bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Surface Roughness and Inlet Turbulence Intensity on a Turbine Nozzle Guide Vane External Heat Transfer: Experimental Investigation on a Literature Test Case
Authors: Bacci Tommaso , Picchi Alessio , Lenzi Tommaso , Facchini Bruno , Innocenti Luca
Published: January 2021

Surface roughness is well known to significantly influence turbine aerodynamics and heat transfer; different studies have been undertaken in the last decades, in order to precisely characterize its effects and pursue a reliable and unified computational fluid dynamics modeling approach. Despite the effort, further research is still required to completely fulfill the goal, due to the complexity of the considered environment, with many other aspects and flow characteristics factoring into the final behavior. In this work, an experimental campaign was carried out to evaluate the heat transfer coefficient on a linear nozzle guide vane geometry. The adopted geometry has been developed and tested, at different inlet turbulence intensity, Reynolds and Mach number, at Von Kármán Institute. The results achieved on a test article with smooth surface were made available. In the present work, the effect of increased turbulence level and surface roughness was taken into account, respectively, using passive grids and conditioning the test sample surface finishing. Experiments were conducted using a transient technique by measuring the surface temperature evolution by IR thermography. The collected results integrate the existing database available in the open literature in order to support development and benchmarking of numerical approaches aimed at a reliable characterization of these aspects.
An Intelligent Prediction for Detecting Bearing Vibration Characteristics Using a Machine Learning Model
Authors: Salunkhe Vishal G. , Desavale R. G.
Published: January 2021

Bearing failure in the heavy rotating machines results in shut down of many other machines and affects the overall cost and quality of the product. Condition monitoring of bearing systems acts as a preventive and corrective measure as it avoids breakdown and saves maintenance time and cost. This research paper proposes advanced strategies for early detection and analysis of taper rolling bearings. In view of this, mathematical model-based fault diagnosis and support vector machining (SVM) are proposed in this work. A mathematical model using dimension analysis by the matrix method (Dimension Analysis Method (DAMM)) and SVM is developed that can be used to predict the vibration characteristic of the rotor-bearing system. Types of defects are created using electrical discharge machining (EDM) and analyzed, and correlation is established between dependent and independent parameters. Experiments were performed to evaluate the rotor dynamic characteristic of healthy and unhealthy bearings. Experimental results are used to validate the model obtained by the DAMM and SVM. Experimental results showed that the vibration characteristic could be evaluated by using a theoretical model and SVM. Efforts have been made to extend the service life of the machines and the assembly lines and to improve their efficiency, so as to reduce bearing failure; what provides novelty to these efforts is the use of four machine learning techniques. Thus, an automatic online diagnosis of bearing faults has been made possible with the developed model based on DAMM and SVM.
Passive Multi-Degree-of-Freedom Stabilization of Ultra-High-Speed Maglev Vehicles
Authors: Circosta Salvatore , Galluzzi Renato , Amati Nicola , Tonoli Andrea , Bonfitto Angelo , Lembke Torbjörn A. , Kertész Milan
Published: January 2021

Over the last decades, the search for fast and efficient transportation systems has raised the interest toward maglev technologies. In this scenario, the Hyperloop paradigm is regarded as a breakthrough for future mobility. However, its practical implementation requires the solution of key shortcomings. Among these, the stability of the electrodynamic levitation system remains partially unexplored. The state of the art presents numerous attempts to attain stable behavior. In recent works, the stabilization of maglev vehicles has been addressed only for the vertical dynamics. Nevertheless, stable operation of all degree-of-freedom is required for a successful implementation of these transportation systems. The present paper addresses the full stabilization of a downscaled vehicle where levitation and guidance are provided by electrodynamic means. To this end, a design methodology supported by analytical modeling is proposed, where the degree-of-freedom are stabilized by suitably introducing secondary suspension elements. The design of the secondary suspension and the guidance system is obtained through the optimization of stability and dynamic performance. Then, a multibody model is developed. Both numerical approaches are compared in the frequency domain for validation purposes. Finally, the multibody model is simulated in the time domain to assess system performance in the presence of track irregularities and evaluate coupling effects between the degree-of-freedom.
Adaptive Neural Network Based Predictive Control of Nonlinear Systems With Slow Dynamics
Authors: Spiller Mark , Bakhshande Fateme , Söffker Dirk
Published: January 2021

In this paper a data-driven approach for model-free control of nonlinear systems with slow dynamics is proposed. The system behavior is described using a local model respectively a neural network. The network is updated online based on a Kalman filter. By predicting the system behavior two control approaches are discussed. One is obtained by calculating a control input from the one step ahead prediction equation using least squares, the other is obtained by solving a standard linear model predictive control problem. The approaches are tested on a constrained nonlinear MIMO system with slow dynamics.
Real-Time Applicable Power Management of Multi-Source Fuel Cell Vehicles Using Situation-Based Model Predictive Control
Authors: Ali Ahmed M. , Söffker Dirk
Published: January 2021

