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Abstract HPV16 and 18 are positively correlated with cervical carcinogenesis. However, HPV prevalence tends to vary according to region, nationality, and environment. The most prevalent high-risk (HR) HPV genotypes are HPV16, 52, 58, 56, 18, 33, and 45), while the low-risk (LR) genotypes are HPV6 and 11 in the Chinese population. Importantly, undetectable low-copy HPV DNA could be an important indicator of integration into the human genome and may be a precursor to cancer progression. The HPV viral load changes dramatically, either increasing or decreasing rapidly during carcinogenesis, and traditional quantitative real-time PCR (qPCR) cannot accurately capture this subtle change. Therefore, in this study, a reliable droplet digital PCR (ddPCR) method was developed to simultaneously detect and quantify HPV genotypes. The ddPCR quantitative results showed high accuracy, sensitivity, and specificity compared to qPCR results employing the same clinical specimens and supplemented the ddPCR assay for HPV52/56/58/6 genotypes according to the infection specificity of the Chinese population. In summary, this procedure is valuable for quantifying HPV DNA, especially under conditions of low template copy number in cervical intraepithelial neoplasia (CIN) and/or cervical cancer. Additionally, this method can dynamically observe the prognosis and outcome of HPV infection and thus be used as an effective means for real-time monitoring of tumor load.

Abstract Background The updated estimates of hepatitis C virus (HCV) seroprevalence are critical for developing strategies to manage or eliminate HCV infection. Methods A comprehensive study on HCV seroprevalence was conducted among 365,210 patients at Jinan Central Hospital, China, from 2008 to 2020. The patients were tested for anti-HCV, HCV core antigen, hepatitis B surface antigen, syphilis antibody, human immunodeficiency virus antigen + antibody, antihepatitis A virus IgM, and antihepatitis E virus IgM. Results HCV seroprevalence was 0.79% and was related to age. HCV seropositivity was lower in children (aged

The improvement of water usage efficiency and productivity, as well as the development of effective water management plans, necessitates a comprehensive understanding of how water utilization patterns in different soil layers within arid and semi-arid climates impact the capacity of plant roots to absorb water. However, there is currently no knowledge regarding the water use strategies employed by artificial yellow willow. So, we conducted a study on the hydrogen and oxygen isotopic composition of rainfall in yellow willow (Salix gordejevii) from the semi-arid region located at the southern edge of the Hunshandak Sandland in China. This study utilized measured data on xylem water, groundwater, soil moisture, and rainfall. By employing a combination of the direct comparison method and the MixSIAR model, we investigated the water uptake strategies employed by yellow willow throughout its growing season. The findings revealed that the mean δ D was highest in precipitation and lowest in groundwater, whereas the mean δ18O was highest in stem water and lowest in groundwater. The δ D and δ18O fluctuated significantly in precipitation but were steady in groundwater. Because precipitation was significantly less than evaporation, the slope and intercept were lower for the local than global atmospheric precipitation line. Water availability steadily declined with increasing depth. Lower δ18O values were caused by precipitation diluting the soil water. The MixSIAR results indicated that the primary source in May, September, and October was utilized at 19%, 18%, and 18%, respectively. In contrast, the utilization rate of each source varied considerably in June, July, and August (the primary source was utilized at 19%, 18%, and 18%, respectively). Comparatively high rates of water absorption and utilization were observed in June (19% of the total water source), July (18%), and August (23%). Therefore, the vertical distribution of the root system and variations in the soil water content regulate water usage for the yellow willow. To prevent excessive water usage and promote ecosystem restoration with artificial yellow willow plantations in water-limited desert settings, policy makers should consider the patterns of plant water use and soil water availability. By selecting drought-adapted plant species and optimizing irrigation management, it is possible to reduce water wastage and ensure that water is used efficiently for revegetation and ecosystem restoration, avoiding overuse of water and maintaining the sustainability of revegetation in water-stressed desert areas.

