bluuebunny/crossref_metadata_2025 huggingface dataset:
Growing Through Change
Authors: Yusop Farrah Dina , Kutty Vijaya Sooria Sangaran , Ramayan Srikumar K. , Gunaseelan Vanieswari
Published: April 2024

This chapter explores Blendspace as a digital teaching and learning tool, its benefits and setbacks, ways to use it, and provides a guide on how to use it. Blendspace.com (now known as TES Teach) is the online educational curriculum tool of TES.com. Blendspace is a web-based learning tool developed and used to gather and package information for teaching and learning purposes. This digital platform is open to non-technical teachers and students from all levels, grades, and subject areas. Blendspace enables teachers to enter the classroom in a seamless, or what can be considered a “hybrid,” manner efficiently and effectively. Correspondingly, Blendspace allows students to create interactive content to showcase their work related to the subject matter. As a content curation platform, students can build interactive content such as storyboards, scrapbooks, and vlogs, among others. Additionally, due to its affordances, teachers can access a range of tools and create immersive lessons by blending digital content with in-class experiences. Blendspace is an alternative digital platform that offers many possibilities for the creation of digital content in one place, the design of fun and interactive lessons, and the monitoring and assessment of student learning through the use of quizzes and discussions. The chapter ends with a sample hands-on activity using Blendspace.
Revisiting Merrill's First Principle of Instruction
Authors: Fuzi Mimi Zairul Mohmad , Yahaya Wan Ahmad Jaafar Wan
Published: April 2024

A problem-solving method known as computational thinking (CT) has been described as a 21st-century skill that all students should learn in preparation for increasingly automated jobs in the future. However, little instructional design approach is available to guide educators and designers when designing mobile learning applications to support CT skills learning and implementation. This study addresses the above issue by revisiting Merrill's first principle of instructional model (FPI) with the CT technique and describing how the proposed CT-FPI instructional design can be used in designing mobile learning applications for problem-solving learning. The decomposition technique, a component of computational thinking, involves breaking down complex problems into smaller, manageable parts. Future studies for this research will contribute valuable insights to the field of instructional design in developing learning aids for mobile applications that promote the CT-decomposition technique for problem analysis in learners.
Reflections of the Ukraine-Russia War on World Trade and Supply Chain and Examination of Its Effects on Turkey
Authors: Fidanoğlu Ahmet , Değirmenci Bekir
Published: April 2024

Russia launched the Russia-Ukraine war by launching an armed attack on Ukraine on February 24, 2022. In response to international attacks on Ukraine, serious sanctions were imposed on Russia. Although the imposed sanctions targeted the Russian economy, they deeply affected the whole world, especially Europe, with the disruption of the global supply chain. This war caused an increase in energy, commodity, and food prices as well as increased inflation in many countries. In this study, the effects of the Russia-Ukraine war on Turkey's imports, exports, and supply chains were revealed through literature review. Extreme increases in commodity prices due to the war damaged the purchasing power of households. On the other hand, with Turkey's important role in the supply chain and its role as an intermediary in both trade and logistics sectors in Russia, the importance of Turkey during this war period was better understood by the countries in the region.
Consumer Preferences Toward Socially Responsible Investments in Germany
Authors: Tariq Waqas , Ashfaq Muhammad , Tariq Adeel , Ali Muhammad
Published: April 2024

The chapter aims to study consumer perceptions and preferences toward socially responsible investments (SRIs) offered by the financial institutions from nine major cities in Germany based on perceived religiosity, age, and educational level. Analysis of variance and principal component analysis of a sample of 342 respondents in the 18-60 age group revealed that Muslims are likely to be more conscious than Christians and Jewish towards SRIs. The study also finds that higher education, knowledge, and awareness of the consumers have a positive effect on their preferences in using services of financial institutions while age is not the main factor in the adoption of SRIs. The findings of the study are important for financial institutions, especially for those offering socially responsible investments. Financial institutions can better offer their products and services by understanding the perceptions of consumers and therefore, better position themselves in changing market dynamics.
Emotional Facets of Car Driving Experience and Purchase Decision Making
Authors: Mahdavi Mehdi , Barbosa Belem , Graham John L.
Published: April 2024

The present chapter aims to map the extant literature on the consequential role of human emotions in car driving experience and purchase decision making. To this end, bibliometric analysis of 274 Scopus-indexed documents published between 1981-2023 shows that the United States share of the published documents is the highest among all the contributing countries. In addition, the journals Accident Analysis and Prevention and Transportation research Part F: Traffic Psychology and Behavior, are two major publishers of the pertinent articles. Although few substantial contributions are noticeable from “marketing” related journals, one paper published in the Journal of Marketing has received the highest number of citations. The findings also reveal that virtually all the three components of emotion, i.e., experiential, physiological, and behavioral, though with different levels of strength, have been addressed by the existing literature. Still, lack of significant dedication by marketing scholars calls for further investigation.
The Influence of Social Media Communications on Consumer-Brand Relationships in the Luxury Brand Context
Authors: Firouznia Maryam , Brochado Ana , Wood Charles
Published: April 2024

