cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23622644.v1
title: Comparative analysis of orbital sensors in soybean yield estimation by the random forest algorithm

description: ABSTRACT Remote sensing has proven to be a promising tool allowing crop monitoring over large geographic areas. In addition, when combined with machine learning methods, the algorithms can be used for estimating crop yield. This study sought to estimate soybean yield through the enhanced vegetation index and normalized difference vegetation index. These vegetation indices were obtained using moderate-resolution imaging spectro-radiometer (MODIS) sensors on AQUA and TERRA satellites and multispectral instrument (MSI) sensor on Sentinel-2 satellite. Random forest (RF) algorithm was used to predict soybean yield and the estimation models were compared with the actual plot’s yield. The RF algorithm showed good performance to estimate soybean yield with our models (R2 = 0.60 and RMSE = 0.50 for MSI; R² = 0.63 and RMSE = 0.59 for MODIS). Vegetation indices with imaging dates corresponding to the crop’s maturation had a higher degree of importance in its predictive ability. However, when comparing the actual and predicted soybean production values, differences of 145 kg ha-1 in contrast to 4 kg ha-1 were found for the MODIS and MSI models, respectively. Therefore, the MSI sensor integrated with machine learning algorithms accurately estimated crop yields.
DOI: 10.6084/m9.figshare.23622644
title: Comparative analysis of orbital sensors in soybean yield estimation by the random forest algorithm

description: ABSTRACT Remote sensing has proven to be a promising tool allowing crop monitoring over large geographic areas. In addition, when combined with machine learning methods, the algorithms can be used for estimating crop yield. This study sought to estimate soybean yield through the enhanced vegetation index and normalized difference vegetation index. These vegetation indices were obtained using moderate-resolution imaging spectro-radiometer (MODIS) sensors on AQUA and TERRA satellites and multispectral instrument (MSI) sensor on Sentinel-2 satellite. Random forest (RF) algorithm was used to predict soybean yield and the estimation models were compared with the actual plot’s yield. The RF algorithm showed good performance to estimate soybean yield with our models (R2 = 0.60 and RMSE = 0.50 for MSI; R² = 0.63 and RMSE = 0.59 for MODIS). Vegetation indices with imaging dates corresponding to the crop’s maturation had a higher degree of importance in its predictive ability. However, when comparing the actual and predicted soybean production values, differences of 145 kg ha-1 in contrast to 4 kg ha-1 were found for the MODIS and MSI models, respectively. Therefore, the MSI sensor integrated with machine learning algorithms accurately estimated crop yields.
DOI: 10.6084/m9.figshare.19602262.v1
title: Selective scandium ion capture <i>through</i> coordination templating in a covalent organic framework

description: Raw datas
DOI: 10.6084/m9.figshare.19602262
title: Selective scandium ion capture <i>through</i> coordination templating in a covalent organic framework

description: Raw datas
DOI: 10.6084/m9.figshare.22580899.v1
title: Cryo-EM structure of GABA transporter 1 reveals substrate recognition and transport mechanism

description: The uploaded data comprises individual Source data for the following figures. Main figure 1 Extended Data Figure 1 Extended Data Figure 2 Extended Data Figure 3 Extended Data Figure 4 Extended Data Figure 7 Extended Data Figure 9
DOI: 10.6084/m9.figshare.22580899
title: Cryo-EM structure of GABA transporter 1 reveals substrate recognition and transport mechanism

description: The uploaded data comprises individual Source data for the following figures. Main figure 1 Extended Data Figure 1 Extended Data Figure 2 Extended Data Figure 3 Extended Data Figure 4 Extended Data Figure 7 Extended Data Figure 9
DOI: 10.6084/m9.figshare.23622647
title: Computer vision by unsupervised machine learning in seed drying process

description: ABSTRACT Analyzing the impact of harvest-time drying data is crucial for successful storage and maintaining regulatory seed quality. This study aimed to assess the performance of fixed and mobile dryers using machine learning techniques. Data were collected from convective dryers, including the total number of dryers used, drying time (in hours), moisture percentages at the product’s entrance and exit, and the humidity difference between them. The study employed the Filtered Clusterer model, which utilizes the Simple K-Means technique and the Resample filter to group data based on similarities. The findings indicated distinct differences between fixed and mobile drying systems, with well-defined variations within each system. The algorithm, combined with the applied filters, proved effective in unsupervised classification by identifying and reducing inter-cluster similarity within the fixed system, thereby creating distinct classes within the dataset. In conclusion, the algorithm successfully clustered the scattered dataset and accurately classified and minimized inter-cluster similarity within the fixed system. Conversely, the mobile system exhibited low drying efficiency.
DOI: 10.6084/m9.figshare.23622647.v1
title: Computer vision by unsupervised machine learning in seed drying process

