Effective Control Measures Research Articles

Rapid and specific on-site H5Nx avian influenza diagnosis via RPA and PAM-independent CRISPR-Cas12a assay combined with anti-NP antibody-based viral RNA purification

Rapid and accurate detection of H5Nx avian influenza viruses is critical for effective surveillance and control measures. Currently, RT-qPCR with spin column RNA extraction is the gold standard for HPAIV surveillance, but its long reaction time and need for specialized equipment limit its effectiveness for rapid response. In this study, we introduce a centrifuge-free, rapid detection method for on-site detection of H5Nx viruses that combines magnetic bead-based ribonucleoprotein (RNP) purification and concentration with a CRISPR-Cas12a system that is independent of the protospacer adjacent motif (PAM) sequence. Our approach employs anti-NP monoclonal antibodies for the targeted isolation of RNA bound to RNPs, facilitating a quick and specific RNA extraction process that negates the need for centrifugation. Additionally, by denaturing the RT-RPA amplicon using 60% DMSO, we activate the trans-ssDNA cleavage activity of the Cas12a protein without the need for a specific PAM (5’-TTTV-3′) sequence. This strategy increases flexibility in CRISPR RNA design, providing a significant advantage when targeting genes with high variability. We validated the efficacy of our magnetic RNP purification and concentration method in combined with an RT-RPA/PAM-independent Cas12a assay for detecting the H5 gene. The assay achieved a sensitivity threshold of 101 EID50 with fluorescent detection and 102 EID50 using lateral flow strips. It also exhibited high specificity, yielding positive results solely for H5Nx viruses among various influenza A virus subtypes. Furthermore, in clinical samples, the assay demonstrated 80% sensitivity and 100% specificity. These results highlight the advantages of using NP-specific antibodies for RNP purification and CRISPR-Cas12a with viral gene-specific crRNA to achieve exceptional diagnostic specificity.

Identification of Rickettsia species in cattle ticks in selected regions of urban Ghana.

Ticks continue to invade new regions spreading pathogens of zoonotic and veterinary importance. Diverse tick species have been reported in Ghana due to the continuous trade of livestock. In this study, ticks were collected from cattle in three sites within Southern Ghana. The 1489 ticks collected were morphologically identified and further confirmed using a molecular assay that amplifies the 660-bp segment of the mitochondrial cytochrome c oxidase subunit 1 (COI) gene. These ticks were pooled and screened for pathogens of zoonotic importance. From the 215 tick pools screened, Rickettsia DNA was detected in 34 (15.81%). Sanger sequencing revealed the occurrence of Rickettsia africae (14.42%), the causative agent of African tick-bite fever, and Rickettsia aeschlimannii (1.39%). Regular monitoring of tick populations is essential to generate data for creating effective control and preventive measures.

Effects of Gas Flaring On Air and Groundwater Quality in Ebedei and Ashaka, Located in Ukwuani, Delta State, Nigeria

This research examines the effects of gas flaring on air and groundwater quality in Ebedei and Ashaka, located in Ukwuani, Delta State, Nigeria. Data on air pollutants, including sulphur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon dioxide (CO₂), as well as groundwater quality parameters, were collected during both the wet and dry seasons through systematic sampling techniques. The findings indicate that levels of SO₂ and NO₂ exceeded the permissible limits set by the World Health Organization (WHO), posing significant threats to air quality and public health. Conversely, CO₂ concentrations remained within acceptable ranges. Groundwater analysis revealed slightly acidic pH levels, elevated biochemical oxygen demand (BOD), and high concentrations of iron, lead, and phosphates, all surpassing WHO standards and pointing to contamination caused by industrial emissions and acid rain. Statistical analyses demonstrated strong links between SO₂ and NO₂ emissions and groundwater quality, highlighting their harmful effects. Seasonal differences in pollutant levels were minor, suggesting that human activities are the primary source of pollution. The study emphasizes the urgent need for stricter environmental policies, effective pollution control measures, and ongoing monitoring to protect local communities and ecosystems.

