bluuebunny/crossref_metadata_2025 huggingface dataset:
Emotional Intelligence and Occupational Stress Among Nursing Professionals in Tertiary Care Hospitals of Bangalore: A Multicentric, Cross-Sectional Study
Authors: Regy Minitta M. , Ramesh Naveen
Published: April 2024

Background:

Nursing profession requires strength and resilience not just physically, but emotionally as well which requires them to adapt in stressful situations that they are often exposed to in their work environment.

Objective:

To determine the prevalence and associated factors of emotional intelligence (EI) and occupational stress (OS) among the nursing professionals from selected tertiary care hospitals in Bangalore, India.

Methods:

This was a multi-centric, cross-sectional study done among nurses with more than 1year of work experience and they were randomly selected from four tertiary care hospitals in Bangalore. The EI and OS were assessed using the Emotional intelligence scale (EIS) and Occupational Stress Index (OSI). Data was collected, both online and offline, owing to the ongoing COVID-19 pandemic. The data was analyzed using SPSS v21.0 to calculate the mean, associations, and regression.

Results:

Out of the total 294, the mean age of the study participants was 27±4.92years. A total of 75 (25.5%) nurses had poor EI and 245 (83.3%) had moderate OSI. None of the participants had high OSI. There was a significant association between the severity grades of EI and OSI (P = 0.010) and a binary logistic regression showed that those staff with high EI had a lesser odd (OR 0.531, 95% CI 0.282-0.999) of developing occupational stress as compared to those with low EI.

Conclusion:

EI plays a significant role in reversing the effect of one’s occupational stress. Thereby, the training curriculum should include skills and measures of resilience to facilitate their EI improvement.
The Role of Silver Diamine Fluoride in Contemporary Dental Practice: A Comprehensive Review
Authors: Brar Anmol , Singh Abhay P. , Narad Chintan , Singh Ramandeep
Published: April 2024

ABSTRACT

Silver diamine fluoride (SDF) has garnered increasing attention in contemporary dental practice due to its unique properties and clinical applications. The minimally invasive nature, antimicrobial efficacy, and desensitization capabilities of SDF position it as a valuable tool in preventive and restorative dentistry. However, esthetic concerns associated with tooth discoloration and the need for further research to understand long-term outcomes underscore the importance of ongoing investigation and clinical integration. This article underscores the transformative potential of SDF in modern dental care and emphasizes the necessity of continued research and education to maximize its benefits.
Biomaterial engineering strategies for modeling the Bruch’s membrane in age-related macular degeneration
Authors: Molins Blanca , Rodríguez Andrea , Llorenç Víctor , Adán Alfredo
Published: April 2024

Age-related macular degeneration, a multifactorial inflammatory degenerative retinal disease, ranks as the leading cause of blindness in the elderly. Strikingly, there is a scarcity of curative therapies, especially for the atrophic advanced form of age-related macular degeneration, likely due to the lack of models able to fully recapitulate the native structure of the outer blood retinal barrier, the prime target tissue of age-related macular degeneration. Standard in vitro systems rely on 2D monocultures unable to adequately reproduce the structure and function of the outer blood retinal barrier, integrated by the dynamic interaction of the retinal pigment epithelium, the Bruch’s membrane, and the underlying choriocapillaris. The Bruch’s membrane provides structural and mechanical support and regulates the molecular trafficking in the outer blood retinal barrier, and therefore adequate Bruch’s membrane-mimics are key for the development of physiologically relevant models of the outer blood retinal barrier. In the last years, advances in the field of biomaterial engineering have provided novel approaches to mimic the Bruch’s membrane from a variety of materials. This review provides a discussion of the integrated properties and function of outer blood retinal barrier components in healthy and age-related macular degeneration status to understand the requirements to adequately fabricate Bruch’s membrane biomimetic systems. Then, we discuss novel materials and techniques to fabricate Bruch’s membrane-like scaffolds for age-related macular degeneration in vitro modeling, discussing their advantages and challenges with a special focus on the potential of Bruch’s membrane-like mimics based on decellularized tissue.
Selecting first-line advanced therapy for ulcerative colitis: A clinical application of personalized medicine
Authors: Mukhtar Mariam S. , Mosli Mahmoud H.
Published: April 2024

Ulcerative colitis (UC) is a chronic autoimmune inflammatory disease that affects the colon, leading to symptoms of bloody diarrhea, abdominal cramps, and urgency. The treatment of UC has evolved over the past few decades from locally active anti-inflammatory compounds to more selective therapies that target specific arrays of the immune system. The challenge of selecting the first advanced therapy became apparent in this rapidly expanding landscape of medications. No current investigational tools, such as genetic, immunologic, or biological markers, can guide the identification of the safest and most effective therapeutic option for each patient. Hence, physicians must carefully assess patient/disease characteristics and match them with the most suitable drug through a clinically driven assessment. In this paper, we outline patient and drug characteristics that play a role in selecting first-line advanced therapies for UC and propose an algorithm for selection.
Rate and Causes of 30-day Unplanned Readmission/Return Following Head and Neck Surgery at a Tertiary Care Center in Saudi Arabia
Authors: Merdad Mazin , Alqutub Abdulsalam , Mogharbel Ahmed , Alghamdi Abdullah A. , Alsulami Omar , Awadh Mohammed , Alsulami Ahmed S.
Published: April 2024

Background:

Identifying and targeting common preventable causes of 30-day hospital readmissions could help improve survival rates and reduce the healthcare burden.

