cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.15112071.v1
title: Supplementary Material for: LncRNA XIST Contributes to Cisplatin Resistance of Lung Cancer Cells by Promoting Cellular Glycolysis through Sponging miR-101-3p

description: <b><i>Background:</i></b> Non-small-cell lung carcinoma is one of the most frequently diagnosed cancers. Cisplatin (CDDP) is a currently applied standard anticancer agent for advanced lung cancers. Although effectively clinical response was achieved initially, a large fraction of lung cancer patients developed cisplatin resistance. Therefore, understanding the molecular mechanisms of chemoresistance is crucial for anti-lung cancer therapy. Long non-coding RNA (lncRNA)-X-inactive-specific transcript (XIST) has been reported to be positively associated with multiple cancers. Currently, the precise role and mechanism of XIST in cisplatin resistance of lung cancer have not been elucidated. <b><i>Methods:</i></b> The expression levels of miR-101-3p and lncRNA XIST were detected by qRT-PCR. Cisplatin-resistant lung cancer cell line was established by selecting the survival cells under gradually increased cisplatin treatments. The cell proliferation was detected by MTT assay, and the cellular glucose metabolism rate was evaluated by Seahorse metabolic flux analysis and glucose uptake and lactate product assays. Glycolysis-related protein expression levels were detected by Western blot. Dual luciferase reporter was constructed to determine the lncRNA-miRNA interaction. <b><i>Results:</i></b> Here, we report XIST is significantly upregulated in lung cancer tissues compared with normal lung tissues. In addition, cisplatin-resistant lung cancer cells displayed remarkably elevated XIST expression. We demonstrated that miR-101-3p functioned as a tumor suppressor in lung cancer and sensitized lung cancer cells to cisplatin. Bioinformatics analysis predicted miR-101-3p could be a potential target of XIST through direct binding with it as a competing endogenous RNA, which was further validated from lung tumor tissues and cell lines by luciferase assay. Intriguingly, XIST significantly promoted cellular glycolysis rate of lung cancer cells. The extracellular acidification rate, glucose uptake, and lactate product were elevated by XIST overexpression. On the contrary, miR-101-3p effectively suppressed glycolysis rate. Finally, we demonstrated silencing XIST significantly recovered miR-101-3p expression and downregulated expression of glycolysis key enzymes, a phenotype could be further overridden by miR-101-3p inhibition. <b><i>Conclusions:</i></b> This study reveals a new molecular mechanism for the lncRNA-XIST-promoted cisplatin resistance via sponging miR-101-3p, leading to de-repression of cellular glycolysis. Moreover, these findings warrant further in vivo investigations to study XIST as a potential target to overcome cisplatin resistance.
DOI: 10.17632/dpvyhpykk9
title: Data for: Leveraging blockchain to improve automotive supply chain traceability

description: The automotive industry worldwide seems to be spontaneously changing with supply chain improvement being one of the main focus areas along with cost reduction, process optimization and enhancing timely throughput. The general success parameter for achieving a better output in all the said focus areas is having an effective traceability system in place. Traceability for the automotive industry is a system documenting the genealogy of parts involved in manufacturing a specific product. Even with companies having an enormous amount of capital invested for perfecting their supply chain and achieving traceability, it is seen that they still have limited visibility and insight into their supply chain at a given instance. This study aims to leverage blockchain technology to eliminate inefficiencies of the conventional automotive supply chains for increasing transparency, streamlining processes and decentralizing network while providing stakeholders and companies with a host of value-adding features that ensure smoother and faster transaction. The data-set contains supporting files for the study that demonstrates the advantages of blockchain enabled automotive supply chain. It also contains the Hyperledger Composer files that was used for deployment of the said network.
DOI: 10.17632/rpkygd9gkt
title: Deep learning TTS Dataset for Malayalam Poem Recitation

description: This dataset can be used to train  deep learning frameworks such asTacotron and WaveGlow to generate deep fake voice
DOI: 10.17632/ggkdb4xsv2
title: Data for: Mathematical Modelling and Experimental Investigation of Vacuum Insulated Semi-Transparent Thin-Film Photovoltaic (PV) Glazing
DOI: 10.17632/ybh7b3mbbv
title: Analysis of the corpus

description: Move and step analysis of the selected conference abstracts in English and Spanish.
DOI: 10.6084/m9.figshare.28497608.v1
title: Tourism