Construction and application of optimized model for mine water inflow prediction based on neural network and ARIMA model

Mine water influx is a significant geological hazard during mine development, influenced by various factors such as geological conditions, hydrology, climate, and mining techniques. This phenomenon is characterized by non-linearity and high complexity, leading to frequent water accidents in coal mines. These accidents not only impact coal production quality but also jeopardize the safety of mine staff. In order to better predict the amount of water surging in mines and to provide an important basis for mine water damage prevention work, based on the time series data of mine water influx from January 2020 to February 2023 in Northern Guizhou Province Longfeng Coal Mine, the BP-ARIMA prediction model was established by combining the BP neural network model and ARIMA autoregressive sliding average model, It also predicted the mine influx for a total of 6 months from July 2022 to February 2023, and compared the prediction results with four models, namely, BP neural network model, ARIMA autoregressive sliding average model, traditional method of Large well method, and GM(1,1) grey model, and used the absolute relative error as the calculation of model accuracy. The results show that the established BP-ARIMA(3,1,1) prediction model is much closer to the actual value, with an average absolute relative error of 1.02% and a maximum absolute relative error of 3.036%, and the goodness of fit R² was 0.93, which is much better than the other four single models, and substantially improves the prediction accuracy of mine water influx. Furthermore, utilizing the BP-ARIMA model, future predictions for mine water influx in Longfeng Mine were made, offering a scientific foundation for effective prevention and control measures.

Prevalence and associated factors of malaria among the displaced population in refugee camps in Africa: a systematic review and meta-analysis

BackgroundThe increased occurrence of malaria among Africa’s displaced communities poses a new humanitarian problem. Understanding malaria epidemiology among the displaced population in African refugee camps is a vital step for implementing effective malaria control and elimination measures. As a result, this study aimed to generate comprehensive and conclusive data from diverse investigations undertaken in Africa.MethodsThis review adhered to PRISMA standards, involving searches across electronic data bases such as Google Scholar, PubMed, Web of Science, Scopus, and Science Direct. In addition, grey literature was retrieved from several professional associations. The quality of selected studies was evaluated using the Newcastle–Ottawa Quality Assessment Scale. Data extraction was executed using Microsoft Excel, and the meta-analysis was performed with STATA 14 software. A random-effects model was used to estimate the pooled prevalence and associated factors of malaria. Meta-regression and subgroup analysis were used to identify heterogeneity, while funnel plots and Egger’s statistical tests assessed the publication bias. Furthermore, a sensitivity analysis was performed.ResultsThe overall random-effects pooled prevalence of malaria infection (comprising symptomatic and asymptomatic cases) across all included studies was 35.93% (95% CI 24.71–47.15). This study showed a high level of heterogeneity between studies (I2 = 97.1; P < 0.001). Of the identified Plasmodium species, Plasmodium falciparum constituted 99.3%. The frost plot indicated that the overall prevalence of P. falciparum was 34.94% (95% CI 24.34–45.53). Subgroup analysis revealed significant variation (P < 0.001) in malaria prevalence between asymptomatic and symptomatic cases, with a prevalence of 4.39% (95% CI 2.57–6.21) and 45.10% (95% CI 27.28–62.92), respectively. Lack of insecticide-treated mosquito net utilization (AOR 2.43; 95% CI 1.01–5.88) and living near mosquito breeding sites (AOR 2.76, 95% CI 1.56–4.87) were risk factors of malaria.ConclusionThis study determined that the pooled prevalence of malaria among displaced individuals in refugee camps was high and exhibited variations across different population groups. This signifying there is still a need to improve and recheck existing malaria prevention and control strategies to establish an effective malaria control and elimination programme in Africa.

Challenges and opportunities of the exotic invasive macroalga Rugulopteryx okamurae (Phaeophyceae, Heterokontophyta)

Abstract The invasion of Rugulopteryx okamurae along the southern European coastline is producing significant ecological and socioeconomic impacts. Its rapid proliferation and high adaptability have cause severe ecosystem disruptions, displacing indigenous species and altering habitat structures. Various factors, including favorable environmental conditions and chemical defenses, have contributed to its rapid spread. This situation has prompted urgent interdisciplinary research and the implementation of management strategies. Regulatory frameworks have been established to address its invasive status, aiming to control the bio-invasion. Valorization strategies could contribute to sustainable marine ecosystem management and marine biotechnology advancements. R. okamurae presents a wide variety of valuable molecules in its internal composition, such as alginates, terpenoids or carotenoids, with potential biotechnological applications. Promising results have been obtained using R. okamurae in compost or biostimulants, as supplements in aquafeed or as part of biomaterial to develop eco-friendly products. Some molecules like terpenoids have shown anti-inflammatory properties with applications in the nutraceutical industry. However, significant challenges remain in fully understanding its biology, ecological impacts, and effective control measures. Coordinated efforts among scientists, politicians, companies and stakeholders are essential to mitigate its spread and explore its potential for sustainable resource utilization. The ecological and economic impacts are being studied but there is a still scarce number of studies to follow a strategy of control based in blue and circular economy.

