Distribution Patterns Research Articles

Prediction and spatial–temporal changes of soil organic matter in the Huanghuaihai Plain by combining legacy and recent data

Soil organic matter (SOM) is critical for soil fertility, crop growth, and plays an important role in the global carbon cycle and climate change. Therefore, spatial prediction of SOM is important to rational soil resource utilization, agricultural production, and ecological environment management. However, large-area SOM mapping research heavily relies on legacy soil data, and large-scale recent SOM mapping may not be possible or have lower accuracy due to limited or less recent data availability. In this study, we aimed to improve SOM prediction and mapping accuracy by combining legacy data with limited recent data. Three models, namely, partial least squares regression (PLSR), random forest (RF), and one-dimensional convolutional neural network (1D-CNN), were applied and compared. The results showed that combining legacy and recent data effectively improved SOM prediction accuracy compared to using only recent data. Among the three modeling methods, 1D-CNN exhibited superior performance, with an averaged determination coefficient of the prediction (R2) of 0.58, a root mean square error (RMSE) of 4.56 g/kg, and a ratio of performance to interquartile distance (RPIQ) of 2.05. The predicted SOM content for both legacy (1980 s) and recent (2010 s) periods showed similar spatial distribution patterns throughout the Huanghuaihai Plain. Generally, there was a noticeable trend of increasing SOM content from northwest to southeast, with higher values observed in Jiangsu and lower values concentrated in Henan, Hebei, and Shandong regions within the study area. Over time, SOM contents in the Huanghuaihai Plain showed an increasing trend, with an average increase of 5.90 g/kg from legacy to recent period. This study provides a promising approach for improving SOM prediction and mapping accuracy at large scales, particularly when recent data availability is limited.

Recombinant neorudin and its active metabolite hirudin: the fate in vivo of a novel anticoagulant drug

Thrombosis, a prevalent condition, can provoke severe health issues like acute coronary syndrome (ACS), deep vein thrombosis (DVT), and pulmonary embolism (PE). The rising incidence of these diseases annually significantly impacts patient wellbeing and poses a substantial burden on healthcare systems. Recombinant neorudin is a developing anticoagulant drug for thrombotic diseases whose phase I clinical trials has been completed. The distribution pattern of it and its active metabolite, hirudin, in thrombi, blood surrounding the thrombus and peripheral blood remains uncertain. This study explored their distribution using a rat arteriovenous bypass thrombosis model, revealing higher neorudin levels in blood surrounding the thrombus and elevated hirudin concentrations in thrombus. Recombinant neorudin significantly increased Thrombin Time (TT) in both plasma surrounding the thrombus and peripheral blood, and reduced the wet weight of the thrombus. The results above demonstrated the anticoagulant and antithrombotic efficacy of recombinant neorudin in vivo. Give the distribution pattern of neorudin and hirudin, we hypothesized that neorudin was cleaved at the site of thrombus formation to produce hirudin, leading to the rapid accumulation of hirudin within local thrombi and resulting in a higher concentration inside the thrombus. This insight was crucial for understanding the action mechanisms of anticoagulants in thrombosis management and provided a valuable guidance for therapeutic strategies in treating thrombotic diseases.

Full-length RNA transcript sequencing traces brain isoform diversity in house mouse natural populations.

The ability to generate multiple RNA transcript isoforms from the same gene is a general phenomenon in eukaryotes. However, the complexity and diversity of alternative isoforms in natural populations remain largely unexplored. Using a newly developed full-length transcripts enrichment protocol with 5' CAP selection, we sequenced full-length RNA transcripts of 48 individuals from outbred populations and subspecies of Mus musculus, and from the closely related sister species Mus spretus and Mus spicilegus as outgroups. The dataset represents the most extensive full-length high-quality isoform catalog at the population level to date. In total, we reliably identified 117,728 distinct isoforms, of which only 51% were previously annotated. We show that the population-specific distribution pattern of isoforms is phylogenetically informative and reflects the segregating SNP diversity between the populations. We find that ancient housekeeping genes are a major source of the overall isoform diversity, and that the generation of alternative first exons plays a major role in generating new isoforms. Given that our data allow us to distinguish between population-specific isoforms and isoforms that are conserved across multiple populations, it is possible to refine the annotation of the reference mouse genome to a set of about 40,000 isoforms that should be most relevant for comparative functional analysis across species.