description: This study aims to explore the factors influencing word-of-mouth (WOM) intentions among cultural tourists
DOI: 10.17632/ntvkj9pbg6
title: Data for: Lineage Networks, Urban Migration and Income Inequality: Evidence from Rural China

description: For replicating “Lineage Networks,Urban Migration and Income Inequality: Evidence from Rural China by Jeremy Foltz, Yunnan Guo, and Yang Yao”. There is one replication do-file, entitled Results_final.do. This file calls the data files household.dta and village.dta. Both are in the data subfolder. These are created from raw data sources listed in the paper, all of which are not publicly available. The log file for cleaning and merging the raw data, makedata_final.log, is also in the replication folder. The do file creates tables, which are stored in the “results” subfolder, and figures, which are stored in the “drafts” subfolder. The log file for all of the results is results_final.log.
DOI: 10.17632/pwkdwprv3j
title: Algorithm for constrained multi-objective land use allocation optimization under uncertainty

description: This dataset describes the software and data to quantify uncertainty in Pareto fronts arised from spatial data. This dataset contains the Python code for a multi-objective land use allocation optimization under uncertainty. The program is an extension to CoMOLA from Strauch et al. 2019 (https://doi.org/10.1016/j.envsoft.2019.05.003). For a detailed description of CoMOLA, we refer to the article. Before executing CoMOLA under uncertainty, extreme lower and upper bound samples need to be generated from the land use and soil fertility map with quantified uncertainty. That preprocessing is described reproducable with the following Mendeley Dataset: Hildemann, Moritz Jan; Verstegen, Judith (2021), “Sampling procedure of land use and soil fertility map under uncertainty”, Mendeley Data, V3, doi: 10.17632/6x6cccfc4x.3. For every produced extreme sample, CoMOLA needs to be performed with the corresponding land use and soil fertility map. As the computational effort and computation time are high (15-20 hours) and ten optimizations were performed for every extreme sample, the runs were performed in parallel on a high-performance Linux cluster (MEGWARE cluster with 15.120 cores, 412 nodes and Intel Xeon Gold 6140 18C 2.30GHz processors). The program is executable for Python 3.7 and 3.8 in a Linux environment. The changes compared to CoMOLA include: an update to Python 3.8, removal of R components in objecting the objective values, and the implementation of a seeding procedure to inject single-objective optima into the first generation of the Genetic Algorithm. The seeding procedure allowed faster and better convergence. The generated Pareto fronts can be used postprocessing to quantify the uncertainty in objective and solution space. Pseudo-random states are used to assure reproducibility despite the stochastic processes.
DOI: 10.17632/j9y7snrbpm
title: Data for "A model for the investment recommender system using ANFIS based on the Potential Investors’ Decision Key Factors (PIDKFs)"

description: A part of the data for the paper titled "A model for the investment recommender system using ANFIS based on the Potential Investors’ Decision Key Factors (PIDKFs)". Authors: Asefeh Asemi, Adeleh Asemi, and Andrea Ko
DOI: 10.6084/m9.figshare.25848856.v1
title: Raw AFM Data from: Real-time single-molecule observation of incipient collagen fibrillogenesis and remodeling

description: Attached are the three raw data files acquired on a Asylum Research Cypher VRS AFM for the corresponding SI videos in the manuscript: "Real-time single-molecule observation of incipient fibrillogenesis and remodeling".The file should be opened through the Asylum Research Application in IGOR PRO to properly view and examine any frame in any of the videos.
DOI: 10.6084/m9.figshare.26543653.v2
title: Structure, thermodynamics, and viscosity of MgSiO<sub>3</sub> liquid in super-Earths and sub-Neptunes

description: Data used in the figures and examples of outputs from molecular dynamics simulations
DOI: 10.17632/vvxvdnxmdj
title: A code and a database for constructing the Continuous BN regression model

description: The code is used to construct a continuous BN model for assessing seismic liquefaction-induced settlement of the free-field ground, and the database comes from numerical simulation results.
DOI: 10.25394/pgs.28783928.v1
title: Enhancing the Robustness of Vehicle Re-Identification in Intelligent Transportation Systems

