ABSTRACT Aim Himalaya is unique with diverse vegetation including Alnus nepalensis having potential for human wellbeing. A. nepalensis tree grows in the Himalaya, particularly in inaccessible areas and creates a barrier to soil erosion. A. nepalensis is fast growing and has the ability to enrich soil through nitrogen fixation. Its key role in biomass production and carbon storage makes it important for restoring degraded lands. Therefore, the aim of the study was to understand its potential for carbon credits for income generation and livelihood security to the local communities. Location The present study was conducted in Rudraprayag district, specifically in Chopta, Tungnath Valley, located between 30°28′39″–30°29′51″ N latitude and 79°12′9″–79°13′21″ E longitude in the Garhwal Himalayas, where good forest stands of A. nepalensis were reported between 1000 to 2500 m above sea level elevations. Time Period The study was carried out during 2023–2024 and data were collected. Major Taxa The major tree species associated with A. nepalensis were Rhododendron arboreum, Acer ceasium, Q. leucotricophora, Neolitsea sp., Lyonia ovalifolia, Q. semicarpifolia, Q. floribunda, Ficus palmata , Pyrus pashia , etc. Methods Soil and vegetation data collection and analysis were done using standard established sampling and analysis methods. Results and Main Conclusions Results of study suggest that A. nepalensis had the highest IVI across all altitudes, with an IVI of 300 (lower altitude), 150.9 (middle altitude) and 159.03 (upper altitude). Among the altitudes, A. nepalensis was reported pure in upper altitude and mixed in both middle and lower. Correlation analysis revealed a strong positive relationship between tree volume and biomass and carbon components ( r = 0.956, p < 0.01), highlighting volume as a key predictor of carbon stock. Aboveground and belowground biomass and carbon variables were perfectly correlated ( r = 1.000**, p < 0.01), indicating a tightly integrated biomass‐carbon dynamic. Tree density also significantly correlated with carbon variables ( r = 0.736, p < 0.01). CO 2 sequestration, net carbon stock and O 2 release were strongly interrelated ( r = 1.000), though less correlated with structural parameters. Results revealed that A. nepalensis forest has potential as an effective carbon sinks across elevation zones. Soil physico‐chemical properties under A. nepalensis stands varied significantly with altitude. Moisture and WHC were strongly correlated ( r = 0.898), however, negatively related to pH, indicating more acidic, moisture‐rich soils at higher elevations. Sand decreased ( r = −0.926) and clay increased ( r = 0.882) with altitude, showing texture shifts. SOC and SOM were positively linked to moisture ( r = 0.901) and negatively to pH, suggesting moisture as a key driver of soil carbon. The C: N ratio increased with depth ( r = 0.884), reflecting vertical variation in organic matter quality. A. nepalensis biomass production, C sequestration and soil properties influence with altitudes. These trends underline altitude and moisture as key factors in soil carbon dynamics.

Abstract. Large-scale industrial and engineering heritage sites are increasingly threatened by obsolescence, restricted access, and demolition, making timely digital documentation essential for preserving their spatial and technical knowledge. This paper presents a multi-sensor documentation campaign conducted at a late twentieth-century space engineering training facility shortly before its demolition. The site’s scale, curved geometry, dense infrastructure, confined spaces, and variable environmental conditions posed significant challenges for data acquisition and processing. A hybrid workflow was developed integrating terrestrial laser scanning (TLS), immersive 360-degree capture, and targeted indoor drone-based image acquisition. TLS formed the metric backbone of the documentation, while immersive capture supported spatial navigation and contextual understanding. Drone imagery was selectively used to enhance visualization of inaccessible interior areas rather than for full photogrammetric reconstruction, due to site-specific limitations. Results demonstrate that no single technology was sufficient to address the combined geometric and operational constraints of the site. Instead, a coordinated multi-sensor approach enabled the creation of a comprehensive digital record that balances accuracy, completeness, and interpretability. The study highlights both methodological limitations and practical solutions relevant to documenting complex space heritage under time-sensitive and constrained conditions. The workflow presented is transferable to other large-scale engineering heritage sites facing similar risks and challenges.

Anatomic characteristics and radiofrequency ablation lesions of the left ventricular summit.

