This study was aimed to examine the recent trends of antibiotic resistance (AR) prevalence in Staphylococcus aureus isolated from milk of animals with clinical mastitis in areas of the Abruzzo and Molise regions in central Italy. Fifty-four S. aureus isolates could be obtained from routine testing for clinical mastitis agents carried out in the author institution in years 2021 and 2022. These were analyzed for phenotypic resistance to eight antibiotics recommended for testing by European norms and belonging to the antibiotic classes used for mastitis treatment in milk producing animals. Moreover, the presence of 14 transferable genetic determinants encoding resistance to the same antibiotics was analyzed by qPCR tests developed in this study. Phenotypic resistance to non-β-lactams was infrequent, with only one 2022 isolate resistant to clindamycin. However, low level resistance to the β-lactam cefoxitin was observed in 59.2% isolates in both years making these isolates classifiable as methicillin resistant. The AR genotypes detected were blaZ gene (50% 2021 isolates and 44.4% 2022 isolates), ermC/T- aphA3-blaZ (one 2021 isolate), ant6-ermC/T-aphA3-blaZ (one 2021 isolate), ermB-blaZ (one 2022 isolate) and mecA-mph (one 2022 isolate). An interview to the veterinarians who conferred the samples, regarding antimicrobials prescribed for mastitis treatment and criteria of usage, indicated a possible causal relation with the AR test results. The low prevalence of AR genotypes, not increasing in time, most probably reflecting the reported management of antibiotic therapies in farms. However, the frequently observed cefoxitin resistance needs to be explained genotypically, further monitored and limited by modifying antibiotic usage practices. The identification of a mecA positive isolate in 2022 suggests to investigate further if this genotype is emerging locally.

Tumor-infiltrating lymphocytes (TILs) are a valuable indicator of the immune microenvironment that plays the central role in new anticancer drugs. TILs has a strong prognostic role in triple negative breast cancer (TNBC). Little is known about his interaction with Androgen receptor (AR) and Forkhead box A1 (FOXA1). We analyzed the relationships between TIL levels, AR and FOXA1 expression and their clinical significance in TNBC patients. Further, we investigated their interaction with other biomarkers like programmed cell death ligand-1 (PD-L1), Breast Cancer Type 1 susceptibility protein (BRCA1), Poly [ADP-Ribose] Polymerase 1 (PARP1) and Na+/H+ Exchanger Regulatory Factor 1 (NHERF1). The expression of the proteins was evaluated by immunohistochemistry in 124 TNBC samples. TILs were performed adhering to International TILs Working Group 2014 criteria. Cox proportional hazards models were also used to identify risk factors associated with poor prognosis. Multivariate analysis identified TILs as independent prognostic factor of disease free survival (DFS) (p=0.045). A Kaplan-Meyer analysis revealed that the patients with high TILs had a better DFS compared to patients with low TILs (p=0.037), and the phenotypes TILs-/AR+ and TILs-/FOXA1- had a worse DFS (p=0.032, p=0.001 respectively). AR was associated with FOXA1 expression (p=0.007), and the tumors FOXA1+ presented low levels of TILs (p=0.028). A poor DFS was observed for AR+/FOXA1+ tumors compared to other TNBCs (p=0.0117). Low TILs score was associated with poor patients’ survival, and TILs level in combination with AR or FOXA1 expression affected patient’s clinical outcome. In addition, AR+/FOXA1+ phenotype identified a specific subgroup of TNBC patients with poor prognosis. These data may suggest new ways of therapeutic intervention to support current treatments.

With the advancement in AR technology, more education-based applications are being developed using Augmented Reality, which has revolutionized the learning experience. However, in order to determine the application’s impact on student’s motivation, performance and their communication with the lecturer, various studies are conducted. These studies use one of the three research methodologies for data analysis and evaluation. In this systematic review, we have analyzed various research methodologies for system evaluation of the AR learning applications and recorded the student response toward the system. Also, we checked which methodology is preferred by researchers and why. A total number of 25 studies were analyzed which were published during the year of 2015 and 2019. The results indicate that most popular research technique is mixed methodology as it combines both qualitative and quantitative techniques. The purpose of this review is to offer new insights to researchers and provide them with advice about evaluation of AR applications and which tool or technique is more effective.

