Our Work

New: Facility Allocation engine RunFacilityAllocation() finds optimal locations for new facilities among candidate sites — UNA's take on location-allocation. Three problem types: max_access — site p …

New: Facility Allocation engine RunFacilityAllocation() finds optimal locations for new facilities among candidate sites — UNA's take on location-allocation. Three problem types: max_access — site p new facilities to maximize demand-weighted access to the nearest open facility (ArcGIS: Maximize Attendance) min_facilities — fewest facilities covering all coverable demand (ArcGIS: Maximize Coverage + Minimize Facilities) max_patronage — maximize total trips under the gravity-cap participation model, with Huff-split per-facility patronage and optional facility attractiveness (≈ ArcGIS: Maximize Market Share) Existing facilities can be pinned open via a column on the candidates layer; the default run (fa_new_facilities = 0) evaluates access or patronage of the existing configuration. Deterministic greedy solver (near-optimal, any scale) or exact MILP (fa_solver="exact", scipy/HiGHS, automatic greedy fallback). Full impedance support: custom edge costs, elevation, turns, obstacles. Outputs join onto the demand and candidates layers, plus a selected-facilities layer that chains directly into RunFlow(). Batch support via RunBatch("facility_allocation", ...). Tutorial 5 (Cambridge after-school centers, data included in docs/Boston/): https://urban-network-analysis.readthedocs.io/en/latest/tutorials/tutorial_5_facility_allocation.html Also in this release about() reports version and last-commit date of the installed copy min_facilities: zero-weight demand never forces coverage (consistent greedy/exact) Example driver examples/UNA_FacilityAllocation.py (siting → flow chaining) Updating conda activate una pip install --upgrade git+https://github.com/City-Form-Lab/urban_network_analysis.git Full changelog: https://urban-network-analysis.readthedocs.io/en/latest/changelog.html

A CLI pipeline that attaches every edition of the Scottish Index of Multiple Deprivation (2004 to 2020v2), its domain ranks and bands and the Urban Rural Classification to the NRS Scottish Postcode Di…

A CLI pipeline that attaches every edition of the Scottish Index of Multiple Deprivation (2004 to 2020v2), its domain ranks and bands and the Urban Rural Classification to the NRS Scottish Postcode Directory and Scottish Statistics Postcode Lookup, from hash-pinned public sources. Column-level provenance: https://mtinti.github.io/postcode-simd/. The pinned open-licence sources are archived in a separate Zenodo record; the NRS postcode products are cited, not redistributed.

Mazkur maqolada kichik biznes va xususiy tadbirkorlik sohasining raqobatbardoshlik salohiyati hamda moliyaviy barqarorligini baholashning statistik uslubiyoti tadqiq etilgan. Kichik biznes va xususiy …

Mazkur maqolada kichik biznes va xususiy tadbirkorlik sohasining raqobatbardoshlik salohiyati hamda moliyaviy barqarorligini baholashning statistik uslubiyoti tadqiq etilgan. Kichik biznes va xususiy tadbirkorlik mamlakat iqtisodiyotining muhim tarkibiy qismi sifatida ish o‘rinlari yaratish, aholi daromadlarini oshirish va mintaqaviy iqtisodiy rivojlanishni ta’minlashda alohida o‘rin tutadi, shu sababli uning raqobatbardoshlik salohiyati va moliyaviy barqarorligini statistik jihatdan to‘g‘ri baholash muhim ilmiy-amaliy ahamiyat kasb etadi. Tadqiqotda raqobatbardoshlik salohiyati va moliyaviy barqarorlikni baholashga qo‘llaniladigan statistik usullar — ko‘rsatkichlar tizimi usuli, reyting baholash usuli, klaster tahlili va diskriminant tahlil — tizimli o‘rganilgan hamda ularning qo‘llanilish imkoniyatlari qiyosiy tahlil qilingan. Tadqiqot natijalari kichik biznes subyektlarining moliyaviy barqarorligini baholashda bir qator o‘zaro bog‘liq ko‘rsatkichlar majmuasidan — likvidlik, moliyaviy mustaqillik, aylanma mablag‘lar bilan ta’minlanganlik va rentabellik ko‘rsatkichlaridan — foydalanish zarurligini ko‘rsatadi. Olingan xulosalar asosida kichik biznes va xususiy tadbirkorlik sohasida statistik monitoring tizimini takomillashtirish bo‘yicha amaliy takliflar ishlab chiqilgan.

