Artificial intelligence (AI) has revolutionized medical imaging with automated disease detection, image segmentation, diagnosis, prognosis prediction, and clinical decision support across various imaging modalities, such as X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, positron emission tomography (PET), retinal imaging, and digital pathology. Recent advances in deep learning, transformer architectures, multimodal learning and foundation models have significantly improved the diagnostic accuracy and reduced the reliance on handcrafted feature engineering. However, challenges like data heterogeneity, model interpretability, external validation, privacy preservation, computational efficiency, and regulatory compliance still hinder the widespread clinical implementation.In this paper, this review presents a comprehensive study on the evolution of modern AI frameworks in medical imaging by integrating recent methodological advances with perspectives on clinical translation. The review covers the latest deep learning architectures, such as convolutional neural networks, Vision Transformers, hybrid CNN–Transformer models, multimodal learning frameworks, generative artificial intelligence, diffusion models, federated learning, privacy-preserving learning, and medical foundation models. In addition, the review covers the cutting-edge explainable AI techniques, including Grad-CAM, SHAP, LIME, and attention visualization, for boosting transparency and clinician confidence. The review also discusses the state-of-the-art performance optimization strategies, including transfer learning, active learning, domain adaptation, neural architecture search, hyperparameter optimization, model compression, and computational resource optimization. Equally important, the latest developments in clinical validation, external evaluation, robustness assessment, fairness, uncertainty estimation, regulatory considerations, and deployment frameworks are critically analyzed to underscore their role in facilitating safe clinical implementation.The review analysis concludes with the identification of key research challenges and directions for the future including multimodal foundation models, vision-language systems, retrieval-augmented generation,
S Sur, Mandal Rakesh Kumar, Chanda Debanil· Zenodo (CERN European Organi...· 0 citations
We demonstrate that the algebraic polynomial family xd = x + 1 (for integer d ≥ 2), whose roots are known as generalized golden ratios, characterizes dual-channel boundary-bulk energy transport on d-dimensional simplicial lattices under a dominant characteristic-delay model. We formulate and prove the Face-Poset Delay Decomposition Theorem, establishing that the combinatorial face-poset topology of a regular d-simplex admits exactly two maximal transit channel classes: a boundary facet transit channel of characteristic delay d-1 hops, and a bulk interior transit channel of characteristic delay d hops. Under the dominant-delay approximation (in which sub-leading multi-hop path corrections are neglected), the unique positive real root cd > 1 of xd = x + 1 induces the growth-rate partition identity cd-(d-1) + cd-d = 1, balancing asymptotic energy transport between boundary and bulk. We explicitly distinguish three conceptual layers: (i) exact algebraic partition and topological channel exhaustion on the simplex face poset, (ii) dynamical mode transport governed by the discrete recurrence u(n) = u(n-(d-1)) + u(n-d) under the leading-order Hamiltonian delay model, and (iii) cross-lattice continuous heat-kernel validations showing that spatial decay rates across Ad (simplicial root), ℤd (hypercubic), and Dd (checkerboard) lattices cross 1/cd at matching timescales, with high-dimensional convergence governed by isotropic Gaussian diffusion. Related Work & Prior Art: The σ-Constant: A Universal Algebraic Invariant for Energy Propagation in d-Dimensional Simplicial Lattices (10.5281/zenodo.20350425) The xd = x + 1 Hierarchy: Cross-Dimensional Spectral Validation on Ad Root Lattices (10.5281/zenodo.20692936)
Casey Lee Race, Inc. Calera Computing· Zenodo (CERN European Organi...· 0 citations
Sustainable economic convergence in emerging markets now hinges on a structural break from the historical fossil‑fuel‑intensive development model. As the document states, “achieving sustainable economic convergence requires nothing less than a fundamental structural decoupling of economic growth from carbon intensity.” This monograph argues that clean technology diffusion—through FDI spillovers, global value chain integration, patent licensing, South‑South cooperation, and AI‑enabled grid modernization—has become the central engine of productivity growth and industrial upgrading across the Global South. Empirical evidence shows that clean capital inflows generate significant Total Factor Productivity (TFP) gains, with green FDI and capital‑goods imports producing elasticities of +0.32% to +0.38% per 10% increase, while domestic absorptive capacity yields the highest long‑run multiplier. The study identifies a persistent cost‑of‑capital divide—where emerging economies face WACCs 2–4× higher than advanced economies—as the largest barrier to clean diffusion, despite dramatic global cost declines in solar, wind, and battery storage. It also highlights systemic risks including transmission grid deficits, CBAM‑driven trade vulnerabilities, and critical mineral refining concentration. To overcome these constraints, the monograph proposes a three‑pillar policy architecture: (1) financial de‑risking via MDB guarantees and FX‑risk mitigation; (2) targeted green industrial policy to build domestic manufacturing and absorptive capacity; and (3) open technology transfer through patent pools, TRIPS flexibilities, and interconnected regional supergrids. Ultimately, the document outlines a phased roadmap (2026–2050) in which emerging economies can achieve full structural convergence—defined as high‑productivity, low‑carbon industrialization—by scaling clean energy, modernizing grids, deploying green hydrogen and advanced manufacturing, and establishing equitable global technology‑transfer systems.