In this study, a total of 59 studies were analyzed. This study presents a bibliometric review of research over the past decade (2010 to 2022). The findings indicated that most studies are conducted in China and applied quantitative method and used questionnaire for data collection on social media platforms such as Facebook, Instagram, and Twitter. Moreover, the findings of this study indicated that 'Brand Luxury,' 'Social Media Marketing,' 'brand equity,' 'luxury marketing,' 'purchase intention,' 'fashion brands,' and 'trust' are the most frequently used keywords. The findings of this study indicated that the major leading journals in the publication of research papers on luxury brands are the “Journal of Global Fashion Marketing,” “Developments in Marketing Science,” and the “Journal of Business Research.” The current study provides a summary of existing studies, uncovers knowledge gaps, and proposes recommendations for future research.
Driving Innovation Through Internal Marketing Initiatives
Authors: Frigenti Pietro Paolo
Published: April 2024

This chapter examines the pivotal role of internal marketing (IM) in fostering marketing innovation within organizations. The chapter identifies challenges faced in IM implementation, including employee reluctance to change, communication gaps, resource limitations, and cultural barriers within organizations. Best practices to mitigate these challenges are then discussed, in the form of facilitators that can support and enable IM implementation. Examples include effective leadership, active staff engagement, proficient communication, training and development, collaborative efforts, and appropriate resource allocation. A practical framework is provided, addressing the main challenges that can occur when implementing IM initiatives, and tending approaches to mitigate the issues. The link with innovation is constantly presented throughout the chapter, which contributes to the IM literature by offering a nuanced understanding of its challenges and best practices, emphasizing IM's role in promoting a culture of innovation and improved organizational performance.
A Policy Framework for Sustainable Marketing Practices and Brand Evaluation Through Instagram Marketing
Authors: Jalal Syed Muhammad , Arshad Iqra , Khalil Shahid , Khalil Muhammad Khuram
Published: April 2024

The negative impact that individuals have on the natural world led to the development of the concept of sustainable marketing. Increasing consumer trends regarding environmentally conscious consumers have created a fresh market chance for the global economic system. Sustainability refers to mankind's general capacity to engage with the many facets of our current situation that demand cognitive focus. In consequence, the objective of this study was to investigate how sustainability marketing practices have an influence on brand evaluation. This research shows how people think about the new sustainability marketing strategies. The current research also includes the mediating role of fashion consciousness among sustainable marketing practices and brand evaluation in the context of Oman. Non-random and convenient sampling techniques are used to collect the data from 336 respondents. SmartPLS 4.0 was employed for data analysis. Findings reveal that sustainable marketing practices have a significant impact on brand evaluation. However, fashion consciousness did not work as a mediator in between sustainable practices and brand evaluation as all concerned mediating hypotheses were not supported.
Public-Private Partnership (PPP) in Agricultural Research Financing in Nigeria
Authors: Akinrinde Ibukunoluwa J. , Aromolaran Opeyemi , Arogundade Sodiq T. , Onuoha Peripaul O.
Published: April 2024

The broad objective of this chapter is to underscore the importance of collaborative PPP in agricultural research financing. The specific objectives are to reveal Nigeria's comparative advantage in agriculture, reveal how Nigeria's comparative advantage in agriculture could be transformed into Michael Porter's concept of competitive advantage through Albert Hirschman's unbalanced growth strategy, and initiate a triple bottom-line approach to agricultural research financing. To achieve the last objective, the United Nations Global Compact (UNGC) members' account balances of firms in Nigeria were collected from annual reports to speculate the agricultural research finance revenue realizable from the private sector. The study adopted the UNGC's financial commitment benchmark for every functional firm registered with the Corporate Affairs Commission (CAC) in Nigeria as an appropriate bottom-line commitment that private sectors should have towards agricultural research financing – if to be regarded as socially responsible in Nigeria.
Precision Irrigation for Sustainable Agricultural Productivity
Authors: Mushtaq Moazzam , Ali Hasnain , Raza Aamir , Maqbool Sheraz , Safdar Muhammad , Ahmed Mubashir , Sattar Jaffar
Published: April 2024

Precision irrigation is a water management strategy that applies water to crops based on their specific needs. It is a sustainable practice that can help to increase crop yields, reduce water use, improve fertilizer use efficiency, and reduce environmental impact. This chapter offers a detailed overview of precision irrigation for sustainable agricultural productivity. It defines precision irrigation and discusses its benefits, types, components, design, implementation, management, applications, and economic and environmental benefits. The chapter also discusses the role of precision irrigation in sustainable agriculture, challenges and opportunities for adoption, and the future of precision irrigation. It is intended to be a valuable resource for farmers, researchers, policymakers, and other stakeholders interested in learning more about precision irrigation's role in sustainable agriculture.
Influence of Corporate Social Responsibility on Competitive Advantage Through the Mediating Role of Green Brand Image and Green Brand Love
Authors: Shafiq Muhammad Aqib , Iqbal Sobia , Shahid Muhammad Naeem , Ahmad Bashir
Published: April 2024

