greater antioxidant potential during shelf life, along with improved survival of F19® after in vitro-simulated gastrointestinal conditions. The cashew by-product revealed to be promising as a substrate for the strains studied and the presence of CB increased the content of phenolics and antioxidant activity during storage, as well as the gastric resistance to the probiotic., leading to a promising healthy product.

In many tropical regions, national forests plantations programs have been promoted. Those plantations contribute frequently to habitat changes. However, it is unclear associated effects on habitat fragmentation and landscape connectivity. From 2008 to 2018, we examined plantation and deforestation data base of Manabí province (Ecuador) for assessing fragmentation and connectivity. At regional scale, forest plantations had a significant effect on land uses changes and fragmentation during the study period. Forests decreased from 33.7% to 32.45% between 2008 and 2018 in the study area, although other natural land uses, mostly shrubs, increased almost double (from 2.4% to 4.68%). Most of the deforestation affected native forests during this period, and most of reforested and afforested areas in 2018 covered former agricultural land. In this period, fragmentation data shows a decrease in the number of patches and an increase in patch average size. When considering reforestation, deforestation was higher than the afforested area (58 km2 of difference) increasing the number of patches but with smaller size. The scenarios that presented better connectivity were those where forest areas increased: avoiding deforestation and considering reforestation. Those scenarios had in general a higher number of links and distance. Regionally, the avoiding deforestation scenario increased connectivity for Puma yagouaroundi in the west part of the Manabí province. On the other hand, for the reforested scenario, the number of links also increased on central and extreme northeast areas. Our findings suggest that plantations may contribute to conservation thanks to an increase in forest plantations connectivity between fragmented patches.

The uptake of buildings employing cross-laminated timber (CLT) assemblies and designed to Passivhaus standard has accelerated internationally over the past two decades due to several factors including design responses to the climate crisis by decarbonising the building stock. Structural CLT technology and the voluntary Passivhaus certification both show measurable benefits in reducing energy consumption, while contributing to durability and indoor comfort. However, there is a general lack of evidence to support a fast uptake of these technologies in Australia. This paper responds to the compelling need of providing quantitative data and adoption strategies, it explores their combined application as a potential pathway for climate-appropriate design of energy-efficient and durable mass timber envelope solutions for subtropical and tropical Australian climates. Hygrothermal risk assessments of interstitial condensation and mould growth of CLT wall assemblies inform best-practice design of mass timber buildings in hot and humid climates. This research found that the durability of mass timber buildings located in hot and humid climates may benefit from implementing the Passivhaus standard to manage interior conditions. The findings also suggested that climate-specific design of the wall assembly is critical for mass timber buildings, in conjunction with excellent stormwater management practices during construction and corrosion protection for metallic fasteners.

Our study analyzes the ecology and distribution of fish communities related to the environmental variables of the Alto Madre de Dios River, an Andean-Amazon watershed of southern Peru, between 300 and 2811 m a.s.l. within the Manu Biosphere Reserve. We provide new ecological and diversity data for these highly unknown rivers and new data for palm swamp habitats. With electric fishing techniques, we collected a total of 1934 fish specimens belonging to 78 species, 42 genera and 15 families. To assess main patterns of diversity we combined SIMPER and ANOSIM with canonical correspondence analysis to obtain an overview of the community structure of fish and their distribution related to aquatic habitats. Our results show an important shift on fish diversity at 700 m a.s.l. separating headwater and middle-lowland communities. Electrofishing was a hindrance due to the depth, flow and low conductivity of the rivers, but also allowed us to capture fish not observed with other techniques. We also compared the use of elevation with slope as an alternative variable for statistical analysis. Our results show that slope offers a solid and equivalent explanation for fish distribution variability, avoids redundance, and instead of giving geographical data offers ecologically solid information.

Evaluation of the effectiveness of protected areas is critical for forest conservation policies and priorities. To evaluate their effectiveness, we used 30-m resolution forest cover change data between 1990 and 2010 for ~4,000 protected areas and analyzed the relationships of the effectiveness of protected areas with socio-economic variables. Our results show that protected areas in the Tropics avoided 83,500 ± 21,200 km2 of deforestation during the 2000s. Brazil’s protected areas have the largest amount of avoided deforestation of 50,000 km2. We also show the amount of international aid received by tropical countries compared to the effectiveness of protected areas. International aid had major benefits in Latin America led by Brazil while tropical Asian countries used the resource ineffectively. Our results demonstrate that protected areas have been relatively more efficient in countries where deforestation pressures were increasing, and governance and forest change monitoring capacity are important factors for enhancing the efficacy of international aid.

We enriched and isolated a novel gammproteobacterial methanotroph; strain FWC3, from tropical freshwater wetland, near Nagaon beach, Alibag, India. FWC3 is a coccoid, flesh pink/peach pigmented, non-motile methanotroph and the cells are present in pairs and as tetracocci. The culture can grow on methane (20%) as well as on a wide range of methanol from concentrations (0.02%-5%). Based on the comparison of genome data, FAME analysis, morphological characters and biochemical characters, FWC3 belongs to the tentatively and newly but not validly described genus ‘Methylotetracoccus’ of which only a single species strain was described, Methylotetracoccus oryzae C50C1. The ANI index between FWC3 and C50C1 strains is 94%, and the DDH value is 55.7%, less than the cut-off values 96% and 70%, respectively. The genome size of FWC3 is smaller (3.4 Mbp) compared to that of C50C1 (4.8 Mbp). Additionally, the FAME profile of FWC3 shows differences in cell wall fatty acid profiles compared to Methylotetracoccus oryzae C50C1. Also, there are other differences on the morphological, physiological and genomic levels. We propose FWC3 to be a member of a novel species of the genus Methylotetracoccus, for which the name Methylotetracoccus aquaticus is proposed. Also, an amended description of the genus Methylotetracoccus gen. nov. is given here. FWC3 is available in two international culture collections with the accession numbers: MCC 4198 (Microbial Culture collection, India) and JCM 33786 (Japan Collection of Microorganisms, Japan).

Having sustained, over the course of more than two decades, record-breaking natural catastrophe losses, American insurers and reinsurers are justifiably questioning the potential linkage between anthropogenic climate change and extreme weather. Here, we explore issues pertaining to this linkage, looking at both the likely short-term implications for the insurance industry, as well as potential longer-term impacts on financial performance and corporate resilience. We begin our discussion with an overview of the implications that climate change is likely to have on the industry, especially as it relates to how catastrophic risks are construed, assessed, and managed. We then present the rudiments of an econometric analysis that explores the financial resilience of the property/casualty (P/C) industry in the face of both natural and man-made catastrophes. In this analysis, we explore the profitability consequences of several illustrative scenarios involving large-scale losses from extreme weather—specifically, a sequence of storms like those striking the U.S. in 2004—and a scenario that explores the prospect of a Katrina-scale storm in combination with a mass terror attack on the scale of 9/11. At systemic levels of aggregation, our analysis suggests a high degree of macro-resilience for the insurance industry. Moreover, we find that insurer resilience is higher for larger impacts, considering both the speed of recovery, as well as the inverse of the area under the unaffected system profile. We conclude with a summary of our findings and a closing commentary that explores the potential implications of these results for P/C insurers moving forward.

Understanding the role of invasive species in ecosystem functioning represents one of the main challenges in ecology. Pteridium aquilinum is a successful cosmopolitan invasive species with negative effects on the ecological mechanisms that allow secondary succession. In this study we evaluated whether P. aquilinum favours the establishment of alternative states, as well as the effect of recovery strategies on the secondary succession. A random stratified sampling was established with three treatments, each one with at least 50 year of fern invasion and with variations on the periodicity of fires and cuttings (chapeos) vs one control without fern bracken We determined the species richness and composition, as well as the relative importance value (IVI) in each treatment. We found that P. aquilinum decreases the action of the mechanisms that allow secondary succession, particularly facilitation. The recovery strategies consist in monthly cuttings and control fires allow to recover the secondary succession and eventually, the regeneration of areas invaded by P. aquilinum. Our study has relevant implications on the ecology of alternative state, and in practical strategies to maintain tropical forests, as well as for the maintenance of environmental services and sustainability.

Towards the investigation and further understanding of the development and propagation of Medicanes, this study explores the forecasting capability of WRF model in case of cyclone “Cleopatra” which affected with extreme rainfall and strong winds Sardinia and Calabria, Italy, in November 2013. This cyclone was unusual in that it developed a warm core but did not fulfill its transformation into a tropical-like cyclone because its core did not expand high enough in the tropospnere. The ERA5 reanalysis dataset was dynamically downscaled from 31 km spatial horizontal resolution to 9 km using WRF model. The methodology consists of; firstly, an extensive physical parameterization schemes sensitivity test and consequently, a short-range ensemble forecasting implementation based on the highest statistical scored physics configuration. All simulation results were validated against surface observations and remote sensing products. Subsequently, the modeled cyclone trajectories are compared to satellite imagery derived from EUMETSAT-SEVIRI gridded data. The findings of the conducted analysis illustrate that ensemble average displays significant difference in performance compared to any of the deterministic runs individually, suggesting that ensemble forecasts will be beneficial in studies assessing cyclonic events in the Mediterranean region.

Marine water pH is becoming progressively reduced in response to atmospheric CO2 elevation. Considering that marine environments support a vast global biodiversity and provide a variety of ecosystem functions and services, monitoring of the coastal and intertidal water pH assumes obvious significance. Because current monitoring approaches using meters and loggers are typically limited in application in heterogeneous environments and are financially prohibitive, we sought to evaluate an approach to acidification biomonitoring using living gastropod shells. We investigated snail populations exposed naturally to corrosive water in Brunei (Borneo, South East Asia). We show that surface erosion features of shells are generally more sensitive to acidic water exposure than other attributes (shell mass) in a study of rocky-shore snail populations (Nerita chamaeleon) exposed to greater or lesser coastal geochemical acidification (acid sulphate soil seepage, ASS), by virtue of their spatial separation. We develop a novel digital approach to measuring the surface area of shell erosion. Surficial shell erosion of a muddy-sediment estuarine snail, Umbonium vestiarium, is shown to capture variation in acidic water exposure for the timeframe of a decade. Shell dissolution in Neripteron violaceum from an extremely acidic estuarine habitat, directly influenced by ASS inflows, was high variable among individuals. In conclusion, gastropod shell dissolution potentially provides a powerful and cost-effective tool for rapidly assessing marine pH change across a range of spatial and temporal frameworks and coastal intertidal environments. We discuss caveats when interpreting gastropod shell dissolution patterns.

Recently, Shehata et al. [37] introduced the r+1Rs(B;C; z) matrix function and established some properties. The aim of this study established to devote and derive certain basic properties including analytic properties, recurrence matrix relations, dierential properties, new integral representations, k- Beta transform, Laplace transform, fractional k-Fourier transform, fractional integral properties, the k-Riemann{Liouville and k-Weyl fractional integral and derivative operators an extended version of r+1Rs;k matrix function. We establish its relationships with other well known special matrix functions which have some particular cases in the context of three parametric Mittag-Leer matrix function, k- Konhauser and k-Laguerre matrix polynomials. Finally, some special cases of the established formulas are also discussed.

The study evaluates the toxic effects of acute and sub-acute oral administration of methanol extracts of Geophila obvallata in rats. During acute study, a dose of 1600, 2900 and 5000 mg/kg bw of extract was orally administered to rats. Rats were observed for signs of toxicity for two weeks. During sub-acute study (28 days), the extract, at doses of 100, 500 and 1000 mg/kg bw were administered orally to rats while control rats were given only tap water. At the end of the study, samples were collected for analyses. In acute toxicity studies, the extract did not induce death after single dose administration. Hence, the LD50 was estimated above 5000mg/kg. The results of sub-acute toxicity study show that no significant changes were observed in the body weights, organ weights, kidney function and organ histology. There were significant changes in hematology and biochemical indices investigated at elevated doses of 500 and 1000 mg/kg bw compared to the control. GOE may be considered non-toxic at a dose of 100 mg/kg with promising applications in drug therapy.

Pollution of sub-surface water reservoirs mainly rivers and streams through contaminated water point sources (CWPS) was studied. The objective was to formulate a discrete time delay mathematical model which describes the dynamics of reservoir pollution using mixing-problem processes that involve single species contaminants such as nitrates, phosphorous and detergents. The concentration of pollutants was expressed as a function of the inflow and outflow rates using the principle for the conservation of mass. Systems of ODEs generated from principles of mixing problems were refined into a system of DDEs so that the concentration of pollutant leaving the reservoir at time would be determined at some earlier instant, for the delay. The formulated model is a mathematical discrete time delay model which would be used to describe the dynamics of sub-surface water reservoir pollution. The results from the validation of the model were analyzed to determine how time delays in the mixing processes affect the rate of particle movement in water reservoirs.

In sub-Saharan Africa (SSA), cervical cancer is a critical public health issue; it is the second leading cause of cancer among women and the leading cause of female cancer deaths. Incidence and mortality rates are substantially higher than in high-income countries with population-based screening programs, yet implementing screening programs in SSA has so far proven to be challenging due to financial, logistical and sociocultural factors. Human Papillomavirus (HPV) vaccination is an effective approach for primary prevention of cervical cancer and presents an opportunity to reduce the burden from cervical cancer in SSA. With a number of SSA countries now eligible for GAVI support for vaccine introduction, it is timely to consider the factors that impede and facilitate implementation of vaccine programs in SSA. This article reviews the epidemiological and clinical features of cervical cancer in SSA and describes the current status of HPV vaccine implementation in SSA countries. The review considers the challenges that will need to be addressed, and effective approaches to the design and implementation of HPV vaccination programs, using Rwanda as a case study. The review aims to provide suggestions and guidance to those involved in the development and implementation of HPV vaccination programs in SSA.