Understanding the clinical and molecular epidemiological characteristics of carbapenem-resistant Acinetobacter baumannii infections within intensive care units of three teaching hospitals

BackgroundCarbapenem-resistant Acinetobacter baumannii (CRAB) is recognized as a common clinical conditional pathogen with blaOXA−23 gene-mediated multidrug-resistance that is a significant threat to public health safety. Timely and effective infection control measures are needed to prevent their spread.MethodsWe conducted a retrospective study of CRAB patients at three teaching hospitals from 2019 to 2022. We identified bacterial isolates, collected clinical data, and performed antimicrobial susceptibility testing. Genome characteristics of isolates were investigated by whole genome sequencing. Multilocus sequence typing and phylogenetic trees were used to assess the genetic similarity of isolates. Acquired antimicrobial resistance genes and virulence factors carried in the isolated group genome were analyzed by ResFinder, PubMLST and VFDB. Sequence alignment was used to analyze genetic environment around blaOXA−23. Phylogenetic tree was constructed to analyze the genetic relationship of isolates.ResultsA total of 92 non-repetitive CRAB isolates were collected, with sputum samples accounting for the majority (94.57%, n = 87) of samples. These were distributed into ST2, with ST2 identified to have the highest prevalence of infection, accounting for 99.99% (n = 91) of all isolates. The major resistance genes identified were blaOXA−23, blaOXA−66, blaOXA−51, and blaADC. Also, 92 CRAB strains showed high levels of resistance to common clinical antibiotics, but not minocycline. Meanwhile, most of the isolates carried virulence genes such as various ompA, csuA, csuB, csuC, csuD, abaI, abaR, lpxC, lpxA, and bmfRS. Single nucleotide polymorphism (SNP) analyses further indicated that the bacterial genome was progressively polymorphic with time. We analyzed the environment of the blaOXA−23 gene and found that CRAB accumulated in the context of prominent environmental antibiotic exposure and had longer survival times in the antibiotic environment, resulting in the tendency of bacteria to develop greater antibiotic resistance.ConclusionsWe find that CRAB is prevalent within the ICU and is progressively resistant to antibiotics over time. Enhanced clinical understanding and timely management of CRAB infections will be crucial to minimize or even eliminate the spread of CRAB within the ICU setting.

Source Apportionment and Analysis of Potentially Toxic Element Sources in Agricultural Soils Based on the Positive Matrix Factorization and Geo-Detector Models

The potentially toxic element pollution of agricultural soils has become a significant environmental threat to food safety and human health. Accurately identifying sources of potentially toxic element pollution is key to developing effective pollution prevention and control measures. In this study, regional potentially toxic element pollution of the soils in the Nanliujiang River Basin was analyzed using the positive matrix factorization (PMF) model and the geo-detector model. First, topsoil samples from the study area were collected to analyze eight potentially toxic elements in the soil, including As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn. The PMF model was used to conduct source apportionment of the potentially toxic element data and identify the primary pollution sources and their contribution rates. Then, the geo-detector model was used to analyze the key factors affecting the spatial distribution of the potentially toxic elements and the influence of natural and human factors on the distribution of the potentially toxic elements. There are four potentially toxic element pollution sources of the agricultural soil in the study area: geological background, agricultural activities, industrial discharge, and river irrigation. The geological background contributed the most. The main factors affecting the spatial distribution of potentially toxic elements included agricultural activities, industrial discharge, and river irrigation. This integrated method can analyze the formation of potentially toxic element pollution in depth from the perspectives of source apportionment and spatial differentiation and provide a scientific basis and decision support for preventing and controlling potentially toxic element pollution in agricultural soils. This study provides a new method and scientific basis for identifying and preventing potentially toxic element pollution sources in agricultural soil and can guide the formulation of targeted soil pollution control measures.

