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  • my first dataset in 2020
    Data Types:
    • Dataset
    • Document
  • Supplemental Figure 1. Molecular features of the present patient Supplemental Figure 2. Sites of the mutations in the domain structure of AP1B1
    Data Types:
    • Image
    • Dataset
    • Document
  • Clinical pictures of seven cases of SJS/TEN-like AGEP with widespread desquamation
    Data Types:
    • Dataset
    • Document
  • Explosive volcanic eruptions are severe natural phenomena that produce pyroclastic materials, eruption columns, and volcanic ash clouds. During moist weather conditions, volcanic eruption products can be coated with water, resulting in wet ash and/or mixtures of ash and rain. Wet ash, which is heavier than dry ash increases the risk of towers and poles collapsing, and rain mixed with volcanic ash is a harmful natural phenomenon that threatens human life, infrastructures, economies, agriculture, etc. Optical measurements, which are made with ground-based instruments (ex, two-dimensional video disdrometer (2DVD), parsivel, etc.), cameras, and satellites, are limited in their ability to detect volcanic ash clouds and eruption columns in cloudy or precipitation conditions. Weather radar is one of the key instruments for studying and monitoring both precipitation and volcanic ash clouds, since it can observe both types of system and can provide valuable information that can discriminate between the two systems through the use of polarimetric parameters. In this paper, our goal is to find characteristic of polarimetric parameters for volcanic ash clouds and precipitation using observed radar data, and to make a classification algorithm for discriminating two systems.
    Data Types:
    • Dataset
    • Document
  • This database contains facial images of volunteers in frontal and random poses. Each facial image collection has a visible light image, an infrared image and a depth image. Version 02 The images in this database version were collected by a single person during the period of December 17 2018 to 01 July of the year 2019 at Univali University. This dataset was created with the approval of CEP (Research Ethics Committee) from University of Itajaí Valley - Brazil with CAAE (Certificate of Presentation of Ethical Appreciation) number: 97615018.9.0000.012. The V2 database contains: 80 volunteers 1600 facial image samples (approximately) a frontal image (VIS, IR, DEPTH) by volunteer an image (VIS, IR, DEPTH) with a face turned to the right by a volunteer an image (VIS, IR, DEPTH) with a face turned to the left by a volunteer an image (VIS, IR, DEPTH) with a face turned up by a volunteer an image (VIS, IR, DEPTH) with a face turned down by a volunteer an image (VIS, IR, DEPTH) with random pose by volunteer Version 01 The images in this database version were collected by a single person during the period of October 10 to 27 of the year 2017. 8 classes in the computer science course at UNIVALI University were invited to participate in this paper, where 64 accepted to participate in this work. The V1 database contains: 64 volunteers 267 facial image samples 267 facial images of the visible light spectrum 267 facial images of the infrared spectrum (corrupted) 267 depth images (3D)
    Data Types:
    • Other
    • Software/Code
    • Image
    • Tabular Data
    • Dataset
  • Linear regression analysis was used to investigate the relationship among the variables. The results showed that academic stress was positively related to psychological distress, which may further lead to severe smartphone dependence. Psychological distress partially mediated the relationship between academic stress and smartphone dependence. The mediating effect of psychological distress between academic stress and smartphone dependence was moderated by academic resilience. Specifically, academic resilience weakened the indirect relationship between academic stress and smartphone dependence that was mediated by psychological distress.
    Data Types:
    • Software/Code
    • Dataset
  • Explosive volcanic eruptions are severe natural phenomena that produce pyroclastic materials, eruption columns, and volcanic ash clouds. During moist weather conditions, volcanic eruption products can be coated with water, resulting in wet ash and/or mixtures of ash and rain. Wet ash, which is heavier than dry ash increases the risk of towers and poles collapsing, and rain mixed with volcanic ash is a harmful natural phenomenon that threatens human life, infrastructures, economies, agriculture, etc. Optical measurements, which are made with ground-based instruments (ex, two-dimensional video disdrometer (2DVD), parsivel, etc.), cameras, and satellites, are limited in their ability to detect volcanic ash clouds and eruption columns in cloudy or precipitation conditions. Weather radar is one of the key instruments for studying and monitoring both precipitation and volcanic ash clouds, since it can observe both types of system and can provide valuable information that can discriminate between the two systems through the use of polarimetric parameters. In this paper, our goal is to find characteristic of polarimetric parameters for volcanic ash clouds and precipitation using observed radar data, and to make a classification algorithm for discriminating two systems.
    Data Types:
    • Dataset
    • Document
  • Dataset for "A systematic review of neurogenesis in animals models of early brain damage: implications for cerebral palsy". The dataset includes the systematic review protocol (PROSPERO), the search strategy used in each database, the reference list of 2329 articles found in databases, the exclusion reasons of "title and abstract screening phase" and "full-text screening phase", the reference list of included studies and the piloted form used for data extraction in the included studies
    Data Types:
    • Tabular Data
    • Dataset
    • Document
  • This paper disserts a video on YouTube of a toy tractor and badly loaded trailer. It presents the existence of a "timebomb" zone where terminal and mostly irrecoverable fishtailing occurs.
    Data Types:
    • Dataset
    • Document
  • This data set captures the problems faced by electricity customers in Delta, State Nigeria. The data was collected by means of a well structured questionnaire that was implemented by well trained interviewers in a field survey. Nigeria is currently bedeviled by a plethora of problems especially in the distribution aspect of the power sector. The data set captures data in both urban and rural areas of Delta State cutting across the three Senatorial Districts. Local Government Headquarters were designated as urban areas whiles villages were taken as rural areas. The data contains information on customers biodata and their experiences with the services of their electricity distribution company. The data set also contains information about the observed problems with the services of the distribution company, Respondents in the survey were asked to score positive statements bordering on their experience with the distribution company on a five-point scale indicating their experience with the distribution company. Respondents were also required to score observed problems with the services of the distribution company on a scare of 0 to 10 inclusive depending on the severity of the problem. A score of zero meaning that the problems in limited while a score of 10 means that the problem is severe, The data set are presented in two different formats i.e. Microsoft Excel and IBM SPSS database format.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset