bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review on Role of Yoga in the Management of Patients with Cardiac Arrhythmias
Authors: Sharma Gautam , Mooventhan A , Naik Gitismita , Nivethitha L
Published: April 2021

Evidence suggests that yoga is safe and effective in improving various risk factors, quality of life (QoL), and psychological burden that is related to arrhythmia. However, this is the first-ever systematic review performed to report the role of yoga in arrhythmia. We have performed a literature search using Cochrane Library, Medline/PubMed, Web of Science Core Collection, and IndMED electronic databases up to 3, January 2018. Of 240 articles, 6 potentially eligible articles were identified and included in the review. Results showed that yoga could be considered an efficient adjuvant in reducing arrhythmia (paroxysmal atrial fibrillation, ventricular tachyarrhythmia, and palpitation) related health problems; blood pressure, heart rate, depression and anxiety scores; and in improving health-related QoL of arrhythmia patients. However, there is a lack of randomized controlled trials and a clear mechanism behind the effect of yoga; studies had relatively a small sample size and different yoga protocols.
Aberrant Right Subclavian Artery
Authors: Ramesh Babu C. S. , Gupta Om Prakash , Kumar Arjun
Published: April 2021

Introduction:

Aberrant right subclavian artery (ARSA) arises as the last branch of normally positioned aortic arch and its prevalence estimated as 0.16%–2.0% varies between different ethnic groups. Our aim was to assess the prevalence and associated branching anomalies of ARSA in the Indian participants.

Material and Methods:

Chest computed tomographic scans of 710 patients were analyzed to study the ARSA and its associated vascular anomalies.

Results:

We have observed 11 cases (5 in males and 6 in females) of ARSA with an estimated prevalence of 1.54%. In seven cases, there were four branches arising from the arch of aorta in the order of right common carotid, left common carotid, left subclavian, and aberrant right subclavian. In three cases, there were three branches – bicarotid trunk (common trunk of right and left carotids), left subclavian, and the aberrant right subclavian. In one case, there were five branches in the order of right common carotid, left common carotid, left vertebral, left subclavian, and aberrant right subclavian. Only two participants reported mild symptoms of dysphagia. In all the cases, the ARSA had retroesophageal course. Kommerell diverticulum was not observed. ARSA remain asymptomatic in most cases, but its presence should alert the clinician to look for associated vascular and any cardiac anomalies.

Discussion and Conclusion:

Awareness of the presence of ARSA is crucial for successful outcome of mediastinal, esophageal, and thoracic spine surgeries. Preprocedural computed tomography for the evaluation of aortic arch branching pattern will be beneficial for the successful performance of various surgical and radiological interventions.
Multiple extubation failures following a rhino-enteroviral infection
Authors: Annamalai MR , Bhalala U
Published: April 2021

This case report reviews the hospital course of a 15-month-old girl admitted to the PICU for acute respiratory failure due to enterovirus infection; who subsequently had multiple extubation failures secondary to acute transverse myelitis. This rare presentation highlights the importance of assessing the neurological status in a patient with rhino-enteroviral respiratory infection and of considering acute transverse myelitis as an etiology for difficulty with extubation.
Clinical Approach to a Case of Anterior Uveitis - A Non-Systematic Review
Authors: Mehta Barkha , Thulasidas Mithun
Published: April 2021

Anterior uveitis is the most common form of uveitis, with varying incidences reported in the literature. Anterior uveitis can be benign at the time of presentation; however, it often can lead to severe morbidity if not managed appropriately. The present article assists ophthalmologists in correctly diagnosing anterior uveitis and improving the quality of patient care. It is essential to go into the detailed history of the patient complaints. A thorough and detailed extraocular and ocular examination should be done. Ophthalmologists need to work up each case in a systematic manner.
High risk of Intraocular Pressure Rise with Difluprednate Post Collagen Cross-Linking for Keratoconus
Authors: Bartolomei Sofia Ramos , Román Lilia Rivera
Published: April 2021

Purpose:

To report intraocular pressure (IOP) after use of difluprednate ophthalmic solution 0.05% (Durezol®; Novartis AG, Basilea, Switzerland) post corneal cross-linking (CXL) versus prednisolone (Pred-Forte®; Allergan Inc., Irvine, CA, USA).

Methods:

A retrospective single-center case series evaluation of 34 keratoconus patients ages 16-“41 (36 eyes) who underwent CXL with Avedro's KXL System® (Avedro Inc; Waltham, MA) between August 2016 and August 2017. Post-CXL, six eyes were given difluprednate and 30 were given prednisolone. IOP was recorded using Reichert model 30 pneumatonometer. Those that exhibited increased IOP at 3 days were given anti-glaucoma medications and changed to fluorometholone or loteprednol.

Results:

IOP's 3 days' postoperative (24.167 ± 5.23) in the difluprednate group were significantly higher than preprocedure (16.5 ± 2.258). In the prednisolone group, 3 days postprocedure the mean IOP (14.2 ± 3.199) was not significantly higher than preoperatory IOP mean (16.8 ± 4.232). The difference between IOP 3 days' postprocedure and before was 7.667 ± 4.546 for the difluprednate group and 2.567 ± 2.648 for the prednisolone group. These were compared using an unpaired t-test (t value = 3.750 ± 1.297) with P = 0.0007.

