cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5061/dryad.n8pk0p30k
title: Data for: Local conditions matter: Minimal and variable effects of soil disturbance on microbial communities and functions in European vineyards

description: Soil tillage or herbicide applications are commonly used in agriculture
 for weed control. These measures may also represent a disturbance for soil
 microbial communities and their functions. However, the generality of
 response patterns of microbial communities and functions to disturbance
 have rarely been studied at large geographical scales. We investigated how
 a soil disturbance gradient (low, intermediate, high), realized by either
 tillage or herbicide application, affects diversity and composition of
 soil bacterial and fungal communities as well as soil functions in
 vineyards across five European countries. Microbial alpha-diversity
 metrics responded to soil disturbance sporadically, but inconsistently
 across countries. Increasing soil disturbance changed soil microbial
 community composition at the European level. However, the effects of soil
 disturbance on the variation of microbial communities were smaller
 compared to the effects of location and soil covariates. Microbial
 respiration was consistently impaired by soil disturbance, while effects
 on decomposition of organic substrates were inconsistent and showed
 positive and negative responses depending on the respective country.
 Therefore, we conclude that it is difficult to extrapolate results from
 one locality to others because microbial communities and environmental
 conditions vary strongly over larger geographical scales.
description: In each country, soil samples were taken at least one season
 after experimental plot preparation (2016 and/or 2017) and at minimum 6
 weeks after tillage/herbicide application around the time of grapevine
 flowering. Eight subsamples were taken in the two central inter-rows of
 each plot to a depth of 10 cm approximately 30 – 50 cm apart from each
 other and were pooled afterwards into one mixed sample, summing up to a
 total of 405 soil samples. The number comprises n= 54 samples for Austria
 2016, France 2017, Romania 2017, Germany 2016 and Germany 2017, but n = 77
 for Switzerland 2016 and n = 58 for Switzerland 2017. Thus, we included
 samples for bacteria and fungi for each country for at least one season
 (2016 for Austria, 2017 for France and Romania) or two seasons for
 Switzerland and Germany. DNA extraction from each soil sample was either
 performed directly after soil sampling or samples were stored frozen at
 -20° C until extraction. DNA was extracted from 0.25 g of mixed soil
 sample per inter-row by using the DNeasyPowerSoil Kit® following the
 manufacturer’s protocol (QIAGEN N.V., Venlo, Netherlands).
 For further information please also check paper supplemetray
 information.
description: Data can be accessed using MS Excel, R and OpenOffice.
DOI: 10.17632/3yymmmkj2x
title: Adaptive PV array reconfiguration using double deep q-networks for performance improvement under partial shading conditions

description: This dataset supports the research article titled "Adaptive PV array reconfiguration using double deep q-networks for performance improvement under partial shading conditions". The study addresses the partial shading problem in PV systems by proposing a Double Deep Q-Network (DDQN) based reconfiguration technique. By reducing the overestimation bias inherent in DQN, the proposed method significantly minimizes mismatch losses and improves power output efficiency.
The dataset consists of files containing specifications of the PV module and switching connections, training results, Q-value estimation bias analysis, daily power profiles with energy yields, cumulative energy production data, mismatch loss calculations, and execution time measurements.
DOI: 10.17632/3yymmmkj2x.1
title: Adaptive PV array reconfiguration using double deep q-networks for performance improvement under partial shading conditions

description: This dataset supports the research article titled "Adaptive PV array reconfiguration using double deep q-networks for performance improvement under partial shading conditions". The study addresses the partial shading problem in PV systems by proposing a Double Deep Q-Network (DDQN) based reconfiguration technique. By reducing the overestimation bias inherent in DQN, the proposed method significantly minimizes mismatch losses and improves power output efficiency.
The dataset consists of files containing specifications of the PV module and switching connections, training results, Q-value estimation bias analysis, daily power profiles with energy yields, cumulative energy production data, mismatch loss calculations, and execution time measurements.
DOI: 10.5061/dryad.73n5tb31q
title: Centris pallida reflectance and hair density dataset