Abstract: In this study the semi-distributed model SWAT (Soil and Water Assessment Tool), were applied to evaluate stream flow of Didessa sub basin, which is one of the major sub basins in Abay river basin of Ethiopia. The study evaluated the quality of observed meteorological and hydrological data, established SWAT hydrological model, identified the most sensitive parameters, evaluated the best distribution for flow and developed peak flow for major tributary in the sub basin. The result indicated that the SWAT model developed for the sub basin evaluated at multi hydro-gauging stations and its performance certain with the statistical measures, coefficient about determination (R2) and also Nash coefficient (NS) with values ranging 0.62 to 0.8 and 0.6 to 0.8 respectively at daily time scale. The values of R2 and NS increases at monthly time scale and found ranging 0.75 to 0.92 and 0.71 to 0.91 respectively. Sensitivity analysis is performed to identify parameters those were most sensitive for the sub basin. CN2, GWQMN, CH_K, ALPHA_BNK and LAT_TIME are the most sensitive parameters in the sub basin. Finally, the peak flow for 2-10000 returns periods were determined after the best probability distribution is identified in EasyFit computer program.

Leishmaniasis is the second deadliest parasitic disease in the world, after malaria, with an estimated 1.6 million new cases each year. While cutaneous leishmaniasis can result in permanent scars from lesions after treatment, the mucocutaneous and visceral diseases can result in life-altering and life-threatening complications. Mucocutaneous leishmaniasis can lead to permanent facial disfigurement and destruction of airways, while the visceral form is nearly 100% fatal if left untreated, as parasites spread into internal organs. Accurate species diagnosis which can be predictive of future disease is critical for treatment and follow-up. PCR-based diagnostics can provide sensitive detection of parasites and identify the species, but are slow, expensive, and not suitable for low-resource environments. In this publication, we describe our efforts to develop a simple, affordable, and instrument-free leishmania DNA diagnostic that can be used in both high-tech settings and the field. We have developed methods for parasite lysis, RPA amplification of DNA, and CRISPR crRNA detection for all leishmania species as well as specific identification of L. panamensis as a predictor of mucocutaneous disease. We have demonstrated the ability to detect single-digit parasites without compromising the specificity in identifying single species. In tube analysis of individual assays were carried out in succession culminating in un-quenched fluorescent signal quantifiable over negative control. The described work is the foundation which will be implemented into a three-track [all leishmania, mucocutaneous or visceral only, and a human positive control] assay that we plan to utilize in a Funnel Adapted Sensing Tube (FAST) single use, instrument free, and affordable diagnostic.

Visceral leishmaniasis (VL), or kala-azar, is a severe and potentially fatal form of leishmaniasis, a disease classified under Neglected Tropical Diseases (NTDs). VL primarily affects the internal organs, with symptoms ranging from chronic fever and weight loss to hepatosplenomegaly and anemia. The disease is transmitted by sandflies, with Leishmania donovani and Leishmania infantum being the primary pathogens. Despite various treatment options like liposomal amphotericin B and miltefosine, challenges remain due to drug toxicity, high costs, and limited availability. Alternative therapeutic approaches, particularly those involving phytocompounds, offer promising potential for overcoming these limitations and improving outcomes for affected populations.

The rapid urbanization process in recent decades has altered the carbon cycle and exacerbated the impact of climate change, prompting many cities to develop tree planting and green area preservation as mitigation and adaptation measures. While numerous studies have estimated the carbon stocks of urban trees in temperate and subtropical cities, data from tropical regions, including tropical botanic gardens, are scarce. This study aimed to quantify the aboveground biomass and carbon (AGB and AGC, respectively) stocks in trees at the Rio de Janeiro Botanical Garden arboretum, Rio de Janeiro, Brazil. Our survey included 6793 stems with a diameter at breast height (DBH) ≥ 10 cm. The total AGB was 8,047.24 Mg, representing 4,023.62 Mg of AGC. The AGB density was 207.4 Mg.ha-1 (AGC = 103.7 Mg.ha-1), which is slightly lower than the density stored in Brazil's main forest complexes: the Atlantic and Amazon forests, but much higher than in many cities worldwide. Our results suggest that, in addition to their global importance for plant conservation, tropical botanic gardens could function as significant carbon sinks within the urban matrix.

The accurate estimation of biomass carbon in forests is of paramount importance for effective forest management and mitigating climate change. This study presents a novel approach to produce a high-resolution map of biomass carbon over forests in Malaysia using the Aboveground Carbon Density Indicator (ACDI) and a comprehensive collection of 12 years of inventory data, i.e., from 2012 to 2023. The ACDI was derived based on several vegetation indices (VIs) that were produced from the original Landsat images to indicate the level of aboveground biomass carbon (AGC) stock in the forested areas. The VIs includes Normalised Difference Vegetation Index (NDVI), Normalised Burn Ratio (NBR), Shadow Index (SI), Soil-Adjusted Vegetation Index (SAVI), Iron Oxide Index (IO), Modified Normalised Difference Water Index (NDWI), and Enhanced Vegetation Index (EVI). The ACDI was then integrated with ground-based measurements, and serves as a robust indicator for estimating AGC. This calculation was conducted on Google Earth Engine (GEE) platform to match the date of field observation with the satellite imagery datasets. The production of seamless mosaic of the latest date of Landsat imagery and the forest type classification were also performed on GEE. The forested areas were classified into three major types, which are dry inland forest, mangrove forest, and peat swamp forest. Results indicated significant spatial variations in AGC across Malaysia's forests. The derived AGC prediction models based on the ACDI varied among the forest types. Based on the estimates, a 30-metre resolution, wall-to-wall map of AGC across the entire forested region of Malaysia has been created. The ACDI was calibrated and validated using a separate validation plots dataset to ensure the accuracy of the AGC estimates. The total AGC in all types of forests in Malaysia was estimated at 3.0 billion Mg C with an attainable accuracy of about 80%. These estimates were also divided into categories and reported to the AGC at the state level. This high-resolution map provides essential information for various stakeholders, with critical implications for carbon sequestration efforts, conservation priorities, and sustainable forest management. The presented methodology not only showcases the value of combining advanced remote sensing techniques with long-term inventory data but also underscores the potential for similar approaches in other tropical forest regions globally. Ultimately, this study contributes to the understanding of carbon dynamics in Malaysian forests and promotes effective strategies for mitigating climate change through better-informed forest conservation and management practices.

Nitrogen and phosphorous loading drives eutrophication of aquatic systems. Lakes and reservoirs are often effective N and P sinks, but information is needed on the variability of their biogeochemical dynamics, especially for tropical systems. A long-term N and P mass balance (2003-2018) in a small tropical eutrophic reservoir lake, Valle de Bravo (VB), Mexico, showed it is a net sink of N (-41.7 g N m-2 y-1), and P (-2.7 g P m-2 y-1), mainly through net sedimentation, equivalent to 181% and 68% of their respective loading (23.0 g N m-2 y-1 and 4.2 g P m-2 y-1). N mass balance showed that VB has a high net N atmospheric influx (31.6 g N m-2 y-1), which was 1.3 times the external load, and likely dominated by N2 fixation. During a period of high water level fluctuations (WLF), the net N atmospheric flux decreased by half compared to high level years. WLF can be a useful management tool to improve the trophic status of water bodies by decreasing anoxic conditions and net atmospheric fluxes, possibly through decreasing nitrogen fixation and/or promoting denitrification and other microbial processes that alleviate the N load.

Enteric methane (CH4) emitted by ruminant species is known as one of the main greenhouse gases produced by the agricultural sector. The objective of this study was to evaluate the chemical composition, in vitro gas production, dry matter degradation (DMD), digestibility, CO2 production and CH4 mitigation potential of five tropical tree species with novel forage potential including: Spondias mombin, Acacia pennatula, Parmentiera aculeata, Brosimum alicastrum and Bursera simaruba mixed at two levels of inclusion (15 and 30%) with a tropical grass (Pennisetum purpureum). Crude protein content was similar across treatments (135 g kg-1 DM), while P. purpureum was characterized by a high content of acid detergent fiber (335.9 g kg-1 DM) and B. simaruba by a high concentration of condensed tannins (20 g kg-1 DM). Likewise, A. pennatula and P. aculeata were characterized by a high content of cyanogenic glycosides and alkaloids respectively. Treatments SM30-PP70 (30% S. mombin + 70% P. purpureum) and BA30-PP70 (30% B. alicastrum + 70% P. purpureum) resulted in superior digestibility than P. purpureum, while in the AP30-PP70 (30% A. pennatula + 70% P. purpureum) was lower than the control treatment (P≤0.05). At 24 and 48 h, treatments that contained P. aculeata and B. alicastrum produced higher CH4 ml g-1 DOM than P. purpureum (P≤0.05). The inclusion of B. simaruba at 30% reduced CH4 at 25% compared to P. purpureum. Tropical tree species can improve the nutritional quality of ruminant rations and reduce CH4 emissions to consequently contribute to the development of sustainable ruminant production systems that generate diverse ecosystem services.

In the past few decades, the tourism sector has emerged as a significant economic activity in island nations, particularly in tropical regions. However, most of the tropical islands face similar constraints. National and international tourists visit the SIDS including A & N Islands and contribute to the GDP to significant share. The Covid-19 outbreaks in SIDs including A & N islands shows that number of people infected were less as compared to metros or big cities. However, tourism activities completely stopped due to lockdown resulting in decreasing tourist’s arrival, declined GDP and per capita income of SIDs to greater extent. The information gathered from various sources, mass media and net analysed and interpreted in this chapter. Due to Covid-19 tourist’s arrival declined which has serious consequences on the livelihood of islander. Our analysis revealed A&N Islands deficit in energy available at from different sources by 18.26%. However, they are surplus in protein. The burden of high expenditure coupled with poor infrastructure makes them more vulnerable in the circumstance of pandemic outbreaks. This outbreak has created the question of survival due to loss of jobs, halted economic activates, psychological, health unrest and livelihood threats among the depending people of these Island nations. Therefore, government interventions and subsidized package is very much essential to revive the tourism industry.

We examine the role of zonal Ekman transport along the coast of Senegal on 30 August, 2015 when the tropical disturbance associated with Tropical Cyclone Fred was located to the west of Senegal causing considerable coastal damage to coastal areas south of Dakar, Senegal. Ten-meter winds from three Weather Research and Forecast model simulations were used to estimate zonal Ekman transport, with the largest values found during the 30 August. The simulations are in agreement with limited coastal observations showing increasing southerly wind speeds during 30 August but are overestimated relative to the 3 coastal stations. The strong meridional winds translate into increased zonal Ekman transport to the coast of Senegal on 30 August. The use of a coupled ocean model will improve the estimates of Ekman transport along the Guinea-Senegalese coast. The observed damage suggests that artificial and natural barriers (mangroves) should be strengthened to protect coastal communities in Senegal.

Background Tropical and subtropical crops such as coffee, cacao, and papaya are valuable commodities and its consumption is a seemingly indispensable part of the daily lives of billions of people across the world. Conventional breeding in these crops is lengthy and yields are threatened by runaway global warming. In this review we propose the application of chromosome engineering and synthetic biology principles in order to enhance synthesis of key metabolites, and transmission of wild traits for resistance to stress and disease. Conclusions It is hoped that the adoption of such technological approaches may enhance the resilience of agricultural communities, lead to economic growth and secure the availability of key resources for generations to come.

Open pit mining is a common activity in the Yucatan peninsula for the extraction of limestone. This mining is known under the generic name of quarries, and regionally as sascaberas (sascab=white soil in Mayan language). These areas are characterized by the total removal of the natural vegetation cover and soil in order to have access to the calcareous material. The present study shows the composition and structure of the vegetation in five quarries after approximately ten years of abandonment, and the conserved vegetation near to each one of the quarries in southeastern Quintana Roo. Using a canonical correspondence analysis (CCA), the distribution of the species was determined in relation to the edaphic variables: soil depth, percentage of organic matter (OM), cationic exchange capacity (CEC), pH and texture. 26 families, 46 genera and 50 species were recorded in the quarries and 25 families, 45 genera and 47 species were recorded in the conserved areas. The dominant species in the quarries belong to the families Poaceae, Fabaceae, Rubiaceae and Anacardiaceae. The quarries with higher values of OM (1.63%), CEC (24.05 Cmol/kg), depth (11 cm) and sand percentage (31.33%) include the following species like Lysiloma latisiliquum, Metopium brownei and Bursera simaruba which are commonly found in secondary forests. On the other hand, quarries with lower values of OM (0.39%), CEC (16.58 Cmol/kg) and depth (5.02), and higher percentage of silt (42.44%) were dominated by herbaceous species belonging to the Poaceae family and by Borreria verticillata, which are typical in disturbed areas of southeastern Mexico. In all cases, the pH was slightly alkaline due to the content of calcium carbonate (CaCO3), characteristic of the soils of the region. The edaphic variables are significantly correlated with the development and distribution of vegetation, and with the structure of the communities.

Research Highlights: The study determined that selective thinning causes different responses, the initial size of the tree released is an influential factor in the growth of species. The temporality of climate and physiological conditions of each species are influential in the growth. It is evident that the defoliation of certain species is an important factor that limits the growth of the species causing thinning to have a negative response. Background and Objectives: The objective is to analyze the behavior of nine timber species, respective to diametric growth after their liberation. This research aims to answer the following questions: (i) How do the selected tree species react to the liberation? (ii) Can the productivity of the trees (diametric growth) be enhanced by liberation? (iii) Are there other factors that influence the diametric growth of the released trees? Materials and Methods: The study was executed in the “Reserva Biológica San Francisco” were 488 trees were monitored, including nine timber species. Therefore, 197 trees were released (removal of competitors) and 251 trees served as reference. To check whether the initial DBH or other factors, like the selective thinning or climate conditions, determine the diameter growth a linear mixed model GLMM was applied. To adjust the linear mixed model a one-way Anova test was executed. Results: Timber species responded differently to the thinning in comparing to reference trees. Therefore, the species analyzed were separated into three groups (positive, negative, and no response to liberation). Conclusions: Liberation potentiates the growth of certain timber species that do not defoliate and considered semi-tolerant to shade. Precipitation and temperature affect all species, but in the defoliate species, it would not be convenient to release them or at least the evidence of these first three years does not show clear differences with control trees. Increase in trees released are higher in trees of the first two diametric classes in all species, this means that larger trees (i.e., older) release does not affect them in a positive way so release should occur in the youngest trees.