In today's highly competitive and technology-driven business landscape, understanding the issues that influence corporate social responsibility, green brand image and green brand love has become critical for organizations seeking to maintain a competitive edge. This quantitative investigation is intended to scrutinize the inspiration of corporate social responsibility on competitive advantage through the mediating role of green brand image and green brand love. The study employs a rigorous quantitative research design, collecting data from a diverse sample of customers across various industries. The discoveries reveal that corporate social responsibility shows a pivotal role in strengthening green brand image, green brand love and competitive advantage Furthermore, green brand image and green brand love has positive association with competitive advantage These findings have important implications for marketers who aim to build green brand image and green brand love through corporate social responsibility and increase competitive advantage.
Implementing CSR Concepts in the Slovenian Aluminium Industry
Authors: Jovanović Nikola , Pastirk Gal , Primec Andreja
Published: April 2024

This chapter examines the integration of corporate social responsibility (CSR) concepts in the Slovenian aluminium industry and their substantial influence on this sector. The aluminium industry's commitment to CSR principles, as emphasized in this article, not only reinforces its path towards sustainable growth but also highlights its fundamental and vital role in promoting environmental responsibility, ethical conduct, and social well-being, contributing significantly to local and global contexts. The case study uncovers the holistic approach the two prominent Slovenian aluminium companies took in adopting evolving CSR principles, spanning technology adoption, human rights advocacy. The research analyses CSR practices within the Slovenian aluminium industry, assessing their accordance with Corporate Sustainability Reporting requirements outlined by the Non-Financial Reporting Directive (NFRD) and the Corporate Sustainability Reporting Directive (CSRD).
Advancing Employee Voice in India
Authors: Munna Afzal Sayed , Rahman Mushfiqur , Shaikh Md Sadeque Imam , Koolmon Ghanshym
Published: April 2024

Legal backgrounds within a country generally have a direct impact on the commercial aspects in which employee voice has been found to be a significant factor. In this case, in the changing environment of the business industries across India, legal systems have also been transitioning into a new body of assessment which can be useful for managing ethical values. Employee voice in business organisations in the Indian context has been subjugated to legal frameworks which have been introduced in the study, along with a detailed analysis of the context in order to aid understanding. Moreover, this study focuses on the state of employee voice within the Indian organisational settings and the private sector, and this concept is explained in an in-depth manner. Furthermore, the Indian Public Sector is highlighted by exploring the legal structure within India in relation to the employee voice. In addition, this study focuses on the sector-specific dynamics by incorporating employee voice.
Pensar los espacios públicos desde la “arquitectura menor”
Authors: Lange-Valdés Carlos , Amigo-Ahumada María Jesús
Published: April 2024

El presente artículo analiza la categoría de “arquitectura menor” como herramienta conceptual que permite abordar y comprender las obras de mejoramiento barrial autogestionadas por los habitantes, dentro del marco disciplinar de la arquitectura, visibilizando sus saberes y conocimientos cotidianos, y promoviendo el aprendizaje en torno a su relevancia para la producción social de los espacios públicos.
Clinical analysis of multiple primary gastrointestinal malignant tumors: A 10-year case review of a single-center
Authors: Zhu Cheng-Lou , Peng Ling-Zhi
Published: April 2024

BACKGROUND

Multiple primary malignant tumors (MPMTs) was first described by Billroth as early as 1889, with the first report published by Warren and Gates in 1932. Since then, numerous cases have been reported. A literature review of 1104269 patients with cancer revealed that the incidence of MPMTs ranged from 0.73 to 11.7%. In recent years, however, there has been a significant upward trend in the incidence of this phenomenon, which may be associated with many different factors, including the advancement of modern diagnostic procedures facilitating the examination and diagnosis of more MPMTs, increased exposure to chemotherapy and radiotherapy that exacerbate the risk of new malignant tumors in patients with cancer, and prolonged survival of patients with cancer allowing sufficient time for the development of new primary cancers.

AIM

To analyze the incidence, clinical features, treatment factors, prevalence, and prognosis of patients with MPMTs in the gastrointestinal tract treated in a single center. Additionally, we analyzed the different tumor combinations, time interval between the occurrence of tumors, and staging.

METHODS

This retrospective cohort study analyzed 8059 patients with pathologically confirmed gastrointestinal malignant tumors treated at the Gansu Province Hospital in Lanzhou, Gansu, China between June 2011 and June 2020. Of these, 85 patients had MPMTs. The clinical features, treatment factors, prevalence, and prognosis of this latter cohort were analyzed.

RESULTS

The incidence of MPMTs in patients with gastrointestinal malignant tumors was 1.05% (85/8059), including 83 double primary malignant tumors and two triple primary malignant tumors of which 57 (67.06%) were synchronous MPMTs (SMPMTs) and 28 (32.94%) were metachronous MPMTs (MMPMTs). The most frequent associations were found between the rectum colon cancers within the SMPMT category and the gastric-colon cancers within the MMPMT category. For the MMPMTs, the median interval was 53 months. The overall 1-, 3- and 5-year survival rates from diagnosis of the first primary cancer were 91.36%, 65.41%, and 45.97%, respectively; those from diagnosis of the second primary cancer were 67.90%, 29.90%, and 17.37%, respectively.

