Miracle-dz/UniFAR-FTUs huggingface dataset:
Highly accurate lidar-based mapping and localization for mobile robots

This thesis contributes novel concepts, methods, and algorithms to the topic of mapping and localization for mobile robots. Mapping is the process of building a model of the robot’s environment based on a collection of sensor measurements, while localization refers to the process of using the resulting map and incoming sensor measurements to estimate the current location of the robot. Together, mapping and localization enable the robot to navigate the world – a prerequisite for any meaningful application of a mobile robot. All of our contributions assume that the mobile robot is equipped with a lidar sensor. Lidar is an acronym of “light detection and ranging”, hinting at the operating principle of a lidar sensor: Typically, it continuously emits light pulses, waits for each pulse to be reflected by a nearby object, measures the time of flight, and uses this measurement to compute the distance to the object. Our first contribution is a novel mathematical model for lidar sensors. By describing the interaction between the sensor and its environment mathematically, it constitutes the theoretical centerpiece of any mapping and localization algorithm. In contrast to related approaches, the proposed model formulates the reflection probability of a light ray emitted by the lidar as an exponential decay process, hence the name decay-rate model. This formulation yields several advantages compared to existing approaches, the most important being that the model makes use of the full ray-path information contained in the measurements. In this way, it achieves higher localization accuracy than comparable methods, which process only part of this information. To the best of our knowledge, it is also the first beam-based lidar sensor model that is not bound to the notion of voxels. Consequently, the decay-rate model is the first model to truly enable continuous mapping, a fact we make use of in our third contribution. The second contribution advances the way in which grid maps produced by the reflection model or the decay-rate model represent the world. Conventionally, these models are used to create maximum-likelihood grid maps of the robot’s environment. Maximum-likelihood maps encode for each cell the
Robust servo-control for underwater robots using banks of visual filters

We present an application of machine learning to the semi-automatic synthesis of robust servo-trackers for underwater robotics. In particular, we investigate an approach based on the use of Boosting for robust visual tracking of color objects in an underwater environment. To this end, we use AdaBoost, the most common variant of the Boosting algorithm, to select a number of low-complexity but moderately accurate color feature trackers and we combine their outputs. The novelty of our approach lies in the design of this family of weak trackers, which enhances a straightforward color segmentation tracker in multiple ways. From a large and diverse family of possible filters, we select a small subset that optimizes the performance of our trackers. The tracking process applies these trackers on the input video frames, and the final tracker output is chosen based on the weights of the final array of trackers. By using computationally inexpensive, but somewhat accurate trackers as members of the ensemble, the system is able to run at quasi real-time, and thus, is deployable on-board our underwater robot. We present quantitative cross-validation results of our spatio-chromatic visual tracker, and conclude by pointing out some difficulties faced and subsequent shortcomings in the experiments we performed, along with directions of future research in the area of ensemble tracking in real-time.
Adsorption Deformation and Structural Transitions in Metal−Organic Frameworks: From the Unit Cell to the Crystal

Much attention has recently been focused on soft porous crystals, a fascinating subclass of metal–organic frameworks that behave in a remarkable stimuli-responsive fashion, presenting structural changes of large amplitude in response to guest adsorption, mechanical pressure, or variations in temperature. In this Perspective, we summarize the recently developed thermodynamic and mechanical theoretical models for the understanding of these materials, based on the concepts of adsorption stress and osmotic thermodynamic ensemble. We show how these models provide a coherent picture of adsorption-induced deformation and structural transitions in flexible metal–organic frameworks, all the way from the length scale of the unit cell to that of the full crystal. In particular, we highlight the new perspectives opened by these models, as well as some of the important open questions in the field.
Tissue Specific Localization of Pectin–Ca2+ Cross-Linkages and Pectin Methyl-Esterification during Fruit Ripening in Tomato (Solanum lycopersicum)

