Tootfinder

This https://arxiv.org/abs/2308.03257 has been replaced.
link: https://scholar.google.com/scholar?q=a

TempFuser: Learning Agile, Tactical, and Acrobatic Flight Maneuvers Using a Long Short-Term Temporal Fusion Transformer
Dogfighting is a challenging scenario in aerial applications that requires a comprehensive understanding of both strategic maneuvers and the aerodynamics of agile aircraft. The aerial agent needs to not only understand tactically evolving maneuvers of fighter jets from a long-term perspective but also react to rapidly changing aerodynamics of aircraft from a short-term viewpoint. In this paper, we introduce TempFuser, a novel long short-term temporal fusion transformer architecture that can lea…

Spectral Theory of Dirac Operators
Tigran Harutyunyan, Yuri Ashrafyan
https://arxiv.org/abs/2403.02761 https://arxiv.org/pdf/2403.027…

Spectral Theory of Dirac Operators
The main issues of the spectral theory of Dirac operators are presented, namely: transformation operators, asymptotics of eigenvalues and eigenfunctions, description of symmetric and self-adjoint operators in Hilbert space, expansion in eigenfunctions, uniqueness theorems in inverse problems, constructive solution of inverse problems, description of isospectral operators, and some other questions. This book is aimed at specialists in spectral theory and graduate students of mathematics at unive…

A Fully-discrete Semi-Lagrangian scheme for a price formation MFG model
Yuri Ashrafyan, Diogo Gomes
https://arxiv.org/abs/2403.02785 https://

A Fully-discrete Semi-Lagrangian scheme for a price formation MFG model
Here, we examine a fully-discrete Semi-Lagrangian scheme for a mean-field game price formation model. We show that the discretization is monotone as a multivalued operator and prove the uniqueness of the discretized solution. Moreover, we show that the limit of the discretization converges to the weak solution of the continuous price formation mean-field game using monotonicity methods. This scheme performs substantially better than standard methods by giving reliable results within a few itera…

Probing the Scalar WIMP-Pion Coupling with the first LUX-ZEPLIN data
J. Aalbers, D. S. Akerib, A. K. Al Musalhi, F. Alder, C. S. Amarasinghe, A. Ames, T. J. Anderson, N. Angelides, H. M. Ara\'ujo, J. E. Armstrong, M. Arthurs, A. Baker, S. Balashov, J. Bang, E. E. Barillier, J. W. Bargemann, K. Beattie, T. Benson, A. Bhatti, A. Biekert, T. P. Biesiadzinski, H. J. Birch, E. J. Bishop, G. M. Blockinger, B. Boxer, C. A. J. Brew, P. Br\'as, S. Burdin, M. Buuck, M. C. Carmona-Benitez…

Probing the Scalar WIMP-Pion Coupling with the first LUX-ZEPLIN data
Weakly interacting massive particles (WIMPs) may interact with a virtual pion that is exchanged between nucleons. This interaction channel is important to consider in models where the spin-independent isoscalar channel is suppressed. Using data from the first science run of the LUX-ZEPLIN dark matter experiment, containing 60 live days of data in a 5.5~tonne fiducial mass of liquid xenon, we report the results on a search for WIMP-pion interactions. We observe no significant excess and set an u…

Kinetic temperature and radial flow velocity estimation using identified hadrons and light (anti-)nuclei produced in relativistic heavy-ion collisions at RHIC and LHC
Junaid Tariq, M. U. Ashraf, Grigory Nigmatkulov
https://arxiv.org/abs/2403.02759

Kinetic temperature and radial flow velocity estimation using identified hadrons and light (anti-)nuclei produced in relativistic heavy-ion collisions at RHIC and LHC
We report the investigation of the kinetic freeze-out properties of identified hadrons ($π^\pm$, $K^\pm$ and $p(\bar p)$) along with light (anti-)nuclei $d (\bar d)$, $t (\bar t)$ and ${}^{3}He$ in relativistic heavy-ion collisions at RHIC and LHC energies. A simultaneous fit is performed with the Blast-Wave (BW) model to the transverse momentum ({\ppt}) spectra of identified hadrons together with light (anti-)nuclei produced in {\auau} collisions at {\sqrtsNN} = 7.7 -- 200 GeV and in {\pbpb} …

Factors Affecting Terahertz Emission from InGaN Quantum Wells under Ultrafast Excitation
Muhammad Farooq Saleem, Ghulam Abbas Ashraf, Muhammad Faisal Iqbal, Rashid Khan, Muhammad Javid, Tianwu Wang
https://arxiv.org/abs/2404.02398

Factors Affecting Terahertz Emission from InGaN Quantum Wells under Ultrafast Excitation
InGaN quantum wells (QWs) grown on c-plane sapphire substrate experience strain due to the lattice mismatch. The strain generates a strong piezoelectric field in QWs that contributes to THz emission under ultrafast excitation. Physical parameters such as QW width, period number, and Indium concentration can affect the strength of the piezoelectric field and result in THz emission. Experimental parameters such as pump fluence, laser energy, excitation power, pump polarization angle, and incident…

This https://arxiv.org/abs/2404.14057 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Bored to Death: Artificial Intelligence Research Reveals the Role of Boredom in Suicide Behavior
Background: Recent advancements in Artificial Intelligence (AI) contributed significantly to suicide assessment, however, our theoretical understanding of this complex behavior is still limited. Objective: This study aimed to harness AI methodologies to uncover hidden risk factors that trigger or aggravate suicide behaviors. Method: The primary dataset included 228,052 Facebook postings by 1,006 users who completed the gold-standard Columbia Suicide Severity Rating Scale. This dataset was analy…

Vision-Language Synthetic Data Enhances Echocardiography Downstream Tasks
Pooria Ashrafian, Milad Yazdani, Moein Heidari, Dena Shahriari, Ilker Hacihaliloglu
https://arxiv.org/abs/2403.19880

Vision-Language Synthetic Data Enhances Echocardiography Downstream Tasks
High-quality, large-scale data is essential for robust deep learning models in medical applications, particularly ultrasound image analysis. Diffusion models facilitate high-fidelity medical image generation, reducing the costs associated with acquiring and annotating new images. This paper utilizes recent vision-language models to produce diverse and realistic synthetic echocardiography image data, preserving key features of the original images guided by textual and semantic label maps. Specif…

Online-Textverarbeitung war vor einigen Jahren in @… echt noch nicht ganz ausgereift mit den Apps "Onlyoffice" und "Community Document Server".
Mittlerweile läufts bei mir einfach und hochwertig mit den Apps "Nextcloud Office" und "Collabora Online - Built-in CODE Server ".
Am besten per Terminal installieren…

Vision-Language Synthetic Data Enhances Echocardiography Downstream Tasks
Pooria Ashrafian, Milad Yazdani, Moein Heidari, Dena Shahriari, Ilker Hacihaliloglu
https://arxiv.org/abs/2403.19880

Vision-Language Synthetic Data Enhances Echocardiography Downstream Tasks
High-quality, large-scale data is essential for robust deep learning models in medical applications, particularly ultrasound image analysis. Diffusion models facilitate high-fidelity medical image generation, reducing the costs associated with acquiring and annotating new images. This paper utilizes recent vision-language models to produce diverse and realistic synthetic echocardiography image data, preserving key features of the original images guided by textual and semantic label maps. Specif…