Numerical simulation of hydrate flow in gas-dominated undulating pipes considering nucleation and deposition behaviors

The distribution and deposition of hydrates in deep-water gas transportation pipelines are crucial for safety. Current simulations of hydrate flow based on the population balance model have predominantly focused on water-dominant systems and neglect the nucleation and deposition of hydrates. By establishing a model for a hydrate flow in a gas-dominant system that considers the uneven distribution of the liquid film on the wall, hydrate nucleation, gas–liquid mass transfer, particle adhesion and aggregation, and dynamic deposition, we achieved simulation of the entire process of hydrate formation, aggregation, breakage, and deposition. Simulations in undulating pipelines were carried out to investigate the effects of gas velocity, liquid injection, pressure, and pipeline structure on distribution patterns. The results showed increasing the gas velocity enhanced the dispersion of particles and increasing the pressure increased the rate of aggregation. The formation of blocky aggregates posed significant risk in the rear section of the lower-bend pipe.

Transactional pathways: Institutional possibilities for status and wealth under racial/caste capitalism

I introduce the concept of transactional pathways, coined by anthropologist Jane Guyer, to trace the institutional processes that contribute to uneven and unjust patterns of wealth and status distribution under systems of colonialism and racial/caste capitalism. Transactional pathways employ historical perspectives to reveal how divergent economic institutions and sources of valuation relate to social hierarchies. This approach links everyday economic transactions with patterns of wealth accumulation that are based not only on class, but intersectional social groups including race, caste, and/or ethnicity. Transactional pathways account for the fact that not only do different groups receive different amounts of valuable resources because of uneven distribution, but they have variable access to the symbolic power required to define which resources are deemed valuable in the first place and to monopolize them accordingly. The article briefly surveys foundational concepts from the economic anthropology literature before detailing transactional pathways. It introduces the case of attempted formalization of waste collection and recycling in Delhi, India, using the related concepts of thresholds and conversions to analyze key moments when wealth and status accumulation becomes especially possible in institutionally plural contexts.

Fast and Efficient Drone Path Planning Using Riemannian Manifold in Indoor Environment

This paper introduces an innovative dual-path planning algorithm rooted in a topological three-dimensional Riemannian manifold (T3DRM) to optimize drone navigation in complex environments. It seamlessly integrates strategies for both discrete and continuous obstacles, employing spherical navigation for the former and hyperbolic paths for the latter. Serving as a transformative tool, the T3DRM facilitates efficient path planning by transitioning between discrete and continuous domains. In uncertain environments with unpredictable obstacle positions, our methodology categorizes these positions as discrete or continuous based on their distribution patterns. Discrete obstacles exhibit random distributions, while continuous obstacles display symmetrical patterns with continuity. Leveraging topological metrics, the T3DRM efficiently classifies these patterns for effective path planning. The findings of this research demonstrate the efficiency of path planning based on classified obstacle positions, enabling swift and efficient drone navigation. This research introduces a pioneering application of a T3DRM, accelerating drone navigation in uncertain environments through a dual approach that simultaneously transforms navigation in primal and dual domains. By enabling spherical and hyperbolic navigation concurrently, the T3DRM offers a comprehensive solution to discrete and continuous path planning challenges. The proposed approach can be used for various indoor applications, especially for warehouse management, surveillance and security, navigation in complex structures, indoor farming, site inspection, healthcare facilities, etc.

Data transformation and model selection in bivariate allometry.

