Our Work

This paper presents a comprehensive study of Tian's $\alpha$-invariant on weighted Grassmannians $G_w(p,p+q)$ and constructs explicit examples of special Lagrangian submanifolds from Calabi-Yau hypers…

This paper presents a comprehensive study of Tian's $\alpha$-invariant on weighted Grassmannians $G_w(p,p+q)$ and constructs explicit examples of special Lagrangian submanifolds from Calabi-Yau hypersurfaces in weighted Grassmannians. We develop a systematic framework using group actions to reduce the analysis to diagonal matrices, construct an explicit extremal function $\Psi_w$, and compute the $\alpha$-invariant for $G_w(2,4)$ with weights $(1,1,1,1,1,m)$, obtaining the explicit formula $\alpha(G_w(2,4)) = \min\{1/2, 1/m\}$. Furthermore, we generalize the construction of special Lagrangian submanifolds from $G_{2,4}\C$ to $G_{2,5}\C$ and $G_{3,6}\C$. We prove that hypersurfaces $X_m \subset G_{2,5}\C$ and $Y_m \subset G_{3,6}\C$ defined by weighted homogeneous polynomials have vanishing first Chern class and thus are Calabi-Yau manifolds. The real loci $L_m = X_m^{\R}$ and $L_m^{(3,6)} = Y_m^{\R}$ are shown to be special Lagrangian submanifolds diffeomorphic to circle bundles over $\R\PP^4$ and $\R\PP^5$, respectively. For generic $m$, these are spherical space forms $S^5/\Z_{5m}$ and $S^8/\Z_{6m}$ (with parity-dependent modifications). A graphical illustration of the $\alpha$-invariant and tables of topological invariants are provided.

Every Queensland state and non-state school with its address, year levels, contacts, region, electorates and coordinates.This is the 2022-09-12 version of this dataset on publicdata.au, with 1,774 row…

Every Queensland state and non-state school with its address, year levels, contacts, region, electorates and coordinates.This is the 2022-09-12 version of this dataset on publicdata.au, with 1,774 rows and 38 fields. The same version is kept at https://publicdata.au/d/qld-school-details/v/2022-09-12/ in 12 formats, with every earlier version and a query API. Each Zenodo version of this record is one publicdata.au version.The data is published by Department of Education under CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. The licence requires this attribution:Department of Education, Queensland Government, State and non-state school details, sourced 3 October 2026, https://www.data.qld.gov.au/dataset/state-and-non-state-school-details, licensed under CC BY 4.0.This is an independent republication. The publisher has not endorsed this site.The rows are in data.parquet, data.csv, data.json and data.xlsx. schema.json describes the fields, and publicdata.json names the version, licence, attribution and the SHA-256 of the publisher's file.

Each amount of unclaimed money held by the Public Trustee of Queensland, with the owner's name, amount, sender and date received.This is the 2026-09-28 version of this dataset on publicdata.au, w…

Each amount of unclaimed money held by the Public Trustee of Queensland, with the owner's name, amount, sender and date received.This is the 2026-09-28 version of this dataset on publicdata.au, with 2,551,529 rows and 6 fields. The same version is kept at https://publicdata.au/d/qld-unclaimed-money/v/2026-09-28/ in 7 formats, with every earlier version and a query API. Each Zenodo version of this record is one publicdata.au version.The data is published by The Public Trustee of Queensland under CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. The licence requires this attribution:The Public Trustee of Queensland, Queensland Government, Unclaimed monies, sourced 3 October 2026, https://www.data.qld.gov.au/dataset/unclaimed-monies, licensed under CC BY 4.0.This is an independent republication. The publisher has not endorsed this site.The rows are in data.parquet and data.csv. schema.json describes the fields, and publicdata.json names the version, licence, attribution and the SHA-256 of the publisher's file.