description: Vehicle Re-identification (ReID) is a critical component of Intelligent Transportation Systems (ITS), enabling effective traffic management and law enforcement. However, achieving robust and efficient ReID remains challenging due to the significant variability in vehicle appearances and environmental conditions. This thesis addresses these challenges and makes several key contributions to enhance robustness, accuracy, and efficiency in vehicle ReID.<br>We developed a comprehensive data set generation pipeline that uses vehicle detection algorithms with confidence scores to select optimal Regions of Interest (ROI) for image cropping. This ensures high-quality datasets tailored for ReID tasks. Comprehensive experiments demonstrated that our designed ROIs can significantly improve vehicle ReID accuracy and tracking performance. Furthermore, we created a unique dataset that combines images from highway cameras and drone footage captured across nine pairs of weaving areas, enriching the diversity of the data and enabling robust model training.<br>To enhance robustness in real-world scenarios, we conducted an aspect ratio analysis and demonstrated that Vision Transformer (ViT)-based ReID models can achieve improved robustness when trained with varying aspect ratios. This approach effectively addresses challenges arising from diverse vehicle shapes and imaging conditions. We incorporated a mixup method applied at the patch level during the ViT’s conversion of images into patches—using spatial attention weights as guidance—and adopted non-uniform strides to more accurately match the inherent aspect ratios of objects. Finally, we proposed a dynamic feature fusion ReID network to further improve model robustness. Our method achieved a 10\% improvement in mean average precision (mAP) on the VehicleID dataset, surpassing existing state-of-the-art methods.<br><br>Furthermore, to address the domain generalization challenge in ReID - where models trained on urban road data struggle to generalize to highway data - we proposed a novel framework to bridge this gap, improving cross-domain performance in vehicle ReID. This work builds upon an existing framework that combines image-level and feature-level disentanglement for improved generalization.We leveraged Conditional Value at Risk (CVaR) to boost robustness and employed a loss landscape smoothing technique—commonly known as sharpness-aware minimization—to foster improved generalization, our approach achieved a 3\% improvement in mAP compared to baseline, setting a new benchmark in cross-domain ReID.Together, these innovations address key challenges in vehicle ReID, providing a pathway to improved accuracy, robustness, and efficiency, and positioning this work as a valuable contribution to real-world ITS applications.<br>
DOI: 10.6084/m9.figshare.19790014.v1
title: hERG Inhibition Data on Novel NL-Compounds

description: Compound 1 is NL221-75 Compound 2 is NL33-104 Compound 3 is NL34-113 Compound 4 is NL350-02 <br>
DOI: 10.6084/m9.figshare.28395197.v1
title: PLANILHA DA RSL - Artigo Linguagem Simples aplicada na Comunicação Pública: uma Revisão Sistemática de Literatura (RSL)

description: Este trabalho apresenta uma Revisão de Literatura Sistemática (RSL) referente ao uso da Linguagem Simples (LS) na Comunicação Pública.
DOI: 10.17632/m7kdz45zfk
title: ODRIC — A one-dimensional linear resistive MHD code in cylindrical geometry

description: Title of program: ODRIC Catalogue Id: AAFZ_v1_0 Nature of problem The primitive linearized resistive MHD equations in cylindrical geometry are advanced in time. Separate equations for the electron and ion temperature perturbations are solved. Hall terms and the thermal force vector are included in Ohm's law. Anisotropic thermal conductivity and viscosity are included in the model. The plasma is assumed to be quasineutral. Fourier analysis in the poloidal and toroidal directions is performed, resulting in a 1-D (radial) system for the perturbed quantities. Versions of this program held in the CPC repository in Mendeley Data AAFZ_v1_0; ODRIC; 10.1016/0010-4655(86)90023-8 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)
DOI: 10.6084/m9.figshare.1385358.v1
title: UPR workshop: Processing TCGA mRNA expression data

description: Handout and figure from a workshop on processing data from The Cancer Genome Atlas project. Uses the RTCGAToolbox to access Broad Institute Firehose data, examine the data and produce plots. The workshop was given in San Juan, PR, at the University of Puerto Rico Medical School, on Friday, April 17, 2015. The workshop was sponsored by the UPR/MDACC Parnership for Excellence in Cancer Research and the Puerto Rico Clinical and Translational Research Consortium.
DOI: 10.17632/yk2gzsgwpf
title: Hurricane Maria

description: Hurricane Data for Maria event, 2017
DOI: 10.6084/m9.figshare.7996598.v2
title: Toxicity percentage at different concentrations of hydro-alcoholic extract

description: Toxicity percentage at different concentrations of hydro-alcoholic extract. Note: phytochemical analyses based on the color change (please see three replications)
DOI: 10.17632/rjhgpvvhdg
title: Embracing Briquettes as a Sustainable Alternative Fuel: A Theory of Planned Behavior Approach

description: Embracing Briquettes as a Sustainable Alternative Fuel: 
A Theory of Planned Behavior Approach



The research objects focus on the following construct: 
1. The intention to use coconut shell briquettes as a sustainable alternative fuel
2. Attitudes towards briquette adoption
3. Environmental support for briquette adoption
4. Self-efficacy in adopting briquettes.