Students of biological allometry have used the logarithmic transformation for over a century to linearize bivariate distributions that are curvilinear on the arithmetic scale. When the distribution is linear, the equation for a straight line fitted to the distribution can be back-transformed to form a two-parameter power function for describing the original observations. However, many of the data in contemporary studies of allometry fail to meet the requirement for log-linearity, thereby precluding the use of the aforementioned protocol. Even when data are linear in logarithmic form, the two-parameter power equation estimated by back-transformation may yield a misleading or erroneous perception of pattern in the original distribution. A better approach to bivariate allometry would be to forego transformation altogether and to fit multiple models to untransformed observations by nonlinear regression, thereby creating a pool of candidate models with different functional form and different assumptions regarding random error. The best model in the pool of candidate models could then be identified by a selection procedure based on maximum likelihood. Two examples are presented to illustrate the power and versatility of newer methods for studying allometric variation. It always is better to examine the original data when it is possible to do so.

Geographical Evaluation of Real Estate Services Offices in the City of Abha - Saudi Arabia, A Geographical Study using Geographic Information Systems (GIS)

Service geography is one of the branches of applied geography that has emerged as an applied intellectual interest to engage with the immediate direct needs of both urban and rural communities. The importance of studying services is due to their connection to economic planning, so geographical interest in them increases, as applied geography is based on a specific approach and philosophy of relevance or social benefit that focuses on the application of geographical knowledge and skills. To come up with solutions to real-world social, economic and environmental problems. The study focused on the use of geographic information systems in analyzing the geographic calendar of rental offices in the city of Abha, relying on the most important applied aspects of geographic information systems represented in spatial analysis. To reveal the characteristics of the spatial distribution of rental offices and their distribution pattern, and to evaluate the efficiency of their distribution according to the local standard. The study came out with a number of results and recommendations, and also verified the hypotheses assumed by the researchers.

Specialists regulate microbial network and community assembly in subtropical seagrass sediments under differing land use conditions

Microorganisms in the sediment play a pivotal role in the functioning and stability of seagrass ecosystems and their dynamics are influenced by the nutrient acquisition strategies of host plants. While the distinct impacts of microbial generalists and specialists on community dynamics are recognized, their distribution patterns and ecological roles within seagrass ecosystems remain largely unexplored. To address this issue, we conducted an analysis of community assembly processes and co-occurrence relationships of both microbial generalists and specialists within sediment profiles (0–100 cm) from seagrass habitats subjected to differing land use conditions. The results revealed that seagrasses in Yifeng Estuary experienced the large proportion of cultivated land and exhibited higher organic carbon content in the 0–20 cm surface sediment layer. Nitrogen-cycling bacteria were predominantly associated with seagrasses from Yifeng Estuary, whereas Vibrio spp. was more prevalent in seagrasses from Liusha Bay. Notably, seagrass Halophia beccarii (YHB) in Yifeng Estuary harbored higher niche breadths for both microbial generalist and specialist compared to Halodule uninervis (LHU) and Halophia ovalis (LHO) from Liusha Bay. Stochastic processes were pivotal in shaping seagrass sediment microbial communities, with a higher immigration rate observed in YHB, suggesting greater microbial turnover in this area. Additionally, YHB sediment presented lower drift and higher dispersal limitation among generalists compared to LHU and LHO, whereas the pattern was reversed among specialists. Specialists were found to play a crucial role in shaping microbial interactions within YHB sediment, with genera Halioglobus identified as keystone species in the network. The specialists were further found to significantly influence microbial β-diversity in seagrass sediment directly. Overall, our findings illustrated how microbial generalists and specialists were distributed in seagrass sediments in response to land use changes and provided new insights into the potential roles of microbial regulation in degraded seagrass ecosystems.

Evaluating the Efficiency of Spatial Distribution of ATM Machines in Abha City using Geographical Information Systems

This study aims to use geographic information systems to analyze the spatial distribution of ATMs in Abha city. This is based on the most important applied aspects of geographic information systems, namely spatial analysis, to reveal the characteristics of the spatial distribution of ATMs and their distribution pattern, and to evaluate the efficiency of their distribution according to spatial variables. The study came out with a number of results and recommendations, the most important of which is increasing the number of ATMs in high-density neighborhoods that are deprived of service, which reduces the pressure on them, in a way that ensures their sustainability, and in a manner that is proportional to both the area and the number of residents in the city's neighborhoods.