description: ABSTRACT Analyzing the impact of harvest-time drying data is crucial for successful storage and maintaining regulatory seed quality. This study aimed to assess the performance of fixed and mobile dryers using machine learning techniques. Data were collected from convective dryers, including the total number of dryers used, drying time (in hours), moisture percentages at the product’s entrance and exit, and the humidity difference between them. The study employed the Filtered Clusterer model, which utilizes the Simple K-Means technique and the Resample filter to group data based on similarities. The findings indicated distinct differences between fixed and mobile drying systems, with well-defined variations within each system. The algorithm, combined with the applied filters, proved effective in unsupervised classification by identifying and reducing inter-cluster similarity within the fixed system, thereby creating distinct classes within the dataset. In conclusion, the algorithm successfully clustered the scattered dataset and accurately classified and minimized inter-cluster similarity within the fixed system. Conversely, the mobile system exhibited low drying efficiency.
DOI: 10.6084/m9.figshare.23622646
title: COMMAS IN TEXTS OF STUDENTS FROM AGE 11 TO 15-YEARS-OLD: A LONGITUDINAL STUDY

description: ABSTRACT In this article, we investigate the presence and the absence of commas in a longitudinal sample of texts of the genre report written by 11 to 15 years-old students from a school in the countryside of São Paulo State. Our hypothesis is that the comma is used when syntactic boundaries match the prosodic ones. The prosodic constituents are formed from syntactic and phonological information, according to principles defined in the Prosodic Phonology theoretical approach. The characterization of the conventional commas and the non-conventional absences of commas was made from the identification of syntactic boundaries in which they should or could be placed, taking as reference a Brazilian Portuguese grammar. The results were that the conventional comma increases during the years of schooling, as expected. However, the presence and absence of comma rates changed depending on the type of syntactic structure and on the occurrence of intonational phrase boundaries. Comma occurred predominantly in positions where intonation phrase boundaries match major syntactic boundaries, as a sentence boundary. In turn, the comma systematically does not occur in positions where the syntactic and prosodic boundaries do not match.
DOI: 10.6084/m9.figshare.23622646.v1
title: COMMAS IN TEXTS OF STUDENTS FROM AGE 11 TO 15-YEARS-OLD: A LONGITUDINAL STUDY

description: ABSTRACT In this article, we investigate the presence and the absence of commas in a longitudinal sample of texts of the genre report written by 11 to 15 years-old students from a school in the countryside of São Paulo State. Our hypothesis is that the comma is used when syntactic boundaries match the prosodic ones. The prosodic constituents are formed from syntactic and phonological information, according to principles defined in the Prosodic Phonology theoretical approach. The characterization of the conventional commas and the non-conventional absences of commas was made from the identification of syntactic boundaries in which they should or could be placed, taking as reference a Brazilian Portuguese grammar. The results were that the conventional comma increases during the years of schooling, as expected. However, the presence and absence of comma rates changed depending on the type of syntactic structure and on the occurrence of intonational phrase boundaries. Comma occurred predominantly in positions where intonation phrase boundaries match major syntactic boundaries, as a sentence boundary. In turn, the comma systematically does not occur in positions where the syntactic and prosodic boundaries do not match.
DOI: 10.6084/m9.figshare.23622650
title: Spectral temporal graph neural network for multivariate agricultural price forecasting

