Miracle-dz/UniFAR-FTUs huggingface dataset:
δLTA: Decoupling Camera Sampling from Processing to Avoid Redundant Computations in the Vision Pipeline

Continuous Vision (CV) systems are essential for emerging applications like Autonomous Driving (AD) and Augmented/Virtual Reality (AR/VR). A standard CV System-on-a-Chip (SoC) pipeline includes a frontend for image capture and a backend for executing vision algorithms. The frontend typically captures successive similar images with gradual positional and orientational variations. As a result, many regions between consecutive frames yield nearly identical results when processed in the backend. Despite this, current systems process every image region at the camera’s sampling rate, overlooking the fact that the actual rate of change in these regions could be significantly lower.In this work, we introduce δLTA (δont’t Look Twice, it’s Alright), a novel frontend that decouples camera frame sampling from backend processing by extending the camera with the ability to discard redundant image regions before they enter subsequent CV pipeline stages. δLTA informs the backend about the image regions that have notably changed, allowing it to focus solely on processing these distinctive areas and reusing previous results to approximate the outcome for similar ones. As a result, the backend processes each image region using different processing rates based on its temporal variation. δLTA features a new Image Signal Processing (ISP) design providing similarity filtering functionality, seamlessly integrated with other ISP stages to incur zero-latency overhead in the worst-case scenario. It also offers an interface for frontend-backend collaboration to fine-tune similarity filtering based on the application requirements.To illustrate the benefits of this novel approach, we apply it to a state-of-the-art CV localization application, typically employed in AD and AR/VR. We show that δLTA removes a significant fraction of unneeded frontend and backend memory accesses and redundant backend computations, which reduces the application latency by 15.22% and its energy consumption by 17%. CCS CONCEPTS• Computing methodologies → Computer vision; • Computer systems organization → System on a chip.
Functional displacement of cortical neuromagnetic somatosensory responses: enhancing embodiment in the rubber hand illusion

The integration of an artificial limb as part of one’s body involves complex neuroplastic changes resulting from various sensory inputs to the brain. While sensory feedback is known to be crucial for embodiment, current evidence points merely to the attenuation of somatosensory processing, while the positive contributions of somatosensory areas to embodiment remain unknown. This study investigated the relationship between embodiment and adaptive neuroplasticity of early-latency somatosensory evoked fields (SEFs) in the primary somatosensory cortex (S1) following the Rubber Hand Illusion (RHI), known to induce short-term artificial limb embodiment. Nineteen healthy adults underwent neuromagnetic recordings during electrical stimulation of the little finger and thumb, before and after the RHI. We found a displacement of early SEF sources. In particular, we observed a correlation between the extent of rubber hand embodiment and specific changes to the m20 component (magnetic equivalent to the N20) in Brodmann Area 3b: a larger displacement and a greater reduction in m20 magnitude predicted the amount of embodiment, highlighting an important functional contribution of this first cortical input. Furthermore, we observed a posteriorly directed m35 displacement towards Area 1, known to be important for visual integration during touch perception (Rosenthal et al., 2023). Our finding that the larger displacement for the m35 did not correlate with the extent of embodiment implies a functional distinction between neuroplastic changes across these two components and areas in their contributions to successful artificial limb embodiment: (i) the earlier neuroplastic changes to m20 may shape the extent of artificial limb ownership, and (ii) the posteriorward shift of the m35 into Area 1 is suggestive of a mechanistic contribution to early visual-tactile integration that initially establishes the embodiment. Taken together, these findings suggest that multiple distinct changes occur during early-latency SEFs and their displacement in S1 last beyond the duration of the illusion and are important for the successful integration of an artificial limb within the body representation.
Integration of rate and temporal codes by hippocampal cell-assemblies supports theta phase coding of episodic information

Spatial information is encoded by location-dependent hippocampal place cell firing rates and sub-second, rhythmic modulation of spike times. These ‘rate’ and ‘temporal’ codes have primarily been characterized in low-dimensional environments under limited cognitive demands; but how is coding configured in complex environments when individual place cells signal several locations, individual locations contribute to multiple routes and functional demands vary? Quantifying rat CA1 population dynamics during a decision-making task, we show that the phase of individual place cells’ spikes relative to the local theta rhythm shifts to differentiate activity in different place fields. Theta phase coding also disambiguates repeated visits to the same location during different routes, particularly preceding spatial decisions. Using unsupervised detection of cell assemblies alongside theoretical simulation, we show that integrating rate and phase coding mechanisms dynamically recruits units to different assemblies, generating spiking sequences that disambiguate episodes of experience and multiplexing spatial information with cognitive context.
Molecular and neuronal mechanisms governing sexually dimorphic prioritization of innate behaviors

