Miracle-dz/UniFAR-FTUs huggingface dataset:
A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm

Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.
Experimental Study on Mechanics and Water Stability of High Liquid Limit Soil Stabilized by Compound Stabilizer: A Sustainable Construction Perspective

Sustainable highway construction and operation are threatened by high-liquid-limit soil with low strength and poor water stability in Dongting Lake areas. In order to obtain a soil stabilizer that can effectively improve its strength and water stability, first the author selected inorganic materials (cement, quicklime and fly ash) and sulfonated oil (SO) as the main components of the composite soil stabilizer. Then, a series of single admixture tests were carried out to explore the strength and water stability mechanism of single admixture stabilized soil. Finally, a series of orthogonal experiments and cost analyses were carried out to obtain the formula of the composite stabilizer. According to the results of single doping, inorganic materials can significantly enhance the strength and stiffness of high-liquid-limit soil. The content of SO has a strong correlation with the water stability of high-liquid-limit soil. On a microscopic scale, X-ray diffraction patterns and scanning electron microscopy images explained this law. According to the orthogonal results, the formula of the composite soil stabilizer is: cement 4.5%, quicklime 1.5%, fly ash 2.5%, and SO 0.2%. This paper provides a method to improve high-liquid-limit soil, which is beneficial to sustainable construction and operation of the highway.
The economic lot-sizing problem with remanufacturing and heterogeneous returns: formulations, analysis and algorithms

We address an extension of the economic lot-sizing problem with remanufacturing, in which the returns are assumed of heterogeneous quality. Costs for remanufacturing and holding inventory depend on the quality of the returns. For the problem with general cost functions, we provide a network flows formulation and a dynamic programming algorithm of pseudopolynomial time. Then, we consider the problem under stationary costs and different set-up schemes for manufacturing and remanufacturing. For the case of a joint set-up scheme, we derive certain properties related to the form of the optimal solutions. Based on these theoretical results, a polynomial-time algorithm is presented for the particular case of a large quantity of low-cost returns. For the case of separate set-up scheme, we show that the problem is NP-hard and present several lot-sizing rules specially designed for the problem. An extensive numerical experimentation was conducted to evaluate the suggested rules under different combinations of inventory and set-up costs. From the results obtained, we can extract several managerial insights, such as in general it is profitable to remanufacture all the available returns of the same quality in certain periods, but not necessarily those of the highest quality.
Exemplifying Power Matters: The Impact of Power Exemplification of Transgender People in the News on Issue Attribution, Dehumanization, and Aggression Tendencies

ABSTRACT Despite the enormous rise in the transgender media visibility in recent years, the news media in particular still predominantly exemplify powerful elite transgender people or exclusively quote their cisgender counterparts, leaving out the voices and lived experiences of transgender people who do not fall into the high-power categories. Such power exemplification has become part of the journalism practice when reporting issues regarding marginalized social groups. Little quantitative social scientific research has explored how such journalistic practice might have contributed to the acceptance of or the increased hostility and hate crimes against transgender people. Through integrating the theories of exemplification, attribution, and dehumanization, this study experimentally investigates how the power exemplification of members from marginalized social groups like the transgender community (i.e., High-Power vs. Low-Power Transgender Exemplar) in the news narrative interacts with the cisgender heterosexual audience’s sex to redirect people’s intergroup attitudes, responsibility attribution for transgender social issues, dehumanization, and aggression towards transgender people. The findings demonstrated that after exposure to the news content featuring a high-power transgender woman exemplar, cisgender heterosexual women respondents reported significantly higher levels of dehumanization in regard to transgender people’s human nature. After exposure to the news content with power exemplification (vs. the control condition) regardless of the levels of power depicted, male participants were significantly more likely to attribute transgender issues to external factors. These findings reveal 1) the significant psychological and social impacts of the journalism practice of power exemplification when reporting transgender issues, and 2) how heterosexual cisgender men and women audiences respond to power exemplification of transgender people in the news differently. These findings not only provide social scientific evidence to guide practitioners to navigate the intricate practice of exemplifying the power of transgender people in the news but also fill the gap in the lack of quantitative experimental audience research in transgender media studies.
Lateralization of lexical processing in monolinguals and bilinguals