A BSTRACT An aneurysmal bone cyst (ABC) is primarily a vascular tumor that causes partial vascular occlusion, leading to bony expansion. It is rare and attributes to only 1%–2% of primary bone tumors. Usually, it is found in long bones, with only 2% tumors in the head and neck region. Pain and slow-growing swelling are the most common presentations while other symptoms are attributed to pressure symptoms due to swelling. Radiologically, there are fluid–fluid interfaces and multiple cysts within ABCs. Biopsy is the mainstay of diagnosis. The only established and standard treatment is surgery. However, ABCs show a high rate of local recurrence even after complete resection. Getting a clear margin is difficult in anatomically inaccessible areas. Selective arterial embolization in large ABCs improves surgical outcome. There is a long data since the era of orthovoltage radiotherapy (RT) regarding the use of RT in ABCs for local control. Still, there is no proper RT guideline in ABC. Here, we are presenting a rare case of ABC of skull base in a 27-year-old man treated with volumetric modulated arc therapy.

Air frying has emerged as a popular low-oil cooking method, yet its impact on indoor air pollutant emissions remains insufficiently understood. In our study, emissions of volatile organic compounds (VOCs), nitrogen oxides (NO x ), and ultrafine particles (UFPs) were measured during the air frying of 12 different dishes within a ca. 0.15 m3 Perspex chamber. Pollutant emissions varied significantly depending on the food type, with rates in the ranges of 17.8-184.0 μg min-1 for total cooking VOCs, 24.6-37.9 μg min-1 for NO x , and 0.1-17.4 × 1012 # min-1 for UFPs, primarily due to Maillard reactions and lipid thermal decomposition. While pollutant concentrations and ozone formation potentials were elevated within the chamber, scaling to the volume of a small kitchen indicated substantially lower levels compared to conventional frying methods. Notably, only high-fat foods produced UFP concentrations comparable to those of deep frying. No NO x emissions were found during blank (empty appliance) runs, and NO x was only detectable while cooking certain types of foods. However, residues accumulating within inaccessible areas of the air fryer following over 70 uses led to increases of 23% in VOC and 236% in UFP concentrations while not cooking food.

Drones are increasingly used to conduct wildlife surveys in complex environments as they can be used in inaccessible areas, quickly survey large areas, and surveys can be reviewed post hoc, often leveraging AI technology. Double-observer methods applied to drone surveys, such as post-survey double-observer review of footage, improve inferences from drone-based wildlife surveys by correcting for individual perceptibility biases of observers. However, occlusion still affects the availability of individuals for detection, especially in complex environments. We explore the possibility that the availability of individuals may be increased by conducting a consecutive repeat survey with a parallel or rotated flight path in a double-observer survey design where individuals are largely stationary. We hypothesized that running this secondary flight would increase the availability of individuals for detection, thereby improving count accuracy, with the most prominent improvement in most complex (e.g., highly vegetated) environments. We explored this using (1) an in-field test of object detectability in environments with differing vegetation, and (2) a simulation of drone wildlife surveys in different levels of occlusion. In both trials, we tested a double-observer detectability estimator tool to correct survey counts. In the field, conducting a secondary flight from a different angle resulted in more accurate counts, with a post-count correction further increasing accuracy. The simulation highlighted detectability benefits from the secondary observer in nearly all trials (99%), and these benefits were generally greater in environments with denser canopies, and from flights paths rotated 90° compared to parallel paths.