Turbulent flame propagation of C10 hydrocarbons/air expanding flames: Possible unified correlation based on the Markstein number

In this study, we experimentally analyzed the influence of turbulence and thermal-diffusional effect on the morphology and turbulent flame speed of premixed expanding flames. The turbulent flames of the n-decane/air and decalin/air mixtures were measured using a fan-stirred constant volume combustion bomb generating near-isotropic turbulence at elevated pressures (1, 2, and 5 bar), temperature (443 K), and a wide range of equivalence ratios (0.8–1.6). The results found that the wrinkling degree of the flame front was greater for Ma<0 compared to Ma>0. However, the distribution patterns of the curvature radius of the flame contours exhibited similarities across different equivalence ratios. Furthermore, an increase in turbulence intensity would aggravate the randomness of flame contour distribution. The turbulent expanding flames of n-decane/air and decalin/air mixtures were self-similar under different turbulence intensities and pressures, and this self-similar propagation followed a correlation between the normalized turbulent flame speed and the turbulent flame Reynolds number (ReT,f) to the one-half power. The similarity in normalized turbulent flame speeds was extended from normal alkanes (C4-C8) and isomeric alkanes (C8, C16) to longer straight-chain alkane (n-decane) and cycloalkane (decalin). As the increase of equivalence ratio, their normalized turbulent flame speeds increased nonlinearly due to the thermal-diffusional effect. Additionally, it was found that the classical, effective, and experimental Lewis numbers were confirmed as unsuitable parameters for characterizing the role of thermal-diffusional effect on the turbulent flame speed for hydrocarbon fuels with large molecular weight. Finally, two possible unified correlations were proposed based on the Markstein number, (d〈r〉/dt)/(σSL)=0.178e−0.231MaReT,f1/2 and (d〈r〉/dt)/(σSL)=(0.170−0.0447Ma+0.0067Ma2)ReT,f1/2, which could predict the turbulent flame speeds of hydrocarbon fuels with large molecular weight such as n-alkanes, iso-alkanes, and decalin.

A comprehensive study on the validation and application of multi-lognormal distribution models for atmospheric particles

The particle number size distribution (PNSD) is crucial for evaluating air quality and mitigating environmental pollution, as particles of different sizes have diverse effects on human health and climate. However, obtaining a comprehensive understanding of PNSD is challenging due to its inherent complexities and variability. Multi-lognormal distribution models are employed to fit PNSD, as seen in climate models, but discrepancies between model fits and observed PNSD persist. This study adopts hourly data from 2017 to 2020 across eight monitoring sites in diverse environments—rural, urban, mountainous, and polar, and compares the observed PNDS with those simulated by multi-lognormal distribution models. The results demonstrated that the model generally achieved a high correlation with observed PNSD data (r2 > 0.75), effectively capturing key characteristics of nucleation and Aitken mode particles. However, the model had a tendency to overestimate the total number concentration by approximately 1.09 times, particularly noticeable under conditions of high concentrations of smaller particles. The model successfully represented prevalent bimodal size distribution patterns in urban areas with high ultrafine particle concentrations, though its performance was slightly less accurate in scenarios involving trimodal distributions. Despite these strong correlations and the model's ability to reflect diurnal and seasonal variations, which suggests its broad applicability and utility, there were notable limitations on smaller time scales and in specific particle size ranges. These limitations were particularly evident in capturing detailed phenomena relevant to new particle formation events, indicating areas where model refinement is necessary. The results highlighted the importance of investigating discrepancies between model predictions and actual observations, which is crucial for refining climate models that utilize PNDS. The uniform comparison facilitated a detailed exploration of particle properties from model results, offering deeper insights into aerosol behavior and its environmental impacts.

