Miracle-dz/UniFAR-FTUs huggingface dataset:
Tracking the tongue contours in rt-MRI films with an autoencoder DNN approach

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Tracking the tongue contours in rt-MRI films with an autoencoder DNN approach Karyna Isaieva, Yves Laprie, Alexis Houssard, Jacques Felblinger, Pierre-André Vuissoz
SAO, AO, QBO, and Long-term trend of the peak OH airglow 1 emission 2

Based on the volume emission rate of the OH airglow observed by TIMED/SABER, we fitted the peak emission 9 rate and the peak height of the OH airglow and analyzed the seasonal and interannual variations of both. The results show 10 similar latitudinal variations in the semiannual oscillation (SAO) and annual oscillation (AO) of peak emission rate and peak 11 height: the amplitude of SAO is greatest in equatorial regions and AO is greatest in mid-latitudes. For interannual variations, 12 we find that OH airglow emission in equatorial regions is modulated by the quasi-biennial oscillation (QBO), while the QBO 13 signal at other latitudes is much weaker than in equatorial regions and can be ignored. The QBO in OH airglow is consistent 14 with the phase variation of the QBO in the tropical lower stratosphere (30km), which is also consistent with the phase variation 15 of the QBO in the migrating diurnal tide. As an important kinetic process affecting OH airglow emission, we suggest that the 16 tides play an important role in the modulation of the OH airglow by the QBO. In addition, we have analyzed the relationship 17 between peak OH airglow emission and solar activity. The results show a good correlation between peak emission rate and 18 solar activity, with a correlation coefficient of 0.89, while peak height shows no significant solar cycle variation, with a 19 correlation coefficient of -0.66. The modulation of peak emission rate by solar activity has significant latitudinal variation. 20 The modulation effect is weakest in the equatorial region and greatest at mid-latitudes in both hemispheres.
ALCOP: Automatic Load-Compute Pipelining in Deep Learning Compiler for AI-GPUs

Pipelining between data loading and computation is a critical tensor program optimization for GPUs. In order to unleash the high performance of latest GPUs, we must perform a synergetic optimization of multi-stage pipelining across the multi-level buffer hierarchy of GPU. Existing frameworks rely on hand-written libraries such as cuBLAS to perform pipelining optimization, which is inextensible to new operators and un-composable with prior tensor compiler optimizations. This paper presents ALCOP, the first framework that is compiler-native and fully supports multi-stage multi-level pipelining. ALCOP overcomes three critical obstacles in generating code for pipelining: detection of pipelining-applicable buffers, program transformation for multi-level multi-stage pipelining, and efficient schedule parameter search by incorporating static analysis. Experiments show that ALCOP can generate programs with 1.23x speedup on average (up to 1.73x) over vanilla TVM. On end-to-end models, ALCOP can improve upon TVM by up to 1.18x, and XLA by up to 1.64x. Besides, our performance model significantly improves the efficiency of the schedule tuning process and can find schedules with 99% of the performance given by exhaustive search while costing 40x fewer trials.
Closing the gap in the tropics: the added value of radio-occultation data for wind field monitoring across the equator

Globally available and highly vertical resolved wind fields are crucial for the analysis of atmospheric dynamics for the benefit of climate studies. Most observation techniques have problems to fulfill both requirements. Especially in the tropics and in the southern hemisphere more wind data availability is required. In this study we investigate the potential of radio occultation (RO) data for climate-oriented wind field monitoring in the tropics, with a specific focus on the equatorial area between ± 5 ◦ latitude. In this region, the geostrophic balance breaks down, due to the Coriolis force term approaching zero. One further 5 aim is to understand how the individual wind components of the geostrophic balance and equatorial balance approximations bridge across the equator and where each component breaks down. We analyze the equatorial balance equation within this latitude band. In a wider range over the tropics, we derive the RO wind fields also using the geostrophic approximation and we compared the RO winds with ERA5 data. From analyzing first the zonal and meridional wind component, we find that the meridional wind component is more volatile in its derivation, however the total wind speed benefits from a computation of 10 both wind components. Investigating next the bias between the RO and ERA5 computed winds, we find that the systematic data bias is smaller than the bias resulting from the approximation itself. As a final aspect we inspected the monthly-mean RO wind data over the full example year 2009. The bias in the upper troposphere and lower stratosphere is mainly smaller than ± 2 ms − 1 , which is in line with the wind field requirements of the World Meteorological Organization. This is encouraging for the use of RO wind fields in climate monitoring over the entire globe including the equatorial region.
Assessing the destructiveness of tropical cyclone by anthropogenic aerosols under an atmosphere-1