CONCLUSION

MPMTs in the gastrointestinal tract have a high incidence and poor prognosis. Thus, it is necessary to perform both gastroscopy and colonoscopy in patients with gastrointestinal tumors. Multidisciplinary comprehensive diagnosis and treatment may improve the diagnosis rate and treatment efficiency of MPMTs.
Causal roles of gut microbiota in cholangiocarcinoma etiology suggested by genetic study
Authors: Chen Zhi-Tao , Ding Chen-Chen , Chen Kai-Lei , Gu Yang-Jun , Lu Chi-Cheng , Li Qi-Yong
Published: April 2024

BACKGROUND

Cholangiocarcinoma (CCA) is a highly malignant biliary tract cancer with poor prognosis. Previous studies have implicated the gut microbiota in CCA, but evidence for causal mechanisms is lacking.

AIM

To investigate the causal relationship between gut microbiota and CCA risk.

METHODS

We performed a two-sample mendelian randomization study to evaluate potential causal associations between gut microbiota and CCA risk using genome-wide association study summary statistics for 196 gut microbial taxa and CCA. Genetic variants were used as instrumental variables. Multiple sensitivity analyses assessed result robustness.

RESULTS

Fifteen gut microbial taxa showed significant causal associations with CCA risk. Higher genetically predicted abundance of genus Eubacteriumnodatum group , genus Ruminococcustorques group , genus Coprococcus , genus Dorea , and phylum Actinobacteria were associated with reduced risk of gallbladder cancer and extrahepatic CCA. Increased intrahepatic CCA risk was associated with higher abundance of family Veillonellaceae , genus Alistipes , order Enterobacteriales , and phylum Firmicutes. Protective effects against CCA were suggested for genus Collinsella , genus Eisenbergiella , genus Anaerostipes , genus Paraprevotella , genus Parasutterella , and phylum Verrucomicrobia. Sensitivity analyses indicated these findings were reliable without pleiotropy.

CONCLUSION

This pioneering study provides novel evidence that specific gut microbiota may play causal roles in CCA risk. Further experimental validation of these candidate microbes is warranted to consolidate causality and mechanisms.
NOX4 promotes tumor progression through the MAPK-MEK1/2-ERK1/2 axis in colorectal cancer
Authors: Xu Yu-Jie , Huo Ya-Chang , Zhao Qi-Tai , Liu Jin-Yan , Tian Yi-Jun , Yang Lei-Lei , Zhang Yi
Published: April 2024

BACKGROUND

Metabolic reprogramming plays a key role in cancer progression and clinical outcomes; however, the patterns and primary regulators of metabolic reprogramming in colorectal cancer (CRC) are not well understood.

AIM

To explore the role of nicotinamide adenine dinucleotide phosphate oxidase 4 (NOX4) in promoting progression of CRC.

METHODS

We evaluated the expression and function of dysregulated and survival-related metabolic genes using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Consensus clustering was used to cluster CRC based on dysregulated metabolic genes. A prediction model was constructed based on survival-related metabolic genes. Sphere formation, migration, invasion, proliferation, apoptosis and clone formation was used to evaluate the biological function of NOX4 in CRC. mRNA sequencing was utilized to explore the alterations of gene expression NOX4 over-expression tumor cells. In vivo subcutaneous and lung metastasis mouse tumor model was used to explore the effect of NOX4 on tumor growth.

RESULTS

We comprehensively analyzed 3341 metabolic genes in CRC and identified three clusters based on dysregulated metabolic genes. Among these genes, NOX4 was highly expressed in tumor tissues and correlated with worse survival. In vitro , NOX4 overexpression induced clone formation, migration, invasion, and stemness in CRC cells. Furthermore, RNA-sequencing analysis revealed that NOX4 overexpression activated the mitogen-activated protein kinase-MEK1/2-ERK1/2 signaling pathway. Trametinib, a MEK1/2 inhibitor, abolished the NOX4-mediated tumor progression. In vivo , NOX4 overexpression promoted subcutaneous tumor growth and lung metastasis, whereas trametinib treatment can reversed the metastasis.

CONCLUSION

Our study comprehensively analyzed metabolic gene expression and highlighted the importance of NOX4 in promoting CRC metastasis, suggesting that trametinib could be a potential therapeutic drugs of CRC clinical therapy targeting NOX4.
Effectiveness and tolerability of programmed cell death protein-1 inhibitor + chemotherapy compared to chemotherapy for upper gastrointestinal tract cancers
Authors: Zhang Xiao-Min , Yang Ting , Xu Ying-Ying , Li Bao-Zhong , Shen Wei , Hu Wen-Qing , Yan Cai-Wen , Zong Liang
Published: April 2024

BACKGROUND

The combination of programmed cell death protein-1 (PD-1) inhibitor and chemotherapy is approved as a standard first- or second-line treatment in patients with advanced oesophageal or gastric cancer. However, it is unclear whether this combination is superior to chemotherapy alone.

