cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/gc9fcwtjvn.1
title: Mining leachate contamination and subfecundity among women living near the United States-Mexico border

description: Design and sample 
We conducted a retrospective cohort study on pregnancy cases of women living across the watershed area of the Sonora River, in those municipalities directly affected by the environmental disaster: Arizpe, Banámichi, Huépac, San Felipe de Jesús, Aconchi, Baviácora, Ures, and some villages belonging to the state capital Hermosillo (Molino de Camou, Topahue, San Francisco de Batuc, El Tronconal and San Pedro El Saucito)  (Lammers., 2014).  In addition, we included Magdalena de Kino as a non-exposed community, whose water supply source is different from the resting municipalities, but shares common climate and ecological characteristics (Figure 1). 
Participants were first identified by the local health centers and then visited at home, where they were asked to participate before signing the informed consent.  Inclusion criteria were women being older than 18 years, planned pregnancy, conception of pregnancy in municipalities considered as exposed and non-exposed in this study after the disaster or before up to 10 years prior, with the possibility of including more than one pregnancy for each participant. Among the criteria for exclusion were having a physical or mental disability to adequately respond the questionnaire or refused to sign the consent. The study sample size had enough statistical power according to the Freedman table (Freedman., 1982), taking into account that previous studies exploring fecundity and metal exposure worked with samples between 41 and 300 pregnancies (Snijders., 2012). The study was approved by either ethical review board of the University of Sonora, Mexico, and the Industrial University of Santander, Colombia.  
Statistical methods
Univariate and bivariate descriptive analysis were made after completing the database, using chi-square, Student’s t, and Mann-Whitney U to test for differences between variables.  Fecundability odds ratios (fOR) obtained from discrete time analogue of Cox’s proportional hazard models were used to estimate associations with logistic regression models using the macro dthaz  (Dinno., 2011).  For multiple analysis, variables included in the model had p<0.25 in the bivariate Wald-test or had effect changes > 20%. Models were adjusted for age at pregnancy, age at first pregnancy, pregnancy order, maternal occupation, father’s occupation, father’s age, and father history of hyperthyroidism. 
Finally,  for each approach to measure exposure (acute, acute plus non-affected zone, and pollution gradient), we developed three models: model 1 included all pregnancies with TTP up to 12 months; model 2 excluded pregnancies with TTP = 1; whereas model 3 only included first time pregnancies in order to control for obstetric history of participants (Idrovo et al., 2005; Weinberg et al., 1994 ). All assumptions and adjustments were evaluated, and Stata 14 was the statistical software used to carry out all the analysis (Stata Corporation, College Station, USA).
DOI: 10.17632/gc9fcwtjvn.2
title: Mining leachate contamination and subfecundity among women living near the United States-Mexico border

description: Design and sample 
We conducted a retrospective cohort study on pregnancy cases of women living across the watershed area of the Sonora River, in those municipalities directly affected by the environmental disaster: Arizpe, Banámichi, Huépac, San Felipe de Jesús, Aconchi, Baviácora, Ures, and some villages belonging to the state capital Hermosillo (Molino de Camou, Topahue, San Francisco de Batuc, El Tronconal and San Pedro El Saucito)  (Lammers., 2014).  In addition, we included Magdalena de Kino as a non-exposed community, whose water supply source is different from the resting municipalities, but shares common climate and ecological characteristics (Figure 1). 
Participants were first identified by the local health centers and then visited at home, where they were asked to participate before signing the informed consent.  Inclusion criteria were women being older than 18 years, planned pregnancy, conception of pregnancy in municipalities considered as exposed and non-exposed in this study after the disaster or before up to 10 years prior, with the possibility of including more than one pregnancy for each participant. Among the criteria for exclusion were having a physical or mental disability to adequately respond the questionnaire or refused to sign the consent. The study sample size had enough statistical power according to the Freedman table (Freedman., 1982), taking into account that previous studies exploring fecundity and metal exposure worked with samples between 41 and 300 pregnancies (Snijders., 2012). The study was approved by either ethical review board of the University of Sonora, Mexico, and the Industrial University of Santander, Colombia.  
Statistical methods
Univariate and bivariate descriptive analysis were made after completing the database, using chi-square, Student’s t, and Mann-Whitney U to test for differences between variables.  Fecundability odds ratios (fOR) obtained from discrete time analogue of Cox’s proportional hazard models were used to estimate associations with logistic regression models using the macro dthaz  (Dinno., 2011).  For multiple analysis, variables included in the model had p<0.25 in the bivariate Wald-test or had effect changes > 20%. Models were adjusted for age at pregnancy, age at first pregnancy, pregnancy order, maternal occupation, father’s occupation, father’s age, and father history of hyperthyroidism. 
Finally,  for each approach to measure exposure (acute, acute plus non-affected zone, and pollution gradient), we developed three models: model 1 included all pregnancies with TTP up to 12 months; model 2 excluded pregnancies with TTP = 1; whereas model 3 only included first time pregnancies in order to control for obstetric history of participants (Idrovo et al., 2005; Weinberg et al., 1994 ). All assumptions and adjustments were evaluated, and Stata 14 was the statistical software used to carry out all the analysis (Stata Corporation, College Station, USA).
DOI: 10.17632/cgdszwgbwf.1
title: Seroprevalencia de SARS-CoV-2 y factores asociados en migrantes con vocación de permanencia, Bucaramanga, Colombia