New onset diabetes mellitus after transplantation (NODAT) is a common complication following solid organ transplantation, with varying incidence rates due to discrepancies in defining NODAT and follow-up duration, alongside modifiable and non-modifiable risk factors. NODAT adversely affects patient survival and graft longevity, warranting early detection, especially in countries experiencing a rise in kidney transplant cases, emphasizing the need for understanding diagnostic criteria, risk factors, pathogenic mechanisms, and post-transplant outcomes.

Androgen deprivation therapy (ADT) has been the mainstay of prostate cancer (PCa) treatment, with success in developing more effective inhibitors of androgen synthesis and antiandrogens in clinical practice. However, hormone deprivation and AR ablation have caused an increase in ADT-insensitive PCas’ associated with poor prognosis. Resistance to ADT arises through various mechanisms, and most castration-resistant PCas’ still rely on the androgen axis, while others become truly androgen receptor (AR)-independent. Our research identified the human tousled-like kinase 1 (TLK1) as a crucial early mediator of PCa cell adaptation to ADT, promoting androgen-independent growth, inhibiting apoptosis, and facilitating cell motility and metastasis. Although explicit, the growing role of TLK1 biology in PCa has remained under-represented and elusive. In this review, we aim to highlight the diverse functions of TLK1 in PCa, shed light on the molecular mechanisms underlying the transition from androgen-sensitive (AS) to an androgen-insensitive (AI) disease mediated by TLK1, and explore potential strategies to counteract this process. Targeting TLK1 and its associated signaling could prevent PCa progression to the incurable metastatic castration-resistant PCa (mCRPC) stage and provide a promising approach to treating PCa.

The concept of a metaverse, a shared virtual space that brings together the physical and digital worlds, has been a topic of interest for decades. With recent advancements in technology, particularly in virtual reality (VR), augmented reality (AR), and blockchain, the metaverse has become a rapidly evolving and promising ecosystem. This paper provides a review of the metaverse, exploring its history, evolution, and current state of development. The paper delves into the different types of the metaverse, including fully immersive VR metaverses, hybrid metaverses that blend the physical and virtual worlds, and decentralized metaverses that are powered by blockchain. Additionally, the paper examines the impact of web 3.0 on the metaverse, as well as the various technologies used to create and sustain the metaverse, including VR, AR, and blockchain. Furthermore, the paper explores the concept of digital ownership and the potential for marketing and commerce within the metaverse. This paper serves as a review of the metaverse and its various components, providing insights into its history, development, and prospects, and is intended to provide a foundation for further research into this exciting and rapidly evolving ecosystem.

The significance of virtual reality (AR/VR/MR) technology stands out because it can be used in various construction fields such as urban design, construction review, maintenance and education, etc. As to prove this, conglomerates such as Facebook, Google, Sony, Microsoft, and Samsung are increasing their investments to preoccupy the virtual reality market and are competing to dominate the contents and platform market. Virtual reality technology has a concept that collectively refers to VR (Virtual Reality), AR (Augmented Reality), and MR (Mixed Reality), but technically, the two technologies are strictly separated. While VR technology is an immersive virtual environment using computer graphic technology, AR technology is a more advanced technology that combines real data and VR data, and MR technology is a technology that combines both AR and VR. In Korea, Republic of, the use of BIM (Building Information Modeling), a 3D information model, becomes mandatory and based on this, the demand for a new market where VR/AR/MR technologies and advanced sensing equipment are combined increases. This study implemented a building maintenance platform using AR based on 5G, and developed matching technology between BIM of the building maintenance platform and AR equipment. Besides this study implemented the technology to enhance the matching rate of the matching technology and carried out the process to enhance the matching rate empirically through continuous tests. As a result, the initial target of 90% matching rate could be improved to 96%. Based on this, it is expected that effective EV (Optimum Life Cycle Cost) could be achieved at a lower cost compared to the previous one by using it for maintenance monitoring after construction and completion of the building, and can be used as an effective solution in the aspect of building maintenance as well.

