Miracle-dz/UniFAR-FTUs huggingface dataset:
Road and Railway Smart Mobility: A High-Definition Ground Truth Hybrid Dataset

A robust visual understanding of complex urban environments using passive optical sensors is an onerous and essential task for autonomous navigation. The problem is heavily characterized by the quality of the available dataset and the number of instances it includes. Regardless of the benchmark results of perception algorithms, a model would only be reliable and capable of enhanced decision making if the dataset covers the exact domain of the end-use case. For this purpose, in order to improve the level of instances in datasets used for the training and validation of Autonomous Vehicles (AV), Advanced Driver Assistance Systems (ADAS), and autonomous driving, and to reduce the void due to the no-existence of any datasets in the context of railway smart mobility, we introduce our multimodal hybrid dataset called ESRORAD. ESRORAD is comprised of 34 videos, 2.7 k virtual images, and 100 k real images for both road and railway scenes collected in two Normandy towns, Rouen and Le Havre. All the images are annotated with 3D bounding boxes showing at least three different classes of persons, cars, and bicycles. Crucially, our dataset is the first of its kind with uncompromised efforts on being the best in terms of large volume, abundance in annotation, and diversity in scenes. Our escorting study provides an in-depth analysis of the dataset’s characteristics as well as a performance evaluation with various state-of-the-art models trained under other popular datasets, namely, KITTI and NUScenes. Some examples of image annotations and the prediction results of our 3D object detection lightweight algorithms are available in ESRORAD dataset. Finally, the dataset is available online. This repository consists of 52 datasets with their respective annotations performed.
Research and design of underwater flow-induced vibration energy harvester based on Karman vortex street

With the increasing development of wireless sensor network (WSN), power supply for WSN nodes had attracted increasing attention, and the energy harvesting system based on Karman vortex street has been widely used in underwater WSN. But the research of the influences of affecting factors towards the energy harvesting system is yet to be completed. So, in this paper, an underwater flow-induced vibration energy harvesting system based on Karman vortex street was proposed and tested. The influence of bluff body geometry and flow velocity towards the performance of the energy harvesting has been researched. The results showed that the output voltage increased as the diameter of bluff body and the water velocity increase. The power generation efficiency was the best when the shape of bluff body was circular.
Tegafur–Uracil/Leucovorin Plus Oxaliplatin (TEGAFOX) as Consolidation Regimen after Short-Course Radiotherapy Is Effective for Locally Advanced Rectal Cancer

This study aimed to explore the safety and efficacy of neoadjuvant SCRT and tegafur–uracil/leucovorin plus oxaliplatin (TEGAFOX) for LARC in comparison to those of the modified 5-fluorouracil, leucovorin, and oxaliplatin (mFOLFOX-6) regimen. We retrospectively evaluated 15 and 22 patients with LARC who underwent SCRT, followed by consolidation chemotherapy with TEGAFOX and mFOLFOX-6 before surgery, respectively, between January 2015 and December 2019. The primary endpoint was the tumor response rate. The secondary endpoints were compliance, toxicity, complications, overall survival (OS), and disease-free survival (DFS). The dose reduction rate was lower in the TEGAFOX group (0 vs. 9.1% (n = 2)). No grade III-IV toxicities occurred in the TEGAFOX group. Two and four patients in the TEGAFOX and mFOLFOX-6 groups, respectively, achieved clinical complete responses. The pathologic complete response rate was lower in the TEGAFOX group (7.7% vs. 17.6%). Overall, 11 (73.3%) and 17 (81.0%) patients had a neoadjuvant rectal (NAR) score of <16 in the TEGAFOX and mFOLFOX-6 groups, respectively. All patients in this study received sphincter-preservation surgery. One patient in each group developed Clavien–Dindo grade III complications. There were no significant between-group differences in the 3-year OS (81.8% vs. 84.8%, p = 0.884) and 3-year DFS (72% vs. 71.6%, p = 0.824) rates. TEGAFOX, as consolidation chemotherapy after SCRT, achieves good tumor downstaging and patient compliance in LARC. The toxicity, complications, and surgical outcomes are similar to those of mFOLFOX-6. Thus, TEGAFOX can be considered a chemotherapy option for rectal cancer treatment.
The Use of Brewer’s Spent Grain after Beer Production for Energy Purposes