Discussion:

This study shows statistically significant difference in postoperative and preoperative IOP values after the use of difluprednate or prednisolone in young patients postCXL. Measuring the pachymetry on follow-up examinations could help see if changes in corneal thickness affect measured IOP. A controlled prospective double-blind study could confirm a greater increase in IOP following difluprednate versus prednisolone use, but due to the high risk, we do not recommend this study.
Anesthetic management in bilateral video-assisted thoracoscopic sympathectomy for refractory ventricular arrhythmias
Authors: Damasceno Camila Biazussi , Delgado Marina Ayres , Pinheiro Paula Alves , Quadros Isadora Megale
Published: April 2021

Cardiac Sympathetic Denervation (CSD) has been shown to reduce shocks and subsequent pain of implantable cardiac defibrillator (ICD) in patients with heart diseases and recurrent Ventricular Tachycardia (VT) who did not respond properly to oral therapy and ablation. A 68-year-old man who presented an idiopathic dilated cardiomyopathy with impaired ejection fraction was treated for VT. A bilateral cardiac sympathetic denervation was performed under general anesthesia. Patient was extubated in the operating room and transferred to ICU where he presented hypotension. He was discharged after five days and remained symptom-free without any incident of VT during hospital stay. Currently no definite anesthetic management is available to treat such patients. This report discusses an approach that made heart rate control and safe patient discharge possible.
The prevalence and the most significant sources of occupational burnout syndrome amongst anesthetic technicians in Saudi Arabia
Authors: Almodibeg Bader Ali , Smith Hazel L.
Published: April 2021

Aims:

To detect the prevalence and the most significant sources of occupational burnout syndrome among anesthetic technicians in Saudi Arabia and draw recommendations that can reduce the level of this syndrome.

Settings and Design:

A cross-sectional descriptive survey was conducted in a central hospital in Saudi Arabia.

Methods:

Maslach Burnout Inventory and a self-created questionnaire was utilized to survey seventeen anesthesia technicians in order to capture the prevalence and most significant sources of burnout.

Statistical Analysis Used:

Descriptive statistics were utilized to conduct the statistical analysis.

Results:

Occupational burnout syndrome has been found in 29%. A level of emotional exhaustion was critically high in 41.2%. Likewise, a level of depersonalization was extremely high in 58.8%, while 76.5% of anesthetic technicians lacked personal accomplishments. There are several sources perceived by anesthetic technicians as the most significant sources of their occupational burnout syndrome. These sources include staff shortage, high workload, occupational hazards, and poor teamwork. However, the limited career pathway of anesthesia technicians seems to be the main predictor.

Conclusions:

A critically high prevalence of occupational burnout syndrome was found among anesthetic technicians, which is the highest among all studies reviewed worldwide. Several recommendations have been made which require urgent implementation into practice in order to protected practitioners' wellbeing and decrease their rate of turnover. These recommendations include implementing physician-led team-based care, provision of training and resources, fostering equity in a workplace and provision of hazard pay.
Prevalence of vasovagal syncope following bariatric surgery
Authors: Al Obeed Omar A. , Traiki Thamer Bin , Alfahad Yara F. , Abdulla Maha-Hamadien , AlAli Mohamed N. , Alharbi Abdulhamed A. , Alharbi Reem , Nouh Thamer , Hersi Ahmad
Published: April 2021

Background:

Obesity is a major global public health problem. Observational studies have shown an increasing incidence of syncope and pre-syncope following bariatric surgery in obese patients. However, there is paucity of the true incidence of syncope following bariatrics sugary in the literature.

Methods:

We have randomly surveyed 200 patients who underwent bariatric surgery between 2016-2018 using Calgary Syncope Score (CSS).

Results:

Of the 200 patients enrolled, 107 (53.5%) were female with 167 patients (83.5%) between 18 and 50 years of age. The most-reported comorbidities were diabetes mellitus 26 (13%) hypertension 25 (12.5%) and pulmonary disease 18 (9%). The majority 98 (49%) of the patients had pre-operative body mass index (BMI) of 40–50 kg/m 2, and most of them had laparoscopic sleeve gastrectomy (LSG). Sixty-two (31%) patients had vasovagal syncope (VVS), 52 (26%) patients had non-VVS and 86 (43%) had no syncope.

Conclusion:

Vasovagal syncope in patients following bariatric sugary is quite common and affects 15% of bariatric patients in our series in the first year postoperatively. Further randomized controlled trials are required to prove our results.
Effectiveness of pre-anesthetic video information on patient anxiety and economical aspects
Authors: Metterlein Thomas , Wobbe Thomas , Brede Marc-Elmer , Möller Katharina , Röder Daniel , Krannich Jens , Kranke Peter , Tannert Andreas , Broscheit Jens
Published: April 2021

Background:

Adequate preoperative information can lessen patient anxiety. Delivering sufficient information during a personal interview, however, is time consuming, and therefore a relevant economical aspect. We investigated whether video information given to the patient before the pre-anesthetic interview has an influence on the patient's anxiety and the duration of the interview.

