Fusion of spectral and topographic features for land use mapping using a machine learning framework for a regional scale application.

This study investigated the dynamics of land use and land cover (LULC) modelling, mapping, and assessment in the Kegalle District of Sri Lanka, where policy decision-making is crucial in agricultural development where LULC temporal datasets are not readily available. Employing remotely sensed datasets and machine learning algorithms, the work presented here aims to compare the accuracy of three classification approaches in mapping LULC categories across the time in the study area primarily using the Google Earth Engine (GEE). Three classifiers namely random forest (RF), support vector machines (SVM), and classification and regression trees (CART) were used in LULC modelling, mapping, and change analysis.

Airborne DNA reveals predictable spatial and seasonal dynamics of fungi.

Fungi are among the most diverse and ecologically important kingdoms in life. However, the distributional ranges of fungi remain largely unknown as do the ecological mechanisms that shape their distributions. To provide an integrated view of the spatial and seasonal dynamics of fungi, we implemented a globally distributed standardized aerial sampling of fungal spores.

Global Spore Sampling Project: A global, standardized dataset of airborne fungal DNA.

Novel methods for sampling and characterizing biodiversity hold great promise for re-evaluating patterns of life across the planet. The sampling of airborne spores with a cyclone sampler, and the sequencing of their DNA, have been suggested as an efficient and well-calibrated tool for surveying fungal diversity across various environments. Here we present data originating from the Global Spore Sampling Project, comprising 2,768 samples collected during two years at 47 outdoor locations across the world.

Future Prediction of Close Contacts in IoT-based Contact Tracing System using a New Real-Life Dataset.

Contact tracing is an effective method for mitigating the infectious diseases spread and it played a crucial role in reducing COVID-19 outbreak. Since the pandemic, there has been an increased concern regarding people's health in hospital and office settings, as these limited air exchange spaces provide a conductive medium for virus spread. Various technologies were used to recognize close contacts autonomously, in addition, multiple machine learning attempts were carried out to determine proximity in contact tracing.

Re-Evaluating : Ancestral State Reconstructions of Selected Characters and Evolution of Nutritional Modes.

(, ) occur in a wide range of habitats as endophytes, saprobes, and pathogens. The order has not been subjected to evaluation since 2019 by Phillips and co-authors using phylogenetic and evolutionary analyses. Subsequently, many studies introduced novel taxa into the order and revised several families separately.

Feasibility of Bluetooth Low Energy wearable tags to quantify healthcare worker proximity networks and patient close contact: A pilot study.

Background: The hospital environment is characterised by a dense network of interactions between healthcare workers (HCWs) and patients. As highlighted by the coronavirus pandemic, this represents a risk for disease transmission and a challenge for contact tracing. We aimed to develop and pilot an automated system to address this challenge and describe contacts between HCWs and patients.

https://botryosphaeriales.org/, an online platform for up-to-date classification and account of taxa of Botryosphaeriales.

Fungi are eukaryotes that inhabit various ecosystems worldwide and have a decomposing effect that other organisms cannot replace. Fungi are divided into two main groups depending on how their sexual spores are formed, viz. Ascomycota and Basidiomycota.

Is leishmaniasis adequately notified in Sri Lanka? A survey among doctors from an endemic district, Sri Lanka.

Background: Leishmaniasis is a notifiable disease in Sri Lanka since 2008. Previous studies show a gap in the notification of leishmaniasis. The purpose of the present study was to determine the Knowledge, attitudes and practice of medical officers regarding leishmaniasis.