Optimal Solar Plant Site Identification Using GIS and Remote Sensing: Framework and Case Study

Many countries have set a goal for a carbon neutral future, and the adoption of solar energy as an alternative energy source to fossil fuel is one of the major measures planned. Yet not all locations are equally suitable for solar energy generation. This is due to uneven solar radiation distribution as well as various environmental factors. A number of studies in the literature have used multicriteria decision analysis (MCDA) to determine the most suitable places to build solar power plants. To the best of our knowledge, no study has addressed the subject of optimal solar plant site identification for the Al-Qassim region, although developing renewable energy in Saudi Arabia has been put on the agenda. This paper developed a spatial MCDA framework catering to the characteristics of the Al-Qassim region. The framework adopts several tools used in Geographic Information Systems (GIS), such as Random Forest (RF) raster classification and model builder. The framework aims to ascertain the ideal sites for solar power plants in the Al-Qassim region in terms of the amount of potential photovoltaic electricity production (PVOUT) that could be produced from solar energy. For that, a combination of GIS and Analytical Hierarchy Process (AHP) techniques were employed to determine five sub-criteria weights (Slope, Global Horizontal Irradiance (GHI), proximity to roads, proximity to residential areas, proximity to powerlines) before performing spatial MCDA. The result showed that ‘the most suitable’ and ‘suitable’ areas for the establishment of solar plants are in the south and southwest of the region, representing about 17.53% of the study area. The ‘unsuitable’ areas account for about 10.17% of the total study area, which is mainly concentrated in the northern part. The rest of the region is further classified into ‘moderate’ and ‘restricted’ areas, which account for 46.42% and 25.88%, respectively. The most suitable area for potential solar energy, yields approximately 1905 Kwh/Kwp in terms of PVOUT. The proposed framework also has the potential to be applied to other regions nationally and internationally. This work contributes a reproducible GIS workflow for a low-cost but accurate adoption of a solar energy plan to achieve sustainable development goals.

On-Site Identification of Pottery with pXRF: An Example of European and Chinese Red Stonewares

The invention of European hard porcelain, which aims at imitating kaolin-containing white paste of Chinese porcelain, had been started by the development of the technology of “red porcelain”, so-called “Jaspisporzellan” by Johann Friedrich Böttger in the early-eighteenth century at Meissen (Saxony). The visual features of the earlier Böttger red stoneware were rather similar to the one produced in Yixing, China. The prominence of Böttger productions allowed the manufacturing to be expanded across Europe to different countries (Holland, England, France, etc.). In this study, the chemical characteristics of nine European unglazed objects produced in England, France, Russia, and Holland from the 17th to 19th century and 10 Chinese (unglazed or enameled) red stoneware have been studied by using an on-site characterization technique pXRF. The results were compared with the previous studies carried out on 25 unglazed, polished, and non-polished Böttger artefacts. This non-invasive, speedy technique allows a methodology to be created for distinguishing the technological differences related to the provenance and authenticity of the artefacts. The elemental measurements explicitly show the significant discrepancy of Dutch objects from the main group, which involves other European and Chinese ones. Both a Lambertus van Eenhoorn (Delft) statue and an Ary de Milde (Delft) teapot are distinguishable from other European red stoneware by the high content of iron and calcium and high content of titanium and potassium, respectively, found in their body compositions. An overall comparison was made between the measurements made at different times in order to evaluate the error range arising from the measurement procedure (e.g., energy resolution of other series of the same instrument model).

Frontiers Approaches to the Diagnosis of Thrips (Thysanoptera): How Effective Are the Molecular and Electronic Detection Platforms?

Thrips are insect pests of economically important agricultural, horticultural, and forest crops. They cause damage by sucking plant sap and by transmitting several tospoviruses, ilarviruses, carmoviruses, sobemoviruses, and machlomoviruses. Accurate and timely identification is the key to successful management of thrips species. However, their small size, cryptic nature, presence of color and reproductive morphs, and intraspecies genetic variability make the identification of thrips species challenging. The use of molecular and electronic detection platforms has made thrips identification rapid, precise, sensitive, high throughput, and independent of developmental stages. Multi-locus phylogeny based on mitochondrial, nuclear, and other markers has resolved ambiguities in morphologically indistinguishable thrips species. Microsatellite, RFLP, RAPD, AFLP, and CAPS markers have helped to explain population structure, gene flow, and intraspecies heterogeneity. Recent techniques such as LAMP and RPA have been employed for sensitive and on-site identification of thrips. Artificial neural networks and high throughput diagnostics facilitate automated identification. This review also discusses the potential of pyrosequencing, microarrays, high throughput sequencing, and electronic sensors in delimiting thrips species.