Aims and objectives: This study aims to investigate how lexical processing (LP) is organized in early Turkish–English bilinguals and Turkish monolinguals. Methodology: We used a visual hemifield paradigm where bilingual (n = 48) and monolingual (n = 53) participants performed a lexical decision task. Bilingual participants performed the task in both their languages. Data and analysis: We recorded response times (RTs) and the accuracy rates (ARs) of the participants. An analysis of variance and t-test were run to analyze the bilingual and monolingual data, respectively. Findings: The results obtained from the analysis of the RTs and ARs for the Turkish and English words showed a balanced hemispheric organization in LP in bilingual speakers. The RTs for Turkish words in the monolingual group provided supportive evidence for the predominant role of the left hemisphere in LP. However, no significant difference was found in the accuracy of their answers, suggesting that the monolingual participants’ performance was not influenced by visual field of presentation of the words. Finally, the comparison of the two groups revealed that bilingual participants’ performance was inferior to monolinguals’ in speed and accuracy of processing of words presented in both visual fields. This result gives further support for the differential representation of LP in monolinguals and bilinguals. Originality: The psycholinguistic literature abounds with studies of LP in bilinguals and monolinguals from a variety of language backgrounds; however, there is much less data regarding the brain correlates of LP in Turkish–English bilinguals and Turkish monolinguals. Implications: Since Turkish–English bilinguals and Turkish monolinguals are underrepresented in the literature as compared to the population who speak other languages with alphabetic writing, this study provides preliminary data for future studies. Limitations: We did not control for gender or lexical factors such as orthographic neighbors when designing the word sets used as stimuli.
Functional traits driving pollinator and predator responses to newly established grassland strips in agricultural landscapes

1. Agricultural biodiversity and associated ecosystem functions are declining at alarm-ing rates due to widespread land use intensification. They can only be maintained through targeted landscape management that supports species with different habitat preferences, dispersal capacities and other functional traits that determine their survival. However, we need better understanding whether short- term measures can already improve functional diversity in European agroecosystems. 2. We investigated spatio- temporal responses of bees (solitary bees, bumblebees and honey bees), hoverflies, carabid beetles and spiders to newly established grassland strips in Lower Austria over 3 years, and along a distance gradient to old grasslands. Specifically, we
Optimization of On-Street Parking Charges Based on Price Elasticity of the Expected Perceived Parking Cost

Price discrimination is widely employed to regulate on-street parking behaviors to provide better service to users, and the prices are usually set according to the occupancy of parking spaces without direct consideration of user perception. A binary logit-style choice model is built to describe the parking choice between on-street parking and off-street parking. A new index, named the price elasticity of expected perceived parking cost, is proposed to evaluate users’ response to parking charge. Based on the theory of second-degree price discrimination, three user types are defined according to the parking duration, namely, the preferred users, the neutral users, and the non-preferred users. The optimized parking prices are calculated by the proposed index. A case study of Guangzhou’s on-street parking is presented. It is found that the current pricing scheme for Type-I Zones (High Demand Zones) is reasonable, while the pricing scheme for the Type-II Zones (Low Demand Zones) does not achieve the objectives of usage optimization of on-street parking spaces. An optimized price scheme for the Type-II Zones is proposed to achieve the usage optimization of on-street parking spaces for short-term parking.
Exploring public charging infrastructure requirements for short-haul electric trucks

Abstract Vehicle electrification has the potential to revolutionize transport systems globally by enabling a pathway toward lower-cost, zero-emission transport options. Heavy vehicles are poised to potentially be one of the greatest beneficiaries due to their high operating costs. Here a facility location problem approach is adopted to analyze a sample of deidentified truck trip data, providing initial insights into charging network configurations that could support a short-haul electric truck fleet using the case study of South East Queensland. The charging network scenarios include up to 10 optimally-located public sites. The results suggest that a relatively modest public charging network should be sufficient to support the majority of short-haul electric trucks operating in similar regions internationally, in line with other studies that have found that the majority of short-haul electric truck charging is likely to be carried out at depots. Additionally, in outlining limitations of this study, we highlight the need for greater cooperation between researchers, policy-makers and industry to secure access to high-resolution truck trip data to more accurately plan regional charging networks, and freight decarbonization more broadly.
English for General Academic Purposes or English for Specific Purposes? Language Learning Needs of Medical Students at a Chinese University