Power management in all-electric powertrains has a significant potential to optimally handle the limited energy and power density of electric power sources. Situation-based power management strategies (SB-PMSs), defining optimized solutions related to specific vehicle situations, offer the ability to reduce computational requirements and enhance the solution optimality of simple rule-based algorithms. Moreover, the local optimality of SB-PMSs can be addressed by considering online optimization of the situated solutions for limited horizons. This paper presents a novel PMSs using model predictive control (MPC) to define optimal control strategies based on situated solutions for fuel cell hybrid vehicles. Vehicle states are defined in terms of multiple characteristic variables and power management decisions are optimized offline for each vehicle states. Prediction of vehicle states is conducted using statistical predictive model based on state transitions in a number of driving cycles. Preoptimized solutions related to predicted states are iterated online to achieve better optimality over the look-ahead horizon. Results analysis from online testing revealed the ability of SB-MPC to improve the optimality of situation-based solutions and hence reduce total energy cost in different driving cycles.
A Lateral Motion Planning Method for Automated Vehicles Based on Sinusoids
Authors: Wang Wei , Wang Zejiang , Chen Xinbo , Wang Junmin
Published: January 2021

For automated driving applications, exact motion planning is pivotal to obstacle-avoidance and local driving, particularly in sophisticated surroundings. Treating this problem from a differential geometric viewpoint aids in simplifying the control and planning processes. Different from the classic differential geometric methods that result in piece-wise solutions with both forward and backward moving, this paper explores the application of sinusoids in exact motion planning regarding both the positive/continuous speed requirements and the system non-holonomic constraint. By converting the vehicle kinematic model to a similar chained form, we apply sinusoidal inputs with biases to generate the reference trajectory and discuss the principles of parameter selection for a given lateral displacement. To overcome the extra constraint brought by l’Hospital rule, we introduce a pair of entry/leave transition periods to ensures an adjustable speed profile and design flexibility. The resulting trajectory reflects an strong applicability to lane-changing or evasive steering scenarios. Since the proposed method does not account for the small-time controllability because of the positive/continuous speed constraint, the reachability problem is further investigated. We provide an analytic estimation of the reachable area edge and compare it with the numerical simulation results. Finally, some indoor field-tests verified the feasibility of the proposed method.
Inverse Reinforcement Learning Based Driver Behavior Analysis and Fuel Economy Assessment
Authors: Ozkan Mehmet Fatih , Ma Yao
Published: January 2021

Human drivers have different driver behaviors when operating vehicles. These driving behaviors, including the driver’s preferred speed and rate of acceleration, impose a major impact on vehicle fuel consumption consequently. In this study, we proposed a feature-based driver behavior learning model from demonstrated driving data utilizing the Inverse Reinforcement Learning (IRL) approach to analyze various driver behaviors and their impacts on vehicle fuel consumption. The proposed approach models the individual driving style as cost function which is a linear combination of the features and their corresponding weights. The proposed IRL framework is used to find the model parameters that fit the observed driving style best. By using the learned driving behavior model, the most likely trajectories are computed and the optimized feature weights are used to analyze different driver behaviors. The different driver behaviors and their impacts on vehicle fuel consumption are then analyzed in real-world driving scenarios. Results show that the proposed IRL framework can successfully learn individual driver behaviors using vehicle trajectory data demonstrated by different real drivers. The learned driver behaviors promise a significant correlation between driving behavior and fuel consumption.
Motion Planning for Autonomous Driving With Extended Constrained Iterative LQR
Authors: Shimizu Yutaka , Zhan Wei , Sun Liting , Chen Jianyu , Kato Shinpei , Tomizuka Masayoshi
Published: January 2021

Autonomous driving planning is a challenging problem when the environment is complicated. It is difficult for the planner to find a good trajectory that navigates autonomous cars safely with crowded surrounding vehicles. To solve this complicated problem, a fast algorithm that generates a high-quality, safe trajectory is necessary. Constrained Iterative Linear Quadratic Regulator (CILQR) is appropriate for this problem, and it successfully generates the required trajectory in realtime. However, CILQR has some deficiencies. Firstly, CILQR uses logarithmic barrier functions for hard constraints, which will cause numerical problems when the initial trajectory is infeasible. Secondly, the convergence speed is slowed with a bad initial trajectory, which might violate the real-time requirements. To address these problems, we propose the extended CILQR by adding two new features. The first one is using relaxed logarithmic barrier functions instead of the standard logarithmic barrier function to prevent numerical issues. The other one is adding an efficient initial trajectory creator to generate a good initial trajectory. Moreover, this initial trajectory helps CILQR to converge to a desired local optimum. These new features extend CILQR’s usage to more practical autonomous driving applications. Simulation results show that our algorithm is effective in challenging driving environments.
Suggestion-Based Fuel Efficient Control of Connected and Automated Vehicles
Authors: Vellamattathil Baby Tinu , Karimi Shahri Pouria , Ghasemi Amir H. , HomChaudhuri Baisravan
Published: January 2021