Hunter Hughes, H Heuristics· Zenodo (CERN European Organi...· 0 citations
Paper 02 showed that a pure solid angle of four pi appears in an inverse-square field. This paper asks when that four pi does not appear; the answer is the moment the source stops being a point. Raising the dimension of the source by one alone turns four pi into two pi and turns the one-over-r fall into a logarithm. No new mathematical theorem and no new law is claimed. Scope of this paper (scope note): no new mathematical theorem and no new law is claimed. The potentials of point, line and plane sources, the volume-conductor approximation, and Krogh's cylinder model are all standard. No electrophysiology is built ── what is used is three solutions, one square root, and a conversion of units. The origin of the four pi is not discussed ── Paper 02 treats that, and this paper treats only the converse, the condition under which that four pi disappears. Inverse problems are not entered ── Paper 99 asks whether the interior conductivity can be recovered from boundary data and Paper 159 separated the senses of ill-posedness, while this paper looks in the forward direction alone, asking which solid angle appears once the shape of the source is given. Capture rates are not treated ── Paper 249 treated the Smoluchowski capture rate for a sphere, in steady state, with an absorbing boundary, whereas this paper takes a cylinder, includes a consumption term, and asks not for a capture rate but for a reach. No physiological claim is made ── no account is offered of why capillaries are arranged as they are; an agreement is reported and no cause is asserted. Tissue is treated as isotropic and homogeneous ── real tissue is neither, and the numbers are values for seeing orders of magnitude rather than measurements on a particular tissue. The source is treated as an infinitely long cylinder ── at finite length the ends return towards four pi, and what is claimed is only that in the infinitely long limit the four pi does not appear. The relation to earlier papers. Paper 02 showed that a pure solid angle of four pi appears in an inverse-square field; this paper writes the domain of that four pi, namely that it appears only when point source, three dimensions and isotropy hold together. Paper 249 showed that the four pi that catches molecules and the four pi that spreads a field share a root; this paper sets out the cases where the same four pi does not appear, since confirming a shared root and confirming a domain are two halves of one thing. Paper 01 showed from four directions that n equals two is unique; what this paper moves is the dimension of the source rather than the exponent, a different axis. Paper 199 wrote that what decides whether you come home is the exponent in the denominator; the fourth section here likewise sets out the form of the denominator, but asks about the fall rather than about recurrence. Paper 112 counted resolution as one of six distinct roots; measurement resolution is not treated here. First, for a point source the four pi stands in the denominator. With a current of one microampere in a medium of conductivity 0.33 siemens per metre, the potential is 48.2288 microvolts at five millimetres, 24.1144 at ten, 12.0572 at twenty and 4.8229 at fifty. Doubling the distance halves the potential exactly, and the four pi in the denominator, 12.566371, is the whole solid angle of the sphere itself. Second, this is the core. Make the source an infinitely long line and the four pi disappears, leaving two pi and a logarithm. With a current of ten to the minus four amperes per metre the prefactor is 4.822877e-5 volts, and the potential difference is that prefactor times the logarithm of the ratio of distances: 33.4296 microvolts for a ratio of two, 111.0508 for ten, and 