Spatial-temporal evolution patterns of influenza incidence in Xinjiang Prefecture from 2014 to 2023 based on GIS

Using GIS technology, this study investigated the spatiotemporal distribution pattern of influenza incidence in Xinjiang from 2014 to 2023 based on influenza surveillance data. The study revealed a noticeable fluctuation trend in influenza incidence rates in Xinjiang, particularly notable spikes observed in 2019 and 2023. The results of the 3-year moving average showed a significant long-term upward trend in influenza incidence rates, confirmed by Theil-Sen method (MAD = 2.202, p < 0.01). Global spatial autocorrelation analysis indicated significant positive spatial autocorrelation in influenza incidence rates from 2016 and from 2018 to 2023 (Moran’s I > 0, P < 0.05). Local spatial autocorrelation analysis further revealed clustering patterns in different regions, with high-high clustering and low-high clustering predominating in northern Xinjiang, and low-low clustering predominating in southern Xinjiang. Hotspot analysis indicated a progressive rise in the number of influenza incidence hotspots, primarily concentrated in northern Xinjiang, particularly in Urumqi, Ili Kazakh Autonomous Prefecture, and Hotan Prefecture. Standard deviation ellipse analysis and the trajectory of influenza incidence gravity center migration showed that the transmission range of influenza in Xinjiang has been expanding, with the epidemic center gradually moving northward. The spatiotemporal heterogeneity of influenza incidence in Xinjiang highlights the need for differentiated and precise influenza prevention and control strategies in different regions to address the changing trends in influenza prevalence.

Unraveling soil geochemical, geophysical, and microbial determinants of the vertical distribution of organic phosphorus pesticide pollutants

Pesticide contamination has emerged as a global threat to humans. Here, we investigate the soil distribution pattern of organic phosphorus pesticide contamination at a pesticide manufacturing site in northern China, exploring their relationships with soil properties and microbial communities. The concentrations of four organic phosphorus pesticides (i.e., phorate, terbuthion, fenitrothion, and parathion) decreased substantially with soil depths from the surface down to 2 m. However, terbuthion, fenitrothion, and parathion had second-peak concentrations at a depth of 8 m. The concentrations of those organic phosphorus pesticides were negatively correlated with soil water content, but positively correlated with sulfide, pH, and total phosphorus. The distribution patterns of organic phosphorus pesticides closely aligned with that of soil organic matter and clay minerals, especially in the presence of montmorillonite, kaolinite, and chlorite. Various bacterial genera known to degrade organic phosphorus pesticides, such as Flavobacterium, Bacillus, Acinetobacter, Lactobacillus, Pseudomonas, Sphingomonas, and Thiobacillus, were correlated with these pesticides. Since these genera were among the top 50 abundant genera in our samples, they might play a significant role in the degradation of organic phosphorus pesticides. Together, this study unveils previously unrecognized pesticide-soil-microbe interactions, thus providing an important knowledge basis for environmental remediation strategies.

A Bajocian event of global coral reef growth: Record from northern Switzerland

Following the extinction event at the Triassic – Jurassic boundary and during the Pliensbachian – Toarcian events, coral reef builders were severely affected, and the number of reef domains during the early Middle Jurassic was at an all-time low. However, new and updated data seem to show that corals were more widespread than previously thought, particularly during the Bajocian (170–168 Ma), but biostratigraphic markers are lacking to constrain the precise timing of reef evolution of this interval. A recently discovered 40 m-thick carbonate unit in northern Switzerland, on the northern Tethys margin, documents this rapid growth. Two cores from this unit display a reef with a high number of specimen but a low coral diversity, dated as Bajocian, which likely grew at a considerable water depth (upper limit of the mesophotic zone or 20–30 m). Additionally, it developed on top of clay mineral-rich accumulation characterised by low relief. Twelve different coral genera were identified, with a strong predominance of Periseris, Isastrea, Thamnasteria and Dendraraea. In the absence of other biostratigraphic markers, palynomorphs were used to provide accurate dating, which shows that palynology is a powerful tool for dating reef deposits. The results show reef growth during the early Bajocian, in the Sauzei and Humphriesianum ammonite zones, based on the palynological data, yielding similar ages to other Bajocian reef localities in the Eastern Paris Basin in France and Luxembourg dated simultaneously. These results indicate that the Middle Jurassic and more specifically the last two ammonite zones of the early Bajocian were periods suitable for coral reef builders, and that global regrowth of coral reefs occurred more rapidly than expected. A new Bajocian reef distribution is presented, showing no reefs at latitudes below 15°. This distribution pattern is probably due to the fact that water temperature was too elevated (> 25 °C) towards the equator for corals, which prevented reef growth. This would tend to favour a scenario in which the global climate, in particular temperature, is a determining factor for coral reef growth.