The aim of this study was to assess the possibilities to use brewer’s spent grains (BSGs) left over from beer production for energy purposes, and to determine its calorific value and chemical composition. The research materials were samples of wet spent grain from a brewery in Poland. Three samples, that are different in ingredient composition, were examined. The examined samples of BSGs were characterised by humidity that is typical for this product (approx. 77–80%). Convective drying of the spent grain contributed to a reduction in the water content in the biomass to below 10%. Samples of dry spent grain that were examined contained a similar amount of ash (3.8–4.1% d.m.) and organic matter (91.0–91.9% d.m.). All the examined spent grain samples demonstrated similar volatile matter content—approx. 77.8–78.7% d.m. and calorific value—approx. 15.6–15.9 MJ/kg. The estimated calorific value for wet samples (approx. 1.4–2.0 MJ/kg) indicated that it is necessary to lower water content in the biomass in order to improve its energy properties.
Sentiment Analysis of Users’ Reactions on Social Media During the Pandemic

During the outbreak of the COVID-19 pandemic, social networks became the preeminent medium for communication, social discussion, and entertainment. Social network users are regularly expressing their opinions about the impacts of the coronavirus pandemic. Therefore, social networks serve as a reliable source for studying the topics, emotions, and attitudes of users that have been discussed during the pandemic. In this paper, we investigate the reactions and attitudes of people towards topics raised on social media platforms. We collected data of two large-scale COVID-19 datasets from Twitter and Instagram for six and three months, respectively. This paper analyzes the reaction of social network users in terms of different aspects including sentiment analysis, topic detection, emotions, and the geo-temporal characteristics of our dataset. We show that the dominant sentiment reactions on social media are neutral, while the most discussed topics by social network users are about health issues. This paper examines the countries that attracted a higher number of posts and reactions from people, as well as the distribution of health-related topics discussed in the most mentioned countries. We shed light on the temporal shift of topics over countries. Our results show that posts from the top-mentioned countries influence and attract more reactions worldwide than posts from other parts of the world.
Autonomous Vehicle Dynamic Model-Based Navigation for Small UAVs

This paper presents a novel approach to autonomous navigation for small UAVs, with no extra sensor added to the conventional INS/GNSS setup. The proposed method significantly increases the accuracy and reliability of autonomous navigation, especially for small UAVs with low-cost IMUs. This improvement is of special interest in the case of GNSS outages, where inertial coasting drifts very quickly. In the proposed architecture, the VDM provides the estimate of position, velocity, and attitude, which is updated within a filter based on available observations, such as IMU data or when available, GNSS measurements. The filter is capable of estimating wind velocity and dynamic model parameters, in addition to navigation states and IMU sensor errors. Monte Carlo simulations reveal major improvements in navigation accuracy compared to conventional INS/GNSS systems during GNSS outages of 5 min. A discussion on the observability is also presented at the end. Copyright (C) 2016 Institute of Navigation.
Passive vibration control by using Nonlinear Energy Sink absorbers. Theoretical study and experimental investigations