Method:

We randomized 302 patients undergoing different types of anesthesia. In all, 151 patients watched a short video with general information about the anticipated anesthesia procedure. Afterward, all patients had a standard pre-anesthetic interview. Patients' anxiety and satisfaction with pre-anesthesia care were assessed after the interview using a visual analogue scale. The duration of the interview was documented. Student t-test and P < 0.05 for differences between the groups.

Results:

There was no difference in gender, age, ASA physical status, previous anesthesia experience, and the planned anesthesia procedure between the two groups. No difference in anxiety and satisfaction with pre-anesthesia care was observed. The duration of the pre-anesthetic interview was also not different between the groups.

Discussion:

Preoperative multimedia information did not reduce anxiety or increase the patient satisfaction undergoing anesthesia. The video containing general information did not save time in the pre-anesthetic interview.
Retrogasserian radiofrequency thermocoagulation
Authors: Demartini L. , Conversa G. , Bettaglio R. , Bonezzi C. , Marchesini M.
Published: April 2021

Background:

Trigeminal neuralgia present an incidence rates ranging between 5.9 and 12.6 per 100.000 persons; although not frequent, it is a pathology often characterized by intense pain, an extremely significant reduction in quality of life and medical therapy is not always effective or tolerated. In these cases, the patient can undergo interventional treatments including radiofrequency thermocoagulation. There are still doubts regarding the effectiveness over time, the injury parameters and the repeatability of the procedure.

Materials and Methods:

We analyze patients with trigeminal pain undergo retrogasserian radiofrequency in a single center over a period of 8 years. The procedure was performed with the following parameters: Lesion time 60 sec, lesion temperature 70°C for first thermolesion 72°C for subsequent thermolesions. Duration of benefit, number of repetitions of the maneuver, and incidence of adverse events were assessed.

Results:

Totally, 122 patients with essential trigeminal neuralgia and 20 patients with trigeminal neuralgia secondary to multiple sclerosis were analyzed; almost all patients (96.5%) showed a significant reduction in pain after one or more procedures over time; 96.5 of the patients showed excellent pain relief after 1 (40%) or more procedures (60%). The average time between one procedure and the next was 26 months.

Conclusion:

The use of time and temperature parameters chosen shows excellent efficacy, in line with the literature, with very low incidence of adverse events. The pain-free time between one procedure and the next does not seem to be a significant prognostic criterion which may or may not indicate the repetition of the procedure.
Teammate Advanced Drive System Using Automated Driving Technology
Authors: Kawasaki Tomoya , Caveney Derek , Katoh Masayuki , Akaho Daisuke , Takashiro Yosuke , Tomiita Kenji
Published: April 2021

Woven Core, Inc. has developed Teammate Advanced Drive, a driving support system with state-of-the-art automated driving technology based on the Mobility Teammate Concept by Toyota Motor Corporation. Teammate Advanced Drive enables intelligent Ramp to Ramp hands-off driving on highways. The system features a self-localization estimation system that uses an HD-Map (High Definition Map) and high-level redundancy across sensors, computing, actuators, power supplies, and data communication. The system also includes digital data uploading and downloading capabilities wirelessly OTA (Over the Air) in order to provide customers the latest map updates as well as new software features and upgraded performance. A number of characteristically unique sensors have been combined to monitor the entire perimeter of the vehicle with high reliability. The perception system combines sensing data from radars, newly developed LiDAR (Light Detection and Ranging), and cameras for redundant omnidirectional detection. Teammate Advanced Drive provides high-performance computing by combining multiple advanced SoC (System on Chip) and highly reliable MCU (Micro Controller Unit), in order to achieve real-time execution of multi-processing system components, including deep neural networks. In order to provide enhanced safety, a fail-safe operation system, which utilizes a high-redundancy structure, has been developed to takeover for the driver when a malfunction or a system limitation is detected. This includes an Emergency Driving Stop System, which is able to guide the vehicle to the road shoulder if the system detects that the human driver is incapacitated or otherwise unable to drive the vehicle manually.
Detection & Tracking of Multi-Scenic Lane Based on Segnet-LSTM Semantic Split Network
Authors: Ye Meng , Tan Gangfeng , Tang Jingning , Feng Jiaming , Huang Xin , Sun Wenchao
Published: April 2021