This study explores the effect of seasonality on soil carbon efflux and pasture growth based on field and lysimeter experiments during summer-fall and winter-spring in two years. Focus is also pointed on irrigation strategies to alleviate the crop response to seasonal fluctuations in precipitation and surface temperatures. Soil respiration, soil and air temperature, leaf photosynthesis, plant dry weight and leaf area index were quantified and analyzed. It has been found significant differences in the CO₂ efflux between the two growing season. Emission of soil CO₂ allowed to characterize and to prioritize the temperature and rain influence in seasonal brachiaria response. During the seasons, the transient variation of CO₂ efflux was highly correlated with rainfall (r = 0.87, P < 0.05), and poorly correlated with soil temperatures (r = 0.5, P < 0.05). The CO₂ efflux and plant response to different level of reposition of evapotranspiration demonstrated that irrigation during fall mitigates the reduction of growth conditioned by drying soil and the lower temperatures. The lower temperatures are limiting only when the soil moisture is below 32% of the field capacity. Thus, we propose to keep the soil moisture around 50% during the fall as a key practices for mitigating the effect of seasonality and its intensification with the climate change, even more if added to management routine practices the soil and water conservation.

A reduction of melatonin function contributes to the acceleration of Alzheimer's disease (AD), and understanding molecular processes of melatonin-related signaling is critical for intervention of AD progression. Recently, we synthesized and tested a series of melatonin derivates with donepezil fragments in silico and in vitro. In this study, one of the most potent compounds, 3c, was studied in an in vivo rat model of pinealectomy (pin) and subsequent icvAβ1-42 infusion. Melatonin was used as a referent drug. The treatment with melatonin and 3c (10 mg/kg, i.p. for 14 days) exerted a beneficial effect on memory decline and concomitant rise of Aβ1-42 and pTAU in the hippocampus in the pin + icvAβ1-42 rats. Melatonin supplementation facilitated the non-amyloidogenic signaling via a non-receptor (histone deacetylase sirtuin 1, SIRT1) and receptor-related signaling (MT/ERK/CREB). The hybrid 3c derivate up-regulated the MT1A and MT2B receptors, pERK and pCREB. Our findings strongly support the hypothesis that melatonin-related derivates may become a promising drug candidate in AD therapy.

The global energy landscape is undergoing a transformative shift, and the potential of LNG as a major energy source is a topic of intense debate. In order to meet the growing demand for sustainable energy supply, it is crucial to maximize the efficiency and environmental friendliness of the LNG supply chain. This research aims to leverage computational modeling and optimization techniques to enhance the production units involved in LNG production. By harnessing the power of advanced algorithms and simulations, we can identify and implement innovative strategies that minimize energy consumption, reduce greenhouse gas emissions, and enhance the overall sustainability of LNG. Through this study, we seek to uncover novel approaches to address the challenges faced by the LNG industry, including improving operational efficiency, optimizing liquefaction processes, and enhancing the utilization of natural resources. By integrating cutting-edge computational tools and considering environmental factors, we aspire to pave the way for a more sustainable and environmentally friendly future powered by LNG. By exploring the immense potential of computational modeling and optimization, we strive to contribute to the ongoing efforts in advancing energy sustainability and shaping the future of LNG as a crucial global energy source."In this paper, our focus is on simulating and optimizing the process of converting natural gas to LNG. Our goal is to achieve the minimum energy consumption per ton of LNG produced. Through our research, we have identified that utilizing a three-stage exchanger is the most effective approach for minimizing energy consumption in an LNG industrial production unit. Moreover, we have discovered that the outlet pressure from the compressor and the type of refrigerant in the cooling system play significant roles in determining the rate of energy conservation. By carefully considering these factors and optimizing their settings, we can further enhance the overall energy efficiency of the LNG production process. Our research aims to provide valuable insights and guidance to industry professionals and decision-makers in the LNG sector. By implementing the findings of this study, we can contribute to the sustainable development and utilization of LNG as a cleaner and more environmentally energy source. Friendly It's great to see the optimized parameters for the refrigerants and pressure settings in the liquefaction and subcooling cycles. With the mass fraction of 0.89 for methane and 0.14 for ethane in the liquefaction cycle, and 0.59 for methane and 0.3 for nitrogen in the composition for achieving energy efficiency in the LNG production subcooling cycle, The optimized outlet pressure of 650 kPa for the compressors in the liquefaction cycle and 1800 kPa for the subcooling cycle furtherr ccontribute to minimizing energy consumption. Based on your findings, the amount of consumed energy at 14.81 kW per ton of produced LNG highlights the success of the optimization efforts. Reducing the energy consumption per ton of LNG produced is a significant accomplishment towards achieving energy sustainability and environmental friendliness in the LNG industry. These results demonstrate the importance of computational modeling and optimization in identifying the best parameters for eenhancing energy efficiency in LNG production. By implementing these optimized settings, we can work towards a more sustainable future with reduced energy consumption and lower environmental impact

(1) Background: Respiratory infections are a major public health problem worldwide, with potentially serious consequences. Indeed, these infections remain one of the main causes of morbidity and mortality in children under 5 years old in developing countries. Etiological information on respiratory infections is crucial for prevention and case management strategies. This systematic review aims to describe the etiology of respiratory infections reported in studies carried out in sub-Saharan African countries; (2) Methods: Using PubMed, HINARI and Google scholar search engines, a systematic search was carried out to identify published articles on the etiology of viral and/or bacterial respiratory infections in sub-Saharan Africa in patients of all ages. We have only considered data from sub-Saharan Africa. Papers published from 2010 to 2021, in English or French have been included in this review; (3) Results: After reviewing 115 articles reporting studies carried out in the African continent, only 32 articles were selected of which, studies were conducted in 15 sub-Saharan African countries, including 6/32 (18.75%) in Cameroon. Twenty (62.5%) were cross-sectional studies, and twenty-four (75%) were hospital-based investigations. In these studies, RT-PCR and culture methods were respectively used for viruses and bacteria investigations. Respiratory syncytial virus was the most frequently identified, with prevalence ranging from 0.6% to 59%, followed by rhinovirus (9.3% -73%), influenza virus (flu) A/B (0.9%-69.1%), and human adenovirus (0.9% - 30.8%). Streptococcus pneumoniae (14.2% - 96%), followed by Haemophilus influenzae type b (2.5% - 54%), and Klebsiella pneumoniae (1.4% - 49.9%) were the most frequently detected bacteria; (4) Conclusions: This review has reported that many pathogens, mainly viruses, are associated with acute respiratory infections in sub-Saharan Africa in both children and adults. Unfortunately, the limited geographical distribution of data across sub-Saharan Africa does not allow most of countries to develop an effective strategy for the prevention and treatment of respiratory infections.

Hemoglobin based oxygen carriers (HBOC) as blood substitutes are one of the great hopes of modern transfusion and emergency medicine. After the major safety-relevant challenges of the last decades seem to be largely overcome, current developments have in common that they are affected by degradation and excretion at an early stage in test organisms. Several possible mechanisms that may be responsible for this are discussed in the literature. One of them is CD163, the receptor of the complex of haptoglobin (Hp) and hemoglobin (Hb). The receptor has been shown in various studies to have an affinity for Hb in the absence of Hp. Thus, it seems reasonable that CD163 could possibly also bind Hb within HBOC and cause phagocytosis of the particles. In this work we investigated the role of CD163 for the uptake of our HbMP (hemoglobin sub-micron particles) in monocytes and additionally screened for alternative ways of particle recognition by monocytes. In our experiments, blockade of CD163 by specific monoclonal antibody proved to partly inhibit HbMP-uptake by monocytes. It appears however, that several other phagocytosis pathways for HbMP might exist, independent of CD163 and also Hb.

Though there has been a decline in the number of new cases of viral hepatitis-induced acute liver failure in Europe and the United States of America, viral hepatitis still remains the leading cause of acute liver failure in Asia-Pacific and South America. However, the epidemiology of viral-hepatitis-induced acute liver failure in sub-Saharan Africa-the world epicenter of viral hepatitis-is unclear. The aim of this review was to collate data on the incidence, prevalence, specific etiologic agents, features/diagnosis, treatment and prognosis of viral-induced acute liver failure in sub-Saharan Africa. One hundred and forty-seven cases of viral-induced acute liver failure were recorded in 11 studies conducted in six countries between 1981-2020. Etiological agents were: Hepatitis viruses A, B, C, and E, as well as Adenovirus, Enterovirus, Parvovirus, Herpes Simplex Virus (HSV) and EBV. HAV was the most frequent in paediatric subjects: (11/16) 69% and (19/30) 63%. HBV was the only etiological agent in the study that only included adults. HEV (genotype 2 in one study) contracted amidst hepatitis E outbreaks was the most commonly reported cause of ALF in pregnant women. Treatment was mainly supportive, and liver transplantation reported only in South Africa. Where reported, case fatality rates were high. In conclusion, viral-hepatitis induced acute liver failure is largely understudied in sub-Saharan Africa. The few available data are consistent with literature from the other parts of the world regarding aetiologic agents. Liver transplantation is not available in most sub-Saharan African countries, and short-term case fatality rates of individuals with acute liver failure could outstrip current rates from the other world regions.

Studies shows that, normal to high serum 25(OH)D status appears to have some beneficial influence on the incidence and severity of some, though not all, types of infections. However, studies with vitamin D supplementation on young children produced conflicting results with respect to the level of vitamin D deficiency among common medical illnesses among children. Method: A systematic review of literatures from PubMed, CINAHL, Web of science, global health and Google scholar electronic databases was conducted to assess the pooled prevalence of vitamin D deficiency among healthy and sick children in sub-Saharan Africa. The data was extracted by two authors independently using standard data extraction format and STATA Version 14 was used for analysis. The heterogeneity of the studies was assessed by using I2 test. A random-effects model was used to estimate the pooled prevalence among both healthy and sick children. Presence of publication bias was checked using Funnel plot and Egger's test. Result: A total of 1212 articles were identified by the total search of utilized data bases of which 13 papers fulfilled the inclusion criteria and accessible with full document. The meta-analysis revealed that the pooled prevalence of vitamin D deficiency among healthy children in this study was 50.06% (95%CI 33.46%, 66.67%) with mean serum vitamin D level of 41.06 nm/L (CI range from 23.82nm/L to 58.31nm/L). The pooled prevalence among the sick children was 39.36% (CI 20.57%, 57.96%) with 66.96nm/L (95% CI 54.81nm/L, 79.11nm/L) mean concentration of vitamin D. Comparing the two level of the pooled prevalence, the prevalence among the healthy children was significantly higher compared to those who have common medical illnesses and the pooled mean concentration among the sick was much higher than the mean concentration among healthy children. Conclusion: The level of pooled prevalence among both group of population was significantly of public health concern and the prevalence among the healthy children was much higher among the sick children implying the need for reconsideration of available recommendations for the prevention of vitamin D deficiency

To bring to the fore the aim of this research, effects of fluctuating temperature, was measured against food and nutrition security in the region using food production index, and undernourished population growth rate as proxies; controlled over share of arable land, irrigation, population and labour share for agriculture. Dynamic panel of generalized method of moments (GMM) was adopted, the period 2000 to 2016 were considered and 29 countries in sub-Sahara Africa were selected within the empirical framework of global water balance as mentioned by Rai and Singh (2012). Findings from the study reveals that the short run effect of temperature increase in degrees pose at least -3.1% negative and significant impact effects on the food production while the long run elasticity hits -7.5% and the controlled effect on arable land revealed a positive impact on the food production to the tune of 3.9%. Contrarily, arable land expansion reduces the under nourished population by -8.55%. Population increase on the other hand increases undernourished population in the region to the tune of 11.95%. The study therefore recommended expansion in the arable land and encourages population control policy in order to negate the undesired effects of temperature on food and nutritional security.

The novel COVID-19 pandemic prompted an unprecedented Institutional reaction to aggregate existing capacity from silos of research laboratories to establish a multidisciplinary research laboratory for COVID19 testing. In less than two weeks, resources were mobilized from the community to strengthen public health response and epidemic control. Such strengthening of institutional research capacity to support public health response contributes to a natural knowledge transfer, facilitates collaboration, and generates new frontiers for knowledge production that should ultimately lead to professional development and retention of skilled human resources. This report describes the pre-established mechanisms and involvement of the authors that made it possible to set-up a multidisciplinary laboratory in a remarkably short period of time. We also discuss the opportunities and sustainability of multidisciplinary laboratory research post-COVID19. Existing institutional capacity can be repurposed to establish multidisciplinary research laboratories to support the strengthening of basic and clinical translational research capacity in resource limited settings and impact on public health and scientific knowledge for socioeconomic development.

This study investigates the effect of different variables in the optimization of a hybrid air charging systems for marine diesel engines, exploring the potential for energy recovery and assistance using electric machines. The optimization parameters include turbine speed, compressor power, start of injection, turbomachine size, and valve timing. At low engine speeds, the larger improvements come from increasing compressor power, which increases air-to-fuel ratio compared with the baseline turbocharging. As free-floating turbocharged engines are known to have low air-to-fuel ratio at low engine speeds, the relative improvement of the hybrid architecture is large at low engine speeds, being near to 10% less BSFC. At high engine speeds, the largest influence is marked by the SOI, an early injection obtains a faster combustion, which improves gross efficiency. However, the relative improvement compared with baseline turbocharger is less than 1% at high engine speeds. Due to the distribution of relative improvement of BSFC, this architecture has a deeper impact on fuel consumption in vessel operating cycles that focus on low engine speeds and loads, such as those of tugboats.