This paper presents a suggestion-based fuel efficient controller for connected and automated vehicles (CAVs) in presence of human-driven vehicles (HDVs). The suggestion-based controller, apart from evaluating the fuel efficient control solution of the host CAV, provides suggested velocity commands to the HDVs so that the fuel efficiency of itself or the group can improve. We assume that in the connected vehicle system, the HDVs are also able to receive information though Vehicle to Vehicle (V2V) communication and they always try to follow the suggested commands. The suggestion-based control provides additional decision variables to the CAVs with which they can influence the actions of the HDVs and hence improve the fuel efficiency of the whole group. The controller is implemented in a model predictive control (MPC) framework where the suggested command velocities are held constant over some prescribed time so that the driver gets enough time to reach the suggested command velocities. For this control method to function, we present a model that captures the response of a HDV to different suggested-commands. The parameters of the model is obtained from a table-top drive simulator. The accuracy of this model is also validated with the experimental data (table-top drive simulator) and the results are presented in this paper. Simulation studies for the control strategies show the efficacy of the proposed control strategy when compared with existing baseline methods.
An Ultrasound Imaging Based Observer for Estimating NMES-Induced Muscle Fatigue: Theory and Simulation
Authors: Sheng Zhiyu , Kim Kang , Sharma Nitin
Published: January 2021

Neuroprosthetic devices that use transcutaneous neuromuscular electrical stimulation (NMES) are potential interventions to restore skeletal muscle function in people with neurological disorders. As commonly noted, how to assess the NMES-induced muscle fatigue is a critical problem. This is because the capability of fatigue assessment is a necessary precursor for optimally modulating the NMES dosage to improve the control performance of a neuroprosthesis and ensure user’s safety. To effectively estimate the NMES-induced muscle fatigue, this paper proposes a novel state observer that combines a mathematical predictive fatigue model and intermittent feedback from ultrasound-derived strain images. The strain images quantify muscle contractility during NMES. Principal component regression (PCR) is used to derive a relationship between the strain images and instantaneous muscle force production. Lyapunov stability analysis was performed to obtain the convergence property of the designed observer. A globally uniformly ultimately bounded (GUUB) result was obtained. Simulations based on pre-recorded data from a human experiment were also conducted to demonstrate the performance of the designed observer.
Inverse Kinematic Analysis of Muscular Hydrostat Inspired Soft Robot With Chain-Like Optimization With an Embedded Controller
Authors: Zamanian Amir Hosein , Richer Edmond
Published: January 2021

In this study, we present a fast computing algorithm for the inverse kinematic analysis of a dexterous robot inspired by muscular hydrostats. First, the forward kinematics based on piecewise constant curvature (PCC) theory was established. Second, an inverse kinematic algorithm based on a chain-like connection comprising rigid link elements with revolute joints is proposed. The inverse kinematic algorithm starts with a solution derived from the Euler-Bernoulli beam equation and then performs an iterative constrained optimization with an embedded integral controller. The algorithm can reach the desired positions and orientations of the end effector with theoretically “zero” error. The simulation results showed that the algorithm can reach all positions and orientations in the continuous workspace with a small number of iterations.
Minimum Safety Distances for Emergency Braking Maneuvers in Car-Following Applications
Authors: Schafer Devin , Chen Pingen
Published: January 2021

Platooning/car following has been considered as a promising approach for improving vehicle efficiency due to the reduction of aerodynamic force when closely following a pilot vehicle. However, safety is a major concern in the close car platooning/following. This paper investigates the minimum inter-vehicle distances required for a passenger vehicle to safely travel behind a heavy-duty truck with three different types of emergency maneuvers. The three emergency maneuvers considered are braking only, steering only, and braking then steering, where steering refers to a single lane change maneuver. Numerical analysis is conducted for deriving the clearance space in the braking only scenario. In addition, simulations are conducted in MATLAB/Simulink, using a bicycle model for the vehicle dynamics, to examine the minimum safe following distance for the other two scenarios. The simulation results show that, for initial vehicle speeds greater than 8 m/s, a lane change maneuver requires the shortest safety distance. Braking followed by lane changing usually requires the largest minimum safety distance.
Optimal Realization of Endpoint Stiffness in Static Human Arm Postures
Authors: Iqbal Kamran
Published: January 2021

The endpoint stiffness, i.e., stiffness displayed by the wrist amid perturbations to the arm, has been used to assess the mechanical stability of the arm posture. The aim of this study is to develop an algorithm to optimally realize a desired end-point stiffness by minimizing muscle forces. The neuro-muscular behavior of the human arm during posture maintenance tasks is approximated by a two-link eight-muscle arm model. The model parameters reflect physiological data taken from published literature. The endpoint stiffness is shown to be a linear function of muscle activations. It is shown that the problem to minimize muscle activations while satisfying torque constraint at the joints can be solved by using non-negative least-squares method. Alternatively, linear programming can be used for this purpose. The biomechanical model is used to demonstrate how endpoint stiffness of desired magnitude, orientation, and eccentricity can be synthesized by activating arm muscles with minimal energy expenditure. Our simulation results suggest that bi-articular muscles play a major role in developing the desired endpoint stiffness. The model can be scaled up to three-dimensions by adding muscle groups.
Cooperation and Null-Space Control of Networked Omni-Directional Mobile Manipulators
Authors: Chua Michael John , Liu Yen-Chen
Published: January 2021