Low temperature is the main factor for global natural disasters affecting the growth and distribution of plants, and cotton may be affected by low temperature and cold damage at all growth stages. In addition, the insecticidal resistance of cultivars has been reported to perform poorly or unstably due to adverse environments. The present study aimed to investigate the impact of low temperature on the levels of insecticidal protein in Bacillus thuringiensis (Bt) transgenic cotton plants during the peak boll stage. To achieve this, two Bt cotton cultivars, Sikang1 (SK1) and Sikang3 (SK3), were subjected to different temperature regimes and durations. The findings of the study demonstrated that the expression of insecticidal protein in the boll shell of Bt transgenic cotton plants was significantly inhibited under low-temperature stress. Specifically, in 2020, compared to the CK (27 °C), the insecticidal protein content in the boll shell of SK3 decreased by 28.19% after a 48 h of a 16 °C temperature. These results suggest that low-temperature stress can negatively impact the expression of insecticidal protein in Bt transgenic cotton, highlighting the need for appropriate measures to minimize its adverse effects on cotton production. In addition, the threshold temperature that leads to a significant decrease in the content of insecticidal proteins symbolizes an upward trend as the duration of stress prolongs. Decreased Bt protein content at low temperatures is associated with changes in the N metabolism. The present study revealed a significant positive correlation between the levels of glutamate oxaloacetate transaminase (GOT) and glutamate pyruvate transaminase (GPT) activities, as well as in the soluble protein levels in the boll shell and the content of the Bt protein. On the other hand, a significant negative correlation was observed between the levels of free amino acids, peptidase, and protease activities, as well as of Bt protein content. These findings suggest that, in Bt cotton production, it is crucial to remain vigilant of prolonged low-temperature disasters, which last for over 12 h and drop below 17–20 °C during the peak boll stage. Such conditions may reduce insecticidal resistance, leading to substantial economic losses.

Abstract Background Genomic instability is a hallmark of cancer. The G1 checkpoint allows cells to repair damaged DNA that may lead to genomic instability. The high-risk human papillomavirus (HPV) E7 gene can abrogate the G1 checkpoint, yet the mechanism is still not fully understood. Our recent study showed that WDHD1 (WD repeat and high mobility group [HMG]-box DNA-binding protein 1) plays a role in regulating G1 checkpoint of E7 expressing cells. In this study, we explored the mechanism by which WDHD1 regulates G1 checkpoint in HPV E7 expressing cells. Methods NIKS and RPE1 derived cell lines were used. Real-time PCR, Rescue experiment, FACS and BrdU labeling experiments were performed to examine role of GCN5 in G1 checkpoint abrogation in HPV-16 E7 expressing cells. Results In this study, we observed that WDHD1 facilitates G1 checkpoint abrogation by modulating GCN5 in HPV E7 expressing cells. Notably, depletion of WDHD1 caused G1 arrest while overexpression of GCN5 rescued the inhibitory effects of WDHD1 knockdown on G1/S progression. Furthermore, siWDHD1 significantly decreased cell cycle proliferation and DNA synthesis that was correlated with Akt phosphorylation (p-Akt), which was reversed by GCN5 overexpression in HPV E7 expressing cells. Conclusions In summary, our data identified a WDHD1/GCN5/Akt pathway leading to the abrogation of G1 checkpoint in the presence of damaged DNA, which may cause genomic instability and eventually HPV induced tumorigenesis.

As the third year of the global COVID-19 pandemic, vaccination remains the most effective tool against infections and symptomatic illness. Comprehension regarding immunity to SARS-CoV-2 is limited, and the durability of immune responses after vaccination is currently not clear. In this study, we randomly collected 395 questionnaires to analyze the current state of COVID-19 vaccination. At the same time, the serum of 16 individuals who had received two doses of the COVID-19 vaccine were collected at different times before and after the booster vaccination. We analyzed the dynamic changes of SARS-CoV-2 S-specific binding antibodies in serum and immunological indicators. By collecting public opinion surveys and analyzing variational trends of SARS-CoV-2 S-specific binding antibodies and immune indicators after COVID-19 booster vaccination, we endeavored to demonstrate the concerns affecting people’s booster vaccinations, as well as the frequency, timing, and necessity of COVID-19 booster vaccinations. The analysis of antibody results in 16 vaccinated volunteers showed that the antibody concentration decreased six months after the second dose and the protective effect of the virus was reduced. The third dose of COVID-19 vaccination is necessary to maintain the antibody concentration and the protective effect of the virus. The vaccination with the vaccine booster depends not only on the time interval but also on the initial concentration of the SARS-CoV-2 S-specific binding antibody before the booster. Our study has important implications for raising public awareness of vaccinating against SARS-CoV-2 and the necessity of COVID-19 booster vaccinations.