222.1017 for a hundred. Raising the dimension of the source from zero to one alone halved the solid angle in the denominator, from 12.566371 to 6.283185. Third, the fall itself reverses direction. Taking one millimetre as the reference for the line source and comparing over the same distances, the point source gives 120.5719 microvolts at two millimetres falling to 4.8229 at fifty, a factor of 25.0, while the line source gives 33.4296 rising to 188.6721, a factor of 5.64 in the other direction. The same distance is being travelled and the directions are opposite. One cannot say that a field weakens with distance without first writing down the shape of the source. The separator is raising the dimension of the source by one, and nothing else: neither the medium, nor the current, nor the number of dimensions of the space has been moved. Fourth, three sources are called over. A point, of dimension zero, gives four pi equal to 12.566371 and falls as one over r. A line or cylinder, of dimension one, gives two pi equal to 6.283185 and falls as a logarithm. A plane or layer, of dimension two, gives two pi and does not fall at all. Each rise in the dimension of the source flattens the fall by one step. The four pi appears in the first row alone, and written out the condition has three items, point source, three dimensions and isotropy, any one of which suffices to remove it when lost. Fifth, sources in living tissue are often cylinders. Oxygen diffuses out of a capillary and is consumed on the way, with a reach equal to the square root of twice the diffusion coefficient times the wall concentration divided by the consumption. With a diffusion coefficient of 2.0e-9 square metres per second, a solubility of 1.4e-3 moles per cubic metre per millimetre of mercury and a partial pressure of forty, the wall concentration is 0.056000 moles per cubic metre. Resting skeletal muscle, consuming 0.3 millilitres per hundred grams per minute, gives 2.232143e-3 moles per cubic metre per second and a reach of 316.8 micrometres; moderate work gives 100.2 micrometres; and maximal exercise, fifty times the resting demand, gives 1.116071e-1 and a reach of 44.8 micrometres. Sixth, that length is not set by the resting demand. The observed capillary spacing, the Krogh radius, is twenty to eighty micrometres. At the resting demand the reach extends to 316.8 micrometres, four times further, so the observed spacing looks excessive; what it matches is the demand at maximal exercise. The length is set by the maximum rather than the average. Since the reach falls as the inverse square root of the consumption, a demand fifty times larger shrinks the distance by the square root of fifty, 7.0711, and 316.8 divided by 7.0711 is 44.8, so the first and third rows correspond exactly. Stated honestly, this paper reports an agreement and no more; it does not claim that the arrangement of capillaries is set by the maximal demand, since that would require evidence from the developmental side which this paper does not have, and treating the tissue as isotropic and homogeneous is also a departure from the real thing. Closing. The four pi that Paper 02 found is not something that appears everywhere. It appears only when point source, three dimensions and isotropy hold together, and raising the dimension of the source by one alone removes it. What appears after it has gone is two pi and a logarithm, and the fall points the other way: over the same distance the point source becomes 25.0 times weaker while the line source becomes 5.64 times stronger. And sources in living tissue are often not points. A capillary is a cylinder, and the reach around it is 316.8 micrometres at rest and 44.8 at maximal exercise, the latter being what matches the observed spacing. One thing separates them, which