description: ABSTRACT: Multivariate time series forecasting has an important role in many real-world domains. Especially, price prediction has always been on the focus of researchers. Yet, it is a challenging task that requires the capturing of intra-series and inter-series correlations. Most of the models in literature focus only on the correlation in temporal domain. In this paper, we have curated a new dataset from the official website of Turkish Ministry of Commerce. The dataset consists of daily prices and trade volume of vegetables and covers 1791 days between January 1, 2018 and November 26, 2022. A Spectral Temporal Graph Neural Network (StemGNN) is employed on the curated dataset and the results are given in comparison to Convolutional neural networks (CNN), Long short-term memory (LSTM) and Random Forest models. GNN architecture achieved a state-of-the-art result such as mean absolute error (MAE): 1,37 and root mean squared error (RMSE): 1.94). To our knowledge, this is one of the few studies that investigates GNN for time series analysis and the first study in architecture field.
DOI: 10.6084/m9.figshare.23622650.v1
title: Spectral temporal graph neural network for multivariate agricultural price forecasting

description: ABSTRACT: Multivariate time series forecasting has an important role in many real-world domains. Especially, price prediction has always been on the focus of researchers. Yet, it is a challenging task that requires the capturing of intra-series and inter-series correlations. Most of the models in literature focus only on the correlation in temporal domain. In this paper, we have curated a new dataset from the official website of Turkish Ministry of Commerce. The dataset consists of daily prices and trade volume of vegetables and covers 1791 days between January 1, 2018 and November 26, 2022. A Spectral Temporal Graph Neural Network (StemGNN) is employed on the curated dataset and the results are given in comparison to Convolutional neural networks (CNN), Long short-term memory (LSTM) and Random Forest models. GNN architecture achieved a state-of-the-art result such as mean absolute error (MAE): 1,37 and root mean squared error (RMSE): 1.94). To our knowledge, this is one of the few studies that investigates GNN for time series analysis and the first study in architecture field.
DOI: 10.6084/m9.figshare.23622652
title: Development and evaluation of content of the mobile app Cinesia for patients with unilateral motor deficits after stroke

description: Abstract Introduction The incidence of stroke in adults has increased in recent years, and individuals who survive often have one or more motor and cognitive deficits. In Brazil, the Unified Health System (SUS) faces difficulties in reabsorbing the entire population that needs physiotherapy after hospital discharge. In addition, the distance to rehabilitation units in Rio de Janeiro can be far, making it impossible for some patients to receive the treatment they need. Objective To create a complementary mobile application for adults with unilateral motor deficits and to evaluate its content through expert judges. Methods Applied research for the construction of a mobile app with the prototyping method by Pressman. Steps: 1) literature review; 2) development of the technological framework; 3) construction of the content; and 4) construction of a prototype. The app content was evaluated using the e-Delphi Method for peer review using a Likert-type questionnaire on the Google Forms platform. Results The application was developed and designed to run on the Android operating system. Three rounds were carried out to evaluate the app's content. The final average of the content validity index (CVI) of all content items was 0.85, reaching the minimum agreement of 0.80, suggested by authors. Conclusion The content of a mobile app for adults with unilateral post-stroke motor deficits was developed and approved, and its content was evaluated by expert judges. We believe that this app can contribute to the promotion of physical rehabilitation in people with unilateral motor deficits after hospital discharge.
DOI: 10.6084/m9.figshare.23622652.v1
title: Development and evaluation of content of the mobile app Cinesia for patients with unilateral motor deficits after stroke

description: Abstract Introduction The incidence of stroke in adults has increased in recent years, and individuals who survive often have one or more motor and cognitive deficits. In Brazil, the Unified Health System (SUS) faces difficulties in reabsorbing the entire population that needs physiotherapy after hospital discharge. In addition, the distance to rehabilitation units in Rio de Janeiro can be far, making it impossible for some patients to receive the treatment they need. Objective To create a complementary mobile application for adults with unilateral motor deficits and to evaluate its content through expert judges. Methods Applied research for the construction of a mobile app with the prototyping method by Pressman. Steps: 1) literature review; 2) development of the technological framework; 3) construction of the content; and 4) construction of a prototype. The app content was evaluated using the e-Delphi Method for peer review using a Likert-type questionnaire on the Google Forms platform. Results The application was developed and designed to run on the Android operating system. Three rounds were carried out to evaluate the app's content. The final average of the content validity index (CVI) of all content items was 0.85, reaching the minimum agreement of 0.80, suggested by authors. Conclusion The content of a mobile app for adults with unilateral post-stroke motor deficits was developed and approved, and its content was evaluated by expert judges. We believe that this app can contribute to the promotion of physical rehabilitation in people with unilateral motor deficits after hospital discharge.
DOI: 10.5281/zenodo.6420886
title: WEEE, A Multi-Device and Multi-Modal Dataset for Wearable Human Energy Expenditure Estimation