The Mission of TerraEnVision 2024 Our planet is undergoing profound changes as a result of human activities. Scientific knowledge of our environment is continuously expanding, providing new insights i…

The Mission of TerraEnVision 2024 Our planet is undergoing profound changes as a result of human activities. Scientific knowledge of our environment is continuously expanding, providing new insights into environmental processes, rates of change, emerging threats, and associated risks. Yet, despite this growing knowledge, the challenges we face are evolving faster than the solutions currently available. Finding feasible and viable pathways towards a society that operates within planetary boundaries requires collaboration across disciplines and sectors. Scientists, policymakers, practitioners, industry, and society must work together to develop and implement solutions that address the complex environmental and societal challenges of our time. TerraEnVision 2024 aims to provide a platform for identifying, discussing, and advancing solutions to these challenges. The conference will promote the exchange of scientific knowledge, innovative solutions from industry, and insights from policy and practice, fostering interdisciplinary collaboration and meaningful networking. A central objective of TerraEnVision is to bring together scientists and stakeholders who share common goals and address the same societal challenges, but who approach them from different perspectives and professional backgrounds. By connecting people, knowledge, experience, and ideas, we aim to create new opportunities for collaboration and accelerate the transition towards a more sustainable and resilient society. The conference will also strengthen the connection between scientific research and major international policy frameworks and initiatives, including the United Nations Sustainable Development Goals (SDGs), the UN Climate Change Conferences (COP), the European Green Deal, and the Common Agricultural Policy (CAP). TerraEnVision 2024 will be structured around a series of themes linked to the major transitions shaping our society. Each theme will begin with two 20-minute plenary keynote presentations, followed by an interactive discussion. These plenary sessions will be complemented by a range of parallel sessions, providing opportunities for deeper discussion, knowledge exchange, and networking. Importantly, TerraEnVision is not a conference exclusively for scientists. We particularly welcome people from outside academia who are actively involved in the transition towards climate change mitigation and adaptation, sustainable cities and agriculture, a circular economy, and the sustainable use and management of natural resources and ecosystems. By bringing together different forms of knowledge and expertise, TerraEnVision seeks to bridge the gap between science, policy, practice, and society and to contribute to the development of practical, innovative, and sustainable solutions for the future of our planet. Dr. Saskia KeesstraChair of the TerraEnVision Organizing CommitteeSenior Researcher in Sustainable Land and Water ManagementThe Netherlands          

Code, partition manifests and per-image predictions supporting the audit and leakage-controlled re-evaluation of the 4,217-image Eye Disease Retinal Images collection.   Contents: the provenance …

Code, partition manifests and per-image predictions supporting the audit and leakage-controlled re-evaluation of the 4,217-image Eye Disease Retinal Images collection.   Contents: the provenance and integrity audit; the manifests defining every evaluation arm image by image (image-level, patient-grouped, size-matched, source-matched, the common test set and the six leave-one-source-out splits); the training and evaluation code; stored per-image class probabilities for every run; the shortcut probes; and the visual adjudication verdicts for all 335 cross-label near-duplicate candidates.   The image collection itself is not redistributed here. It is available at https://www.kaggle.com/datasets/python16/eye-disease-retinal-images and the manifests reference it by relative path.

Anonymised replication package for a paper under double-anonymous review. Contains the adaptive tracing controller, the trace replay simulator and its byte ledger, every analysis script, the trained m…

Anonymised replication package for a paper under double-anonymous review. Contains the adaptive tracing controller, the trace replay simulator and its byte ledger, every analysis script, the trained models with their conformal references, and the per-run per-policy results from which every table and figure in the paper is regenerated.The tables regenerate byte-identically from the included results with a single command; see README.md. Audit scripts are included that re-derive every quoted number from the data rather than comparing against a stored table.The derived per-(window, container) measurements for all 304 recorded runs (~22 GB) are published as separate archives in this record. They are needed only to re-run the replay from scratch. The ~8 TB of raw kernel traces behind them are not redistributed; the derived measurements are the level at which replay operates, so what is published here is sufficient to reproduce every policy comparison in the paper.