Lane detection is an important component in automatic pilot system and advanced driving assistance system (ADAS). The stability and precision of lane detection will directly determine precision of control and lane plan of vehicles. Traditional mechanical vision lane detection approaches in complicated environment have the deficiencies of low precision and feature semantic description disabilities. But the lane detection depending on deep learning, e.g. SCNN network, LaneNet network, ENet-SAD network have imbalance problems of splitting precision and storage usage. This paper proposes an approach of high-efficiency deep learning Segnet-LSTM semantic segmentation network. This network structure is composed with encoding network and corresponding decoding networks. First, convolution and maximum pooling. The proposal extracts texture details of five images and stores searching position of maximum pooling. Meanwhile, it will implement interpolate processing to the lost points. Then, by up-sampling and convoluting with decoders and predicts category of a specific pixel with Softmax function. At the same time, it splits with long and short term memories of LSTM network and finally, the output is a complete image that enables detection and tracking of lanes in during the day and at night. Experiments have suggested that this approach provides more fitting precision and feature extraction precision in comparison with Unet-LSTM algorithm. This algorithm provide accuracy that is 3.724% higher than that of Unet-LSTM in the day in perspective of miou value and the precision of lane pixel categorization is 4.126% higher than that of Unet-LSTM. Besides, miou of this algorithm at night is 5.6% higher than that of Unet-LSTM and the precision of lane pixel categorization is 4.1398% higher. Moreover, the algorithm allows balance between storage involvement and precision of lane detection on the basis of high fitting precision, guaranteeing real-time performance and stability in various senses, assisting auto pilots in more efficiently.
Assessing the Access to Jobs by Shared Autonomous Vehicles in Marysville, Ohio: Modeling, Simulating and Validating
Authors: Meneses Cime Karina , Cantas Mustafa Ridvan , Fernandez Pedro , Aksun Guvenc Bilin , Guvenc Levent , Joshi Adit , Fishelson James , Mittal Archak
Published: April 2021

Autonomous vehicles are expected to change our lives with significant applications like on-demand, shared autonomous taxi operations. Considering that most vehicles in a fleet are parked and hence idle resources when they are not used, shared on-demand services can utilize them much more efficiently. While ride hailing of autonomous vehicles is still very costly due to the initial investment, a shared autonomous vehicle fleet can lower its long-term cost such that it becomes economically feasible. This requires the Shared Autonomous Vehicles (SAV) in the fleet to be in operation as much as possible. Motivated by these applications, this paper presents a simulation environment to model and simulate shared autonomous vehicles in a geo-fenced urban setting. To simulate the aforementioned applications, a simulation environment that has a realistic rendering of the chosen real-world environment with realistic traffic generated around the SAVs is developed first using a geo-fenced area centered at the city of Marysville in Ohio as an example. This paper, then, presents an algorithm to optimally utilize multiple autonomous vehicles for shared rides based on modeling of pickup locations corresponding to affordable housing at the periphery of the geo-fenced area connected to destination locations corresponding to jobs and other locations of opportunity. The presented work showcases SAV operation as a solution to the spatial mismatch between affordable housing and job locations in a realistic simulation environment in an urban setting.
Simulation-Based Evaluation of Cooperative Maneuver Coordination and Its Impact on Traffic Quality
Authors: Lizenberg Viktor , Bischoff Daniel , Haridy Youssef , Eberle Ulrich , Knapp Steffen , Koester Frank
Published: April 2021

Cooperative Maneuver Coordination (CMC) is one of the cornerstone technologies on the way to automated and connected driving of the future. The goal of this technology is to increase traffic safety and efficiency, by solving potential conflict situations on the road, based on cooperative maneuver planning, negotiation and decision-making, with the aid of inter-vehicular communication. This innovative topic represents a wide area for research projects, e.g., such as German funded project IMAGinE. A variety of different approaches for CMC has already been implemented and evaluated in the related work of the recent past. However, due to the high system complexity in general and vast testing effort in particular of these solutions, their actual impact on the traffic quality has not yet been extensively addressed, and therefore must be further investigated. In order to fulfill this task, one needs a methodology with appropriate evaluation metrics alongside with a suitable testing environment, in order to obtain comprehensive results. The scientific contribution of the work at hand involves a simulation-based evaluation methodology for CMC. For this, we will propose a novel CMC algorithm, which is built upon a direct trajectory exchange via inter-vehicular communication and a decentralized decision-making process, suitable for both manually operated as well as autonomous vehicles. In order to examine this algorithm, we will introduce a co-simulation environment with automatic scenario generation and multi-instances capability, which consists of a coupled simulation of traffic flow and vehicle dynamics. Eventually, we will present a set of metrics, which we determined in order to evaluate effectiveness and efficiency of our CMC algorithm, considering its impact on various aspects of the traffic quality.
Infrastructure-Based Sensor Data Capture Systems for Measurement of Operational Safety Assessment (OSA) Metrics
Authors: Altekar Niraj , Como Steven , Lu Duo , Wishart Jeffrey , Bruyere Donald , Saleem Faisal , Head K. Larry
Published: April 2021