The debate over the appropriacy of EGAP and ESP has been an ongoing concern in many higher education contexts. In this paper we discuss how teachers’ and students’ perceptions of English curriculum needs are reflected in the conflict between short-term goals, such as passing exams, and long-term goals, such as career development. Students, doctors and teachers at a medical university in the central part of China were asked about their needs through questionnaires and structured interviews. The findings suggest that whilst many felt the need for medical English to be taught in the early years, particularly through medical texts, there was also push back due to the need for general English to pass English exams, such as CET4/6. We argue that through the incorporation of medical texts, students can start to develop their medical English from the first year of university. This not only ensures the motivation for students to study medical English for professional purposes, but also fulfills the perceived need to prepare for the exam.
Two New Triterpenoid Saponins from the Roots ofGypsophila paniculata with Potent α-Glucosidase Inhibition Activity

Abstract Aim To investigate chemical constituents of Gypsophila paniculata . Methods The compounds were isolated by silica gel, Sephadex LH-20, Rp-C 18 column chromatography and preparative liquid chromatography. Their structures were elucidated by ESI-MS, NMR techniques ( 1 H, 13 C, HMQC, HMBC, TOCSY) and acid hydrolysis. Moreover their α-glucosidase inhibition activity was evaluated compared with that of their aglycone. Results Two triterpenoid saponins, caryophyllacosides A ( 1 ) and B ( 2 ), were isolated from the roots of Gypsophila paniculata , without having recourse to chemical degradation or modification. Both of them were found to have potent α-glucosidase inhibitiory activity. Conclusion The two triterpenoid saponins are new boactive compounds.
Augmented Reality of 3D Content Application in Common Operational Picture Training System for Army

ABSTRACT The purpose of this article is to discuss how to improve the ways the Taiwanese Ground Forces use the common operational picture (COP) for training to improve the efficacy of tactical training and understanding of the combat field. Augmented Reality (AR) has made huge progress in the past decade and is widely applied in education, industrial sector, medical industry, military industry. More attention is focused on training simulations for soldiers and improving battlefield perception systems. The application of AR in tactical training is still an emerging realm of research but has a huge potential. Related studies have shown the application and technical limitations of AR technology in the military field. Then, using a user-oriented research method, a tactical training system based on 3D augmented reality is proposed and constructs a system prototype to combine virtual information with the real environment and provide the advantages of intuition, interaction, and information visualization. The experiment had an experimental group and control group, and an independent sample “t” was tested for evaluation and comparison. The experimental results show that the understanding of battlefield situations and tactical actions in the AR-based tactical teaching system has changed significantly. The system prototype and experimental content provide useful contributions to the tactical teaching of the Army Academy, and it can be used as a reference for the development of AR in future military applications.
Trajectory of post-traumatic stress and depression among children and adolescents following single-incident trauma

ABSTRACT Objective Post-traumatic stress disorder and depression have high comorbidity. Understanding their relationship is of clinical and theoretical importance. A comprehensive way to understand post-trauma psychopathology is through symptom trajectories. This study aims to look at the developmental courses of PTSD and depression symptoms and their interrelationship in the initial months post-trauma in children and adolescents. Methods Two-hundred-and-seventeen children and adolescents aged between eight and 17 exposed to single-event trauma were included in the study. Post-traumatic stress symptoms (PTSS) and depression symptoms were measured at 2 weeks, 2 months and 9 months, with further psychological variables measured at the 2-week assessment. Group-based trajectory modelling (GBTM) was applied to estimate the latent developmental clusters of the two outcomes. Logistic regression was used to identify predictors associated with high symptom groups. Results The GBTM yielded a three-group model for PTSS and a three-group model for depression. PTSS trajectories showed symptoms reduced to a non-clinical level by 9 months for all participants (if they were not already in the non-clinical range): participants were observed to be resilient (42.4%) or recovered within 2 months (35.6%), while 21.9% experienced high level PTSS but recovered by 9 months post-trauma. The depression symptom trajectories predicted a chronic non-recovery group (20.1%) and two mild symptom groups (45.9%, 34.0%). Further analysis showed high synchronicity between PTSS and depression groups. Peri-event panic, negative appraisals, rumination and thought suppression at 2 weeks predicted slow recovery from PTSS. Pre-trauma wellbeing, post-trauma anxiety and negative appraisals predicted chronic depression. Conclusions Post-trauma depression was more persistent than PTSS at 9 months in the sampled population. Cognitive appraisal was the shared risk factor to high symptom groups of both PTSS and depression. HIGHLIGHTS GBTM models estimated trajectories of PTS and depression symptoms from 2 weeks to 9 months posttrauma. PTSS trajectories were highly consistent with depression trajectories. Cognitive appraisal was the shared risk factor to high symptom groups in PTSS and depression.
Risk Management in the Import/Export Process of an Automobile Company: A Contribution for Supply Chain Sustainability