description: We present WEEE, a multi-device and multi-modal dataset collected from 17 participants under different physical activities.<br> WEEE contains: 1) sensor data collected using 7 wearable devices placed on 4 body locations - head, ear, chest, and wrist<br> -, 2) respiratory data collected with an indirect calorimeter serving as ground-truth information, 3) demographics and body<br> composition data (e.g., muscle or fat percentage), 4) activity type - and their corresponding metabolic equivalent of task (MET) values - and intensity level, and 5) answers to questionnaires related to physical activity level, diet, stress and sleep. Thanks to the diversity of sensors and body locations of the WEEE dataset, we envision that this dataset will enable the development of novel human energy expenditure estimation techniques for a diverse set of application scenarios. Energy expenditure (EE) refers to the amount of energy an individual uses to maintain body functions and as a result of physical activity. The ability to estimate EE allows computing systems obtaining valuable insights regarding people’s physical activity and providing personalized recommendations for promoting a healthier and more active lifestyle.
DOI: 10.5281/zenodo.6420884
title: WEEE, A Multi-Device and Multi-Modal Dataset for Wearable Human Energy Expenditure Estimation

description: We present WEEE, a multi-device and multi-modal dataset collected from 17 participants under different physical activities.<br> WEEE contains: 1) sensor data collected using 7 wearable devices placed on 4 body locations - head, ear, chest, and wrist<br> -, 2) respiratory data collected with an indirect calorimeter serving as ground-truth information, 3) demographics and body<br> composition data (e.g., muscle or fat percentage), 4) activity type - and their corresponding metabolic equivalent of task (MET) values - and intensity level, and 5) answers to questionnaires related to physical activity level, diet, stress and sleep. Thanks to the diversity of sensors and body locations of the WEEE dataset, we envision that this dataset will enable the development of novel human energy expenditure estimation techniques for a diverse set of application scenarios. Energy expenditure (EE) refers to the amount of energy an individual uses to maintain body functions and as a result of physical activity. The ability to estimate EE allows computing systems obtaining valuable insights regarding people’s physical activity and providing personalized recommendations for promoting a healthier and more active lifestyle.
DOI: 10.6084/m9.figshare.23003246.v1
title: Recurrent photic zone euxinia limited ocean oxygenation and animal evolution during the Ediacaran

description: Includes Table S1, S2 and S3. Table S1 is mercury isotope compositions of reference materials and standards. Table S2 is mercury isotope compositions of all samples in this study, including four black shale sections of the Doushantuo Formation at South China (Wuhe, Taoyin, Yuanjia, Weng'an). Table S3 includes raw and normalized Hg concentrations (Hg/TOC, Hg/S, Hg/Al, Hg/Fe). TOC, Spyrite, Al and total Fe data are from Sahoo et al. 2016.
DOI: 10.6084/m9.figshare.23003246
title: Recurrent photic zone euxinia limited ocean oxygenation and animal evolution during the Ediacaran

description: Includes Table S1, S2 and S3. Table S1 is mercury isotope compositions of reference materials and standards. Table S2 is mercury isotope compositions of all samples in this study, including four black shale sections of the Doushantuo Formation at South China (Wuhe, Taoyin, Yuanjia, Weng'an). Table S3 includes raw and normalized Hg concentrations (Hg/TOC, Hg/S, Hg/Al, Hg/Fe). TOC, Spyrite, Al and total Fe data are from Sahoo et al. 2016.
DOI: 10.6084/m9.figshare.23622655
title: Use of a one-step freezing protocol for boar sperm with distinct cryoprotectants