The global outbreak of SARS-CoV-2 spread rapidly throughout the world which transmitted among humans through various routes. Asymptomatic (carriers) and possible fecal-oral transmission, resulted into a large-scale spread. These issues pose great challenges to disease diagnosis and epidemic control. We obtained data on 29 cases of COVID-19 patients in Jinan, China, and reported the clinical data of asymptomatic patients confirmed with stool samples positive. Some patients with gastrointestinal infections are secondary to pulmonary infections, and during the patients' recovery period, the virus may still existin the patient's gastrointestinal tract over 7 days. We combined with epidemiological and clinical data of asymptomatic patients to analyze the possible routes of viral transmission and infection, including eyes-nose, hands-eyes, fecal-oral, and eyes-oral, et al., thus first presented the two-way transmission through eyes-oral. Through associating infection symptoms with the transmission routes of virus and the patient course of the disease, we expect to provide guidelines for clinical diagnosis and the basis for suppressing the spread of the virus and antiviral treatment.

The early detection and differential diagnosis of respiratory infections increase the chances for successful control of COVID-19 disease. The nucleic acid RT-PCR test is regarded as the current standard for molecular diagnosis. However, the maximal specificity confirmation target ORF1ab gene is considered to be less sensitive than other targets in clinical application. In addition, recent evidence indicated that the initial missed diagnosis of asymptomatic patients with SARS-CoV-2 and discharged patients with "re-examination positive" might be due to low viral load, and the ability of rapid mutation of SARS-CoV-2 also increases the rate of false-negative results. Moreover, the mixed sample nucleic acid detection is helpful in seeking out the early community transmission of SARS-CoV-2 rapidly, but the detection kit needs ultra-high detection sensitivity. Herein, the lowest detection concentration of different nucleic acid detection kits was evaluated and compared to provide direct evidence for the selection of kits for mixed sample detection or make recommendations for the selection of validation kit, which is of great significance for the prevention and control of the current epidemic and the discharge criteria of low viral load patients.

Condyloma acuminatum (CA) is a benign epithelium hyperplasia mainly caused by human papillomavirus (HPV), which is now the second most common viral sexually transmitted infection (STI) in China. In total, 90% of CA patients are caused by the low-risk HPV 6 and 11. Aside from low-risk HPV infection there are likely other factors within the local microenvironment that contribute to CA and there has been related research before. In this study, 62 vaginal specimens were analyzed using 16S rRNA gene sequencing. The diversity of the vaginal microbiota was higher and the composition was different with LR-HPV infection. While the relative abundance of dominant Firmicutes was lower, Actinobacteria, Proteobacteria, and Fusobacteria phyla were significantly higher; at the genus level Gardnerella, Bifidobacterium, Sneathia, Hydrogenophilus, Burkholderia, and Atopobium were higher. This study firstly confirmed a more accurate and comprehensive understanding of the relationship between low-risk HPV infection and vaginal microbiota, in order to provide a theoretical basis for further research on the occurrence and development of CA.

Our study investigated the epidemiology of respiratory viruses in adult patients with upper respiratory tract infection (URTI) between August 2009 and September 2010 in Jinan, northern China. Nasal and throat swabs (n=596) were collected from adult patients with URTIs. Nine respiratory-related viruses, including IFV, PIV, HRV, HMPV, HBoV, HCoV, ADV, RSV, and EV, were detected in all samples by conventional and reverse transcription polymerase chain reactions. Positive detection rate for respiratory virus was 38.76% and codetection rate was 4.70% in adults with acute respiratory tract infections. IFV (20.81%) was the dominant agent detected and IFVB had a higher incidence (12.58%) than IFVA (7.72%). Detection rates of 8.22%, 5.03%, 3.69%, and 2.52% were observed for HBoV, HRV, EV, and RSV, respectively. HCoV had the lowest detection rate of 0.50%. HBoV, HRV, EV, and ADV infection rates were higher in the 14–25-year-old group than in the 26–65-year-old group. Codetection rates were higher (7.52%) in the 14–25-year-old group than in the older age group (2.64%). The spectrum of respiratory virus infection in adult patients with URTIs was different in Jinan compared with other cities in China.