У статті досліджено сучасні теоретичні та практичні аспекти використання цифрових двійників у промисловості та інженерії в умовах цифрової трансформації виробничих систем. Визначено, що концепція цифр…

У статті досліджено сучасні теоретичні та практичні аспекти використання цифрових двійників у промисловості та інженерії в умовах цифрової трансформації виробничих систем. Визначено, що концепція цифрового двійника (Digital Twin, DT) є однією з ключових технологій Industry 4.0, оскільки забезпечує інтеграцію фізичного та цифрового середовищ через неперервний обмін даними, аналітичне моделювання та інтелектуальну підтримку прийняття рішень. Проаналізовано основні архітектурні компоненти DT, серед яких особливе значення мають промисловий Інтернет речей, алгоритми штучного інтелекту, хмарні та периферійні обчислення, мережі 5G, а також засоби віртуальної та доповненої реальності. У роботі розглянуто сучасні підходи до інтеграції цифрових двійників із фізико-математичними моделями та методами машинного навчання. Встановлено, що використання гібридних фізико-статистичних моделей дозволяє підвищити точність прогнозування технічного стану обладнання та забезпечити адаптивність моделей до змін умов експлуатації. Досліджено особливості використання цифрових двійників у енергетиці, важкій промисловості, транспортній інфраструктурі та будівництві. Показано, що застосування DT сприяє оптимізації виробничих процесів, підвищенню енергоефективності та зниженню експлуатаційних витрат. Водночас встановлено, що масштабне впровадження цифрових двійників стримується низкою технічних і організаційних проблем, серед яких складність інтеграції різнорідних даних, недостатня стандартизація архітектур, проблеми масштабованості, валідації моделей та забезпечення кібербезпеки. Зроблено висновок, що цифрові двійники поступово перетворюються на фундаментальний елемент сучасної цифрової промисловості та інтелектуального управління складними інженерними системами. Перспективи подальших досліджень пов'язані з розвитком когнітивних цифрових двійників, удосконаленням гібридних моделей та створенням універсальних стандартів взаємодії й валідації DT-систем у промисловому середовищі.

An in-context tabular classifier for corporate credit risk, pretrained exclusively on synthetic data and never on real tables. Prediction is a single forward pass with the user's table supplied as con…

An in-context tabular classifier for corporate credit risk, pretrained exclusively on synthetic data and never on real tables. Prediction is a single forward pass with the user's table supplied as context; there are no gradient steps at fit time and no per-dataset tuning.The repository is organised around a numbered measurement log and a claims ledger that record retractions and superseded results as prominently as confirmations. Measured externally on TabArena it places 94th of 95; on real corporate-default panels its calibration is consistently among the best measured while its discrimination consistently loses to tuned gradient boosting. Both facts are reported together.Code and the published binary checkpoint are Apache-2.0.

Data and analysis code for: Peripersonal space maps onto future hand- and tool-mediated interactions, Johanna K. Theuer and Martin V. Butz, 2026 We conducted two experiments investigating the anticipa…

Data and analysis code for: Peripersonal space maps onto future hand- and tool-mediated interactions, Johanna K. Theuer and Martin V. Butz, 2026 We conducted two experiments investigating the anticipatory crossmodal congruency effect (aCCE). We aimed to investigate whether 1) this effect can be substantiated in real object interactions, extending a previous paradigm using VR or pantomimic interactions, and 2) given peripersonal hand space may be remapped onto a grasping tool during a grasp, the aCCE may be found in tool-mediated interaction. Preregistrations of this work can be found under:https://doi.org/10.17605/OSF.IO/EV9DN (Experiment 1)https://doi.org/10.17605/OSF.IO/9XMCB (Experiment 2)