Males and females display dimorphic innate behaviors and further prioritize them differently. How the sexually dimorphic behavioral prioritization is mediated is poorly understood. In Drosophila, around 60 pairs of pC1 neurons in males and 6 pairs in females control sexually dimorphic behaviors. We show that an increase of pC1 activity determines the sequential execution of behaviors such as sex, aggression, sleep, and feeding in a sex-specific way. We identify distinct subsets of pC1 neurons in both males and females that regulate different behaviors. We further discover diuretic hormone 44 (DH44) and acetylcholine (ACh) as co-transmitters in pC1 neurons. ACh promotes the execution of each behavior in both sexes, whereas DH44 functions in a sex-specific and activity-dependent manner to establish the sexually dimorphic behavioral outputs. These findings provide a framework for understanding the molecular and cellular mechanisms underlying sexually dimorphic prioritization of innate behaviors.
Working Papers / Documents de travail

We investigate the effect of changing ENSO patterns on global commodity prices, including energy, metals/minerals and agriculture real commodity price subsets, while controlling for global economic output and interest rate via a global factor local projections (GFALP) model. We study the responses to climate shocks using a nonlinear multivariate model to assess differential effects across ENSO climate regimes. We find that commodity inflation is reactive to El Niño and La Niña events, but that this sensitivity can occur either in the shortor long-term depending on the commodity under investigation. For commodities in agriculture, we uncover an asymmetric influence of El Niño and La Niña shocks. More central banks are questioning whether climate change is part of their mission to stabilize prices. Our results indicate the existence of a direct link between weather anomalies and commodity inflation, one that should be integrated into the central banks’ inflation targeting framework. JEL Classification: C32, F44, O13, Q54.
Working Papers / Documents de travail

We examine the issue of stability of stochastic endogenous growth. First, stochastic stability concepts are introduced and applied to stochastic linear homogenous differential equations to which several stochastic endogenous growth models reduce. Second, we apply the mathematical theory to two models, starting with the stochastic AK model. It’s shown that in this case exponential balanced paths, which characterize optimal trajectories in the absence of uncertainty, are not robust to uncertainty: the economy may almost surely collapse at exponential speed even though productivity is initially arbitrarily high. Finally, we revisit the seminal global diversification endogenous growth model (Obstfeld, 1994): taking into account stochastic stability calls for a redefinition of the mean growth concept, which leads to revisit the established wisdom on the growth effect of global diversification.
Rupture Risk Assessment of Hemodynamics in Intracranial Aneurysm Role Confounding Factor Dissemination? The CFD: Computational Fluid Dynamics or

SUMMARY: Image-basedcomputationalﬂuiddynamicsholdsaprominentpositionintheevaluationofintracranialaneurysms,especially as a promising tool to stratify rupture risk. Current computational ﬂuid dynamics ﬁndings correlating both high and low wall shear stress with intracranial aneurysm growth and rupture puzzle researchers and clinicians alike. These conﬂicting ﬁndings may stem from inconsistent parameter deﬁnitions, small datasets, and intrinsic complexities in intracranial aneurysm growth and rupture. In Part 1 of this 2-part review, we proposed a unifying hypothesis: both high and low wall shear stress drive intracranial aneurysm growth and rupture through mural cell–mediated and inﬂammatory cell–mediated destructive remodeling pathways, respectively. In the present report, Part 2, we delineate different wall shear stress parameter deﬁnitions and survey recent computational ﬂuid dynamics studies, in light of this mechanistic heterogeneity. In the future, we expect that larger datasets, better analyses, and increased understanding of hemodynamic-biologic mechanisms will lead to more accurate predictive models for intracranial aneurysm risk assessment from computational ﬂuid dynamics.
3D point cloud registration based on the assistant camera and Harris-SIFT

3D(Three-Dimensional) point cloud registration technology is the hot topic in the field of 3D reconstruction, but most of the registration method is not real-time and ineffective. This paper proposes a point cloud registration method of 3D reconstruction based on Harris-SIFT and assistant camera. The assistant camera is used to pinpoint mobile 3D reconstruction device, The feature points of images are detected by using Harris operator, the main orientation for each feature point is calculated, and lastly, the feature point descriptors are generated after rotating the coordinates of the descriptors relative to the feature points’ main orientations. Experimental results of demonstrate the effectiveness of the proposed method.
Heat and Water-vapor Budget in Large and Small Scale in Winter over the middle of the Japan Islands

Heat and water-vapor budget in large scale and small scale network are analysed by using radiosonde observations over the middle of the Japan Islands during the period from Feb. 16th to Feb. 20th, 1962. The calculation scheme suitable for this analysis is introduced at first. Budget of heat and water-vapor are compared mainly in the relation between the condensation and heating due to released latent heat. The problems of vertical eddy transport and liquid-water content are also discussed as the important factors in budget analysis. Finally, the results of heat and water-vapor budget are related to the synoptic weather situations.
A convenient urban landscape 3D visualization method

