Miracle-dz/UniFAR-FTUs huggingface dataset:
Motion-constrained Road User Tracking for Real-time Traffic Analysis

Reliability of numerous smart traffic applications are highly dependent on the accuracy of underlying road user tracker. Demand on scalability and privacy preservation pushes vision-based smart traffic applications to sense and process images on edge devices and transmit only concise information to decision/fusion nodes. One of the requirements for deploying a vision algorithm on edge devices is its ability to process captured images in real time. To meet these needs, we propose a real-time road user tracker which outperforms state-of-the-art trackers. Our approach utilizes double thresholding on detector responses to suppress initialization of false positive trajectories while assuring corresponding detector responses required for updating trajectories are not wrongly discarded. Furthermore, our proposed Bayes filter reduces fragmentation and merging of trajectories which highly effect the performance of subsequent smart traffic applications. The performance of our tracker is evaluated on the real life traffic data in turning movement counting (TMC) application and it achieves a high precision of 96% and recall of 95% while state-of-the-art tracker in comparison achieves 92% on precision
Near and Far Interaction for Augmented Reality Tree Visualization Outdoors

: The implementation of augmented reality in nature and in an environmental education context, is not a common case. Furthermore, augmented reality is often used basically for visualization, which puts users in a rather passive state. In this paper we investigate how near and far interaction using a head-mounted-display can be combined with visualization on a tree outdoors and which of the interaction techniques are suitable for a future use in an environmental education application. We examine the interaction with virtual leaves on the ﬂoor combined with a virtual-real interaction with a real tree. Parameters like type of interaction, different real surroundings and time task performance, as well the interplay and connection between them are discussed and investigated. Additionally, process visualization in a nature setting like clouds and rain, and growing of tree roots are included in the augmented reality modules and evaluated in user tests followed by a questionnaire. The results indicate, that for a future educational application both, near and far interaction, can be beneﬁcial.
A Natural Interaction Paradigm to Facilitate Cardiac Anatomy Education using Augmented Reality and a Surgical Metaphor

This paper presents a design approach to creating a learning experience for cardiac anatomy by providing an interactive visualisation environment that uses Head Mounted Display (HMD)-based Augmented Reality (AR). Computed tomography imaging techniques were used to obtain accurate model geometry that was optimised in a 3D modelling software package, followed by photo-realistic texture mapping using 3D painting software. This method simplifies the process of modelling complex, organic geometry. Animation, rendering techniques, and AR capability were added using the Unity game engine. The system’s design and development maximises immersion, supports natural gesture interaction within a real-world learning setting, and represents complex learning content. Hand input was used with a surgical-dissection metaphor to show cross-section rendering in AR in an intuitive manner. Lessons learned from the modelling process are discussed as well as directions for future research.
Covalent polymer functionalization of graphene/graphene oxide and its application as anticorrosion materials

Research on grapheme-polymer composites as the promising ion barrier materials to tackle the corrosion issue is rapidly developing and attracts interests from both academia and industry. In this minireview, we highlight the covalent functionalization of graphene and its derivatives such as graphene oxide (GO) with polymer brushes, and their application in anticorrosion within the last 3 years. There are some recent excellent reviews published on single layer graphene and graphene-based polymer composites for anticorrosion. However, the covalent functionalization of graphene and GO with polymer brushes for application in anticorrosion has not been addressed in those reviews. In this review, we describe first the current state of the art of covalent functionalization of graphene/GO with polymer brushes. We then discuss the application of pristine graphene as anticorrosion material and its drawbacks which can be overcome by graphene-based polymer composites. Afterwards, we discuss in detail the recent progress and development of covalent polymer functionalized graphene/GO as anticorrosion coatings, reported within the last 3 years. Finally, as perspective, we will briefly summarize the work on composites of polymers with other two-dimensional (2D) materials as anticorrosion coatings. Herein, hexagonal boron nitride, the most studied 2D materials after graphene, and Ti3C2T x MXene which is the rising star of 2D transition metal carbide/nitride will be discussed.
Animating and Adjusting 3D Orthodontic Treatment Objectives

: In this paper, we present an interactive system to adjust and animate 3D orthodontic treatment objectives, the main goal is to improve the communication tools used by orthodontists to exchange with their patients. Given a 3D pathological patient model and a treatment objective, we propose to automatically generate intermediate steps using script-like treatment scenarios. The intermediate steps can then be adjusted using intuitive manipulators, and used to produce an animation of the treatment. The resulting animation is a useful tool to help patients visualize the potential evolution of their dentition and accept the treatment. The proposed system relies on the registration of a reference model on both the treatment objective and the patient-speciﬁc 3D segmented mesh, to automatically position key feature points and create control curves. These primitives are used to both, guide teeth movements during the animation, and provide manipulators to allow for user interactions. The key contributions of this work are (a) the use of a registered reference model to position and create intuitive control primitives, and (b) the introduction of script-like treatment scenarios to facilitate and minimize user interactions during the creation of intermediate treatment steps.
Oxidative Stress Enhances the TGF-β2-RhoA-MRTF-A/B Axis in Cells Entering Endothelial-Mesenchymal Transition