The operational safety of automated driving system (ADS)-equipped vehicles (AVs) needs to be quantified for an understanding of risk, requiring the measurement of parameters as they relate to AVs and human driven vehicles alike. In prior work by the Institute of Automated Mobility (IAM), operational safety metrics were introduced as part of an operational safety assessment (OSA) methodology that provide quantification of behavioral safety of AVs and human-driven vehicles as they interact with each other and other road users. To calculate OSA metrics, the data capture system must accurately and precisely determine position, velocity, acceleration, and geometrical relationships between various safety-critical traffic participants. The design of an infrastructure-based system that is intended to capture the data required for calculation of OSA metrics is addressed in this paper. The designed multi-modal sensor system includes a combination of traffic video cameras, vehicle-to-infrastructure (V2I) roadside units (RSUs), National Transportation Communications for Intelligent Transportation System Protocol (NTCIP)-compliant signal controllers streaming Signal Phase and Timing (SPAT) data, and Light Detection and Ranging (LIDAR) sensors. The system is contrasted with other design options to evaluate trade-offs between capability and cost. The designed data capture system was deployed at a SMARTDrive ProgramSM Test Bed intersection in Anthem, AZ that has been developed by the University of Arizona Transportation Research Institute (TRI) in cooperation with the Maricopa County Department of Transportation (MCDOT). The intersection is equipped with a sensor system that includes a fiber optic data transfer backbone to support the data transfer to a server at the MCDOT Traffic Management Center. A measurement uncertainty (MU) analysis has been conducted using experimental data to better understand the performance and reliability of the proposed sensor system design. The data capture system will enable the development and validation of a methodology to continuously measure OSA metrics by gaining rich information through fusion of multimodal data collected from available sources for safety assessment of the transportation system that includes AVs.
Multi-task Learning of Semantics, Geometry and Motion for Vision-based End-to-End Self-Driving
Authors: Ni Hailong , Wu Jian , Zhang Dong , Wang Guojun , Chen Zhicheng
Published: April 2021

It’s hard to achieve complete self-driving using hand-crafting generalized decision-making rules, while the end-to-end self-driving system is low in complexity, does not require hand-crafting rules, and can deal with complex situations. Modular-based self-driving systems require multi-task fusion and high-precision maps, resulting in high system complexity and increased costs. In end-to-end self-driving, we usually only use camera to obtain scene status information, so image processing is very important. Numerous deep learning applications benefit from multi-task learning, as the multi-task learning can accelerate model training and improve accuracy with combine all tasks into one model, which reduces the amount of calculation and allows these systems to run in real-time. Therefore, the approach of obtaining rich scene state information based on multi-task learning is very attractive. In this paper, we propose an approach to multi-task learning for semantics, geometry and motion. The multi-task learning includes four tasks: semantics segmentation, instance segmentation, depth regression, optical flow estimation. Optical flow method is currently an important method of moving image analysis and it not only contains the motion information of the observed object, but also contains rich information about the three-dimensional structure of the scene. Through the above work we can get compressed information about semantics, distance estimation and action recognition. As we all know, self-driving based on deep learning requires a lot of data to train neural network models. However, the basic attributes of the end-to-end system determine that it cannot be trained and learning in real world, such as collision testing and traffic accidents during reinforcement learning. Therefore, integrating existing autonomous driving data sets for model training and generalizing them to virtual environments for application is very critical. Finally, we use the virtual scene constructed by CARLA to train and evaluate the end-to-end self-driving system.
Constitutive, Formability, and Fracture Characterization of 3rd Gen AHSS with an Ultimate Tensile Strength of 1180 MPa
Authors: Noder Jacqueline , Gutierrez Jon Edward , Zhumagulov Amir , Khameneh Farinaz , Ezzat Hesham , Dykeman James , Butcher Cliff
Published: April 2021

The superior formability and local ductility of the emerging class of third generation of advanced high-strength steels (3rd Gen AHSS) compared to their conventional counterparts of the same strength level offer significant advantages for automotive lightweighting and enhanced crash performance. Nevertheless, studies on the material behavior of 3rd Gen AHSS have been limited and there is some uncertainty surrounding the applicability of developed methodologies for conventional dual-phase (DP) steels to this new class of AHSS. The present paper provides a comprehensive study on the quasi-static and dynamic constitutive behavior, formability characterization and prediction, and the fracture behavior of two commercial 3rd Gen AHSS with an ultimate strength of 1180 MPa that will be contrasted with a conventional DP1180. The hardening response to large strain levels was determined experimentally using tensile and shear tests and then validated with 3-D simulations of tensile tests. In general, the strain rate sensitivity of the two 3rd Gen AHSS was significantly different as one grade exhibited larger transformation-induced behavior. The in-plane formability of the three 1180 MPa steels determined using Marciniak tests was similar but with a stark contrast in the local formability for the 3rd Gen AHSS. The forming limit curves could be accurately predicted using the experimentally measured hardening behaviour and the modified Bressan-Williams through-thickness shear model. An efficient experimental approach to fracture characterization for AHSS was developed that exploits tool contact and bending to obtain fracture strains on the surface of the specimen by suppressing necking. Miniature conical hole expansion and biaxial punch tests are used along with the VDA 238-100 bend test.
Development and Validation of an Accurate 1D Model for Pressure Drop in Complex Coolant Piping Systems of Hybrid and Electric Vehicles
Authors: Lucena Kreppel Paes Paulo , Vijay Dig , Kanani Yousef , Framke Nils-Henning , Harnish Shawn , Spasov Mihail
Published: April 2021