Objective:

To determine the rate and causes of unplanned hospital return/readmission to the Outpatient Department (OPD) or Emergency Department (ED) within 30 days after discharge following head and neck surgery (HNS) at a tertiary hospital in Western Saudi Arabia.

Methods:

This retrospective study included all adult patients (aged ≥18 years) who had undergone HNS at King Abdulaziz University Hospital, Jeddah, Saudi Arabia, between January 2015 and December 2022 and returned to the OPD or ED within 30 days of being discharged.

Results:

Of 1041 patients who had undergone HNS, 84 (8.1%) returned to the hospital within 30 days after discharge: 63 (6.1%) to the OPD and 21 (2.0%) to the ED. A total of 9 (0.9%) patients were readmitted as inpatients, most commonly for infections (33.3%) and neurological symptoms, including weakness and seizures (22.2%). For OPD visits, common causes were wound swelling (25.4%) and neurological symptoms (17.5%). For ED returns, frequent causes were neurological symptoms (23.8%) and surgical site bleeding (19.1%). Readmission was associated with intensive care unit (ICU) admission during the primary hospital stay (P = 0.003) and higher preoperative baseline health burdens when examined using the American Society of Anesthesiology score (P = 0.022), the Cumulative Illness Rating Scale (P = 0.007), and the Charlson Comorbidity Index (CCI) (P = 0.006).

Conclusion:

The rate of 30-day unplanned hospital return following head and neck surgery was 6.1% and 2.0% through the OPD and the ED, respectively; 0.9% were readmitted as inpatients. Common causes of return included wound swelling, infections, bleeding, and neurological symptoms.
Prescribing Trends of Renin-Angiotensin System Inhibitors and Mortality among Acute Coronary Syndrome Patients: Insights from the Malaysian National Cardiovascular Disease Registry
Authors: Suki Siti Zaleha , Zuhdi Ahmad Syadi Mahmood , Yahya Abqariyah , Adnan Wan Ahmad Hafiz Wan Md , Zaharan Nur Lisa
Published: April 2024

Background:

Despite guideline recommendations, suboptimal prescription rates of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) have been observed in patients with acute coronary syndrome.

Objective:

This study aimed to examine the temporal trends, variations, and mortality outcomes among acute coronary syndrome patients prescribed ACEIs/ARBs in the multi-ethnic population of Malaysia.

Methodology:

This retrospective study utilized data from the Malaysian National Cardiovascular Disease–Acute Coronary Syndrome registry, encompassing consecutive patient records from 2008 to 2017 (N = 60,854). Ten-year temporal trends of on-discharge ACEIs/ARBs prescription were examined. Demographics, clinical characteristics and 1-year all-cause mortality outcomes were compared between patients prescribed and not prescribed ACEIs/ARBs.

Results:

The 10-year prescription rate of on-discharge ACEIs/ARBs was 52.8% (n = 32,140), with a significant decline over the years [linear trend test, P = 0.008; SD = 0.03; SE = 0.001; 95% CI = 0.55-0.64]. Patients aged ≥65 years (aOR = 0.79; 95% CI = 0.73–0.86) were less likely to be prescribed ACEIs/ARBs than those aged <65 years. In addition, patients with comorbid diabetes mellitus (DM) (aOR = 0.85; 95% CI = 0.79–0.92) and chronic kidney disease (CKD) (aOR = 0.34; 95% CI = 0.30–0.40) were significantly less likely to receive ACEIs/ARBs. IPW-adjusted survival analysis revealed a 38% lower 1-year all-cause mortality rate in patients prescribed on-discharge ACEIs/ARBs (HR = 0.62; 95% CI = 0.56–0.69; P < 0.001).

Conclusion:

Acute coronary syndrome patients with concomitant DM and CKD were less likely to receive on-discharge ACEIs/ARBs in Malaysia. Suboptimal prescription rates of ACEIs/ARBs persisted over the 10-year period, despite improved 1-year survival in ACS patients prescribed ACEIs/ARBs.
Impact of Privatization on Healthcare System: A Systematic Review
Authors: Alayed Tareq M. , Alrumeh Assem S. , Alkanhal Ibrahim A. , Alhuthil Raghad T.
Published: April 2024

Background:

A notable shift in healthcare policy is healthcare privatization, which refers to the transfer of ownership, management, or provision of healthcare services from the public sector to private entities.