description: This dataset was analyzed to determine the SARS-CoV-2 seroprevalence in migrants temporally residing in Bucaramanga, and to identify factors associated with previous SARS-CoV-2 infection. A survey was conducted that included demographic variables, comorbidities, smoking, height and weight to calculate the Body Mass Index (BMI), presence of symptoms suggestive of COVID-19, exposure to suspected or confirmed COVID-19 cases. Also, some practices related with the transmission of SARS-CoV-2 was collected. Subsequently, temperature, pulse, oximetry, and a venous blood sample were taken. Using chemiluminescence immunoassays, SARS-CoV-2 IgM and IgG in serum were performed. In this study 462 participants were included. The IgM seroprevalence was 11.69% (95%CI 9.07–14.94), IgG was 32.90% (95%CI 28.77–37.31) and IgM or IgG was 36.15% (95%CI 31.89-40.63). Exposure to a COVID-19 confirmed case (PR:1.54; 95%CI 1.04-2.29) or COVID-19 suspected case (PR:1.56; 95%CI 1.13-2.16), six or more cohabitants (PR:1.52; 95%CI 1.05-2.20), stay in Colombia ≥2 years (PR:1.43; 95%CI 1.11-1.92) and the presence of symptoms (PR:1.62; 95%CI 1.26-2.10) were associated with higher IgG seroprevalence.  The details can be found in the paper "Seroprevalencia de SARS-CoV-2 y factores asociados en migrantes con vocación de permanencia, Bucaramanga, Colombia" published in the Revista Cuidarte (https://revistas.udes.edu.co/cuidarte) (Free access).
DOI: 10.17632/cgdszwgbwf.2
title: Seroprevalencia de SARS-CoV-2 y factores asociados en migrantes con vocación de permanencia, Bucaramanga, Colombia

description: This dataset was analyzed to determine the SARS-CoV-2 seroprevalence in migrants temporally residing in Bucaramanga, and to identify factors associated with previous SARS-CoV-2 infection. A survey was conducted that included demographic variables, comorbidities, smoking, height and weight to calculate the Body Mass Index (BMI), presence of symptoms suggestive of COVID-19, exposure to suspected or confirmed COVID-19 cases. Also, some practices related with the transmission of SARS-CoV-2 was collected. Subsequently, temperature, pulse, oximetry, and a venous blood sample were taken. Using chemiluminescence immunoassays, SARS-CoV-2 IgM and IgG in serum were performed. In this study 462 participants were included. The IgM seroprevalence was 11.69% (95%CI 9.07–14.94), IgG was 32.90% (95%CI 28.77–37.31) and IgM or IgG was 36.15% (95%CI 31.89-40.63). Exposure to a COVID-19 confirmed case (PR:1.54; 95%CI 1.04-2.29) or COVID-19 suspected case (PR:1.56; 95%CI 1.13-2.16), six or more cohabitants (PR:1.52; 95%CI 1.05-2.20), stay in Colombia ≥2 years (PR:1.43; 95%CI 1.11-1.92) and the presence of symptoms (PR:1.62; 95%CI 1.26-2.10) were associated with higher IgG seroprevalence.  The details can be found in the paper "Seroprevalencia de SARS-CoV-2 y factores asociados en migrantes con vocación de permanencia, Bucaramanga, Colombia" published in the Revista Cuidarte (https://revistas.udes.edu.co/cuidarte) (Free access).
DOI: 10.17632/mmt5h4g23m.1
title: Data from different applications of Nickel-Titanate yellow pigments

description: This data set shows the change in color tone in plastic (masterbatch), enamel, ceramic coloring with different NIO ratios of PY53 Nickel-Titanate-Pigment calcined at different rates by solid-state reaction. When the nickel oxide ratio increased, the yellowness value for the plastic increased and a darker pigment was obtained. Different results were obtained in other applications. This data set can enable a researcher working with PY53 pigment to reach the desired pigment color by determining the ratios of raw materials.
DOI: 10.17632/mmt5h4g23m.2
title: Data from different applications of Nickel-Titanate yellow pigments