Background: Recent advances allow the usage of Augmented Reality (AR) for many medical procedures. We perform different AR-assisted knee surgery techniques using optical surgical navigation with ArUco-type artificial marker sensors. Our study aimed to evaluate the system’s accuracy using an in vitro protocol. We hypothesised that the system’s accuracy was equal to or less than 1mm and 1° for distance and angular measurements, respectively. Methods: Our research was an in-vitro laboratory with a 316 L steel model. We evaluated absolute reliability according to the Hopkins criteria with seven independent evaluators. Each observer measured the thirty palpation points and the trademarks to acquire direct angular measurements on three occasions separated by at least two weeks. Results: The accuracy of the system to assess distances had a mean error of 1.203mm and an un-certainty of 2.062, and for the angular values, a mean error of 0.778° and an uncertainty of 1.438. The intraclass correlation coefficient was for all intra-observer and inter-observer almost perfect or perfect. Conclusions: The mean error for the distance’s determination has been statistically larger than 1mm (1.203mm) but with a trivial effect size. The mean error assessing angular values was sta-tistically minor than 1°. Our results are similar to those published by other authors in accuracy analyses of AR systems.

Background: The AR-V7 splice variant is a cause of castration-resistant prostate cancer (CRPC). However, testing for the presence of AR-V7 by RT-PCR shows AR-V7 positivity in healthy individuals. We hypothesized that the positivity reflected contamination by hematopoietic cells. We tried a novel CTC enrichment instrument using Celsee® to clear hematopoietic cells. Methods: We tested whole blood or Celsee-enriched samples for AR-V7 by RT-PCR and included samples from 41 CRPC patients undergoing sequential therapy. We evaluated the associations between AR-V7 status and clinical factors. We evaluated factors affecting AR-V7 positivity. Results: AR-V7 positivity was lower in Celsee-enriched than in whole blood specimens. AR-V7 and clinical factors did not predict the therapy effectiveness. We found no significant differences in the effectiveness of Enz/Abi upon AR-V7 evaluation. All AR-V7 positive patients had resistance to Enz/Abi. DTX, CBZ, and Radium223 treatment showed no significant difference in the treatment effectiveness, regardless of AR-V7 presence. AR-V7 was more frequently positive than EOD2 in cases with bone metastases. Conclusion: Celsee® CTC enrichment suppresses the AR-V7 false positivity. All AR-V7 positive patients presented resistance to Enz/Abi. DTX, CBZ, and Radium223 were effective and remained treatment options. AR-V7 positivity should progressively appear in patients with advanced bone metastases.

Prostate cancer (PCa) is a major cause of cancer-related mortality worldwide, with a rising incidence observed over the years. The androgen receptor (AR) signaling pathway plays a pivotal role in male development and maintaining masculine characteristics. Dysregulation of AR signaling in prostate cancer can lead to disease progression and resistance to standard therapies. Understanding the intricate regulation and function of AR in both healthy and diseased states is crucial for developing effective treatment strategies. This review comprehensively explores the role of androgen receptors in prostate cancer susceptibility, disease progression, and treatment response by analyzing recent literature. An extensive search of peer-reviewed publications in major databases, including PubMed, Scopus, and Web of Science, was conducted using specific keywords related to androgen receptor, prostate cancer, disease progression, and treatment resistance. Relevant conference abstracts and clinical trial reports were also included. The review presents an overview of the role of androgen receptors in prostate cancer initiation, progression, and treatment resistance. It highlights emerging biomarkers associated with AR signaling dysregulation and their potential utility for early detection and personalized treatment approaches. Additionally, recent advances in targeting the AR pathway for novel therapeutic strategies to improve patient outcomes and overcome treatment resistance in advanced prostate cancer are discussed. The findings contribute to a comprehensive understanding of the AR signaling pathway in prostate cancer and offer insights into its multifaceted role in disease development and treatment response. They may pave the way for innovative therapeutic interventions and precision medicine approaches based on specific AR signaling profiles, enhancing patient care and reducing the burden of this lethal disease.

