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#cs

13 posts11 participants3 posts today
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amen zwa, esq.

Today’s cutting-edge innovations in #CS are powered by the electronic engineering of the 2020s.

The programming languages and software techniques that now run the technology sector were sired by CS research from the 1990s.

Its prominance notwithstanding, though, CS is a very young field, having matured into an independent discipline only in the 1960s.

It was born relatively recently, in the 1930s, as a subfield of mathematics.

And when—rather, if—society transitions to quantum computing, a good portion of CS will be based on physics of the 1900s.

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Zbigniew 'Emill' Pławecki ♿️🎮

#TVPSport niedawno pisalo o "intensywnym okresie" #LegiaWarszawa, czyli TRZECH spotkaniach w ciagu 7 dni, o czym pisal @smatyszczak - pol.social/@smatyszczak/114139 (oczywiscie nalezy do tego doliczyc treningi, itp.)

Tymczasem, 4 ostatnie dni #CS-owej ekipy #fnatic - 12 spotkan BO3 (czyli minimum 2 godziny na kazde, maksimum... 3h+ bo ewentualne dogrywki) 🙃 plus rowniez czas poswiecony na treningi

#esport #CS2 #fnatic #sport #football #PilkaNozna @esport

Zrzut ekranu przedstawiający wyniki meczów drużyny Fnatic w turniejach Counter-Strike 2 z dni 8-11 marca 2025 roku. Wyniki są uporządkowane chronologicznie i obejmują różne rozgrywki, takie jak CCT Season 2 Europe Series i PGL Bucharest 2025 Europe. Każdy mecz zawiera nazwę przeciwnika, wynik oraz nazwę turnieju. Fnatic wygrało niektóre mecze (np. 2-0 przeciwko Ninjas in Pyjamas, Partizan), ale także poniosło porażki (np. 0-2 przeciwko BC.Game, Apogee).
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Rxiv mechanobio

📰 "Cell as Point: One-Stage Framework for Efficient Cell Tracking"
arxiv.org/abs/2411.14833 #CellDivision #Q-Bio.Qm #Eess.Iv #Cs.Cv #Cell

arXiv logo
arXiv.orgCell as Point: One-Stage Framework for Efficient Cell TrackingConventional multi-stage cell tracking approaches rely heavily on detection or segmentation in each frame as a prerequisite, requiring substantial resources for high-quality segmentation masks and increasing the overall prediction time. To address these limitations, we propose CAP, a novel end-to-end one-stage framework that reimagines cell tracking by treating Cell as Point. Unlike traditional methods, CAP eliminates the need for explicit detection or segmentation, instead jointly tracking cells for sequences in one stage by leveraging the inherent correlations among their trajectories. This simplification reduces both labeling requirements and pipeline complexity. However, directly processing the entire sequence in one stage poses challenges related to data imbalance in capturing cell division events and long sequence inference. To solve these challenges, CAP introduces two key innovations: (1) adaptive event-guided (AEG) sampling, which prioritizes cell division events to mitigate the occurrence imbalance of cell events, and (2) the rolling-as-window (RAW) inference strategy, which ensures continuous and stable tracking of newly emerging cells over extended sequences. By removing the dependency on segmentation-based preprocessing while addressing the challenges of imbalanced occurrence of cell events and long-sequence tracking, CAP demonstrates promising cell tracking performance and is 10 to 55 times more efficient than existing methods. The code and model checkpoints will be available soon.
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amen zwa, esq.

Over the past quarter century, the #CS programmes at the ordinary US colleges have been busy pumping out coders for the #IT industry. Only those kids who get into the top colleges receive solid theoretical foundation. There are obvious, short-term gains aplenty: the colleges get tuition fees; the industry gets their cheap drones; the kids get their immediate employment. But this strategy has hidden, long-term deleterious effects upon all involved.

In my view, the CS curricula ought to focus on "moulding future computer scientists" who know well both theory and practice, and leave the task of "stamping out generate-first, ask questions never coders" to those week-long coding camps.