description: Incoming solar radiation (wavelengths 290–2500 nm) significantly affects
 an organism’s thermal balance via radiative heat gain. Species adapted to
 different environments can differ in solar reflectance profiles. We
 hypothesized that conspecific individuals using thermally distinct
 microhabitats to engage in fitness-relevant behaviors would show
 intraspecific differences in reflectance: we predicted individuals that
 use hot microclimates (where radiative heat gain represents a greater
 thermoregulatory challenge) would be more reflective across the entire
 solar spectrum than those using cooler microclimates. Differences in
 near-infrared (NIR) reflectance (700–2500 nm) are strongly indicative of
 thermoregulatory adaptation as, unlike differences in visible reflectance
 (400–700 nm), they are not perceived by ecological or social partners. We
 tested these predictions in male Centris pallida (Hymenoptera: Apidae)
 bees from the Sonoran Desert. Male C. pallida use alternative reproductive
 tactics that are associated with distinct microclimates: large-morph
 males, with paler visible coloration, behave in an extremely hot
 microclimate close to the ground, while small-morph males, with a dark
 brown dorsal coloration, frequently use cooler microclimates above the
 ground near vegetation. We found that large-morph males had higher
 reflectance of solar radiation (UV through NIR) resulting in lower solar
 absorption coefficients. This thermoregulatory adaptation was specific to
 the dorsal surface and produced by differences in hair, not cuticle,
 characteristics. Our results showed that intraspecific variation in
 behavior, particularly in relation to microclimate use, can generate
 unique thermal adaptations that change the reflectance of shortwave
 radiation among individuals within the same population.
DOI: 10.17632/c2dbdv97jj
title: In karst fragile habitats, abiotic factors, particularly soil organic carbon, dominate over microbial communities in determining soil multifunctionality.

description: Karst ecosystem is a typical vulnerable habitat globally, facing severe soil degradation and rocky desertification.. Revealing how different restoration approaches and disturbance intensities affect soil properties and microbial community characteristics, and clarifying the resulting differences in soil multifunctionality, is of great significance for ecological management in this region. To this end, in areas of severe rocky desertification in Southwest China, we investigated five typical land-use types to represent varying disturbance intensities and restoration approaches, mainly including: farmland (high-intensity disturbance), grassland (moderate disturbance/grassland restoration), shrubland (low disturbance/shrub restoration), plantation forest (artificially assisted restoration), and secondary forest (natural restoration). Soil samples were collected from three depths (0–10, 10–20, 20–30 cm) to assess five key soil functions: nutrient provisioning, microbial growth efficiency, soil organic matter decomposition, nutrient cycling, and plant-microbe symbiosis. We found that microbial growth efficiency, SOM decomposition capacity, and soil multifunctionality in farmland and grassland were significantly lower than those in forests. Surface soil (0–10 cm) in shrubland exhibited the highest soil multifunctionality, with significant functional variation across soil depths. In addition, farmland and grassland had higher bacterial α-diversity, and both showed significant differences from forests in the structure of bacterial and fungal communities. Shrubland exhibited higher bacterial community stability and network complexity, while plantation forests had the highest network complexity. Driving factor analysis revealed that while microbial network properties influenced multifunctionality, abiotic factors had a stronger independent explanatory power.. Structural equation modeling further identified that SOC as the key variable linking different restoration/disturbance approaches and soil layer depths, as well as enhancing soil multifunctionality. This study emphasizes the importance of adopting shrubland restoration to improve soil multifunctionality in rocky desertification areas, which not only helps to enhance the specificity and effectiveness of rocky desertification management, but also promotes the transformation of regional ecosystems from “degradation remediation” to “functional enhancement.”
DOI: 10.17632/c2dbdv97jj.1
title: In karst fragile habitats, abiotic factors, particularly soil organic carbon, dominate over microbial communities in determining soil multifunctionality.