is writing down the dimension of the source. Write it down, and the occasions where four pi may be used separate from the occasions where using it is wrong by a factor of two. Do not write it down, and one fits a one-over-r to a field that grows stronger with distance. On the making of this work: The ideas and content of this work stem from the author's own considerations. Assistance from an AI (a large language model) was used for structuring, English translation, and checking the algebra. Any remaining errors or misinterpretations are solely the author's. Feedback and corrections are sincerely appreciated. ----- 論文02 は、逆二乗場に純粋な立体角 4π が現れることを示した。本稿が問うのは、その 4π はいつ現れないのかである。答は、源が点でなくなった瞬間である。源の次元を一つ上げるだけで、4π は 2π になり、1/r という落ち方は対数に変わる。新しい数学定理も新しい法則も主張しない。 本稿の射程(射程注記):新しい数学定理も新しい法則も主張しない。点源・線源・面源の電位、容積導体という近似、クローの円柱模型は、いずれも標準的である。電気生理学を作らない──使うのは三つの解と、一つの平方根と、単位の換算だけである。4π の由来を論じない──論文02 が扱う。本稿は逆に、その 4π が消える条件だけを扱う。逆問題に入らない──論文99 は境界データから内部の導電率を復元できるかを問い、論文159 は不良設定を分けた。本稿は順方向であり、源の形が与えられたときにどの立体角が出るかだけを見る。捕捉率を扱わない──論文249 はスモルコフスキーの捕捉率を球・定常・吸収境界で扱った。本稿は円柱で、消費項があり、問うのが捕捉率ではなく到達距離である。生理学を主張しない──毛細血管の配置がなぜそうなっているかの説明を与えない。一致を報告するだけであり、因果を述べない。生体組織を等方均質として扱っている──現実の組織は異方的で不均質である。数値は桁を見るための値であり、特定の組織の測定値ではない。源を無限に長い円柱として扱っている──有限長では端で 4π 側へ戻る。本稿が言うのは、無限に長い極限で 4π が出ないという一点である。 既刊との関係。論文02 は逆二乗場に純粋立体角 4π が現れることを示した。本稿はその 4π の定義域を書く。点源・三次元・等方の三つが揃ったときだけである。論文249 は拡散が捕らえる 4π と場が広がる 4π が同根だと示した。本稿は同じ 4π が出ない場合を並べる。同根の確認と、定義域の確認は対になっている。論文01 は n = 2 が唯一であることを四方向から示した。本稿が動かすのは指数ではなく源の次元であり、別の軸である。論文199 は帰ってこられるかを分母の指数が決めると書いた。本稿の第4節も分母の形を並べるが、問うのは再帰性ではなく落ち方である。論文112 は分解能を六つの別根の一つに数えた。本稿は測定の分解能を扱わない。 第一に、点源では 4π がそのまま分母に立つ。電流 1 マイクロアンペア、導電率 0.33 S/m で、電位は 5 mm で 48.2288 マイクロボルト、10 mm で 24.1144、20 mm で 12.0572、50 mm で 4.8229 になる。距離を 2 倍にすると電位はちょうど半分になり、分母の 4π=12.566371 は球の全立体角そのものである。 第二に、これが本稿の芯である。源を無限に長い線にすると 4π が消え、2π と対数が出る。単位長あたり 10 のマイナス4乗アンペアなら前係数は 4.822877e-5 ボルトで、電位差はその前係数に距離の比の対数を掛けたものになる。比が 2 なら 33.4296 マイクロボルト、10 なら 111.0508、100 なら 222.1017 である。源の次元を 0 から 1 に上げただけで、分母の立体角が 12.566371 から 6.283185 に半分になった。 第三に、落ち方そのものが逆を向く。線源の基準を 1 mm にとって同じ距離で並べると、点源は 2 mm で 120.5719 マイクロボルト、50 mm で 4.8229 まで 25.0 分の 1 に落ちるのに、線源は 33.4296 から 188.6721 へ 5.64 倍に増える。同じ距離を離れているのに向きが逆である。源の形を書かずに「距離が離れれば弱くなる」と言うことはできない。分離子は源の次元を一つ上げることだけであって、媒質も、電流も、空間の次元数も動かしていない。 第四に、三つの源で立体角を点呼する。次元 0 の点は 4π=12.566371 で 1/r に落ち、次元 1 の線(円柱)は 2π=6.283185 で対数に落ち、次元 2 の面(層)は 2π で距離に依らない。源の次元を一つ上げるたびに、落ち方が一段平らになる。4π が出るのは一行目だけであり、条件を書き出すと点源・三次元・
Yuuki Yamagishi· Zenodo (CERN European Organi...· 0 citations
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1. Summary This paper bridges the gap between macroscopic geotechnical engineering (soil consolidation and secondary creep) and microscopic pharmaceutical science (controlled-release polymer hydrogels). By replacing abstract phenomenological parameters with rigorous physical units, the framework demonstrates that both systems share an identical differential dissipation topology governed by coupled deformation and stress gradients. 2. Key Formulas & Equations Coupled State-Space Memory Equation: $$\frac{d}{dt} \begin{bmatrix} x(t) \\ p(t) \end{bmatrix} = \begin{bmatrix} 0 & \frac{1}{m_{eff}} \\ -k & -\gamma \end{bmatrix} \begin{bmatrix} x(t) \\ p(t) \end{bmatrix} - \int_{0}^{t} M(t-t') \begin{bmatrix} 0 \\ v(t') \end{bmatrix} dt'$$ (Where $x(t)$ is displacement/strain, $p(t)$ is momentum/stress, $k$ is structural stiffness, $\gamma$ is instantaneous damping, and $M(t-t')$ is the historical memory kernel). 3. Key Vocabulary & Keywords Isomorphic Topology: Identical mathematical structure governing disparate physical systems. Memory Kernel ($M(t)$): Integral term capturing historical relaxation and delayed energy dissipation over time. Non-Fickian Transport: Deviations from standard diffusion caused by polymer chain relaxation and swelling stress. Darcy Flow / Pore Pressure: Macroscopic hydraulic gradients driving fluid expulsion in granular media. 