Miracle-dz/UniFAR-FTUs huggingface dataset:
Domain generalization of 3D semantic segmentation in autonomous driving

Using deep learning, 3D autonomous driving semantic segmentation has become a well-studied subject, with methods that can reach very high performance. Nonetheless, because of the limited size of the training datasets, these models cannot see every type of object and scene found in real-world applications. The ability to be reliable in these various unknown environments is called domain generalization.Despite its importance, domain generalization is relatively unexplored in the case of 3D autonomous driving semantic segmentation. To fill this gap, this paper presents the first benchmark for this application by testing state-of-the-art methods and discussing the difficulty of tackling Laser Imaging Detection and Ranging (LiDAR) domain shifts.We also propose the first method designed to address this domain generalization, which we call 3DLabelProp. This method relies on leveraging the geometry and sequentiality of the LiDAR data to enhance its generalization performances by working on partially accumulated point clouds. It reaches a mean Intersection over Union (mIoU) of 50.4% on SemanticPOSS and of 55.2% on PandaSet solid-state LiDAR while being trained only on SemanticKITTI, making it the state-of-the-art method for generalization (+5% and +33% better, respectively, than the second best method). The code for this method is available on GitHub: https://github.com/JulesSanchez/3DLabelProp.
Too Slow to Be Useful? On Incorporating Humans in the Loop of Smart Speakers

Real-time crowd-powered systems, such as Chorus/Evorus, VizWiz, and Apparition, have shown how incorporating humans into automated systems could supplement where the automatic solutions fall short. However, one unspoken bottleneck of applying such architectures to more scenarios is the longer latency of including humans in the loop of automated systems. For the applications that have hard constraints in turnaround times, human-operated components' longer latency and large speed variation seem to be apparent deal breakers. This paper explicates and quantifies these limitations by using a human-powered text-based backend to hold conversations with users through a voice-only smart speaker. Smart speakers must respond to users' requests within seconds, so the workers behind the scenes only have a few seconds to compose answers. We measured the end-to-end system latency and the conversation quality with eight pairs of participants, showing the challenges and superiority of such systems.
Finite difference scheme for automatic costate calculation

A method for the automatic calculation of costates using only results obtained from direct optimization techniques is presented. The approach is based on finite differences and exploits the relation between the costates and certain sensitivities of the cost function. The complete theory for treating free, control constrained, interior-point constrained, and state constrained optimal control problems is presented. An important advantage of the method presented here is that it does not require a priori identification of the optimal switching structure. As a numerical example, a state constrained version of the Brachistochrone problem is solved, and the results are compared to the optimal solution obtained from Pon try a gin's minimum principle. The agreement is found to be excellent.
Inexact bilevel stochastic gradient methods for constrained and unconstrained lower-level problems

Two-level stochastic optimization formulations have become instrumental in a number of machine learning contexts such as continual learning, neural architecture search, adversarial learning, and hyperparameter tuning. Practical stochastic bilevel optimization problems become challenging in optimization or learning scenarios where the number of variables is high or there are constraints. In this paper, we introduce a bilevel stochastic gradient method for bilevel problems with lower-level constraints. We also present a comprehensive convergence theory that covers all inexact calculations of the adjoint gradient (also called hypergradient) and addresses both the lower-level unconstrained and constrained cases. To promote the use of bilevel optimization in large-scale learning, we introduce a practical bilevel stochastic gradient method (BSG-1) that does not require second-order derivatives and, in the lower-level unconstrained case, dismisses any system solves and matrix-vector products.
Mode description of the dynamical evolution of an acousto-optic bistable device

An analysis of the output of an acousto-optic bistable device is presented in relation to the modes arising from the linear stability analysis of the equation describing the system. The second mode is shown to undergo a period-doubling sequence when the first mode is selectively attenuated. Finally, periodic oscillations occuring inside the chaotic domain are described in terms of coupling between these modes.
Phase-field simulation of thermal conductivity in porous polycrystalline microstructures

Mesoscale computer simulations are used to study the effective thermal conductivity of two-dimensional polycrystalline model microstructures containing finely dispersed stationary voids. The microstructural evolution is captured by phase-field modeling in which the competing mechanisms of curvature-driven grain-boundary (GB) migration and Zener pinning due to the void/grain-boundary interactions control the grain-growth kinetics. We investigate porosity fractions between 0% and 8% by systematically increasing the number of voids in the simulation cell. The temperature distribution throughout the microstructure at progressive instances in time is calculated by solving the solid-state heat-conduction equation. The thermal conductivity of each grid point is assigned a value according to the microstructural feature it represents (grain interiors, GBs, and voids) as determined by the phase-field order parameters. The effective conductivities of the microstructures are analyzed with respect to average grain siz.
Development of a GIS Based Public Transport Composite Social Need Index in Jeddah