21 Intense tropical cyclones (TCs) can cause catastrophic damages to coastal regions after 22 landfall. Recent studies have linked the TC’s devastation to climate change that induces favorable 23 conditions, such as increasing sea-surface temperature, to supercharge the storms. Meanwhile, 24 environmental factors, such as atmospheric aerosols, also impact the development and intensity of 25 TCs, but their effects remain poorly understood, particularly coupled with the ocean dynamics. 26 Here we quantitatively assess the aerosol microphysical effects and aerosol-modified ocean 27 feedbacks during Hurricane Katrina using a cloud-resolving atmosphere-ocean coupled model - 28 Weather Research and Forecasting (WRF) in conjunction with the Regional Ocean Model System 29 (ROMS). Our model simulations reveal that an enhanced destructive power of the storm, as 30 reflected by larger integrated kinetic energy, heavier precipitation, and higher sea-level rise, is 31 linked to the combined effects of aerosols and ocean feedbacks. These effects further result in an 32 expansion of the storm circulation with a reduced intensity because of decreasing moist static 33 energy supply and enhancing vorticity Rossby wave outward propagation. Both accumulated 34 precipitation and storm surge are enhanced during the mature stage with elevated aerosol 35 concentrations, implying exacerbated flooding damage over the coastal region. The ocean 36 feedback following the aerosol microphysical effects tends to mitigate the vertical mixing cooling 37 in the ocean mixing layer and offsets the aerosol-induced storm weakening, by enhancing cloud 38 and precipitation near the eyewall region. Our results highlight the importance of accounting for 39 the effects of aerosol microphysics and ocean-coupling feedbacks to improve the forecast of TC 40 destructiveness, particularly near the heavily polluted coastal regions along the Gulf of Mexico.
Asymptotic expansions of solutions of stochastic differential equations driven by multivariate fractional Brownian motions having Hurst indices greater than

Abstract In this paper, we consider n-dimensional stochastic differential equations driven by multivariate fractional Brownian motion with Hurst indices greater than . Using a Taylor type development we obtain an expansion of expectations for small t, where denotes the solution of the mentioned stochastic differential equation with initial value and is a sufficiently smooth function. Also we compute coefficients appearing in the expansion of in the case when the fractional Brownian motions have the Hurst indices greater than . Finally, we consider the case of commutative vector fields getting Kolmogorov’s backward partial differential equation for the function .
The development and validation of an Inhomogeneous Wind Scheme for Urban Street