The development of efficient, reliable, and affordable Hybrid and Electric Vehicles (xEVs) relies on optimized Vehicle Thermal Management System (VTMS) architecture and control strategies. Compared to conventional vehicles, xEVs have more complex VTMS due to additional powertrain components and cooling circuits to meet distinct thermal requirements. The cooling circuits comprise a combination of hoses, straight, and bent pipes to route coolant flow around obstacles between powertrain components at distinct locations in the vehicle. The increased length and geometrical complexity of these piping systems, compared to conventional vehicles, results in increased pressure losses. Thus, accurate predictions of pressure drop within these piping systems is critical for component selection for an optimized VTMS. Numerical simulations are often used to study interactions between components from a system-level perspective allowing early stage rapid assessment of performance. In this work, an accurate 1D model for pressure drop in piping systems is developed based on literature review and validated using 3D Computational Fluid Dynamics (CFD) predictions. The 1D model is implemented in the software tool GT-SUITE which is used for integrated 0D/1D/3D multi-physics system simulation of the entire VTMS. The CFD calculations are performed using GT-CONVERGE. Overall, the pressure drop predictions of the 1D model are in good agreement with the 3D CFD for a range of Reynolds numbers including laminar, transition, and turbulent regimes and even when significant losses are present due to flow redevelopment after bends. Typically, commercial tools often ignore flow redevelopment and were originally developed for high Reynolds number flows. A typical battery electric vehicle is constructed in GT-SUITE and results indicate that deviations on pressure drop predictions lead to significant deviations on pump operating conditions and isentropic efficiency. The 1D model allows fast and accurate simulations over a broad range of complex piping configurations for an optimized VTMS.
In-Vehicle Test Results for Advanced Propulsion and Vehicle System Controls Using Connected and Automated Vehicle Information
Authors: Rajakumar Deshpande Shreshta , Gupta Shobhit , Kibalama Dennis , Pivaro Nicola , Canova Marcello , Rizzoni Giorgio , Aggoune Karim , Olin Pete , Kirwan John
Published: April 2021

A key enabler to maximizing the benefits from advanced powertrain technologies is to adopt a systems integration approach and develop optimized controls that consider the propulsion system and vehicle as a whole. This approach becomes essential when incorporating Advanced Driver Assistance Systems (ADAS) and communication technologies, which can provide information on future driving conditions. This may enable the powertrain control system to further improve the vehicle performance and energy efficiency, shifting from an instantaneous optimization of energy consumption to a predictive and “look-ahead” optimization. Benefits from this approach can be realized at all levels of electrification, from conventional combustion engines to hybrid propulsion systems and full electric vehicles, and at all levels of vehicle automation.

This paper documents an extensive simulation and experimental campaign that provides a systematic quantification of fuel economy and mobility benefits resulting from leveraging Vehicle-to-Everything (V2X) connectivity, longitudinal (Level 1+) automation, and advanced cylinder deactivation to improve the propulsion system and vehicle efficiency. A Vehicle Dynamics and Powertrain (VD&PT) optimization framework, developed jointly by The Ohio State University and BorgWarner, utilizes advanced route information available from the navigation system and GPS, and Vehicle-to-Infrastructure (V2I) communication when available to minimize the cumulative fuel consumption over a driver-selected route.

To assess the benefits of these technologies in real-world conditions, a Monte Carlo simulation framework was developed to quantify the impact of Signal Phase and Timing (SPaT), variability in traffic conditions, and behavior of different drivers on the fuel consumption and vehicle travel time. Further, verification through in-vehicle testing was conducted by reconstructing a subset of these scenarios on a proving ground.
Analysis of Fuel Properties on Combustion Characteristics in a Narrow-Throat Pre-Chamber Engine
Authors: Hlaing Ponnya , Echeverri Marquez Manuel , Burgos Paula , Cenker Emre , Ben Houidi Moez , Johansson Bengt
Published: April 2021

In this study, the authors investigated the effect of fuel properties on the combustion characteristics by employing methane, methanol, ethanol, and primary reference fuels (PRFs) as the main chamber fuel while using methane for the pre-chamber. Global excess air ratios (λ) from 1.6 to lean limit were tested, while 13% of total fuel energy supplied to the engine was delivered via the pre-chamber. The gaseous methane was injected into the pre-chamber at the gas exchange top-dead-center (TDC). Port fuel injection was tested with both open and closed inlet valves. The pre-chamber assembly was designed to fit into the diesel injector pocket of the base engine, which resulted in a narrow throat diameter of 3.3 mm. The combustion stability limit was set at 5% of the coefficient of variation of gross IMEP, and the knock intensity limit was set at 10 bar. GT-Power software was used to estimate the composition of pre-chamber species and was used in heat release analysis of the two chambers. It was found that the rich limit was controlled by engine knock. Hence a higher reactivity fuel (lower octane) had to be operated leaner. However, with the increasing reactivity, the lean limit was also extended, while the peak efficiency was also obtained with a leaner mixture. With PRF 90, the lean limit was at global-λ = 3.0, while the limit was 2.3 with methane. The alcohol fuels exhibited a different behavior from the methane and the PRFs. Ethanol has the same lean limit as PRF100, but methanol could be operated up to global-λ = 3.2. The pre-chamber combustion did not change much with the different fuels in the main chamber, so the combustion stability trends must be related to the transition from burning jets to ignition of the main chamber charge and its subsequent combustion.
Analytical Modeling and Calculation of Electromagnetic Torque of Interior Permanent Magnet Synchronous Motor Considering Ripple Characteristics
Authors: Wu Zhipeng , Zuo Shuguang , Chen Siyue
Published: April 2021