This paper presents cooperation and null-space control for networked mobile manipulators with high degrees of freedom (DOFs). First, kinematic model and Euler-Lagrange dynamic model of the mobile manipulator, which has an articulated robot arm mounted on a mobile base with omni-directional wheels, have been presented. Then, the dynamic decoupling has been considered so that the task-space and the null-space can be controlled separately to accomplish different missions. The motion of the end-effector is controlled in the task-space, and the force control is implemented to make sure the cooperation of the mobile manipulators, as well as the transportation tasks. Also, the null-space control for the manipulator has been combined into the decoupling control. For the mobile base, it is controlled in the null-space to track the velocity of the end-effector, avoid other agents, avoid the obstacles, and move in a defined range based on the length of the manipulator without affecting the main task. Numerical simulations have been addressed to demonstrate the proposed methods.
Adaptive Impedance Control for the Haptic Shared Driving Task Based on Nonlinear MPC
Authors: Izadi Vahid , Ghasemi Amir H.
Published: January 2021

This paper presents an adaptive haptic shared control framework wherein a driver and an automation system are physically connected through a motorized steering wheel. The automation system is modeled as an intelligent agent that is not only capable of making decisions but also monitoring the human’s behavior and adjusting its behavior accordingly. To enable the automation system to smoothly exchange the control authority with the human partner, this paper introduces a novel self-regulating impedance controller for the automation system. To determine an optimal modulation policy, a cost function is defined. The terms of the cost function are assigned to minimize the performance error and reduce the disagreement between the human and automation system. To solve the optimal control problem, we employed a nonlinear model predictive approach and used the continuation generalized minimum residual method to solve the nonlinear cost function. To demonstrate the effectiveness of the proposed approach, simulation studies consider a scenario where the human and the automation system both detect an obstacle and negotiate on controlling the steering wheel so that the obstacle can be avoided safely. The simulations involve four interaction modes addressing the cooperation status (cooperative and uncooperative) and the desired direction of the control transfer (active safety and autopilot). The results of the numerical studies show that when the automation system acts as autopilot, using the proposed modulation method, the automation adopts smaller impedance controller gains, which results in a smaller disagreement between the human and automation systems. On the other hand, when the human’s control command is insufficient, by modulating and adopting larger values for the impedance controller parameters, the automation system gains the control authority and ensures the safety of the obstacle avoidance task.
A new model for the optimal structural context for giant porphyry copper deposit formation
Authors: Piquer José , Sanchez-Alfaro Pablo , Pérez-Flores Pamela
Published: January 2021

Porphyry-type deposits are the main global source of copper and molybdenum. An improved understanding of the most favorable structural settings for the emplacement of these deposits is necessary for successful exploration, particularly considering that most future discoveries will be made under cover based on conceptual target generation. A common view is that porphyry deposits are preferentially emplaced in pull-apart basins within strike-slip fault systems that favor local extension within a regional compressive to transpressive tectonic regime. However, the role of such a structural context in magma storage and evolution in the upper crust remains unclear. In this work, we propose a new model based on the integration of structural data and the geometry of magmatic-hydrothermal systems from the main Andean porphyry Cu-Mo metallogenic belts and from the active volcanic arc of southern Chile. We suggest that the magma differentiation and volatile accumulation required for the formation of a porphyry deposit is best achieved when the fault system controlling magma ascent is strongly misoriented for reactivation with respect to the prevailing stress field. When magmas and fluids are channeled by faults favorably oriented for extension (approximately normal to σ3), they form sets of parallel, subvertical dikes and veins, which are common both during the late stages of the evolution of porphyry systems and in the epithermal environment. This new model has direct implications for conceptual mineral exploration.
Transport and accumulation of plastic litter in submarine canyons—The role of gravity flows
Authors: Zhong Guangfa , Peng Xiaotong
Published: January 2021

Manned submersible dives discovered plastic litter accumulations in a submarine canyon located in the northwestern South China Sea, ∼150 km from the nearest coast. These plastic-dominated litter accumulations were mostly concentrated in two large scours in the steeper middle reach of the canyon. Plastic particles and fragments generally occurred on the upstream-facing sides of large boulders and other topographic obstacles, indicating obstruction during down-valley transportation. Most of the litter accumulations were distributed in the up-valley dipping slopes downstream of the scour centers. This pattern is tentatively linked to turbidity currents, which accelerated down the steep upstream slopes of the scours and underwent a hydraulic jump toward the scour centers before decelerating on the upstream-facing flank. Associated seabed sediment consisted of clayey and sandy silts, with unimodal or bimodal grain-size distributions, which are typical for turbidites. The focused distribution of the litter accumulations is therefore linked to turbidity currents that episodically flush the canyon. Our findings provide evidence that litter dispersion in the deep sea may initially be governed by gravity flows, and that turbidity currents efficiently transfer plastic litter to the deeper ocean floor.
Cerebral protothecosis mimicking high-grade glioma
Authors: Samarasekara James , Mukherjee Soumya , Ismail Azzam , Corns Robert
Published: January 2021