Passive vibration control methods using linear dampers have been largely studied and investigated, and they have nowadays a broad range of applications. However, linear dampers are efficient when tuned to the specific frequency to control but present substantial limitations when applied to primary systems with uncertainties on the modal parameters or to systems having a natural frequency that may vary with external forcing. In this thesis the vibration mitigation in mechanical systems by means of a Nonlinear Energy Sink absorber is studied. The phenomenon governing the physics of this kind of device is referred to as Targeted Energy Transfer and it consists in an irreversible energy transfer from the primary system to the NES where the energy is then dissipated. This energy transfer may occur over a broad range of frequencies with no need for the NES to be tuned to a specific one. The dynamics of a first type of NES called Vibro-Impact Nonlinear Energy Sink (VI-NES) is experimentally investigated via a harmonically forced single-degree-of-freedom linear oscillator to which a VI-NES is attached. A Targeted Energy Transfer from the LO towards the VI-NES is experimentally observed and a significant reduction of the primary system's resonance peak is obtained. The system is analytically studied by means of the Multiple Scales method and the nonlinear behavior experimentally observed is theoretically explained. The second type of NES presented is the Magnetic-Strung NES with energy harvesting. This study adds the energy harvesting aspect to the research on nonlinear vibration absorbers. The system consists in a harmonically forced single-degree-of-freedom linear oscillator to which the MS-NES is applied. The type of nonlinearity used can be shaped thanks to a magnetic force aptly introduced, allowing the NES to have several possible configurations. The resulting system is an electro-mechanical system in which the vibration energy of the primary system is absorbed by the NES and subsequently partially dissipated by the viscous damping and partially converted into electrical power. The numerical and experimental studies analyze the performances of the MS-NES both as an energy absorber and as an energy harvester. Finally, ideas and perspectives arising from this study are discussed and future work directions are provided.
Colonic Fluid and Electrolyte Transport 2022: An Update

Colonic epithelial cells are responsible for maintaining a delicate balance between luminal secretion and the absorption of fluids and ions. This review aims to discuss and update the model of colonic electrolyte secretion and absorption via the cystic fibrosis transmembrane regulator (CFTR), epithelial sodium channel (ENaC), Na-K-Cl cotransporters (NKCC1 and 2), Na-H exchangers (NHE1–4), colonic H,KATPase, and several other key components involved in multi-level transepithelial ion transport. Developments in our understanding of the activity, regulation, localization, and relationships of these ion transporters and their interactions have helped forge a more robust understanding of colonic ion movement that accounts for the colonic epithelium’s role in mucosal pH modulation, the setting of osmotic gradients pivotal for fluid retention and secretion, and cell death regulation. Deviations from homeostatic ion transport cause diarrhea, constipation, and epithelial cell death and contribute to cystic fibrosis, irritable bowel syndrome (IBS), ulcerative colitis, and cancer pathologies. Signal transduction pathways that regulate electrolyte movement and the regulatory relationships between various sensors and transporters (CFTR as a target of CaSR regulation and as a regulator of ENaC and DRA, for example) are imperative aspects of a dynamic and comprehensive model of colonic ion homeostasis.
Prediction of Medical Conditions Using Machine Learning Approaches: Alzheimer’s Case Study

Alzheimer’s Disease (AD) is a highly prevalent condition and most of the people suffering from it receive the diagnosis late in the process. The diagnosis is currently established following an evaluation of the protein biomarkers in cerebrospinal fluid (CSF), brain imaging, cognitive tests, and the medical history of the individuals. While diagnostic tools based on CSF collections are invasive, the tools used for acquiring brain scans are expensive. Taking these into account, an early predictive system, based on Artificial Intelligence (AI) approaches, targeting the diagnosis of this condition, as well as the identification of lead biomarkers becomes an important research direction. In this survey, we review the state-of-the-art research on machine learning (ML) techniques used for the detection of AD and Mild Cognitive Impairment (MCI). We attempt to identify the most accurate and efficient diagnostic approaches, which employ ML techniques and therefore, the ones most suitable to be used in practice. Research is still ongoing to determine the best biomarkers for the task of AD classification. At the beginning of this survey, after an introductory part, we enumerate several available resources, which can be used to build ML models targeting the diagnosis and classification of AD, as well as their main characteristics. After that, we discuss the candidate markers which were used to build AI models with the best results in terms of diagnostic accuracy, as well as their limitations.
Software-defined mobility management and base station control for green cellular networks

