Tropical Research Research Articles

Sea surface temperature error under tropical cyclone in the western North Pacific.

Tropical cyclone forecasting relies on accurate sea surface temperature, yet the errors in available sea surface temperature products remain unclear. Here, I evaluate the sea surface temperature errors under tropical cyclones in the western North Pacific based on surface drifters across eight widely-used datasets, including satellite, atmospheric and oceanic analysis-or-reanalysis products, spanning from 2014 to 2023. The ensemble mean bias and root-mean-squared-error are firstly quantified. Both satellite and oceanic analysis sea surface temperatures exhibit a cold bias, while atmospheric analysis-or-reanalysis sea surface temperature shows a warm bias. Specifically, atmospheric analysis-or-reanalysis products consistently show a warm bias in the right-rear quadrant of the tropical cyclone coordinate system. Regarding root-mean-squared-error, for most products, the right side consistently exhibits higher errors than the left side. SST bias significantly impacts tropical cyclone intensity change as indicated by empirical relationship. These results provide direct insights for operational tropical cyclone forecasting and research.

Global malaria vaccine research and community perception in Africa: a systematic review

Abstract Background Malaria vaccine is one of the critical areas in tropical health research, considering the success recorded in other vaccine-preventable diseases. This review provides an overview of global malaria vaccine research and systematically reviews community perception of the vaccine in Africa. Methods A validated search was conducted to identify scientific literature on malaria vaccines in the Scopus database from 2005. Bibliometric indicators explored include publication/citation indices over time and the overall research themes using VOSviewer. A further in-depth search was undertaken in five databases to identify studies on community perception of malaria vaccine in Africa. Studies were screened, quality appraised, and narratively synthesized. Results 6457 malaria-vaccine-related documents were found in 160 journals/sources from 189 countries/territories. There were 214,323 total citations, with 33.2 average citations per document and 167 documents’ h-index. The United States, United Kingdom and Australia combined produced more than 60% of the publication output. Six themes emerged from the global malaria vaccine research: Merozoite surface protein, characterization, trials, infant/children, traveler, and research/review. Twenty studies (n = 20) met the inclusion criteria for the systematic review. Overall perceptions of malaria vaccines varied in African communities (26.2-88.2%), in addition to higher willingness to accept the vaccines (32.3%-96.0%), poor knowledge/awareness (11%-60%) and misconceptions (19.2%-20.9%). Other issues identified include vaccine availability and logistics. Conclusions Malaria vaccine research and citations have increased considerably, mainly targeting vaccine development and safety/efficacy in Africa. African communities’ perceptions of the vaccine varied, with most of the population willing to accept the vaccine. Key messages • An increase in number of malaria vaccine research targeting vaccine development, and safety and efficacy in Africa. • Varried malaria vaccine perception in Africa, including willingness to accept the vaccine, awareness, misconceptions, availability and logistics.

Evaluation of an electronic clinical decision support algorithm to improve primary care management of acute febrile illness in rural Cambodia: protocol for a cluster-randomised trial

IntroductionAcute febrile illness (AFI), traditionally attributed to malaria, is a common reason for seeking primary healthcare in rural South and Southeast Asia. However, malaria transmission has declined while health workers...

Utilization of EOS-06 Observations in Tropical Cyclone Research: A Case Study on Cyclone Mocha

Utilization of EOS-06 Observations in Tropical Cyclone Research: A Case Study on Cyclone Mocha

Improving soil moisture prediction with deep learning and machine learning models