The research involves the Indonesian community, including households and businesses that typically use charcoal for cooking or industrial purposes.

The sampling method utilizes purposive sampling techniques with respondent criteria including Indonesians who use charcoal in daily cooking activities, are at least 18 years old, reside in various regions of Indonesia (both urban and rural), and have access to information about coconut shell briquettes. 

An online questionnaire based on the Theory of Planned Behavior was distributed between March and July 2024. The questionnaire assessed attitudes towards briquette adoption, environmental support for briquette adoption, self-efficacy in briquette adoption, and briquette adoption intention using a 5-point Likert Scale, ranging from "1 = strongly disagree" to "5 = strongly agree." Table 1 presents the operationalization of the variables.
DOI: 10.6084/m9.figshare.10003133.v2
title: HIV1V1V1.fasta

description: Fasta file from 3DPCR sequencing of APOBEC1 edited DNA sequences<br>
DOI: 10.17632/9jp7n6xc53
title: Supplementary Table files of AJP-GI 2025

description: Supplementary Table 1: List of the primary antibodies and the secondary antibodies in this study
Supplementary Table 2: List of primers of qPCR in this study
DOI: 10.25946/24556981.v1
title: Phytochemical and Bioassay Dataset

description: Phytochemistry: Phytochemical assays, HPLC phenolic profile, LC-MS/MS data, and GC-MS data. Bioassays: Anticancer and antimicrobial bioassays.
DOI: 10.17632/mgv252y9vr
title: Electric vehicle battery pack capacity per vehicle in the U.S. market 2022

description: We compiled a list of electric vehicle (EV) battery pack capacities per vehicle for EVs (i.e., battery electric vehicles and plug-in hybrid electric vehicles) in the U.S. market. We use this dataset to further estimate the average EV battery pack per vehicle capacity in the current U.S. market. In this dataset, you will find the make of EVs, the model, year, and their EV battery pack per vehicle capacities in kWh.
DOI: 10.6084/m9.figshare.27765966.v2
title: Papalexi et al. 2021 ECCITE-seq

description: MuData file with preprocessed ECCITE-seq data from Papalexi et al., 2021 (https://www.nature.com/articles/s41588-021-00778-2) as used in "Modeling variable guide efficiency in pooled CRISPR screens with ContrastiveVI+" (Weinberger et al., 2024).
DOI: 10.17632/fzjhzyg5nf
title: Human activity and soil N impact spatial distribution patterns of soil heavy metal pollution in China

description: Soil heavy metal pollution has emerged as a critical environmental challenge in China. Despite growing concerns, the spatial distribution patterns and land-use pollution characteristics remain poorly characterized. This nationwide investigation analyzed 7 priority heavy metals (cadmium (Cd), arsenic (As), lead (Pb), zinc (Zn), copper (Cu), chromium (Cr) and nickel (Ni)) across 33 study sites, employing structural equation modeling and random forest analysis to quantify drivers for heavy metal pollution pattern. Our results showed that the spatial distribution pattern of heavy metal pollution in China was negatively correlated with latitude. Cd, As, Pb and Zn should be the priority heavy metals to be controlled, with Cd exceeding the national standard by as much as 27.3 %. In addition, compared with other land, industrial and mining storage land pollution is the most serious, should be given priority control. The structural equation model showed that human, soil and climate together explain 39 % of the variance of heavy metal pollution. Random forest analysis suggested that human activity and N had the greatest relative influence on heavy metal pollution evaluation indexes. These findings provide a scientific basis for developing targeted remediation strategies and implementing differentiated land use management programs.
DOI: 10.4121/21792347.v1
title: List of Withdrawn Proposals - The European Commission's right of withdrawal of proposals