Mobile communication systems have revolutionized in order to fulfill exponentially increasing data traffic volume due to the introductio n of new devices such as smartphones and tablets and success of social networking service s. Evolving cellular networks include emerging technologies such as Software-Defined Net work (SDN) and Network Function Virtualization (NFV). SDN is an emerging network a chitecture that allows dynamic and flexible network operations with centralized cont r ller. NFV addresses the problem of a large and increasing number of hardware applian ces and focuses on optimizing the network services themselves. With SDN and NFV, ce llular networks are able to provide more flexible and agile management that can better align and support the mobile users. In this dissertation, we address location management and ha ndover to reduce data traffic toward the core network and to reduce energy consumpt ion. Location management iii is a key control task in cellular network operations. We prop ose and develop an efficient group location management scheme as a virtualized network f unction for group cellular applications. The performance improvement is mainly achie ved by the virtualized and separate group management architecture and an efficient dyn amic group profiling algorithm. We conduct theoretical analyses of our scheme for sig naling costs and performance gains under diverse traffic conditions. Furthermore, we car ry out extensive evaluations using both real traces and synthetic human mobility data, and w e validate the efficiency of the proposed scheme in both location updates and paging. Moreover, in order to tackle the issues of mounting deployme nts and large energy consumption of base stations, it is integral to devise schem es to improve energy efficiency in cellular networks. We propose a virtualized network func tion of cell management on an SDN architecture. We develop a cell management algorithm on the architecture that can effectively control the sleep and awake modes of base statio ns and perform handover operations in a cellular network. It provides significant be nefits over current cellular networks that suffer from inflexible management and complex control. Our extensive trace-driven evaluation results show that the proposed con trol architecture and the cell management algorithm achieve significant energy savings, a d incur less control message exchanges, more cells in a sleep mode for longer durations, a nd less cell status changes than existing energy saving approaches for cellular networ ks.
Molecular tracking and prevalence of the red colour morph restricted to a harvested leopard population in South Africa

The red leopard (Panthera pardus) colour morph is a colour variant that occurs only in South Africa, where it is confined to the Central Bushveld bioregion. Red leopards have been spreading over the past 40 years, which raises the speculation that the prevalence of this phenotype is related to low dispersal of young individuals owing to high off‐take in the region. Intensive selective hunting tends to remove large resident male leopards from the breeding population, which gives young male leopards the chance to mate with resident female leopards that are more likely to be their relatives, eventually increasing the frequency of rare genetic variants. To investigate the genetic mechanisms underlying the red coat colour morph in leopards, and whether its prevalence in South Africa relates to an increase in genetic relatedness in the population, we sequenced exons of six coat colour‐associated genes and 20 microsatellite loci in twenty Wild‐type and four red leopards. The results were combined with demographic data available from our study sites. We found that red leopards own a haplotype in homozygosity identified by two SNPs and a 1 bp deletion that causes a frameshift in the tyrosinase‐related protein 1 (TYRP1), a gene known to be involved in the biosynthesis of melanin. Microsatellite analyses indicate clear signs of a population bottleneck and a relatedness of 0.11 among all pairwise relationships, eventually supporting our hypothesis that a rare colour morph in the wild has increased its local frequency due to low natal dispersal, while subject to high human‐induced mortality rate.
A 10–40 GHz switched step attenuator in 0.13 µm CMOS technology

ABSTRACT A 4-bit switched step attenuator is designed and presented at 10–40 GHz. Body-switching technique is used to improve attenuation range and flatness of the proposed attenuator. The circuit is implemented in a standard 0.13 µm CMOS technology and the simulation results are reported. The design shows approximately constant attenuation range of 13.5 dB across the frequency band. The flatness is less than 1.5 dB in the reference state and less than 1.8 dB in the attenuation state. Moreover, the input and output return losses are better than 12 dB and the minimum IIP3 is greater than 23.5 dBm across the operating frequency.
Biologically inspired approach for robot design and control

