Find research datasets worth reusing

opencc-by-4.0Sep 2022View details →

Cloud computing is one of the most popular and sophisticated technologies adopted by organizations worldwide. Some world-leading organizations enhance their efficiency and effectiveness by using cloud computing technology. Working from home (WFH) has been a popular trend among organizations during the coronavirus (COVID-19) pandemic. The COVID-19 saw a breakthrough in work cultures and environments where working from home was a remarkable success in remote working environments, despite being a rare phenomenon in Sri Lanka. Yet, it is argued that the deployment of work from home has not been effective among Sri Lankan business organizations due to a lack of IT infrastructure, facilities, and knowledge. The purpose of the study is to investigate the impact of cloud computing, embracing the service models (Infrastructure as a Service, Platform as a Service, and Software as a Service) as theoretical lenses and testing the COVID-19 as the moderator. The study has been conducted based on a deductive approach and adopted a stratified random sampling method. The sample consisted of 384 IT employees among those who had experienced working from home. The study utilized multiple regression and found that cloud computing service models significantly impact work from home with the moderating effect of COVID-19.

Cloud computing is one of the most popular and sophisticated technologies adopted by organizations worldwide. Some world-leading organizations enhance their efficiency and effectiveness by using cloud computing technology. Working from home (WFH) has been a popular trend among organizations during the coronavirus (COVID-19) pandemic. The COVID-19 saw a breakthrough in work cultures and environments where working from home was a remarkable success in remote working environments, despite being a rare phenomenon in Sri Lanka. Yet, it is argued that the deployment of work from home has not been effective among Sri Lankan business organizations due to a lack of IT infrastructure, facilities, and knowledge. The purpose of the study is to investigate the impact of cloud computing, embracing the service models (Infrastructure as a Service, Platform as a Service, and Software as a Service) as theoretical lenses and testing the COVID-19 as the moderator. The study has been conducted based on a deductive approach and adopted a stratified random sampling method. The sample consisted of 384 IT employees  among those who had experienced working from home. The study utilized multiple regression and found that cloud computing service models significantly impact work from home with the moderating effect of COVID-19.

opencc-zeroApr 2024View details →

Data from: A theoretical model for host-controlled regulation of symbiont density

There is growing empirical evidence that hosts (such as insects and corals) actively control the density of their mutualistic symbionts according to their requirements. Such active regulation can be facilitated by compartmentalisation of symbionts within host tissues, which confers a high degree of control of the symbiosis to the host. Here, we build a general theoretical framework to predict the underlying ecological drivers and evolutionary consequences of host-controlled endosymbiont density regulation for a mutualistic association between a host and a compartmentalised, vertically transmitted symbiont. Building on the assumption that the costs and benefits of hosting a symbiont population increase with symbiont density, we use state-dependent dynamic programming to determine an optimal strategy for the host, i.e., that which maximises host fitness, when regulating the density of symbionts. Simulations of active host-controlled regulation governed by the optimal strategy predict that the density of the symbiont should converge to a constant level during host development, and following perturbation. However, a similar trend also emerges from alternative strategies of symbiont regulation. The strategy which maximises host fitness also promotes symbiont fitness compared to alternative strategies, suggesting that active host-controlled regulation of symbiont density could be adaptive for the symbiont as well as the host. Adaptation of the framework allowed the dynamics of symbiont density to be predicted for other host-symbiont ecologies, such as for non-essential symbionts, demonstrating the versatility of this modelling approach.

opencc-by-4.0Feb 2023View details →

Datasets and R script to replicate the theoretical modeling from the article entitled Multiple hosts, multiple impacts: the role of vertebrate host diversity in shaping mosquito life history and pathogen transmission

Datasets and R script to replicate the theoretical modeling from the article entitled " Multiple hosts, multiple impacts: the role of vertebrate host diversity in shaping mosquito life history and pathogen transmission" by Vantaux A., Moiroux N., Dabire K. R., Cohuet A., Lefevre T. 2023

opencc-by-4.0Mar 2023View details →

Supporting information for "Kinetics of CN(v=1) reactions with butadiene isomers at low temperature by cw-Cavity Ringdown in a pulsed Laval flow with theoretical modelling of rates and entrance channel branching

This file contains the master equation inputs for all the reactions studied, as well as all the details on stationary points and VRC-TST fluxes necessary to reproduce the simulations.

opencc-zeroMay 2023View details →

The role of chloroplast movement in C4 photosynthesis: A theoretical analysis using a 3-D reaction-diffusion model for maize