Fruit ripening is one of the developmental processes accompanying seed development. The tomato is a well-known model for studying fruit ripening and development, and the disassembly of primary cell walls and the middle lamella, such as through pectin de-methylesterified by pectin methylesterase (PE) and depolymerization by polygalacturonase (PG), is generally accepted to be one of the major changes that occur during ripening. Although many reports of the changes in pectin during tomato fruit ripening are focused on the relation to softening of the pericarp or the Blossom-end rot by calcium (Ca2+) deficiency disorder, the changes in pectin structure and localization in each tissues during tomato fruit ripening is not well known. In this study, to elucidate the tissue-specific role of pectin during fruit development and ripening, we examined gene expression, the enzymatic activities involved in pectin synthesis and depolymerisation in fruit using biochemical and immunohistochemical analyses, and uronic acids and calcium (Ca)-bound pectin were determined by secondary ion-microprobe mass spectrometry. These results show that changes in pectin properties during fruit development and ripening have tissue-specific patterns. In particular, differential control of pectin methyl-esterification occurs in each tissue. Variations in the cell walls of the pericarp are quite different from that of locular tissues. The Ca-binding pectin and hairy pectin in skin cell layers are important for intercellular and tissue–tissue adhesion. Maintenance of the globular form and softening of tomato fruit may be regulated by the arrangement of pectin structures in each tissue.
Long‐term effects of aquifer overdraft and recovery on groundwater quality in a Ramsar wetland: Las Tablas de Daimiel National Park, Spain

Las Tablas de Daimiel National Park is one of Spain's most representative groundwater‐dependent ecosystems. Under natural conditions, water inflows combined brackish surface water from River Gigüela with freshwater inputs from River Guadiana and the underlying aquifer. Since the mid‐1970s, aquifer overexploitation caused the desiccation of the wetlands and neighbouring springs. The National Park remained in precarious hydrological conditions for three decades, with the only exception of rapid floods due to extreme rainfall events and sporadic water transfers from other basins. In the late 2000s, a decrease in groundwater abstraction and an extraordinarily wet period reversed the trend. The aquifer experienced an unexpected recovery of groundwater levels (over 20 m in some areas), thus restoring groundwater discharge to springs and wetlands. The complex historical evolution of the water balance in this site has resulted in substantial changes in surface and groundwater quality. This becomes evident when comparing the pre‐1980 groundwater quality and the hydrochemical status in the wetland in two different periods, under “dry” and “wet” conditions. Although the system is close to full recovery from the groundwater‐level viewpoint, bouncing back in the major hydrochemical constituents has not yet been obtained. These still appear to evolve in response to the previous overexploitation state. Moreover, in some sectors, there are groundwater‐dependent ecosystems that remain different to those found in preoverexploitation times. The experience of Las Tablas de Damiel provides an observatory of long‐term changes in wetland water quality, demonstrating that the effects of aquifer overexploitation on aquatic ecosystems are more than a mere alteration of the water balance and that groundwater quality is the key to aquifer and aquatic ecosystem sustainability.
Sexual selection on song and cuticular hydrocarbons in two distinct populations of Drosophila montana

Sexual selection has the potential to contribute to population divergence and speciation. Most studies of sexual selection in Drosophila have concentrated on a single signaling modality, usually either courtship song or cuticular hydrocarbons (CHCs), which can act as contact pheromones. We have examined the relationship between both signal types and reproductive success using F1–3 offspring of wild-collected flies, raised in the lab. We used two populations of the Holarctic species Drosophila montana that represent different phylogeographic clades that have been separate for ca. 0.5 million years (MY), and differ to some extent in both traits. Here, we characterize the nature and identify the targets of sexual selection on song, CHCs, and both traits combined within the populations. Three measures of courtship outcome were used as fitness proxies. They were the probability of mating, mating latency, and the production of rejection song by females, and showed patterns of association with different traits that included both linear and quadratic selection. Courtship song predicted courtship outcome better than CHCs and the signal modalities acted in an additive rather than synergistic manner. Selection was generally consistent in direction and strength between the two populations and favored males that sang more vigorously. Sexual selection differed in the extent, strength, and nature on some of the traits between populations. However, the differences in the directionality of selection detected were not a good predictor of population differences. In addition, a character previously shown to be important for species recognition, interpulse interval, was found to be under sexual selection. Our results highlight the complexity of understanding the relationship between within-population sexual selection and population differences. Sexual selection alone cannot predict differences between populations.
Azimuthal anisotropy beneath north central Africa from shear wave splitting analyses

This study represents the first multistation investigation of azimuthal anisotropy beneath the interior of north central Africa, including Libya and adjacent regions, using shear wave splitting (SWS) analysis. Data used in the study include recently available broadband seismic data obtained from 15 stations managed by the Libyan Center for Remote Sensing and Space Science, and those from five other stations at which data are publicly accessible. A total of 583 pairs of high‐quality SWS measurements utilizing the PKS, SKKS, and SKS phases demonstrate primarily N‐S fast orientations with an average splitting delay time of approximately 1.2 s. An absence of periodic azimuthal variation of the observed splitting parameters indicates the presence of simple anisotropy, and lack of correlation between surficial features and the splitting parameters suggests that the origin of the observed anisotropy is primarily asthenospheric. This conclusion is enhanced by nonperiodic azimuthal variation of the splitting parameters observed at one of the stations located near the boundary of areas with different anisotropic properties. We interpret the observed anisotropy to be the consequence of northward movement of the African plate relative to the asthenosphere toward the Hellenic and Calabrian subduction zones. Local variance in fast orientations may be attributable to flow deflection by the northern edge of the African continental root. The observations provide critical and previously lacking constraints on mantle dynamic models in the vicinity of the convergent boundary between the African and Eurasian plates.
Gender Identification from Facial Image using Compound Local Binary Pattern (CLBP

