Georeferencing was added to historic images, using street view data as a reference for those not already georeferenced. All historical images, complete with their camera positioning and directional data, have been integrated into the GIS database system. On a map, each compilation is depicted as an arrow that emanates from the camera's position and travels along the camera's line of sight. By means of a specialized software tool, a correlation was established between contemporary and historical imagery. Historical imagery sometimes permits only a substandard re-photograph. Historical images, along with all other original pictures, are continually being incorporated into the database, furnishing valuable data for enhancing rephotography methods in years to come. Image pairs resulting from the process are applicable to the fields of image alignment, changes in the landscape, urban development studies, and cultural heritage research. Beyond its core purpose, the database is instrumental for public engagement in heritage and can be employed as a benchmark for subsequent rephotographic projects and time-based research.

This data brief provides an overview of leachate management and disposal strategies at 43 active or closed municipal solid waste (MSW) landfills in Ohio, USA, including the planar surface area measurements for 40 of these. The Ohio Environmental Protection Agency (Ohio EPA)'s publicly available annual operational reports were the source of data that was extracted and compiled into a digital dataset of two delimited text files. Data points regarding monthly leachate disposal totals, sorted by management type and landfill, reach a count of 9985. While leachate management data for some landfills covers the years 1988 to 2020, the majority of records are restricted to the span from 2010 to 2020. Annual planar surface areas were derived from the topographic maps included in the yearly reports. Sixty-one hundred data points were generated for the annual surface area dataset. This dataset collects and categorizes the data, facilitating access and boosting its application across engineering analysis and research projects.

This paper details the reconstructed dataset and methods for predicting air quality, encompassing time-dependent air quality, meteorological, and traffic data, and including specifics about the monitoring stations and their associated measurement points. Given the various sites of monitoring stations and measurement points, the integration of their time-series data into a spatiotemporal dimension is paramount. The output, specifically the reconstructed dataset, served as input for a variety of predictive analyses, including applications in grid-based (Convolutional Long Short-Term Memory and Bidirectional Convolutional Long Short-Term Memory) and graph-based (Attention Temporal Graph Convolutional Network) machine learning algorithms. The unprocessed data originates from the Open Data portal of the Madrid City Council.

How the human brain processes and represents different auditory categories through learning is a fundamental question in auditory neuroscience. Addressing this question might allow us to gain a deeper understanding of how our brains process and learn speech, a crucial aspect of the neurobiology of speech learning and perception. Despite this, the neural processes involved in auditory category learning are not yet fully elucidated. During category training, we discovered the development of neural representations for auditory categories, and the structure of the auditory categories significantly dictates the arising dynamics of the representations [1]. Drawn from [1], this dataset was compiled to study the neural processes involved in learning two distinct categorizations: rule-based (RB) and information-integration (II). Participants underwent training in categorizing these auditory categories, receiving corrective feedback after each trial. The neural activity related to category learning was measured using the functional magnetic resonance imaging (fMRI) technique. Idasanutlin In order to conduct the fMRI experiment, sixty adult native Mandarin speakers were recruited. The subjects were separated into two learning categories, RB (n = 30, 19 female participants) and II (n = 30, 22 female participants). For each task, there were six training blocks, each containing 40 trials. Neural representations' development during learning has been examined by using multivariate representational similarity analysis with a focus on spatiotemporal aspects [1]. This open-access dataset could prove instrumental in exploring the neural mechanisms involved in auditory category learning, encompassing the examination of functional network organizations underpinning the learning of various category structures and the identification of neuromarkers associated with individual behavioral learning success.

To gauge the relative abundance of sea turtles, we undertook standardized transect surveys in the neritic waters of the Mississippi River delta in Louisiana, USA, over the summer and fall of 2013. The data gathered include sea turtle positions, observation conditions, and environmental factors documented at the start of each survey line and during the observation of each turtle. Turtles were identified and logged, specifying their species, size class, position in the water column, and their distance from the transect line. Transects were undertaken on an 82-meter vessel; two observers, located on a 45-meter elevated platform, ensured a consistent vessel speed of 15 km/hr. For the first time, these data quantify the relative abundance of sea turtles observed from small vessels operating within this specific area. Exceeding aerial survey data, the specifics of turtle detection, particularly for specimens under 45 cm SSCL, provide superior details. The data's purpose is to keep resource managers and researchers informed about these protected marine species.