Air pollution has recently gained much attention from the general population. Despite pollution control being an issue in both urban and rural regions, most of the available research has concentrated on urban districts. Hence, investigations into how urban-rural transition affects PM2.5 are warranted within the framework of urban-rural integration. Using the Yellow River Basin as a case study, this study employed the entropy method and Analytic Hierarchy Process (AHP) to uncover the extent of urban-rural transformation. It then used the spatial autocorrelation method to investigate the spatiotemporal features of PM2.5 and the spatial econometric model to investigate the mechanisms that influence the relationship between urban-rural transformation and PM2.5. The results are as follows: (1) Over time, there was a discernible upward tendency in the change in urban-rural areas. The development has progressed from asymmetrical north-east and south-west elevations to a more balanced pattern of north-east, middle-east, and west-west elevations. (2) The PM2.5 concentration increased steadily, then fluctuated, and finally decreased. Notably, the general pattern has not changed much, and it is high in the east and low in the west. (3) Different subsystems of the urban-rural transformation have different impacts on air pollution at different stages. The influence of industrial transformation (IT) on PM2.5 showed an inverted “N-shaped” curve of negative-positive-negative changes, and the industrial structure played a leading role in the spatiotemporal evolution of PM2.5. Currently, an inverted "U-shaped" curve forms the left side of the impact of population transition (PT) on PM2.5. Land development (LT) has a "U-shaped" curve for its effect on PM2.5. This research provides a new perspective on the topic of PM2.5 and its connection to urban-rural integration, which is crucial to understanding the dynamics of this shift. To achieve its goal of high-quality development, it supports regional initiatives to reduce PM2.5 emissions in the Yellow River Basin. Moreover, it can provide a reference for decision-makers in the world’s densely populated areas that suffer from serious air pollution.

This work presents noble composites of AAILs@MCM-48 by functionalizing ordered mesopo-rous silicon MCM-48 with two amino acid-based ionic liquids (AAILs) ([Emim][Gly] and [Em-im][Ala]) to improve carbon capture and selectivity of CO2 over nitrogen. Thermogravimetric and XRD analyses of the composites show that the MCM-48 support's thermal and structural in-tegrity was preserved after the AAILs were encapsulated. An N2 adsorption-desorption study at 77 K also confirms AAIL encapsulation in the porous support. Under post-combustion flue gas conditions, both [Emim][Gly]@MCM-48 and [Emim][Ala]@MCM-48 demonstrated improved CO2 adsorption in comparison to unmodified MCM-48, with a CO2 partial pressure of around 0.15 bar. In terms of maximal CO₂ uptake, the 40wt%-[Emim][Gly] composite outperformed the others at 303K, with values of 0.74 and 0.82 mmol g-1, respectively, at 0.1 and 0.2 bar. These numbers show a 10x and 5x increase, respectively, as compared to the pure MCM-48 under iden-tical conditions. In addition, the selectivity of the composites was improved significantly, at 0.1 bar, the selectivity of composites containing 40wt% [Emim][Ala] increased to 17, compared to 2 for pristine MCM-48.

Agro-industrial lignocellulosic waste can be bioconverted to fungal biomass and then utilized as a high nutritional value food alternative for ruminants, with potential for ruminal methane (CH4) mitigation. This study was carried out to evaluate the changes in the enzymatic expression and nutritional value of palm kernel cake fermented with Pleurotus ostreatus (FPKC), as well as the differences in the in vitro fermentation parameters and methane production in diets based on tropical forages with the inclusion of 20% FPKC. The highest activity of laccases and cellulases occurred on day 13 with values of 0.75 ± 0.09 U/g and 266.7 ± 20.8 U/g; respectively. The biological pretreatment decreased the contents of (p< 0.05) neutral detergent fiber (NDF), acid detergent fiber (ADF) and lignin (LIG) by 29%, 20.5% and 46.6% respectively, while those of crude protein (CP) increased by 69.65%. The inclusion of FPKC resulted in increases (p

Co-management is increasingly recognized as an effective approach of forest governance while recognizing local people's forest dependency and traditional rights. Moreover, co-management is expected to positively impact forest cover and ecosystem health. Bangladesh, facing a rapid decline in forest cover, has one of the lowest per capita forest areas worldwide. For quite a while, co-management practices have been used to improve forest cover and the livelihoods of forest-dependent people in Bangladesh. Several studies have assessed the efficacy of co-management in different protected areas in Bangladesh from livelihood, social, and cultural aspects. However, the overall changes in forest cover due to co-management from the very beginning of co-management initiatives in the country have been overlooked. We used remotely sensed Landsat images to assess the changes in forest cover and overall land use in five forest protected areas where co-management was piloted. Three major vegetation indices (NDVI, EVI, and MSAVI) were examined to ensure the study's robustness. This study aims to assess the scope and weaknesses of the current policy that incorporates co-management in the country's first five protected areas (SNP, LNP, RKWS, TWS, and CWS), which were brought under co-management in 2003, and compare the efficacy of the co-management relative to non-comanaged protected areas (RRF). The land cover analysis based on NDVI, MSAVI, and EVI values indicated dominant dense forest coverage (41–71%) across five protected areas. During the co-management period (2004–2015), there was a significant decrease in the dense forest proportion, with slopes ranging from -3.7 to -0.96. Similarly, the RRF showed a decreasing pattern, with the slope of the decreasing trendline ranging from -0.48 to -0.62 across the three indices. Agriculture and forest-agriculture mosaics showed a significant increase, with varying slopes among protected areas in both co-managed and non-comanaged sites. Pixel-to-pixel changes revealed dynamic shifts in vegetation indices, and Global Forest Watch data highlighted forest cover losses, notably in CWS (158.77 ha) and SNP (0.49 ha).

Tropical regions face unique challenges in building sustainability due to high temperatures, humidity, and heavy rainfall. While building energy regulations are essential for promoting energy efficiency, their effectiveness in addressing tropical climate conditions needs to be studied more. This research aims to systematically investigate tropical building sustainability issues and evaluate the impacts of building energy regulations on these challenges. The study will identify gaps in current regulations by analyzing existing research and recommend strategies for developing more comprehensive frameworks that promote sustainable building practices in tropical regions. This research contributes to developing effective policies and strategies for achieving sustainable and energy-efficient built environments in tropical climates.

Invasive species are one of the five main causes of biodiversity loss, along with habitat destruction, overexploitation, pollution, and climate change. Represent one of the first barriers to overcome in ecological conservation programs, since are difficult to control and eradicate. Due to the lack of records of invasive exotic species in Panama, this research is necessary to identify and register the documented groups of invasive species of the Chordates and Arthropod groups in Panama. This exhaustive search of invasive species was carried out in different bibliographic databases, electronic portals and scientific journals which addressed the topic at a global level. The results indicate that approximately 133 invasive exotic species of the Arthropoda and Chordata Phylum have been reported in Panama. Of the 133 species, 49 species belong to the Arthropoda Phylum and 84 species belong to the Chordate Phylum. The Panamanian economic activity could promote the introduction of alien species in this country. The study provides the first list of invasive exotic chordate and arthropod species reported for the Republic of Panama.

Assessing carbon stocks in tropical forests is crucial for understanding their role in mitigating climate change. (1) Background: However, existing assessments have underestimated certain factors that can substantially influence carbon dynamics. (2) Methods: This study focuses on one such factor - buttress roots from a tropical forest. (3) Results: Our findings reveal that a significant proportion of trees (69.57%) had 3 to 5 buttress roots per tree. The total biomass of the buttress roots and the aboveground portion of the trees with buttress roots were calculated to be 8.5 tonnes/ha and 10.7 tonnes/ha respectively. The buttress root biomass accounted for 16.18% of the total tree biomass. It was observed that the presence of buttress roots during both the rainy and dry seasons increased the soil organic carbon content by an average of 20.8% in the upslope areas with buttress roots. During the rainy season, the presence of buttress roots did not affect the heavy fraction organic carbon in the soil layers in a statistically significant way. Regardless of the season, the soil respiration rate in the areas without buttress roots was higher than that in the areas with buttress roots. The presence of buttress roots had a positive effect on soil nutrient concentration in all seasons, creating a healthier environment for trees. Tree species with buttress roots had on average 20% higher organic carbon content during both the wet and dry seasons. (4) Conclusions: These findings highlight the importance of considering buttress roots in carbon stock assessments and forest management strategies. By integrating buttress roots into carbon accounting models, we can obtain more accurate estimates of carbon stock potential and develop more effective conservation and restoration strategies for tropical forests.

Control of Tropical Theileriosis, a tick-borne disease with a strong impact on cattle breeding, can be facilitated by using marker-assisted selection in breeding programs. Genome-wide association studies (GWAS) using high-density arrays are extremely important for the ongoing process of identifying genomic variants associated with resistance to Theileria annulata infection. In this work, Single Nucleotide Polymorphisms (SNPs) were analyzed in the Portuguese autochthonous cattle breeds Alentejana and Mertolenga. In total, 14 SNPs suggestive of significance (p ≤ 10-4) were identified for Alentejana cattle and 20 SNPs for Mertolenga cattle. The genomic regions around these SNPs were further investigated for annotated genes and Quantitative trait loci (QTLs) previously described by other authors. Regarding the Alentejana breed, the MAP3K1, CMTM7, SSFA2, and ATG13 genes are located near suggestive SNPs and appear as candidate genes for resistance to Tropical Theileriosis, considering its action the immune response and resistance to other diseases. On the other hand, in the Mertolenga breed, the UOX gene is also a candidate gene due to its apparent link to the pathogenesis of the disease. These results may represent a first step towards the possibility of including genetic markers for resistance to Tropical Theileriosis in current breed selection programs.

Asphalt pavement temperature has several applications, including pavement structural design and evaluation, asphalt mixture design, asphalt binder grade determination and material aging characterization. However, available asphalt pavement temperature prediction models were mostly developed for temperate climatic conditions, outside of the tropics. Before such models are adopted for use in a tropical climate, their applicability must be evaluated. This study evaluated five empirical asphalt pavement temperature prediction models developed by Lukanen et al. [1], Park et al. [2], Diefenderfer et al. [3], Taamneh [4] all in the United States and Asefzadeh et al. [5] in Canada to ascertain their prediction accuracy in tropical climate, using Ghana as a case study. In-situ asphalt pavement temperature data were measured at two sites for eight months: Kumasi and Tamale in the Forest and Savannah climatic zones, respectively. The measured pavement temperature data were statistically compared with predicted temperatures, and it was found that the Park et al. [2] model provided a more accurate pavement temperature prediction in both climatic zones. The other models either over-predicted or under-predicted asphalt pavement temperature with significant error margins. However, there is a need to improve the prediction accuracy of the Park et al. [2] model or a local model developed.

Urban Tree Canopy (UTC) greatly enhances the livability of cities by reducing urban heat buildup, mitigating stormwater runoff, and filtering airborne particulates, among other ecological services. These benefits, combined with the relative ease of measuring tree cover from aerial imagery, have led many cities to adopt management strategies based on UTC goals. In this study, we conducted canopy analyses for the 300 largest cities in Florida to assess the impacts of development practices, urban forest ordinances, and hurricanes on tree cover. Within the cities sampled, UTC canopy ranged from 5.9% to 68.7% with a median canopy coverage of 32.3% Our results indicate that the peak gust speeds recorded during past hurricanes events were a significant predictor of canopy coverage (P-value = <0.001) across the sampled cities. As peak gust speeds increased from 152 km/h (i.e., a lower-intensity Category 1 storm) to 225 km/h (lower-intensity Category 4 and the maximum gusts captured in our data), predicted canopy in developed urban areas decreased by 7.7%. Beyond the impacts of hurricanes and tropical storms, we found that historic landcover and two out of eight urban forest ordinances were significant predictors of existing canopy coverage (P-landcover <0.001; P-tree preservation ordinance = 0.02, P-heritage tree ordinance = 0.03). Results indicate that local policies and tree protections can protect or enhance urban tree canopy, even in the face of rapid development and periodic natural disturbances.

This paper constructs a model of climate-related damage for small island developing states (SIDS). We focus on the loss of private productive capital stocks through extreme climate events. In contrast to most economic analyses of climate impacts, which assume temperature-dependent damage functions, we draw on the engineering literature to allow for a greater or lesser degree of anticipation of climate change when designing capital stocks and balancing current adaptation expenditure against future loss & damage. We apply the model to tropical storm damage in the small island developing state of Barbados and show how anticipatory behavior changes the damage to infrastructure for the same degree of climate change. Thus, in the model, damage depends on behavior as well as climate variables.

Secondary forests (SF) are important carbon sinks, removing CO₂ from the atmosphere through the photosynthesis process and storing photosynthates in their aboveground live biomass (AGB). This process occurring at large-scales partially counteracts C emissions from land-use change, playing, hence, an important role in the global carbon cycle. The absorption rates of carbon in these forests depend on forest physiology, controlled by environmental and climatic conditions as well as on the past land use, which is rarely considered for retrieving AGB from remotely sensed data. In this context, the main goal of this study is to evaluate the potential of full polarimetric ALOS-2 PALSAR-2 data for estimating AGB by taking into account the past-land use of SF areas in the Brazilian Amazon. We surveyed a chronosequence of 42 SF plots (20 ha) near the Tapajós National Forest in Pará state to quantifying AGB growth rates. We explored the full polarimetric data testing three regression models including non-linear (NL), multiple linear regressions models (MLR), and the semi-empirical extended water cloud model (EWCM). The results showed that the intensity of previous use has affected the structure of SF by reducing the AGB accumulation and being noticeable by several polarimetric attributes. The combination of multiple prediction variables with MLR improved the AGB estimation by 70% comparing amongst other models (R² adj. = 0.51; RMSE = 13.2 Mg ha^-1) bias = 2.1 ± 37.9 Mg ha^-1. The error propagation of the MLR model was estimated to be 15%.

Hydrological modeling allows us to make a comprehensive assessment of the interaction between dynamics of the hydrological cycle, climate conditions, and land use. These modeling results are relevant in water resources management field. We use TopModel (TOPography based hydrological MODEL for the hydrological modeling of an area of 17 000 km² in the Middle Magdalena Valley (MMV), a tropical basin located in Colombia. This study is located in the intertropical convergence zone (ITCZ) which is characterized by special meteorological conditions and fast water fluxes over the year. This area has been subjected to significant land use changes, as a result of intense economic activities, e.g., agriculture, hydropower energy and oil & gas production (Avellaneda, 2003). The proposed model is based on a record of 12 years of: i.) daily precipitation data from observed gauges, ii.) daily evapotranspiration data from temperature data and iii.) daily streamflow data as observed data. A calibration process was performed using data from 2000 to 2008, and a validation was performed with data from 2009 to 2012. The Nash-Sutcliffe coefficient was used as an objective function to assess the quality of these processes (values of this metric are between 0.74 and 0.73 respectively, for model calibration and validation). The results show us an adequate performance of the model in areas of the tropical region and allow us to analyze the relationship between water storage capacity in the soils of the area with subsurface runoff. This conclusion is consistent with the characteristics of the region. The calibrated model provides an idea about the hydrological functioning of the basin and estimates an approximation of the groundwater recharge in the region. The estimation of the recharge is important to quantify the interaction of surface water and groundwater, especially during the dry season, due to its importance in the analysis of scenarios with climate variability.