BackgroundPrecise periodontal diagnosis is taught and routinely performed during dental school training. The aims of this study were to determine to what extent the measurement values obtained by students during their clinical training years correspond to those of licensed dentists; to assess the distribution of divergent results relative to measurement positions; and to identify sources of error. The study also investigated whether fewer errors are made in accessible areas such as the anterior teeth and vestibular areas in comparison with inaccessible areas. Finally, it investigated the influence of students’ level of experience on measurement accuracy.Materials and methodsData for probing depths in 6858 measurements made by students in comparison with dentists were documented and analyzed statistically. The influence of periodontal pocket depths on measurement accuracy was examined, and it was investigated whether the location of pockets (vestibular/oral, anterior/posterior, quadrant, mesial/medial/distal) influenced measurement divergences.ResultsThere were significant differences (P < 0.001) between the students’ and dentists’ measurements, which were in agreement in 63% of cases. Differences of 1 mm were observed in 80% of cases, 2 mm in 15.3%, and 3, 4, or 5 mm in fewer than 5%. Measurement differences in the last clinical course were significantly the largest (P < 0.01). Accuracy in medial measurement points was significantly better (P < 0.001). Differences in measurement accuracy in the anterior and posterior teeth, as well as on the vestibular and oral surfaces, only became apparent after analysis of subgroups for healthy, mild, and severe cases. Patients with severe cases had significantly smaller measurement differences in both the oral and vestibular areas (P < 0.02). Healthy patients had significantly better measurement values in the posterior region (P = 0.02), and patients with mild conditions had significantly better values in the anterior region (P = 0.03).ConclusionsThe results of this retrospective examination show that students already achieve a comparatively high level of measurement accuracy, but that differences occur, particularly in the approximal region. Targeted practical training and structured feedback systems could help further improve diagnostic precision, which is particularly important when there is a recall system with changing practitioners.

Remote Sensing technologies have become effective methods for monitoring animal populations and critical habitats in large, inaccessible areas. This paper discusses new technologies in satellite imagery, uncrewed aerial vehicles, LiDAR, and machine learning for wildlife population estimation and habitat protection. The main purpose is to assess the roles of multi-source remote sensing data in enhancing the accuracy, efficiency, and scalability of wildlife monitoring relative to conventional field-based procedures. Multispectral and hyperspectral high-resolution images are combined with LiDAR derived structural metrics to determine species distribution, population density, and habitat quality. Sophisticated image classification, object detection, and change-detection systems are used to examine temporal and spatial changes in ecosystems. These findings illustrate the significant advances in wildlife presence detection, habitat fragmentation mapping, and conservation hotspot identification, while minimizing human disturbance. Remote sensing-based monitoring allows near-real-time evaluation of ecological change and supports proactive conservation planning and policy formulation. On the whole, the results outline the opportunities of remote sensing solutions to optimize biodiversity conservation, to ease sustainable management of wild animals and to reinforce the decision-making patterns towards the safeguarding of essential habitats in the face of growing environmental demands.

Forested areas in Poland comprise numerous post-mining sites that hinder effective forest management. Such mining remnants may pose a threat to humans, animals, and operating forest machines. This study aimed to determine the feasibility of inventorying such man-made landforms as mining waste heaps, excavations, remnants of shallow shafts, adits, etc., using the Digital Elevation Model (DEM) based on Airborne Laser Scanning (ALS) data provided by the national agency (the Head Office of Geodesy and Cartography—HOGC) as open data. The DEM, when combined with other cartographic materials using GIS, accurately reflects the anthropogenic transformation evident in the topography. This paper presents the results of inventorying remnants of iron ore mining in the present-day forested area located between Krzepice, Kłobuck, and Częstochowa in southern Poland. The identification and inventory of post-mining landforms, mainly mounds resulting from shallow shaft mining operations, were supplemented by their digitization, automatically providing information on parameters such as perimeter (ranged in most cases from 24.3 to 159 m), surface area (46.9 to 1656 m2), length and width (7.8 to 59.2 m). The heights of the investigated structures were also read from the DEM, ranging from 0.3 to 4.1 m. Much larger structures were also identified, but they occurred accidentally (up to 23.5 m in height). In this manner, approximately 823 morphological forms were characterized, resulting in a database. Test fieldwork was then conducted to verify the DEM readings. It was proposed to calculate deformation indexes (Id [%]) for forested areas and apply them when estimating the forest management hindrance index used by the State Forests. The studied forest compartments managed by State Forests were characterized by an Id value from 0.1 to 55.5%. This type of measure provides a helpful tool in planning forestry operations in areas with diverse topography, including those transformed by mining activities. The actual environmental impact is highlighted. Forest management practices in the study area must take into consideration, in particular, topography, as well as geology and hydrology. Studies have shown that the DEM based on the ALS data is sufficiently accurate to detect even minor post-mining deformations (which may be important, in particular, in inaccessible areas). The recorded parameters can be considered when planning management, protection interventions, or reclamation activities.