Objectives:

To provide a narrative examination of the impact of privatization on various dimensions of healthcare, including quality, equity, accessibility, and cost-effectiveness. Policymakers can utilize the findings of this study to make well-informed decisions regarding privatization strategies.

Materials and Methods:

A systematic review was implemented using the following databases: PubMed, Scopus, and Google Scholar. Studies conducted from January 2000 to January 2023 in developing or developed countries that assessed the impact of healthcare privatization on population health within public sector institutions were included.

Results:

Eleven studies were included. The findings revealed diverse perspectives on the impact of healthcare privatization, with four studies (36.4%) supporting privatization (two of these were conducted in Saudi Arabia), six studies (54.5%) opposing it (three of these were conducted in European countries), and one study (9.1%) taking a neutral stance. Two studies investigated the impact on healthcare quality, and both revealed that privatization negatively impacts uninsured patients and low-income populations. In addition, five studies investigated the healthcare access and equity dimensions following privatization: one was in favor, one was neutral, and three were opposing it. Four studies investigated the cost-effectiveness dimension, with three in favor and one study opposing it.

Conclusion:

This review highlights different perspectives on healthcare privatization. While studies, as those from Saudi Arabia, suggest benefits in terms of efficiency and innovation, others, particularly from European countries, emphasize negative consequences such as inequity and reduced quality. This emphasizes the need for more investigations to understand privatization’s impact on healthcare.
Exploring Mental Fatigue and Burnout in the Workplace: A Survival Analysis Approach
Authors: Eswar Reddy R , K Santhi
Published: April 2024

INTRODUCTION: Employee burnout is a prevalent concern in contemporary workplaces, adversely impacting both individual well-being and organizational productivity.
OBJECTIVES:  In this paper, we conducted a comprehensive analysis of a dataset focusing on mental fatigue and burnout among employees, employing various survival analysis techniques including Kaplan Meier, Nelson-Aalen, and Cox proportional-hazards models, as well as Frailty Models and Competing Risks Analysis.
METHODS:  This research underscored significant associations between mental fatigue, burnout, and adverse outcomes, emphasizing the critical need for early identification and intervention. Kaplan Meier analysis revealed differences in survival probabilities, while Nelson-Aalen analysis depicted cumulative hazard functions over time. Cox proportional-hazards models identified mental fatigue and burnout as significant predictors of adverse events, supported by Frailty Models accounting for individual-level variability. Additionally, Competing Risks Analysis elucidated the simultaneous occurrence of multiple adverse events among employees experiencing burnout.
RESULTS: This research underscored significant associations between mental fatigue, burnout, and adverse outcomes, emphasizing the critical need for early identification and intervention. Kaplan Meier analysis revealed differences in survival probabilities, while Nelson-Aalen analysis depicted cumulative hazard functions over time. Cox proportional-hazards models identified mental fatigue and burnout as significant predictors of adverse events, supported by Frailty Models accounting for individual-level variability. Additionally, Competing Risks Analysis elucidated the simultaneous occurrence of multiple adverse events among employees experiencing burnout.
CONCLUSION: This study contributes valuable insights into understanding and addressing mental fatigue in the workplace, highlighting the importance of evidence-based interventions to support employee well-being and organizational resilience. The insights gained from this analysis inform evidence-based strategies for mitigating burnout-related risks and promoting a healthier work environment.
The Digital Transformation of College English Classroom: Application of Artificial Intelligence and Data Science
Authors: Yanling Li
Published: April 2024

A major step forward in educational technology is the application of Data Science additionally Artificial Intelligence (AI) into undergraduate English courses. Improving teaching approaches and student involvement in the context of English language acquisition is an important issue that this study seeks to address. Even though there have been great strides in educational technology, conventional English classes still have a hard time meeting the demands of their different student bodies and offering individualized lessons. This is a major problem that prevents English language training from being effective, according to the material that is already available. In this study, we provide an approach to this issue called English Smart Classroom Teaching with the Internet of Things (ESCT-IoT). Utilizing data science techniques, artificial intelligence (AI) algorithms, and Internet of Things (IoT) sensors, ESCT-IoT intends to provide a personalized learning environment that is both immersive and adaptable. The fuzzy hierarchical evaluation technique is used to determine the assessment's final result, which measures the smart classroom's instructional impact. To overcome the limitations of conventional education, ESCT-IoT gathers and analyses data in real time to give adaptive material, individualized feedback, and learning suggestions. There are noticeable benefits as compared to traditional methods of instruction when it comes to evaluation metrics like student engagement, learning outcomes, and teacher satisfaction. Furthermore, ESCT-IoT is excellent in encouraging active learning, improving language fluency, and boosting overall academic achievement, according to qualitative comments from both students and teachers.
Commensurating HNN-extensions: Hierarchical hyperbolicity and biautomaticity
Authors: Hughes Sam , Valiunas Motiejus
Published: April 2024

We construct a

\mathrm{CAT}(0)

hierarchically hyperbolic group (HHG) acting geometrically on the product of a hyperbolic plane and a locally-finite tree which is not biautomatic. This gives the first example of an HHG which is not biautomatic, the first example of a non-biautomatic