Despite extensive studies on the thermodynamic mechanism governing molecular adsorption at the solid--water interface, a comprehensive understanding of the crucial role of interface properties in mediating the entropy--enthalpy compensation during adsorption is lacking, particularly at a quantitative level. Herein, we employed two types of surface models (hydroxyapatite and graphene) along with a series of amino acids to successfully elucidate how distinct interfacial features dictate the delicate balance between entropy and enthalpy variations. The adsorption of all amino acids on the hydroxyapatite surface is an enthalpy-dominated process, where the water-induced enthalpic component of the free energy and the surface--adsorbate electrostatic interaction term alternatively act as the driving force for adsorption in different regions of the surface. Although favorable interactions are observed between amino acids and the graphene surface, the entropy--enthalpy compensation exhibits dependence on the molecular size of the adsorbates. For small amino acids, favorable enthalpy changes predominantly determine their adsorption behavior; however, larger amino acids tend to bind more tightly with the graphene surface, which is thermodynamically dominated by the entropy variations despite the structural characteristics of amino acids. This study reveals specific entropy--enthalpy mechanisms underlying amino acid adsorption at the solid--liquid interface, providing guidance for surface design and synthesis of new biomolecules. [ABSTRACT FROM AUTHOR]

Remote sensing images (RSIs) spatiotemporal fusion (STF) make a significant contribution to acquisition of RSIs sequence with simultaneously high temporal and spatial resolution, which broadens its application fields. However, the existing RSIs STF methods lack effective strategies for extracting global information and fusion features between different images. Conversely, the existing state-of-the-art (SOTA) methods generally require more than two RSIs from different satellites as reference, which increases the difficulty of data collection and limits the application in practice. To address these problems, this article proposed an end-to-end CNN and Transformer combined RSIs STF model (CTSTFM) based on two reference RSIs. Specifically, the proposed CTSTFM consists of three basic modules: multikernel convolutional transformer encoder (MKCE), cross fusion module (CFM), and convolutional-based compression decoder (CCD). The MKCE combines multikernel channel attention block and multikernel spatial attention block to extract shadow features and long-term interdependencies in reference RSIs. The CFM uses the unique cross exchange transformer block and combine fusion transformer block to enhance the feature fusion results. Due to the powerful encoder and fusion module, in the CCD part we only use a simple design convolution module to save the consumption of computational resources. Experiments on two well-known open access datasets show that CTSTFM achieves competitive results in both qualitative and quantitative comparisons compared to the SOTA methods. Meanwhile, we conduct experiment to analyze the image Tessellation effects and its solution. The effectiveness of the proposed module will be demonstrated through ablation experiments.

Multi-stage attacks are one of the most critical security threats in the current cyberspace. To accurately identify multi-stage attacks, this paper proposes an anomaly-based multi-stage attack detection method. It constructs a Multi-Stage Profile (MSP) by modeling the stable system's normal state to detect attack behaviors. Initially, the method employs Doc2Vec to vectorize alert messages generated by the intrusion detection systems (IDS), extracting profound inter-message correlations. Subsequently, Hidden Markov Models (HMM) are employed to model the normal system state, constructing an MSP, with relevant HMM parameters dynamically acquired via clustering algorithms. Finally, the detection of attacks is achieved by determining the anomaly threshold through the generation probability (GP). To evaluate the performance of the proposed method, experiments were conducted using three public datasets and compared with three advanced multi-stage attack detection methods. The experimental results demonstrate that our method achieves an accuracy of over 99% and precision of 100% in multi-stage attack detection. This confirms the effectiveness of our method in adapting to different attack scenarios and ultimately completing attack detection.

The built environment’s impact on human activities has been a hot issue in urban research. Compared to motorized spaces, the built environment of pedestrian and cycling street spaces dramatically influences people’s travel experience and travel mode choice. The streets’ built environment data play a vital role in urban design and management. However, the multi-source, heterogeneous, and massive data acquisition methods and tools for the built environment have become obstacles for urban design and management. To better realize the data acquisition and for deeper understanding of the urban built environment, this study develops a new portable, low-cost Arduino-based multi-sensor array integrated into a single portable unit for built environment measurements of street cycling spaces. The system consists of five sensors and an Arduino Mega board, aimed at measuring the characteristics of the street cycling space. It takes air quality, human sensation, road quality, and greenery as the detection objects. An integrated particulate matter laser sensor, a light intensity sensor, a temperature and humidity sensor, noise sensors, and an 8K panoramic camera are used for multi-source data acquisition in the street. The device has a mobile power supply display and a secure digital card to improve its portability. The study took Beijing as a sample case. A total of 127.97 G of video data and 4794 Kb of txt records were acquired in 36 working hours using the street built environment data acquisition device. The efficiency rose to 8474.21% compared to last year. As an alternative to conventional hardware used for this similar purpose, the device avoids the need to carry multiple types and models of sensing devices, making it possible to target multi-sensor data-based street built environment research. Second, the device’s power and storage capabilities make it portable, independent, and scalable, accelerating self-motivated development. Third, it dramatically reduces the cost. The device provides a methodological and technological basis for conceptualizing new research scenarios and potential applications.