Supply chain risk management (SCRM) is imperative to achieve business sustainability in the long-term perspective and also to increase companies’ competitiveness. ISO 31000—Risk Management explains in its latest versions the need for companies to integrate a risk management process into their business models. Complementary to this standard, ISO 31010 presents 31 risk tools to guide companies in this task. However, a question of practical application arises as to which tools should be used for each stage of the SCRM process. In view of the raised question, the main objective of this research is to select ISO 31010 tools that can be used in each of the stages (identify, analyze, and evaluate) of the risk management of the import and export process of an automotive industry located in Brazil. For this, the analytic hierarchy process (AHP method) was used in a case study to prioritize the tools to compose the SCRM. As practical implications, this study resulted in the suggestion of a structured risk management process, considering the assessment of key professionals of the department studied in the company.
Variation in Postharvest Quality Attributes of Fresh Cowpea (Vigna unguiculata L.) Beans Harvested from Different Crop Mulching Regime

Background: Present study, aimed to assess effect of organic and inorganic crop mulching on physical, physiological and biochemical quality of fresh cowpea beans.Methods: Cowpea (cv. Kashi Kanchan bush-type) was grown during two consecutive seasons from April 2018 to July 2019 under four different mulching treatments. Mulching treatments included no mulch; wheat straw mulch (organic mulch); black mulch and silver mulch. Black and silver mulches were made of 25 microns LDPE sheet. Cowpea was grown as per standard agronomic practices and physical, biochemical and postharvest quality parameters of beans were evaluated.Result: Results indicated that bean length (28.7cm) was highest under silver mulch whereas bean thickness (9.10mm), width (9.29mm) and 100 bean weight (1094.5g) were highest under organic mulch. Likewise, protein content (28.63%), total phenolic content (17.0µg GAE/100g) and total antioxidant activity (46.84µmol trolox equiv./100g) were found highest in beans produced under organic mulch. Overall results demonstrated that crop mulching could be used for enhancing the antioxidants, phenolic content of cowpea beans.
Fast and Robust Dictionary-based Classification for Image Data

Dictionary-based classification has been promising in knowledge discovery from image data, due to its good performance and interpretable theoretical system. Dictionary learning effectively supports both small- and large-scale datasets, while its robustness and performance depends on the atoms of the dictionary most of the time. Empirically, using a large number of atoms is helpful to obtain a robust classification, while robustness cannot be ensured when setting a small number of atoms. However, learning a huge dictionary dramatically slows down the speed of classification, which is especially worse on the large-scale datasets. To address the problem, we propose a Fast and Robust Dictionary-based Classification (FRDC) framework, which fully utilizes the learned dictionary for classification by staging - and -norms to obtain a robust sparse representation. The new objective function, on the one hand, introduces an additional -norm term upon the conventional -norm optimization, which generates a more robust classification. On the other hand, the optimization based on both - and -norms is solved in two stages, which is much easier and faster than current solutions. In this way, even when using a limited size of dictionary, which makes sure the classification runs very fast, it still can gain higher robustness for multiple types of image data. The optimization is then theoretically analyzed in a new formulation, close but distinct to elastic-net, to prove it is crucial to improve the performance under the premise of robustness. According to our extensive experiments conducted on four image datasets for face and object classification, FRDC keeps generating a robust classification no matter whether using a small or large number of atoms. This guarantees a fast and robust dictionary-based image classification. Furthermore, when simply using deep features extracted via some popular pre-trained neural networks, it outperforms many state-of-the-art methods on the specific datasets.