identification of male and female from facial image allows many useful applications in biometrics, surveillance, and human-computer interaction. This paper presents a robust face feature descriptor for gender classification from facial image. The proposed method is based on the compound local binary pattern (CLBP), an extension of the LBP texture operator. The CLBP operator exploits 2P bits to encode the information of a local neighborhood of P neighbors, where P bits are used to express the sign information and the other P bits are used to express the magnitude information of the differences between the center and the neighbor gray values. The performance of the proposed method has been evaluated using a large dataset comprising 1800 facial images collected from the FERET database. Extensive experiments with support vector machine classifier show the superiority of the CLBP feature descriptor against some well-known texture operators.
Properties of the parametric Lyapunov equation based low gain design with applications in stabilization of time-delay systems

This paper studies some properties of the recently developed parametric Lyapunov equation based low gain feedback design method. As applications of these new properties, alternative and simpler solutions are proposed to the (global) stabilization problem for a class of linear systems with input delay and the semi-global stabilization problem when the systems are in addition subject to actuator saturation. Besides the simplicity in their construction, the new solutions can also be easily scheduled online to achieve global result in the presence of input saturation.
A New Silicon Retina Model and Its Advantages

A new model of silicon retina based on the receptive field structure of retinal ganglion cells has been proposed. Unlike previous neuromorphic models, the proposed model directly incorporates into the receptive field model, contribution from both the inner and outer plexiform layer of the retina, as a linear combination of the two. It has been shown that such a system is capable of aiding in the computation of zero-crossing maps, in higher regions of the brain, using a fourth or higher order derivative. This model is likely to have a neuromorphic implication in generating and implementing a simplistic derivative analyzer mimetic of the Human Visual system (HVS) and is also endowed with additional advantages from the perspective of image retrieval
New IM torque control with implicit rotor field tracking and efficiency maximization

The paper proposes an IM torque control based on the stator current vector reference frame. The introduced control concept rejects the paradigm of decoupled control with constant rotor flux vector. Instead of this widespread assumption the proposed control is derived from augmented dynamic equilibrium conditions assuring the existence and uniqueness of inverse mapping between the required torque end stator current vector. The rotor flux trajectories are forced to change only inside the globally stable sector under all operating conditions by manipulating simultaneously the magnitude and the rotation speed of the stator current vector in an appropriate way. Additional features include the maximal torque per ampere steady state ratio, almost perfect command tracking at non-zero rotor flux and insensitivity to the bounded perturbation of the rotor time constant mark introduced control. Implementation of this control requires estimation of the machine torque and cascaded current controllers. Experimental results confirm the key expectations and show the potential and benefits of the proposed control.
Journal of Network and Computer Applications

Fog computing is an evolving paradigm that addresses the latency-oriented performance and spatio-temporal issues of the cloud services by providing an extension to the cloud computing and storage services in the vicinity of the service requester. In dynamic networks, where both the mobile fog nodes and the end users exhibit time-varying characteristics, including dynamic network topology changes, there is a need of mobility-aware fog computing, which is very challenging due to various dynamisms, and yet systematically uncovered. This paper presents a comprehensive survey on the fog computing compliant with the OpenFog (IEEE 1934) standardised concept, where the mobility of fog nodes constitutes an integral part. A review of the state-of-the-art research in fog computing implemented with mobile nodes is conducted. The review includes the identification of several models of fog computing concept established on the principles of opportunistic networking, social communities, temporal networks, and vehicular ad-hoc networks. Relevant to these models, the contributing research studies are critically examined to provide an insight into the open issues and future research directions in mobile fog computing research.
The Neural Basis of Centre-Surround Interactions in Visual Motion Processing