Prototheca wickerhamiiis a common, indolent alga that seldom causes central nervous system infections in humans. We report the first UK case of cerebral protothecosis in an immunocompetent 56-year-old woman who presented with a 5-month history of intermittent fatigue followed by a 2-week history of symptoms, including right arm and leg weakness, a loss of fine motor coordination, worsening gait, right facial tingling, diplopia and a metallic oral taste. MRI scans revealed a multifocal abnormality suggestive of high-grade glioma. Given the clinical presentation, absence of immunodeficiency and characteristic MRI features, a diagnosis of high-grade glioma was deemed most likely by the multidisciplinary team. Surgical biopsy provided material for histopathological and microbiological diagnosis. She underwent a 2-year course of antimicrobials with surveillance MRI scans. The patient made a good functional recovery but still retains mild neurological sequelae.
Difficulties in diagnosing vertebral osteomyelitis in a child
Authors: Holzmann Jonathan , Pam Sunday , Clark Geoffrey
Published: January 2021

Vertebral osteomyelitis is a rare diagnosis and often delayed diagnosis in children. This is a case of a child presenting with fever, back pain and raised C reactive protein who was found to have aStaphylococcus aureus (S.aureus)bacteraemia. Initial imaging with CT, MRI of the spine and abdominal ultrasound failed to demonstrate a vertebral osteomyelitis or identify another source of the bacteraemia. Due to the high clinical suspicion of a spinal source of the infection, second-line investigations were arranged. A bone scan identified an area of increase metabolic activity in the 12th thoracic vertebrae (T12) and subsequently a diagnosis was confirmed with a focused MRI of T12. This serves as an opportunity to discuss the diagnostic difficulty presented by paediatric vertebral osteomyelitis and more generally the need for clinicians to pursue their clinical suspicion in the face of false negative results to make an accurate and timely diagnosis.
Diffuse breast uptake of technetium-99m tetrofosmin during myocardial perfusion imaging in a lactating mother
Authors: Khan Muhammad Taha , Sultan Fateh Ali Tipoo
Published: January 2021

Myocardial perfusion imaging (MPI) is a useful modality to rule out myocardial ischaemia in patients presenting with chest pain. In nursing mothers imaging with radioisotope is usually avoided but under certain circumstances it is unavoidable. We present the case of a 45-year-old woman with chest pain, who underwent MPI for assessment of ischaemia. The scan showed anterior artefact due to diffuse breast uptake in both the breasts, as the patient was a lactating mother. The case highlights the importance of breast uptake of radioisotope in the lactating mother on MPI and the necessary steps which need to be taken if radiotracer is injected into a lactating woman.
Recurrent coronary thrombotic events in a moderate case of COVID-19
Authors: Muguerza Julian , Loizeau Pierre A
Published: January 2021

We describe the case of a healthy patient with moderate COVID-19 infection without thrombophilia nor coronary disease background who presented with a relapsing thrombotic occlusion of the right coronary artery despite normal oxygenation, adequate antiaggregation and prophylactic anticoagulation. Prophylactic anticoagulation recommendations in COVID-19 were inadequate for this patient. Further data are needed to propose full-dose therapeutic anticoagulation for patients with coronary thrombosis and COVID-19 infection. This could nevertheless be considered even in mild forms of COVID-19.
Conservative management of adult pancreatic haemangioma: case study and literature review
Authors: Langmaid Tess , Ellis Samantha , Fisher Leon , Pilgrim Charles
Published: January 2021

Pancreatic haemangiomas are a rare cause of pancreatic lesions in adults. Diagnosis is challenging as they are seldom suspected and difficult to differentiate on imaging. Historically, pancreatic haemangiomas have been managed surgically despite their benign nature, largely due to diagnostic uncertainty. We present the case of a 69-year-old woman who, through combination of radiological, biochemical and endoscopic investigations, was diagnosed with pancreatic haemangioma and managed conservatively, avoiding the morbidity and mortality associated with surgical resection of a benign lesion.
Resection of a giant retroperitoneal lipoma herniating through the inguinal canal
Authors: Nardi Walter Sebastián , Diaz Saubidet Hernán , Porto Eduardo Agustín , Quildrian Sergio Damián
Published: January 2021

Retroperitoneal lipomas are extremely rare with few cases reported so far in the literature. They can reach different sizes and present with a variety of symptoms. The differential diagnosis is mainly with well-differentiated liposarcoma (WDLPS). We present a 34-year-old woman with a retroperitoneal lipoma herniating through the inguinal canal into the proximal thigh. The patient underwent complete oncological resection using a Karakousis’s abdominoinguinal incision. Retroperitoneal lipomas are a very rare condition and sometimes require resections technically challenging. MDM2 amplification is critical for its differential diagnosis with WDLPS.
Unique case of a post-traumatic nasoseptal arteriovenous malformation
Authors: Lim Kelvin Yong Jie , Soon Alvin Yong Quan , Tan Jian Li
Published: January 2021

Extracranial manifestation of arteriovenous malformations (AVMs) is uncommon. Nasoseptal AVMs are an even rarer entity. In this case report, we present an interesting and first-of-its-kind case of the development of a left nasoseptal AVM in a 60-year-old man after a fall. This was likely post-traumatic, unlike the usual congenital AVMs described in the literature. The patient was managed conservatively with regular follow-up for the AVM as he was asymptomatic.
Do sociodemographic variables moderate effects of an internet intervention for mild to moderate depressive symptoms? An exploratory analysis of a randomised controlled trial (EVIDENT) including 1013 participants
Authors: Nolte Sandra , Busija Ljoudmila , Berger Thomas , Meyer Björn , Moritz Steffen , Rose Matthias , Schröder Johanna , Späth-Nellissen Christina , Klein Jan Philipp
Published: January 2021

Objective

To explore the moderating effects of sociodemographic variables on treatment benefits received from participating in an internet intervention for depression.