Museums are called to respond to contemporary challenges and contribute to the formation of more progressive societies. One of the major challenges of our time is climate change and museums could construct cocreated narratives around climate and implement targeted actions for the audiences through their sensorial and affective experiences. More specifically, Geology and Palaeontology museums are repositories of knowledge on geoheritage and geoconservation, recognized for their scientific, pedagogical, cultural and recreational values. The educational potential of geological and paleontological exhibits could be used in informal education activities regarding the climate emergency. Taking the above into consideration, this study focuses on both the creation and evaluation of an educational program for the Natural History Museum of Arsakeio Campus at Psychicko.

Background: Prostate cancer remains a significant global health concern, and understanding the molecular drivers of this disease is crucial for developing effective diagnostic and therapeutic strategies. Steroid Receptor Coactivator-3 (SRC-3), a member of the SRC family, has emerged as a key player in prostate cancer pathogenesis. This review comprehensively examine the role of SRC-3 in prostate cancer, encompassing molecular mechanisms, clinical implications, and therapeutic opportunities. Methods: A systematic literature search following PRISMA guidelines was conducted in PubMed, PMC, and other relevant databases to identify studies that investigate SRC-3 in prostate cancer. A total of 67 articles were selected based on predetermined inclusion criteria. Results: 785 articles were retrieved from databases using specific keywords and MeSH terms related to SRC-3 and Prostate Cancer. After removing 461 duplicates, 260 articles were excluded based on title and abstract review. Subsequently, a comprehensive screening by three researchers resulted in 47 relevant articles for this systematic review. We summarize its contributions to AR-mediated transcriptional regulation, tumor growth, and metastasis. Evidence suggests that SRC-3 expression correlates with prostate cancer aggressiveness, disease recurrence, and poor patient outcomes. Its potential as a diagnostic biomarker and therapeutic target is explored, offering insights into personalized medicine approaches. Conclusions: SRC-3 plays a pivotal role in prostate cancer, influencing disease progression and clinical outcomes. Understanding the molecular intricacies of SRC-3 in prostate cancer offers new opportunities for precision medicine and innovative therapeutic approaches. This review provides a comprehensive overview of SRC-3's involvement in prostate cancer, emphasizing its clinical relevance and potential as a therapeutic target, ultimately contributing to improved patient care in the era of personalized oncology.

The rapid growth of virtual reality (VR) and augmented reality (AR) services in various industries has stimulated innovation. This study proposes a research framework and theoretical model based on self-determination theory (SDT) to examine consumers’ purchase intentions for VR and AR service technologies. The research scope includes fashion brands that use VR and AR service technologies. The study employs in-depth interviews to identify the key drivers of VR and AR technologies for fashion brands. The research design uses an online survey of 675 fashion brand consumers to collect questionnaire data employing structural equation modeling (SEM) and fuzzy set qualitative comparative analysis fuzzy-set qualitative comparative analysis (fsQCA) to test the research hypotheses and answer the research questions. This study contributes to understanding consumer technology and psychological perceptions about implementing fashion brands with VR and AR service technologies for future service design and marketing. The research findings show that perceived value, perceived enjoyment, perceived informativeness, presence, and consumer experience affect purchase intention positively when using AR/VR service technologies. Further, the results highlight that perceived value, enjoyment, and informativeness affect consumer experience. The results of the FsQCA show that the causal conditions of perceived value, perceived enjoyment, perceived informativeness, presence, and consumer experience are sufficient and necessary for higher purchase intention for consumers in the fashion brand context.