The origination of most free-living animal species is predictable. ‘Light’ order production in the trophic levels below is the key. Absent from the abiotic environment (pre-primary level) and prokaryotes, ‘light’ order consists of differences in species composition between highly-developed, species-packed communities in which extinction may be the precursor to speciation, particularly ecologically comparable tropical continental lowland ones of Africa, Australia, India, and South America. Based on but not itself of matter and non-burnable, its nil waste heat content ‘compensates’ for burned-up food energy. Where the amounts of it on infra-apical trophic levels form an inverted pyramid like waste heat’s, occupancy of trophic levels from primary to apical is predictable (variation and selection assumed). Terminal non-inversion predicts post-apical vacancy. Examined communities were from grasslands (grasses, large grazing mammals, large carnivores), and woodlands (woody plants, butterflies, insect-eating birds, raptorial birds). Linnaeus’s binomial classificational system turned out to be unexpectedly rich in new content. A new object of study, the neoLinnaean, is recognised and a new process, the neoLyellian, advanced to explain it. Relations to Darwin’s and Lyell’s non-predictive theories of change, to ecology and evolution, to thermodynamics, statistical mechanics and quantum mechanics, and to neurology are discussed.

A testable hypothesis with quantitative predictions is put forward, proposing that strong acids produced on land at a rate correlated with global population are an increas-ing cause of increasing atmospheric CO2 pressure (pCO2). This hypothesis widens the imbalance assumed between the global uptake of CO2 by photosynthesis and emissions of CO2 from all sources, including the combustion of fossil fuels, causing greater atmos-pheric pCO2. Our modelling tests for reactions of dissolved inorganic carbon show that increasing atmospheric CO2 is caused thermodynamically by falling land surface pH values, but only with bicarbonate present. Strong acids generated by oxygen from re-duced inorganic compounds of nitrogen and sulphur emit CO2 almost stoichiometrically from dissolved bicarbonate in the pH range of most global soils, between 6 to above 8. We show that each decrease of aqueous pH value of 0.01 units from acidification of sur-face water near pH 8 potentially increases the pCO2 in the atmosphere by about 7 ppmv. The surface pH value of the ocean near 8.10 in 2000 has been shown to decrease at this rate, a result of equilibrating with the rising atmospheric pCO2. Therefore, our qualita-tive estimates of increasing atmospheric CO2 driven by irreversible acidification on land are critical and need broad scale validation. Unfortunately, these acidifying processes on land from excessive nitrogen fertiliser, export of alkaline produce from farmlands and other processes were not considered by previous biogeochemical reviews. However, several very recent research studies showing CO2 emissions from soil during nitrifica-tion are consistent with our hypothesis. Despite counter measures to curb excessive CO2 emissions, including carbon capture and geological storage, the increasing Keeling curve for pCO2 may continue to rise because zero carbon policies do not address these causes. We recommend that this hypothesis be further tested by in situ experiments in neutral soils and water, designed to compare CO2 emissions under the acidifying conditions de-scribed in this article. Corrective counter measures can then be designed and applied.

The affinity constant, also known as the equilibrium constant, binding constant, equilibrium association constant, or the reciprocal value, the equilibrium dissociation constant (K_d), can be considered as one of the most important characteristics for any antibody-antigen pair. Many methods based on different technologies have been proposed and used to determine this value. However, since a very large number of publications and commercial datasheets do not include this information, significant obstacles in performing such measurements seem to exist. In other cases where such data are reported, the results have often proved to be unreliable. This situation may indicate that most of the technologies available today require a high level of expertise that does not seem to be available in many laboratories. In this paper, we present a simple approach based on standard immunoassay technology that is easy and quick to perform. It relies on the effect that the molar IC₅₀ approaches the K_d value in the case of infinitely small concentrations of the reagent concentrations. A two-dimensional dilution of the reagents leads to an asymptotic convergence to K_d. The approach has some similarity to the well-known checkerboard titration used for the optimization of immunoassays. A well-known antibody against the FLAG peptide, clone M2, was used as a model system and the results were compared with other methods. This approach could be used in any case where a competitive assay is available or can be developed. The determination of an affinity constant should belong to the crucial parameters in any quality control of antibody-related products and assays and should be mandatory in papers using immunochemical protocols.

Rice (Oryza spp.) is mostly grown directly from seed and sown on wet or dry seed beds or usually used as transplants on nursery bed. With all the economically important viral diseases in the world, Rice yellow mottle virus (RYMV), is only prevalent in rice-growing countries in Africa. RYMV had turned out to be the main rice production constraint in Africa, throughout the last 20–25 years, causing yield loss of 10 to 100%, depending on age of the plant at the time of infection, degree of varietal susceptibility and the exiting climatic conditions. Good agricultural practices and utilization of biotechnological tools in the development of improved resistant cultivars have been extensively active in controlling the disease. This review focused on RYMV, its epidemiology, serological and molecular typing, disease management and the way forward for sustainable rice production.

Two decades after the antiretroviral therapy (ART) introduction, several challenges still prevail in maintaining people living with HIV (PLHIV), even with "Test and Treat" and/or "Rapid Start of ART" initiatives, as well as the scale-up of ART worldwide to promote access and adherence to treatment. This review examined articles on ART adherence in Africa between 2016 and 2023, published in English and indexed in PubMed. A total of 16 articles out of 2415 were eligible and included for analyses. Overall, ART adherence rates in SSA regions ranged from 43% to 84%. Rates in the centre of the SSA region ranged from 58% to 80%, in the north from 50% to 83%, in the south from 77% to 84%, in the west from 43% to 60% and in the east from 69% to 73%. Most African countries use the self-report to assess treatment adherence, although unreliable. The main factors with negative influence on ART adherence were comorbidities, lack of motivation, socioeconomic difficulties or side effects. Conclusion: Adherence to ART is a good indicator for controlling the spread of HIV. It is important to overcome the barriers that make it difficult to comply with ART and reinforce the factors that facilitate the accession of medication.

This essay critically discusses the integration of queer theory into human geography while emphasizing its ties to the principles of traditional geography. The need for a separate sub-discipline called queer geography is questioned. At the same time, legitimate concerns about possible departures from the fundamental goals of geography and the risks of anachronistic interpretations in applying modern concepts to historical landscapes are acknowledged. In this discourse, we strongly advocate for values such as freedom of speech, freedom of expression, and international human rights. It is important to emphasize that it is not the intent of this essay to denigrate campaigns for feminism or equality or to disparage the scholarship that emerges from the application of queer theory. On the contrary, we recognize the emergence of gender theories out of a need to advance social justice approaches. We believe that traditional human geography, itself, is capable of comprehensively examining space, time, and the complexity of human experience and offering workable solutions within its established framework. We therefore believe that the inclusion of queer theory can be harmoniously integrated into the contours of human geography, eliminating the need for a separate sub-discipline while preserving the integrity and purpose of the discipline.

: Urinary schistosomiasis caused by the parasite Schistosoma haematobium is the most common form of schistosomiasis. This parasite has a high potential for genetic exchange within parasite populations giving rise to the genetic diversity that is important for its survival. Genetic differ-ences may lead to some parasite strains being more immunogenic which may have a negative impact on management and control of schistosomiasis. Therefore, understanding these genetic differences in the parasite may lead to better management of the disease. A literature search was done on PubMed, African Journals online and Google scholar using predefined search terms such as urinary schistosomiasis, S. haematobium, genetic diversity in sub-Saharan Africa in com-bination with Boolean operators (AND, OR). The search included studies published from 2000-2020 that emphasised on genetic diversity of Schistosoma haematobium in sub-Saharan Africa. Sixteen studies from 18 sub-Saharan African countries that met the inclusion criteria were se-lected. Most studies conducted in these countries showed a high genetic diversity of Schistosoma haematobium studies with microsatellite markers being the most commonly used method for ge-netic diversity determination. Fisher’s exact test showed that the distribution of genetic diversity in sub-Saharan African regions was not statistically significant (p=0.768). The highest number of studies on genetic diversity of Schistosoma haematobium were conducted in West Africa with Ni-geria and Zimbabwe in Southern Africa conducting the most studies, 4/36 (11%) each. Results obtained show the need for continued monitoring of genetic variations in Schistosoma haemato-bium in sub- Saharan Africa. This will aid in understanding the epidemiology of disease, ad-vancing novel treatment and vaccine strategies.

Mobile health devices are emerging applications that could help deliver point-of-care (POC) diagnosis, particularly in settings with limited laboratory infrastructure, such as sub-Saharan Africa (SSA). The advent of coronavirus has resulted in an increased deployment and use of mHealth-linked POC diagnostics in SSA. We performed a systematic review and meta-analysis to evaluate the accuracy of mobile-linked point-of-care diagnostics in SSA. Our systematic review and meta-analysis were guided by the Preferred Reporting Items requirements for Systematic Reviews and Meta-Analysis (PRISMA). We exhaustively searched PubMed, Science Direct, Google Scholar, MEDLINE, and CINAHL with full-text via EBSCOhost databases from mHealth inception to March 2021. The statistical analyses were conducted using OpenMeta-Analyst software. All 11 included studies were considered for the meta-analysis. The included studies focused on malaria infections, Schistosoma haematobium, Schistosoma mansoni, soil-transmitted helminths, and trichuris trichiura. The pooled summary of sensitivity and specificity estimates were moderate compared to the gold reference standard. The overall pooled estimates of sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio of mobile-linked POC diagnostic devices were as follows: 0.499 (95% CI: 0.458-0.541); 0.535 (95% CI: 0.401-0.663); 0.952 (95% CI: 0.60-1.324); 1.381 (95% CI: 0.391-4.879); and 0.944 (95% CI: 0.579-1.538), respectively. Evidence shows that mobile-linked POC diagnostics' diagnostic accuracy is presently moderate in detecting infections in sub-Saharan Africa. Future research is recommended to evaluate mHealth devices' diagnostics with excellent sensitivities and specificities in diagnosing diseases in this setting.

United Nations Framework Conventions on Climate Change (UNFCC) conventions in their conference of parties (COPs) has continuously considered and agreed reducing emission level in order to minimize the impact of global climate change. Reducing emission due to deforestation and degradation (REDD) ,was considered as one of the major activities in this regard during Kyoto protocol in 2009 which laid foundation for the participating countries to be compensated financially for reduced carbon emission. Mexico convention -2012 required the countries to develop and implement a transparent and consistent monitoring, reporting and verification (MRV) process. Later in Paris agreement-2015, the parties agreed to limit the global warming to 2 degree centigrade and with further efforts to 1.5-degree centigrade furthering entailing the parties to prepare and communicate nationally determined contributions (NDCs) every five years. Nepal aimed to decrease the average annual deforestation rate by 0.05 percent from existing 0.44 percent in the terai region and 0.1 percent in the Chure. Nepal decided to develop its forest reference level (FRL) in national level for the historical period 2000-2010 considering Carbon dioxide and carbon pools above and below ground. As per the Forestry Sector Strategy, Nepal aims to increase carbon stock growth by at least 5% by 2025 as compared to 2015 and decrease mean annual deforestation rate to 0.05. After major change in administrative division in Nepal, forest management responsibility has shifted down to the Sub-national level. But forest resource studies have not been conducted yet in these levels. Despite a small country, Nepal has at least four clear physiological regions. The amount of carbon stock stored by different forest type are different depending upon species distribution, carbon volume and density for each species, and their distribution along ecological and physiological regions. Sal (shorea Robusta), for example, having one of the highest carbon densities, is a major forest types in Nepal. The purpose of this study was to generate forest map of the country, calculate carbon stock, gain and loss, and their rate in each province due to deforestation/afforestation using remote sensing data. Further Sal forest map was generated and its contribution in carbon stock was calculated using averaged national carbon density as well as using regional density method. According to the study, around 5.1 million hectares of Nepali land was forest in 2015 increasing from 4.2 million hectares in 2005. However, Sal forest has decreased during the same period. Province 1 contributed the maximum (130 Tg) and Province 2 the minimum (40Tg) of Carbon stock in 2015. Using the conventional method of calculation with national average density (108.08 t/ha), a total of 36.7T CO2 yr-1 carbon sink was observed in the Country. Whereas, with the new approach of calculation, a total of 44.7 T CO2 e of carbon sink per year was estimated during the same period. This approach holds potential for qualifying as an MRV process of Nepal. The subnational level forest and carbon statistics produced during this study can be important assets for the better forest governance. This can also pave way for policy formation and preparation of action plan for sustainable forest management and intervention strategy and obtaining better financial incentives participating in the reduction of emission due to deforestation and forest degradation (REDD) plus programs.

A cross-sectional study was carried out to determine the prevalence of subclinical mastitis (SCM) among medium to large scale household dairy farms in southwestern district, Jhenaidah, Bangladesh during July to December 2019. A total of 78 (n=100) lactating cows from household dairy farms (N=32) having three or more dairy cows were selected randomly as sampled populations. Milk samples were screened for SCM by using Surf Field Mastitis Test (SFMT). The prevalence of SCM varied among farm level [71.9% (95% CI: 53.3-86.3)], individual animal level [67.9% (95% CI: 56.4-86.3)] and quarter level [29.5% (95% CI: 24.5-34.9)]. Descriptive statistics represented the farmers and farm demography, characteristics of the sampled population, and overall management feature. Random Effect Logistic Regression identified, Body Condition Score (BCS) [OR=3.8 and 2.9, at cows level and quarter level respectively (BCS-2 vs. BCS-≥3)], and breed [OR=5.1 and 2.9, at cows level and quarter level respectively (HF× Sahiwal vs. HF × Local)] as potential risk factors. This study shows that SCM is highly prevalent in the study area, which is a major threat to the dairy industry's production performance. Regular screening by SFMT, proper hygiene, improve the management system, and farmer’s awareness is required to control the disease.