description: ABSTRACT: The present study evaluated the cryoprotectant efficacy of dimethylacetamide (DMA) and ethylene glycol in a one-step protocol to freeze boar sperm. The sperm-rich portion of the ejaculates from two boars were collected once a week, for 10 weeks. After collection, the ejaculates were diluted (1:1; v/v) in the cooling extender. After determining their spermatozoa concentration, the ejaculates were pooled with the same number of spermatozoa from each boar and stabilized at 20°C for 120 min. Distinct cryoprotectants were added to the cooling extender at 20 °C, at different concentrations, composing six treatments: 1.25% and 2.5% glycerol (control); 1.25% and 2.5% ethylene glycol; 2.5% and 5.0% DMA. The samples were stored in 0.25 mL straws, containing 35 × 106 spermatozoa. After 90 min at 20 °C, the straws were submitted to a cooling curve until 5 °C (0.3 to 0.5 °C/min) and kept at 5°C for 60 min. Freezing was conducted by placing the straws horizontally 5 cm above the liquid nitrogen for 10 min, followed by immersion on liquid nitrogen. After thawing at 37 °C for 30 seconds, sperm quality was evaluated through a computer-assisted semen analysis system and flow cytometry. Sperm motility was greater (P&lt; 0.05) in treatments with 5.0% and 2.5% DMA (22.2 ± 2.6% and 20.0 ± 2.8%, respectively) than in treatment with 2.5% ethylene glycol (8.2 ± 1.0%). The integrity of the plasma membrane (P = 0.08) and mitochondrial membrane potential (P = 0.27) was similar among the treatments. The treatment with 2.5% ethylene glycol was the least efficient to maintain intact acrosome membrane (P&lt; 0.01). Some kinetics parameters (DAP, DCL, DSL, VAP, VCL, VSL e ALH) were positively affected by 5.0% DMA. The one-step freezing protocol resulted in unsatisfactory boar sperm motility after thawing, regardless of the cryoprotectant.
DOI: 10.6084/m9.figshare.23622655.v1
title: Use of a one-step freezing protocol for boar sperm with distinct cryoprotectants

description: ABSTRACT: The present study evaluated the cryoprotectant efficacy of dimethylacetamide (DMA) and ethylene glycol in a one-step protocol to freeze boar sperm. The sperm-rich portion of the ejaculates from two boars were collected once a week, for 10 weeks. After collection, the ejaculates were diluted (1:1; v/v) in the cooling extender. After determining their spermatozoa concentration, the ejaculates were pooled with the same number of spermatozoa from each boar and stabilized at 20°C for 120 min. Distinct cryoprotectants were added to the cooling extender at 20 °C, at different concentrations, composing six treatments: 1.25% and 2.5% glycerol (control); 1.25% and 2.5% ethylene glycol; 2.5% and 5.0% DMA. The samples were stored in 0.25 mL straws, containing 35 × 106 spermatozoa. After 90 min at 20 °C, the straws were submitted to a cooling curve until 5 °C (0.3 to 0.5 °C/min) and kept at 5°C for 60 min. Freezing was conducted by placing the straws horizontally 5 cm above the liquid nitrogen for 10 min, followed by immersion on liquid nitrogen. After thawing at 37 °C for 30 seconds, sperm quality was evaluated through a computer-assisted semen analysis system and flow cytometry. Sperm motility was greater (P&lt; 0.05) in treatments with 5.0% and 2.5% DMA (22.2 ± 2.6% and 20.0 ± 2.8%, respectively) than in treatment with 2.5% ethylene glycol (8.2 ± 1.0%). The integrity of the plasma membrane (P = 0.08) and mitochondrial membrane potential (P = 0.27) was similar among the treatments. The treatment with 2.5% ethylene glycol was the least efficient to maintain intact acrosome membrane (P&lt; 0.01). Some kinetics parameters (DAP, DCL, DSL, VAP, VCL, VSL e ALH) were positively affected by 5.0% DMA. The one-step freezing protocol resulted in unsatisfactory boar sperm motility after thawing, regardless of the cryoprotectant.
DOI: 10.6084/m9.figshare.23622659
title: Before the Performance: contributions of speculative pragmatism to the sociology of art

description: Abstract: The aim of this paper is to analyze the main aspects that constitute the performance experience, as well as to examine the contributions of speculative-pragmatism to the renewal of the field of sociology of art. The text is structured in three parts: 1) a contextualization of the work within the scope of the research project Protocols for the Musealization of Performative Actions in Public Art Museums and its problematic from the sociological point of view; 2) a definition of the concept of experience; 3) verification of the analytical yield of this concept for research in performance arts. As a main conclusion, the text sought to systematize the ways in which pragmatic-speculative sociology may provide access to the complex networks of actors and social practices involved in contemporary artistic production.