Background Augmented reality (AR) in surgery can offer an enhanced view of reality through the superimposition of computer-generated digital images on the real environment. It allows surgeons to integrate image visualisation, improving operative efficiency, surgical outcomes, surgical training and patient education. This review aims to evaluate the current status of augmented reality in surgery, surgical training and potential future applications. Methods We performed a non-systematic review of available literature from January 2005 to August 2021 by searching PubMed, EMBASE and the Cochrane library using a combination of terms “augmented reality”, “virtual reality”, “surgery”, “simulation” and “training”. Articles considered for this review were identified by relevant search criteria including title, keywords, abstract, and full-text. Conclusions AR technologies present an exciting new trend with multiple potential applications in surgery. Intraoperative AR systems have shown promise in specialties involving fine movement of organs during surgical procedures, including Neurosurgery, Ears, Nose and Throat and Orthopaedic Surgery. AR has also exhibited the potential to enhance surgical training and improve knowledge acquisition; it can foster international collaborations via telesurgery and telepresence. In the near future, AR will likely work in symbiosis with surgeons, serving as a complex computer-human coalition which can improve patient outcomes, patient education and surgical training.

Scaffoldings play a critical role as temporary structures in supporting construction processes. Accidents at construction sites frequently stem from issues related to scaffoldings, including insufficient support caused by deviations from the construction design, insecure rod connections, or absence of cross bracing, which result in uneven loading and potential collapse, leading to casualties. In this study, we introduce a deep-learning-based, augmented reality (AR)-enabled system called scaffolding assembly deficiency detection system (SADDS) to assist field inspectors in identifying deficiencies in scaffolding assemblies. Inspectors have the flexibility to utilize SADDS through various devices, such as video cameras, mobile phones, or AR goggles (i.e., Microsoft HoloLens 2), for automated detection of deficiencies in scaffolding assemblies. The training test yielded satisfactory results, with a mean average precision of 0.89 and individual precision values of 0.96, 0.82, 0.90, and 0.89 for “qualified” frames and frames with the “missing cross-tie rod,” “missing lower-tie rod,” and “missing footboard” deficiencies, respectively. Field tests conducted at two construction sites demonstrated improved system performance compared to that in the training test. However, these field tests also revealed certain limitations of the SADDS system.

This paper presents a novel dynamic camera parameter control method for position and posture estimation of highly miniaturized AR markers (micro AR markers) using a low cost general camera. The proposed method performs iterative calculation of the marker’s position and posture to converge them to specified accuracy with dynamically updating the camera’s zoom, focus and other parameter values based on the detected marker’s depth distances. For a 10 mm square micro AR marker, the proposed system demonstrated recognition accuracy of better than ±1.0% for depth distance and 2.5∘ for posture angle with a maximum recognition range of 1.0 m. In addition, the iterative calculation time was at most 0.7 seconds in an initial detection of the marker. These experimental results suggest that the proposed method and system can be applied to a robotic precise handling of small objects with low cost.

Augmented reality (AR) offers an accessible, inexpensive, and rich user experience that has the potential to engage end-users in an immersive environment. Along with vivid visualizations coupled with virtual agents, this technology further develops learning interest in end-users, guides them in various tasks, and boosts motivation and productivity. In this study, we leverage the deep penetration of mobile phones in daily lives and their advanced features to design, develop and demonstrate an AR application (CirculAR) that offers unique user-environment interaction in a gamified way. CirculAR combines learning with enjoyment to help end-users understand fundamental sustainability and circular economy principles. The application has been showcased in a controlled environment to heterogenous audiences and has been shown to improve end-user engagement and motivation. First, participants older than 18 were recruited to showcase the technology acceptance and engagement towards circular economy principles through AR. Then, students aged 5 to 15 years old, along with their parents and educators, were invited to a treasure hunt game where our virtual agent ARis guided them through a map full of virtual experiences. Assessment and evaluation were performed through a survey and a questionnaire. The outcome of their analysis showcased an increase in the dedication and enjoyment of the performed activities, engagement and learning attributes given the AR virtual agent supporting functionalities. Observations during showcasing reported a need for more commitment from the younger audience compared to the older one. This application contributes to the discourse on mobile AR as a tool for the education of novel concepts with a high impact on our daily lives and decisions and aims to shed light on the design principles of educative tools.