4. Physical Significance Eliminates the need for separate, disconnected empirical models for soil compaction and hydrogel drug delivery. Proves that apparent behavioral complexity across physical scales stems from parameter variation ($G, \eta, k_B$) rather than structural mathematical novelty. Provides a predictive pathway to fit experimental laboratory trial data directly into a unified differential framework. 5. License & Archival Metadata Repository Target: Zenodo Preprint Repository. License Recommendation:Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) Attribution: Independent Research Conspectus, under the Conserved Informational Modulation (CIM) and Systemic Relaxation Tensors framework.
Egidijus Kasiulevičius, Azuolas Kasiulevicius, Saule Kasiuleviciute et al.· Zenodo (CERN European Organi...· 0 citations
The prevailing narrative of the AI race assumes that technological competition culminates in a single winner, a malformed rhetoric that rests on an under-specified concept of victory (Siegel, 2026). Unlike historical technological competitions, the AI race has no agreed endpoint, no universally accepted metric of success, and no consensus on whether achievement should be defined by artificial general intelligence (AGI), frontier-model capability, compute capacity, scientific productivity, economic competitiveness, military advantage, or global diffusion (Akula & Guest, 2026). Consequently, assertions that one state will ultimately win the AI race are conceptually incomplete. This working paper therefore shifts attention from identifying a presumed winner to examining an alternative question: whether strategic influence may depend not only on frontier capability, but also on how AI systems are adopted, trusted, and deployed across third-country markets. The following corpus outlines ten working parts.
We ask whether a pretrained language model and a pretrained physics model can run as one system — two frozen networks answering a single question with communication carried entirely by hidden states, the way the brain’s hemispheres cooperate across the corpus callosum. As of August 2026 we find no published work coupling a pretrained LLM to a neural-operator physics model through a bidirectional latent channel at inference. We build such a system, ΨLM, on a consumer laptop (Apple M2, 24 GB), in four steps. (1) Tool-loop baselines reproduce the known capability-gap effect: a simulator adds +28.3 points to a 3B model on physics QA but hurts a 0.5B model. (2) We produce, to our knowledge, the first public reproduction of the Bicameral Model [12]: two frozen Qwen2.5-0.5B streams coupled by a 6.2M-parameter gated hidden-state interface reproduce the paper’s phase transition, reaching 100% exact tool recall through the latent channel alone. (3) With the auxiliary language model replaced by a frozen Fourier Neural Operator, ΨLM answers Burgers-equation field-value questions at 100% (tolerance ±0.05; MAE 0.014) where the LLM alone achieves 5%, matching the accuracy of an oracle that states the answer in text — with no text at the interface. (4) The result survives hardening: held-out question families expose a clean generalization law (support coverage — readouts generalize only where their training support covers the test distribution, a hypothesis we confirm by refuting the alternative), and the architecture transfers to 2D reaction–diffusion with a pretrained physics foundation model (DPOT-Tiny) as the hemisphere, scoring 95%, within five points of the oracle ceiling. All experiments, including two failed designs and one refuted hypothesis, are reproducible from the public repository on a single consumer machine.