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Rxiv mechanobio

📰 "Treatment of Wall Boundary Conditions in High-Order Compact Gas-Kinetic Schemes"
arxiv.org/abs/2503.04493 #Physics.Comp-Ph #Dynamics #Math.Na #Cs.Na #Cell

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arXiv.orgTreatment of Wall Boundary Conditions in High-Order Compact Gas-Kinetic SchemesThe boundary layer represents a fundamental structure in fluid dynamics, where accurate boundary discretization significantly enhances computational efficiency. This paper presents a third-order boundary discretization for compact gas-kinetic scheme (GKS). Wide stencils and curved boundaries pose challenges in the boundary treatment for high-order schemes, particularly for temporal accuracy. By utilizing a time-dependent gas distribution function, the GKS simultaneously evaluates fluxes and updates flow variables at cell interfaces, enabling the concurrent update of cell-averaged flow variables and their gradients within the third-order compact scheme. The proposed one-sided discretization achieves third-order spatial accuracy on boundary cells by utilizing updated flow variables and gradients in the discretization for non-slip wall boundary conditions. High-order temporal accuracy on boundary cells is achieved through the GKS time-dependent flux implementation with multi-stage multi-derivative methodology. Additionally, we develop exact no-penetration conditions for both adiabatic and isothermal wall boundaries, with extensions to curved mesh geometries to fully exploit the advantages of high-order schemes. Comparative analysis between the proposed one-sided third-order boundary scheme, third-order boundary scheme with ghost cells, and second-order boundary scheme demonstrates significant performance differences for the third-order compact GKS. Results indicate that lower-order boundary cell treatments yield substantially inferior results, while the proposed third-order treatment demonstrates superior performance, particularly on coarse grid configurations.
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Rxiv mechanobio

📰 "A linearly-implicit energy preserving scheme for geometrically nonlinear mechanics based on non-canonical Hamiltonian formulations"
arxiv.org/abs/2503.04695 #Physics.Comp-Ph #Mechanics #Dynamics #Math.Na #Matrix #Cs.Na

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arXiv.orgA linearly-implicit energy preserving scheme for geometrically nonlinear mechanics based on non-canonical Hamiltonian formulationsThis work presents a novel formulation and numerical strategy for the simulation of geometrically nonlinear structures. First, a non-canonical Hamiltonian (Poisson) formulation is introduced by including the dynamics of the stress tensor. This framework is developed for von-Kármán nonlinearities in beams and plates, as well as finite strain elasticity with Saint-Venant material behavior. In the case of plates, both negligible and non-negligible membrane inertia are considered. For the former case the two-dimensional elasticity complex is leveraged to express the dynamics in terms of the Airy stress function. The finite element discretization employs a mixed approach, combining a conforming approximation for displacement and velocity fields with a discontinuous stress tensor representation. A staggered, linear implicit time integration scheme is proposed, establishing connections with existing explicit-implicit energy-preserving methods. The stress degrees of freedom are statically condensed, reducing the computational complexity to solving a system with a positive definite matrix. The methodology is validated through numerical experiments on the Duffing oscillator, a von-Kármán beam, and a column undergoing finite strain elasticity. Comparisons with fully implicit energy-preserving method and the explicit Newmark scheme demonstrate that the proposed approach achieves superior accuracy while maintaining energy stability. Additionally, it enables larger time steps compared to explicit schemes and exhibits computational efficiency comparable to the leapfrog method.
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Michael Engel

Does anyone have an electronic copy of the CMU tech report of Michael Wayne Young Ph.D. thesis
"Exporting a User Interface to Memory Management from a Communication-Oriented Operating System"?

This is CMU technical report CMU-CS-89-202. The CMU tech report server has no entries for 1989...