The eruption of the COVID-19 pandemic has affected every sphere of life and may forever change how we have always lived and conducted our businesses, and no one can resist the wind of change that is blowing. Of all the sectors of governance, the educational sector, particularly at the tertiary level, appears to have been most greatly affected and therefore requires a more pragmatic approach to resolution. As of 29th June, Sub-Sahara Africa has reported 382,190 cases of COVID-19. In rejoinder to the virus epidemic, several Sub Sahara African governments implement the resolution to slam learning institutions to enclose the infection. Consequently, advanced schooling institutions obliged to reorganize their loom, becoming more digitally become forward, and changing to online platforms.

In this paper, the validity of the Wagner’s law is investigated in tenth selected Sub- Saharan African countries, namely Botswana, Equatorial Guinea, Mauritania, Nigeria, South Africa, Sierra Leone, Tanzania, Ethiopia, Madagascar, and DR Congo. Five variants of the Wagner’s law were tested for the period 2005-2014, using panel econometric approaches encompassing cointegration and causality. The study found a long run relationship between the public expenditure and the various explanatory variables used as proxies of income. The long-run causality tests indicate that there is bidirectional causality between expenditure and income in all models with the exemption of the Gupta model. It is concluded that for Sub-Saharan Africa, both the Wagner’s law the Keynesian hypothesis tend to be valid under the period of investigation. The explanation is that there has been the tendency for public expenditure to grow relative to national income (Wagner’s law) and that public expenditure is a policy instrument (an exogenous factor) for improving national income (Keynesian hypothesis) during the 10-year period.

An important aspect of the new sustainable development goals (SDGs) is a greater emphasis on reducing the health impacts of urban ambient air pollution (AAP) in developing countries. Meanwhile, the burden of disease attributable to AAP in sub-Saharan Africa (SSA) is growing, yet estimates of its impact in the region are likely underestimated due to a lack of air quality monitoring, the paucity of epidemiological studies, and important population vulnerabilities in the region. The lack of studies in the SSA region also represents an important global health disparity and environmental justice issue because thousands of air pollution health effects studies have been conducted in Europe and North America rather than in some of the most polluted regions of the world, such as SSA. In this review, we synthesize all of the ambient air pollution epidemiological studies that have been conducted in SSA to date. We highlight the gaps in AAP epidemiological studies conducted in different sub-regions of SSA and provide methodological recommendations for future environmental epidemiology studies addressing AAP in the SSA region.

The accumulation of high levels of lead or lead ions in a human body is harmful, particularly to children. Its neurotoxic effect is profound, damaging the central and peripheral nervous systems, resulting in stunted growth, behavioral problems and learning disabilities. The major source of lead or lead ions comes from the drinking water and tap water. The assessment of the water quality, including lead or lead ion content, is usually completed by a regional water department professional. This assessment is time-consuming and requires expensive instruments and skilled operators. Therefore, there is a need to produce a simple-use and relatively inexpensive method to detect lead or lead ions in water samples. This research has developed a simple-use, cost effective sensor system for the detection of lead ions in tap water. An under-potential deposited bismuth sub-layer on a thin gold film based electrochemical sensor was designed, manufactured and evaluated. Differential pulse voltammetry (DPV) measurement technique was employed in this detection. Tap water from the Cleveland, Ohio, USA regional water district was the test medium. Concentrations of lead ion in the range of 8 X 10^-8 M to 8 x 10^-4 M were evaluated. This DPV detection system required 3 -6 minutes to complete the detection measurement. A longer measurement time of 6 minutes was used for the lower lead ion concentration. The selectivity of this lead ion sensor was very good, and Fe III, Cu II, Ni II and Mg II at a concentration level of 5×10^-4 M did not interfere with the lead ion measurement.

The Greater Amanzule Peatland (GAP) in Ghana represents an important ecosystem facing dynamic land cover changes as a result of both natural and anthropogenic factors. This study integrates multispectral and radar remote sensing data from Landsat-7 and -8, L-band SAR, and SRTM to conduct a machine learning-based analysis of these changes from 2010 to 2020 and to predict future scenarios up to 2040. Findings reveal a 12% expansion in peatland cover, equivalent to approximately 6,570 ± 308.59 hectares, despite declines in specific peatland types. Concurrently, anthropogenic land uses have increased, evidenced by an 85% rise in rubber plantations (from 30,530 ± 110.96 hectares to 56,617 ± 220.90 hectares) and a 6% reduction in natural forest cover (5,965 ± 353.72 hectares). Sparse vegetation, including smallholder farms, decreased by 35% from 45,064 ± 163.79 hectares to 29,424 ± 114.81 hectares. Projections for 2030 and 2040 indicate minimal changes based on current trends; however, these do not consider potential impacts from climate change, large-scale development projects, and demographic shifts, necessitating cautious interpretation. The results highlight areas of stability and vulnerability within the GAP and offer critical insights for the development of targeted conservation strategies. Additionally, the methodological framework presented provides a robust approach for accurate and detailed landscape-scale monitoring of tropical peatlands, applicable to other regions facing similar environmental challenges.

One of the main factors that influence the fertility of cattle in grazing systems in hot tropical climates is heat stress. The objective of this study was to evaluate the effect of season, breed, hormonal and physiological condition on the quantity and quality of cumulus-oocyte complexes (COCs) and embryos produced in vitro, from Romosinuano (RM) and Tropical Milking (TM) donors. Three ovum pick-up and in vitro fertilization (OPU-IVF) were performed, one per season; hot dry (HD; 10, 10), hot humid (HH; 9, 9) and fresh dry (FD; 7, 10) in RM and LT donors. Serum levels of cortisol, insulin and glucose were measured, in addition to heart rate (HR), respiratory rate (RR) and rectal temperature (RT). Effect of season x genotype interaction (p≤0.05) was observed in all COCs variables and only in cleavage embryos (CLI) (p≤0.05). Body weight (BW) affected all COCs variables (p≤0.01), except unviable (UNV) although affected degenerated embryos (DEG) (p≤0.01) and total blastocysts (BLAST) (p≤0.01). Cow age only affected viable COCs (VIAB) (p ≤ 0.05), code one blastocysts (BC1) and BLAST (p≤0.01). Cortisol affected total COCs (COCsT), VIAB and total matured in vitro (TMIV) (p≤0.01), as well as CLI, BC1 (p≤0.01) and BLAST (p≤0.05). Insulin affected COCsT (p≤0.01), UNV (p≤0.05), denuded oocytes (DE) (p≤0.01), BC1 and code two blastocysts (BC2) (p≤0.01). Glucose affected all COCs variables (p≤0.01), except UNV and all embryo variables except BC2. HR affected COCsT, DE, TMIV (p≤0.01), CLI, BLAST and DEG (p≤0.05). RR affected COCsT, UNV, VIAB, CLI (p≤0.05), BC1, BLAST and DEG (p≤0.01). RT only affected DE, VIAB (p≤0.01) and BLAST (p≤0.05). The seasonal climatic year variation of Veracruz and changes in physiological and hormonal variables have diverse effects on the cumulus-oocyte complexes and embryos produced by RM and TM donors.

This review article focuses on the role of Artificial Intelligence (AI) in transforming healthcare in Africa, specifically in combatting infectious diseases, neglected tropical diseases (NTDs), and antimicrobial resistance. We provide a comprehensive overview of the significance of AI in the healthcare industry, highlighting its urgency and importance in addressing these specific health challenges in Africa. We begin by discussing the role of AI in infectious disease surveillance and outbreak detection. We explore how AI technology can be employed for real-time tracking and prediction of outbreaks, providing examples of successful AI applications in infectious disease surveillance within the African context.Next, we examine the potential of AI-enabled diagnosis and treatment for faster and more accurate diagnoses of infectious diseases and NTDs. We highlight specific examples of AI applications in diagnosing and treating these diseases in Africa, showcasing the potential of AI to improve clinical outcomes and save lives.Furthermore, we focus on how AI-driven drug discovery and development can expedite the search for new treatments for infectious diseases and combat antimicrobial resistance. We present examples of AI applications in drug discovery within the African context, illustrating the potential for AI to revolutionize the development of effective therapeutics.In addition, we delve into how AI-powered public health interventions can enhance the design and implementation of targeted interventions. We explore how AI can optimize resource allocation and facilitate data-driven decision-making processes, providing examples of AI applications in public health in Africa.Finally, we address the challenges and limitations of implementing AI in combatting infectious diseases, NTDs, and antimicrobial resistance in Africa. We discuss potential barriers and ethical concerns surrounding AI applications in healthcare, aiming to encourage informed and responsible utilization of AI technologies.Overall, this review emphasizes the importance and potential of AI in combatting infectious diseases, NTDs, and antimicrobial resistance in Africa. It positions AI as a catalyst for revolutionizing healthcare in the region, leading to more effective disease surveillance, diagnosis, treatment, drug discovery, and public health interventions.

Flood modeling and forecasting are key to managing and preparing for extreme flood events. Hydrological flood forecasting aims to predict the system response to different input changes with minimum uncertainties. In that sense, streamflow Data Assimilation (DA) seeks to combine errors between hydrological model and water discharge observations through the update of model states. This paper aims to assess a sub-daily flood forecast system in a basin of the Peruvian Tropical Andes using two sequential data assimilation algorithms called the Ensemble Kalman Filter (EnKF) and the Particle Filter (PF). The study was conducted in the Vilcanota River basin during the rainiest months in 2022 to assess recent potential river floods. This basin is in the southern Peruvian Andes and was selected because it is continually affected by river floods such as occurred in 2010. For this purpose, the lumped GR4H rainfall-runoff model was run forward with 100 ensemble members using two different Satellite Precipitation sources (IMERG-E' and GSMaP-NRT'). Also, four DA experiments (IMERG-E'+EnKF, IMERG-E'+PF, GSMaP-NRT'+EnKF, and GSMaP-NRT'+PF) were conducted by assimilating real-time hourly discharges at the Pisac stream gauge station to examine the improvement of forecast accuracy for lead times of 1—24 hours. Results display good forecast performances during the first 10 hours, especially for the GSMaP'+EnKF scheme. Finally, this work benchmarks the application of streamflow DA in and Andean basin of Peru with sparse data availability and will support the development of more accurate climate services in Peru through hydrologic ensemble predictions.

This study aims to identify the optimal combination of microphysics (MP) and cumulus (CU) parameterization schemes for accurately simulating heavy to violet rainfall events associated with Tropical Cyclones (TCs) and atmospheric disturbances in Thailand using the coupled Weather Research and Forecasting (WRF) and Regional Oceanic Model (ROMS), hereafter referred to as WRF-ROMS. Three CU schemes, namely Betts–Miller–Janjic (BMJ), Grell 3D Ensemble (G3), and Kain–Fritsch (KF), along with three MP schemes, namely Eta (ETA), Purdue Lin (LIN), and WRF Single-moment 3-class (WSM3), are selected for the sensitivity analysis. Seven instances of heavy to violent rainfall in Thailand, occurring during summer season of 2020 and associated with tropical storms and atmospheric disturbances, are simulated using all possible combinations of the chosen physics schemes. The simulated rain intensities are compared against observations from the National Hydroinformatics Data Center. Performance was assessed using the Probability of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) metrics. The models showed proficiency in predicting light to moderate rainfall, with certain combinations performing better in specific rainfall categories. However, forecasting heavy and violent rainfall proved challenging for all models and lead-time forecasts. Specific combinations, particularly those incorporating the KF scheme, demonstrated superior prediction of heavy to violent rainfall. The FAR values increased with lead-time and rain intensity, and the KF scheme combinations showed improved predictions of intense rainfall with lower FAR values. The CSI values indicated comparable performance between the control model and combination models across light to heavy rain categories, with the KF scheme showing better predictions for longer lead-times. However, accurately predicting intense rainfall remained limited. These findings highlight the need for further improvements, including refining model parameters and exploring advanced techniques to enhance accuracy and skill, particularly for longer-term forecasts. Sub-seasonal to seasonal prediction should be considered to extend forecast capabilities.

Trypanosomatids are mainly responsible for leishmaniasis, sleeping sickness, and Chagas disease, which are the most challenging among the neglected tropical diseases due to the problem of drug resistance. Although problems of target deconvolution and polypharmacology are encountered, a target-based approach is a rational method for screening drug candidates targeting a biomolecule that causes diseases. The present study aims to summarize the latest information re-garding potential inhibitors of squalene synthase and farnesyl phosphate synthase with anti-Trypanosomatidae activity. The information was obtained by referencing textbooks and major scientific databases from their inception until April 2023. Based on in vitro experiments, more than seventy compounds were reported to inhibit squalene synthase and farnesyl diphosphate synthase. Among these compounds, more than 30 were found to be active in vitro against Trypanosomatidae, inferring that these compounds can be prospected as scaffolds for the development of new drugs against trypanosomatid-related infections. Over-all, natural and synthetic products can inhibit enzymes that are crucial for the survival and virulence of trypanosomatids. Moreover, in vitro experiments have confirmed the activity of more than half of these inhibitors using cell-based as-says. Nevertheless, additional studies on the cytotoxicity, pharmacokinetics, and lead optimization of potent anti-Trypanosomatid compounds should be investi-gated.

The difficulty in obtaining commercial fertilizers by smallholder farmers in sub-Saharan Africa makes it very important to optimize the use of local organic resources. In VilanKulo, Mozambique, a study was carried out on okra (Abelmoschus esculentus) over two growing seasons in a haplic Lixisol, a loamy-sand textured soil, applying both bat guano and biochar prepared by an artisanal process. Bat guano was applied at two rates (5 and 10 t ha−1), one month and just before sowing. Biochar was also used at two rates (5 and 10 t ha−1) applied close to sowing. Mixtures of biochar and guano at two rates (1 and 4 t ha−1, and 2 and 8 t ha−1, respectively) were also used along with a non-fertilized control. Field trials were arranged in a completely randomized design with three replicates. The treatments receiving high rates of guano tended to show significantly higher fruit yields (&gt; 10 t ha−1, being the two-year average) in comparison to the control, which showed the lowest average okra fruit yield (6.21 t ha−1). In guano treatments, the apparent recovery by okra of some important nutrients, such as nitrogen (N), was greater than the amount of nutrient contained in the guano itself. This result, together with many others related to tissue nutrient concentration, soil properties and residual fertilizing value in guano plots, indicates a strong mineralization of guano during the growing season, probably due to its low carbon (C)/N ratio and favourable environmental conditions for the mineralization process, such as high temperature and well-aerated soil. The result also suggests some kind of manuring effect, i.e., a fertilizing effect of guano beyond what can be explained by the nutrient supply. The use of biochar increased total organic C in the soil and cation exchange capacity (CEC) compared to the control, but did not affect variables related to plant performance, such as tissue nutrient concentration or plant growth and yield.