Anopheles mosquitoes in Mondulkiri forest, Cambodia: abundance, distribution, seasonal patterns and Plasmodium prevalence

BackgroundMosquitoes are important drivers of infectious diseases transmission, with Anopheles mosquitoes being responsible of malaria transmission. In Cambodia, where malaria is prevalent in forested regions, understanding the ecology of these vectors is crucial. This study aimed to investigate the abundance, distribution, seasonal patterns, biting behaviour of Anopheles mosquitoes, and prevalence of Plasmodium, in Mondulkiri province, Northeastern Cambodia.MethodsConducted in 9 sites, seven in forested and two in neighbouring villages, over one year, the collection of Anopheles mosquitoes was made hourly for a 72-h period every month, using a human-baited double net trap. Each mosquito was collected using a mouth-aspirator and identified morphologically, and screened for the presence of Plasmodium.ResultsPrimary vectors, including Anopheles baimaii, Anopheles dirus, Anopheles maculatus, and Anopheles minimus, constituted 11.1% of all female mosquitoes, while 12 secondary vector species represented 29.4% of the overall collection. Anopheles species were more prevalent during the late rainy season (August to November), with year-round activity observed. Primary vectors were predominantly found in forest sites, while other vector species were found in both village and forest environments. Notably, primary vectors exhibited a preference for nocturnal biting, yet a significant proportion (19.2%) displayed daytime activity, highlighting a potential risk of daytime malaria transmission. Among 5,056 Anopheles specimens tested, only 36 Plasmodium spp.-infected samples were detected, mainly in forest sites (94%), and in specimens collected at night. This study provides essential insights into the ecology of Anopheles in Mondulkiri Forest.ConclusionsThe identification of primary and secondary vectors, their seasonal dynamics, and biting behaviour contribute to enhances our understanding of malaria transmission risks in these areas, guiding future strategies toward effective and context-specific control measures, while stressing the need for individual protection during daytime.

Molecular Mechanisms Underlying Resistance to Bacillus thuringiensis Cry Toxins in Lepidopteran Pests: An Updated Research Perspective

Genetically modified crops that produce insecticidal proteins from Bacillus thuringiensis (Bt) are currently the most efficient and safest method of pest control worldwide. However, the prolonged planting period has led to a reduction in the efficacy of Bt crops due to the evolution of pest resistance in the field. This review paper examines the resistance status of lepidopteran pests to Bt crops under field conditions, elucidates the molecular mechanism underlying their resistance to Bt Cry toxins, and discusses resistance management strategies based on these mechanisms. Extensive research has demonstrated that mutations and alterations in expression patterns of midgut receptor genes are closely associated with Bt resistance. As our understanding of molecular mechanisms progresses, several innovative approaches such as DNA molecular detection techniques, engineering modified Cry toxins, and combining Bt toxin with RNAi technology have been developed for effective pest control measures. Future research will further unravel the intricate molecular mechanisms underlying this phenomenon to develop scientifically sound integrated pest management strategies.

Listeria monocytogenes, Salmonella spp., and Staphylococcus aureus: Threats to the Food Industry and Public Health.

Foodborne pathogens have always been of public health concern and represent safety issues for food processors. These pathogens develop new ways to overcome antibiotics, survive in different environmental conditions, and the ability to reproduce in many hostile environments configure them as serious health hazards. Considering the huge number of microorganisms, three bacterial representatives were selected to provide a better knowledge about the question of which one is the worst enemy for humans, from the food industry point of view, taking into consideration their multiplication specificity, virulence, and resistance. As we constantly are exposed to these pathogens in our nutritional habits, this overview aims to summarize the most relevant characteristics associated with the pathogenicity, clinical symptoms and most importantly, how deadly Listeria monocytogenes, Salmonella spp., and Staphylococcus aureus can be in the hospital and the food industry, by comparing among them. Overall, the microbiological knowledge clearly suggests that while all three pathogens are dangerous, L. monocytogenes presents the highest risk of death due to their ability to cause severe complications in vulnerable populations as it presents a range of virulence factors that facilitate evasion of the immune system and cytological effects. Additionally, it shows great resistance to standard food processing and preservation techniques, making it one of the most difficult pathogens to control. Understanding the risks and characteristics of these foodborne pathogens is essential for implementing effective control measures to prevent their occurrence in food products and to promote public health.