The layout of urban buildings shows significant heterogeneity, which leads to the significant spatial inhomogeneity of the wind field in and over the canopy of urban street canyons. However, most of the current urban canopy models do not fully consider the heterogeneity of the urban canopy. Large discrepancies thus exist between the wind speeds simulated by the current urban canopy models and those observed in the street canyon. In this study, a parameterization scheme for wind field, 15 Inhomogeneous Wind Scheme for Urban Street (IWSUS), is developed to better characterize the heterogeneity of the urban canopy. We use a Computational Fuild Dynamics method to generate the IWSUS scheme and compare with observations of wind profile and turbulent flux in and over the street canyon for validation. In IWSUS, the wind speed vertical profiles at six representative positions located in a typical street canyon (i.e., the windward or leeward side of a long straight street, or the inflow or outflow end) are parameterized separately. The wind profile by IWSUS thus can better describe the horizontal 20 heterogeneity of the urban near-surface wind field, e.g., the dynamic drag effect of building in the lower atmosphere layer over the urbanized land use. The validation based on observations shows that the performance of simulation results by IWSUS is better than that by logarithmic-exponential (exp-log) law widely used in the current urban schemes. As we consider typical building arrangement and specific street orientations in IWSUS for wind field simulations, which can better match the distribution characteristics of street canyons around the observation point in the street canyon. The averaged wind profiles and 25 turbulence energy fluxes in the model grids of urban area by IWSUS are also more approach to the observation than those by exp-log law. The normalized mean errors (NME) between the simulated and the observed vertical average wind speed are 49.0% for IWSUS and 56.1% for exp-log law in the range from the ground to four times the average height of the building, and 70% for IWSUS and 285.8% for exp-log law in the street canyon (range from the ground to building top). This study proves that the accuracy of land surface process and near-grounded meteorological process simulations over urban canopy can 30 be improved by fully considering the heterogeneity of the urban canopy layout structures and the inhomogeneous of wind field distributions in and over the street canyon. The IWSUS is expected to be coupled with mesoscale atmospheric models to improve the accuracy of the wind field, land surface energy budget, meteorological, and atmospheric chemistry simulations.
Retrospective: A dynamically configurable coprocessor for convolutional neural networks

In 2008, parallel computing posed significant challenges due to the complexities of parallel programming and the bottlenecks associated with efficient parallel execution. Inspired by the remarkable scalability achieved by networking and storage systems in handling extensive packet traffic and persistent data respectively by leveraging best-effort service, we proposed a new and fundamentally different approach of best-effort computing [1]. Having observed that a broad spectrum of existing and emerging computing workloads were from applications that had an inherent forgiving nature [2], [5], we proposed besteffort computing. The new approach resulted in disproportionate gains in power, energy and latency, while improving performance. While contemplating the concept of best-effort computing [2], we noticed the resurgence of convolutional neural networks, which generated approximate but acceptable outcomes for numerous recognition, mining, and synthesis tasks. The lead author of this retrospective had previously conducted research on neural networks for his doctoral dissertation over a decade ago, and the reemergence of neural networks proved both surprising and exciting. Recognizing the connection between best-effort computing and convolutional neural networks, in 2008 we embarked on developing a programmable and dynamically reconfigurable convolutional neural network capable of performing best-effort computing for various machine learning tasks that inherently allow for multiple acceptable answers. This combination of our thoughts on best-effort computing and the gradual evolution of convolutional neural networks (deep neural networks emerged much later) culminated in our 2010 ISCA work on dynamically reconfigurable convolutional neural networks.
Ultrasound Mid-Air Tactile Feedback for Immersive Virtual Reality Interaction (cid:63)

Ultrasound mid-air haptic (UMH) devices are promising for tactile feedback in virtual reality (VR), as they do not require users to be tethered to, hold, or wear any device. This approach is less cumber-some, easy to set up, can simplify tracking, and leaves the hands free for concurrent interactions. This chapter explores work conducted at CNRS-IRISA dealing with the challenges arising from the integration of UMH interfaces in immersive VR through three main axes. These are discussed in the wider context of the state-of-the-art on UMH for augmented and virtual reality, and illustrated through several VR use-cases. A ﬁrst axis deals with device integration into the VR ecosystem. Interaction in immersive VR is based on the synergy between complex input devices allowing real-time tracking of the user and multimodal feedback devices delivering a coherent visual, auditory and haptic picture of a simulated virtual environment (VE). Using UMH in immersive VR therefore hinges on integrating UMH devices such that their operation does not interfere with other input and feedback devices. It is also critical to ensure that UMH feedback is adequately synchronised and co-located with respect to other stimuli, and delivered within a workspace that is compatible with that of VR interaction. Regarding this ﬁnal point, we propose PUMAH, a robotic solution for increasing the usable workspace of UMH devices. Thesecond and third axes, respectively, focus on stimulus perception and rendering of VE properties. Virtual object properties can be rendered in a variety of ways, through e.g. amplitude modulation (AM) or spatio-temporal modulation (STM), with many parameters (modula-tion frequency, spatial sampling, etc.) coming into play, raising questions about the limits of
Consumer Intention to Use OFD Services Within The TPB Framework: The Impact of The Covid-19 Pandemic Case