\mathrm{CAT}(0)

group of flat-rank

2

, and the first example of an HHG which is injective but not Helly. Our proofs heavily utilise the space of geodesic currents for a hyperbolic surface.
Mechanical response and energy absorption characteristics of origami-inspired honeycomb under quasi-static compression and dynamic impact
Authors: Wu Pengjiang , Wu Chunfu , Ye Guorui , Zhao Yonghong , Ye Baowen , Wang Liangmo , Wang Tao , Zhang Zeming
Published: April 2024

The origami structures have received increasing attention in recent years due to the high stiffness ratio and lightweight feature. This paper has proposed an origami-based honeycomb structure and investigated the mechanical properties of the structure. The compression response and energy absorption of the structure under quasi-static loading have been investigated experimentally and numerically. The numerical results closely matched the experimental results in terms of the compression force curve and deformation patterns. The effects of different structural parameters on the mechanical response and energy absorption characteristics were analyzed with the validated model. Finally, the comparative results show that the origami-inspired honeycomb structure, which is characterized by rotational folding mode under axial compression, has better performance in terms of mechanical response and energy absorption. Two parameters, the thickness and the height have a greater influence on the structural performance, and the angle of rotation has a lesser influence. This structure can have a better application prospect in the energy-absorbing box, B-pillar, door sill beam and other parts of the car.
Enhancement of Physical and Mechanical Attributes of a Natural Fiber-Reinforced Composite for Engineering Applications
Authors: Karthika M R , Deb Anindya , Arockiasamy Madasamy
Published: April 2024

A natural fiber based polymer composite has the advantage of being more environment-friendly from a life cycle standpoint when compared to composites reinforced with widely-used synthetic fibers. The former category of composites also poses reduced health risks during handling, formulation and usage. In the current study, jute polymer laminates are studied, with the polymeric resin being a general purpose polyester applied layer-by-layer on bi-directionally woven jute plies. Fabrication of flat laminates following the hand layup method combined with compression molding yields a jute polymer composite of higher initial stiffness and tensile strength, compared to commonly used plastics, coupled with consistency for engineering design applications. However, the weight-saving potential of a lightweight material such as the current jute-polyester composite can be further enhanced through improvement of its behavior under mechanical loading. A weakness of a natural fiber reinforced composite is its propensity for moisture absorption which can lead to a substantial degradation in its stiffness and strength. In the current study, it is shown that addition of a limited number of plies of a lightweight metal such as an aluminum alloy in a meshed state can lead to substantive improvement in its physical and mechanical properties such as a 7.4% drop in mass for same surface area, a 57% increase in tensile modulus and a 12% rise in tensile strength. A noticeable enhancement in hygroscopic response of the hybrid jute composite has also been found in the moisture-absorption study that was carried out. It is noted that the hybrid jute-aluminum laminate investigated here has not been reported earlier in published literature. The current strategy of hybridization can be potentially extended to a wider class of natural fiber reinforced polymeric composites.
Durability of Elastomeric Bushings Computed from Track-Recorded Multi-Channel Road Load Input
Authors: Mars William , Barbash Kevin , Wieczorek Matthew , Braddock Scott , Goossens Joshua , Steiner Ethan
Published: April 2024

The qualification requirements of automakers derive from track testing in which road load and moment inputs to a part in x, y and z directions are recorded over a set of driving conditions selected to represent typical operation. Because recorded histories are lengthy, often comprising many millions of time steps, past industry practice has been to specify simplified block cycle schedules for purposes of durability testing or analysis. Simplification, however, depends on imprecise human judgement, and risks fidelity of the inferred life and failure mode relative to actual. Fortunately, virtual methods for fatigue life prediction are available that are capable of processing full, real-time, multiaxial road load histories. Two examples of filled natural rubber ride bushings are considered here to demonstrate. Each bushing is subject to a schedule of 11 distinct recorded track events. Endurica EIETM map building procedures are first used together with a finite element solution to map the 6 channel loading space and to obtain stress/strain solutions at each gridpoint in the load space. EIE is then used with the recorded histories to interpolate from the recorded road load inputs on the bushing to stress-strain history at each element centroid in the finite element model. The interpolated stress-strain histories are then used to compute damage accrual and fatigue life across all 11 events. The computational requirements of this workflow are benchmarked with the outcome that the entire schedule in full detail can be analyzed on a timescale well suited for use at the earliest stages of business development and engineering.
Research on the Control Strategy of Electric Vehicle Active Suspension Based on Fuzzy Theory
Authors: Jing Li Jing
Published: April 2024

