The supporting data comprises preliminary crustal velocity models, the result of a joint inversion of the parameters associated with the hypocenters that were detected. This study was predicated on several parameters: a 6-layer model of crustal velocity (Vp and Vp/Vs ratio), analysis of earthquake incidence times, statistical assessment of recorded earthquakes, and relocation of their hypocentral data based on the updated crustal velocity model. The outcomes were illustrated in a 3D graphical display of the region's seismogenic depth. For earth science specialists, this dataset uniquely allows for the analysis and reprocessing of detected waveforms, leading to the characterization of seismogenic sources and active faults in Ghana. The Mendeley Data repository [1] now holds the metadata and waveforms.
Data within the dataset pertains to spectroscopically confirmed microplastic particles and fibers found in 44 surface water samples collected from the Baltic Sea's Gulf of Riga and the Eastern Gotland Basin. The Manta trawl, having a 300-meter mesh, was utilized for the collection of samples. Organic matter was subsequently processed with sodium hydroxide, hydrogen peroxide, and enzymes for digestion. Samples, after filtration through glass fiber filters, were visually examined to determine the characteristics of each item, including shape, size, and color. Where practical, the polymer type was determined with the help of the Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) spectroscopy method. The concentration of plastic particles, per cubic meter, within the filtered water, was established. Researchers studying microplastic pollution, meta-analyzing related data, and calculating microplastic flow could potentially benefit from the data presented in this article. The paper 'Occurrence and spatial distribution of microplastics in the surface waters of the Baltic Sea and the Gulf of Riga' discusses the interpretation and analysis of all the acquired data concerning micro debris and microplastics.
The subjective perception of a space by occupants is dependent on their previous interactions, as highlighted in [1], [2], and [3]. Four visitor experiences were undertaken within the University of Pisa's Natural History Museum [4]. Located inside the Monumental Charterhouse of Calci, close to Pisa, is the museum, encompassing the National Museum of the Charterhouse [5]. The historical survey encompassed four of the Museum's permanent exhibition halls, the Historical Gallery, Mammal's Hall, Ungulates' Gallery, and Cetaceans' Gallery. Four distinct groups of 117 participants were formed based on the type of visit experience: a real-life group, a group exposed to video recordings, a group exposed to photos, and a group exposed to computer-generated photorealistic images. Experiences are put through a rigorous process of comparison. Objective measurements of illuminance and subjective assessments of space perception, as captured by questionnaires, are included in the comparison. Illuminance measurements were performed with a Delta Ohm HD21022 photoradiometer datalogger, which incorporated an LP 471 PHOT probe. Mounted 120 meters above the floor, the probe was calibrated to record vertical illuminance readings at 10-second intervals. Questionnaires were employed to assess participants' perspectives on the spatial environment. The provided data originate from the study “Perception of light in museum environments: comparison between real-life and virtual visual experiences” [1]. This data set allows for a comprehensive evaluation of the potential of implementing virtual experiences within a museum setting, replacing real-life encounters, and assessing whether this substitution negatively or positively affects the visitor's perception of the museum's environment. Virtual experiences facilitate cultural transmission effectively, circumventing the limitations in mobility, such as those due to the SARS-CoV-2 pandemic.
Soil sampled from the grounds of Chiang Mai University in Chiang Mai, Thailand, contained a Gram-positive, spore-forming bacterium, specifically strain CMU008. The precipitation of calcium carbonate and the stimulation of sunflower sprout growth are outcomes of the activity of this strain. The Illumina MiSeq platform facilitated the completion of whole genome sequencing. The draft genome of strain CMU008 had a total length of 4,016,758 base pairs, and consisted of 4,220 protein-coding sequences with a G+C content of 46.01 percent. Comparative ANIb analysis of strain CMU008 and its closely related type strains, Bacillus velezensis NRRL B-41580T and B. velezensis KCTC13012T, indicated 9852% similarity. ML323 The construction of a phylogenomic tree supports the designation of strain CMU008 as a member of the species *B. velezensis*. Data from the genomic sequence of Bacillus velezensis strain CMU008 aids in the taxonomic characterization of this strain and opens doors for further research into its biotechnological uses. The Bacillus velezensis strain CMU008's draft genome sequence is now accessible through the DDBJ/EMBL/GenBank databases, its accession number is JAOSYX000000000.