This study aims to explain the intention to use OFD services within the TPB framework to improve consumer experience in using OFD and consumers' desire to order food during the COVID-19 pandemic and post-pandemic 19. In this study the variables observed were OFD, consumer desire, consumer experience, and the SDG framework (attitudes, subjective norms and behavioral controls). Every food choice is innovating products or services to address the challenges posed by the COVID-19 pandemic by enhancing the value of the consumer experience and stimulating consumer desire. Structural equation modeling (SEM) was used to verify the research hypothesis and to analyze the intention to use OFD services. An online survey was also conducted and a total of 300 questionnaires were distributed, invalid questionnaires were ignored with incomplete answers, and a total of 236 questionnaires were considered valid. The results of the study are as follows: (1) attitudes, subjective norms, and control of consumer behavior have a significant positive effect on the value of consumer experience in using OFD services before and consumer desires; (2) the value of consumer experience on the previous use of OFD services and consumer desires have a significant and positive effect on the effect of intention to use OFD services; and (3) the values of consumer experiences on the use of OFD services before and consumer desires have a mediating effect on attitudes, subjective norms, behavioral control, and intention to use OFD services. Based on the results of the analysis, OFD managers can identify the main factors that drive consumer intentions to use their services to formulate effective management strategies and create greater business opportunities for their organizations.
Modelling the scores and performance statistics of NBA basketball games

Abstract This paper investigates the problem of modeling and forecasting the outcomes of NBA basketball games based on performance statistics. A bivariate normal mean regression model is developed to model the scores and performance statistics. Two methods for forecasting the performance statistics ex ante are proposed in order to predict the outcomes of NBA basketball games, including the final scores of two teams and the probability that a specific team wins the game. Besides, a betting strategy is developed and efficiency tests in the handicap betting market are conducted. Empirical study shows that the proposed model works well.
Dynamic rupture process of the Mw 7.8 Kahramanmara¸s earthquake (SE T¨urkiye): Variable rupture speed and implications for seismic hazard

We considered various non-uniformities such as branch faults, rotation of stress ﬁeld directions, and changes in tectonic environments to simulate the dynamic rupture process of the 6th February 2023 Mw 7.8 Kahramanmara¸s earthquake in SE T¨urkiye. We utilized near-fault waveform data, GNSS static displacements, and surface rupture to constrain the dynamic model. The results indicate that the high initial stress accumulated in the seismic gap leads to the successful triggering of the East Anatolian Fault (EAF) and the supershear rupture in the northeast segment. Due to the complexity of fault geometry, the rupture speed along the southeastern segment of the EAF varied repeatedly between supershear and subshear, which contributed to the unexpectedly strong ground motion. Furthermore, the triggering of the EAF reminds
Content Based SMS Fraud Detection Using Supervised Learning Approach