Reliable soil moisture (SM) data is critical for effective water resources management, yet its accurate measurement and prediction remain challenging. This study was conducted to develop a deep learning regression network for sub-hourly SM prediction and compare its performance with traditional machine learning models, including the eXtreme gradient boosting (XGB), light gradient-boosting (LGB), cat boosting (CB), random forest (RF), k-nearest neighbors (kNN), and long short-term memory (LSTM) models. Sub-hourly SM, electrical conductivity (EC), soil temperature (ST), and weather parameters were collected during research experiments conducted for two years (2020–2021 and 2021–2022) at the Tropical Research and Education Center (TREC), University of Florida. A network of SM sensors and a weather station were installed at the experimental site with 24 plots of green beans and sweet corn under full and three deficit irrigation treatments with three replications. Model performance metrics such as coefficient of determination (r2) and global performance indicator (GPI) were used to evaluate the performance of the models. Results showed that all MLs and DL models performed more than satisfactorily in simulating SM of green beans and sweet corn plots. The testing average r2 and GPI of MLs were 0.83 and 0.02 (green beans) and 0.85 and 0.02 (sweet corn). However, XGB and LGB models outperformed the remaining ML and DL models. The testing r2 and GPI of XGB were 0.86 and 0.014 for green beans, whereas 0.88 and 0.015 for sweet corn. The r2 and GPI values for the LGB were 0.85 and 0.014 for green beans, while 0.88 and 0.015 for sweet corn. Even though DL model took longer and resources to be trained, its performance was not as accurate as that of XGB and LGB models. However, the performance of DL was better than the LSTM model. The r2 and RMSE of the LSTM model were 0.68 and 0.02cm 3 cm-3 for green beans and 0.75 and 0.02cm 3 cm-3 for sweet corn, respectively. Whereas the r2 and RMSE of DL were 0.84 and 0.015cm 3 cm-3 (green beans) and 0.85 and 0.02 cm 3 cm-3 (sweet corn). The ML and DL models performed better in simulating SM of sweet corn plots than green beans. Overall, these results confirmed that the ML and DL models could be alternative tools for SM prediction for agricultural fields, with potential applications for irrigation scheduling and water resources management.

Developing a photographic equipment description tool: insights from the Tropical Research Institute Collection in Lisbon

Photographic equipment that had been used in scientific missions in Portugal’s former Asian and African colonies and now held in the National Museum of Natural History and Science at Lisbon University are the focus of this study. It has been acknowledged that the description tool for cataloguing and accession used within the institution was too generic and could not account for the intersected fields and data necessary for characterising the technical and historical specificities of this equipment. To overcome this need, a literature review and a national and international survey were carried out to understand the descriptive methods and tools commonly used elsewhere. From this work it was concluded that there is no appropriate tool available. However, due to the Covid-19 pandemic, the authors decided to begin focussing on designing a multilevel description prototype tool suitable for the specificities of the project and the collection. The prototype was then discussed and evaluated in a working session with a group of Portuguese photographers, conservators and cultural heritage sector workers. The collaborative nature of that work allowed for the improvement of the prototype, which is now under further review. This article presents the scope and concept behind the design of the description tool, and outlines the various working stages undertaken and the contents and structure covered by the prototype.

Protocol of a cost-effectiveness analysis of a combined intervention for depression and parenting compared with enhanced standard of care for perinatally depressed, HIV-positive women and their infants in rural South Africa

IntroductionPoverty, HIV and perinatal depression represent a triple threat to public health in sub-Saharan Africa because of their combined negative effects on parenting and child development. In the resource-constrained context...

Assessment of Hepatocellular Carcinoma Patients Infected with Covid-19 Infection during the Pandemic

Hepatocellular carcinoma (HCC) patients are more susceptible to decompensation if they get Coronavirus disease 2019 (COVID-19) infection that leads to significant reduction in HCC related health services, reduction in surveillance activities and progression of HCC. On the other hand, symptoms of covid-19 infection are usually severe in HCC patients. Assessment of severity of covid-19 infection in HCC patients. And assessment of clinical course and outcome of HCC patients when they get infected by Covid-19. This is a retrospective case control study including 100 HCC patients (50 of them were infected by covid-19 while the other 50 were not infected). All patients were Egyptians presented to HCC clinic in national hepatology & tropical research institute (NHTMRI) from 1/2022 to 1/2023 assessed for covid-19 infection (by typical CT chest, covid swab and covid symptoms) and assessed for HCC staging (by Barcelona clinic liver cancer BCLC), clinical course over six months (by Child Pugh score) and mortality rates. Most of Covid-19 infected HCC patients had severe covid symptoms and progressive HCC course with mortality 72%, while low percentage of covid-19 HCC infected group were mild with stationary course. On the other hand, high percentage of non-infected HCC group have stationary HCC course with low mortality 24%. COVID-19 infection seems to have a significant effect on clinical course and outcome of HCC. Also, HCC patients are vulnerable to have more severe COVID-19 symptoms.

