Share your research data

Files generated by Vensim Professional software (version 10.3.2, Ventana System Inc., Harvard, MA) containing raw data for causal loop diagram (CLD) representing the conceptual model of feeding behavior. Figure 1. Causal loop diagram (CLD) representing the meal structure in dairy cows. The reinforcing loop (R1, red) links meal size, duration and frequency, while a balancing loop (B) represents feedback mechanisms associated with feeding, contributing to meal start and termination. The two loops provide an aggregated representation of the interacting processes contributing to the daily feeding pattern. Dashed arrows indicate variables that can be estimated from the three measurable variables, and double slashes indicate delays. Figure 2. Causal loop diagram (CLD) representing the conceptual model of feeding behavior. The variables influencing those shown in Fig. 1 and determining daily meal pattern are grouped (clockwise) into physiology, metabolism and health status; environment and feed bunk management; feed characteristics; and animal traits. A total of 15 feedback loops were identified: R1: feeding behavior; R2: integration of orexigenic signals; R3: tissue mobilization and hepatic intake regulation; R4: propionate-mediated control of intake; R5: ruminal VFA (volatile fatty acids) dynamics; R6: animal physical activity and requirements; R7: ruminal passage rate; R8: competition for feeding space; B1: energy deficit regulation; B2: feed intake and ruminal VFA dynamics; B3: animal physical activity and energy regulation; B4: animal physical activity and feeding frequency; B5: fill effect; B6: management of the feed station; and B7: feed sorting. Among these, nine loops are highlighted as they represent key mechanisms controlling feed intake: physiological (R2, R3, R4, R5, B1), physical (B5), and psychogenic (R8, B6, B7) (Mertens, 1987). Numbers in parentheses next to the arrows refer to the explanation of each feedback link provided in Supplementary Table S3.

This dataset was generated as a result of the experiment described in the paper “Spillover effects of cooperative behaviour when switching tasks: the role of gender”. This is the updated version of the replication package, corresponding to the version of the paper forthcoming in the Journal of Economic Behavior & Organization (JEBO). It includes the data and the Stata code of the laboratory experiment and of the two supplementary online studies.

Numerical data for: Nanoscale mechanisms of mesocrystal formation during non-classical heterogeneous growth of manganese (hydr)oxides on ferrihydrite (Final version)

Anonymous survey data (N = 404) on perceived authenticity, digital escapism, social approval seeking, need for uniqueness and destination preference, Indonesia, 2026. A codebook is included.

Research Data: Role of Binomial Chirp Order in Laser-Driven Plasma Wakefield Excitation Description This dataset contains the numerical results supporting the figures and findings reported in the manuscript entitled "Role of Binomial Chirp Order in Laser-Driven Plasma Wakefield Excitation." The results were obtained using a relativistic cold-fluid model within the quasi-static approximation. The governing equations were solved numerically using a fourth-order Runge–Kutta method implemented in Fortran. Dataset Contents • Figure 1: Longitudinal and transverse distributions of the plasma wakefield for different binomial chirp orders. • Figure 2: Radial distribution of the maximum longitudinal wakefield for different chirp orders. • Figure 3: Spatial distributions of the normalized radial force. • Figure 4: Maximum normalized longitudinal wakefield as a function of the chirp parameter. • Figure 5: Two-dimensional distributions of the maximum wakefield as functions of the chirp parameter and radial position. • Figure 6: Normalized transverse momentum of plasma electrons as a function of the co-moving coordinate. Physical and Numerical Parameters The laser and plasma parameters are specified in the corresponding data files and source codes. The dataset includes the numerical results obtained for the chirp orders and chirp-parameter ranges considered in the manuscript. Data Format Numerical data are provided in plain-text DAT format. The first line of each file specifies the column names. Spatial coordinates, field quantities, and momentum values follow the normalization conventions defined in the manuscript. Correspondence For further information about the dataset, please contact the corresponding author.

Data and code to replicate results for the manuscript titled "Non-Linearities in the Response of Monetary Policy to Oil Supply News Shocks".

Supplementary data for the JAAD article "Reflectance Confocal Microscopy Improves Clinicopathologic Correlation in Facial Lentigo Maligna: A Prospective Real-Life Study"

Replication materials for "Analyst Individualism and the Readability of Investment Research: Evidence from China". The public archive contains four derived analysis-ready datasets, Stata estimation code, variable dictionaries, table-to-data mappings and reference results. Analyst names, report titles and bodies, emails and URLs are excluded. Analyst and source row/event identifiers are replaced with package-local labels; no identity crosswalk is distributed. Original named research inputs are retained separately by the authors and are not part of this public archive. The main full-model readability sample contains 60,326 observations from 2007–2022. Text and market analyses use their documented subsamples. The later market design contains 5,120 events, including 612 isolated events, from 2009–2022. Table 11 uses an earlier event design; Tables 12–13 use the later two-component readability design. See the README and table mapping for these distinctions. A Stata rerun of 44 models matched 679 available reference coefficient rows, standard errors and p values within 0.000002. The package also documents the check following identifier replacement. Optional selection-weighted models are supplied separately and were not part of the 44-model rerun. Construction scripts are provided as references and require upstream files and path configuration. The principal data sources are CNRDS and CSMAR; name-character frequency references are derived from ChineseNames. The depositor has confirmed permission to redistribute the research data and code.

SDS-PAGE, Western blot, MS data, cryo-EM, spectral assays, cell bioassays

Le Val-d'Oise (95) compte 85 centres de contrôle technique dans l'annuaire national de la DGCCRF, répartis dans 44 communes (extraction du 29/10/2026). L'extrait régional publié sur le portail de la région Île-de-France en compte 81 pour le département. Les deux chiffres sont donnés tels quels, sans correction. Fichiers : - centres_controle_technique_95_2026-10-29.csv : 85 centres du département dans l'annuaire national (code postal, commune, catégories de véhicules, énergies). Les noms, adresses et SIRET restent dans la source. - communes_95_centre_le_plus_proche_2026-10-29.csv : 48 communes du Val-d'Oise (code INSEE, nombre de centres dans la commune, commune du centre le plus proche, distance à vol d'oiseau en km). 35 de ces communes ont au moins un centre sur leur territoire. Séparateur ";", encodage UTF-8. Sources : DGCCRF, Annuaire des centres de contrôle technique (data.economie.gouv.fr), version du 29/10/2026 ; DGCCRF, Annuaire des centres de contrôle technique franciliens (data.iledefrance.fr), version du 28/10/2026. Licence des sources : Licence Ouverte v2.0 (Etalab), compatible avec CC BY 4.0. Jeu préparé par O'PAREBRISE 95 (IMK AUTOS SAS, Franconville), garage de vitrage automobile. English summary: number of vehicle inspection centres (contrôle technique) per municipality in the Val-d'Oise department (France), derived from the official DGCCRF directory, with the nearest centre and straight-line distance for 48 municipalities.