During the past decades, the potential effects of extremely low-frequency electromagnetic fields (ELF-EMFs) on human health have gained great interest all around the world. Though the International Commission on Non-Ionizing Radiation Protection recommended a 100 μT, and then a 200 μT magnetic field limit, the long-term effects of ELF-EMFs on organisms and systems need to be further investigated. It was reported that both electrotherapy and possible effects on human health could be induced under ELF-EM radiation with varied EM frequencies and fields. This present article intends to systematically review the in vivo experimental outcome and the corresponding mechanisms to shed some light on the safety considerations of ELF-EMFs. This will further advance the subsequent application of electrotherapy in human health.

Background: Several prognostic biomarkers have been validated for acute myeloid leukemia (AML), a heterogeneous hematopoietic malignancy. However, the factors associated with the cumulative incidence of relapse (CIR) and leukemia-free survival (LFS) in real-world patients with AML have not been well defined. Methods: This study examined clinical and mutational data of 246 patients with newly diagnosed AML who received the traditional “3 ​+ ​7” regimen in PLA General Hospital from January 2008 to August 2020. Factors associated with CIR and LFS in patients newly diagnosed with AML were analyzed using next-generation sequencing. Results: Additional sex combs-like 1 (ASXL1) and Serine/arginine-rich splicing factor 2 (SRSF2) mutations were found to be associated with an increased risk of CIR and a reduced LFS in univariate analysis, while only SRSF2 mutations were associated with these factors in the multivariate analysis. Hyperleukocytosis maintained an independent effect on LFS in the multivariate analysis. Hematopoietic stem cell transplantation conferred a significant prognostic benefit on both CIR and LFS in our cohort. Furthermore, we validated the risk classification of patients with AML receiving traditional induction regimens across a broad age range. Based on next-generation sequencing results, we concluded that SRSF2 mutations were predictive of an increased risk of relapse, inferior LFS rates, and non-relapse mortality in patients with newly diagnosed AML. Conclusion: These findings indicate that patients with SRSF2 mutations might not benefit from the conventional “3 ​+ ​7” regimen. Our results may help in developing molecular stratification strategies and could guide treatment decisions for patients with newly diagnosed AML.

Urban green spaces (UGS) play a crucial role in the urban environmental system by aiding in mitigating the urban heat island effect, promoting sustainable urban development, and ensuring the physical and mental well-being of residents. The utilization of remote sensing imagery enables the real-time surveying and mapping of UGS. By analyzing the spatial distribution and spectral information of a UGS, it can be found that the UGS constitutes a kind of low-rank feature. Thus, the accuracy of the UGS segmentation model is not heavily dependent on the depth of neural networks. On the contrary, emphasizing the preservation of more surface texture features and color information contributes significantly to enhancing the model’s segmentation accuracy. In this paper, we proposed a UGS segmentation model, which was specifically designed according to the unique characteristics of a UGS, named the Green Space Reverse Pixel Shuffle Network (GSRPnet). GSRPnet is a straightforward but effective model, which uses an improved RPS-ResNet as the feature extraction backbone network to enhance its ability to extract UGS features. Experiments conducted on GaoFen-2 remote sensing imagery and the Wuhan Dense Labeling Dataset (WHDLD) demonstrate that, in comparison with other methods, GSRPnet achieves superior results in terms of precision, F1-score, intersection over union, and overall accuracy. It demonstrates smoother edge performance in UGS border regions and excels at identifying discrete small-scale UGS. Meanwhile, the ablation experiments validated the correctness of the hypotheses and methods we proposed in this paper. Additionally, GSRPnet’s parameters are merely 17.999 M, and this effectively demonstrates that the improvement in accuracy of GSRPnet is not only determined by an increase in model parameters.