Provision of public transport is critical for all social groups with high need. The provision of effective public transport system in Jeddah is at the top priorities of the national, regional and local plans. This paper attempts to develop a public transport composite social need index in Jeddah using GIS. Population density, car ownership, family size and income level indicators were considered for identifying the social need in Jeddah. Results indicate that Jeddah is in high social need for public transport and the provision of an efficient public transport is crucial for the city. The composite social need index has shown both dispersed and clustered patterns of high need for public transport in Jeddah. The results of this study facilitate the identification of the high social need for public transport in Jeddah. Further studies are highly recommended to include other social need indictors in Jeddah city.
Effects of seed size and toucan regurgitation on the germination of the tropical tree Eugenia uniflora

Abstract Understanding the quality of seed dispersal effectiveness of frugivorous species can elucidate how endozoochory structures tropical forests. Large seeds, containing more resources for growth, and gut passage by frugivores, which remove seed pulp, both typically enhance the speed and probability of germination of tropical seeds. However, the interaction of seed size and gut passage has not been well studied. We assessed the role of two species of toucans (Ramphastos spp.) in seed germination of the tropical tree Eugenia uniflora, which produces seeds that vary considerably in size (3.7–14.3 mm), using 151 control and 137 regurgitated seeds in germination trials. We found that toucan regurgitation did not increase germination success, although 93.4% germinated compared to 76.8% of control seeds; however, larger seeds germinated more often at faster rates. Although only marginally significant, germination rates were 3.6× faster when seeds were both large and regurgitated by toucans, demonstrating that toucan regurgitation can disproportionally benefit larger E. uniflora seeds. As tropical forests are increasingly disturbed and fragmented by human activities, the ability of toucans to continue providing seed dispersal services to degraded habitats may be vital to the persistence of many tropical plants that contain larger seeds and depend on larger dispersers.
Detecting Attacks on Computer Networks Using Artificial Intelligence Algorithms

This paper presents a neural network model which was developed and trained to detect attacks on computer networks and to identify the differences indicating what distinguishes them from the regular network traffic. The influence of some parameters on the operation of the network was examined in order to select those characteristic for cyberattack. A certain number of models was tested for binary and multi-class classification. The accuracy of recognition by the network was evaluated for both the entire set and individual categories of the network traffic. The results obtained are promising based on comparison to those published in related work studies on intrusion detection systems.
Bonding state of the C60 molecule adsorbed on a Si(111)-(7X7) surface

We report here the measurements of the valence spectra, the C $1s$ and the Si $2p$ core-level spectra of ${\mathrm{C}}_{60}$ molecules adsorbed on a $\mathrm{Si}(111)\ensuremath{-}(7\ifmmode\times\else\texttimes\fi{}7)$ surface, using photoelectron spectroscopy. In the valence spectra, the highest occupied molecular orbital (HOMO) of a ${\mathrm{C}}_{60}$ splits into two peaks at a coverage lower than 0.25 ML. The binding energies of the split peaks are 1.8 and 2.4 eV. Taking into account the polarization-dependence of the valence spectra and the binding energy of the C $1s$ core-level spectra, it is found that the 2.4-eV peak observed in the valence spectra is the covalent bonding state between a ${\mathrm{C}}_{60}$ molecule and the Si substrate, and that the 1.8-eV peak is the shifted HOMO. The Si $2p$ core-level spectra suggest that the bonding site is localized at the interface. We also present the energy-level scheme of the bonding state in terms of the symmetry of the HOMO.
Periodic entrainment of power dropouts in mutually coupled semiconductor lasers

We examine the effect of current modulation in the irregular dropout dynamics exhibited by two mutually coupled semiconductor lasers. Our experimental results show that a weak periodic modulation in the injection current of one of the lasers entrains the power dropouts in a very efficient way. It is also observed that the laser with the highest frequency leads the dynamics independent of which laser is modulated. As a result, the entrainment is anticipative when modulation is applied to the laser with lowest frequency. Numerical simulations of a model based on delay-coupled rate equations successfully reproduce the behavior observed.
Optimal tracking performance of networked control systems with channel input power constraint

In this study, the optimal tracking performance of multiple-input multiple-output (MIMO) networked control systems is investigated. The system under consideration is finite-dimensional, linear time-invariant over an additive white Gaussian noise (AWGN) channel between the controller and the plant. The power of the tracking error is adopted as the measure of the performance and is minimised subject to the channel input power constraint searching through all stabilising two-parameter controllers. It is shown that, under the channel input power constraint, the optimal tracking performance is closely dependent on non-minimum phase zeros, unstable poles of the plant and the characteristics of the signals and the channel. Finally, computer simulations are provided to illustrate the analytical results obtained.
Device Isolation by Plasma Treatment for Planar Integration of Enhancement/Depletion-Mode AlGaN/GaN High Electron Mobility Transistors

