The importance of utilizing an optimal and efficient braking system is emphasized in this study. Braking system optimization and efficiency were practically determined through successive tests on the brake dynamometer, according to road safety regulations. Subsequently, the results were correlated with practical tests involving consecutive braking at different speeds, tracking both the time and distance of braking. The coefficient of friction (COF) was established for each braking instance by utilizing the braking force measured on the brake dynamometer. This paper aims to highlight the genuine impact of the braking system by measuring and establishing its braking efficiency depending on the car’s speed, time, and distance of braking.

This study explored drivers’ emotion-based impressions of car-borne central control platforms (CBCCPs) personal-use vehicles. Thus, this preference-based study examined experts’ and drivers’ opinions regarding CBCCPs’ appeal from the perspective of Miryoku engineering. To this end, this study analyzed data via the EGM (evaluation grid method (EGM) and quantification theory type I. Results: Drivers’ preferences for specific CBCCP design characteristics were categorized into the factors “legible,” convenient,” and “tasteful,” which comprised the core of the EGM semantic hierarchical diagram. In addition, the importance of CBCCPs’ appeal factors and characteristics was assessed through quantification theory type I.The findings of this study provide valuable insights for designers, manufacturers, and researchers interested in the design of CBCCPs. Additionally, the results of this study can contribute to research on applied psychology, human-computer interactions, and car interface design.

The extended cleavage specificity of catfish granzyme-like II has been characterized using substrate phage display. The preference for particular amino acids at and surrounding the cleavage site was further validated by using a panel of recombinant substrates. This serine protease, which has previously been isolated as cDNA from a catfish natural killer-like cell line showed a preference for alanine in the P1 position of the substrate, and for multiple basic amino acids N-terminally of the cleavage site. Using a set of recombinant substrates revealed the enzyme was most active on substrates with an alanine preceded by 3 or 4 basic amino acids in a row, but also showed activity against substrates with two basic amino acids, as well as with two basic amino acids separated by one amino acid just N-terminally of the Ala. The characteristics of this separating amino acid seemed less important, as many different amino acids were accepted in this position, except for proline. The amino acids following the basic amino acids and the P1 Ala residue also appeared to be of major importance for efficient cleavage. The most preferred P1 residue was Ala, and replacing Ala with Gly or Leu resulted in a clear reduction in the cleavage rate. A closely-related zebrafish serine protease (Zebrafish esterase-like) showed a very similar cleavage specificity, indicating an evolutionary conservation of this protease specificity among various fish species. Two catfish serine proteases, originating from NK-like cells, have now been isolated and characterized. One of them is highly specific met-ase with similar characteristics as the mammalian granzyme M. This enzyme may be involved in the induction of apoptosis in virus infected cells, with a potential target in (catfish) caspase 6. In contrast to catfish granzyme -like I, the second enzyme analysed here, doesn’t seem to have a direct counterpart in mammalian NK-cells, and its role in the immune function of catfish NK cells is therefore still not known. However, this enzyme seems to be able to cleave a number of cytoskeletal proteins indicating a separate strategy to induce apoptosis in target cells. Both of these enzymes are very interesting targets for further studies of their roles in catfish immunity, as enzymes with similar specificities have been identified also in zebrafish.

The purpose of this study is to investigate the failure mechanism and preventive strengthening methods of prefabricated full length small box girder (PSBG) under car explosion. After damage analysis during blast loads using the commercial software Autodyn, three strengthening methods are presented to improve the blast mitigation performance. The results show that the failure modes and bearing capacity are significantly different with various strengthening measures. Adhering U-shaped steel plate can effectively enhance the shear performance of PSBG under blast loads. Strengthening the bottom of the upper flange of box girder with steel plate can effectively mitigate the local bending failure, and enhance the overall flexural capacity during car explosion.

In this study, we investigate the growth of EV ownership among Swedish households. Through detailed socio-economic data and the Swedish vehicle register, we are able compare characteristics of households that bought an EV in 2016 with those that became EV owners in 2020. We are thus able to describe and analyse the transition from the early EV owners to the early majority. Unlike many prior studies in the field, which are based on surveys or interviews, this study relies on registry data, thereby encompassing all car owners in Sweden. In this study, we have also scrutinized the significance of ownership mode by distinguishing between households that have chosen to purchase a car and those that have chosen to lease one. The results show that the demand for EVs has reached new consumer groups, e.g. both younger and older car buyers, and that the option to lease a car privately has broadened the market for new cars in general, and for EV’s in particular.