BIOLOGICALLY INSPIRED APPROACH FOR ROBOT DESIGN AND CONTROL By Jianguo Zhao Robots will transform our daily lives in the near future by moving from controlled industrial lines to unstructured and uncertain environments such as home, offices, or outdoors with various applications from healthcare, service, to defense. Nevertheless, two fundamental problems remain unsolved for robots to work in such environments. On one hand, how to design robots, especially meso-scale ones with sizes of a few centimeters, with multiple locomotion abilities to travel in the unstructured environment is still a daunting task. On the other hand, how to control such robots to dynamically interact with the uncertain environment for agile and robust locomotion also requires tremendous efforts. This dissertation tries to tackle these two problems in the framework of biologically inspired robotics. On the design aspect, it will be shown how biologically principles found in nature can be used to build efficient meso-scale robots with various locomotion abilities such as jumping, wheeling, and aerial maneuvering. Specifically, a robot (MSU Jumper) with continuous jumping ability will be presented. The robot can achieve the following three performances simultaneously. First, it can perform continuous steerable jumping based on the self-righting and the steering capabilities. Second, the robot only requires a single actuator to perform all the functions. Third, the robot has a light weight (23.5 g) to reduce the damage from landing impacts. Based on the MSU Jumper, a robot (MSU Tailbot) with multiple locomotion abilities is discussed. This robot can not only wheel on the ground but also jump up to overcome obstacles. Once leaping into the air, it can also control its body angle using an active tail to dynamically maneuver in mid-air for safe landings. On the control aspect, a novel non-vector space control method that formulates the problem in the space of sets is presented. This method can be easily applied to vision based control by considering images as sets. The advantage of such a method is that there is no need to extract and track features during the control process, which is required by traditional methods. Based on the non-vector space approach, the compressive feedback is proposed to increase the feedback rate and reduce the computation time. This method is ideal for the control of meso-scale robots with limited sensing and computation ability. The bio-inspired design illustrated by the MSU Jumper and MSU Tailbot in this dissertation can be applied to other robot designs. Meanwhile, the non-vector space control with compressive feedbacks lays the foundation for the control of high dynamic meso-scale robots. Together, the biologically inspired method for the design and control of meso-scale robots will pave the way for next generation bio-inspired, low cost, and agile robots.
Methodical Aspects for Measuring Customers‘ Satisfaction of eServices in Automated CRM Systems

The main purpose of the paper is to identify a method for measuring customers’ satisfaction of eServices in CRM systems. The research is conducted through elaborate overview analysis of enterprises using ERP systems. On the bases of the analysis suggestions for companies relying on CRM systems, a conceptual agenda for agile BI monitoring of service quality and client’s perceptions is proposed.
Nonlinear Phase Based Control to Generate and Assist Oscillatory Motion with Wearable Robotics

Wearable robotics is a growing sector in the robotics industry, they can increase the productivity of workers and soldiers and can restore some of the lost function to people with disabilities. Wearable robots should be comfortable, easy to use, and intuitive. Robust control methods are needed for wearable robots that assist periodic motion. This dissertation studies a phase based oscillator constructed with a second order dynamic system and a forcing function based on the phase angle of the system. This produces a bounded control signal that can alter the damping and stiffens properties of the dynamic system. It is shown analytically and experimentally that it is stable and robust. It can handle perturbations remarkably well. The forcing function uses the states of the system to produces stable oscillations. Also, this work shows the use of the phase based oscillator in wearable robots to assist periodic human motion focusing on assisting the hip motion. One of the main problems to assist periodic motion properly is to determine the frequency of the signal. The phase oscillator eliminates this problem because the signal always has the correct frequency. The input requires the position and velocity of the system. Additionally, the simplicity of the controller allows for simple implementation.
Power and area efficient reconfigurable delta sigma ADCs

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