Study on the Deformation Characteristics of Railway Subgrade Structures Induced by Groundwater Level Changes

The groundwater extraction will lead to a drop in water level, causing a change in the distribution of additional stress in the strata. This phenomenon leads to uneven settlement of the railway subgrade. In severe cases, this could threaten the safe operation of trains. Therefore, the degree and main factors influencing groundwater extraction in the settlement of the railway subgrade need to be determined through research. Based on railway subgrade engineering, the first step involved monitoring the settlement resulting from groundwater extraction during the spring irrigation period. Following this, the settlement characteristics of the subgrade structure were analysed. Subsequently, based on the Biot consolidation theory of the soil, a numerical simulation model was established to study the threshold parameters of the groundwater extraction on site. Finally, the primary and secondary relationships of the influencing factors must be clarified. The research results show that: (1) According to the monitoring data, groundwater extraction resulted in a subgrade subsidence of 15.2 mm, exceeding the prescribed threshold, affecting the engineering quality. (2) By the numerical simulation results, the distance parameter of the wells is the most significant factor affecting the deformation of the subgrade, followed by the quantity of extraction. So, the distance between the wells and the tracks should be kept at more than 150 m; the pumping volume should not exceed 1500 m3/day. (3) Using horizontal jet grouting piles to reinforce the subgrade can reduce the maximum uneven deformation from 18.14 to 7.86 mm, an effective settlement control measure.

Tracing metals in Mediterranean and Atlantic Sardina pilchardus: Unveiling impacts on food safety.

This study evaluates the concentration of metals and trace elements (Al, Cd, Cu, Fe, Li, Pb, Zn) in the muscle tissue of Sardina pilchardus from three northeast Atlantic localities (Lisbon, Canary Islands, Rabat) and two western Mediterranean sites (Málaga, Cartagena) to assess food safety and environmental impact. A total of 100 sardines were sampled between January and June 2019, with specimens collected, homogenized by size and weight, and analyzed for metal content using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). Results show significant geographical variation in metal concentrations, with Cartagena exhibiting the highest levels due to industrial and urban activities, while the Canary Islands had the lowest, likely influenced by geographical isolation and stringent environmental regulations. Intermediate levels were observed in Lisbon, Rabat, and Málaga, with Rabat ranking second highest. Importantly, none of the samples exceeded EU safety limits for lead (0.3mg/kg) or cadmium (0.25mg/kg), confirming their suitability for human consumption regarding metal content. These findings emphasize the role of local environmental and industrial factors in influencing metal bioaccumulation in marine ecosystems. Genetic and ecological dynamics, such as the Almería-Oran Front and the Canary Islands' isolation, likely contribute to these patterns. The study underscores the importance of continuous monitoring to safeguard food safety and marine ecosystem health. Despite Cartagena's elevated contamination levels, which pose a higher potential risk if sardine consumption is frequent, sardines from all locations remain within safety limits. Moving forward, research should prioritize long-term monitoring and explore genetic and ecological factors influencing bioaccumulation trends, contributing to sustainable management and effective pollution control measures. This highlights the interconnectedness of environmental health and human dietary safety, emphasizing the need for a proactive approach to monitoring marine contamination.

Identification of the primary pollution sources and dominant influencing factors of soil heavy metals using a random forest model optimized by genetic algorithm coupled with geodetector.