Employing Classical Laminate Theory [1], the most reliable stress within the 90th layer of cross-ply laminates subjected to fatigue was calculated. This process involved measuring mechanical and thermal properties for a new TP402/T700S 12K/35% composite material, utilizing two distinct unidirectional tape prepregs – 30 g/m² and 150 g/m². Thermal property measurements of samples with orientations including 0 unidirectional (UD-0), 90 unidirectional (UD-90), 45, and 10 off-axis were carried out on specimens produced in an autoclave. An Instron 4482 and an oven were used for the tensile and thermal tests, respectively, with strain gauges employed in both instances. The collected data underwent analysis, adhering to established technical standards. Calculations encompassing the mechanical properties, specifically elastic and shear stiffness, strength, and coefficients of thermal expansion 1 and 2, were undertaken, and the associated statistical results were also determined.
Cefas, acting on behalf of the United Kingdom (consisting of England, Scotland, Wales, and Northern Ireland), and the Channel Islands (Jersey, Guernsey) and the Isle of Man, describes their annual data collection and analysis process in this paper. For each reporting year (January to December), the relevant regulatory authorities provide information on permits issued for dredged material disposal, including the amount of material disposed of at designated sites. The contaminant load at each disposal site is ascertained by analyzing the data. International treaties, such as the Convention for the Protection of the Marine Environment of the North-East Atlantic and the London Convention (London Protection), receive data analysis outputs to evaluate progress in reducing marine pollution, aligning with set objectives.
This article features three data sets, which scrutinize scientific literature published between 2009 and 2019, revealing the intersections of circular economy, bioenergy, education, and communication. All datasets were the product of a thorough, Systematic Literature Review (SLR) methodology. Twelve Boolean operators, each containing words linked to circular economy, bioenergy, communication, and education, were identified to facilitate the data collection process. By utilizing the Publish or Perish software, 36 database queries were made, encompassing Web of Science, Scopus, and Google Scholar. With the articles now in hand, the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) model and checklist were applied in the process. A manual filtering process was used to single out 74 articles, determined by their connection to the field. A detailed evaluation of the articles was executed through the DESLOCIS framework, emphasizing the aspects of design, data collection, and data analysis. Therefore, the primary data collection includes the details and measurements associated with the publications. The analytical approach is documented in detail within the second data set. ML323 The third stage entails a thorough analysis of the corpora used in the publication. Regarding circular economy and bioenergy, the data underscores opportunities for longitudinal studies and meta-reviews through an educational and communication framework.
By incorporating human bioenergetics into the study of the palaeobiology of our human ancestors during recent years, our grasp of human evolution has been broadened. Questions concerning the physiology of past humans frequently defy simple explanations derived solely from the fossil record's taxonomy and phylogenetic relationships. To comprehend the evolutionary limitations on hominin ecophysiology, data regarding the energetics and physiology of contemporary humans, along with in-depth investigations of body proportions and composition in connection to human metabolism, are essential. Besides this, particular datasets including the energetic metrics of present-day humans are imperative to modeling hominin paleophysiology. The National Research Centre on Human Evolution (CENIEH, Burgos, Spain) saw the gradual development of the EVOBREATH Datasets, beginning in 2013, a project aimed at storing and managing all data gathered by the Palaeophisiology and Human Ecology Group and the Palaeoecology of Mammals Group in their Research Programs on Experimental Energetics. Employing either the CENIEH BioEnergy and Motion Lab (LabBioEM) or mobile devices in the field, all experimental tests were developed. Experimental data from multiple studies involving 501 in vivo subjects across different age groups (adults, adolescents, and children) and genders contain quantitative measurements of human anthropometry (height, weight, postcranial dimensions, hand and foot measurements, anatomical indices), body composition (fat mass, lean mass, muscle mass, body water), and energetics (resting metabolic rate, energy expenditure during various physical activities, including breath-by-breath oxygen and carbon dioxide). ML323 Facilitating the reuse of experimental data within the scientific community is a critical function of these datasets, which also contribute to optimizing their time-consuming creation.