Design

Randomised, assessor-blind, controlled trial.

Setting

Online intervention, with participant recruitment using multiple settings, including inpatient and outpatient medical and psychological clinics, depression online forums, health insurance companies and the media (eg, newspaper, radio).

Participants

The EVIDENT trial included 1013 participants with mild to moderate depressive symptoms.

Interventions

The intervention group subjects (n=509) received an online intervention (Deprexis) in addition to care as usual (CAU), while 504 participants received CAU alone.

Methods

To explore subgroup differences, moderating effects were investigated using linear regression models based on intention-to-treat analyses. Moderating effects included sex, age, educational attainment, employment status, relationship status and lifetime frequency of episodes.

Primary and secondary outcome measures

The primary endpoint was change in self-rated depression severity measured by the Patient Health Questionnaire-9 (PHQ-9), comparing baseline versus 12-week post-test assessment. Secondary outcome measures were the Hamilton Rating Scale for Depression and the Quick Inventory of Depressive Symptoms each at 12 weeks and at 6 and 12 months, and PHQ-9 at 6 and 12 months, respectively. In this article, we focus on the primary outcome measure only.

Results

Between-group differences were observed in post-test scores, indicating the effectiveness of Deprexis. While the effects of the intervention could be demonstrated across all subgroups, some showed larger between-group differences than others. However, after exploring the moderating effects based on linear regression models, none of the selected variables was found to be moderating treatment outcomes.

Conclusions

Our findings suggest that Deprexis is equally beneficial to a wide range of people; that is, participant characteristics were not associated with treatment benefits. Therefore, participant recruitment into web-based psychotherapeutic interventions should be broad, while special attention may be paid to those currently under-represented in these interventions.

Trial registration number

NCT01636752.
Self-harm among in-school and street-connected adolescents in Ghana: a cross-sectional survey in the Greater Accra region
Authors: Quarshie Emmanuel Nii-Boye , Shuweihdi Farag , Waterman Mitch , House Allan
Published: January 2021

Objectives

To identify the prevalence, methods, associations and reported reasons for self-harm among in-school and street-connected adolescents in Ghana.

Design

A cross-sectional survey. We applied multi-level regression models and model-based cluster analysis to the data.

Setting

Three contexts in the Greater Accra region were used: second cycle schools, facilities of charity organisations and street census enumeration areas (sleeping places of street-connected adolescents, street corners, quiet spots of restaurants, markets, train and bus stations, and lorry and car parks).

Participants

A regionally representative sample of 2107 (1723 in-school and 384 street-connected) adolescents aged 13–21 years.

Outcome measures

Participants responded to a structured self-report anonymous questionnaire describing their experience of self-harm and eliciting demographic information and social and personal adversities.

Results

The lifetime prevalence of self-harm was 20.2% (95% CI 19.0% to 22.0%), 12-month prevalence was 16.6% (95% CI 15.0% to 18.0%) and 1-month prevalence was 3.1% (95% CI 2.0% to 4.0%). Self-injury alone accounted for 54.5% episodes and self-poisoning alone for 16.2% episodes, with more than one method used in 26% of episodes. Self-cutting (38.7%) was the most common form of self-injury, whereas alcohol (39.2%) and medications (27.7%) were the most commonly reported means of self-poisoning. The factors associated with self-harm were interpersonal: conflict with parents (adjusted OR (aOR)=1.87, 95% CI 1.24 to 2.81), physical abuse victimisation (aOR=1.69, 95% CI 1.16 to 2.47), difficulty in making and keeping friends (aOR=1.24, 95% CI 0.85 to 1.80), sexual abuse victimisation (aOR=1.21, 95% CI 0.78 to 1.87) and conflict between parents (aOR=1.07, 95% CI 0.73 to 1.56).