With the recent developments in augmented reality (AR) technologies comes an increased interest in the use of smart glasses for hands-on training. Whether this interest is turned into market success or not depends at the least on whether the interaction with smart AR glasses satisfies users, an aspect of AR use that so far has received little attention. With this contribution, we seek to change this. The objective of the article, therefore, is to investigate user satisfaction in AR applied to three cases of practical use. User satisfaction of AR can be broken down into satisfaction with the interaction and satisfaction with the delivery device. A total of 142 participants from three different industrial sectors contributed to this study, namely, aeronautics, medicine, and astronautics. In our analysis, we investigated the influence of different factors, such as age, gender, level of education, level of Internet knowledge, and the roles of the participants in the different sectors. Even though users were not familiar with the smart glasses, results show that general computer knowledge has a positive effect on user satisfaction. Further analysis using two-factor interactions shows that there is no significant interaction between the different factors and user satisfaction. The results of the study affirm that the questionnaires developed for user satisfaction of smart glasses and the AR application performed well, but leave room for improvement.

Visualization techniques are a powerful communication tool between construction stakeholders. The advancement of technology from 2D drawings to 3D models, Virtual Reality (VR), and Augmented Reality (AR) has emphasized the crucial role of efficient communication of ideas, designs, and concepts in preventing project delays and other issues in the Architecture, Engineering, and Construction (AEC) industry. Contemporary innovations such as web-based virtual reality cloud platforms that facilitate collaborative AEC projects and Head-mounted Displays that enable the viewing of VR environments are some of the latest technological developments that are emerging in the construction industry. These technological advances have the potential to improve communication, increase project efficiency, and enhance the quality of construction work. The purpose of this research is to identify existing trends and potential future directions by appropriating the state of the art of the intellectual growth of Virtual reality and Augmented Reality. The study used scientometric analysis in reviewing existing publications to scientifically map the evolution of VR and AR in the AEC sector. The study observed an emerging but little amount of publications on VR and AR in construction. While Africa contributes little significance, advancement in VR and AR research is led by United States and America. The study expresses concern over the dearth of research and the low amount of collaborations amongst institutions in diverse countries. The study concludes that VR and AR research in the AEC sector must be afforded the needed focus and attention. In recent times, the global Coronavirus pandemic has shown that technology such as VR and AR is inevitable in the success of a project.

The nuclear receptor superfamily comprises a large group of proteins with functions essential for cell signaling, survival and proliferation. There are multiple distinctions between nuclear superfamily classes defined by hallmark differences in function, ligand binding, tissue specificity, and DNA binding. In this review, we utilize the initial classification system, which defines subfamilies based on structure and functional difference. The defining feature of the nuclear receptor superfamily is that these proteins function as transcription factors. The loss of transcriptional regulation or gain of functioning of these receptors is a hallmark in numerous diseases. For example, in prostate cancer the androgen receptor is a primary target for current prostate cancer therapies. Targeted cancer therapies for nuclear hormone receptors have been more feasible than others to develop due to ligand availability and cell permeability of hormones. To better target these receptors, it is critical to understand their structural and functional regulation. Given that late-stage cancers often develop hormone insensitivity, we will explore the strengths and pitfalls of targeting other transcription factors outside of the nuclear receptor superfamily such as the signal transducer and activator of transcription (STAT).

To assess AR’s role in TNBC treatment, various existing and completed clinical trials targeting AR or co-targeting AR with other pertinent signaling molecules were analyzed. Cyclin-dependent kinase 4/6 (CDK4/6), cytochrome P450 17α-hydroxylase/17,20-lyase (CYP17 lyase), and the phosphatidylinositol 3kinase (PI3K)/protein kinase B (AKT) signaling pathway were some of the most prevalent biomarkers used in combination therapy with AR inhibitors in these trials. Studying how AR functions in tandem with these molecules can have increasing breakthroughs in the treatment options for TNBC. Previous studies have been largely unsuccessful in utilizing AR as the sole drug target for systemic targeted treatment in TNBC. However, there is a lack of other commonly used drug target biomarkers in the treatment of this disease, as well. Thus, analyzing the clinical benefit rate (CBR) within clinical trials that are using combination therapy can prove to be imperative to the progression of improving treatment options and prognoses.