AIM

To assess the comparative effectiveness and tolerability of combining PD-1 inhibitors with chemotherapy vs chemotherapy alone in patients with advanced gastric cancer, gastroesophageal junction (GEJ) cancer, or oesophageal carcinoma.

METHODS

We searched the PubMed and Embase databases for studies that compared the efficacy and tolerance of PD-1 inhibitors in combination with chemotherapy vs chemotherapy alone in patients with advanced oesophageal or gastric cancer. We employed either random or fixed models to analyze the outcomes of each clinical trial, encompassing data on overall survival (OS), progression-free survival (PFS), objective response rate, and adverse events (AEs).

RESULTS

Nine phase 3 clinical trials (7016 advanced oesophageal and gastric cancer patients) met the inclusion criteria. Our meta-analysis demonstrated that the pooled PD-1 inhibitor + chemotherapy group had a significantly longer OS than the chemotherapy-alone group [hazard ratio (HR) = 0.76, 95% confidence interval (CI): 0.71-0.81]; the pooled PFS result was consistent with that of OS (HR = 0.67, 95%CI: 0.61-0.74). The count of patients achieving an objective response in the PD-1 inhibitor + chemotherapy group surpassed that of the chemotherapy-alone group [odds ratio (OR) = 1.86, 95%CI: 1.59-2.18]. AE incidence was also higher in the combination-therapy group than in the chemotherapy-alone group, regardless of whether ≥ grade 3 only (OR = 1.30, 95%CI: 1.07-1.57) or all AE grades (OR = 1.88, 95%CI: 1.39-2.54) were examined. We performed a subgroup analysis based on the programmed death-ligand 1 (PD-L1) combined positive score (CPS) and noted extended OS and PFS durations within the CPS ≥ 1, CPS ≥ 5, and CPS ≥ 10 subgroups of the PD-1 inhibitor + chemotherapy group.

CONCLUSION

In contrast to chemotherapy alone, the combination of PD-1 inhibitor and chemotherapy appears to present a more favorable option for initial or subsequent treatment in patients with gastric cancer, GEJ tumor, or oesophageal cancer. This holds true particularly for individuals with PD-L1 CPS scores of ≥ 5 and ≥ 10.
On-Road Testing to Characterize Speed-Following Behavior in Production Automated Vehicles
Authors: Duoba Michael , Vellamattathil Baby Tinu , Pulpeiro Gonzalez Jorge , HomChaudhuri Baisravan
Published: April 2024

A fully instrumented Tesla Model 3 was used to collect thousands of hours of real-world automated driving data, encompassing both Autopilot and Full Self-Driving modes. This comprehensive dataset included vehicle operational parameters from the data busses, capturing details such as powertrain performance, energy consumption, and the control of advanced driver assistance systems (ADAS). Additionally, interactions with the surrounding traffic were recorded using a perception kit developed in-house equipped with LIDAR and a 360-degree camera system. We collected the data as part of a larger program to assess energy-efficient driving behavior of production connected and automated vehicles. One important aspect of characterizing the test vehicle is predicting its car-following behavior. Using both uncontrolled on-road tests and dedicated tests with a lead car performing set speed maneuvers, we tuned conventional adaptive cruise control (ACC) equations to fit the vehicle’s behavior. We developed specific methods of applying the dedicated tests to separately fine-tune ACC equation components (speed, headway gap, system delays). The results showed a strong alignment between the tuned equation outputs and the observed data. The additional tuning methodologies show promise and invite researchers to explore them further.
Modelling of Airflow-Snow Interaction on Metal Surfaces Using FVM and SPH-Based Solvers on a Wedge Geometry
Authors: Makam Sri Lalith Madhav , Shah Srishty , Varghese Rixson , Walia Rajat
Published: April 2024

The potential blinding of Advanced Driver Assistance Systems (ADAS) sensors due to contamination poses a notable threat to autonomous vehicles. These sensors' performance can be compromised by diverse sources such as dust, water, or snow. However, our investigation concentrates primarily on snow-related contamination, a frequent occurrence during winter. The accumulation of snow and ice significantly hampers the operational efficacy of autonomous vehicles. Over the years, a series of field tests and wind tunnel experiments have been conducted to analyze the mechanisms of snow interaction and soiling patterns on vehicles and bluff bodies. Notably distinctive patterns of soiling have been identified across multiple areas of these structures. The central challenge revolves around constructing an accurate model to predict snow buildup on vehicles. The precision in capturing the airflow dynamics, which substantially influences how the snow interacts with the specific body, is crucial for forecasting the resulting soiling patterns. This project's objective is to establish a digital simulation approach for depicting interactions between air, snow, and metal surfaces. This methodology is substantiated by comparisons with established wind tunnel findings.