The performance of suspension system has a direct impact on the riding comfort and smoothness. For the traditional suspension can not effectively alleviate the impact of road surface and the poor anti-vibration performance, The dynamics model of vehicle suspension system is established, and the control model of vehicle four-degree-of-freedom active suspension is designed with fuzzy control strategy. On this basis, a comprehensive simulation model of the control model of vehicle active suspension coupled with road excitation is established. and the ride comfort of vehicles under different types of suspension are tested through Simulink. The simulation results show that compared with the passive suspension, the reduction of vehicle acceleration and dynamic deformation of the active suspension controlled by fuzzy PID can reach 33.76% and 22.45%. and the reduction of pitch Angle speed and dynamic load of the active suspension controlled by fuzzy PID can reach 16.18% and 10.72%. Under fuzzy PID control, the amplitude of each evaluation index of active suspension in the suspension system is substantially reduced than that of the passive suspension, and the root-mean-square value decreases by about 10% on average. It can be seen that the active suspension with fuzzy PID control can improve the performance of the suspension system on the basis of ensuring the stability and rapid response of the system, and can well reduce the random vibration caused by the impact of the vehicle on the random road surface during the driving process, improve the ride comfort, smoothness and ride safety of the vehicle, and achieve a good control effect on the vehicle suspension.
Analysis of Intrinsic Characteristics and Dynamic Response of New Energy Vehicle Battery Pack System
Authors: Guo Yi Ming , Shao Xiaowei , Xiao Lei , Li GuoHong , Shangguan Wen-Bin
Published: April 2024

As the main power source of new energy vehicles, the durability and fatigue characteristics of the battery pack directly affect the performance of the vehicle. The battery pack system was modelled using multi-body dynamics software, with 7 and 13 degree of freedom models developed. Using the established model, the intrinsic properties of the battery pack are computationally analyzed. To calculate the dynamic characteristics, a sinusoidal displacement excitation is applied to the wheel centre of mass, and the displacement and acceleration of the battery pack centre of mass are calculated for both models.The displacement and acceleration curves at the centre of mass of the battery pack of the two models are compared. The results show that the amplitude of the displacement and acceleration curves at the centre of mass of the 13 degrees of freedom model of the battery pack has decreased significantly.
Study on Aircraft Wing Collision Avoidance through Vision-Based Trajectory Prediction
Authors: Zhu Hengjia , Xu Yitong , Xu ZiShuo , JiYuan Liu , Zhang Wei
Published: April 2024

When the aircraft towing operations are carried out in narrow areas such as the hangars or parking aprons, it has a high safety risk for aircraft that the wingtips may collide with the surrounding aircraft or the airport facility. A real-time trajectory prediction method for the towbarless aircraft taxiing system (TLATS) is proposed to evaluate the collision risk based on image recognition. The Yolov7 module is utilized to detect objects and extract the corresponding features. By obtaining information about the configuration of the airplane wing and obstacles in a narrow region, a Long Short-Term Memory (LSTM) encoder-decoder model is utilized to predict future motion trends. In addition, a video dataset containing the motions of various airplane wings in real traction scenarios is constructed for training and testing. Compared with the conventional methods, the proposed method combines image recognition and trajectory prediction methods to describe the relative positional relationship between the wings and obstacles, which enhances the accuracy of aircraft wing collision prediction during aircraft towing operations.
Virtual Methodology for Active Force Cancellation in Automotive Application Using Mass Imbalance & Centrifugal Force Generation (CFG) Principle
Authors: Paul Abhishek , Latcha Michael
Published: April 2024

A variety of structures resonate when they are excited by external forces at, or near, their natural frequencies. This can lead to high deformation which may cause damage to the integrity of the structure. There have been many applications of external devices to dampen the effects of this excitation, such as tuned mass dampers or both semi-active and active dampers, which have been implemented in buildings, bridges, and other large structures. One of the active cancellation methods uses centrifugal forces generated by the rotation of an unbalanced mass. These forces help to counter the external excitation force coming into the structure. This research focuses on active force cancellation using centrifugal forces (CFG) due to mass imbalance and provides a virtual solution to simulate and predict the forces required to cancel external excitation to an automotive structure. This research tries to address the challenges to miniaturize the CFG model for a body-on-frame truck. The virtual tool presented in this paper will help predict the maximum amplitude cancellation at resonance for given imbalance mass and frequency of forced excitation.
Sound Transmission Loss through Front of Dash and Instrumental Panel
Authors: Yang Wenlong , Hamilton Jamie , Yin Gang , Gordon Kara
Published: April 2024

The subsystem of front of dash (FOD) and instrument panel (IP) is a critical path to isolate the powertrain noise and road noise for vehicles. This subsystem mainly consists of sheet metal, dash mats, IP, and the components inside IP such as HVAC and wiring harness. To achieve certain level of cabin quietness, the sound transmission loss performance of this subsystem is usually used as a quantifier. In this paper, the sound transmission loss through the FOD and IP is investigated up to 10kHz, through both acoustic testing and numerical simulation. In the acoustic testing, the subsystem is cut from a vehicle and installed on the wall of two-rooms STL testing suite, with source room being reverberant and receiver room being anechoic. In the testing, various scenarios are measured to understand the contributions from different components. The numerical simulation is based on statistical energy analysis (SEA) because deterministic methods have difficulty to predict the STL up to 10k Hz due to problem size. Good correlations are obtained for all the scenarios. From the investigation, the contribution from different components to the overall STL performance is evaluated and ranked. Taking advantage of the correlated numerical models, design changes which are not feasible or easy to be measured are studied. As an example, in the “virtual” design changes related to the IP components, the influence from IP skin and leakages are checked.
Experimental Investigation of Internal and External EGR Effects on a CNG-OME Dual-Fuel Engine
Authors: Jost Ann-Kathrin , Guenthner Michael , Weigel Alexander
Published: April 2024