description: This data set shows the change in color tone in plastic (masterbatch), enamel, ceramic coloring with different NIO ratios of PY53 Nickel-Titanate-Pigment calcined at different rates by solid-state reaction. When the nickel oxide ratio increased, the yellowness value for the plastic increased and a darker pigment was obtained. Different results were obtained in other applications. This data set can enable a researcher working with PY53 pigment to reach the desired pigment color by determining the ratios of raw materials.
DOI: 10.17632/mmt5h4g23m.3
title: Data from different applications of Nickel-Titanate yellow pigments

description: This data set shows the change in color tone in plastic (masterbatch), enamel, ceramic coloring with different NIO ratios of PY53 Nickel-Titanate-Pigment calcined at different rates by solid-state reaction. When the nickel oxide ratio increased, the yellowness value for the plastic increased and a darker pigment was obtained. Different results were obtained in other applications. This data set can enable a researcher working with PY53 pigment to reach the desired pigment color by determining the ratios of raw materials.
DOI: 10.17632/x2vxf48mn3.1
title: Dataset for Green hydrogen in Colombia: a view into the country's available resources and their potential to meet domestic and international H2 demand

description: This dataset contains the results from the research focused in calculating Colombia's potential to produce hydrogen by: (1) electrolysis powered with solar photovoltaics (SPV), onshore (WON) and offshore wind turbines, as well as (2) biomass involved processes such as gasification, digestion and ethanol steam reforming. 
The inputs for these calculations were taken mostly from government sources and energy organizations. 
"Calculations for electrolysis H2 production" consists in two parts: (i) an estimation of the H2 production rate potential calculated by the possible WON, WOF, hydropower and SPV capacity that could be installed in Colombia. The last (SPV) at the same time was an estimation calculated based on information from SPV plants in Colombia, so two possibilities were calculated: (a) installing the same capacity and (b) using 1 % of available surface of each region in Colombia to install SPV. (ii) Furthermore, scenarios to comply with domestic and international demand were calculated. 
"Calculations for Biomass H2 production" consists in two parts: (i) an estimation of the H2 production rate potential calculated by the possible technologies (i.e. gasification, digestion and ethanol reforming) and the biomass with higher production in Colombia: Banana and plantain, sugar and panela cane, rice, oil palm, livestock wastes and bioethanol. A projection for the growth of these residues and feedstock production is also presented to determine the H2 potential from these sources in future years. (ii) Therefore,
scenarios to comply with domestic and international demand were calculated.
DOI: 10.17632/29kw38kzwj.1
title: Battery Test Data (LiFePO4 18650 Rechargeable Cell 3.3V 1100 mAh, Panasonic NCR18650B 3400mAh, Murata VTC6 18650 3000mAh 15A)

description: The included tests were performed at the University of Malaya by Dr. Prashant Shrivastava (prashant.xev.ess@gmail.com). If this data is utilized for any purpose, it should be appropriately referenced. 
The tests can be used to test Machine Learning Algorithms, Non-Linear observers and Filters Kalman Filter based State of Charge / State of Energy algorithms, or to develop battery models, and are intended to be a reference so researchers can compare their algorithm and model performance for a standard data set. The test data, or similar data, has been used for numerous publications, including:

P. Shrivastava, T. K. Soon, M. Y. I. B. Idris, S. Mekhilef and S. B. R. S. Adnan, " Comprehensive Co-estimation of Lithium-ion Battery States (SOC, SOE, SOP), Actual Capacity and Maximum Available Energy for EV Applications” J. Energy Storage, vol. 56, p. 102704, Dec. 2022, https://doi.org/10.1016/j.est.2022.106049.

P. Shrivastava, T. K. Soon, M. Y. I. B. Idris, S. Mekhilef and S. B. R. S. Adnan, “Model-based SOX estimation of Lithium-ion Battery for Electric Vehicle Applications” Int J Energy Res. 2022; 46 (8): 10704- 10723. doi:10.1002/er.7874.

P. Shrivastava, T. K. Soon, M. Y. I. B. Idris, S. Mekhilef and S. B. R. S. Adnan, "Combined State of Charge and State of Energy Estimation of Lithium-Ion Battery using Dual Forgetting Factor-based Adaptive Extended Kalman Filter for Electric Vehicle Applications," in IEEE Transactions on Vehicular Technology, doi: 10.1109/TVT.2021.3051655. 