The primary objective of endodontic treatment and apical surgery is the prevention or elimination of inflammatory conditions in the periapical tissues. Such inflammation develops as a result of the metabolic activity of diverse colonies of pathogenic and opportunistic microorganisms colonizing the root canal system. Apical microsurgical intervention represents a promising treatment modality for teeth resistant to conventional (orthograde) therapy. The reported success rate of this procedure exceeds 90%, even in the presence of complications. The occurrence of such complications is often associated with insufficient theoretical training of narrowly specialized clinicians, a lack of appropriate instrumentation, and limited access to magnification equipment, such as binocular loupes or a stationary operating microscope. In some cases, repeated endodontic retreatment proves ineffective and leads to the persistence of apical periodontitis despite technically successful conservative therapy. In these situations, the inflammatory focus is localized within the periodontal space at the apex of the affected tooth. Its etiology is attributed to bacteria persisting in anatomically inaccessible areas of the root canal system. The bacterial biofilm in the apical portion of the root canal system exhibits a complex anatomical configuration, which often cannot be completely eliminated using conventional endodontic techniques.

Background: Despite advances in monitoring and forecasting systems, natural disasters continue to cause significant human losses. During the response phase, fast decisions are required to allocate limited resources, particularly rescue helicopters, which play a key role in reaching inaccessible areas. However, helicopter allocation involves trade-offs between efficiency and operational safety under uncertain conditions. Methods: This study proposes a decision-support methodology based on Multi-Criteria Decision Analysis (MCDA) for allocating rescue helicopters during disaster response. The approach integrates Value-Focused Thinking (VFT) and Multi-Attribute Value Theory (MAVT) to structure objectives, assign weights, and evaluate alternatives using criteria related to mission safety, response time, and expected number of rescued victims. The method is illustrated through a simulated flood response scenario in a Brazilian regional context. Results: The results show that the model allows decision-makers to compare allocation scenarios and to make explicit the trade-offs between operational efficiency and safety. The application indicates that small reductions in efficiency may lead to relevant gains in operational safety, particularly under adverse weather conditions. Conclusions: The proposed approach provides a transparent and traceable structure for supporting helicopter allocation decisions during disaster response. It contributes to more consistent decision-making in critical operations, especially in contexts characterized by uncertainty and time pressure.

This study provides an in-depth examination of the technical and operational parameters of modern unmanned aerial vehicles (UAVs) in order to determine their suitability for firefighting missions in hard-to-reach, hazardous, or otherwise inaccessible areas. With rapid technological development expanding the capabilities of UAV systems, their potential use in emergency response continues to grow, creating the need for a structured assessment of the criteria that define their effectiveness in real operational conditions. The research identifies, analyzes, and systematizes the key UAV parameters that have a direct impact on performance during firefighting tasks. The methodology employed in this study relies on quantitative secondary data collection, supported by statistical comparison methods. This approach ensures a high level of objectivity when evaluating such characteristics as payload capacity, flight stability, endurance, propulsion systems, and resistance to environmental factors. Special attention is given to the technical requirements necessary for UAVs to operate with firefighting equipment, particularly firehoses and nozzles, which introduce additional weight, reactive forces, and aerodynamic challenges. The results clearly indicate that multi-rotor UAVs represent the most suitable configuration for modern firefighting operations. Their ability to perform vertical takeoff and landing, maintain precise hovering, and maneuver safely in confined urban spaces makes them significantly more adaptable than fixed- wing or hybrid platforms. These operational capabilities are essential for effective suppression of fires in complex environments where traditional firefighting vehicles cannot easily reach the source of the fire. The study also evaluates the relationship between UAV payload capacity and the specifications of firefighting tools, including firehose diameter and the type and intensity of extinguishing agents. The analysis demonstrates that accurate determination of these parameters is crucial for ensuring both mission effectiveness and operational safety. The article concludes by establishing a set of recommended UAV characteristics required for firefighting deployment, such as the ability to lift and stabilize a firehose, withstand wind and nozzle reaction forces, and sustain sufficient flight duration during active firefighting operations. Future research will focus on identifying the correlation between minimum critical extinguishing-agent intensity and the required dimensions of firehoses and nozzles, which will further support determining the optimal UAV payload necessary for efficient and safe firefighting performance.