This paper brought forward a way based on CAD data and high-resolution remote sensing image to create 3D models of city landscape.This method is used to create 3D models using polygons of the buildings as underside and the number of floors as heights in 2D GIS software.Then it put the models,orthograph and DEM together in a proper way.In a case study of Nanjing Xinjiekou,the results show that the method,which can be widely used in urban GIS-related research,is an economic and efficient urban landscape 3D visualization way.
P260 Working conditions and health of minas gerais court workers, brazil: a longitudinal study (justicel-mg)

The Brazilian judiciary system is being changed. Technological innovations and new management practices are in progress in order to obtain a greater efficiency in serving the population. Nevertheless, this new context has costs for the Court workers. The present report aims to describe the development of a longitudinal study about labour conditions and health status in Minas Gerais State Court, Brazil. All permanent workers (N = 12,215) allocated in the 296 Minas Gerais law districts was eligible. Ineligibility criteria were pregnancy, vacation and sick leave during the data collection phase. Data was collected by phone; the first wave was in 2016, the second one will be realised in 2017. The estimation of the sample size (n = 1370) considered the following parameters: number of workers, prevalence of sick leave of 40% and 95% confidence interval. A stratified proportional random sampling was performed; the variables considered for stratification were function, law district, age and sex. Five groups of outcomes were developed: 1) life habits, including food consumption, physical activity, and smoking; 2) nutrition status, measured as self-reported weight and height (body mass index); 3) mental health (psychiatric medication use and sleep problems); 4) chronic diseases; and 5) sick leave. Regarding organisational risk factors, we assessed environmental conditions, psychological harassment, job demands, work control, social support, reward and exposure to technological innovation (electronic tools use). Sociodemographic and job characteristics were also controlled for future analysis. The longitudinal follow-up will allow us to detect risk and protective factors for general health among Minas Gerais Court workers. The results will be useful to support health policies in the Brazilian judiciary sector.
A Simulation of Appliance Control Using ESP8266 Microcontroller

The fast-moving and revolutionary technology that makes daily life more convenient has recently attracted a lot of attention to control appliances at home. Digitalization and automation have almost completely taken over. The Internet of Things (loT) and mobile technology will make appliances control at home simpler and more common. This article describes the simulation of design and implementation of remote appliances/devices controller that allows users to manage all of their devices through an Android app on a smartphone. In the proposed research, android platform serves as the basis for creating mobile application wherein the ESP8266 microcontroller board and Android app communicate using the HTTP web interface. Espressif Systems' ESP8266 is a low-cost Wi-Fi microprocessor with integrated TCP/IP networking software and a microcontroller. The aim of the proposed work is to develop an Android application that allows users to control GPIO (General Purpose Input/Output) pins on an external device using an IP address. By enabling users to establish a connection and send HTTP requests, they can conveniently manipulate the state of GPIO pins. The work strives to simplify the process of controlling external devices through a mobile application, enhancing user convenience and accessibility. To confirm the proposed idea's efficacy and applicability, it is tested in the lab and in real-world situations. Furthermore, it is made sure that the technology and hardware required for the concept put forward are affordable and widely accessible. The outcomes of the experiment underline its importance and ratify the concept's proof.
Inverter Threshold Comparator Based Optimized 3-Bit Flash ADC

In modern electronics, an Analog-to-Digital Converter (ADC) plays a pivotal role by converting continuous analog signals into discrete digital representations, facilitating easy processing by microprocessors. Traditional Flash ADCs use op-amp-based bulky comparators whereas ITC-based Flash ADC uses only a single inverter as a comparator. In this work, ITC-based topology is combined with a mux-based encoder, thereby limiting the total number of transistors to 36 and yielding an area of 0.0039 mm2 and power consumption of 27.44 uW for a 10 MS/s sampling rate, after layout extraction.
Software System for Determining and Visualizing Locations and Routes of Underwater Robots

This paper presents a software system for visualization of location and route of an underwater robot. The visualization is based on photos of seabed, which are taken by the camera of the robot. The robot also takes records for the photographed objects and stores them into KML format. The photos and the KML data are transferred to a device (a laptop or a computer), where the data are processed and the location and the traveled route of the robot are shown on a map in the web interface of the system. The robot and the presented system can be used to research the seabed relief and habitats, thus avoiding participation of divers and decreasing the risks for human lives under water.
Decision Tree Based Early Termination Algorithm for Affine Prediction in AVS3