Dual-fuel engines powered by renewable fuels provide a potential solution for reducing the carbon footprint and emissions of transportation, contributing to the goal of achieving sustainable mobility. The investigation presented in the following uses a dual-fuel engine concept running on biogas (referred to as CNG in this paper) and the e-fuel polyoxymethylene dimethyl ether (OME). The current study focuses on the effects of exhaust gas rebreathing and external exhaust gas recirculation (EGR) on emissions and brake thermal efficiency (BTE).

A four-cylinder heavy-duty engine converted to dual-fuel operation was used to conduct the engine tests at a load point of 1600 min-1 and 9.8 bar brake mean effective pressure (BMEP). The respective shares of high reactivity fuel (HRF, here: OME) and low reactivity fuel (LRF, here: CNG) were varied, as were the external and internal EGR rates and their combinations. CNG was injected into the intake manifold to create a homogeneous air-fuel mixture, while OME was introduced as a pilot injection directly into the combustion chamber. Results showed an increase in total hydrocarbons (THC) and carbon monoxide (CO) emissions, while nitric oxide (NOx) emissions were significantly reduced compared to diesel operation. Soot emissions were completely mitigated due to the absence of direct carbon bonds in both CNG and OME. For the initial stage of the study, exhaust gas rebreathing was implemented on only one exhaust valve through a second event lift. For the second part of the study, the second event lift was also installed on the other exhaust valve. At a substitution rate of 50 % CNG, THC emissions could be lowered by up to 35 %, CO emissions by up to 50 % and NOx emissions by up to 18 % with the use of internal EGR. The combination of internal and external EGR reduced emissions even further.
A Study on Optimizing Headlining Open-Structure for Face-to-Face Roof-Airbag Deployment
Authors: Park Jiseob
Published: April 2024

In this study, an optimized structure for opening the headlining considering the deployment of the face-to-face roof airbag was studied. It was confirmed that the deployment performance differs depending on the skin of the headlining, and a standardized structure with mass production was proposed.

Non-woven fabric and Tricot skin, which are economical and high-end specifications, satisfy the performance of PVC fusion application specifications after cutting 80% of the skin. The structure that satisfies the entire body including the knit specifications is a type that separates the roof airbag area piece, the corresponding soft piece is separated, and the deployment performance is satisfied with safety. Therefore, the structure is proposed as a standardized structure.

This structure is expected to be applicable to roof DAB (Driver Airbag), PAB (Passenger Airbag), and Sunroof Airbag, which will be necessary technologies to secure indoor space. Regardless of which area the airbag will be applied to, and which area the headlining skin specifications will be selected by the customer, it can be applied only if the mounting bracket conditions are satisfied. A patent will be applied for the structure to secure intellectual property rights.
Do Drivers Pay Attention during Highway-Based Automated Lane Changes while Operating under Hands-Free Partially Automated Driving?
Authors: Llaneras Robert , Glaser Daniel , Glaser Yi
Published: April 2024

This study assessed a driver’s ability to safely manage Super Cruise lane changes, both driver commanded (Lane Change on Demand, LCoD) and system triggered Automatic Lane Changes (ALC). Data was gathered under naturalistic conditions on public roads in the Washington, D.C. area with 12 drivers each of whom were provided with a Super Cruise equipped study vehicle over a 10-day exposure period. Drivers were shown how to operate Super Cruise (e.g., system displays, how to activate and disengage, etc.) and provided opportunities to initiate and experience commanded lane changes (LCoD), including how to override the system. Overall, drivers experienced 698 attempted Super Cruise lane changes, 510 Automatic and 188 commanded LCoD lane changes with drivers experiencing an average of 43 Automatic lane changes and 16 LCoD lane changes. Analyses characterized driver interactions during LCoD and ALC maneuvers exploring the extent to which drivers actively monitor the process and remain engaged and alert relative to manually executed lane changes (e.g., mirror checks, interventions, etc.). Results found evidence to suggest that drivers remain vigilant during Super Cruise automated lane changes, both when driver commanded LCOD (LCoD) and when executed automatically. Further, search behavior persisted over time and with experience; drivers were observed to search mirrors or make direct Over-the-Shoulder glances for nearly all executed lane changes, both under Super Cruise or Manual driving modes. No significant differences were found regarding either the duration or number of check glances across Super Cruise or manually executed lane changes. While drivers remained attentive during lane changes operating under a partial automated driving system, additional longer-term studies may be helpful to reinforce these findings that these safety behaviors persist after significant experience and usage.
Image-Based Driver Status Monitoring System for Determining the Transfer of Dynamic Driving Tasks in Autonomous Vehicles
Authors: Su Yi-Feng , Hsu Chih-Yuan , Wang Yu-Chieh , Yeh Chung-Yu
Published: April 2024