P. Shrivastava, T. K. Soon, M. Yamani Bin Idris and S. Mekhilef, "Lithium-ion Battery Model Parameter Identification Using Modified Adaptive Forgetting Factor-Based Recursive Least Square Algorithm," 2021 IEEE 12th Energy Conversion Congress & Exposition - Asia (ECCE-Asia), 2021, pp. 2169-2174, doi: 10.1109/ECCE-Asia49820.2021.9479079. 

P. Shrivastava, T. Kok Soon, M. Yamani Bin Idris, S. Mekhilef and S. Bahari Ramadzan Syed Adnan, "Lithium-ion Battery State of Energy Estimation Using Deep Neural Network and Support Vector Regression," 2021 IEEE 12th Energy Conversion Congress & Exposition - Asia (ECCE-Asia), 2021, pp. 2175-2180, doi: 10.1109/ECCE-Asia49820.2021.9479413. 


For the tests, brand new 18650 cells of different chemistries such as LFP, NCA, and NMC were tested under controlled temperature using ESPEC SU-241 temperature chamber with Neware BTS 4000 battery tester.
A series of tests, including drive cycles including DST, FUDS, UDDS, WLTP, US06; HPPC, and pulse (dis) charge test, were performed at four different temperatures.
DOI: 10.34730/276fe4d3d8e74f61b142165dc6ffe72f
title: Forecasting near-surface ozone using temporally decomposed input variables and deep neural networks

description: Poster "Forecasting near-surface ozone using temporally decomposed input variables and deep neural networks" and preprint "O3ResNet: A deep learning based forecast system to predict local ground-level daily maximum 8-hour average ozone"
DOI: 10.17632/cwgswk84wv.1
title: Traftic Accidents Bucaramanga 2019

description: Diseño del estudio y población Estudio descriptivo, transversal, con análisis de datos secundarios provenientes de los registros de accidentes de tránsito de Bucaramanga en 2019, proporcionados por la Dirección de Tránsito y el Observatorio Digital municipal de Bucaramanga, muestreo tipo censo. Recolección de datos Con base en los 7,038 registros de personas involucrados de un total de 3,150 siniestros de tránsito ocurridos en Bucaramanga en 2019 reportados por la Dirección de Tránsito y la información de atención en salud del Observatorio Digital Municipal a partir de las diferentes Instituciones Prestadoras de Salud (IPS), se obtuvo información de costos de 812 personas atendidas en las IPS de la ciudad; posteriormente, se realizó la extracción, depuración y cruzamiento de las bases de datos. Ver Figura 1. La variable dependiente fue costos directos derivados de la atención en salud (urgencias, hospitalización, quirófanos), que las IPS reportaron a la Secretaria de Salud de Bucaramanga que incluyen la valoración/atención (médico general, especialista y atención de enfermería), las ayudas diagnosticas (laboratorios, rayos X, tomografías, Resonancias, etc.) y tratamientos instaurados (medicamentos, procedimientos quirúrgicos). Además, se tuvieron en cuenta las siguientes covariables: identificador, genero(femenino, masculino), edad (en años y en categorías de &lt;18 años, 18-25, 26-35, 36-45, 46-60 y &gt;60 años), tipo de vehículo involucrado (automóvil, motocicleta, camioneta, camión, bus), hipótesis del accidente (desobedecer señales y normas de tránsito, no mantener la distancia segura, girar bruscamente, impericia en el manejo, exceso de velocidad, adelantar invadiendo el carril), lugar de ocurrencia, porte de licencia, porte del seguro obligatorio de accidente de tránsito, sitio de atención en salud, gravedad, fecha de ocurrencia, día de la semana (lunes, martes, miércoles, jueves,. Viernes, sábado o domingo), comuna, instituciones prestadoras de servicios de salud, requerimiento de cirugía, muerte, parte del cuerpo afectada (cabeza, cuello, tórax, abdomen, miembros superiores, miembros inferiores, diferentes partes del cuerpo, tejidos blandos, genitales, esta variable organizada en base a los códigos CIE-10) diagnóstico, actor vial y costo general de la atención en salud en pesos colombianos. Continua en Step for reproduction
DOI: 10.17632/cwgswk84wv.2
title: Traffic Accidents Bucaramanga 2019

description: Diseño del estudio y población 
Estudio descriptivo, transversal, con análisis de datos secundarios provenientes de los registros de accidentes de tránsito de Bucaramanga en 2019, proporcionados por la Dirección de Tránsito y el Observatorio Digital municipal de Bucaramanga, muestreo tipo censo.