Stingless bee beekeeping provides new opportunities to improve the incomes of many households in Malaysia through the sale of honey and other bee products. While Heterotrigona itama is one of the most commonly cultured species of stingless bees, its behavior is not very well understood. Hence, we conducted this study to investigate the behavior of H. itama in exploiting food sources by ascertaining the nectar sugar concentration preferred by the bee. We also aimed to determine the preferred distance of food source from the bee hive. Our results suggest that H. itama prefers high sugar concentrations of 35% and above, and they would fly up to 7 m from the hive to collect food. We discuss how nectar concentration and food distance influence the number of bees exploiting food sources and the overall foraging pattern of H. itama.

My innovative entropy measure, Ismail entropy, namely, (IE) is an ultimate generalization to numerous generalized entropies within the literature. The fractal dimension of IE is identified in this paper. On another applicative note, this paper offers some potential applications of fractal dimension to smart cities. The paper ends with closing remarks combined with some challenging open problems and the next phase of research.

This study examines how profitability moderates capital structure and dividend policy in selected Sub-Saharan African manufacturing enterprises. The study analyses 2012–2022 data from 131 listed firms in six countries using a quantitative and ex post facto research design. Debt-to-equity, asset structure, debt-to-asset, and return on assets are variable of interest. The debt-to-equity ratio negatively affects dividend policy, but asset structure positively affects it, according to pooled OLS and moderated regression models. Profitability considerably moderates the association between debt-to-equity and dividend policy, while debt-to-asset ratio has a positive but negligible influence. The findings emphasize the role of profitability in financial decision-making and suggest that firms should balance their capital structure and profitability to optimize dividend policies. The study fills gaps in emerging economy literature and offers managers and policymakers practical advice to improve financial performance and shareholder value in Sub-Saharan African-listed manufacturing enterprises.

Innovative urban farming plays a vital role in enhancing food security, nutrition, livelihood resilience, and environmental sustainability in Sub-Saharan African cities. Despite this, agricultural policy and extension services have largely ignored urban contexts. Recently, national and international initiatives have started addressing this oversight by promoting circular innovations in urban food systems. To boost productivity, it is crucial to understand the challenges, opportunities, and prospects associated with innovative urban farming. Therefore, exploratory qualitative research, specifically focus group discussions, was conducted in Alimosho Local Government Area of Lagos, Nigeria, to gather the perspectives of various stakeholders. The analysis, using mind maps and a consensus index, compared views from private urban farming practitioners and local public sector representatives. Urban farmers see significant potential in innovative technologies such as hydroponics, aquaponics, recirculating aquaculture systems (RAS), drip irrigation, sack farming, and waste upcycling to improve productivity. However, they express frustration over the lack of public sector support for embracing these circular innovations. Conversely, public sector representatives cite urban farmers' behavioral and educational shortcomings, particularly their lack of internal coordination and commitment to adopting innovations. These discrepancies underscore the complex interactions between urban farmers and local public agricultural policymakers and extension agents. The study highlights the need for fundamental changes in both public and private sectors to address the challenges in urban farming innovations. Establishing local-level dialogues, as demonstrated in this study, can provide valuable insights for developing urban farming and policy in Sub-Saharan Africa.

A novel low-power MOS-only voltage reference is presented. The Enz-Krummenacher-Vittoz (EKV) model is adopted to provide a new perspective on the operating principle. The normalized charge density, introduced as a new variable, serves as an indicator when trimming the output temperature coefficient. The proposed voltage reference consists of a specific current generator and a 5-bit trimmable load. Thanks to the well-match between the current source stage and the output stage, the non-linear temperature dependence of carrier mobility is automatically canceled out. The circuit is designed in 55 nm COMS technology. The operating temperature ranges from -40 ∘C to 120 ∘C. The average temperature coefficient of the output voltage can be reduced to 21.7 ppm/∘C by trimming. The power consumption is only 23.2 nW with a supply voltage of 0.8 V. The line sensitivity and the power supply rejection ratio at 100 Hz are 0.011 %/V and -89 dB respectively.

Introduction: Nephrotic syndrome (NS) remains the most frequent mode of presentation of glo-merular diseases in children; in addition, the NS is primitive, i.e., idiopathic in 90% of cases with an average age of onset between 2 and 10 years. The objective of our study was to describe the char-acteristics and outcome of NS in children from 3 major hospitals from one of the poorest countries worldwide (Chad). Patients and Methods: Observational, cross-sectional, descriptive and multicenter study which took place over a period of 36 months (January 1,2019-December 31,2021) carried out in 3 hospitals in N’Djamena (Chad). All children aged 1-15 years presenting with NS were included. Results: Out of 16,776 children hospitalized or followed-up in outpatient clinics, 24 cases of NS were identified, giving a prevalence of 0.14%. The median age at presentation was 6.16(1-10) years. Nineteen children were male (sex ratio 3.8). There were 8 impure NS (33.3%). Edema was present in all patients, oliguria in 29.16%(n=7), and arterial hypertension in 20.83%(n=5) of cases. Mean proteinuria, albuminemia and total proteins were 2.86g/L, 19.13g/L and 30.41g/L respectively. Median serum creatinine was 87.3 µmol/L(75-1375µmol/L); three patients had acute renal failure on admission. Four patients had secondary NS. All patients (n=20) with idiopathic NS had received corticosteroid therapy; steroid-sensitivity was found in 90% of patients. Those who were not ster-oid-sensitive or relapsed underwent kidney biopsy (n=7); the most represented histological lesion was focal segmental glomerulosclerosis (FSGS; n=4), followed by minimal change disease (n=2), and membranoproliferative glomerulonephritis (n=1). The median length of hospitalization stay was 10.67 (5-27) days. None of the patients with idiopathic NS died. At last follow-up sixteen patients (80%) achieved long-term complete remission with normal renal function; however, 4 had subse-quent relapses. 16 patients. One patient with secondary NS died. Conclusion: In Chad childhood idiopathic nephrotic syndrome involves mostly young male; steroid sensitivity is as high as 95% and in the long-term 80% of the patients are in remission with normal renal function.

In this paper, a new multi parameter iterative algorithm is proposed to address the PageRank problem based on the multi-splitting iteration method described by Gu et al . The proposed method in each iteration needs to solve two linear subsystems by splitting the coefficient matrix, therefore, we consider inner and outer iteration to find the approximate solutions of these linear subsystems. It can be shown that the iterative sequence generated by the multi parameter iterative algorithm finally converges to the PageRank vector when the parameters satisfy the certain conditions. Numerical experiments show that the proposed algorithm has better convergence and numerical stability than the existing algorithms.

Infection of liver flukes (Opisthorchis viverrini) is partly due to their suitability for habitats in sub-basin areas, which causes the intermediate host to remain in the watershed system in all seasons. Spatial monitoring of fluke infection at the small -basin analysis scale is important because this can enable analysis at the level of the spatial factors involved and influencing infections. A geographic weighted regression model was developed to analyze the spatial characteristics of liver fluke infection, aiming to 1. analyze the spatial factors associated with human liver fluke infection according to sub-basin boundaries and 2. generate an alternative model for enhancing the effectiveness of preventive public health management to reduce the risk of liver fluke infection in humans. The number of infected persons was obtained from local authorities and converted into a percentage of infected people and generated as raster data with a heat map so that the data were continuous and defined as dependent variables. The independent set consisted of nine variables, both vector and raster data, that correlated the location with the village location of an infected person. The results showed that the variables X5stream, X7ndmi, and X9savi were statistically significantly correlated to the percentage of infected people, with the t-stat and p-value being (-2.068, 1.875, and -2.661) and (0.048, 0.034, and 0.021), respectively. The GWR model was able to increase accuracy more than the comparable models such as OLS, in all tests of the four alternative models, with an accuracy increase in R2 of 7.69% (0.576 to 0.624). This study confirms that the development of spatial models with GWR models can screen for factors associated with liver fluke infection at the level of small spatial units such as sub-basins.

Land resources have been under tremendous anthropogenic pressure with the consequence of their degradation. It is therefore necessary that the land resources must be managed effectively for sustainable development. Different from the developed countries, carbon inventories and data bank to monitor carbon sequestration potential of different ecosystems are unavailable in India. Micro-level studies are essential for sustainable land use management for a land scarce nation like India. To achieve the desirable goal of the present study, a total of 33 tree-based land uses were identified from forested and agricultural landscapes. Of these total land uses, five were in forest landscapes and rest in agricultural landscapes categorized into forest tree plantations (8 land uses), agroforestry (nine land uses), commercial crop plantations (six land uses) and fruit orchards (five land uses). A stratified random nested quadrate sampling method was adopted for vegetation analysis of the different land uses. The SOC, biomass and carbon accumulation in the tree-based land uses were significantly different from each other. Mixed forest soil had the highest amount of SOC, primary nutrients, standing biomass carbon, and ecosystem carbon. Positive correlations were observed between SOC, total standing biomass, litter production, and ecosystem carbon. The sequence of best tree based land uses in terms of total SOC (up to 60 cm depth), total plant biomass, total plant biomass carbon and ecosystem carbon was mixed species forest (126.67, 781.21, 390.61 and 517.27) > sole tree species stands in forest landscape (109.71, 192.56, 96.28 and 205.98) > tea plantations (103.19, 77.07, 38.54 and 141.74) > homegardens (90.34, 97.38, 48.69 and 139.02) > mixed plantation of Anthocephalus cadamba + Swietenia macrophylla (60.07, 111.86, 55.93 and 116.02) > Swietenia macrophylla based agroforestry (62.49, 83.82, 41.91 and 104.40) > mixed plantation of Tectona grandis + Milvus migrans (60.0, 85.97, 42.99 and 102.90). Similarly, the order of the major land uses was forest > commercial crop plantation > forest tree plantations > agroforestry > fruit orchards. The overall average ecosystem carbon accumulation in forests was 3.24 times more than the land uses in agricultural landscapes. The ecosystem carbon accumulation in the tree-based land uses in both forest and agricultural landscape was highly variable and was significantly different from each other. Land use conversion from forest to agriculture can reduce more than half of the carbon stock, but converting into homegardens, tree plantations or agroforestry enhanced carbon storage of the land use systems. The present findings can be used as baseline information for developing prediction models for probable effects of different land use, future intervention and sustainable management of land use systems.

The quantification of sea surface temperature (SST) through space platforms has revolutionized how we obtain information at a global level. However, the main disadvantage of obtaining SST with satellite images consists of its inherent coarse spatial resolution. One solution could be the use of downscaling algorithms to create sequences of matrices at a higher resolution. We used the same SST data source from the MODIS-Aqua sensor at three spatial resolutions of 9 km, 4.5 km, and 1 km in the Gulf of California. Based on an open-source algorithm, the original SST images were downscaled to 4.5 km, 1 km, 500 m, 250 m, and 125 m per pixel scales. Results indicate a strong linear relationship between the original SST-MODIS data and the modeled data for all spatial resolutions. This study demonstrates the feasibility of an open-source downscaling algorithm to enhance the spatial resolution of SST images in a marginal sea.

Validation of satellite sea surface salinity (SSS) products is typically based on comparisons with in-situ measurements at a few meters depth, that are mostly done at a single location and time. The difference in term of spatio-temporal resolution between the in-situ near-surface salinity and the two-dimensional satellite SSS results in a sampling mismatch uncertainty. The Climate Change Initiative (CCI) project has merged SSS from three satellite missions. Using an optimal interpolation, weekly and monthly SSS and their uncertainties are estimated at a 50 km spatial resolution over the global ocean. Over the 2016-2018 period the mean uncertainty on weekly CCI SSS is 0.13, whereas the standard deviation of weekly CCI minus in-situ Argo salinities is 0.24. Using high resolution SSS simulations, we estimate the expected uncertainty due to the CCI versus Argo sampling mismatch. Most of the largest spatial variability of the satellite minus Argo salinity are observed in regions with large mismatch. A quantitative validation is performed by considering the statistical distribution of the CCI minus Argo salinity normalized by the sampling and retrieval uncertainties. This quantity should follow a Gaussian distribution with a standard deviation of 1, if all uncertainty contributions are properly considered. We find that 1) the sampling mismatch can explain most of the observed differences between Argo and CCI data, especially for monthly products and in dynamical regions (river plumes, fronts), 2) overall, the uncertainties are well estimated in CCI version 3, much better compared to CCI version 2. There are a few dynamical regions where discrepancies remain, and where the satellite SSS, their associated uncertainties and the sampling mismatch estimates should be further validated.

Global malaria epidemiology has changed in the last decade with a substantial increase in cases and death being recorded. Over 90% of global cases and deaths occur in Sub-Saharan Africa (SSA). Tanzania accounts for about 4% of all cases and deaths reported in recent years. It is believed that several factors contribute to the resurgence of malaria, parasite resistance to antimalarials and mosquito resistance to insecticides being at the top of the list. The presence of sub-microscopic infections poses a significant challenge to malaria rapid diagnostic tests (mRDT), particularly in low-endemic areas. Our cross-sectional surveys in Handeni and Moshi, Tanzania assessed the effect of low parasite density on mRDT. A significant difference (P˂0.001) in malaria prevalence by mRDT, light microscopy (LM) and nested polymerase chain reaction (PCR) was found among age groups. In comparison to all other groups, school-age children (5-15 years) had the highest prevalence of malaria. Based on the results of this study, mRDT may miss up to 6% of cases of malaria mainly due to low-density parasitaemia. Routinely used mRDT will likely miss the sub-microscopic parasitemia which will ultimately contribute to the continued spread of malaria and hinder efforts to control and eliminate it.