Identifying and quantifying the dominant factors influencing heavy metal (HM) pollution sources are essential for maintaining soil ecological health and implementing effective pollution control measures. This study analyzed soil HM samples from 53 different land use types in Jiaozuo City, Henan Province, China. Pollution sources were identified using Absolute Principal Component Score (APCS), with 8 anthropogenic factors, 9 natural factors, and 4 soil physicochemical properties mapped using Geographic Information System (GIS) kernel density estimation. Geodetector and a genetic algorithm optimized random forest model (GA-RF) were employed to quantify the dominant factors and precisely identify pollution sources. A Monte Carlo model was further applied to assess source-oriented health risk probabilities across age groups in the study area. The results revealed three principal components representing pollution sources, with contribution rates of 47.2 %, 33.3 %, and 19.5 %, respectively. For pollution source 1, industrial activities were dominant, with factory density (27.7 %) and distance from the factory (36.3 %) identified as the main factors. Cr, Cu, Mn, and Ni had high loads in this source. Pollution source 2, a combination of natural and transportation influences, was primarily affected by the normalized difference vegetation index (NDVI, 37.8 %), road network density (16.8 %), and proximity to roads (15.3 %). Pollution source 3 was linked to agricultural activities, with cultivated land density (CLD) contributing 39.1 %. As exhibited a high load (91.1 %) in this source, with an exceedance rate of 93 % in cultivated soil, a moderate enrichment factor of 2.33, and a strong ecological risk index of 615.72, making it the most polluted metal in the area. The source-oriented Health Risk Assessment (HRA) showed that agricultural activities contributed 88.7 % to the carcinogenic risk from As in cultivated land. Overall, 99.3 % of the population faced an acceptable cancer risk level. Unlike traditional source apportionment methods, the GA-RF model effectively quantified the contributions of specific influencing factors (e.g., factory density) to pollution sources, rather than merely estimating the percentage contributions of the sources themselves. This approach provides a novel perspective for HM source apportionment under complex environmental conditions.

α-MnO2 catalysts with efficient ozone-catalyzed decomposition under high humidity conditions.

Ground-level ozone pollution poses significant risks to ecosystems and human health and requires effective control measures. This study focused on the monolithic ozone degradation catalyst based on powdered α-MnO2 and comprehensively investigated its catalytic performance, moisture resistance, and stability. The monolithic catalyst achieved the optimal catalytic activity with an ozone conversion rate of 99% after being calcined at 400 °C for 3 hours. The detailed characterization of the catalyst properties at pH = 1, 4, and 7 revealed the adverse effects of residual acid ions on the catalyst activity. The catalyst at pH = 7 had more oxygen vacancies, which was related to the reduction of sulfate ion residues and the exposure of more active sites during the washing process. At pH = 7 and a space velocity of 900 000 h-1, the conversion rates of α-MnO2 to 18 ppm ozone reached 100% and 95% within 3 hours under 90% relative humidity and dry conditions, respectively. In addition, the monolithic catalyst exhibited significant moisture resistance and performed well in continuous alternating humidity cycle tests and sustained high humidity. It still maintained 90% ozone decomposition efficiency after 3 hours of testing under high humidity conditions. Meanwhile, the α-MnO2 monolithic catalyst showed excellent stability, with an ozone conversion rate exceeding 99% during the 50 - hour test period. These findings highlight the great potential of the α-MnO2 monolithic catalyst in ozone removal applications.

Molecular epidemiological survey of Babesia species infecting cattle in Paraguay

Paraguay, an agricultural country in South America, has a high prevalence of tick infestations in its cattle population due to warm temperatures, high humidity, and extensive grazing management practices. Consequently, Babesia infections, which are transmitted by ticks, might have a wide distribution in Paraguay, but the current status of these infections remains uncertain. Therefore, we aimed to assess the infection status of three clinically significant Babesia species, including Babesia bovis, Babesia bigemina, and Babesia naoakii, among cattle populations in Paraguay. Blood samples were collected from a total of 326 cattle across nine departments in Paraguay, and their DNAs were screened with species-specific PCR assays. Of the surveyed cattle, single infections of B. bovis and B. bigemina were detected in 24 (7.4 %) and 127 (39.0 %), respectively, while co-infection with both the parasite species was detected in 38 (11.7 %). In contrast, all of the surveyed cattle were negative for B. naoakii infection. The prevalence of B. bigemina-single infection was higher in the Eastern region (49.0 %) compared to the Western region (34.6 %), in cattle under extensive management (51.3 %) compared to those under semi-intensive management (34.6 %), and in Bos indicus cattle (50.3 %) compared to Bos taurus (15.8 %). Our findings demonstrated a wide distribution of B. bovis and B. bigemina infections among cattle in Paraguay, underscoring the importance of implementing effective control measures to reduce the potential economic losses associated with bovine babesiosis.