description: Aggregate list of the total OLP proposals lapsed/withdrawn by the European Commission, based on data obtained from the European Parliament’s Legislative Observatory Database. The data is restricted to OLP proposals actually withdrawn (excluding those that simply became lapsed and where the Commission did not effectively use its right of withdrawal), setting the withdrawn proposal as the unit of analysis. The withdrawn proposals are classified by type of procedure or legislative instrument and policy-issue, by the number of years passed between proposal initiation and proposal withdrawal, and by the the reaction of the co-legislators (Council and Parliament) on the withdrawal of the proposal. The generated database includes a total of 261 entries, of which 11 are dropped because they were lapsed, but not withdrawn. The final sample (n) is composed of a total of 250 withdrawn proposals between 1994 and 2020.
DOI: 10.6084/m9.figshare.6208652.v1
title: Additional file 1: of Equine strongyle communities are constrained by horse sex and species dipersal-fecundity trade-off

description: Table S1. Individual worm counts and associated metadata relative to each of the 48 horses considered: sex, breed, year of birth, premise, premise type, pre-treatment faecal egg count and worm counts for each nematode species. (XLS 72 kb)
DOI: 10.6084/m9.figshare.5123752.v1
title: Supplementary Material for: Effective Improvement of <i>D</i>-Phenylglycine Aminotransferase Solubility by Protein Crystal Contact Engineering

description: Structure-guided genetic engineering of <i>D</i>-phenylglycine aminotransferase (<i>D</i>-PhgAT) aimed at increasing protein solubility was attempted. In silico analyses predicted the Asn439 and Gln444 as highly solvent-exposed β-turn residues involved with protein crystal contact (CC) potential candidates for solubility-improving mutations. They were replaced with Asp and Glu creating the N439D and Q444E single mutants, and N439D/Q444E double mutant with 2.5-, 3.3- and 5.9-fold increases in solubility, respectively. The protein CC prevention effect rather than the net charge effect accounted for the dramatically improved solubility since the N439D, Q444E and N439D/Q444E mutations altered the isoelectric point of <i>D</i>-PhgAT by only 0.1, 0.1 and 0.3 units, respectively. Examination of the <i>D</i>-PhgAT structural model revealed that the N439D mutation weakened the CC attraction force and the Q444E mutation created electrostatic repulsion at the CC point. Analysis of circular dichroism spectra, melting temperature, and <i>D</i>-PhgAT-specific activity showed that the mutations posed no unfavorable effect on the conformational stability and catalytic performance of the enzyme. The protein solubility-improving strategy employed on <i>D</i>-PhgAT in this study was successful with minimal protein structure modification required. It should be applicable with a high chance of success for other proteins, especially those with 3-D structural models available.
DOI: 10.17632/z7wc63gxx4
title: The interrelation of the dividend policies of peers in emerging markets

description: Data set includes annual data for 605 public non-financial companies from 45 industries in emerging markets for the time period from 2000 to 2019. Data set consists of dividend per share, market capitalization, free cash flow, leverage, retained earnings, stock return, stock return volatility observations gathered from Thomson Reuters Eikon. Data was used in a Master’s thesis to test hypotheses regarding the interrelation of the dividend policies of peers in emerging markets. The main result of the research is a significant peer influence on dividend policies in emerging markets.
DOI: 10.17632/p86pfzwhsw
title: Data for: Foreign Language Effect in Decision-making: How Foreign Is It?

description: The file contains the row data of the four studies described in the manuscript
DOI: 10.6084/m9.figshare.27156000.v1
title: ScRNA seq data of human placental tissue and peripheral blood samples from the same donor

description: These scRNA seq data were a subset of dataset E-MTAB-6701 from EBI ArrayExpress, containing scRNA seq data of 6 placental samples and 2 peripheral blood samples from the same donor. Human placenta samples were obtained from the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR, http://www.hdbr.org). ScRNA seq was performed with droplet-based encapsulation (using the 10x Genomics Chromium system) and the sequencing data were aligned and quantified using the Cell Ranger Single-Cell Software Suite (version 2.0, 10x Genomics against the GRCh38 human reference genome provided by Cell Ranger.
DOI: 10.17632/4t8xr72k6t
title: FACTORS AFFECTING ON CONSUMER'S PERCEPTION TOWARDS DIGITAL PAYMENT IN NEPAL

description: The primary data has been collected through structured questionnaire from Nepalese market. 6 point Likert scale has been used to collect the primary data.