Chloroplast movement within mesophyll (M) cells in C4 plants is hypothesized to enhance the CO2 concentrating mechanism (CCM), but this is difficult to verify experimentally. A three-dimensional (3-D) leaf model can help analyze how chloroplast movement influences the operation of CCM. The first volumetric reaction-diffusion model of C4 photosynthesis that incorporates: detailed 3-D leaf anatomy, light propagation, ATP and NADPH production and CO2, O2 and bicarbonate concentration driven by diffusional and assimilation/emission processes, was developed and implemented for maize leaves to simulate various chloroplast movement scenarios within M cells: the movement of all M chloroplasts towards bundle-sheath (BS) cells (aggregative movement) and movement of only those of interveinal M cells towards BS cells (avoidance movement). Light absorbed by bundle-sheath (BS) chloroplasts relative to M chloroplasts increased in both cases. Avoidance movement decreased light absorption by M chloroplasts considerably. Consequently, total ATP and NADPH production and net photosynthesis rate increased for aggregative movement and decreased for avoidance movement case compared to the default case of no chloroplast movement at high light intensities. Leakiness increased in both chloroplast movement scenarios due to the imbalance in energy production and demand in M and BS cells. These results suggest the need to design strategies for coordinated increases in electron transport and Rubisco activities for an efficient CCM at very high light intensities.

opencc-by-4.0Jun 2023View details →

Theoretical and numerical comparison of quantum- and classical embedding models for optical spectra

This repository contains the files for the computational study on "Theoretical and numerical comparison of quantum- and classical embedding models  for optical spectra". The repository is organized into different folders as described below: ==================================================================================================== 1_pna This folder contains the configuration structures for p-nitroaniline extracted from the Molecular Dynamics (MD) simulations in *.xyz format that were used for any further calculations. ==================================================================================================== 2_pftaa This folder contains the configuration structures for pentameric formyl thiophene acetic acid extracted from the Molecular Dynamics (MD) simulations in *.xyz format that were used for any further calculations. ==================================================================================================== We acknowledge funding by the German Research Foundation (DFG) through the Emmy Noether Young Group Leader Programme (CK, project KO 5423/1-1), The Villum Foundation, Young Investigator Program (EDH, grant no. 29412), the Swedish Research Council (EDH, grant no. 2019-04205), and Independent Research Fund Denmark (EDH, grant no. 0252-00002B and grant no. 2064-00002B) for support.

publicMay 2023View details →

The role of chloroplast movement in C4 photosynthesis: A theoretical analysis using a 3-D reaction-diffusion model for maize

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publicSep 2025View details →

Data from: A proof-of-concept experimental-theoretical model to predict pesticide resistance evolution

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publicApr 2024View details →

Data from: A theoretical model for host-controlled regulation of symbiont density

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dryad32/100

Ions release from hydroxyapatite and substituted hydroxyapatites in different immersion liquids: In vitro experiments and theoretical modelling study

The multi-substituted hydroxyapatites (ms-HAPs) are currently gaining more consideration due to their multifunctional properties and biomimetic structure, owning thus an enhanced biological potential in orthopedic and dental applications. In this study, nano hydroxyapatite (HAP) substituted with multiple cations (Sr2+, Mg2+ and Zn2+) for Ca2+ and anion (SiO44-) for PO43- and OH-, specifically HAPc-5%Sr and HAPc-10%Sr (where HAPc is HAP-1.5%Mg-0.2%Zn-0.2%Si), both lyophilized noncalcined and lyophilized calcined, were evaluated for their in vitro ions release. These nanomaterials were characterized by SEM, FE-SEM and EDX, as well as by AFM images and by surface-specific areas and porosity. Further, the release of cations and of phosphate anions were assessed from nano HAP and ms-HAPs, both in water and in simulated body fluid (SBF), in static and simulated dynamic conditions, using inductively coupled plasma optical emission spectrometry (ICP-OES). The release profiles were analyzed and the influence of experimental conditions was determined for each of the six nanomaterials and for various periods of time. The pH of the samples soaked in the immersion liquids was also measured. The ions release mechanism was theoretically investigated using the Korsmeyer-Peppas model. The results indicated a mechanism principally based on diffusion and dissolution, with possible contribution of ion exchange. The surface of ms-HAP nanoparticles is more susceptible to dissolution into immersion liquids due to the lattice strain provoked by simultaneous multi-substitution in HAP structure. According to the findings, it is rational to suggest that both materials HAPc-5%Sr and HAPc-10%Sr are bioactive and can be potential candidates in bone tissue regeneration.

opencc-zeroDec 2020View details →

opencc-zeroApr 2016View details →

Data file for the paper "General Models for the Electrochemical Hydrogen Oxidation and Hydrogen Evolution Reactions – Theoretical Derivation and Experimental Results Under Near Mass-Transport Free Conditions", J. Phys Chem. C., 2016, DOI:10.1021/acs.jpcc.6b00011