Spatial pattern of forest aboveground biomass and its environmental influencing factors in Qinling-Daba Mountains, central China

Accurate estimation of forest aboveground biomass (AGB) is crucial for understanding and managing forest ecosystems in the context of global environmental change, and also provides a scientific basis for national and regional ecological planning and carbon emission reduction policies. In order to investigate the regional pattern of forest AGB and its influencing factors in central China, a total of 469 sample plots were measured along four sample transects and on six mountains in field survey. The results showed that: 1) Two longitudinal distribution patterns of forest AGB were found, and one was that the AGB in the Qinling Mountains and the Daba Moutains gradually decreased from east to west, and the other was that the AGB in the areas between the two mountains gradually increased from east to west. The latitudinal distribution pattern of the forest AGB showed an "increasing–decreasing-increasing–decreasing" trend from south to north. The altitudinal distribution pattern showed a "first increasing-then decreasing" pattern with increasing altitude. 2) The influence of each factor on the spatial pattern of forest AGB was manifested as temperature > precipitation > HAI > topography, indicating that the spatial pattern of forest AGB in central China was the result of the interaction of climate, human activities and natural factors.

Comparison of cat stone matrix and cat urine proteomes to human calcium oxalate stone matrix and urine proteomes.

Cat calcium oxalate monohydrate kidney stone matrix proteome showed great similarity to human calcium oxalate monohydrate stone matrix proteome, but inference of mechanistic similarity was limited by the absence of cat urine proteomic data. In this study, urine proteome distributions were measured by the same methods in 7 healthy cats for comparison to both the published human urine and cat calcium oxalate stone matrix proteomes to assess for similar enrichment patterns in both species. Furthermore, proteomic distributions were determined in cat struvite stone matrix to test for similarity to calcium oxalate monohydrate stone matrix and urine proteomes. Cat urine proteins demonstrated a similar distribution of abundance as a function of isoelectric points or net charge to human urine samples, and consequently the similarly altered patterns of protein distributions seen in calcium oxalate monohydrate stone matrix seen from both cat and human stones likely derives from the same preferential adsorption mechanism. Furthermore, the fact that protein abundance patterns seen in cat struvite stone matrix samples differ from both urine and calcium oxalate monohydrate stone matrix proteomes in systematic ways suggests that a combination of protein-protein and protein crystal interactions underly the formation of the crystal aggregates that comprise stones.

Size-dependent finite element buckling analysis of porous cylindrical micro-shells reinforced by graphene platelets

This study introduces a spatial shear deformable rectangular element formulation to investigate the size-dependent buckling behavior of porous graphene platelets (GPL) reinforced micro-shells within the framework of the modified couple stress theory (MCST) for the first time in the worldwide term. The rectangular element, characterized by 4 nodes with 19 degrees of freedom each and possessing weak continuity of order C 1 , incorporates a length scale parameter enabling size-dependent analyses of shells. The research considers three distinct functions for the distribution of porosity combined with three different patterns of the GPL distribution (called by patterns A to C) along the micro-shell thickness. The elastic modulus of the nanocomposite in the absence of porosity is obtained using the Halpin-Tsai micromechanics model. Subsequently, the study meticulously validates the modeling accuracy and then investigates variations in the critical buckling load with respect to porosity distribution functions, distribution patterns of GPL, porosity coefficient, weight percentage of GPL, geometric parameters of the cylinder, and the length-scale parameter. The results reveal that the combination of the GPL pattern A with the first symmetric type porosity distribution yields the highest critical buckling loads. On the contrary, if the pattern B is combined with the second symmetric type of porosity distribution, the lowest critical buckling load will be observed. Given the accuracy of the results obtained and the versatility of the finite element method (FEM) in handling complex geometries together with diverse boundary conditions, the developed element holds promise for analyzing shells of various shapes under different boundary conditions.