Based on the classical dq theory, this paper proposes a new electromagnetic torque analytical model (AM) for interior permanent magnet synchronous motor (IPMSM) considering ripple characteristics, including permanent magnet (PM) torque ripple and reluctance torque ripple. The analytical expression of PM torque considering the effect of PM flux linkage harmonics is first derived according to dq transformation and energy method. Then, an improved inductance calculation method considering the non-sinusoidal magnetic field distribution and cross-coupling effect is proposed, and the reluctance torque model is established by taking the influence of inductance harmonics into consideration. Subsequently, the total electromagnetic torque can be obtained by the superposition of PM torque and reluctance torque. Finally, the proposed AM was verified by finite-element method (FEM). The results show that the proposed AM is accurate enough to predict the instantaneous electromagnetic torque waveforms and the average electromagnetic torque. In addition, according to the proposed AM, the sources and order features of torque ripples can be directly determined, and the intrinsic relationship between key electromagnetic parameters and torque harmonics can be revealed.
Fail-Safe Study on Brake Blending Control
Authors: Lehne Christoph , Augsburg Klaus , Ivanov Valentin , Ricciardi Vincenzo , Büchner Florian , Schreiber Viktor
Published: April 2021

Battery electric vehicles (BEV) share the ability of regenerative braking since
they are equipped with two independent types of deceleration devices, namely the
electric motor working as a generator and the friction brakes. Correct
interaction of these systems in terms of driving safety and energy efficiency is
a function of the Brake Blending Control. Individual electric motors for each
wheel and a decoupled brake system provides the Brake Blending with a high
design flexibility that allows significant advantages regarding energy
consumption, brake performance, and driving comfort. This paper is focusing on
the fail behaviour and analyses the robustness and redundancy abilities of such
systems against various error scenarios. For this purposes, a distributed
x-in-the-loop environment, consisting of dedicated simulation and hardware
testing components, is introduced. The investigation is carried out based on a
high-fidelity real-time simulation model of an electric sport utility vehicle
with four in-wheel motors (IWM) and decoupled electro-hydraulic brake system.
This model can be used for a detailed analysis of vehicle dynamics in case of
brake system fails. The electro-hydraulic decoupled brake system is implemented
through a Hardware-in-the-loop test rig, which allows a realistic fault
injection. The vehicle stability and controllability is investigated under the
circumstances of various brake system failures in the regenerative and friction
brake system, respectively. These studies are presented according to
standardized test scenarios like Straight line braking (DIN 70028) and
Brake-in-turn (ISO 7975). With obtained x-in-the-loop simulation results, the
impact of a failure on vehicle dynamics is discussed in the final part of the
paper.
Knowledge, Attitude and Practice of Exclusive Breastfeeding amongst Mothers of Infants in Gwagwalada Area Council, FCT, Abuja, Nigeria
Authors: Okoroiwu G.I.A. , Ubosi N.I. , Aliyu S.M. , Eya C.P.
Published: April 2021

Exclusive breastfeeding provides nutritional, and developmental psychological advantages with regard to general wellbeing of an infant and has dramatically reduced infant deaths in developing countries. This study assessed the Knowledge, Attitude and Practice of Exclusive Breastfeeding among women attending antenatal clinic in four communities within Gwagwalada Area Council of FCT, Abuja. The questionnaire sought socio-demographic information, Religion and cultural influence as well as knowledge and awareness level of EBF practice. The data collected was analyzed using Odd ratio, frequencies and simple percentages. The result of the study showed that 70.0% had the knowledge of exclusive breastfeeding, 54.4% exclusively breastfed their newborns for the first six months of life. There was positive attitude among the participants towards exclusive breastfeeding as 70.0% of them agreed that breast milk alone is sufficient for the baby during the first six months of life. There was high level of knowledge on exclusive breastfeeding among therespondents, almost half of the participants practiced exclusive breastfeeding and relatively all the respondents had positive attitude toward exclusive breastfeeding. However, Illiteracy (60.0%; OR = 1.5) and Culture (66.7%; OR = 2.0) negatively influenced exclusive breastfeeding in the area council. Although, majority of the women in this study had good knowledge and attitude towards Exclusive Breastfeeding (EBF), the practice is not high. There is still need for improvement. More awareness on the benefits of exclusive breastfeeding must be emphasized in order to increase the knowledge and compliance of the women as only 54.4% actually practiced it. Promotion of EBF should involve programmes that will capture not only nursing mothers and health workers, but other members in the communities, most especially husbands and older women who are involved in child care.
Examining E-learning as an alternative solution to conventional learning during and post Covid-19 in Nigeria.
Authors: Ebelogu Christopher Ubaka , Ejiofor Virginia Ebere , Omeiza Aliyu , Audu Lucy Hassana
Published: April 2021