Targeting the Aryl Hydrocarbon Receptor (AhR): A Review of the In-Silico Screening Approaches to Identify AhR Modulators

Aryl hydrocarbon receptor (AhR) is a biological sensor that integrates environmental, metabolic, and endogenous signals to control complex cellular responses in physiological and pathophysiological functions. The full-length AhR encompasses various domains, including a bHLH, a PAS A, a PAS B, and transactivation domains. With the exception of the PAS B and transactivation domains, the available 3D structures of AhR revealed structural details of its subdomains interactions as well as its interaction with other protein partners. Towards screening for novel AhR modulators homology modeling was employed to develop AhR-PAS B domain models. These models were validated using molecular dynamics simulations and binding site identification methods. Furthermore, docking of well-known AhR ligands assisted in confirming these binding pockets and discovering critical residues to host these ligands. In this context, virtual screening utilizing both ligand-based and structure-based methods screened large databases of small molecules to identify novel AhR agonists or antagonists and suggest hits from these screens for validation in an experimental biological test. Recently, machine-learning algorithms are being explored as a tool to enhance the screening process of AhR modulators and to minimize the errors associated with structure-based methods. This chapter reviews all in silico screening that were focused on identifying AhR modulators and discusses future perspectives towards this goal.

SeamDock: An Interactive and Collaborative Online Docking Resource to Assist Small Compound Molecular Docking

In silico assessment of protein receptor interactions with small ligands is now part of the standard pipeline for drug discovery, and numerous tools and protocols have been developed for this purpose. With the SeamDock web server, we propose a new approach to facilitate access to small molecule docking for nonspecialists, including students. The SeamDock online service integrates different docking tools in a common framework that allows ligand global and/or local docking and a hierarchical approach combining the two for easy interaction site identification. This service does not require advanced computer knowledge, and it works without the installation of any programs with the exception of a common web browser. The use of the Seamless framework linking the RPBS calculation server to the user’s browser allows the user to navigate smoothly and interactively on the SeamDock web page. A major effort has been put into the 3D visualization of ligand, receptor, and docking poses and their interactions with the receptor. The advanced visualization features combined with the seamless library allow a user to share with an unlimited number of collaborators, a docking session, and its full visualization states. As a result, SeamDock can be seen as a free, simple, didactic, evolving online docking resource best suited for education and training.

Clinical trial site identification practices and the use of electronic health records in feasibility evaluations: An interview study in the Nordic countries

Introduction: Feasibility evaluations are performed to create the best possible starting point for the set-up and execution of a clinical trial, and to identify any obstacles for successful trial conduct. New digital technologies can provide various types of data for use in feasibility evaluations. There is a need to identify and compare such data sources for trial site identification and for evaluating the sites’ patient recruitment potential. Especially, information is needed on the use of electronic health records. We investigated how different data sources are used by pharmaceutical companies operating in the Nordic countries for identifying trial sites and for evaluating their potential to recruit trial participants. Methods: This was a semi-structured qualitative interview study with 21 participants from pharmaceutical companies and contract research organizations operating in Finland, Sweden, Denmark and Norway. Qualitative content analysis was applied. Results: For identifying countries and trial sites on a global level, the trial sponsors mostly used databases on previous trial performance. The use of electronic health record data was very limited. Sites’ and investigators’ visibility in various databases was seen as fundamental for their countries becoming selected into new clinical trials. For estimating the sites’ recruitment projections, most sites were seen to base their patient count estimates solely on their previous experience. Some sites had reviewed their electronic health record data, which was considered to increase the accuracy of their recruitment estimates and these sites’ attractivity. Along with dialogs with investigators, the sponsors used various data sources to validate the investigators’ estimates. Legislative obstacles were seen to hinder the use of electronic health record queries for estimation of patient counts. Conclusion: Visibility in the databases used by trial sponsors is crucial for the countries and sites to be identified. Site selection appears to be based on trust and relationships built from experience, but electronic data provide the support upon which the trust is based. Estimation of the number of potential trial participants is a complex and time-consuming process for both investigators and sponsors. Sponsors seem to favour sites who could support their patient count estimates with electronic health record data as they were quicker in providing the estimates and more reliable than sites with no electronic health record evidence. The patient count evaluation process could be simplified, accelerated and made more reliable with more systematic use of electronic health record evidence in the feasibility evaluation phase. This would increase the accuracy of the patient count estimates and, on its part, contribute to improved recruitment success.