Around 45% of deaths in the EU and the US are due to fibrotic diseases. Although myofibroblasts are detected in various fibrotic tissues, they are mostly transdifferentiated from endothelial cells during the endothelial-mesenchymal transition (EndMT) induced by tumor growth factor-beta (TGF-β) family members. Growing evidence indicates that oxidative stress might enhance the sensitivity and the effects of TGF-β stimulation; however, the molecular mechanisms involved in the coordination of oxidative stress and TGF-β inductions remain poorly understood. Our findings indicate for the first time that oxidative stress enhances mesenchymal trans-differentiation of human microvascular endothelial cells (HMEC-1 cells) and that the oxidative stress-dependent TGF-β2-RhoA/Rac1-MRTF-A axis is critical for the induction of later stages of EndMT. This additive effect was manifested in TGF-β1-stimulated and Snail-overexpressed cells, where it caused higher cell elongation and faster migration on collagen I layers. Additionally, Western blot assay indicated the presence of alterations in cell contraction and EndMT markers. We conclude that complex anti-fibrotic therapies based on the inhibition of MRTF activities and oxidative stress might be an attractive target for fibrosis treatment.
Theoretical Performance Analysis of Solar Chimney Power Plant for Kota Region of Rajasthan, India

A solar chimney power plant (SCPP) sometimes also called 'solar updraft tower' is a part of the solar thermal group of indirect solar conversion technologies, utilizing a combination of solar air collector and central updraft tube or chimney to generate a solar induced convective flow which drives pressure staged turbines to generate electricity. In this paper the performance of a solar chimney power plant (SCPP) is evaluated if established in the Kota region of Rajasthan in India. Kota has high intensity of solar radiation with more than 270 sunny days in a year. To investigate the theoretical performance evaluation of the solar chimney power plant in Kota region, total energy generation and average power output for every ten minute interval has been calculated on the basis of solar radiation and temperature data provided by Centre for wind energy Technology (C-WET) available for the period from June 2011-May 2012 for every ten minute interval. Subsequently day wise and month wise calculations have been performed for energy generation and power output for the year June 2011 - May 2012. Further, annual average power output of SCPP is calculated at Kota for different sets of dimensions of SCPP and assuming different values of collector efficiency. Power produced at the plant established in Kota region is compared with power output estimated by J. Schlaich by their experience gained from prototype of SCPP in Manzanares, Spain. Land area required for solar chimney power plant if installed in Kota region of Rajasthan India is calculated for 200 MW capacity plant.
Heterologous Challenge with PRRSV-1 MLV in Pregnant Vaccinated Gilts: Potential Risk on Health and Immunity of Piglets

Simple Summary Modified live virus (MLV) vaccines are considered as the key component to control the Porcine Reproductive and Respiratory Syndrome Virus (PRRSV). The majority of pig farms apply the ‘mass’ vaccination strategy in breeding female animals. However, this PRRS MLV vaccination protocol involves the risk of inoculation of sows in the last stage of gestation, resulting in possible infection of the fetus as the virus can efficiently cross the placenta during the last period of pregnancy. Thus, we evaluated the ability of the vaccine virus to act as a pathogenic strain, to be transmitted to fetuses and to affect the health status of neonatal piglets. The results indicated that the study gilts transmitted the vaccine virus to their offspring, as well as that the PRRSV-infected piglets showed a poor clinical performance. Consequently, the pig farms that apply PRRS MLV vaccination in a routine blanket vaccination strategy must avoid inoculating pregnant gilts the last week before their parturition. Abstract The objective of the present study was to evaluate the potential risks of the four commercial PRRS-1 MLV vaccines in pregnant vaccinated gilts at the last stage of gestation under field conditions. The study was conducted at four pig farms, including 25 gilts from each farm (25 × 4 = 100 gilts), which were equally allocated to five different study groups. A PRRS-1 MLV vaccination was applied on the 100th day of their pregnancy with the different commercial vaccines that are available in the Greek market. The results indicated virus congenital infection and viremia in piglets (20/200 = 10% PRRSV infected piglets), and detection of PRRSV-specific antibodies (181/200 = 90.5% piglets found with PRRSV antibodies). The subsequent phylogenetic analyses revealed high percentages of similarity between the PRRSV-1 strain detected in infected litters and the PRRSV-1 vaccine strain to which the study gilts had been previously exposed to. Health status analyses of trial piglets resulted in differences between litters from vaccinated sows and litters from non-vaccinated sows at 110th day of gestation as regards the number of weak-born piglets, mummies, and piglets with splay-leg and/or respiratory symptoms. The current study’s results indicate several potential dangers of the PRRS MLV vaccination in late gestation.
Classification Performance of RanSaC Algorithms with Automatic Threshold Estimation