It is no longer news that the novel Corona Virus pandemic (COVID-19) is ravaging and still destroying the world, killing so many people and sending economies in different countries into recession. COVID-19 came as a thief in the night in the household of traditional schooling. Gradually, the face-to-face traditional way of teaching and learning was immediately put on hold and all parties running to their shelves for cover as measure to avert the spread of the dreaded virus. What came up as a viable alternative to face-to-face or conventional mode of teaching-learning in school and higher institution is E-learning. So many of these educational institutions had to resort to learning through some E-learning platforms which include ZOOM, YouTube, Google Meet, Google Classroom, Duo, Free Conference Call, etc. This established the fact that majority of the organizations have made an instant switch to online collaboration inclusive of schooling systems. This paper therefore sort to examine how Nigerian schools are reshaping the schooling/education system as to align with the alternative model of teaching-learning most essentially as E-learning rest on major pillars which are undoubtedly deficient in Nigeria and amongst Nigerians. There are challenges to overcome in achieving the e-learning phenomenon in Nigeria, many students without reliable internet access, power supply and technology struggle to participate in digital activities, which hinder online learning. The paper was approached in an E-learning subscriber or user point of view around FCT Abuja metropolis which includes teachers and learners (students/pupils). Questionnaires were distributed to the E-learning users and also the teachers of E-learning. Data were collected and analyzed using percentage method and Likert method to arrive at a conclusion and useful recommendations were made to enhance e-learning during and post COVID-19 in the various educational institutions in Nigeria.
Face mask detection application and dataset
Authors: Matthias Daniel , Managwu Chidozie , Olumide O.
Published: April 2021

The COVID–19 pandemic is, without any doubt, changing our world in ways that are beyond our wildest imagination. In a bid to curb the spiraling negative fallouts from the virus that has resulted in a large number of casualties and security concerns. The World Health Organization, amongst other safety protocols, recommended the compulsory wearing of face masks by individuals in public spaces. The problem with the enforcement of this and other relevant safety protocols, all over the world, is the reluctance and outright refusal of citizens to comply and the inability of relevant agencies to monitor and enforce compliance. This paper explores the development of a CCTV–enabled facial mask recognition software that will facilitate the monitoring and enforcement of this protocol. Such models can be particularly useful for security purposes in checking if the disease transmission is being kept in check. A constructive research methodology was adopted, where a pre-trained deep convolutionary neural network (CNN) (mostly eyes and forehead regions) used and the most probable limit (MPL) was use for the classification process. The designed method uses two datasets to train in order to detect key facial features and apply a decision-making algorithm. Experimental findings on the Real-World-Masked-Face-Dataset indicate high success in recognition. A proof of concept as well as a development base are provided towards reducing the spread of COVID-19 by allowing people to validate the face mask via their webcam. We recommend that the use of the app and to further investigate the development of highly robust detectors by training a deep learning model with respect to specified face-feature categories or to correctly and incorrectly wear mask categories.
Pedagogical use of mobile technologies during Coronavirus school closure
Authors: Onyema Edeh Michael , Eucharia Ani Ukamaka , Gbenga Faluyi Samuel , Roselyn Akindutire Opeyemi , Daniel Omachi , Kingsley Nnaekwe Uchenna
Published: April 2021

The unplanned closure of schools due to Coronavirus Disease 2019 (COVID-19) left millions of students out of schools. However, the use of mobile technologies offered opportunities for educators and students to engage in remote pedagogical activities during the school closures. The study investigated the effects of the usage of mobile technologies on educators’ and students’ pedagogical activities during the COVID-19 school closure, and on the students’ attitudes towards pedagogical activities during the COVID-19 school closure. A total of 150 questionnaires were administered to participants that consist of educators and students from different levels of education in Nigeria. The samples were selected through simple random sampling technique, and collected data were analyzed using percentages, frequencies, and statistical methods of regression and ANOVA. The results show that the use of mobile technologies had statistically significant effects on the pedagogical activities of students and educators during the COVID-19 school closure, and on the attitudes of students towards pedagogical activities during the COID-19 school closure. Majority of the participants agreed that the use of mobile technologies such as: laptops, mobile phones, mobile apps, MP3, and other PDAs positively influenced their pedagogical activities during the COVID-19 school closure. The study concludes that mobile technologies have become an important and promising pedagogical tool which can be harnessed to enhance ubiquitousness and continued education during and after school closure or outbreak of pandemics.