Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
This record provides the reproducibility materials for the statistical analyses reported in the preprint “TIDE: Tractography-Informed Dose Estimation for individualised TMS intensity.” It complements TIDE v1.30.0 by providing analysis-ready derived data and standalone Python code for reproducing the manuscript-level analyses for objectives 1 and 2. The TIDE source code is archived separately. The deposit contains two independent archives. objective_1_zenodo.zip contains the behavioural-validation analyses based on 19 participants and six frontal aslant tract stimulation sites. The workflow produces dose-recommendation summaries, pooled and site-specific dose–behaviour analyses, multiple-comparison corrections, control analyses, and the manuscript figures associated with this objective. objective_2_zenodo.zip contains the multi-bundle variability analyses based on 6,492 evaluated grid poses from 27 participants and 13 target bundles. The workflow performs participant-by-bundle reduction, bundle-level variability and stimulation-efficiency summaries, boundary analyses, and data-quality checks. Each archive contains de-identified derived CSV data, Python analysis scripts, pinned software requirements, SHA-256 input checksums, software tests, and a complete README with installation and execution instructions. Subject labels use consistent numeric codes of the form sub-NN. Original subject labels and the private linkage key are not included. Running python scripts/run_all.py generates the statistical tables, text summaries, and figures in a local results directory. Python 3.11 is recommended. TIDE v1.30.0 software archive: https://doi.org/10.5281/zenodo.22019737 GitHub repository: https://github.com/marcotag93/TIDE TIDE preprint: https://doi.org/10.64898/2026.08.20.746040 The software components contained in these archives are distributed under the GNU General Public License v3.0 or later, as specified in the LICENSE file included in each archive. TIDE is research software. It is not a medical device and must not be used for diagnosis, treatment planning, or clinical decision-making.
This publication proposes a definition and a classification of agile software development approaches and analyses ten software development methods that can be characterized as being "agile" against the defined criterion.
P. Abrahamsson, O. Salo, Jussi Ronkainen et al.· arXiv.org· 727 citations· ⚡54
The study shows that agile practices improve both informal and formal communication, but indicates that, in larger development situations involving multiple external stakeholders, a mismatch of adequate communication mechanisms can sometimes even hinder the communication.
M. Pikkarainen, Jukka Haikara, O. Salo et al.· Empirical Software Engineeri...· 401 citations· ⚡48
The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.
Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al.· Information and Software Tec...· 394 citations· ⚡54
The results show that the embedded industry has been able to apply agile methods in its development processes and that the appreciation of the agile methods and their individual practices appears to increase once adopted and applied in practice.
O. Salo, P. Abrahamsson· IET Software· 238 citations· ⚡9
Consequences of happiness and unhappiness that are beneficial and detrimental for developers' mental well-being, the software development process, and the produced artifacts are found.
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The Mobile-D approach is briefly outlined here and the experiences gained from four case studies are discussed, which helped develop an agile development approach for mobile application development.
P. Abrahamsson, Antti Hanhineva, H. Hulkko et al.· Conference on Object-Oriente...· 225 citations· ⚡18
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Microsoft Research Blog· microsoft.comOct 30, 2026
Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of real organizations, yet real enterprise data contains sensitive information that cannot be used for evaluation under any circumstances. The post From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence appeared first on Microsoft Research.
Microsoft Research Blog· microsoft.comOct 29, 2026
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
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