The study utilizes simplified bluff bodies, specifically employing a Wedge geometry, to minimize unexpected errors. For aerodynamic simulations, STAR-CCM+ featuring the Detached Eddy Simulation (DES) turbulence model was adopted. This effectively captures transient aerodynamics, particularly in the wake region, which has been identified as a critical aspect influencing soiling patterns. The Smooth Particle Hydrodynamics (SPH) based tool, PreonLab, was employed to simulate snow particle accumulation. An extensive parametric analysis within the PreonLab snow solver was conducted, exploring its competency in simulating snow particles and their interactions with airflow and bluff bodies. A comprehensive framework for simulating snow accumulation was formulated, encompassing snow properties, drag models, adhesion, and roughness of surface. The simulation outputs demonstrate good alignment with the outcomes of wind tunnel tests.
Evaluating Vehicle Response Through Non-Traditional Pedestrian Automatic Emergency Braking Scenarios
Authors: Bartholomew Meredith , Helber Nicholas , Heydinger Gary , Zagorski Scott
Published: April 2024

Pedestrian Automatic Emergency Braking (P-AEB) is a technology designed to avoid or reduce the severity of vehicle to pedestrian collisions. This technology is currently assessed and evaluated via EuroNCAP and similar procedures in which a pedestrian test target is crossing the road, walking alongside the road, or stationary in the forward vehicle travel path. While these assessment methods serve the purpose of providing cross-comparison of technology performance in a standardized set of scenarios, there are many scenarios which could occur which are not considered or studied. By identifying and performing non-EuroNCAP, non-standardized scenarios using similar methodology, the robustness of P-AEB systems can be analyzed. These scenarios help identify areas of further development and consideration for future testing programs. Three scenarios were considered as a part of this work: straight line approach, curved path approach, and parking lot testing. Exemplar tests were performed for each scenario using a test vehicle. Straight line approach testing is directly related to standardized test scenarios and is a useful basis to evaluate a vehicle’s performance against other testing facilities results. Curved path braking adds the complicating factors of a steering input and a target path not perpendicular to the vehicle travel path during most of the approach. Finally, parking lot testing adds visual and radar clutter and a dense environmental background to traditional straight line approach testing scenarios. While there are many more tests which could be performed to further evaluate the behavior of the P-AEB system, these three scenarios provide useful insights into vehicle behavior including alert and braking onset timing, scenario specific challenges, and more.
The Effectiveness of Forward Collision Warning Systems in Detecting Real-World Passenger and Nonpassenger Vehicles Relative to a Surrogate Vehicle Target
Authors: Kidd David , Anctil Benoit , Charlebois Dominique
Published: April 2024

Automatic emergency braking and forward collision warning (FCW) reduce the incidence of police-reported rear-end crashes by 27% to 50%, but these systems may not be effective for preventing rear-end crashes with nonpassenger vehicles. IIHS and Transport Canada evaluated FCW performance with 12 nonpassenger and 7 passenger vehicle or surrogate vehicle targets in five 2021-2022 model year vehicles. The presence and timing of an FCW was measured as a test vehicle traveling 50, 60, or 70 km/h approached a stationary target ahead in the lane center. Equivalence testing was used to evaluate whether the proportion of trials with an FCW (within ± 0.20) and the average time-to-collision of the warning (within ± 0.23 sec) for each target was meaningfully different from a global vehicle car target (GVT). A similar approach was used to determine if FCW performance was reproducible between 3 targets tested by both IIHS and Transport Canada and was equivalent between surrogate car and motorcycle targets produced by different companies. FCW systems provided fewer and later warnings when the vehicles approached nonpassenger vehicles compared with the GVT. Results were reproducible between IIHS and Transport Canada, but FCW performance with passenger car and motorcycle surrogate targets representing the same vehicle were not always equivalent. Testing organizations should evaluate AEB and FCW systems with nonpassenger vehicle targets to ensure that AEB and FCW performance observed with passenger vehicles extends to other vehicle types, particularly motorcycles and medium or large trucks that are commonly struck in fatal rear-end crashes.
Energy Efficiency Technologies of Connected and Automated Vehicles: Findings from ARPA-E’s NEXTCAR Program
Authors: Sofos Marina , Bakaya Priyanka , Mousa Saleh , Atkinson Chris , Heffner Reid
Published: April 2024

This paper details the advancements and outcomes of the NEXTCAR (Next-Generation Energy Technologies for Connected and Automated on-Road Vehicles) program, an initiative led by the Advanced Research Projects Agency-Energy (ARPA-E). The program focusses on harnessing the full potential of Connected and Automated Vehicle (CAV) technologies to develop advanced vehicle dynamic and powertrain control technologies (VD&PT). These technologies have shown the capability to reduce energy consumption by 20% in conventional and hybrid electric cars and trucks at automation levels L1-L3 and by 30% L4 fully autonomous vehicles. Such reductions could lead to significant energy savings across the entire U.S. vehicle fleet. This study summarizes the results from Phases I and II of the NEXTCAR program, highlighting the contributions of four teams that participated in both phases: Southwest Research Institute, Michigan Technical University, Ohio State University, and the University of California, Berkeley. The study details the technologies developed by each team, including eco-routing, power-split optimization, cooperative driving, blended mode, speed harmonization, predictive cruise control, charge-sustaining engine on/off optimizer, and eco-approach and departure, among other innovative solutions. It outlines the energy savings achieved by these innovations. These technologies have experimentally demonstrated significant energy savings, ranging from 10-30%, while maintaining travel times.