Exploring uncharted territory: new frontiers in environmental DNA for tropical fisheries management.

Tropical ecosystems host a significant share of global fish diversity contributing substantially to the global fisheries sector. Yet their sustainable management is challenging due to their complexity, diverse life history traits of tropical fishes, and varied fishing techniques involved. Traditional monitoring techniques are often costly, labour-intensive, and/or difficult to apply in inaccessible sites. These limitations call for the adoption of innovative, sensitive, and cost-effective monitoring solutions, especially in a scenario of climate change. Environmental DNA (eDNA) emerges as a potential game changer for biodiversity monitoring and conservation, especially in aquatic ecosystems. However, its utility in tropical settings remains underexplored, primarily due to a series of challenges, including the need for a comprehensive barcode reference library, an understanding of eDNA behaviour in tropical aquatic environments, standardized procedures, and supportive biomonitoring policies. Despite these challenges, the potential of eDNA for sensitive species detection across varied habitats is evident, and its global use is accelerating in biodiversity conservation efforts. This review takes an in-depth look at the current state and prospects of eDNA-based monitoring in tropical fisheries management research. Additionally, a SWOT analysis is used to underscore the opportunities and threats, with the aim of bridging the knowledge gaps and guiding the more extensive and effective use of eDNA-based monitoring in tropical fisheries management. Although the discussion applies worldwide, some specific experiences and insights from Indian tropical fisheries are shared to illustrate the practical application and challenges of employing eDNA in a tropical context.

Application of confocal laser microscopy for identification of modern and fossil pollen grains, an example in palm Mauritiinae

Confocal scanning laser microscopy (CSLM) is becoming a powerful tool for palynological studies. CSLM allows palynomorph image sectioning, internal and surface structures visualization, and 3D reconstruction at a higher resolution than standard light microscopy without extra processing. CSLM images are suitable for several image analysis techniques that could help improve the accuracy and reproducibility of taxa identification. Here, using the palm subtribe Mauritiinae (Arecaceae: Calamoideae: Lepidocaryeae) as a model group, we identify modern and fossil pollen grains using CSLM images coupled with ImageJ/Fiji 1.54f plugins and machine learning statistical analyses. Modern taxa pollen grains including Lepidocaryum tenue Mart., Mauritia flexuosa L.f., Mauritiella armata (Mart.) Burret and Mauritiella aculeata (Kunth) Burret were obtained from Smithsonian Tropical Research Institute (STRI) pollen collection or herbarium exsiccates. Fossil pollen of Grimsdalea magnaclavata Germeraad et al. 1968, and Mauritiidites franciscoi (van der Hammen) van der Hammen & Garcia de Mutis 1966, both from Miocene, and Mauritia pollen type from Holocene were obtained from STRI collection. We measured nine shape and exine quantitative parameters, and one qualitative parameter (pollen aperture). Pollen volume was the most important variable (28.270 mean decrease accuracy), followed by pollen aperture (15.003), Skewness (13.466), and spine density (10.246). The machine learning analysis, which included CART and Random Forests, correctly identified both fossil and extant grains. CSLM and the quantitative analysis of morphological traits are a new frontier in palynological studies.

Defining the hidden burden of disease in rural communities in Bangladesh, Cambodia and Thailand: a cross-sectional household health survey protocol

IntroductionIn low-income and middle-income countries in Southeast Asia, the burden of diseases among rural population remains poorly understood, posing a challenge for effective healthcare prioritisation and resource allocation. Addressing this...