Recolección de datos
Con base en los 7,038 registros de personas involucrados de un total de 3,150 siniestros de tránsito ocurridos en Bucaramanga en 2019 reportados por la Dirección de Tránsito y la información de atención en salud del Observatorio Digital Municipal a partir de las diferentes Instituciones Prestadoras de Salud (IPS), se obtuvo información de costos de 812 personas atendidas en las IPS de la ciudad; posteriormente, se realizó la extracción, depuración y cruzamiento de las bases de datos. Ver Figura 1. 

La variable dependiente fue costos directos derivados de la atención en salud (urgencias, hospitalización, quirófanos), que las IPS reportaron a la Secretaria de Salud de Bucaramanga que incluyen la valoración/atención (médico general, especialista y atención de enfermería), las ayudas diagnosticas (laboratorios, rayos X, tomografías, Resonancias, etc.) y tratamientos instaurados (medicamentos, procedimientos quirúrgicos). 

Además, se tuvieron en cuenta las siguientes covariables: identificador, genero(femenino, masculino), edad (en años y en categorías de <18 años, 18-25, 26-35, 36-45, 46-60 y >60 años), tipo de vehículo involucrado (automóvil, motocicleta, camioneta, camión, bus), hipótesis del accidente (desobedecer señales y normas de tránsito, no mantener la distancia segura, girar bruscamente, impericia en el manejo, exceso de velocidad, adelantar invadiendo el carril), lugar de ocurrencia, porte de licencia, porte del seguro obligatorio de accidente de tránsito, sitio de atención en salud, gravedad, fecha de ocurrencia, día de la semana (lunes, martes, miércoles, jueves,. Viernes, sábado o domingo), comuna, instituciones prestadoras de servicios de salud, requerimiento de cirugía, muerte, parte del cuerpo afectada (cabeza, cuello, tórax, abdomen, miembros superiores, miembros inferiores, diferentes partes del cuerpo, tejidos blandos, genitales, esta variable organizada en base a los códigos CIE-10) diagnóstico, actor vial y costo general de la atención en salud en pesos colombianos. 
 
Continua en Step for reproduction
DOI: 10.17632/cwgswk84wv.3
title: Factors related to healthcare costs of road traffic accidents in Bucaramanga, Colombia

description: Diseño del estudio y población 
Estudio descriptivo, transversal, con análisis de datos secundarios provenientes de los registros de accidentes de tránsito de Bucaramanga en 2019, proporcionados por la Dirección de Tránsito y el Observatorio Digital municipal de Bucaramanga, muestreo tipo censo.

Recolección de datos
Con base en los 7,038 registros de personas involucrados de un total de 3,150 siniestros de tránsito ocurridos en Bucaramanga en 2019 reportados por la Dirección de Tránsito y la información de atención en salud del Observatorio Digital Municipal a partir de las diferentes Instituciones Prestadoras de Salud (IPS), se obtuvo información de costos de 812 personas atendidas en las IPS de la ciudad; posteriormente, se realizó la extracción, depuración y cruzamiento de las bases de datos. Ver Figura 1. 

La variable dependiente fue costos directos derivados de la atención en salud (urgencias, hospitalización, quirófanos), que las IPS reportaron a la Secretaria de Salud de Bucaramanga que incluyen la valoración/atención (médico general, especialista y atención de enfermería), las ayudas diagnosticas (laboratorios, rayos X, tomografías, Resonancias, etc.) y tratamientos instaurados (medicamentos, procedimientos quirúrgicos). 

Además, se tuvieron en cuenta las siguientes covariables: identificador, genero(femenino, masculino), edad (en años y en categorías de <18 años, 18-25, 26-35, 36-45, 46-60 y >60 años), tipo de vehículo involucrado (automóvil, motocicleta, camioneta, camión, bus), hipótesis del accidente (desobedecer señales y normas de tránsito, no mantener la distancia segura, girar bruscamente, impericia en el manejo, exceso de velocidad, adelantar invadiendo el carril), lugar de ocurrencia, porte de licencia, porte del seguro obligatorio de accidente de tránsito, sitio de atención en salud, gravedad, fecha de ocurrencia, día de la semana (lunes, martes, miércoles, jueves,. Viernes, sábado o domingo), comuna, instituciones prestadoras de servicios de salud, requerimiento de cirugía, muerte, parte del cuerpo afectada (cabeza, cuello, tórax, abdomen, miembros superiores, miembros inferiores, diferentes partes del cuerpo, tejidos blandos, genitales, esta variable organizada en base a los códigos CIE-10) diagnóstico, actor vial y costo general de la atención en salud en pesos colombianos. 
 
Continua en Step for reproduction