This study investigates the correlation between CO2 solubility and temperature, considering various compositional attributes (protein, fat, moisture, sugar, and salt) across diverse food types, including dairy, fish, and meat. Resulting from a thorough meta-analysis of major papers published on the topic between 1980 and 2021, the composition of 81 food products is demonstrated, complete with 362 solubility measurements. Data on compositional parameters for each food was collected from either the original material or from open-source databases. For comparative analysis, the dataset was augmented with measurements from pure water and oil samples. For easier comparison between different data sources, the data have been semantically structured and organized using an ontology enhanced with specialized terms. Data is stored in a publicly accessible repository, offering access through the @Web tool, a user-friendly interface supporting capitalization and query operations.

Within the diverse coral ecosystems of Vietnam's Phu Quoc Islands, Acropora is a particularly abundant genus. The presence of marine snails, notably the coralllivorous gastropod Drupella rugosa, could potentially endanger the survival of many scleractinian species, thus causing modifications in the overall health and bacterial diversity of coral reefs in the Phu Quoc Islands. Illumina sequencing techniques are used to delineate and describe the makeup of bacterial communities, specifically those associated with the coral species Acropora formosa and Acropora millepora, in this study. Collected in May 2020 from Phu Quoc Islands (955'206N 10401'164E), this dataset includes 5 coral samples classified by their status, either grazed or healthy. Ten coral samples were found to contain 19 phyla, 34 classes, 98 orders, 216 families, and 364 bacterial genera in their entirety. Idasanutlin In all examined samples, Proteobacteria and Firmicutes were the two most prevalent bacterial phyla. The abundance of the genera Fusibacter, Halarcobacter, Malaciobacter, and Thalassotalea showed substantial differences when comparing grazing-stressed animals to those in a healthy state. Although there was no comparison in the alpha diversity indices between the two status, The dataset's investigation additionally identified Vibrio and Fusibacter as primary genera in the grazed sample groups, with Pseudomonas prominently featuring as the primary genus in the healthy samples.

This paper presents the datasets used to develop the Social Clean Energy Access (Social CEA) Index, which is comprehensively outlined in [1]. Social development data, focusing on electricity access and derived from a multitude of sources, is presented in this article. The data was processed using the methodology detailed in [1]. Across 35 Sub-Saharan African countries, a new composite index, composed of 24 indicators, evaluates the social standing of electricity access. Idasanutlin The literature review regarding electricity access and social development directly influenced the selection of indicators for the Social CEA Index, driving its development. Using correlational assessments and principal component analyses, the soundness of the structure was evaluated. The raw data facilitates stakeholders' focus on specific country indicators and how their respective scores influence a country's overall position in the ranking. The Social CEA Index helps to determine, from the 35 countries assessed, which perform best for each respective indicator. This enables various stakeholders to recognize the weakest facets of social development, consequently facilitating the prioritization of funding for specific electrification initiatives. Weights for stakeholders' specific requirements can be assigned based on the data. Ultimately, through a dimensional breakdown, the Ghana dataset enables the tracking of Social CEA Index progress over time.

A neritic marine organism, Mertensiothuria leucospilota, or bat puntil, is widespread in the Indo-Pacific, notable for its white threads. Within the intricate web of ecosystem services, they play a vital role, and it was determined that they contain numerous bioactive compounds with considerable medicinal benefits. Abundant as H. leucospilota may be within Malaysian marine environments, records of its mitochondrial genome from that region are presently insufficient. Herein, we describe the mitogenome of *H. leucospilota* originating from Sedili Kechil, Kota Tinggi, Johor, Malaysia. The Illumina NovaSEQ6000 sequencing system successfully sequenced the whole genome, and de novo methods assembled the resultant mitochondrial contigs.