Conclusions

Self-harm is a significant public health problem among in-school and street-connected adolescents in the Greater Accra region of Ghana. Its origins are very largely in social and familial adversity, and therefore prevention and treatment measures need to be focused in these areas.
Pulsating and Rotating Spirals in a Delayed Feedback Diffractive Nonlinear Optical System
Authors: Budzinskiy Stanislav , Razgulin Alexander
Published: January 2021

We study spiral waves in a mathematical model of a nonlinear optical system with a feedback loop. Starting from a delayed scalar diffusion equation in a thin annulus with oblique derivative boundary conditions, we shrink the annulus and derive the limiting equation on a circle. Based on the explicitly constructed normal form of the Hopf bifurcation for the one-dimensional delayed scalar diffusion equation, we make predictions about the existence and stability of two-dimensional spirals that we verify in direct numerical simulations, observing pulsating and rotating spiral waves.
Quasiperiodic-Chaotic Neural Networks and Short-Term Analog Memory
Authors: Ichinose Natsuhiro
Published: January 2021

A model of quasiperiodic-chaotic neural networks is proposed on the basis of chaotic neural networks. A quasiperiodic-chaotic neuron exhibits quasiperiodic dynamics that an original chaotic neuron does not have. Quasiperiodic and chaotic solutions are exclusively isolated in the parameter space. The chaotic domain can be identified by the presence of a folding structure of an invariant closed curve. Using the property that the influence of perturbation is conserved in the quasiperiodic solution, we demonstrate short-term visual memory in which real numbers are acceptable for representing colors. The quasiperiodic solution is sensitive to dynamical noise when images are restored. However, the quasiperiodic synchronization among neurons can reduce the influence of noise. Short-term analog memory using quasiperiodicity is important in that it can directly store analog quantities. The quasiperiodic-chaotic neural networks are shown to work as large-scale analog storage arrays. This type of analog memory has potential applications to analog computation such as deep learning.
Unilateral Global Bifurcation from Infinity in Nonlinearizable One-Dimensional Dirac Problems
Authors: Aliyev Ziyatkhan S. , Neymatov Nazim A. , Rzayeva Humay Sh.
Published: January 2021

In this paper, we study the unilateral global bifurcation from infinity in nonlinearizable eigenvalue problems for the one-dimensional Dirac equation. We show the existence of two families of unbounded continua of the set of nontrivial solutions emanating from asymptotically bifurcation intervals and having the usual nodal properties near these intervals.
A New Solving Procedure for the Kelvin–Kirchhoff Equations in Case of a Falling Rotating Torus
Authors: Ershkov Sergey V. , Leshchenko Dmytro , Giniyatullin Ayrat R.
Published: January 2021

We present a new solving procedure in this paper for Kelvin–Kirchhoff equations, considering the dynamics of a falling rigid rotating torus in an ideal incompressible fluid, assuming additionally the dynamical symmetry of rotation for the rotating body, [Formula: see text].

The fundamental law of angular momentum conservation is used for the aforementioned solving procedure. The system of Euler equations for the dynamics of torus rotation is explored for an analytic way of presentation of the approximated solution (where we consider the case of laminar flow at slow regime of torus rotation). The second finding is that the Stokes boundary layer phenomenon on the boundaries of the torus also assumed additionally at the formulation of basic Kelvin–Kirchhoff equations (for which the analytical expressions for the components of fluid’s torque vector [Formula: see text] were obtained earlier). The results for calculating the components of angular velocity [Formula: see text] should then be used for full solving the momentum equation of Kelvin–Kirchhoff system. The trajectories of motion can be divided into, preferably, three classes: zigzagging, helical spiral motion, and the chaotic regime of oscillations.
A Simple Guide for Plotting a Proper Bifurcation Diagram
Authors: Jafari Ali , Hussain Iqtadar , Nazarimehr Fahimeh , Golpayegani Seyed Mohammad Reza Hashemi , Jafari Sajad
Published: January 2021

In this paper, we propose a guideline for plotting the bifurcation diagrams of chaotic systems. We discuss numerical and mathematical facts in order to obtain more accurate and more elegant bifurcation diagrams. The importance of transient time and the phenomena of critical slowing down are investigated. Some critical issues related to multistability are discussed. Finally, a solution for fast obtaining an accurate sketch of the bifurcation diagram is presented. The solution is based on running the system for only one sample in each parameter value and using the system’s state in the previous value of the parameter as the initial condition.
Dynamics of a Four-Dimensional System with Cubic Nonlinearities
Authors: Rech Paulo C.
Published: January 2021

In this paper, we investigate a three-parameter four-dimensional dynamical system, which is modeled by a set of four first-order nonlinear ordinary differential equations, each of which contains a crossed cubic term. Dynamical behaviors are characterized in the parameter space of the model. In fact, we use some cross-sections of a three-dimensional parameter-space, namely three related parameter planes, to locate regular and chaotic regions, as well as multistability regions. Lyapunov exponents spectra, bifurcation diagrams, and phase-space portraits are used to complete the analysis.
Sensitivity of Nonautonomous Dynamical Systems on Uniform Spaces
Authors: Salman Mohammad , Wu Xinxing , Das Ruchi
Published: January 2021

We introduce the concepts of sensitivity, multisensitivity, cofinite sensitivity, and syndetic sensitivity for nonautonomous dynamical systems on uniform spaces and obtain some sufficient conditions under which topological transitivity and dense periodic points imply sensitivity for nonautonomous systems on Hausdorff uniform spaces. We also study sensitivity and other stronger versions of sensitivity for the systems induced on hyperspaces and for the product of nonautonomous dynamical systems on uniform spaces.
Palindromes in finite groups and the Explorer-Director game
Authors: Ásgeirsson Dagur Tómas , Devlin Pat
Published: January 2021