We demonstrate a new planar fabrication technology for integrating enhancement/depletion (E/D) mode AlGaN/GaN high electron mobility transistors (HEMTs) using fluoride plasma treatment techniques. The CF4 plasma treatment is used in two separate steps to achieve two objectives: 1) active device isolation; and 2) threshold voltage control for the E-mode HEMT formation. Compared with the devices formed by standard mesa etching, the HEMTs by planar process have comparable DC characteristics, with no obvious difference in device isolation. By using the planar process, the E/D-mode HEMTs are integrated on the same chip, and a direct-coupled FET logic inverter and a 17-stage ring oscillator are fabricated. When the supply voltage is 4.5 V, the ring oscillator yields a frequency of 146 MHz, corresponding to a propagation delay of 201 ps/stage.
Astrophysical Jet Experiments with Colliding Laser-produced Plasmas

Presented are the results of experiments in which jets are created through the collision of two laser-produced plasmas. These experiments use a simple “v-foil” target design: two thin foils are placed at an angle of 140° to each other and irradiated with a high-energy laser. The plasmas from the rear face of these foils collide and drive plasma jets moving with a velocity of ~300 km s−1. By carefully choosing the foil thickness and material to suit the laser conditions available, it has proven possible to create plasma jets for which the relevant scaling parameters show significant overlap with those of outflows associated with young stellar objects (YSOs). Preliminary results are also shown from experiments to study the effect of an ambient gas on jet propagation. Nominally identical experiments are conducted either in vacuum or in an ambient medium of 5 mbar of nitrogen gas. The gas is seen to increase the jet collimation and to introduce shock structures at the head of the outflow.
Top-down effects in motor generalization

To generate adaptive movements we must generalize what we have previously learned to novel situations. The generalization of adapted movements has typically been framed as a consequence of neural tuning functions that overlap for similar movement kinematics - what might be considered bottom-up generalization. However, as is true in many domains of human behavior, generalization can also be framed as the result of deliberate decisions about how to act (top-down generalization). Here we attempt to broaden the scope of theories about motor generalization, hypothesizing that part of the typical motor generalization function can be characterized as a consequence of top-down decisions concerning the subjective similarity of different movement contexts. We tested this proposal by having participants make explicit similarity ratings over both traditional kinematic contextual dimensions (movement direction) and more abstract contextual dimensions (target shape), and perform a visuomotor adaptation generalization task where trials varied over those dimensions. Across five experiments, we measured the relationship between subjective similarity ratings and motor generalization. In some cases this link was rather strong, though it was determined by both task-relevance and explicit instruction. These results support a broadening of the descriptive framework used to understand the generalization of motor behaviors and support a more careful deployment of instructions in generalization studies. Significance Statement Generalization describes the transfer of knowledge from one context to another, and is typically thought to result from a higher-order inference process. However, in the motor adaptation domain, generalization is thought to arise from neural representations tuned to low-level kinematics. To bridge these differing views, we measured peoples’ subjective similarity judgements of different task contexts during sensorimotor adaptation. We found that motor generalization was closely linked to participant’s subjective judgements, and that explicit instructions about the consequential dimension of different contexts further shaped generalization. These findings emphasize that in addition to low level kinematic considerations, top-down inferences about which action to take in a given context should be considered as another key component of motor generalization.
Discordant results among MHC binding affinity prediction tools

A large number of machine learning-based Major Histocompatibility Complex (MHC) binding affinity (BA) prediction tools have been developed and are widely used for both investigational and therapeutic applications, so it is important to explore differences in tool outputs. We examined predictions of four popular tools (netMHCpan, HLAthena, MHCflurry, and MHCnuggets) across a range of possible peptide sources (human, viral, and randomly generated) and MHC class I alleles. We uncovered inconsistencies in predictions of BA, allele promiscuity and the relationship between physical properties of peptides by source and BA predictions, as well as quality of training data. Our work raises fundamental questions about the fidelity of peptide-MHC binding prediction tools and their real-world implications.
Controlling the bioelectrical properties of neurons with ferritin-based Magnetogenetics