description: Karst ecosystem is a typical vulnerable habitat globally, facing severe soil degradation and rocky desertification.. Revealing how different restoration approaches and disturbance intensities affect soil properties and microbial community characteristics, and clarifying the resulting differences in soil multifunctionality, is of great significance for ecological management in this region. To this end, in areas of severe rocky desertification in Southwest China, we investigated five typical land-use types to represent varying disturbance intensities and restoration approaches, mainly including: farmland (high-intensity disturbance), grassland (moderate disturbance/grassland restoration), shrubland (low disturbance/shrub restoration), plantation forest (artificially assisted restoration), and secondary forest (natural restoration). Soil samples were collected from three depths (0–10, 10–20, 20–30 cm) to assess five key soil functions: nutrient provisioning, microbial growth efficiency, soil organic matter decomposition, nutrient cycling, and plant-microbe symbiosis. We found that microbial growth efficiency, SOM decomposition capacity, and soil multifunctionality in farmland and grassland were significantly lower than those in forests. Surface soil (0–10 cm) in shrubland exhibited the highest soil multifunctionality, with significant functional variation across soil depths. In addition, farmland and grassland had higher bacterial α-diversity, and both showed significant differences from forests in the structure of bacterial and fungal communities. Shrubland exhibited higher bacterial community stability and network complexity, while plantation forests had the highest network complexity. Driving factor analysis revealed that while microbial network properties influenced multifunctionality, abiotic factors had a stronger independent explanatory power.. Structural equation modeling further identified that SOC as the key variable linking different restoration/disturbance approaches and soil layer depths, as well as enhancing soil multifunctionality. This study emphasizes the importance of adopting shrubland restoration to improve soil multifunctionality in rocky desertification areas, which not only helps to enhance the specificity and effectiveness of rocky desertification management, but also promotes the transformation of regional ecosystems from “degradation remediation” to “functional enhancement.”
DOI: 10.5061/dryad.6wwpzgn31
title: Germplasm diversity of sunflower volatile terpenoid profiles across vegetative and reproductive organs

description: Cultivated sunflower (Helianthus annuus) is the fourth most important
 oilseed crop globally and is known to have experienced multiple genetic
 bottlenecks during domestication and improvement. Homogenization of crop
 germplasm may limit breeding efforts to improve pest and pathogen
 resistance or optimize other biotic interactions like pollinator
 attraction. Such interactions are often strongly influenced by plant
 phytochemistry, especially volatile compounds like terpenoids. Here we use
 solid-phase microextraction gas chromatography mass spectrometry (SPME
 GC-MS) to evaluate volatile phytochemistry across leaves, involucral
 bracts, disc florets, and ray floret petals in a collection of twelve
 inbred lines selected to represent a cross-section of sunflower germplasm
 diversity. Results indicate considerable compositional diversity of
 volatiles among lines, though substantial reduction in total volatile
 abundance relative to wild H. annuus. From leaves and bracts to disc
 florets and petals, we observe a strong increase in the proportion of
 monoterpenoids relative to sesquiterpenoids accompanying the transition to
 reproductive structures, with consistently over 85% monoterpenoids in disc
 florets and petals. This pattern is driven by substantially higher
 production of monoterpenoids (especially alpha-pinene and sabinene) in
 reproductive structures. Sesquiterpenoid production is roughly similar
 across organs, and in leaves varies among lines from 21–55% of volatiles,
 dominated by cadinene-type sesquiterpenoids. This work suggests that the
 compositional diversity of volatile terpenoids within cultivated germplasm
 may be sufficient for many breeding applications, though for breeding
 increased volatile production the use of wild H. annuus and other wild
 Helianthus germplasm may be necessary.
description: This dataset was collected using solid-phase microextraction gas
 chromatography mass spectrometry (SPME GC-MS) to evaluate volatile
 phytochemistry across leaves, involucral bracts, disc florets, and ray
 floret petals in a collection of twelve inbred lines selected to represent
 a cross-section of sunflower germplasm diversity. Tissue was snap-frozen
 from a large hoophouse experiment, weighed and analyzed with SPME-GC-MS,
 and output data for each sample was manually curated to extract
 mass-normalized peak areas for each identified compound. See full text for
 more details.
description: Data files are CSV, no proprietary software is required.
DOI: 10.17632/mr8n6sgcsd
title: BanGRev (Bengali Gadget Review) Dataset

description: Bengali ranks seventh globally among spoken languages yet faces severe constraints in computational text analysis resources. Bangladesh's e-commerce sector has expanded rapidly, with internet users reaching 121.75 million by December 2023, making online consumer reviews increasingly influential in purchasing decisions. Studies indicate that 91% of consumers rely on such reviews when making product choices.