In this paper, we use the notion of twisted subgroups (i.e. subsets of group elements closed under the binary operation [Formula: see text]) to provide the first structural characterization of optimal play in the Explorer-Director game, introduced as the Magnus–Derek game by Nedev and Muthukrishnan and generalized to finite groups by Gerbner. In particular, we reduce the game to the problem of finding the largest proper twisted subgroup, and as a corollary we resolve the Explorer-Director game completely for all nilpotent groups.
Representations of Gn3 and related groups
Authors: Fedoseev Denis A. , Kim S. , Manturov Vassily O.
Published: January 2021

In this paper, we study representations of [Formula: see text]-like groups. The group [Formula: see text] itself appeared in works of the third named author on non-Reidemeister knot (and braid) theory. This group is closely related to dynamical systems of points and their invariants. Representations of [Formula: see text]-like groups are useful both for the study of those groups themselves, and constructing invariants of knots and braids based on the [Formula: see text]-like group structure.
Model of nonlinear axion-electrodynamics
Authors: Bruce S. A. , Diaz-Valdes J. F.
Published: January 2021

Within the framework of a derivable construction of QED, a formulation of nonlinear axion-electrodynamics is investigated. This approach is intended to predict possible strong-QED processes with a discussion of the role of axion-like particles that might be significant in nonlinear electrodynamics (NLED). We introduce a nonlinear model of axion-electrodynamics with remaining questions to be further explored.
Video Inpainting: A Complete Framework
Authors: Zarif Sameh , Ibrahim Mina
Published: January 2021

Reconstructing and repairing of corrupted or missing parts after object removal in digital video is an important trend in artwork restoration. Video inpainting is an active subject in video processing, which deals with the recovery of the corrupted or missing data. Most previous video inpainting approaches consume more time in extensive search to find the best patch to restore the damaged frames. In addition to that, most of them cannot handle the gradual and sudden illumination changes, dynamic background, full object occlusion, and object changes in scale. In this paper, we present a complete video inpainting framework without the extensive search process. The proposed framework consists of a segmentation stage based on low-resolution version and background subtraction. A background inpainting stage is applied to restore the damaged background regions after static or moving object removal based on the gray-level co-occurrence matrix (GLCM). A foreground inpainting stage is based on objects repository. GLCM is used to complete the moving occluded objects during the occlusion. The proposed method reduces the inpainting time from hours to a few seconds and maintains the spatial and temporal consistency. It works well when the background has clutter or fake motion, and it can handle the changes in object size and in posture. Moreover, it is able to handle full occlusion and illumination changes.
A Study on the Combined Driven Refrigeration Cycle Using Ejector
Authors: Raza Waseem , Ko Gwang Soo , Park Youn Cheol
Published: January 2021

The rising need for thermal comfort has resulted in a rapid increase in refrigeration systems’ usage and, subsequently, the need for electricity for air-conditioning systems. The ejector system can be driven by a free or affordable low-temperature heat source such as waste heat as the primary source of energy instead of electricity. Heat-driven ejector refrigeration systems become a promising solution for reducing energy consumption to conventional compressor-based refrigeration technologies. An air-conditioning system that uses the ejector achieves better performance in terms of energy-saving. This paper presents a study on the combined driven refrigeration cycle based on ejectors to maximize cycle performance. The experimental setup is designed to determine the coefficient of performance (COP) with ejector nozzle sizes 1.8, 3.6, and 5.4[Formula: see text]mm, respectively. In this system, the R-134a refrigerant is considered as a working fluid. The results depict that the efficiency is higher than that of the conventional refrigeration method due to comparing the performance of the conventional refrigeration cycle and the combined driven refrigeration cycle. The modified cycle efficiency is better than the vapor compression cycle below 0∘C, which implies sustainability at low temperatures by using low-grade thermal energy. For the improvement of mechanical efficiency, proposed cycle can be easily used.
A Case for Elevating the Edge to be a Peer of the Cloud
Authors: Ramachandran Umakishore , Gupta Harshit , Hall Adam , Saurez Enrique , Xu Zhuangdi
Published: January 2021

Over the last 20 years, mobile computing has evolved to encompass a wide array of increasingly data-rich applications. Many of these applications were enabled by the Cloud computing revolution, which commoditized server hardware to support vast numbers of mobile users from a few large, centralized data centers. Today, mobile's next stage of evolution is spurred by interest in emerging technologies such as Augmented and Virtual Reality (AR/VR), the Internet of Things (IoT), and Autonomous Vehicles. New applications relying on these technologies often require very low latency response times, increased bandwidth consumption, and the need to preserve privacy. Meeting all of these requirements from the Cloud alone is challenging for several reasons. First, the amount of data generated by devices can quickly saturate the bandwidth of backhaul links to the Cloud. Second, achieving low-latency responses for making decisions on sensed data becomes increasingly difficult the further mobile devices are from centralized Cloud data centers. And finally, regulatory or privacy restrictions on the data generated by devices may require that such data be kept locally. For these reasons, enabling next-generation technologies requires us to reconsider the current trend of serving applications from the Cloud alone.