The data in this folder is supplementary information for the paper: Anthony Kucernak and Christopher Zalitis, "General Models for the Electrochemical Hydrogen Oxidation and Hydrogen Evolution Reactions – Theoretical Derivation and Experimental Results Under Near Mass-Transport Free Conditions", J. Phys Chem. C., 2016, DOI:10.1021/acs.jpcc.6b00011 The information is © Anthony Kucernak A description of the models used in these files is provided in that paper. Below is a description of the files Experimental Data.xlsx   -  This file contains the experimental data used to produce figures 6 and 7 in the aforementioned paper Model.xlsx   -  This file contains verified versions of the Heyrovsky-Volmer, Tafel-Volmer and Heyrovsky-Tafel-Volmer mechanisms developed in the paper mentioned above. These excel spreadsheets may be used to fit experimental data user the Solver function in Excel. Heyrovsky-Tafel.cdf, Heyrovsky-Tafel-Volmer.cdf, Tafel-Volmer.cdf, Heyrovsky-Volmer.cdf  -  These are "computable document format" files produced using Wolfram Mathematica. They allow easy and quick modification of model parameters to allow real-time exploration of the effect of the parameters on current density (as linear and Tafel plots), hydrogen coverage, Effective Tafel slope, and derived parameters. The CDF viewer is availble to download from the Wolfram site - www.wolfram.com

opennotspecifiedJan 2022View details →

Figure 1 in A theoretical composite model for population sex-specific shell size dynamics in Strombidae (Gastropoda, Neostromboidae)

Figure 1. Modelling male and females population distribution curves showing the mean size (μ) of each sex and the (1) Sex dependant factors: a) time to maturity; b) intra-male competition; c) femalespecific sexual selection; d) fecundity; (2) Inter-sex dependant factors: e) time to maturity; f) sex bias towards larger numbers of females; and (3) Population factors: g) environmental conditions; and h) universal size regulators that affect the size ratio between females and males.

openSep 2022View details →

Input data for Bayesian and information theoretic model selection and similarity analysis

This data serves as input to the codes found in the following repository https://github.com/MariaFMoralesOreamuno/Bayesian_Information_theoretic_model_selection.git

opencc-by-4.0Jun 2022View details →

Data access - Operando characterization and theoretical modelling of metal|electrolyte interphase growth kinetics in solid-state-batteries - part I: experiments

The zip file contains XPS and EIS data used in parts 1 and 2 of the publication entitled: "New insights into the kinetics of metal|electrolyte interphase growth in solid-state-batteries via an operando XPS analysis" Folders description:  - "XPS" contains three subfolders with the XPS data and fitting models (in .vms format, CasaXPS) corresponding to the reference Na metal sample, the Na|NZSPas interface and Na|NZSPpolished interface - "EIS" contains two subfolders with the EIS data from the Na|NZSPas and Na|NZSPpolished symmetrical cells. The raw data is stored as .mpr files (EC-lab), and the fitted data is stored as .eis3 files (RelaxIS)

opencc-by-4.0Jun 2024View details →

Replication data for the paper "Leveraging Large Language Models for Comprehensive Psychological Analysis: Insights from Four Theoretical Frameworks"