Ryoji Furui· Zenodo (CERN European Organi...· 0 citations
Sustainable economic convergence in emerging markets now hinges on a structural break from the historical fossil‑fuel‑intensive development model. As the document states, “achieving sustainable economic convergence requires nothing less than a fundamental structural decoupling of economic growth from carbon intensity.” This monograph argues that clean technology diffusion—through FDI spillovers, global value chain integration, patent licensing, South‑South cooperation, and AI‑enabled grid modernization—has become the central engine of productivity growth and industrial upgrading across the Global South. Empirical evidence shows that clean capital inflows generate significant Total Factor Productivity (TFP) gains, with green FDI and capital‑goods imports producing elasticities of +0.32% to +0.38% per 10% increase, while domestic absorptive capacity yields the highest long‑run multiplier. The study identifies a persistent cost‑of‑capital divide—where emerging economies face WACCs 2–4× higher than advanced economies—as the largest barrier to clean diffusion, despite dramatic global cost declines in solar, wind, and battery storage. It also highlights systemic risks including transmission grid deficits, CBAM‑driven trade vulnerabilities, and critical mineral refining concentration. To overcome these constraints, the monograph proposes a three‑pillar policy architecture: (1) financial de‑risking via MDB guarantees and FX‑risk mitigation; (2) targeted green industrial policy to build domestic manufacturing and absorptive capacity; and (3) open technology transfer through patent pools, TRIPS flexibilities, and interconnected regional supergrids. Ultimately, the document outlines a phased roadmap (2026–2050) in which emerging economies can achieve full structural convergence—defined as high‑productivity, low‑carbon industrialization—by scaling clean energy, modernizing grids, deploying green hydrogen and advanced manufacturing, and establishing equitable global technology‑transfer systems.
Hunter Hughes, H Heuristics· Zenodo (CERN European Organi...· 0 citations
Emerging economies can no longer follow the historical industrialization sequence of “build first, clean later.” As the report states, “they must now industrialize, decarbonize, and climate‑proof their industrial base simultaneously” . This constraint—what the report terms the Convergence Paradox—arises because the same income growth that expands absorptive capacity also drives emissions upward on every historical pathway. Unlike OECD industrializers, today’s EMDEs face a shrinking global carbon budget and accelerating physical climate impacts that are already visible in factories, ports, and labor markets. The data show a structural mismatch between where energy demand is rising and where capital is flowing. In 2024, emerging economies accounted for 82% of global energy demand growth, yet received only 7% of global clean‑energy investment through international public finance . Adaptation finance is even more constrained: developing‑country needs of $310–365B annually contrast with only $26B in current flows—a 12–14× gap UNEP describes as “running on empty” . This underfunding directly affects industrial competitiveness, as climate exposure in manufacturing zones is already generating measurable economic losses. Case evidence from Vietnam, Indonesia, India, and Morocco illustrates both the promise and limits of leapfrogging. Vietnam’s solar boom demonstrates rapid diffusion but remains heavily dependent on Chinese inputs; Indonesia’s nickel downstreaming builds scale but is powered by captive coal; India’s green hydrogen and green steel push shows domestically anchored decarbonization; and Morocco’s renewables‑based industrial corridor represents a rare “Decouple‑first” pathway. Across all cases, the report finds that growth without matched decarbonization and climate‑proofing erodes its own dividend. To address this simultaneity problem, the report introduces the Compound Vulnerability Multiplier—capturing how exposure density, cumulative climate burden, and absorptive capacity interact—and the 4D Framework (Decouple, Diffuse, Defend, Direct) as a concurrent operating model for industrial policy. The central conclusion is clear: EMDEs cannot out‑grow the paradox. They must compress the historical emissions curve without compressing development itself, and the window for doing so is rapidly closing.
