In this article, we introduce a data set concerning electric-power consumption-related features registered in seven main municipalities of Nariño, Colombia, from December 2010 to May 2016. The data set consists of 4427 socio-demographic characteristics, and 7 power-consumption-referred measured values. https://www.selleckchem.com/products/dc-ac50.html Data were fully collected by the company Centrales Eléctricas de Nariño (CEDENAR) according to the client consumption records. Power consumption data collection was carried following a manual procedure wherein company workers are in charge of manually registering the readings (measured in kWh) reported by the electric energy meters installed at each housing/building. Released data set is aimed at providing researchers a suitable input for designing and assessing the performance of forecasting, modelling, simulation and optimization approaches applied to electric power consumption prediction and characterization problems. The data set, so-named in shorthand PCSTCOL, is freely and publicly available at https//doi.org/10.17632/xbt7scz5ny.3. © 2020 The Authors.A standardised, single-centre, longitudinal imaging protocol was used to evaluate longitudinal brainstem alterations in 100 patients with amyotrophic lateral sclerosis (ALS) with reference to 33 patients with primary lateral sclerosis (PLS), 30 patients with frontotemporal dementia (FTD) and 100 healthy controls. "Brainstem pathology in amyotrophic lateral sclerosis and primary lateral sclerosis A longitudinal neuroimaging study" [1] ALS patients were scanned twice; 4 months apart. T1-weighted imaging data were acquired on a 3 T Philips Achieva MRI system, using a 3D Inversion Recovery prepared Spoiled Gradient Recalled echo (IR-SPGR) sequence. Raw MRI data underwent meticulous quality control before pre-processing. A Bayesian segmentation algorithm was utilised to parcellate the brainstem into the medulla oblongata, pons and mesencephalon before estimating the volume of each segment. Vertex-based shape analyses were carried out to characterise anatomical patterns of atrophy. Brainstem volume loss in ALS was dominated by medulla oblongata atrophy, but significant pontine pathology was also detected. Brainstem volume reductions were more significant in PLS than in ALS after correcting for demographic variables and total intracranial volume. Shape analyses revealed bilateral 'flattening' of the medullary pyramids in ALS compared to healthy controls. Our data demonstrate that computational neuroimaging readily detects brainstem pathology in vivo in both amyotrophic lateral sclerosis and primary lateral sclerosis. © 2020 The Authors.We obtained data regarding the metabolites from flowers, the skin pulp, green beans and peaberry green beans of the robusta coffee plant (Coffea canephora). The beans were processed using a wet-hulled method. The volatile compounds from the flowers were extracted using a solid-phase microextraction. Secondary metabolites from the skin pulp, green beans, and peaberry green beans were extracted by a maceration method using methanol as a solvent. The separation and identification of metabolites were conducted using gas chromatography-mass spectrometry. The flower's volatile compounds were identified by matching the generated spectra with the NIST14 library as a reference, whereas the metabolites in the skin pulp, green beans, and peaberry green beans were identified using the WILLEY09TH library as a reference. The identified volatile compounds in flowers have been listed in Table 1, and the identified skin pulp, green bean, and peaberry green bean metabolite compounds have been listed in Table 2. © 2020 The Authors.This dataset includes data obtained at the Atmospheric Microphysics and Radiation Laboratory (LAMAR) of the Huancayo Observatory (12.04° S, 75.32° W, 3313 m ASL). Two Parsivel2 and two tipping bucket rain gauges are used in this dataset which are operating together since 2018. Data is given in NetCDF format, including two types of files, one NetCDF for precipitation totals and another which contains Parsivel2 data. This data set was collected in the complex topography conditions of the tropical Andes, and its potential use is to study the microphysics of orographic rainfall, atmospheric models and rainfall estimation algorithms. © 2020 Geophysical Institute of Peru.This paper presents dataset collected from social networks that are mostly used by youth of Commonwealth of Independent States (CIS) countries. The data was collected from public accounts of VKontakte social network by using VK.api and applying the most used keywords that would signify depressive mood. The collected data was classified by psychologists into two types depressive and non-depressive. The dataset consists of 32 018 depressive posts and 32 021 non-depressive posts. Since the most common language that is spoken in CIS countries is Russian, the posts are written in Russian, consequently the collected data is in Russian language as well. The data can mostly be useful for researchers who explore tendencies to depression in CIS countries. The dataset is important for the research community, as it was not only collected from open sources, but also marked by our psychiatrists from the republican scientific and practical center of mental health. Since the dataset has very high validity, it can be used for further research in the field of mental health. © 2020 The Author(s).This article contains the data set and model code for the negative emission polygeneration system described in Tan et al. (2019). The data was generated utilizing an optimization model implemented in LINGO 18.0 and includes information on the operating state of each process unit in the system. The maximum annual profit of the system was determined at different carbon footprint targets. The data set and model code can be utilized for further analysis on the interdependence between the process units of this polygeneration system, its operational and environmental performance, and the potential impact of integrating new process units into the network. © 2020 The Author(s).Objective To analyze and evaluate the diagnostic performance of conventional diagnostic (qualitative) imaging features versus LI-RADSv2018 lexicon for indeterminate and atypical Hepatocellular carcinoma (HCC) on dynamic liver imaging with reference to histopathology. Patients and methods This retrospective study (June 2009-June 2019) evaluated the performance characteristics of conventional imaging findings, versus the Liver Imaging Reporting and Data System (LIRADS) v2018, for interpretation of indeterminate and atypical HCC, in patients who underwent subsequent histopathological analysis (gold standard). A total of 100,457 dynamic hepatobiliary CT and MR examinations were performed over ten years at our institute. Using current international imaging guidelines, 3218 patients were found to have suspected liver cancer lesions on imaging. Classical enhancement pattern of typical HCC was seen in 2916 of these patients. These patients did not require further biopsy. We enrolled, the remaining (n = 302) patients, who underwent biopsy, into our study group.