Illuminating arthropod diversity in a tropical forest: Assessing biodiversity by automatic light trapping and DNA metabarcoding

AbstractAlthough studies of insect decline have recently dominated headlines worldwide, their interpretation requires caution since for most species, we lack long‐term population baselines. In the tropics, where most insect species thrive, our knowledge is even more limited and so reliable insect assessments must originate from well‐established long‐term monitoring efforts. Combining the extensive monitoring data from the Arthropod Program of the Smithsonian Tropical Research Institute (STRI) on Barro Colorado Island (BCI), Panama, we compare whether known arthropod diversity can be detected through metabarcoding of bulk insect samples obtained through automatic light‐trapping. Our study detected 4402 species based on Barcode Index Numbers (BIN) and detected fine‐scale differences between wet and dry seasons and sampling localities. We further refined our analysis to indicate which families and genera explained seasonal turnover. Using samples collected in parallel, but sorted manually as part of the ongoing arthropod monitoring program, we compared these methods. Out of 538 BINs recovered through manual sorting, there was a 70% overlap with the metabarcoding data; however, it represented 30% of the total BINs detected through metabarcoding. Expecting higher detection through metabarcoding, we also compare the results with the 14 years of sampling in BCI to better understand how well the monitoring program has captured the diversity of focal groups. Our results revealed a ~50% overlap between both methods and similar total catch. Barcode Index Numbers manually detected but not recovered by metabarcoding highlight some of the limitations of molecular detection methods such as primer bias. Contrastingly, BINs detected with metabarcoding, but not recovered by the traditional monitoring scheme, highlight the importance of local and regional barcode reference libraries.

Woody debris removal modifies carbon stocks and soil properties in a fragmented tropical rainforest

AbstractWe examined whether and how woody debris removal for domestic fuel affects carbon storage and soil properties in an Indian rainforest. Fuelwood removal reduced aboveground carbon stocks, increased soil bulk density, and possibly reduced soil phosphorus stocks. Equitably balancing this subtle trade‐off between climate‐regulating and vital, widely utilized provisioning functions, is a challenge for tropical forest research and management.

The challenges in rebuilding a quality public health in Brazil

In recent years, Brazil has grappled with a denialist approach to its healthcare system, the Unified Health System (SUS), especially during the COVID-19 pandemic. Influential figures, including public personalities, have cast doubt on science, leading to widespread uncertainty. Despite the challenges, Brazil boasts a strong National Immunization Plan (PNI) that has served as a global reference. The country faces the demographic transition, with an aging population requiring healthcare adaptation. Addressing chronic diseases becomes paramount, as does managing the economic implications of an older workforce supporting retirees. Inequalities in access to quality public healthcare persist due to socioeconomic disparities, a divided healthcare system, geographic disparities, ethnic and racial inequalities, education and cultural factors, and long wait times in the public healthcare system. Environmental issues, like deforestation, wildfires, climate change, water pollution, pesticide use, industrial pollution, and food security, impact public health. Sustainable policies and awareness are crucial. Health research in Brazil thrives in universities, institutions, and through international collaboration. Clinical research, epidemiology, public health research, and tropical medicine research are prevalent, but funding challenges and research misconduct persist. Combating infodemia and fake news is essential to ensure that public health decisions are based on reliable information. Fact-checking organizations, healthcare professionals, and education play a vital role. Expanding vaccination coverage is critical to protect against infectious diseases. Brazil employs campaigns, vaccination centers, home visits, school vaccination, partnerships, effective communication, vaccination records, education, and prioritizing high-risk groups. Strengthening the First Level of Health Care through the Family Health Strategy, coverage expansion, professional qualification, electronic health records, prevention programs, management strategies, specialized care, service integration, and community participation can improve healthcare access and coordination. Health education in Brazil focuses on health promotion, disease prevention, child and family health, sexual education, community engagement, school education, information accessibility, and trust in public health policies. The growth of health technology in Brazil can enhance care quality, access, resource management, disease prevention, cost savings, and innovation. However, ethical considerations, equitable access, and data privacy are vital. A democratic environment in public health promotes community participation, accountability, equity, evidence-based decision-making, individual and collective rights, anti-corruption efforts, conflict resolution, and long-term policy planning. SUS funding faces challenges of insufficient resources, budget predictability, dependence on unstable funding sources, regional inequalities, healthcare professional shortages, underfunding of complex services, lack of prevention investment, corruption, and an aging population. Addressing these challenges is vital to maintain SUS as an equitable and effective healthcare system. In conclusion, addressing these healthcare challenges and opportunities is crucial for Brazil's future. It requires ongoing investment in public policies, a multidisciplinary approach, and active community participation. Strengthening primary healthcare and combating misinformation are essential steps toward a healthier and more equitable Brazil.