Hunter Hughes· Zenodo (CERN European Organi...· 0 citations
The proliferation of algorithmically synthesized visual con-tent broadly labelled as deepfake poses a mounting threat to theintegrityofdigitalinformationecosystems. Despiterapid advancesingenerativemodelling, robustautomateddetection remains challenging, as synthesis quality now routinely ex-ceedsthethresholdofreliablehumaninspection.Thispaper fine-tunesaVisionTransformer(ViT)classifierfromthepub-licly released dima806/deepfake_vs_real_image_detection checkpoint via the Hugging Face Trainer API on a balanced corpus of 190,081 images drawn from Kaggle, comprising equalproportionsofauthenticphotographsandAI-generated samples spanning GAN-based and latent diffusion architec-tures.The fine-tuned model achieves an overall classifi-cation accuracy of 99.20% and a macro-averaged F1-score of 0.9920 on a held-out evaluation set of 38,081 images, withsymmetricper-classerrorrates(128falsepositives;175 false negatives).These results demonstrate that the Vision Transformer, whose globally unconstrained multi-head self-attentionmechanismenablesdetectionofthelong-rangespa-tial incoherence characteristic of synthetic imagery, consti-tutesacomputationallytractableandhigh-performingarchi-tectureforsynthetic-imageforensics,surpassingallsurveyed CNN and frequency-domain baselines on the same bench-mark.
Kanwerjit, Deep Gaurav, Kaur Sumandeep· Zenodo (CERN European Organi...· 0 citations
Accurate reproduction of hydrodynamic and solute mixing processes within cylinder arrays is vital for many environmental modelling applications. Traditional approaches use a second-order finite volume (FV2) method to solve the two-dimensional (2D) planar Reynolds-Averaged Navier-Stokes (RANS) equations and the advection diffusion equation (ADE) to simulate both flow hydrodynamic and solute concentration fields. However, FV2‑based RANS solvers need fine mesh resolutions around the cylinders, resulting in impractical computational costs for large‑scale applications. This study demonstrates the utility of an alternative coarser resolution approach: second-order discontinuous Galerkin (DG2) based solvers of both the shallow water equations (SWE) and the ADE compared to FV2-based RANS and ADE solvers (CFD software) on meshes using much finer resolutions. Results show that these DG2‑based solvers competitively simulate flow hydrodynamic and solute concentration fields at 10 times coarser resolution in the vicinity of cylinders than with the FV2‑based RANS and ADE simulators (ANSYS Fluent). These DG2-based solvers may be a useful alternative to CFD software to support large/field-scale studies where resolution and computational needs are major constraints.
Georges Kesserwani, Xitong Sun· Digital Water· 0 citations
This paper introduces a rigorous mathematical framework named Sonic Cognition and Sensory Kinematics, bridging continuous cosmic/neural background fields with localized biophysical velocity responses. We define two infinite, unbounded coordinators—Sonic Light (\(SL\)) governing visual fields and Sonic Motion (\(SM\)) governing kinetics—which project into the tangible world as finite, localized agents (\(LS\) and \(MS\)) through discretization field operators. Focusing on vision-kinetic coupling during interactive physical events (e.g., a ball player tracking and striking a target), we formulate a coupled kinematic differential equation where mechanical motor velocity (\(\mathbf{v}_{MS}\)) accelerates proportionally to incoming visual information velocity (\(\mathbf{v}_{LS}\)), modulated by a central neural transfer tensor (\(\mathbf{T}_{brain}\)) and biological damping (\(\gamma \)). To map the temporal duality of human consciousness, we formalize the global Electro-Magnetic Biological (\(EMB\)) state using a time-dependent circadian switch matrix (\(\theta(t)\)). During the nighttime dream state (\(\theta(t) = 0\)), a strict boundary condition enforces total somatic motor disconnection (\(\mathbf{v}_{MS\_real} = \mathbf{0}\)), while the brain reconstructs an informational, virtual visual velocity (\(\mathbf{v}_{dream}\)) governed by non-linear memory diffusion equations. Numerical Python simulations of this complex dynamical system confirm a clean state transition at sleep onset, characterized by an instantaneous collapse of physical velocity alongside a computational spike and subsequent relaxation of virtual dream velocity. Finally, the framework applies this temporal integration to congenital blindness, proving analytically why a structural lack of lifetime visual source tokens results in an absolute zero value for visual dream vectors.
abdelhadi Abouelfida· Zenodo (CERN European Organi...· 0 citations
What if pathology foundation models could do more with less? GigaPath-Flash and GigaTIME-Flash cut computational demands while maintaining strong performance, opening the door to larger studies and broader exploration. The post GigaPath-Flash and GigaTIME-Flash: Toward population-scale discovery with efficient pathology foundation models appeared first on Microsoft Research.