The primary obstacle to automated review analysis in Bengali has been dataset scarcity. Most deep learning approaches require at least 8,000 samples for adequate performance. Beyond scale limitations, previous datasets relied on single-platform collection, missing the linguistic variation across different user demographics and communication contexts. Bengali presents particular challenges for computational processing. The language's complex morphology and regional dialectal variations complicate automated analysis. Tech product reviews add another layer of complexity through specialized vocabulary, technical specifications, and product-specific evaluation criteria.

BanGRev addresses these gaps through systematic multi-source collection from e-commerce platforms, social media, and video comments, combined with rigorous three-class annotation protocols validated at Fleiss' Kappa of 0.73.
DOI: 10.5061/dryad.bzkh189dt
title: Evaluating the effects of pod-based electronic cigarettes on human endothelial cell function

description: Pod-based electronic (e-) cigarettes more efficiently deliver nicotine
 using a protonated formulation. The cardiovascular effects associated with
 these devices are poorly understood. We evaluated whether pod-based
 e-liquids and their individual components impair endothelial cell
 function.  We isolated endothelial cells from people who are pod
 users (n=10), tobacco never users (n=7), and combustible cigarette users
 (n=6). After a structured use, pod users had lower acetylcholine-mediated
 endothelial nitric oxide synthase (eNOS) activation compared with never
 users and was similar to levels from combustible cigarette users (overall
 P=0.008, P=0.01 pod vs never; P=0.96 pod vs combustible cigarette). The
 effects of pod-based e-cigarettes and their constituents on vascular cell
 function were further studied in commercially available human aortic
 endothelial cells (HAECs) incubated with flavored JUUL e-liquids or
 propylene glycol (PG):vegetable glycerol (VG) at 30:70 ratio with or
 without 60 mg/mL nicotine salt for 90 min. A progressive increase in cell
 death with JUUL e-liquid exposure was observed across 0.0001-1% dilutions;
 PG:VG vehicle with and without nicotine salt-induced cell death.
 A23187-stimulated nitric oxide production was decreased with all JUUL
 e-liquid flavors, PG:VG and nicotine salt exposures. Aerosols generated by
 JUUL e-liquid heating similarly decreased stimulated nitric oxide
 production. Only mint-flavored e-liquids increased inflammation and
 menthol-flavored e-liquids enhanced oxidative stress in HAECs. In
 conclusion, pod e-liquids and their individual components appear to impair
 endothelial cell function. These findings indicate the potential harm of
 pod-based devices on endothelial cell function and thus may be relevant to
 cardiovascular injury in pod-type e-cigarette users.
DOI: 10.17632/mr8n6sgcsd.1
title: BanGRev (Bengali Gadget Review) Dataset

description: Bengali ranks seventh globally among spoken languages yet faces severe constraints in computational text analysis resources. Bangladesh's e-commerce sector has expanded rapidly, with internet users reaching 121.75 million by December 2023, making online consumer reviews increasingly influential in purchasing decisions. Studies indicate that 91% of consumers rely on such reviews when making product choices.

The primary obstacle to automated review analysis in Bengali has been dataset scarcity. Most deep learning approaches require at least 8,000 samples for adequate performance. Beyond scale limitations, previous datasets relied on single-platform collection, missing the linguistic variation across different user demographics and communication contexts. Bengali presents particular challenges for computational processing. The language's complex morphology and regional dialectal variations complicate automated analysis. Tech product reviews add another layer of complexity through specialized vocabulary, technical specifications, and product-specific evaluation criteria.