Autonomous driving technology has advanced significantly in recent years, thanks to the innovations in vehicle design and artificial intelligence. This technology provides a more convenient and comfortable driving experience for both drivers and passengers. However, current autonomous driving systems still face some difficulties, such as the need for human intervention in critical situations. Switching control from the system to the driver without assessing their alertness or health status could pose a risk. Therefore, autonomous driving systems should be able to monitor and evaluate the driver's condition before handing over the control. This paper thus proposes an in-cabin detection system that monitors driver status using a camera. The system consists of software modules that use deep learning techniques to analyze the input from an IR camera. The modules include face detection, head pose estimation, eye state detection, and gaze estimation, which are used to evaluate the driver's condition. The system runs on an edge computing platform, with an average processing speed of about 10 FPS, 99% accuracy for driver availability detection, about 100% accuracy for driver unavailability detection and 100% warning rate for driver presence. The detection results are displayed visually on screen and applied to the testing of self-driving electric bus. It allows the vehicle to perform conditional autonomous driving, which is Level 3. This means that the system can assume the responsibility of driving the vehicle and comply with the UN R157 regulations that require the driver to be present and ready to intervene.
Understand Driving Behaviors Based on Comprehensive Grading System and Unsupervised Learning
Authors: Guo Bin , Hansen John
Published: April 2024

Understanding driving behavior is crucial for enhancing traffic safety. While previous studies have primarily explored driving behavior using either statistical or machine learning methods, comprehensive assessments employing both methods under various driving mode are limited. In this study, we employ both machine learning and statistical approaches to model driving behavior. First, we design a comprehensive driver grading system to assess the behavior of drivers under different driving modes. Additionally, we present an extended isolation forest-based model to classify driving behavior using data without labels, saving time and effort. Results illustrate that safe driving is more consistent and stable, while aggressive driving exhibits more intensive changes. They also demonstrate that drivers can exhibit various behaviors under different modes, serving as a benchmark for further driver modeling.
Thermal Management System Test Bench for Electric Vehicle Technology
Authors: Wray Alex , Dutta Nilabza , Ebrahimi Kambiz , Watson Andrew
Published: April 2024

The importance of designing and sizing a thermal management system for electric vehicle powertrains cannot be overstated. Traditional approaches often rely on model-based system design using supplier reference component data, which can inadvertently lead to undisclosed errors arising from the interactions between the components and the environment. This paper introduces a novel test facility for battery electric vehicle thermal management technology, which has been designed for neural network virtual sensor and non-linear multi-in multi-out control development. The paper demonstrates how a digital twin of the test bench can used to support the development of such technology. Additionally, this paper presents preliminary results from the test bench revealing insights into the performance and interactions of key components. For instance, there is an observed 30% reduction in the maximum flow rate of the pump integrated into the test bench compared to the specified value. Furthermore, the interactions between the pump and valve resulted in a non-linear flow rate response which is essential knowledge prior to developing new multi-in multi-out control strategies.
Sequence Training and Data Shuffling to Enhance the Accuracy of Recurrent Neural Network Based Battery Voltage Models
Authors: Chen Junran , Kollmeyer Phillip , Panchal Satyam , Masoudi Yasaman , Gross Oliver , Emadi Ali
Published: April 2024

Battery terminal voltage modelling is crucial for various applications, including electric vehicles, renewable energy systems, and portable electronics. Terminal voltage models are used to determine how a battery will respond under load and can be used to calculate run-time, power capability, and heat generation and as a component of state estimation approaches, such as for state of charge. Previous studies have shown better voltage modelling accuracy for long short-term memory (LSTM) recurrent neural networks than other traditional methods (e.g., equivalent circuit and electrochemical models). This study presents two new approaches – sequence training and data shuffling – to improve LSTM battery voltage models further, making them an even better candidate for the high-accuracy modelling of lithium-ion batteries. Because the LSTM memory captures information from past time steps, it must typically be trained using one series of continuous data. Instead, the proposed sequence training approach feeds a fixed window of prior data (e.g., 100 seconds) into the LSTM at each time step to initialize the memory states properly and then only uses the output at the current time step. With this method, the LSTM just requires the prior data window to be continuous, thereby allowing the handling of discontinuities. This also means that during the training process, the data can be shuffled randomly, enabling mini-batches to speed up the training significantly. When these approaches were applied, LSTM voltage estimation error was reduced by 22%, from 28.5 mV to 22.3 mV RMS error over four drive cycles and temperatures from -20 to 25°C.
Lightweight Composite Rear Under Run Protection Device (RUPD) for ILCV & MHCV Trucks
Authors: Srivastava Sanjay , Sonkusare Shailesh
Published: April 2024