Although field investigations constitute the cornerstone of geological studies, yet its application is often constrained by limited accessibility, time consumption, and high costs particularly in complex or remote terrains. However, recent advances in remote sensing technologies have significantly improved the ability to map large and inaccessible areas. In this regard, this study presents one of the detailed investigations integrating both optical and radar remote sensing data for the Kerdous and Ait Abdellah inliers in the western Anti-Atlas, Morocco. It aims to evaluate the effectiveness of Landsat 8 OLI and Sentinel-1 SAR datasets for litho-structural mapping, while also providing updated and detailed geological maps for both inliers. Several image processing methods were applied to Landsat 8 data for lithological discrimination, while Sentinel-1 data were used to extract structural lineaments. The results obtained show the effectiveness of PCA in refining lithological outcrops by clearly identifying facies such as quartzite, gabbro, rhyolite, and sedimentary breccias. Also, RGB composites (B2, B5, B7) allowed the visualization of formations like limestone, dolomite, and clay, while band ratio analysis revealed facies such as the Lie-de-vin shales, gabbro, and leucogranite. Moreover, lineament analysis reveals significant tectonic implications, highlighting predominant fault orientations of NE–SW in the Ait Abdellah inlier and NW–SE in the Kerdous inlier. Field verification and correlation with existing geological maps demonstrate this study’s contribution to identifying additional geological features, such as recent clay and scree deposits, previously undocumented or poorly represented. The findings highlight the enhanced accuracy and reliability of integrating multisensor remote sensing data for litho-structural mapping, providing a scalable framework for future investigations. However, it should be noted that the main limitations potentially affecting the results are the spatial and spectral resolution of the satellite data and the characteristics of arid and semi-arid terrains.

Advancements in remote sensing technology have enabled the use of satellite imagery, such as Landsat 8 and HLS-L30, for the spatial and temporal estimation of Land Surface Temperature (LST) with improved resolution. In the context of geothermal exploration, the availability of thermal infrared bands in these datasets facilitates more efficient and cost-effective mapping and identification of surface temperature anomalies, particularly across large and inaccessible areas. This study aims to compare LST estimations derived from Landsat 8 and HLS-L30 imagery using the Mono Window Algorithm (MWA) and Split Window Algorithm (SWA) at 18 geothermal manifestation points within the Mount Ungaran Geothermal Working Area (WKP). A Focal Statistic process was applied to 20 LST datasets, resulting in a total of 100 LST layers. From each layer, LST values were extracted at the 18 manifestation points, producing a total of 1,800 data points. A binary logistic regression analysis was conducted using these LST values alongside those from 20 randomly selected comparison points. The results indicate that the median LST derived from HLS-L30 imagery using the Split Window Algorithm with the minimum Focal Statistic yielded the most optimal performance in classifying geothermal manifestation presence. This method achieved statistical significance (p = 0.028), indicating its capability to effectively distinguish between manifestation and non-manifestation points. However, the pseudo-R² value of 0.107 suggests that the model explains approximately 11% of the variance in the data. These findings underscore the potential application of satellite-based LST analysis in the early detection and assessment of geothermal surface anomalies within WKPs.Keywords : Geothermal, LST, Landsat, HLS-L30, Ungaran

Abstract Semi-arid savanna ecosystems are increasingly vulnerable to climate change and anthropogenic disturbances, leading to significant changes in woody cover and structure. Monitoring and managing these changes are critical, especially in protected areas where resources are limited and traditional methods such as in situ field data collection are labour-intensive, expensive and not sufficient to capture large-scale spatial and temporal shifts. This study aims to evaluate the reliability of remote sensing for detecting abrupt ecosystem shifts by comparing it with expert knowledge and field observations, identifying their ecological drivers, and assessing its potential to support landscape-scale conservation planning. The analysis was performed in the Kruger National Park, South Africa using several data sources from the time period 1982 to 2023, allowing the use of findings for prioritising management actions. Despite differences in methods, remote sensing and expert-delineated maps showed strong agreement, with a spatial overlap of 65.6% and an overall accuracy of 82%. Remote sensing proved particularly valuable in detecting changes in inaccessible areas, validating its role in broad-scale ecological monitoring. Furthermore, we observed significant differences in species diversity, dominant species and vegetation structure in areas where remote sensing detected shifts, confirming the validity of the method. Shrub encroachment, which may be associated with herbivory pressure and increased rainfall severity, emerged as a key factor in ecosystem transformation. The integration of remote sensing, expert knowledge and ground-level data provides a robust approach to understanding and managing savanna ecosystem dynamics. This research highlights the importance of integrating multiple data sources to enhance ecosystem monitoring and inform management strategies to ensure resilient savanna landscapes.