#CS#Mach#OS
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Rxiv mechanobio

📰 "Particle-based plasma simulation using a graph neural network"
arxiv.org/abs/2503.00274 #Physics.Plasm-Ph #Physics.Comp-Ph #Dynamics #Cs.Lg #Cell

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arXiv.orgParticle-based plasma simulation using a graph neural networkA surrogate model for particle-in-cell plasma simulations based on a graph neural network is presented. The graph is constructed in such a way as to enable the representation of electromagnetic fields on a fixed spatial grid. The model is applied to simulate beams of electrons in one dimension over a wide range of temperatures, drift momenta and densities, and is shown to reproduce two-stream instabilities - a common and fundamental plasma instability. Qualitatively, the characteristic phase-space mixing of counterpropagating electron beams is observed. Quantitatively, the model's performance is evaluated in terms of the accuracy of its predictions of number density distributions, the electric field, and their Fourier decompositions, particularly the growth rate of the fastest-growing unstable mode, as well as particle position, momentum distributions, energy conservation and run time. The model achieves high accuracy with a time step longer than conventional simulation by two orders of magnitude. This work demonstrates that complex plasma dynamics can be learned and shows promise for the development of fast differentiable simulators suitable for solving forward and inverse problems in plasma physics.
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Rxiv mechanobio

📰 "Engineering morphogenesis of cell clusters with differentiable programming"
arxiv.org/abs/2407.06295 #Morphogenesis #Mechanical #Q-Bio.Cb #Cs.Lg #Cell

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arXiv.orgEngineering morphogenesis of cell clusters with differentiable programmingUnderstanding the rules underlying organismal development is a major unsolved problem in biology. Each cell in a developing organism responds to signals in its local environment by dividing, excreting, consuming, or reorganizing, yet how these individual actions coordinate over a macroscopic number of cells to grow complex structures with exquisite functionality is unknown. Here we use recent advances in automatic differentiation to discover local interaction rules and genetic networks that yield emergent, systems-level characteristics in a model of development. We consider a growing tissue with cellular interactions mediated by morphogen diffusion, cell adhesion and mechanical stress. Each cell has an internal genetic network that is used to make decisions based on the cell's local environment. We show that one can learn the parameters governing cell interactions in the form of interpretable genetic networks for complex developmental scenarios, including directed axial elongation, cell type homeostasis via chemical signaling and homogenization of growth via mechanical stress. When combined with recent experimental advances measuring spatio-temporal dynamics and gene expression of cells in a growing tissue, the methodology outlined here offers a promising path to unraveling the cellular bases of development.
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Paul Houle

🔗 SHACL-SKOS Based Knowledge Representation of Material Safety Data Sheet (SDS) for the Pharmaceutical Industry

arxiv.org/abs/2502.07944

arXiv.orgSHACL-SKOS Based Knowledge Representation of Material Safety Data Sheet (SDS) for the Pharmaceutical IndustryWe report the development of a knowledge representation and reasoning (KRR) system built on hybrid SHACL-SKOS ontologies for globally harmonized system (GHS) material Safety Data Sheets (SDS) to enhance chemical safety communication and regulatory compliance. SDS are comprehensive documents containing safety and handling information for chemical substances. Thus, they are an essential part of workplace safety and risk management. However, the vast number of Safety Data Sheets from multiple organizations, manufacturers, and suppliers that produce and distribute chemicals makes it challenging to centralize and access SDS documents through a single repository. To accomplish the underlying issues of data exchange related to chemical shipping and handling, we construct SDS related controlled vocabulary and conditions validated by SHACL, and knowledge systems of similar domains linked via SKOS. The resulting hybrid ontologies aim to provide standardized yet adaptable representations of SDS information, facilitating better data sharing, retrieval, and integration across various platforms. This paper outlines our SHACL-SKOS system architectural design and showcases our implementation for an industrial application streamlining the generation of a composite shipping cover sheet.
#rdf#shacl#skos
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Rxiv mechanobio