Coastal Vulnerability Assessment to Tidal (ROB) Flooding In Indramayu Coast, West Java, Indonesia

Aquaculture practices in developing countries, particularly Indonesia, are currently operating without effective control measures, leading to high tidal and other climate-related issues. Therefore, this study aimed to modify Coastal Vulnerability Index (CVI) assessment to evaluate the physical vulnerability of coastal areas in Indramayu Regency, West Java (62 sections) to tidal flooding (Rob). A total of 6 primary characteristics, including geomorphology, beach slope, water level rise sea, coastline alterations, tidal range, and high tide, as well as 2 additional parameters, namely land cover and mangrove breadth, were used for analysis. Based on the evaluation, CVI was divided into four groups, including (1) low, (2) moderate, (3) high, and (4) very high. The results showed that Indramayu District struggled to recover from tidal flooding, with 24.56%, 22.13%, 41.03%, and 12.28% being placed in the very high, high, moderate, and low categories. This underscored the role of local governments in improving coastal communities' capacity to respond to tidal flooding disasters. Furthermore, the results were expected to be used by local governments to enhance disaster mitigation systems, particularly for coastal areas in developing nations with comparable ecological conditions.

Analysis of desert locust (Schistocerca gregaria) suitability in Yemen: an integrated evaluation based on MaxEnt and space–time cube approaches

ABSTRACT Desert locust outbreaks pose severe threats to agricultural production and ecological environments. Hence, understanding the distribution of habitat suitability is crucial for establishing effective prevention and control measures. We introduce an innovative method for analyzing the temporal and spatial variations of desert locust habitat suitability in Yemen. This method integrates ecological niche models with space–time cube analysis. First, we gathered key environmental variables that affect desert locust distribution, including vegetation and soil types, precipitation, and temperature. Subsequently, we employed the MaxEnt model to assess habitat suitability for desert locusts in Yemen for 2010 and 2013–2021. Finally, we applied the space–time cube method for spatiotemporal analysis to reveal the spatiotemporal dynamics of habitat suitability distribution. The MaxEnt model results showed that the kappa coefficients exceeded 0.46 and the area under the curve exceeded 0.75. The spatiotemporal analysis results showed that from 2010 to 2021, the Red Sea coastal plains in western Yemen exhibited the highest habitat suitability levels, with significant increases in habitat suitability in the western and central regions. This study offers a new perspective on studying the spatial and temporal characteristics of desert locust habitat suitability distribution and can provides a scientific basis for the management of desert locusts.

The pollution and the ecological influence of chemical and industrial waste

Pollution from chemical and industrial wastes has far-reaching effects on ecosystems. Harmful substances such as heavy metals, persistent organic pollutants (e.g., polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs)), acid and alkali waste streams and other harmful substances enter the coastal and marine environments through rivers, sewage pipelines and other pathways, posing a serious threat to marine ecosystems and human health. Not only do these pollutants tend to accumulate in sediments, but they are also gradually amplified through the food chain, eventually reaching high concentrations in top predators and leading to biomagnification effects. In addition, ocean acidification and discharge of highly alkaline waste streams further affect carbonate-dependent marine organisms and disrupt the marine ecological balance. Understanding the environmental behavior of these pollutants and their ecological impacts is essential for developing effective pollution control and ecological protection measures.

Increasing Incidence of Apple Valsa Canker and Predominance of Cytospora mali in Gyeongsangbuk-do, South Korea

From 2015 to 2023, a survey was conducted to determine the occurrence of apple Valsa canker disease in major apple-producing regions in Korea. Infected branches were collected for the isolation and identification of the pathogens. During the survey period, a total of 38 fungal strains were isolated from trees infected with apple Valsa canker disease. A phylogenetic analysis using a combined dataset of the internal transcribed spacer (ITS) region and large subunit (LSU), actin (act1), RNA polymerase II (rpb2), and translation elongation factor 1-α (tef1-α) gene sequences was performed, identifying all of the isolates as Cytospora mali. According to the survey, the average annual incidence rate of apple Valsa canker disease was 2.8%. The infection rate was 2.2% in 2015, and it showed a decreasing trend until 2017. However, in 2018, the incidence rate began to gradually increase, reaching 4.2% in 2022 and sharply rising to 6.8% in 2023. The increasing incidence of apple Valsa canker disease is causing significant economic damage to apple producers, highlighting the need for effective control measures. Although a total of 21 pathogen species causing apple Valsa canker disease have been reported in East Asia, this study confirmed that C. mali is the dominant species causing the disease in Korea.