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Abstract Despite recent research efforts to explore the co-occurrence patterns of diverse microbes within soil microbial communities, a substantial knowledge-gap persists regarding global climate influences on soil microbiota behaviour. Comprehending co-occurrence patterns within distinct geoclimatic groups is pivotal for unravelling the ecological structure of microbial communities, that are crucial for preserving ecosystem functions and services. Our study addresses this gap by examining global climatic patterns of microbial diversity. Using data from the Earth Microbiome Project, we analyse a meta-community co-occurrence network for bacterial communities. This method unveils substantial shifts in topological features, highlighting regional and climatic trends. Arid, Polar, and Tropical zones show lower diversity but maintain denser networks, whereas Temperate and Cold zones display higher diversity alongside more modular networks. Furthermore, it identifies significant co-occurrence patterns across diverse climatic regions. Central taxa associated with different climates are pinpointed, highlighting climate’s pivotal role in community structure. In conclusion, our study identifies significant correlations between microbial interactions in diverse climatic regions, contributing valuable insights into the intricate dynamics of soil microbiota.

Backgrοund: In mοdern sοciety, the use οf sοurces that emits electrοmagnetic radiatiοn (EMR) such as televisiοn, radiο, mοbile telephοny, etc. cοnstantly increases, resulting in a parallel increase in the stress οf the general pοpulatiοn, abοut the effects that may be caused tο health. Fοr this reasοn, EMR measurements and their evaluatiοns shοuld be cοmmunicated tο the pοpulatiοn tο reduce misinfοrmatiοn and undue stress. The purpοse οf this wοrk is tο is tο Geοreferencing οf Expοsure tο 4G and 5G Radiοfrequency Electrοmagnetic Fields frοm mοbile phοnes in Thessaly Regiοn (Central Greece). Methοds: 220 measurements were perfοrmed in the regiοn οf Thessaly, in οrder tο cοmpare the electrοmagnetic expοsure befοre and after 5G installatiοn. A pοrtable field strength analyzer (SRM 3006, Narda Safety Test Sοlutiοns, Pfullingen, Germany) and a three-axis isοtrοpic antenna were used, and 4G and 5G electrοmagnetic radiatiοn measurements were perfοrmed in 3 cities οf Central Greece, in the regiοn οf Thessaly. We used GIS, especially Kriging algοrithm tο create electrοmagnetic envirοnment maps. Results: Befοre the installatiοn οf 5G, measurements cοnducted in the Thessaly regiοn, in all cities (Larisa, Karditsa, Vοlοs) shοwed an mean expοsure ratiο οf 0.0003, with a median value οf 0.0001. After the installatiοn οf 5G, measurements shοwed an mean and median expοsure ratiο οf 0.0008. Cοnclusiοns: The recοrded expοsure values within the Thessaly regiοn cοnsistently remained belοw the internatiοnally recοmmended benchmark levels established by the ICNIRP. Cοnsequently, there is nο significant risk οf electrοmagnetic radiatiοn frοm mοbile phοnes and base statiοns in sensitive lands (schοοls, kindergarten etc) lοcated in the cities οf Thessaly.

Forest monitoring benefits from biophysical parameters such as Leaf Area Index (LAI), Plant Area Index (PAI) and fractional vegetation cover (FCOVER) and can be obtained from optical and LiDAR remote sensing, such as Sentinel-2 (S2) and the Global Ecosystem Dynamics Investigation (GEDI). While GEDI-derived products consider all phyto-elements, those from S2 refer to green elements only. Apart from individual accuracies, systemic deviations among products are thus expectable. However, products from S2 and GEDI lack inter-comparison. We evaluated S2 and GEDI-derived LAI, PAI and FCOVER with digital hemispherical photography observations (DHP) in a forest disturbance hotspot in Germany across various forest conditions, including vital stands, standing deadwood and clearings. We found moderate to high agreement with in-situ data, with highest accuracy for S2-derived LAI (R2 = 0.54) and GEDI-derived FCOVER (R2 = 0.73). Agreements between S2 and GEDI products were low, which we attribute to systematic influences of woody components, GEDI’s limitations in sloped terrain, and saturation of optical signals in dense canopy. In conclusion, findings suggest that while GEDI is effective in dense canopies, S2 products are beneficial for monitoring forest recovery. We also see potential for synergistic use in monitoring standing deadwood for habitat mapping and fire risk assessment.

An attempt has been made to develop Rishikesh Urban Information System (RUIS) with this concern in mind so that efforts made during data collection and acquisition of latest data on resources available in the Rishikesh township and its environs can be used by the administrators, town planners, tourists and even common man to locate and appraise of the areas of their interest. The study of Rishikesh township and its environs carried out in this work would be useful in formulating developmental planning strategies in the area, as the spatial and attribute information about various utilities-facilities and geoenvironmental parameters is available in a georeferenced GIS mode. RUIS is a GIS based application system that amalgamates Visual Basic .Net, ESRI MAP OBJECT 2.0, and Microsoft Access. This system allows linkage of spatial and attributes data with suitable visual display of both the data types. RUIS supports on screen map viewing with attribute information to provide meaningful insights into the geo-aspects of the region for updating the knowledge of planners and tourists interested in this area. Anyone can easily access it anytime, anywhere by using internet.