The p53 tumor suppressor protein shows antiviral activity. The replication of viruses is also antagonized by interferons (IFNs) – cytokines, which control immunity genes by the STAT transcription factors. The best studied interferons belong to type I (e.g. IFNα) and type II (IFNγ) groups. IFNα and IFNγ both induce activating phosphorylation of STAT1 on Tyr701. Previously, we noticed that p53 activates SOCS1, which is a negative regulator of STAT1 phosphorylation. Thus, we hypothesized that p53 by activating SOCS1 expression reduces phosphorylation of STAT1 and attenuates activation of genes stimulated either by IFNα or IFNγ. To test this hypothesis, we exposed p53-proficient and p53-deficient cells to strong p53 activators, and either to IFNα or IFNγ. Subsequently, we estimated the phosphorylation status of STAT1 and the expression of genes regulated by either of these cytokines. Strong activation of p53 reduced the phosphorylation of STAT1 on Tyr701, however surprisingly it did not lead to reduced expression of most tested interferon-stimulated genes. On contrary, p53 and IFNγ synergized in the activation of CASP1, IFIT1 and IFIT3 genes. We conclude that the interactions between p53 and interferon-activated pathways are more complicated than initially expected, but the apparent cooperation between p53 and IFNγ deserves further studies.

Tunnel-interchange connecting sections pose significant safety challenges on mountainous expressways due to their high incidence of accidents. Improving road safety necessitates a comprehensive understanding of driver behavior in such areas. This study explores the influences of road characteristics, signage information volume, and traffic conditions on drivers' car-following and lane-changing behavior in tunnel-interchange diverging areas. Utilizing driving data from 25 subjects of 72 simulated road models, driving performance is assessed using Friedman rank test and multivariate variance analysis. The results highlight the significant influence of both connection distance and signage information load on driving behavior. In tunnel-interchange scenarios, the reduction of velocity increased by 62.61%, and speed variability surged by 61.11%, indicating potential adverse effects on driving stability due to the environmental transitions. Decreased connection distances are associated with reduced lane-changing durations, larger steering angles, and increased failure rates. Furthermore, every two units increase in signage information leads to a 13.16% rise in maximum deceleration and a 5% increase in time headway. Notably, the signage information volume shows a significant interaction with connection distance (F=1.60, P=0.045) for most car-following indicators. Hence, the study recommends a maximum connection distance of 700 m and signage information not exceeding nine units for optimal safety and stability.

This paper presents a comprehensive simulation study of Automated Guided Vehicles (AGVs) in a fabricated production environment for toy car assembly. This paper uses Petri Nets for modeling and the General Petri Net Simulator (GPenSIM) for model implementation on MATLAB and simulation. The primary focus of this research is to analyze the operational efficiency of AGVs under varying conditions, particularly examining the impact of battery charge reduction rates and the strategic placement of charging stations within the production line. By employing Colored Petri Nets (CPN) within GPenSIM, we have developed a detailed and dynamic model that captures the intricate movements and interactions of AGVs in a simulated manufacturing setting. By presenting an approach to simulating AGVs in a production environment, this paper specifically focuses on two critical operational parameters: the battery charge reduction rate of AGVs and the number of charging stations available in the production line. Unlike previous studies that have primarily concentrated on general path planning or bottleneck detection in manufacturing systems, this paper delves into the intricate balance between AGV operational efficiency and the logistical constraints imposed by battery life and charging infrastructure.

Lymphocyte collection by apheresis for CAR-T production usually does not include mobilized blood using Granulocyte Colony Stimulating Factor (G-CSF) due to the widespread knowledge that it causes a decrease in the number and functionality of lymphocytes. However, it is used for stem cell transplant, which is a common treatment for hematological malignancies. The growing demand for CAR therapies (CAR-T and NK-CAR), both in research and clinic, makes necessary to evaluate whether mobilized PBSC products may be potential candidates for use in such therapies. This review collects recent work that experimentally verifies the role and functionality of T and NK lymphocytes, and the generation of CAR-T, from apheresis after G-CSF mobilization. As discussed, T cells do not vary significantly in their phenotype, the ratio of CD4+ and CD8+ remains constant and the different sub-populations remain stable. In addition, its expansion and proliferation rate are invariant regardless mobilization with G-CSF, as well as the secretion of proinflammatory cytokines and the cytotoxic ability. Therefore, cells mobilized before apheresis are postulated as a new alternative source of T cells for adoptive therapies that will serve to alleviate high demand, increase availability, and take advantage of the substantial number of existing cryopreserved products.

Accurate traffic simulation models play a crucial role in developing intelligent transport systems that offer timely traffic information to users and efficient traffic management. However, calibrating these models to represent real-world traffic conditions accurately poses a significant challenge due to the dynamic nature of traffic flow and the limitations of traditional calibration methods. This article introduces a machine learning-based approach to calibrate macroscopic traffic simulation models using real-time traffic video stream data. By leveraging computer vision technologies to extract key traffic parameters from video streams, the approach demonstrated a notable improvement in aligning the generated data from the calibrated simulation model with car sensor data, achieving an average improvement of over 50% compared to the uncalibrated macroscopic model. Moreover, there was a substantial reduction in data drift for the machine learning model integrated into the virtual transport space using vehicle-to-everything technology, resulting in a more than fourfold decrease in the average absolute error of the model.