Perception of a moving visual stimulus can be suppressed or enhanced by surrounding context in adjacent parts of the visual field. We studied the neural processes underlying such contextual modulation with fMRI. We selected motion selective regions of interest (ROI) in the occipital and parietal lobes with sufficiently well defined topography to preclude direct activation by the surround. BOLD signal in the ROIs was suppressed when surround motion direction matched central stimulus direction, and increased when it was opposite. With the exception of hMT+/V5, inserting a gap between the stimulus and the surround abolished surround modulation. This dissociation between hMT+/V5 and other motion selective regions prompted us to ask whether motion perception is closely linked to processing in hMT+/V5, or reflects the net activity across all motion selective cortex. The motion aftereffect (MAE) provided a measure of motion perception, and the same stimulus configurations that were used in the fMRI experiments served as adapters. Using a linear model, we found that the MAE was predicted more accurately by the BOLD signal in hMT+/V5 than it was by the BOLD signal in other motion selective regions. However, a substantial improvement in prediction accuracy could be achieved by using the net activity across all motion selective cortex as a predictor, suggesting the overall conclusion that visual motion perception depends upon the integration of activity across different areas of visual cortex.
Exploiting Tag Relations to Improve Search in Collaborative Tagging Systems

The main problem of tag-based search in collaborative tagging system (CTS) is the lack of explicit semantic relations between tags. To address this problem, we propose an approach based on the integration of symmetrical and asymmetrical similarity measures to calibrate the relatedness between tags and then further organize them into an ontological structure. We also demonstrate how this extracted knowledge will help to apply semantic web techniques to existing web2.0 applications such as CTS and improve their search and browse capabilities.
Genetic evidence implicates the immune system and cholesterol Genetic evidence implicates the immune system and cholesterol metabolism in the aetiology of Alzheimer's disease metabolism in the aetiology of Alzheimer's disease

Background: Late Onset Alzheimer’s disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes. Methodology: We applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset. PrincipalFindings: We found a significant overrepresentation of association signals in pathways related to cholesterol metabolism and the immune response in both of the two largest genome-wide association studies for LOAD. Significance: Processes related to cholesterol metabolism and the innate immune response have previously been implicated by pathological and epidemiological studies of Alzheimer’s disease, but it has been unclear whether those findings reflected primary aetiological events or consequences of the disease process. Our independent evidence from two large studies now demonstrates that these processes are aetiologically relevant, and suggests that they may be suitable targets for novel and existing therapeutic approaches.
Scheduling - A Secret Sauce For Resource Disaggregation

This technical report describes the design & implementation of a constraint-based framework for scheduling & resource allocation in a disaggregated data center (DDC) where we build logical servers from disaggregated resources. We show that an Service Level Objective (SLO)-aware constraint-based solver could improve a data center’s resource utilization by finding better solutions based on provided workload characteristics.
A review of congestion control algorithm for event-driven safety messages in vehicular networks

Congestion control algorithm in Vehicular Networks (VANETs) has been extensively studied. However, most of congestion control algorithms are not directly applicable to uni-priority of event-driven safety messages. The event-driven safety messages have stringent requirement on delay and reliability. The uni-priority of event-driven safety messages are caused by the traffic of the same priority, typically the warning messages of safety applications from different transmitters. The uni-priority messages should be schedule before the node starts the transmitting process. In dense network, a large number of vehicles broadcast a beacon messages at a high number of frequency. Then the Control Channel (CCH) easily congested. It’s very important to keep the CCH channel free from congestion to ensure timely and reliable delivery of event-driven safety messages [9, 20]. Hence, this study takes a closer look at existing congestion control algorithms to solve congestion problems because it affects the performance of safety messages. The study further exposes the weaknesses and advantages of some of these congestion control algorithms which can assist researchers to tackle the inherent problems of congestions in VANETs. This paper also concludes with a planned future research for disseminating uni-priority of event-driven safety messages while solving congestion problems.
Serving Deep Learning Models from Relational Databases

Serving deep learning (DL) models on relational data has become a critical requirement across diverse commercial and scientific domains, sparking growing interest recently. In this visionary paper, we embark on a comprehensive exploration of representative architectures to address the requirement. We highlight three pivotal paradigms: The state-of-the-art DL-centric architecture offloads DL computations to dedicated DL frameworks. The potential UDF-centric architecture encapsulates one or more tensor computations into User Defined Functions (UDFs) within the relational database management system (RDBMS). The potential relation-centric architecture aims to represent a large-scale tensor computation through relational operators. While each of these architectures demonstrates promise in specific use scenarios, we identify urgent requirements for seamless integration of these architectures and the middle ground in-between these architectures. We delve into the gaps that impede the integration and explore innovative strategies to close them. We present a pathway to establish a novel RDBMS for enabling a broad class of data-intensive DL inference applications.