Grasslands across the African continent are under pressure from climate change and human activities, particularly in arid ecosystems. From a remote sensing perspective, these ecosystems have not received much scientific attention, especially in Namibia. To address this knowledge gap, various remote sensing methods were implemented using new generation spaceborne imaging spectrometers amongst others. Therefore, this research provides a first methodological approach aimed at mapping and evaluating the distribution of grasslands within two private nature reserves, namely, the NamibRand Nature Reserve (NRNR) and ProNamib Nature Reserve (PNNR) with surrounding farmlands on the edge of Namib Sand Sea. The multi-sensor approach utilizes Mixture Tuned Matched Filtering (MTMF) and incorporated spectral information collected in the field to analyze grasslands. The research involves a sensor comparison of multispectral Sentinel-2 and PlanetScope data, hyperspectral data from Environmental Mapping and Analysis Programme (EnMAP) and PRecursore IperSpettrale della Missione Applicativa (PRISMA) and an additional data fusion product derived from Sentinel-2 and EnMAP imagery based on a Smoothing Filter-based Intensity Modulation Hypersharpening method (SFIM-HS). Additionally, a unique spectral library of collected field spectra was established and inter-species spectral separability and intra-species spectral homogeneity was analyzed. This library presents newly published spectra of individual species. Due to dry initial conditions, the calculated spectral separability of individual grasses is limited, making only a mean endmember feasible for partial unmixing. The validation results of satellite comparison show that data fusion products (R2 = 0.51 with Normalized Difference Vegetation Index (NDVI); R2 = 0.66 with Soil Adjusted Vegetation Index (SAVI)) are more suitable for mapping arid grasslands than multispectral or hyperspectral data (all R2 < 0.35). More research is required and potential methodological adjustments are discussed to further investigate the spatio-temporal dynamics of arid grasslands and to aid conservation efforts in the Greater Sossusvlei-Namib Landscape in line with the United Nations Decade of Restoration.

Research over the past decades has demonstrated the explanatory power of emotions, feelings, motivations, moods, and other affective processes when trying to understand and predict how we think and behave. In this consensus article, we ask: has the increasingly recognized impact of affective phenomena ushered in a new era, the era of affectivism?

Everyday living environments concentrate a growing amount of wireless communications leading to increased public concern for radiofrequency (RF) electromagnetic fields (EMF) exposure. Recent technological advances are turning the focus on Internet of Things (IoT) systems that enable automated and continuous real-time EMF monitoring, facing however several challenges mainly stemming from infrastructural costs. This paper seeks to provide a comprehensive view of RF-EMF levels in Greece and evidence-based decision support for a spatially prioritized deployment of an IoT RF-EMF monitoring system. We applied the stratified sampling method to estimate Electric Field Strength (EFS) in the 27MHz-3GHz range in 661 schools. Three different residential areas were considered, i.e. urban, semi-urban and rural. Results showed that the 95% confidence interval for the EFS is (0.40, 0.44) with central value equal to the sample mean 0.42 V/m. We obtained strong evidence that the mean EFS value for all Greek schools is 0.42, which is 52 times lower than the Greek safety limit and equal to 1% of international limits. Mean EFS values of individual residential areas were also significantly below safety limits. Rural areas displayed the highest EFS peaks comprising the strongest candidate to start the deployment of an IoT RF-EMF monitoring system from.

We review the establishment of computational biology in Greece and Cyprus from its inception to date and issue recommendations for future development. We compare output to other countries of similar geography, economy, and size—based on publication counts recorded in the literature—and predict future growth based on those counts as well as national priority areas. Our analysis may be pertinent to wider national or regional communities with challenges and opportunities emerging from the rapid expansion of the field and related industries. Our recommendations suggest a 2-fold growth margin for the 2 countries, as a realistic expectation for further expansion of the field and the development of a credible roadmap of national priorities, both in terms of research and infrastructure funding.

Radiotherapy (RT) is a major part of cancer treatment. The reported variability in patient response to this modality can interfere with the continuation of best-possible care, promote side effects, and lead to long-term morbidity. Tools to predict a patient’s response to radiation could be highly useful in improving therapeutic outcomes while minimizing unnecessary and toxic exposure to radiation. This study investigates the potential of using molecular biomarkers as predictors of radiosensitivity in clinical practice. We review relative studies researching the positive correlation between various molecular biomarkers and patient radiosensitivity, including DNA damage response and repair proteins, inflammation and apoptosis markers, cell cycle regulators, and other biological markers. The clinical perspectives and applicability of these biomarkers in the prediction of radiosensitivity are also critically discussed. Conclusively, we underline the dynamics of molecular biomarkers to improve the efficacy and safety of radiotherapy in clinical practice and highlight the need for further research in this field. Identification of the most prominent markers is crucial for the personalization of therapies entailing ionizing radiation.

An attempt has been made to delineate and identify the alignment of a new route between two important cities of north India, Haridwar & Roorkee using Geoinformatics techniques. Geo-engineering parameters like slope, aspect, geology, land use, drainage and soil along with some techno-economical parameters have been used for this purpose. Multi-criteria weight method has been applied. Five weighting methods (AHP - Analytical Hierarchy Process, Rank Sum, Rank Reciprocal, Rank Exponent and Ratio Estimation) were applied simultaneously to eliminate biasness in weight assignment to the input parameters. The results show that AHP method is the best and ratio estimation method is the second best method for identification of optimum route alignment. Few more parameters were used for final selection of optimum route viz., minimum construction cost; minimum number of bridges and culverts on that route; maximum number of settlement within 5 km buffers on both sides of route; maximum number of tourist locations like temples, waterfalls, springs etc. within 5 km buffer zone on both side of route. The proposed route between Roorkee and Haridwar towns is only 29.22 km long (includes a 17.10 km long part of the existing road), the new road required is 12.12 km, while the existing longer route between Roorkee and Haridwar is 33 km (instead of 29.22 km). By using multi-criteria weighted methods of route alignment, a length of approximately 3.78 km can be avoided. It was also observed that slope, land use and drainage parameters are more sensitive for route alignment.