Vertical Greenery Systems in Tropical Climate - A Review

In burgeoning tropical urban areas, impermeable surfaces exacerbate urban heat stress, creating Urban Heat Islands (UHI). Mitigating this requires the adaptation of Vertical Greenery Systems (VGS) in the built environment. While studies explore VGS, few address their environmental impact in tropical contexts, where adverse weather challenges the design and management. Guided by 'Green wall,' this study categorizes literature on VGS into systems, technical properties, and tropical challenges. Scrutinizing climate, maintenance, and cost as barriers, the study aims to identify factors influencing successful VGS deployment in the tropics. Objectives include exploring typologies, designs, performances, irrigation, maintenance challenges, and climatic factors. Insights seek to offer a nuanced understanding of their efficacy across climates. Recommendations stress the need for targeted tropical research, a multidisciplinary maintenance approach, meticulous material selection, and ongoing technological adaptation for sustainable VGS in tropical urban landscapes.

Agroforestry as an approach to rehabilitating degraded tropical peatland in Indonesia

Peatland is a unique ecosystem with water saturation; peatland regulates hydrological processes, climate, environmental conditions, and biodiversity. Poor management practises regarding peatlands can lead to land degradation, and peatland degradation typically has negative effects. Recent tropical peatland research in Indonesia has predominantly revolved around the examination of the ecological consequences resulting from various management approaches. There is little study on farmers' agroforestry efforts to preserve and restore degraded peatlands. A comprehensive examination was undertaken to assess a range of facts, information, and scholarly articles pertaining to the practise of agroforestry on peatlands in Indonesia. The primary incentive for farmers to adopt agroforestry systems originates from their recognition of the impending scarcity of trees. By integrating intercrops with cultivated trees, farmers anticipate generating adequate money to fulfil their family's economic requirements. Farmers who choose intensive intercropping practises are motivated by market demand, whereas farmers who do not adopt this approach tend to favour crops that necessitate less rigorous management. The provision of governmental assistance holds significant importance, and there is a pressing need for additional guidance and support. The potential for rehabilitating degraded peatlands by the implementation of agroforestry practises of native tree species is considerable. Their growth patterns contribute to enhanced vegetative coverage, resulting in heightened moisture levels, reduced temperatures, diminished fire hazards, and improved peat soil quality. The relationship between the physiography of the land and the depth of the peat is directly associated with the patterns and components of agroforestry in peatland environments.

Recent Trends in Malaria Vaccine Research Globally: A Bibliometric Analysis From 2005 to 2022.

Aim: Malaria vaccine is one of the critical areas in tropical health research, considering the success recorded in other vaccine-preventable diseases. This study is aimed at reviewing recent trends in global malaria vaccine research from 2005 to 2022. Method: A validated search strategy was undertaken to identify scientific literature on the malaria vaccine in the Scopus database. Bibliometric indicators identified include a pattern of publication growth and citations over the study period; top authors, countries, funding organizations, and journals; keywords, including different malarial parasite species, and the overall research themes. Result: A total of 6457 documents were found from 2005 to 2022, published in 160 journals/sources in 189 countries/territories. Malaria Journal published the highest number of research outputs (478, 7.4%) within the study period, and the highest number of documents (468, 7.3%) were published in 2021. There were 214,323 total citations, with 33.2 average citations per document and 167 documents' h-index. The United States, United Kingdom, and Australia combined produced more than 60% of the publication output, with most collaboration with African countries such as Kenya. Plasmodium falciparum is the most occurring parasite species keyword (754, 11.7%), with a growing interest in Plasmodium knowlesi (30, 0.5%). Merozoite surface protein, characterization, trials, infant/children, traveler, and research/review were the six themes that emerged from the studies. Conclusion: The last one and half decades have seen a significant increase in malaria vaccine research and citations, mainly targeting vaccine development, safety, and efficacy in Africa. This necessitates more international efforts to improve the vaccines' effectiveness considering different Plasmodium species.