This article presents and describes the results of research on determining the accuracy of a Digital Terrain Model (DTM) developed based on image data obtained from an Unmanned Aerial Vehicle (UAV). The Digital Terrain Model was created using image data acquired by an Unmanned Aerial Vehicle, specifically the fixed-wing with electric propulsion, flying at an altitude of 300 meters. The image data were collected during a photogrammetric survey conducted over a mountainous area in 2021. The final elevation values of the Digital Terrain Model were recorded in a GRID format with a spatial resolution of 5 meters. The article also includes a comparison of the DTM elevations with results obtained from the satellite GPS RTK technique. Based on this, an accuracy of elevation determination for different vertical profiles ranged from 0.19 m to 0.24 m was obtained. Moreover, the study also involves the development of a DTM from data acquired by the Unmanned Aerial Vehicle at an altitude of 150 meters. In this case, the accuracy of determining the elevations of the DTM for different vertical profiles ranged from 0.10 m to 0.16 m. The results of the research are very interesting for the application of UAV technology in aerial photogrammetry, particularly in inaccessible areas, especially mountainous regions.

Abstract The holy cave shrine of Amarnath is thronged annually by over three lakh devotees. However, the cryogenic-sensitive region is increasingly becoming vulnerable to anomalies in precipitation events and rising anthropogenic footprints. On the evening of 8 July 2022, a highly localized extreme rainfall event took place leading to a short-lived flash flood along with unsorted debris flow in the Amarnath valley, surmounting heavy loss of lives and local livelihoods. This article uses Earth Observation (EO) datasets to capture and understand the implications of using such data applications in mitigating disasters for remote and inaccessible areas. Despite the valuable insights provided by EO data, their applicability is often restricted by the temporal limitations, particularly those derived from open-source radar and optical satellite imagery, which are frequently incapable of capturing ephemeral or rapidly evolving phenomena. Some meaningful information about the present study was captured with the use of GPM (IMERG) satellite-based rainfall data, while others failed to gauge the situation. Eight topographical parameters have been examined to understand the local factors contributing to flash flood conditions in the Amarnath watershed. An AHP-based flash flood susceptibility zonation (FFSZ) was derived using Google Earth Engine (GEE) along with an interactive user interface was developed for visualization of the computed parameters. The FFSZ contains five classes with their areal percentages: Very Low (20.03%), Low (19.69%), Moderate (20.43%), High (20.14%) and Very High (19.71%) respectively. Our findings suggest the need for more ground-based automated weather stations (AWS) complementing satellite-based EO systems' limitations for providing high-precision regular interval observation. Finally, we propose a new ‘4S’ framework, namely, ‘source’, ‘setting’, ‘susceptibility’ and ‘solution’ for flash flood risk assessment. This framework has also been discussed in complementary to a cross-sectoral interface containing ‘science-governance-disaster risk reduction (DRR)-society’ aspects alongside major targets based on Global Goals (UN SDGs) and India’s national DRR agenda points.