News on the imaging of large vessel vasculitis

Large vessel vasculitis, including giant cell arteritis (GCA) and Takayasu arteritis (TAK), are autoimmune diseases primarily affecting the aorta and its branches. GCA is the most common primary vasculitis. Inflammatory changes in the vessel walls can cause serious complications such as amaurosis, stroke, and aortic dissection and rupture. Imaging techniques have become an integral part for the diagnosis and monitoring of large vessel vasculitis, allowing for effective disease monitoring. GCA and TAK exhibit similar patterns of vascular distribution. However, the temporal arteries are never involved in TAK, and axillary arteritis occurs more frequently in GCA. In most centers, ultrasound of the temporal and axillary arteries has replaced temporal artery biopsy as the primary diagnostic tool for GCA. In addition to ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), and [18F]-FDG (fluorodeoxyglucose) positron emission tomography-computed tomography (PET) are important, particularly for visualizing the aorta. Moreover, PET-CT is now also capable of assessing the temporal arteries, although it is not yet widely available. In polymyalgia rheumatica (PMR), ultrasound of the shoulder and hip regions is part of the ACR/EULAR classification criteria. MRI allows detailed visualization of additional inflammatory extraarticular manifestations, showing characteristic inflammatory lesions in entheses, tendons, and ligaments. [18F]-FDG-PET-CT also enables the visualization of musculoskeletal inflammation, especially in the shoulder and hip regions, as well as paravertebral areas. Ultrasound can detect subclinical GCA in up to 23% of patients with PMR, which should be treated like GCA. Technological innovations such as new radiotracers and improved MRI imaging could further enhance the diagnosis and monitoring of large vessel vasculitis and PMR, thus playing acrucial role in improving the prognosis through faster initiation of therapy.

Vector Borne Disease Ecology and Environment: Remote Sensing and GIS for Control and Management: A Systematic Review

The prevalence of vector borne disease epidemics are influenced by the thickness of the vectors persistent to climate, landscape, and environment. Historically evidenced of triggering epidemics in both vertical magnitude and horizontal spread (spatial diffusion) of increasing vector borne diseases, such as; malaria, dengue, chikungunya, Japanese encephalitis, filariasis, leishmaniases, scrub typhus, Kyasanur forest disease (KFD), West Nile virus, Lyme disease, Zika virus, and Rift valley fever in the tropical and subtropical regions, particularly, in the third world countries for the past several decades. The geographical analysis of each one VBD epidemics has a unique vector ecology and environment. The prevalence of epidemic distribution patterns and seasonal variations, and associated vector ecology were analyzed throughout the world for the past periods, in order to assess the probability of potential risk and delineate the hotspot regions susceptible to the VBD outbreaks in the country, using Remote Sensing and GIS mapping analysis. It offers a quick and efficient approach to mapping of land uses/land cover patterns and its changes over space and time, and the information on these changes linking with vector profusion and disease ecology. Vector-borne disease epidemics across the country have been evidently associated with climate factors, landscape changes, potential breeding sources; such as, water bodies, rivers, streams, and mega water resource irrigation projects, dams / reservoirs, water pools, lakes, urban agglomerations, Urban sprawl, urban dynamics, industrial developments and growths, floating population, urban migration, land use / land cover changes, wet irrigation agriculture practices, seasonal migrations on occupation, cargo shipping movements, trade and commerce, etc., and have been acted upon changing the aboriginal territories by extent of epidemic scenarios into the non-endemic regions. The integrated Earth Observation Resource Satellite data integrated with GIS has effectiveness upon proved to disease mapping, ecological niche modeling, risk assessment, spatial prediction, and offering answers to both the public health programmers and research scientists concerned on vector fecundity, and vector borne disease ecology, and thus, the geographical, ecological and environmental determinants of its range is considered to be essential for sustainable public health planning. Accordingly, prevention measures and appropriate control strategy may possibly be applied during the sporadic outbreaks situations in the new epidemic regions as well in the hot spot endemic regions regularly, so as to control the erratic transmission and prevent acceleration of epidemics early in advance successfully.