The third generation of Audio Video Standard(AVS3) has adopted affine prediction(including affine merge mode and affine inter mode), which can characterize non-translational motions such as rotation, zooming, and shearing. Though affine prediction leads to BD-Rate saving, it also results in substantial computational complexity. In this paper, we propose a fast algorithm to address this problem. Some useful features are introduced and used to train five decision tree classifiers to skip unnecessary calculations in affine prediction. Experimental results show that compared to HPM 14.0, the proposed algorithm reduces 19% affine merge time, 18% affine inter time, and 6% encoding time, with negligible coding performance loss under random access(RA) configurations.
Coverage Analysis Based on Throughput Decay Modeling for 5G SA Communication

With the evolution of mobile networks, several concepts were implemented to perform high throughput. Among these features, higher order modulations and Multiple Input and Multiple Output (MIMO) antennas can increase the communication capabilities. Considering the 5G system, many features can additionally be adopted, such as higher frequency bands, larger bandwidths and different sub-0carrier spacing options. In this context, the signal coverage distance also depends on these features. However, the large-scale decay does not consider such characteristics. Thus, this study proposes a maximum coverage analysis and throughput decay modeling according the the propagation loss based on laboratory measurements. These measurements consider the throughput attenuation due to the fading channel through Reference Signal Received Power (RSRP) levels, as well as MIMO and modulation for the n78 band (3500 MHz). The results point to poorer coverage compared to the classical propagation studies. A multi-slope model dependent on the network configurations is presented, which can be an useful tool for 5G coverage planning.
Memristor-Based Neural Network Implementation with Adjustable Synaptic Weights in LTSPICE

The memristors are innovative electronic elements with nano-sized structure and with very good memory and switching abilities. They have very low power consumption and a good compatibility to CMOS integrated chips, and they could be used in neural networks, memories, and many other schematics. In this paper an LTSPICE model of artificial neural network with memristor-based synapses is proposed. In this network, each synapse is realized with only one memristor, thus providing a higher reduction in circuit complexity and with main benefit of that individual memristor resistance value can be adjusted with external control voltage signals. The summing and scaling component implementations are based on op-amps and memristors. We use the most common logarithmic-sigmoidal activation function and it is realized by a voltage-controlled source. The operation of the proposed memristor neural network is analyzed and simulated in both L TSPICE and MATLAB, and the derived results are compared and verified successfully. The proposed memristor-based neural network is a significant step for engineering low power complex networks in very high-density integrated circuits and chips.
A Methodology for GNSS Signals Acquisition for Non-Conventional Spectral Estimation Techniques Evaluation Using Software-Defined Radio

In this paper, we present a signal acquisition and verification methodology to code a performance evaluation study of several non-conventional spectral estimation techniques for spectrum sensing, with the objective of detecting weak GNSS signals transmitted in high noise conditions. Traditionally, the Fast Fourier Transform has been used as a mechanism for performing correlation operations in the spectral domain for Global Navigation Satellite System (GNSS) signal acquisition. However, non-conventional techniques have been implemented to increase the robustness of the detector in low signal-to-noise ratio (SNR) environments. We implemented a Global Positioning System (GPS) signal receiver in GNU Radio to compare non-conventional spectral estimation techniques such as Burg, Yule-Walker, and Correlogram, for the purpose of detecting real GNSS signals under higher noise conditions.
Synchronization of Chaotic Systems Using Novel Sliding Mode Neural Network Controller

In this paper, a novel exponentially perturbed sliding mode neural (NEPSMN) control scheme is investigated for the synchronous control problem of chaotic systems with unknown parameters and disturbances. The proposed control scheme synchronizes the master-slave system by designing a disturbance observer that reduces the switching gain of the sliding mode control. In addition to that, a radial-basis functions neural network (RBF-NN) with adaptive wights is used to describe the uncertainty in the master-slave dynamics. It is shown that by using this control scheme, the synchronization error dynamics is stable and the error quickly convergences to zero. In addition, it has a strong ability to suppress external disturbances. By using the Lyapunov's stability theory, it is proved that the new control scheme guarantees the stability of a third-order nonlinear chaotic master-slave system. Beside that, the simulation results show the performance superiority of the proposed controller in comparison to a conventional (PI) controller.
Emerging Ubiquitous Systems and Pervasive Networks ( EUSPN-2013 ) An Optimal Energy Efficient and Minimum Delay Scheduling for Periodic WSN Applications

Wireless Sensor Network (WSN) enables pervasive, ubiquitous, and seamless communication with the physical world. This paper investigates an optimal cross-layer joint routing and scheduling problem for WSN with periodic data collection. The problem is formulated as an Integer Linear Program (ILP) model such that a joint scheduling and routing is developed to maximize network lifetime and minimize delay. In this paper, an ILP model with multi objective cost function is proposed. The proposed ILP model represents the operation of Energy-Efficient Distributed Schedule-Based (EEDS) protocol. The ILP model is solved for different network configurations. The optimal solutions assuming different objectives are compared. © 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [name organizer]