This is a replication data for the paper titled "Leveraging Large Language Models for Comprehensive Psychological Analysis: Insights from Four Theoretical Frameworks" submitted for a blind review. Abstract The rapid advancement of generative Artificial Intelligence (AI) has significantly transformed various research domains. This paper introduces a novel, fully automated methodology for applying Large Language Models (LLMs) to psychological text analysis. The approach includes prompt design for zero-shot and few-shot learning, model internal consistency analysis, autonomous machine evaluation, and additional human validation. Applied to four psychological theories—Self-Determination Theory, the Big Five Personality Traits, Psychological Well-being, and Cognitive Behavioral Therapy—this methodology is tested on a dataset of 25,780 emails written by a senior executive (called Person X) over 16 years. The analysis involves extracting psychological characteristics from the emails and regressing these characteristics against personal, professional, and environmental factors. The results demonstrate that the methodology provides unique insights into the examined psychological theories, offering a detailed understanding of how various factors influence psychological states and traits over time. This research highlights the potential of LLMs in capturing and analyzing complex psychological patterns in large text corpora, contributing a robust framework for future studies and practical applications in psychological assessment and intervention. The findings underscore the transformative impact of generative AI in psychological research, opening new avenues for understanding human behavior through advanced language models. The zipped file contains five csv files: <ol> <li>Email_classification-csv: LLM (GPT-3.5 Turbo) classification of 25,780 emails for four psychological theories: SDT, Big Five, PWB and CBT.</li> <li>SDT_regression_data.csv</li> <li>Big_Five_regression_data.csv</li> <li>PWB_regression_data.csv</li> <li>CBT_regression_data.csv</li> </ol> For 2-5 files the dependent variable is monthy percentage share of emails the were assigned a given value for categories of one of the four psychological theories analyzed.  Linear regression model has been applied, where dependent variable is the percentage of emails in a specified category that assigned a specific value in this category. For example in Big Five Traits Model, for the Openness category, for each month we calculated percentage of emails that exhibit High or Low openness, or None if the content of the email does not provide enough information to assess whether the specific need is relevant. Two dependent variables were created: Openness-high and Openness-low and regressed on all independent variables. Regressions were not run for the None values. Descriptions of independent variables: - income_index: Person X salary income and consulting fees in a given month, normalized to [0,1]. - card_spending: Person X credit card expenditures in a given month, normalized to [0,1]. - abroad_far: dummy variable set to 1 for months when Person X worked in Central Asia - abroad_near: dummy variable set to 1 when Person X worked in other EU country - death_1_war: variable set to 1 in a month when Person X’ farther in law passed away. In the same month Russia invaded Ukraine. The variable was set to .75 in the following month, and to .5 in the month after that. - death_2: variable set to 1 in a month when Person X’ mother passed away. The variable was set to .75 in the following month, and to .5 in the month after that. - court_case: dummy variable set to 1 for months with the emotionally engaging inheritance court case involving other family members. - BIG4_partner: dummy variable set to 1 for months when Person X worked as a partner in BIG4 accounting firm, which resulted in adopting a professional activity sharply different from the usual Person X habits. - AI_company: dummy variable set to 1 for months when Person X worked as C-level executive at a company specializing in artificial intelligence. - elections: dummy variable set to 1 for months when Person X unsuccessfully run in parliamentary elections - covid_lockdown: dummy variable set to 1 for month where Polish government imposed tough measures during two covid lockdowns. - no_receive: number of different email recipients each month, normalized to [0,1]. - avg_length: average number of words in emails sent each month, normalized to [0,1].             While the email data was collected for January 2008 – March 2014 period, financial data was available from October 2009. There were some months where no emails with more than 10 words were sent, yielding 166 monthly observations used for regressions, before removing outliers.             Independent variables were tested for multicollinearity, outlier months were removed, regressions were estimated with robust standard errors, and a range of standard tests were conducted for normality and autocorrelation of residuals, confirming good statistical properties of estimated models. Due to privacy concerns, the email texts cannot be publicly shared. However, the classifications of psychological categories derived from the email texts, along with all other relevant data, are made publicly available in this open access repository, with the consent of email author.

opencc-by-4.0Jun 2024View details →

A Unified Theoretical Framework for the Synergistic Integration of Transformers and Diffusion Models

This paper introduces a novel, comprehensive theoretical framework for the synergistic integration of Transformer and Diffusion models, two paradigms that have independently revolutionized machine learning. We establish a fundamental correspondence between these models through a unified representation and a generalized dynamics equation, bridging the gap between their seemingly disparate architectures. Our key contributions include: (1) A unified mathematical formulation that encapsulates both Transformer and Diffusion processes; (2) A novel Diffusion-Enhanced Attention mechanism that incorporates Diffusion dynamics into Transformer attention; (3) Rigorous theoretical analyses including convergence guarantees, generalization bounds, and sample efficiency proofs for the integrated model. We provide detailed mathematical derivations and empirical validations across various tasks, demonstrating significant improvements over standalone models and existing hybrid approaches. This work lays the foundation for a new class of AI models that leverage the strengths of both paradigms, potentially leading to more powerful, efficient, and versatile AI systems. Our framework opens up new avenues for research in areas such as enhanced language modeling, advanced image generation, and multi-modal learning, paving the way for the next generation of AI technologies.

opencc-by-4.0Sep 2024View details →

Testing a Theoretical Model of Parent-Child Relationship on Sleep Problem Mediated by Problematic Smartphone Usage and Nomophobia

The dataset is derived from 672 senior high schools’ students from six schools in Yogyakarta city, Indonesia. The dataset provides important information about data of parent-child relationships, problematic smartphone usage, nomophobia, and sleep problems.

opencc-by-4.0Aug 2021View details →

Impacts of concentrated seepage flow on suffusion development in cohesionless soil: insight from a theoretical model

The uploaded file is the original data of a paper submitted to the journal of " Water Resources Research"