Every pool safety inspector licensed by QBCC, with licence number, name, business address and licence grade.This is the 2024-09-02 version of this dataset on publicdata.au, with 501 rows and 5 fields.…

Every pool safety inspector licensed by QBCC, with licence number, name, business address and licence grade.This is the 2024-09-02 version of this dataset on publicdata.au, with 501 rows and 5 fields. The same version is kept at https://publicdata.au/d/qld-pool-safety-inspectors/v/2024-09-02/ in 9 formats, with every earlier version and a query API. Each Zenodo version of this record is one publicdata.au version.The data is published by Queensland Building and Construction Commission under CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. The licence requires this attribution:Queensland Building and Construction Commission, Queensland Government, Pool safety register, sourced 3 October 2026, https://www.data.qld.gov.au/dataset/poolsafetyregister, licensed under CC BY 4.0.This is an independent republication. The publisher has not endorsed this site.The rows are in data.parquet, data.csv, data.json and data.xlsx. schema.json describes the fields, and publicdata.json names the version, licence, attribution and the SHA-256 of the publisher's file.

Queensland properties whose pools have been issued pool safety certificates, with the date each was submitted.This is the 2024-09-02 version of this dataset on publicdata.au, with 113,800 rows and 11 …

Queensland properties whose pools have been issued pool safety certificates, with the date each was submitted.This is the 2024-09-02 version of this dataset on publicdata.au, with 113,800 rows and 11 fields. The same version is kept at https://publicdata.au/d/qld-pool-safety-certificates/v/2024-09-02/ in 9 formats, with every earlier version and a query API. Each Zenodo version of this record is one publicdata.au version.The data is published by Queensland Building and Construction Commission under CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. The licence requires this attribution:Queensland Building and Construction Commission, Queensland Government, Pool safety register, sourced 3 October 2026, https://www.data.qld.gov.au/dataset/poolsafetyregister, licensed under CC BY 4.0.This is an independent republication. The publisher has not endorsed this site.The rows are in data.parquet, data.csv, data.json and data.xlsx. schema.json describes the fields, and publicdata.json names the version, licence, attribution and the SHA-256 of the publisher's file.

Every Queensland property with a registered regulated swimming pool, by address and lot and plan, with its number of pools.This is the 2024-09-02 version of this dataset on publicdata.au, with 448,470…

Every Queensland property with a registered regulated swimming pool, by address and lot and plan, with its number of pools.This is the 2024-09-02 version of this dataset on publicdata.au, with 448,470 rows and 10 fields. The same version is kept at https://publicdata.au/d/qld-pool-safety-register-pools/v/2024-09-02/ in 9 formats, with every earlier version and a query API. Each Zenodo version of this record is one publicdata.au version.The data is published by Queensland Building and Construction Commission under CC BY 4.0, https://creativecommons.org/licenses/by/4.0/. The licence requires this attribution:Queensland Building and Construction Commission, Queensland Government, Pool safety register, sourced 3 October 2026, https://www.data.qld.gov.au/dataset/poolsafetyregister, licensed under CC BY 4.0.This is an independent republication. The publisher has not endorsed this site.The rows are in data.parquet, data.csv, data.json and data.xlsx. schema.json describes the fields, and publicdata.json names the version, licence, attribution and the SHA-256 of the publisher's file.

The proliferation of the Internet of Things (IoT) increases interconnectivity across homes, healthcare, manufacturing, transportation and other cyber-physical systems, while also expanding the attack …

The proliferation of the Internet of Things (IoT) increases interconnectivity across homes, healthcare, manufacturing, transportation and other cyber-physical systems, while also expanding the attack surface of those networks. This paper reports an implemented and evaluated explainable deep-learning detector for anomalies in IoT network traffic. The study uses the CICIoT2023 corpus of the Canadian Institute for Cybersecurity. After cleaning, label encoding, z-score normalisation fitted on the training partition only, Extra Trees feature selection and training-set class balancing, a stacked Gated Recurrent Unit (GRU) classifier was trained on sliding windows of length 10. The trained network performs 34-class traffic attribution and is also mapped to a binary benign-versus-anomalous decision. SHapley Additive exPlanations (SHAP) were computed after training to obtain global feature rankings and local explanations of individual alerts. On the held-out test set the implemented GRU attained 97.56% accuracy, 97.41% weighted precision, 97.56% weighted recall, 97.42% weighted F1-score and a Cohen kappa of 0.9736. Family-level analysis shows that flooding classes are detected reliably, whereas reconnaissance, spoofing, web-based and brute-force traffic remain the hardest minority groups. The same train/test split was used to train Random Forest, deep neural network, convolutional and long short-term memory baselines; the GRU obtained the strongest combined accuracy and weighted F1 among those models. Mean inference latency on the experimental workstation was 76 microseconds per flow for the classifier alone. The results support the combination of GRU temporal modelling and SHAP explanation for IoT intrusion analysis, while also documenting the hardware, sequence construction, class-wise errors and explanation cost that a deployment study must consider.  