BanGRev addresses these gaps through systematic multi-source collection from e-commerce platforms, social media, and video comments, combined with rigorous three-class annotation protocols validated at Fleiss' Kappa of 0.73.
DOI: 10.5061/dryad.bcc2fqzh7
title: High‐resolution genomic analysis of four local Vietnamese chicken breeds

description: A total of 96 individuals were sampled from four populations of Vietnamese
 local chickens (28 Ho, 32 Dong Tao, 18 Mong, and 18 Mia) distributed in
 four provinces (Bac Ninh, Hung Yen, Ha Nam, and Hanoi, respectively) in
 the North of Vietnam. All individuals were from the same conservation
 program in Vietnam, originating from either private farms or public
 institutions involved in this program. Neither pedigree nor phenotypic
 information was available. We used stratified sampling for flocks,
 ensuring a distance of at least 500 m between the selected flocks and
 random sampling of one or two individuals in each selected flock. Genomic
 DNA was extracted from the blood samples of all chickens. The HD array for
 chickens allows for the simultaneous genotyping of approximately 580,000
 SNPs. This array comprises SNPs on 28 autosomal chromosomes, two sex
 chromosomes (Z and W for poultry), and two linkage groups (LGE64 and LGE
 22C19W28). Only SNPs on the 28 autosomes were considered in the present
 study. The SNPs with more than 10% missing genotypes or minor allele
 frequencies lower than 1% were removed, yielding a consensus panel of
 454,297 autosomal SNPs for the analysis of population genetic structure.
 We applied a second quality control within each breed. Specifically, SNPs
 with within-breed minor allelic frequencies lower than 0.05 or SNPs with
 significant (P &lt; 0.0001) deviation from the Hardy-Weinberg
 equilibrium were filtered out. This second filter led to 368,652, 383,792,
 405,535, and 432,631 SNPs for Ho, Dong Tao, Mong, and Mia breeds,
 respectively. Of note, removing monomorphic SNPs within breeds may lead to
 the elimination of SNPs that are polymorphic across breeds. Due to the
 large number of available SNPs, we did not consider the potential effect
 of these filtered markers as important for subsequent analyses. Genetic
 diversity analyses were performed on the remaining 308,307 SNPs shared by
 all four breeds.
description: All statistical analyses were performed using R.
DOI: 10.17632/9dcb8jmbts
title: Dataset: Daily Air Quality Index and Pollutant Concentrations for Mumbai, India

description: This dataset provides daily air quality measurements and Air Quality Index values for Mumbai, India, derived from multiple Maharashtra Pollution Control Board monitoring stations. The data spans from June 2019 to January 2026 and represents long term urban air quality conditions across different regions of the city.

The dataset is organized into station level files and aggregated outputs. Individual station files contain daily pollutant concentrations and AQI values computed independently for each monitoring location, including Kurla, Bandra, Bandra Kurla Complex, Sion, and Chhatrapati Shivaji International Airport. These stations capture spatial variability in air pollution across residential, commercial, industrial, and traffic influenced zones of Mumbai.

Hourly air quality measurements were sourced from the OpenAQ platform and aggregated to daily values. PM2.5, PM10, NO2, and SO2 concentrations are calculated as daily means from hourly data. CO and O3 concentrations are calculated as the daily maximum of rolling 8 hour averages, following the Central Pollution Control Board methodology. Daily AQI is computed using CPCB breakpoint tables, where the final AQI for each day is defined as the maximum sub index among available pollutants, and the dominant pollutant is recorded.

The files included are:
- Station specific daily AQI datasets for five MPCB monitoring locations in Mumbai
- A combined stations dataset with all station observations stacked by date and station
- A city averaged daily dataset representing mean air quality across Mumbai

Missing values indicate days or pollutants not reported by a station. The temporal coverage varies by station due to differences in commissioning dates, maintenance outages, and data availability. The dataset preserves these gaps to maintain transparency and support rigorous data quality handling.

This dataset is suitable for long term air quality trend analysis, spatial variability studies, exposure assessment, policy evaluation, and machine learning applications related to air pollution forecasting in Mumbai.