Additionally, the paper examines the challenges in commercializing these technologies and highlights ARPA-E's envisioned actions to provide a unified testing environment for all teams. This environment will allow for the assessment of all developed technologies under similar conditions, aiming to overcome the limitations of standardized Environmental Protection Agency EPA testing cycles and more accurately reflect real-world driving conditions. This approach validates the effectiveness of CAV technologies and supports their commercialization.
A Terminal-Velocity Heuristic Method for Speed Optimization of EVs in Multi-Intersection Scenarios
Authors: Hao Zhengyi , Zhang Zeyang , Jiang Yuyao , Chu Hongqing , Gao Bingzhao , Chen Hong
Published: April 2024

The optimization of speed holds critical significance for pure electric vehicles. In multi-intersection scenarios, the determination of terminal velocity plays a crucial role in addressing the complexities of the speed optimization problem. However, prevailing methodologies documented in the literature predominantly adhere to a fixed speed constraint derived from traffic light regulations, serving as the primary basis for the terminal velocity constraint. Nevertheless, this strategy can result in unnecessary acceleration and deceleration maneuvers, consequently leading to an undesirable escalation in energy consumption. To mitigate these issues and attain an optimal terminal velocity, this paper proposes an innovative speed optimization method that incorporates a terminal-velocity heuristic. Firstly, a traffic light state model is established to determine the speed range required to avoid coming to a stop at signalized intersections. Subsequently, by addressing the effect of vehicle spacing and utilizing a fitted model of energy consumption within the permissible speed range, an optimal cruising speed trajectory that minimizes energy usage is derived. Finally, the optimal cruising speed becomes a terminal velocity constraint term in the optimization problem, which is solved using a model predictive control algorithm. To assess the effectiveness of the proposed speed planning algorithm, a benchmark algorithm is selected for comparison, which traverses a traffic intersection at the onset of the green light window. Both the proposed algorithm and the benchmark algorithm are tested in two distinct traffic flow scenarios, and the results demonstrate that the proposed optimization algorithm achieves energy savings of 1.5704% and 1.1583%, respectively, making it energy efficient.
WITHDRAWN A Digital Design Agent for Ground Vehicles
Authors: Rogers Nathan , Turner Cameron , Castanier Matthew P. , Hartman Gregory , Rapp Stephen , Wagner John
Published: April 2024

The design of transportation vehicles, whether passenger or commercial, typically involves a lengthy process from concept to prototype and eventual manufacture. To improve competitiveness, original equipment manufacturers are continually exploring ways to shorten the design process. The application of digital tools such as computer-aided-design and computer-aided-engineering, as well as model-based computer simulation enable team members to virtually design and evaluate ideas within realistic operating environments. Recent advances in machine learning (ML)/artificial intelligence (AI) can be integrated into this paradigm to shorten the initial design sequence through the creation of digital agents. A digital agent can intelligently explore the design space to identify promising component features which can be collectively assessed within a virtual vehicle simulation. In this paper, the framework for a python-based ML/AI virtual agent will be presented and applied to a vehicle suspension within an off-road ground vehicle. A case study investigates four suspension designs and their corresponding component feature characteristics with attention focused on ride quality, weight, and maximum force. Representative results are presented and discussed to offer insight into the methodology and briefly contrast it with traditional optimization approaches. The path forward for the inclusion of multiple design agents within a “collaborative digital design bowl” are presented in the conclusion.
Reduced Order Modeling of Engine Coolant Temperature Model in Plug-In Hybrid Electric Vehicles
Authors: Sugai Tomotaka , Shintani Kohei , Honda Takumu , Sakamoto Hironobu , Tsuchiyama Minoru
Published: April 2024

In recent years, swift changes in market demands toward achieving carbon neutrality have driven significant developments within the automotive industry. Consequently, employing computer simulations in the early stages of vehicle development has become imperative for a comprehensive understanding of performance characteristics. Of particular importance is the cooling performance of vehicles, which plays a vital role in ensuring safety and overall performance. It is crucial to predict optimal cooling performance, particularly about the heat generated by the powertrain during the initial phases of vehicle development. However, the utilization of thermal analysis models for assessing vehicle cooling performance demands substantial computational resources, rendering them less practical for evaluating performance associated with design changes in the planning phase. This paper introduces a method for constructing a low-dimensional model capable of predicting the time series response of cooling performance using a surrogate model based on thermal analysis. The thermal analysis model in this study is evaluated using design variables obtained through experiments, and a training data matrix is constructed from the corresponding time series responses. Unsupervised learning is employed to extract key features from these responses. For the regression model, a Gaussian process is applied to each latent variable derived from the unsupervised learning process. This transformation allows for a reduction in computational costs, shifting from high-dimensional calculations to a low-dimensional latent space for prediction. The proposed method is then applied to analyze the time series response of engine coolant temperature, obtained from the engine thermal analysis model, effectively demonstrating its utility.
Charging Load Estimation for a Fleet of Autonomous Vehicles
Authors: Paudel Saroj , Zhang Jiangfeng , Ayalew Beshah , Skowronska Annette
Published: April 2024

