Our Work

This release contains the analysis code used to prepare the plots and tables included in Symplectic lattice gauge theories in the Grid framework: domain wall fermions and continuum extrapolations. Fo…

This release contains the analysis code used to prepare the plots and tables included in Symplectic lattice gauge theories in the Grid framework: domain wall fermions and continuum extrapolations. For more information see the README.md file.

This dataset contains behavioural and pupillometry data collected during an experiment investigating the temporal deployment of attention in response to rapid visual stimulation and its…

This dataset contains behavioural and pupillometry data collected during an experiment investigating the temporal deployment of attention in response to rapid visual stimulation and its modulation by the emotional content of successive targets. The experiment used a rapid serial visual presentation (RSVP) paradigm in which participants viewed a sequence of emotional faces containing two task-relevant targets (T1 and T2). The temporal separation between the two targets was manipulated across different lags, and the emotional content of the targets was varied. Participants reported the emotional category of the targets after each trial. Pupil responses were recorded during the task. The dataset provides the processed behavioural and pupil data used to examine how temporal separation and emotional content influence attentional processing. Participants viewed a rapid sequence of face stimuli presented using an RSVP paradigm. Each stimulus was presented for 100 ms, followed by a 50 ms blank interval, resulting in a stimulus onset asynchrony (SOA) of 150 ms. Two task-relevant targets, T1 and T2, were embedded within the RSVP stream. T1 appeared at serial positions 6–8, while T2 appeared at one of three temporal lags following T1: Lag 1, 2, 3 and 5. The target faces were either happy or angry, producing four possible target-pair conditions: HH: Happy T1 – Happy T2, HA: Happy T1 – Angry T2, AH: Angry T1 – Happy T2 and  AA: Angry T1 – Angry T2. The remaining stimuli in the RSVP stream were neutral faces. Trials included both two-target and single-target conditions. The dataset contains data from 37 participants, out of which 32 were included in the final analysis. Participants were between 18 and 24 years of age. Participant-level identifiers in the dataset are pseudonymised and do not contain directly identifying information. Pupil data were recorded using an EyeLink 1000 eye tracker at a sampling rate of 500 Hz, using the right eye. The recorded pupil signal was processed before analysis. Processing included blink handling, interpolation of missing samples, downsampling, and baseline correction. The resulting pupil time series were aligned to the RSVP onset and used for subsequent analysis. File Format: The data are provided in DataMatrix (.dm) format. DataMatrix is a Python-based data structure and file format designed for behavioural and experimental research data. The .dm files can be read using the DataMatrix Python package. The dataset is provided in its original .dm format to preserve the structure used during data preprocessing and analysis. Here is a direct link to DataMatrix Package

La gestion inclusive de la ressource en eau assure la collaboration et la cohérence des réponses apportées face aux crises hydriques. Ces stratégies sont mesurées en…

La gestion inclusive de la ressource en eau assure la collaboration et la cohérence des réponses apportées face aux crises hydriques. Ces stratégies sont mesurées entre les pratiques individuelles et collectives, au sein des territoires. Cette étude cherche à identifier les stratégies de gestion inclusive de la ressource en eau dans la SUGP Moyenne Casamance. Il s’agit de relever dans les projets et programmes l’ensemble des activités qui facilitent la participation de tous les acteurs à la gouvernance de l’eau. Pour cette étude, une méthodologie mixte a été utilisée. Elle s’est appuyée sur des entretiens avec 03 responsables de services déconcentrés, 03 autorités territoriales, 06 présidents de comités de gestion de l’eau, 03 présidentes de coopératives de productrices agricoles et 03 animateurs de terrain des projets. En complément, des enquêtes quantitatives ont été menées auprès de 149 maraîchers, producteurs de banane, agriculteurs et usagers domestiques afin d’évaluer leur niveau d’implication et leur connaissance des réformes liées à la gestion de l’eau. L’étude montre l’existence de 03 cadres de gestion de l’eau dans les communes visitées, avec des rôles et missions spécifiques. Grâce aux projets SEN’GIRE et USAID-GIRE, ces cadres ont été redynamisés et ont contribué, selon les acteurs, à promouvoir la GIRE territorial. Les activités de sensibilisation sur la GIRE et la réglementation de la police de l’eau menées permettent une appropriation locale globale. L’intervention des 9 a permis l’application d’une gestion collégiale et plus adaptée aux réalités locales, favorisant une réponse efficace aux besoins en eau des communautés, et aux inégalités socio environnementales. Toutefois, près de 88 % des enquêtés ne connaissent pas l’existence des cadres qui régulent la gestion de l’eau, 57 % affirment que les règles de gestion ne sont pas respectées, ce qui constitue une limite et nécessite une large diffusion de ce processus décisionnel.

Work with model files (setup, input, output) from the hydrological catchment model HYPE: Streamlined file import and export, standard evaluation plot routines, diverse post-processing and aggregation …

Work with model files (setup, input, output) from the hydrological catchment model HYPE: Streamlined file import and export, standard evaluation plot routines, diverse post-processing and aggregation routines for hydrological model analysis. The HYPEtools package is also archived at and can be cited in publications with Brendel et al. (2024) .

This archive provides the source code, fixed evaluation splits, aggregate predictions, and statistical analysis resources accompanying the study “MakamGraph: Evaluating Relational Representation…

This archive provides the source code, fixed evaluation splits, aggregate predictions, and statistical analysis resources accompanying the study “MakamGraph: Evaluating Relational Representations for Symbolic Turkish Makam Classification.” MakamGraph represents symbolic compositions as directed, duration-weighted pitch-transition graphs. The archive also includes a graph-aware Transformer that injects composition-specific same-pitch, forward-transition, reverse-transition, interval-proximity, and two-hop relational biases into self-attention. The experiments compare low-order statistical representations, matched and graph-aware Transformers, piece- and window-level graph-native models, transition controls, composer-disjoint evaluation, duplicate audits, input-length-matched comparisons, and a validated transition-bias ablation. The controlled evaluation subset contains 711 compositions from nine Turkish makam classes, with 79 compositions per class. The original SymbTr corpus is not redistributed. Users must obtain SymbTr separately under its original terms. Exact composition identities, original stratified fold assignments, composer-disjoint fold assignments, portable corpus-relative paths, aggregate results, and the package versions used in the final experiments are included to support reproducibility.

Presentation given by Irene Celino at the final event of the PERKS project, on September 23rd 2026, at the X-Lab of the Beko factory in Cassinetta di Biandronno, Varese, Italy