BackgroundIn the northeastern region of India, perennial malaria transmission persists in certain hotspots in areas geographically adjacent to the international borders with Bhutan, Bangladesh, and Myanmar, where both Plasmodium vivax and Plasmodium falciparum coexist, particularly in remote, forested, and inaccessible areas. This northeastern landscape harbors a wide diversity of anopheline vector species; Anopheles minimus and Anopheles baimaii are the traditional primary vectors of malaria. The extensive deployment of long-lasting insecticidal nets (LLINs) and indoor residual spraying as traditional vector control strategies has resulted in regional and temporal changes in species composition, specifically An. minimus and An. baimaii, and their resting and feeding behavior. Despite the reduced abundance of these primary anopheline vectors, the persistence of malaria suggests the involvement of additional anopheline species. Secondary malaria vectors may also play a role in transmitting malaria, along with primary malaria vectors, and are widely distributed across northeastern India. Secondary malaria vectors have significantly lower sporozoite rates compared with primary malaria vectors, yet are capable of sustaining malaria transmission in a specific region. This study aimed to investigate the sporozoite positivity of secondary anopheline species in the high-malaria-endemic district of Kokrajhar, Assam, in northeastern India.MethodsDuring the study period, 1794 female mosquitoes representing five genera in Anopheles, Culex, Aedes, Mansonia, and Armigeres were collected using three methods: CDC light trap collection, indoor resting collection using the mouth aspiration method, and pyrethrum spray captures. Morphologically identified Anopheles maculatus group specimens were validated by polymerase chain reaction targeting the Internal Transcribed Spacer 2 region within the nuclear ribosomal DNA and referred to as An. maculatus, a species of the Maculatus Group of subgenus Cellia (Diptera: Culicidae).ResultsThe Plasmodium positivity (Percent, number/total number) was highest in An. maculatus (4%; 5/80), followed by An. minimus (4.8%; 1/21), and Anopheles kochi (4.6%; 1/22). These results suggest that anopheline species beyond the traditionally recognized primary vectors, such as An. minimus and An. baimaii, may play a role in sustaining malaria transmission in endemic areas of northeastern India.ConclusionsRecognizing and integrating the behavior and ecology of secondary vectors into malaria control programs is essential for the development and deployment of more targeted and sustainable vector control strategies.Graphical abstractSupplementary InformationThe online version contains supplementary material available at 10.1186/s13071-025-07110-5.

The Immunization Agenda 2030 (IA2030), led by WHO and partners, targets the global challenge of zero-dose children, who face higher risks of vaccine-preventable diseases. Globally, 18 million children remain zero-dose, with over half in conflict or humanitarian settings. In Somalia, about 60% of children are zero-dose, and during the 2022-2024 drought, over 70,000 deaths occurred, with nearly 40% among children under five. This review explores the burden, determinants, and geographic distribution of zero-dose children in Somalia's conflict-affected regions. This narrative review followed SANRA guidance. We searched PubMed, Scopus, Web of Science, Google Scholar, and key institutional sites (WHO, UNICEF, ReliefWeb, MoH Somalia, NGOs) for English-language literature (1990-July 31, 2025). From 197 records were identified, 82 new studies were included, resulting in a total of 279 studies after de-duplication and two-reviewer screening. Evidence was synthesized thematically and aligned to Immunization Agenda 2030 (IA2030) priorities. Zero-dose hotspots are concentrated in rural, nomadic, and conflict-affected zones, with Lower Juba reaching a peak of 62%. Key challenges include insecurity, limited access, disrupted supply chains, workforce shortages, and demand-side barriers like mistrust and misinformation. Humanitarian efforts are frequently hindered by checkpoints, blockades, and security concerns. From 2000 to 2024, Somalia's routine immunization program showed significant progress, with MCV-1 coverage rising from 50 to 71%, and MCV-2 from 5 to 55%, as per the WHO/UNICEF WUENIC data for the African region. Zero-dose children in inaccessible Somali districts are a pressing equity and health-security challenge. Sustaining recent national gains while fulfilling Immunization Agenda 2030 (IA2030)'s "leave no one behind" requires tailored outreach to remote communities, strengthened surveillance and e-registries for defaulter tracing, resilient cold-chain and WASH linkages, empowered community health workers (especially women), negotiated humanitarian access, and a progressive domestic co-financing roadmap alongside partner support.

Microbially influenced corrosion (MIC) is a widely studied phenomenon that continues to be poorly understood due to its inherent multifaceted nature. MIC involves complex interactions between microbial communities, their metabolic activities, and the surrounding environmental and material conditions. With the recent rapid expansion of human exploration into previously inaccessible areas, such as the deep sea, new questions about how the physiological adaptations of microbial communities influence their corrosive capabilities have been raised. This study investigates the relationship between corrosion in sulfate-reducing bacteria and the proteomic responses to environmental stresses in differently adapted organisms. It suggests that microorganisms sharing the same core metabolic pathways can drive corrosion through different mechanisms and highlights how hydrostatic pressure adaptations can impact MIC severity.