Abstract Background The response rate of the first-line therapy with corticosteroid for acute graft versus host disease (aGVHD) is about 50%, and steroid-refractory disease is associated with high mortality. The improved response rate to the first-line therapy of newly diagnosed aGVHD patients would result in therapeutic benefits. Ruxolitinib, a selective Janus kinase (JAK) 1/2 inhibitor, has been approved for the treatment of steroid-refractory acute GVHD. The addition of ruxolitinib to the first-line therapy may improve the efficacy of corticosteroids. Methods This investigator-initiated, open-label, multicenter, prospective randomized, and controlled two-arm phase II study compares the efficacy and safety of ruxolitinib combined with 1 mg/kg methylprednisolone versus 2 mg/kg methylprednisolone alone in newly diagnosed aGVHD patients. Patients with intermediate or high-risk aGVHD, as defined by the Minnesota aGVHD high-risk score and biomarker algorithm, are eligible for this study. A total of 198 patients will be randomized at a 1:1 ratio and assigned a GVHD risk (intermediate versus high risk) and disease status before transplantation (complete remission versus no complete remission). The primary endpoint is the overall response rate on day 28, which is defined as an improvement of at least one stage in the severity of aGVHD in one organ without deterioration in any other organ or disappearance of any GVHD signs from all organs without requiring new systemic immunosuppressive treatment. The secondary objectives consist of response time, response duration, overall survival, disease-free survival, non-relapse mortality, failure-free survival, and changes in serum levels of proinflammatory cytokines and GVHD-related biomarkers. Discussion This open-label, multicenter, two-arm randomized trial will evaluate whether the addition of ruxolitinib combined with corticosteroid is superior to corticosteroid alone in newly diagnosed high-risk aGVHD. Trial registration ClinicalTrials.gov NCT04061876 (version number: 2019.5.18). Registered on July 16, 2019

Cemetery landscapes are austere and generally require maintenance. The materials and equipment used for maintenance emit greenhouse gases (GHGs). This research aimed to quantify the annual GHG emissions and global warming potential (GWP) indices of traditional and natural cemeteries for more environmentally friendly green and grey facility planning of cemetery areas. Based on life cycle assessment (LCA), in Yorkshire, UK, as an example, traditional cemeteries were found to be mostly established with landscaped cemetery facilities, and natural cemeteries were found to include mostly underground burials covered with wild plants. The average GHG emissions per hm2 in traditional cemetery maintenance (1,552.88 kg/CO2-e) were 1.8 times those in natural cemeteries (870.88 kg/CO2-e). In the cemetery plant community, the mean GHG emissions for grassland maintenance (1,867.65 kg/CO2-e) were 6.7, 2.8 and 2.3 times higher than the woodland, meadow and shrub maintenance values of 280.77, 673.03 and 821.00 kg/CO2-e, respectively. The mean GWP indexes for traditional and natural cemetery green space maintenance were 0.027 and 0.015, respectively, which were generally higher than those for urban green space maintenance (0.010). This research recommends replacing grasslands with wild meadows, reducing the size of ground cemetery facilities and limiting the application of maintenance materials (i.e., irrigation water and pesticides) to reduce the environmental impact of green space in cemeteries.

IntroductionThis research investigated the effects of three psychological needs (competence, autonomy, and relatedness) of self-determination theory (SDT) and automation trust on the intention of users to employ new interaction technology brought by autonomous vehicles (AVs), especially interaction mode and virtual image.MethodThis study focuses on the discussion from the perspective of psychological motivation theory applied to AV interaction technology. With the use of a structured questionnaire, participants completed self-report measures related to these two interaction technologies; a total of 155 drivers’ responses were analyzed.ResultThe results indicated that users’ intentions were directly predicted by their perceived competence, autonomy, and relatedness of SDT and automation trust, which jointly explained at least 66% of the variance in behavioral intention. In addition to these results, the contribution of predictive components to behavioral intention is influenced by the type of interaction technology. Relatedness and competence significantly impacted the behavioral intention to use the interaction mode but not the virtual image.DiscussionThese findings are essential in that they support the necessity of distinguishing between types of AV interaction technology when predicting users’ intentions to use.