Human papillomavirus (HPV) self-sampling (Self-HPV) is a promising strategy to improve cervical cancer screening coverage in low-income countries. However, issues associated with women who prefer conventional HPV clinical-sampling over HPV self-sampling may affect screening participation. To address this issue, our study assessed factors associated with women’s preferences related to Self-HPV. This study was embedded in a large clinical trial recruiting women aged 30–49 years in a primary HPV-based study termed “3T-Approach” (for Test-Triage-Treatment), launched in 2018 at Dschang District Hospital, West Cameroon. Participants were invited to perform a Self-HPV. After the sampling and before receiving the results, participants completed a questionnaire about cervical cancer screening and their preferences and perceptions around Self-HPV. The median age of the 2201 participants was 40.6 (IQR 35–45) years. Most (1693 (76.9%)) preferred HPV self-sampling or had no preference for either method and 508 (23.1%) preferred clinician-sampling. Factors associated with an increased likelihood of reporting a clinician-sampling preference were tertiary educational level (14.4% CI: 12.8–16.1 vs 29.5% CI: 25.6–33.6) and being an employee with higher grade professional or managerial occupations (5.5% CI: 3.8–7.9 vs 2.6% CI: 2.3–2.8). The main reported reason for women preferring clinician-sampling was a lack of “self-expertise”. Most women (&gt;99%) would agree to repeat HPV self-sampling and would recommend it to their relatives. HPV self-sampling in the cultural context of central Africa was well accepted by participants, but some participants would prefer to undergo clinician sampling. Health systems should support well-educated women to increase self-confidence in using HPV self-sampling.

Critical care of neonates involves substantial usage of antibiotics and exposure to multidrug resistant (MDR) nosocomial pathogens. These pathogens are often exposed to sub-MIC doses of antibiotics which might result in a range of physiological effects. Therefore, to understand the outcome of sub-inhibitory dosage of antibiotics on Staphylococcus populations, nasal swab specimens were collected from 34 neonates admitted to the Sick Newborn Care Unit between 2017-2018, a total of 41 non-repetitive isolates were included in this study. Staphylococcus haemolyticus was the prevalent species (58.54%) with high non-susceptibility to cefotaxime (CTX) (79.16%), gentamicin (87.50%), and meropenem (54.17%). Biofilm forming abilities of S. haemolyticus isolates in the presence of sub-optimal CTX (30μg/mL), the predominantly prescribed β-lactam antibiotic, were then determined by crystal violet assays and extracellular DNA (eDNA) quantitation. CTX was found to significantly enhance biofilm production among the non-susceptible isolates (p-valueWilcoxin test- 0.000008) with increase in eDNA levels (p-valueWilcoxin test- 0.000004). Additionally, no changes in non-susceptibility were observed among populations of two MDR isolates, JNM56C1 and JNM60C2 after >500 generations of growth in the absence of antibiotic selection in vitro. These findings demonstrate that sub-MIC concentration of CTX induces biofilm formation and short-term non-exposure to antibiotics does not alter non-susceptibility among S. haemolyticus isolates.

This paper examines the asymmetrical relationship between exchange rate and consumer prices in 40 Sub-Saharan African (SSA) countries from 1990q1 to 2017q4. The exchange rate pass-through (ERPT) to consumer prices is estimated for each country by using the nonlinear autoregressive distributed lags (NARDL) framework and dynamic panel estimators robust to cross-sectionally correlated errors. Firstly, our findings suggest an asymmetrical ERPT in the SSA region during the short-term, whereas there are mixed results across sub-regions in the long-term. Next, we find incomplete and significant ERPT to consumer prices in the entire SSA region which is higher during the depreciation of the local currency than after appreciations. Third, we find nonlinear ERPT with respect to the size of the exchange rate. The pass-through is higher during large exchange rate changes than after small changes. Finally, we find that the pass-through is greater in the countries with fixed exchange rate regime (CFA franc zone) having low inflationary environment than in the other SSA countries with flexible exchange rate regime and high inflation levels. As a result, policymakers should take into account these asymmetries and non-linearities to improve the credibility of monetary policy, strengthen trade liberalization and establish competitive market structures in the Sub-Saharan region.

The unsustainability of the services related to water, sanitation and hygiene in informal settlements in Sub-Saharan Africa services is deeply embedded in current societal and governance structures, cultures and practices; it is context-dependent and involves numerous actors with different interests. The field of sustainability transitions research addresses such persistent and large scale societal challenges, with transition management being one of its widely applied governance approach. By drawing on an analysis of the root causes of unsustainability and unreliability of WASH services in three case studies in Sub-Saharan Africa (Arusha-Tanzania, Dodowa-Ghana, Kampala-Uganda), we explore how a transition management approach can be designed to support a transition towards sustainable Water, Sanitation and Hygiene (WASH) in Sub-Saharan Africa. We distinguish the following contextual dimensions related to the unsustainability of WASH services: a) Multiplicity of WASH practices, structures and arrangements, b) Governance capacities for WASH services and maintenance, c) Landownership for sustainable access to WASH, d) Public participation in decision-making related to WASH, e) socio-economic structures governing access to WASH. These dimensions prompt the identification of conceptual and application challenges for transition management. Based on these challenges, recommendations were formulated for the design of a prescriptive transition management process that is not only functional but also emancipatory of character.

Abstract: Rice is one of the most important food crops in sub-Saharan Africa. Climate change, variability, and economic globalization threaten to disrupt rice value chains across the subcontinent, undermining their important role in economic development, food security, and poverty reduction. This paper maps existing research on the vulnerability of rice value chains, synthesizes the evidence and the risks posed by climate change and economic globalization, and discusses agriculture and rural development policies and their relevance for the vulnerability of rice value chains in sub-Saharan Africa. Important avenues for future research are identified. These include the impacts of multiple, simultaneous pressures on rice value chains, the effects of climate change and variability on parts of the value chain other than production, and the forms and extent to which different development policies hinder or enhance the resilience of rice value chains in the face of climatic and other pressures.

This study aims to assess the impact of deforestation and carbon sequestration within the Gandoca-Manzanillo Wildlife Refuge, Costa Rica, using high-resolution satellite imagery from Planet NICFI and Sentinel-2. The research evaluates the impact of forest degradation on forest health and carbon absorption during two periods in 2024 (January and August). Advanced vegetation indices (NDVI, GNDVI, EVI, and SAVI) were applied to assess changes in forest cover and health. Planet NICFI data revealed a 0.41% loss in forest cover, identifying subtle degradation less detectable with Sentinel-2. In terms of carbon sequestration, Sentinel-2 showed a modest increase in CO₂ absorption from 180,231.88 tons to 186,211.33 tons, while Planet NICFI indicated a decrease from 3,984,470.82 tons to 3,820,917.83 tons, suggesting forest degradation. These findings highlight the importance of high-resolution satellite imagery in detecting fine-scale disturbances that lower-resolution data might miss. However, the study’s short timeframe, covering only two periods in 2024, limits long-term trend analysis. The research underscores the need for improved remote sensing technologies and stronger legal frameworks to protect areas like Gandoca-Manzanillo from illegal logging. Despite programs like Payment for Ecosystem Services (PES) in Costa Rica, significant challenges remain in protecting biodiversity-rich regions.

Lassa Fever is a deadly viral haemorrhagic disease, causing annually several hundreds of deaths in the Gulf of Guinea. This zoonotic disease is primarily transmitted to humans by rodents of the genus Mastomys, while secondary interhuman transmission accounts for approximately 20% of cases. Although this disease has been endemic in rural zones of the Gulf for hundreds of years, it is also characterised by epidemic outbreaks in the dry season, responsible for heavy death tolls. No licensed vaccine or satisfying treatment is currently available. Disease management is hindered by the incomplete knowledge of the epidemiology and distribution of the disease, resulting from an inadequate health and surveillance system. Additional scientific constraints such as the genetic diversity of the virus and the lack of understanding of the mechanisms of immune protection complexify the development of a vaccine. The intricate socio-economic context in the affected regions, and the lack of monetary incentive for drug development, allow the disease to persist in some of West Africa’s poorest communities. The increase in the number of reported cases and in the fatality rate, the expansion of the endemic area, as well as the threat Lassa Fever represents internationally should urge the global community to work on the disease control and prevention. The disease control requires collaborative research for medical countermeasures and tailored public health policies. Lassa Fever, created by the interconnection between animals, humans, and ecosystems, and embedded in an intricate social context, should be addressed with a ‘One Health’ approach. This article provides an overview of Lassa Fever, focusing on Nigeria, and discusses the perspectives for the control of disease.

Estimating the ocean’s subsurface thermohaline information from satellite measurements is essential for understanding ocean dynamics and El Niño phenomenon. This paper proposes an improved double-output Residual Neural Network (DO-ResNet) model to concurrently estimate the ocean subsurface temperature (OST) and ocean subsurface salinity (OSS) in the tropical Western Pacific using multi-source remote sensing data, including sea surface temperature (SST), sea surface salinity (SSS), sea surface height anomaly(SSHA), sea surface wind (SSW), and geographical information (including longitude (LON) and latitude (LAT)). In the model experiment, Argo data were used to train and validate the model, and the root mean square error (RMSE), normalized root mean square error (NRMSE) and coefficient of determination (R²) were employed to evaluate the model's performance. The results showed that the sea surface parameters selected in this study have a positive effect on the estimation process, and the average RMSE and R² values for estimating OST (OSS) by the proposed model are 0.34 °C (0.05 psu) and 0.91 (0.95), respectively. Under the data conditions considered in this study, DO-ResNet demonstrates superior performance relative to the extreme gradient boosting model, random forest model, and artificial neural network model. Additionally, this study evaluates the model’s accuracy by comparing its estimations of OST and OSS across different depths with Argo-derived data, demonstrating the model's ability to effectively capture the most spatial features, and by comparing NRMSE across different depths and seasons, the model displays strong seasonal adaptability. In conclusion, this research introduces a novel artificial intelligence technique for estimating OST and OSS in the tropical Western Pacific Ocean.

The Puuc Biocultural State Reserve (PBSR is an unique model for tropical dry forest conservation in Mexico. Preserving forest biodiversity and carbon within the PBSR depends on the mainte-nance of low impact productive activities coordinated by multiple communal and private land-owners. In this study, we used state-of-the-art remote sensing data to investigate past spatial patterns in forest clearing dynamics and its relation to forest carbon density and forest plant species richness and diversity in the context of the forest conservation goals of the PBSR. We used a Landsat-based continuous change detection product for the 2000-2021 period and compared it to carbon density and tree species richness models generated from ALOS-2 PALSAR 2 imagery and national scale forest inventory data. The estimated error-adjusted area of detected annual forest clearings from the year 2000 until the year 2021 was 230,511 ha in total (+19,979 ha). The analysis of annual forest clearing frequency and area suggests that although forest clearing was significantly more intensive outside of the PBSR than within the PBSR during the entire 2000-2021 period, there is no evidence suggesting that the frequency and magnitude of forest clearing has changed over the years after the creation of the PBSR in 2011. An emergent hotspot analysis shows, however, that high spatiotemporal clustering of forest clearing events (hotspots) during the 2012-2021 pe-riod was less common than prior to 2011 and these more recent hotspots have been confined to areas outside the PBSR. After comparing forest clearing events to carbon density and tree species richness models, results show that land owners outside the PBSR often clear forests with lower carbon density and species diversity than land owners inside the PBSR. This suggests that, compared to land owners outside the PBSR, land owners within the PBSR might be practicing longer fallow periods allowing forests to attain higher carbon density and tree species richness and hence better soil nutrient recovery after land abandonment. In conclusion, our results show that the PBSR effectively acted as a stabilizing forest management scheme during the 2012-2021 period minimizing the impact of productive activities by lowering the frequency of forest clearing events and preserving late secondary forests within the PBSR. We recommend the continuation of efforts for providing alternative optimal field data collection strategies and modeling techniques to spatially predict key tropical forest attributes. The combination of these models with contin-uous change detection datasets will allow to reveal underlying ecological processes and generate information better adapted to forest governance scales.

Objective: The objective of this study is to determine the epidemic dynamics and clinical features of COVID-19 in southern Hainan Island, China, and provide experience for other tropical areas of the world. Methods: This retrospective study included confirmed cases of COVID-19 in southern Hainan. All enrolled patients were treated in Sanya, and data on epidemiological and clinical features of the disease and infection prevention and control measures adopted by the local government during the epidemic were collected. Results: Of the 74 cases, 71 (95.95%) were imported from Wuhan, Hubei Province (47, 63.51%), other cities in Hubei Province (11, 14.86%), or provinces other than Hubei and Hainan (13, 17.57%). Three (4.06%) patients were infected in southern Hainan, including one autochthonous case in Sanya. Fifty-four cases (72.97%) were detected in Sanya, and 27 cases (27.03%) were diagnosed in other cities. The rate of severe or critical cases was 28.38% (21/74), and mortality was 2.7% (2/74). The serum lactate levels and base excess of severe-critical patients were higher than those of patients with mild-moderate disease. Multivariate logistic regression analysis showed that chronic conditions were risk factors for severe and critical COVID-19. Seventy-four patients were diagnosed with COVID-19 over a 22-day period in Sanya, and the epidemic period in the city was 48 days. The outbreak was controlled rapidly because the local government adopted strict infection prevention and control measures. Conclusions: The clinical characteristics of COVID-19 in Hainan Island were similar to those reported in other regions. In Sanya, the rate of severe and very severe cases was higher than in other regions; however, most cases were imported, and there was only one autochthonous case. The rapid control of the outbreak in Sanya may be related to the tropical climate, adoption of strict infection prevention and control measures, daily reporting of new cases, increased public awareness about the epidemic, and other emergency actions implemented by the local government.

Data on the seasonally dry tropical forests of Mexico have been examined in the light of statistical mechanics. The results suggest a division into two classes of species. There are drifting populations of a cosmopolitan class capable of existing in most dry forest sites; these have a statistical distribution previously only observed (globally) for populations of alien species. A high proportion of species found only at a single site are endemic and these prefer sites comparatively low in species richness.