The RANdom SAmpling Consensus method (RanSaC) is a staple of computer vision systems and offers a simple way of fitting parameterized models to data corrupted by outliers. It builds many models from small sets of randomly selected data points, and then scores them to keep the best. The original scoring function is the number of inliers, points that fit the model up to some tolerance. The threshold that separates inliers from outliers is dataand model-dependent, and estimating the quality of a RanSaC method is difficult as ground truth data is scarce or not quite reliable. To remedy that, we propose a data generation method to create at will ground truths both realistic and perfectly reliable. We then compare the RanSaC methods that simultaneously fit a model and estimate an appropriate threshold. We measure their classification performance on those semisynthetic feature correspondence pairs for homography, fundamental, and essential matrices. Whereas the reviewed methods perform on par with the RanSaC baseline for standard cases, they do better in difficult cases, maintaining over 80 % precision and recall. The performance increase comes at the cost of running time and analytical complexity, and unexpected failures for some algorithms.
Experimental investigation and analysis of thickness distribution in elliptically hydroformed Al6061T4 tube samples under different internal pressures

ABSTRACT In the present paper, the elliptical tube hydroforming samples have been deformed inside an elliptical die cavity with the help of internal pressure of water. Bulging thickness distribution of tube has been studied experimentally and numerically as well. The tube hydroforming process is depending on various hydroforming variables such as internal pressure, friction factor, axial force etc. In this experiment, axial feed is kept under constrained condition and performed under unique friction factor. The main attention of this paper is to measure the thickness at various major and minor axis points on tube sample deformed under different internal pressures. The percentage thinning of different major and minor axis points has been also discussed and plotted against simulated results. Finite element analysis (FEA) was carried out on elliptical samples using Abaqus software. The simulation results showed an agreement with the experimental data with some relative error which has been also plotted. Comparative results of incremental FEA prediction and experimental data have also been plotted with some deviation.
Adjoint Optimization of Wind Farm Layouts for Systems Engineering Analysis

Wind is an important renewable energy resource, but in order for it to be competitive with other energy sources, wind farm layouts must be optimized to reduce the levelized cost of energy (LCOE). This requires an analysis that integrates high-fidelity flow models with physical turbine and cost models. We present a new flow model and turbine optimization tool, WindSE, that optimizes wind turbine locations and axial induction factors as part of the National Renewable Energy Laboratory’s open source wind energy systems engineering software tool WISDEM. WindSE enables gradient-based layout optimization by solving the discrete adjoint equations corresponding to the forward flow model. This provides a computationally efficient way to calculate gradients used in the optimization process. We discuss the development of WindSE and provide optimization results based on simulations of single and multiple inflow directions. In the case of strongly directional wind roses the optimal layouts take advantage of flow curvature and speedup effects that are not generated by standard industry linear flow models. When optimizing with respect to a uniform wind rose, local speedup effects are found to be less beneficial and the optimal layouts instead reduce wake losses by maximizing spacing. Sensitivity to wind direction bin sizes and weights is demonstrated with a full layout and axial induction factor optimization using a wind rose from an offshore wind farm.
Vacuum Packaging Can Extend Fresh Color Characteristics of Beef Steaks during Simulated Display Conditions

Packaging technology is evolving, and the objectives of this study were to evaluate instrumental surface color, expert color evaluation, and lipid oxidation (TBARS) on beef longissimus lumborum steaks packaged in vacuum-ready packaging (VRF) or polyvinyl chloride (PVC) overwrap packaging. Paired strip loins (Institutional Meat Purchasing Specifications # 180) were cut into 2.54-cm-thick steaks and assigned randomly to one of two packaging treatments, VRF or PVC. Steaks packaged in VRF were lighter in color (p < 0.05) as the display period increased, whereas steaks packaged in PVC became darker (p < 0.05). Redness (a*) values were greater (p < 0.05) for PVC steaks until day 5, whereas VRF steaks had a greater (p < 0.05) surface redness from day 10 to 35 of the display period. Calculated spectral values of red to brown were greater (p < 0.05) for steaks in VRF than PVC. In addition, expert color evaluators confirmed VRF steaks were less brown and less discolored (p < 0.05) from day 5 to 35 of the display. Nonetheless, lipid oxidation was greater (p < 0.05) for PVC steaks from day 10 through day 35 of the display. Results from this study suggest that the use of vacuum packaging for beef steaks is plausible for maintaining surface color characteristics during extended display periods.
Incidence and risk factors associated with early death in patients with emergency department septic shock