The EFFECT OF ADMINISTRATION OF PAITAN (Tithonia diversifolia) LIQUID EXTRACT ON THE GROWTH OF TISSUE CULTURAL PRODUCTS OF BARANGAN BANANA (Musa acuminata L.) SEEDLINGS

Bananas (Musa spp.) are tropical plants that are very popular in Indonesia. Banana plants in the nursery require a planting medium that contains the nutrients the plants need. Tithonia is an annual weed that is suitable for use as a source of plant nutrients. This research aims to determine the effect of giving Tithonia liquid extract on the growth of Barangan banana seedlings resulting from tissue culture at the seedling stage and the best dose for using Tithonia liquid extract. This research was conducted at the Germplasm Nursery and Breeding Laboratory of the Tropical Fruit Plant Research Institute, Solok, West Sumatra, from September to December 2020. This research used the RAL method (Completely Randomized Design) with four treatments and six replications, in the form of 1) Without Tithonia extract, 2) Giving 1 ml of Tithonia extract, 3) Giving 2 ml of Tithonia extract, and 4) Giving 3 ml of Tithonia extract. The parameters observed were plant height, number of leaves, leaf length, leaf width, and stem diameter. Data was tested statistically. If calculated F > F table then it is tested further using the Duncan Multiple Range Test (DNMRT) with a level of 5%. The results of the research showed that giving Tithonia liquid extract had an effect on the growth of Barangan banana seedlings resulting from tissue culture. Significantly different results were obtained for the leaf width increase parameter. On the other hand, the results were not significantly different for other parameters such as plant height, number of leaves, leaf length and stem diameter. Giving 1 ml of Tithonia liquid extract was the best dose in this study.

Applicability Evaluation of the Global Synthetic Tropical Cyclone Hazard Dataset in Coastal China

A tropical cyclone dataset is an important data source for tropical cyclone disaster research, and the evaluation of its applicability is a necessary prerequisite. The Global Synthetic Tropical Cyclone Hazard (GSTCH) dataset is a dataset of global tropical cyclone activity for 10,000 years from 2018, and has become accepted as a major data source for the study of global tropical cyclone hazards. On the basis of the authoritative Tropical Cyclone Best Track (TCBT) dataset proposed by the China Meteorological Administration, this study evaluated the applicability of the GSTCH dataset in relation to two regions: the Northwest Pacific and China’s coastal provinces. For the Northwest Pacific, the results show no significant differences in the means and standard deviations of landfall wind speed, landfall pressure, and annual occurrence number between the two datasets at the 95% confidence level. They also show the cumulative distributions of central minimum pressure and central maximum wind speed along the track passed the Kolmogorov–Smirnov (K-S) test at the 95% confidence level, thereby verifying that the GSTCH dataset is consistent with the TCBT dataset at sea-area scale. For China’s coastal provinces, the results show that the means or standard deviations of tropical cyclone characteristics between the two datasets were not significantly different in provinces other than Guangdong and Hainan, and further analysis revealed that the cumulative distributions of the tropical cyclone characteristics in Guangdong and Hainan provinces passed the K-S test at the 95% confidence level, thereby verifying that the GSTCH dataset is consistent with the TCBT dataset at province scale. The applicability evaluation revealed that no significant differences exist between most of the tropical cyclone characteristics in the TCBT and GSTCH datasets, and that the GSTCH dataset is an available and reliable data source for tropical cyclone hazard studies in China’s coastal areas.

Effects of the Tropical Climate of Vietnam on the Properties of Synthetic Greases with Urea Thickeners

This study investigated, for the first time, the effects of the tropical climate of Vietnam on the properties of synthetic greases with urea thickeners. The greases were exposed to seven-month field tests at climatic test stations of the Joint Russian–Vietnamese Tropical Research and Technological Center in three regions of Vietnam. This short-term exposure decreased the ultimate strength and affected the colloidal stability of the samples (in the colloidal stability measurements, the amount of separated oil was reduced). At the same time, the chemical composition of the greases remained essentially unchanged, as confirmed by IR spectroscopy. It would be reasonable to assume that the degradation of polyurea greases in tropical climates is primarily associated with their colloidal structural changes. This assumption, however, requires confirmation in further research that should involve longer exposure and a larger number of grease samples prepared from different base oils. It was additionally found that introducing a heterogeneous modifier into polyurea greases impairs their stability in tropical climate.