As the automotive industry focuses on fuel-efficient and eco-friendly vehicles along with reducing the carbon footprint, weight reduction becomes essential. Composite materials offer several advantages over metals, including lighter weight, corrosion resistance, low maintenance, longer lifespan, and the ability to customize their strength and stiffness according to specific loading requirements. This paper describes the design and development of the Rear Under Run Protection Device (RUPD) using composite materials. RUPD is designed to prevent rear under-running of passenger vehicles by heavy-duty trucks in the event of a crash. The structural strength and integrity of RUPD assembly are evaluated by applying loads and constraints in accordance with IS 14812:2005. The design objective was to reduce weight while maintaining a balance between strength, stiffness, weight, manufacturability, and cost. The process involved detailed laminate design, finite element analysis, and optimization using Altair Radioss and OptiStruct solvers. The layup configuration was designed to apply the pultrusion manufacturing process to it, which is well-suited for applications requiring a constant cross-section and high production rates. This technique offers a more efficient and cost-effective solution. Pultruded laminates are created by aligning rovings along the major axis of the component, while different continuous strand mats and fabrics are used to provide strength in the cross or transverse direction. The coupon tests were performed on various layup configurations to characterize the material in different directions for failure analysis material models. The design undergoes validation and optimization through quasi-static analysis, considering all load cases according to the standard. After finalizing the design through simulation, a final prototype was made based on the final laminate thickness, and the component was manufactured using the pultrusion manufacturing process. As a result, the weight of the newly designed RUPD was reduced by 25% compared to the previous metal component.
Economic Analysis of Online DC-Drive System for Long Distance Heavy-Duty Transport Vehicle Incorporating Multi-Factor Sensitivities
Authors: Zhou Wenbo , Bi Gaoxin , Wang Yuhai , Zhao Jian
Published: April 2024

Currently, the rapid expansion of the global road transport industry and the imperative to reduce carbon emissions are propelling the advancement of electrified highways (EH). In order to conduct a comprehensive economic analysis of EH, it is crucial to develop a detailed /8.and comprehensive economic model that takes into account various transportation modes and factors that influence the economy. However, the existing economic models for EH lack comprehensiveness in terms of considering different transportation modes and economic factors. This study aims to fill this gap by designing an economic model for an EH-based Online DC-driven system (ODS) for long distance heavy-duty transport vehicle incorporating multi-factor sensitivities. Firstly, the performance parameters of the key components of the system are calculated using vehicle dynamics equations which involves selecting and matching the relevant components and determining the fundamental cost of vehicle transformation. Secondly, the system economic model is established by considering two operation modes of ODS: integrated operation-construction mode and separated operation-construction mode as well as two transportation scenarios: one-way full load and two-way full load. Finally, the optimal road construction plan for the road is determined, and the sensitivity of the payback period to various parameters is analyzed. The findings of the analysis reveal that the optimal road construction plan entails the construction of 10MW and 14MW traction substations under the one-way full load and two-way full load scenarios, respectively. The estimated investment cost for road construction is 316 million RMB and 320.8 million yuan, respectively. Moreover, ODS exhibits significant improvements in economics for both investors and drivers, resulting in a substantial reduction in the payback period.
What the Flicker Is Going on Here? Temporal Light Modulation in Automotive Lighting
Authors: Miller Naomi , Irvin Lia
Published: April 2024

Temporal light modulation (TLM), colloquially known as “flicker,” is an issue in almost all lighting applications, due to widespread adoption of LED and OLED sources and their driving electronics. A subset of LED/OLED lighting systems delivers problematic TLM, often in specific types of residential, commercial, outdoor, and vehicular lighting. Dashboard displays, touchscreens, marker lights, taillights, daytime running lights (DRL), interior lighting, etc. frequently use pulse width modulation (PWM) circuits to achieve different luminances for different times of day and users’ visual adaptation levels. The resulting TLM waveforms and viewing conditions can result in distraction and disorientation, nausea, cognitive effects, and serious health consequences in some populations, occurring with or without the driver, passenger, or pedestrian consciously “seeing” the flicker. There are three visual responses to TLM: direct flicker, the stroboscopic effect, and phantom array effect (also called the “beads effect”). Metrics for the first two have limitations in both calculation and application. The phantom array effect has no established visibility measure at all, and this is the effect most associated with vehicular flicker because of the viewing conditions and frequency, plus the widespread use of PWM. Conventional wisdom from the recent past, especially concerning acceptable driver frequency ranges, needs to be reconsidered and replaced with improved guidelines to protect health and comfort. Four principal TLM waveform characteristics affect TLM visibility: frequency, modulation depth, duty cycle, and waveshape. This paper proposes much higher frequency operation if PWM control cannot be avoided; but it may be possible to modify the four principal waveform characteristics together to achieve reduced TLM visibility and improved health and comfort.