📰 "Boltzsim: A fast solver for the 1D-space electron Boltzmann equation with applications to radio-frequency glow discharge plasmas"
arxiv.org/abs/2502.16555 #Physics.Plasm-Ph #Pressure #Math.Na #Cs.Ce #Cs.Na #Cell

arXiv.orgBoltzsim: A fast solver for the 1D-space electron Boltzmann equation with applications to radio-frequency glow discharge plasmasWe present an algorithm for solving the one-dimensional space collisional Boltzmann transport equation (BTE) for electrons in low-temperature plasmas (LTPs). Modeling LTPs is useful in many applications, including advanced manufacturing, material processing, and hypersonic flows, to name a few. The proposed BTE solver is based on an Eulerian formulation. It uses Chebyshev collocation method in physical space and a combination of Galerkin and discrete ordinates in velocity space. We present self-convergence results and cross-code verification studies compared to an in-house particle-in-cell (PIC) direct simulation Monte Carlo (DSMC) code. Boltzsim is our open source implementation of the solver. Furthermore, we use Boltzsim to simulate radio-frequency glow discharge plasmas (RF-GDPs) and compare with an existing methodology that approximates the electron BTE. We compare these two approaches and quantify their differences as a function of the discharge pressure. The two approaches show an 80x, 3x, 1.6x, and 0.98x difference between cycle-averaged time periodic electron number density profiles at 0.1 Torr, 0.5 Torr, 1 Torr, and 2 Torr discharge pressures, respectively. As expected, these differences are significant at low pressures, for example less than 1 Torr.
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Rxiv mechanobio

📰 "Hierarchical poromechanical approach to investigate the impact of mechanical loading on human skin micro-circulation"
arxiv.org/abs/2502.17354 #Physics.App-Ph #Mechanical #Q-Bio.To #Cs.Ce #Cell

arXiv.orgHierarchical poromechanical approach to investigate the impact of mechanical loading on human skin micro-circulationResearch on human skin anatomy reveals its complex multi-scale, multi-phase nature, with up to 70% of its composition being bounded and free water. Fluid movement plays a key role in the skin's mechanical and biological responses, influencing its time-dependent behavior and nutrient transport. Poroelastic modeling is a promising approach for studying skin dynamics across scales by integrating multi-physics processes. This paper introduces a hierarchical two-compartment model capturing fluid distribution in the interstitium and micro-circulation. A theoretical framework is developed with a biphasic interstitium -- distinguishing interstitial fluid and non-structural cells -- and analyzed through a one-dimensional consolidation test of a column. This biphasic approach allows separate modeling of cell and fluid motion, considering their differing characteristic times. An appendix discusses extending the model to include biological exchanges like oxygen transport. Preliminary results indicate that cell viscosity introduces a second characteristic time, and at high viscosity and short time scales, cells behave similarly to solids. A simplified model was used to replicate an experimental campaign on short time scales. Local pressure (up to 31 kPa) was applied to dorsal finger skin using a laser Doppler probe PF801 (Perimed Sweden), following a setup described in Fromy Brain Res (1998). The model qualitatively captured ischemia and post-occlusive reactive hyperemia, aligning with experimental data. All numerical simulations used the open-source software FEniCSx v0.9.0. To ensure transparency and reproducibility, anonymized experimental data and finite element codes are publicly available on GitHub.
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Rxiv mechanobio

📰 "MIML: Multiplex Image Machine Learning for High Precision Cell Classification via Mechanical Traits within Microfluidic Systems"
arxiv.org/abs/2309.08421 #Mechanical #Q-Bio.Qm #Eess.Iv #Cs.Cv #Cs.Lg #Cell

arXiv.orgMIML: Multiplex Image Machine Learning for High Precision Cell Classification via Mechanical Traits within Microfluidic SystemsLabel-free cell classification is advantageous for supplying pristine cells for further use or examination, yet existing techniques frequently fall short in terms of specificity and speed. In this study, we address these limitations through the development of a novel machine learning framework, Multiplex Image Machine Learning (MIML). This architecture uniquely combines label-free cell images with biomechanical property data, harnessing the vast, often underutilized morphological information intrinsic to each cell. By integrating both types of data, our model offers a more holistic understanding of the cellular properties, utilizing morphological information typically discarded in traditional machine learning models. This approach has led to a remarkable 98.3\% accuracy in cell classification, a substantial improvement over models that only consider a single data type. MIML has been proven effective in classifying white blood cells and tumor cells, with potential for broader application due to its inherent flexibility and transfer learning capability. It's particularly effective for cells with similar morphology but distinct biomechanical properties. This innovative approach has significant implications across various fields, from advancing disease diagnostics to understanding cellular behavior.
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