This dataset contains the data, supplementary materials, and computational code supporting the study “A Dual-Driven DEMATEL-AISM Framework for Revealing the Structural Relationships of Ecologica…

This dataset contains the data, supplementary materials, and computational code supporting the study “A Dual-Driven DEMATEL-AISM Framework for Revealing the Structural Relationships of Ecological Product Value Realization in Marine Ranching.” The deposited materials include factor definitions and data documentation, zone-level observations of seven data-driven factors across 34 Chinese marine ranching demonstration zones during 2019–2022, descriptive statistics, anonymized information on the expert panel, expert questionnaires, intermediate DEMATEL–AISM matrices, and Python scripts used for the main computational procedures. The materials are provided to enhance the transparency and reproducibility of the study.

This paper establishes a synthesis between the Pythagorean angle lattice and the Omni-Metallic family, a four-parameter generalisation of the classical metallic means defined as the unique positive re…

This paper establishes a synthesis between the Pythagorean angle lattice and the Omni-Metallic family, a four-parameter generalisation of the classical metallic means defined as the unique positive real root of a prescribed polynomial. The arithmetic kernel of the Omni-Metallic side is the counting function that records the number of Universal Metallic representations of a positive integer. The Mellin transform of this kernel is evaluated in closed form as a combination of the Riemann zeta function at shifted arguments, an identity here called the Bridge Identity, and its finite part at the double pole yields an alternative expression for the circle constant. The Borel transform of the same kernel is evaluated at unity and yields an alternative expression for the base of the natural logarithm. A regularised infinite product over the kernel is computed by zeta regularisation and is expressed in terms of the Glaisher and Kinkelin constant. The Generalized Integer Value Theorem is proved for all admissible parameters, characterising exactly when a member of the Omni-Metallic family is a positive integer. A Quarter-Angle Bridge is proved, giving in exact and unconditional form the value of the lattice under quarter-angle projection for every primitive Gaussian integer, and identifying precisely when that value is a classical metallic mean of integer index. The Crown Identity connecting the Universal Metallic family to primitive Pythagorean triples is established. For the cubic projection an exact irreducibility criterion is obtained: the associated cubic is reducible over the rationals precisely when the generating Gaussian integer is itself a cube, and explicit reducible instances are exhibited. The integer values attained by the lattice are determined completely: they occur only at even projection indices, and the associated multiplicities are computed. A spectral decomposition over odd projection indices is stated as a conjecture.

Archival snapshot of OpenSkiStats, deposited 2026-10-03, produced by dhimmel/openskistats@e32fa86. Deposited by GitHub Actions workflow run 37129852111. OpenSkiStats generates statistics on downhill s…

Archival snapshot of OpenSkiStats, deposited 2026-10-03, produced by dhimmel/openskistats@e32fa86. Deposited by GitHub Actions workflow run 37129852111. OpenSkiStats generates statistics on downhill ski slopes and areas worldwide from OpenSkiMap/OpenStreetMap data. This deposit contains the exact inputs, source code, and outputs of one analysis run: code.zip: repository source code at the producing commit openskimap/: GeoJSON inputs from OpenSkiMap data of 2026-10-02, with download provenance in openskimap/info.json *.parquet: derived outputs for runs, lifts, and ski areas _variables.yaml: computed statistics interpolated into the website and manuscript webapp.zip: the rendered website served at openskistats.org images.zip: figures Licensing varies by component: data derived from OpenSkiMap/OpenStreetMap (openskimap/, *.parquet, _variables.yaml) is released under the Open Database License (ODbL); code is BSD-2-Clause-Patent; produced works such as the website and figures are CC-BY-4.0.