Background Limited research has explored early mortality among patients presenting with septic shock. The objective of this study was to determine the incidence and factors associated with early death following emergency department (ED) presentation of septic shock. Methods A prospective registry of patients enrolled in an ED septic shock clinical pathway was used to identify patients. Patients were compared across demographic, comorbid, clinical, and treatment variables by death within 72 hours of ED presentation. Results Among the sample of 2,414 patients, overall hospital mortality was 20.6%. Among patients who died in the hospital, mean and median time from ED presentation to death were 4.96 days and 2.28 days, respectively. Death at 24, 48, and 72 hours occurred in 5.5%, 9.5%, and 11.5% of patients, respectively. Multivariate regression analysis demonstrated that the following factors were independently associated with early mortality: age (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.03–1.05), malignancy (OR, 1.53; 95% CI, 1.11–2.11), pneumonia (OR, 1.39; 95% CI, 1.02–1.88), urinary tract infection (OR, 0.63; 95% CI, 0.44–0.89), first shock index (OR, 1.85; 95% CI, 1.27–2.70), early vasopressor use (OR, 2.16; 95% CI, 1.60–2.92), initial international normalized ratio (OR, 1.14; 95% CI, 1.07–1.27), initial albumin (OR, 0.55; 95% CI, 0.44–0.69), and first serum lactate (OR, 1.21; 95% CI, 1.16–1.26). Conclusions Adult septic shock patients experience a high rate of early mortality within 72 hours of ED arrival. Recognizable clinical factors may aid the identification of patients at risk of early death.
Real-Time Forest Fire Detection Framework Based on Artificial Intelligence Using Color Probability Model and Motion Feature Analysis

As part of the early warning system, forest fire detection has a critical role in detecting fire in a forest area to prevent damage to forest ecosystems. In this case, the speed of the detection process is the most critical factor to support a fast response by the authorities. Thus, this article proposes a new framework for fire detection based on combining color-motion-shape features with machine learning technology. The characteristics of the fire are not only red but also from their irregular shape and movement that tends to be constant at specific locations. These characteristics are represented by color probabilities in the segmentation stage, color histograms in the classification stage, and image moments in the verification stage. A frame-based evaluation and an intersection over union (IoU) ratio was applied to evaluate the proposed framework. Frame-based evaluation measures the performance in detecting fires. In contrast, the IoU ratio measures the performance in localizing the fires. The experiment found that the proposed framework produced 89.97% and 10.03% in the true-positive rate and the false-negative rate, respectively, using the VisiFire dataset. Meanwhile, the proposed method can obtain an average of 21.70 FPS in processing time. These results proved that the proposed method is fast in the detection process and can maintain performance accuracy. Thus, the proposed method is suitable and reliable for integrating into the early warning system.
Multi-Objective Optimization-Based Health-Conscious Predictive Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles

The Energy Management Strategy (EMS) in Fuel Cell Hybrid Electric Vehicles (FCHEVs) is the key part to enhance optimal power distribution. Indeed, the most recent works are focusing on optimizing hydrogen consumption, without taking into consideration the degradation of embedded energy sources. In order to overcome this lack of knowledge, this paper describes a new health-conscious EMS algorithm based on Model Predictive Control (MPC), which aims to minimize the battery degradation to extend its lifetime. In this proposed algorithm, the health-conscious EMS is normalized in order to address its multi-objective optimization. Then, weighting factors are assigned in the objective function to minimize the selected criteria. Compared to most EMSs based on optimization techniques, this proposed approach does not require any information about the speed profile, which allows it to be used for real-time control of FCHEV. The achieved simulation results show that the proposed approach reduces the economic cost up to 50% for some speed profile, keeping the battery pack in a safe range and significantly reducing energy sources degradation. The proposed health-conscious EMS has been validated experimentally and its online operation ability clearly highlighted on a PEMFC delivery postal vehicle.
Brain-lung interaction: a vicious cycle in traumatic brain injury

The brain-lung interaction can seriously affect patients with traumatic brain injury, triggering a vicious cycle that worsens patient prognosis. Although the mechanisms of the interaction are not fully elucidated, several hypotheses, notably the “blast injury” theory or “double hit” model, have been proposed and constitute the basis of its development and progression. The brain and lungs strongly interact via complex pathways from the brain to the lungs but also from the lungs to the brain. The main pulmonary disorders that occur after brain injuries are neurogenic pulmonary edema, acute respiratory distress syndrome, and ventilator-associated pneumonia, and the principal brain disorders after lung injuries include brain hypoxia and intracranial hypertension. All of these conditions are key considerations for management therapies after traumatic brain injury and need exceptional case-by-case monitoring to avoid neurological or pulmonary complications. This review aims to describe the history, pathophysiology, risk factors, characteristics, and complications of brain-lung and lung-brain interactions and the impact of different old and recent modalities of treatment in the context of traumatic brain injury.