: Although modern mobile phones are becoming more and more equipped with a variety of communication media messenger applications, SMS (Short Message Service) is still the preferred choice as a communication medium. It is a messaging technique that makes use of cell phones and smartphones. Spam emails and SMS have been seen to dramatically grow in volume in recent years. With the increased use of mobile devices, there has been a surge in SMS fraud. There is a type of cybercrime which uses text messages to trick and defraud people. Spam communications have been overflowing, leading to violation of personal rights, financial and may be societal issues. Like email spam, the problem of SMS spam can be addressed through governmental, commercial, or technological means. Because SMS broadcasting rates are reasonable, there is a surge in SMS spam, which some people utilize as a substitute for advertising and fraud. Hence, it becomes a major societal matter which needs to be addressed. This project's study suggests using machine learning to identify fraudulent SMS texts. This study's objective is to evaluate the Naive Bayes method with Counter Vectorization's performance in identifying and removing SMS spam. We created a dataset of SMS messages, which comprised both valid messages and fraudulent messages, and utilized this dataset to train machine learning models, by supplying useful message metadata, SMS headers can also be employed in machine learning techniques to weed out spam messages. This report provides the design document for the proposed fraud detection system using ML approach.
Power, mixing and ﬂow dynamics of the novel Allegro TM stirred tank reactor

(cid:1) Allegro STR 50–2000 L bioreactor range is successfully scaled down to 1 L. (cid:1) Agreement of power and mixing number across 1 to 200 L bioreactor scale. (cid:1) Square cross-section of vessel increases impeller power number. (cid:1) Mean ﬂow characterisation of unique vessel geometry. (cid:1) Allegro STR geometry enhances mixing and kinetic energy distribution.
High-resolution downscaling of CMIP6 Earth system and global climate models using deep learning for Iberia

Abstract. Deep learning (DL) methods have recently garnered attention from the climate change community for being an innovative approach to downscaling climate variables from Earth system and global climate models (ESGCMs) with horizontal resolutions still too coarse to represent regional- to local-scale phenomena. In the context of the Coupled Model Intercomparison Project phase 6 (CMIP6), ESGCM simulations were conducted for the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) at resolutions ranging from 0.70 to 3.75∘. Here, four convolutional neural network (CNN) architectures were evaluated for their ability to downscale, to a resolution of 0.1∘, seven CMIP6 ESGCMs over the Iberian Peninsula – a known climate change hotspot, due to its increased vulnerability to projected future warming and drying conditions. The study is divided into three stages: (1) evaluating the performance of the four CNN architectures in predicting mean, minimum, and maximum temperatures, as well as daily precipitation, trained using ERA5 data and compared with the Iberia01 observational dataset; (2) downscaling the CMIP6 ESGCMs using the trained CNN architectures and further evaluating the ensemble against Iberia01; and (3) constructing a multi-model ensemble of CNN-based downscaled projections for temperature and precipitation over the Iberian Peninsula at 0.1∘ resolution throughout the 21st century under four Shared Socioeconomic Pathway (SSP) scenarios. Upon validation and satisfactory performance evaluation, the DL downscaled projections demonstrate overall agreement with the CMIP6 ESGCM ensemble in magnitude for temperature projections and sign for the projected temperature and precipitation changes. Moreover, the advantages of using a high-resolution DL downscaled ensemble of ESGCM climate projections are evident, offering substantial added value in representing regional climate change over Iberia. Notably, a clear warming trend is observed in Iberia, consistent with previous studies in this area, with projected temperature increases ranging from 2 to 6 ∘C, depending on the climate scenario. Regarding precipitation, robust projected decreases are observed in western and southwestern Iberia, particularly after 2040. These results may offer a new tool for providing regional climate change information for adaptation strategies based on CMIP6 ESGCMs prior to the next phase of the European branch of the Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX) experiments.
Lobe-speci c Analysis of Perioperative Chemotherapy for Non-small Cell Lung Cancer Patients

Xi Lei Tianjin Medical University General Hospital Tong Li Tianjin Medical University General Hospital Fuling Mao Tianjin Medical University General Hospital Fan Ren Tianjin Medical University General Hospital Quanying Tang Tianjin Medical University General Hospital Weibo Cao Tianjin Medical University General Hospital Lingling Zu Tianjin Medical University General Hospital Song Xu (  xusong198@hotmail.com ) Tianjin Medical University General Hospital