In intelligent surveillance and reconnaissance (ISR) missions, multiple autonomous vehicles, such as unmanned ground vehicles (UGVs) or unmanned aerial vehicles (UAVs), coordinate with each other for efficient information gathering. These vehicles are usually battery-powered and require periodic charging when deployed for continuous monitoring that spans multiple hours or days. In this paper, we consider a mobile host charging vehicle that carries distributed sources, such as a generator, solar PV and battery, and is deployed in the area where the UAVs and UGVs operate. However, due to uncertainties, the state of charge of UAV and UGV batteries, their arrival time at the charging location and the charging duration cannot be predicted accurately. We propose a stochastic modeling approach to deal with these uncertainties based on certain physical assumptions such as the flight time for a UAV, distance travelled for a UGV, and the final state of charge of the battery before they leave the host charging vehicle. Based on the stochastic model, an aggregated charging power demand is forecasted. A model predictive control-based operation is then used for the operation of the distributed sources on the host vehicle to meet the forecasted charging power demand. The host vehicle battery works as a buffer during abrupt changes in the charging power demand. The operational scenario is simulated with ten UAVs, ten UGVs and a host vehicle carrying a diesel generator, a battery pack and a PV system. The result of this work is applicable to energy-aware charging management for a fleet of vehicles.
Quantifying the Costs of Charger Availability Uncertainty for Residents of Multi-Unit Dwellings
Authors: Rabinowitz Aaron , Tal Gil , Bradley Thomas
Published: April 2024

Even when charging at the highest rates currently available, Electric Vehicles (EVs) add range at substantially lower rates than Internal Combustion Engine Vehicles (ICVs) do while fueling. In addition, DC charging comes at a cost premium and leads to accelerated battery degradation. EV users able to rely on AC charging during long dwells at home or work may experience cost and time savings relative to ICV users with similar driving patterns. However, EV users unable to charge during long dwells will face higher charging costs and higher dedicated charging time. An important question is how occupants of Multi-Unit Dwellings (MUDs), which provide some AC Electric Vehicle Supply Infrastructure (EVSE) but not enough for all cars to charge at once, will be effected. In this paper the authors’ previously published method for quantifying EV user inconvenience due to charging is extended to deal with stochastic charger availability. Stochastic Mixed Integer Linear Programming (S-MILP) is used to determine optimal charging behavior for EV users based on itineraries and the likelihood of availability of charging. Expected inconveniences for levels of charger availability and the quantitative value of additional EVSE and of charger scheduling schemes are presented.
Assessing Resilience in Lane Detection Methods: Infrastructure-Based Sensors and Traditional Approaches for Autonomous Vehicles
Authors: Patil Pritesh , Fanas Rojas Johan , Kadav Parth , Sharma Sachin , Masterson Alexandra , Wang Ross , Ekti Ali , DaHan Liao , Brown Nicolas , Asher Zachary
Published: April 2024

Traditional autonomous vehicle perception subsystems that use onboard sensors have the drawbacks of high computational load and data duplication. Infrastructure-based sensors, which can provide high quality information without the computational burden and data duplication, are an alternative to traditional autonomous vehicle perception subsystems. However, these technologies are still in the early stages of development and have not been extensively evaluated for lane detection system performance. Therefore, there is a lack of quantitative data on their performance relative to traditional perception methods, especially during hazardous scenarios, such as lane line occlusion, sensor failure, and environmental obstructions. We address this need by evaluating the influence of hazards on the resilience of three different lane detection methods in simulation: (1) traditional camera detection using a U-Net algorithm, (2) radar detections using infrastructure-based radar retro-reflectors (RRs), and (3) direct communication of lane line information using chip-enabled raised pavement markers (CERPMs). The performance of each of these methods is assessed using resilience engineering metrics by simulating the individual methods for each sensor technology’s response to related hazards in the CARLA simulator. Using simulation techniques to replicate these methods and hazards acquires extensive datasets without lengthy time investments. Specifically, the resilience triangle was used to quantitatively measure the resilience of the lane detection system to obtain unique insights into each of the three lane detection methods; notably the infrastructure-based CERPMs and RRs had high resistance to hazards and were not as easily affected as the vision-based U-Net. However, while U-Net was able to recover the fastest from the disruption as compared to the other two methods, it also had the most performance loss. Overall, this study demonstrates that while infrastructure-based lane keeping technologies are still in early development, they have great potential as alternatives to traditional ones.