Magnetogenetics promises remote control of neurons, but its validity is questioned due to controversies surrounding the underlying mechanisms and deficits in reproducibility. Recent studies discovered that ferritin, used in Magnetogenetics, transduces radiofrequency (RF) magnetic fields into biochemical signals (reactive oxygen species and oxidized lipids). Magnetic stimulation of ferritin-tethered TRPV channels induces Ca2+ responses and modulates behavior but electrophysiological studies indicate that a particular channel, Magneto2.0, is ineffective in affecting the neuronal bioelectrical properties. We investigated this problem using the Magnetogenetic technique FeRIC. We resolved the electromagnetic interference caused by RF in patch-clamp recordings and supported the data with voltage imaging experiments. In neurons expressing TRPV4FeRIC, RF depolarizes the membrane potential and increases the spiking frequency. In neurons expressing the chloride-permeable TMEM16AFeRIC, RF hyperpolarizes the membrane potential and decreases the spiking frequency. Our study reveals the control of neuronal bioelectrical properties with Magnetogenetics that is non-instantaneous, long-lasting, and moderate, but effective and comparable to that induced by endogenous signaling molecules.
Pynapple, a toolbox for data analysis in neuroscience

Datasets collected in neuroscientific studies are of ever-growing complexity, often combining high dimensional time series data from multiple data acquisition modalities. Handling and manipulating these various data streams in an adequate programming environment is crucial to ensure reliable analysis, and to facilitate sharing of reproducible analysis pipelines. Here, we present Pynapple, the PYthon Neural Analysis Package, a lightweight python package designed to process a broad range of time-resolved data in systems neuroscience. The core feature of this package is a small number of versatile objects that support the manipulation of any data streams and task parameters. The package includes a set of methods to read common data formats and allows users to easily write their own. The resulting code is easy to read and write, avoids low-level data processing and other error-prone steps, and is open source. Libraries for higher-level analyses are developed within the Pynapple framework but are contained within in a collaborative repository of specialized and continuously updated analysis routines. This provides flexibility while ensuring long-term stability of the core package. In conclusion, Pynapple provides a common framework for data analysis in neuroscience. Highlights An open-source framework for data analysis in systems neuroscience. Easy-to-use object-oriented programming for data manipulation. A lightweight and standalone package ensuring long-term backward compatibility.
Disruption of fos causes craniofacial anomalies in developing zebrafish

Craniofacial development is a complex and tightly regulated process and disruptions can lead to structural birth defects, the most common being nonsyndromic cleft lip and palate (NSCLP). Previously, we identified FOS as a candidate regulator of NSCLP through family-based association studies, yet its specific contributions to oral and palatal formation are poorly understood. This study investigated the role of fos during zebrafish craniofacial development through genetic disruption and knockdown approaches. Fos was expressed in the periderm, olfactory epithelium and other cell populations in the head. Genetic perturbation of fos produced an abnormal craniofacial phenotype with a hypoplastic oral cavity that showed significant changes in midface dimensions by quantitative facial morphometric analysis. Loss and knockdown of fos caused increased cell apoptosis in the head, followed by a significant reduction in cranial neural crest cells (CNCCs) populating the upper and lower jaws. These changes resulted in abnormalities of cartilage, bone and pharyngeal teeth formation. Periderm cells surrounding the oral cavity showed altered morphology and a subset of cells in the upper and lower lip showed disrupted Wnt/β-catenin activation, consistent with modified inductive interactions between mesenchymal and epithelial cells. Taken together, these findings demonstrate that perturbation of fos has detrimental effects on oral epithelial and CNCC-derived tissues suggesting that it plays a critical role in zebrafish craniofacial development and a potential role in NSCLP. Summary statement Perturbation of fos, a candidate gene associated with nonsyndromic cleft lip and palate in humans, causes a distinctive orofacial phenotype in zebrafish as a result of abnormal development of craniofacial tissues. Disruption of fos in the oral epithelial, cranial neural crest and Wnt responsive cell populations around the oral cavity causes anomalies that suggest a potential role in the etiology of NSCLP.
Asymmetric Switching of Ferroelectric Polarization in a Heteroepitaxial BaTiO3 Thin Film Capacitor

Asymmetric switching of ferroelectric polarization was measured and analyzed for a heteroepitaxial BaTiO3 thin film of 58 nm thickness. The BaTiO3 film prepared on a SrRuO3/SrTiO3 substrate by radio-frequency magnetron sputtering has a c-axis oriented normal to the surface which is 3% longer than that of the bulk due to lattice misfit between SrRuO3 and BaTiO3. When positive and negative voltage pulses of the same amplitude were sequentially applied, asymmetric responses were observed in the transient current. Although the switching charge densities Qsw were the same for both the polarities, the switching time ts was longer and the peak current imax was smaller for the positive response. From the analyses of the transient current, the asymmetric switching of polarization was attributed to the discrepancy in coercive voltages Vc between polarities.