These days, numerous organizations and Analysis Centers (AC) offer various Ambiguity Resolution (AR) products using various methodologies. To use it for time-frequency transfer, there is no associated study. This paper chooses 16 MGEX stations with external high-precision atomic clocks to constitute 15 international time comparison links and uses AR products data from CNES, SGG, CODE, and PRIDE laboratory, using three ambiguity-fixed strategies, to thoroughly evaluate the effects of various strategies and AR products for high-precision time-frequency transfer. We reach the following results by using the IGS final clock product as a reference and comparing it to ambiguity-float. With various ambiguity-fixed procedures, the time stability STD of time transfer is increased for a single GPS, and the improvement ranges from 10% to 40%. The frequency stability has barely improved; up to 40%, the most notable improvement comes from FCB with GRM products. The time stability STD of combinations has improved after the addition of the Galileo system compared to the single GPS, and the improvement ranges from 2% to 9%. Most strategies have improved, while a few techniques have weakened with the GEC (GPS+Galileo+BDS) combination. We feel that the stability has not significantly increased with the system's increase within short-term stability after comparing multiple groups of linkages.

Slave Province in Canada is an Archean granite-supracrustal terrane at the northwestern corner of the Canadian Shield. It is bordered by the Thelon–Taltson orogen (2.0 to 1.9 Ga) to the south-east and the Wopmay orogen (1.9 to 1.8 Ga) to the west. Acasta gneisses exposed in the western-most Slave province and the Wopmay rocks close to the gneisses were collected systematically for K-Ar and laser step-heating 40Ar /39Ar analyses of the biotite and amphibole. The K-Ar biotite ag-es of the four Wopmay samples range from 1816 ± 18 Ma to 1854 ± 26 Ma, which is within the reported U-Pb zircon age range of the Wopmay orogen. The K-Ar biotite ages of the fifteen Acasta gneisses range from 1779 ± 25 Ma to 1877 ± 26 Ma, except for a younger sample (1711 ± 25 Ma). The 40Ar/39Ar biotite analyses of the three samples from the Wopmay orogen give the plateau ages of 1826 ± 21 Ma, 1886 ± 13 Ma, and 1870 ± 18 Ma. On the other hand, the 40Ar/39Ar analyses of the biotite crystals from the Acasta gneiss show a variety of ages. Three samples show the plateau ages of 1877 ± 8 Ma, 1935 ± 14 Ma, and 1951 ± 11 Ma. These plateau ages are a little older than the total gas ages. The 40Ar/39Ar analyses of the amphibole crystals show more varied age rela-tions. The two samples show consistent age relations between the plateau ages (1814 ± 22 Ma and 1964 ± 12 Ma) and the total gas ages (1789 ± 23 Ma and 1967 ± 11 Ma), respectively. Some sam-ples have the apparent old age of 2000 Ma in the middle temperature fractions. These old frac-tions are due to that the originally existed amphibole crystals formed in Archean were affected by the thermal events during the Wopmay orogeny. but did not fully reset. The results suggest that the K-Ar system ages of the biotite and amphibole of the Archean Acasta gneiss that is aged from 4200 to 2600 Ma of zircon U-Pb ages were rejuvenated in the Paleo–Proterozoic ages. The heat source that rejuvenated the K-Ar system ages may have arisen due to the asthenospheric intrusion into the wedge mantle, which took place because of the subduction rollback.

As Automated Driving Systems (ADS) technology gets assimilated into the market, the driver’s obligation will be changed to a supervisory role. A key point to consider is the driver’s engagement in the secondary task to maintain the driver/user in the control loop. The paper’s objective is to monitor driver engagement with a game and identify any impacts the task has on hazard recognition. We designed a driving simulation using Unity3D and incorporated three tasks: No-task, AR-Video, and AR-Game tasks. The driver engaged in an AR object interception game while monitoring the road for threatening road scenarios. From the results, there was less than 1 second difference between the means of gaming task (mean = 2.55s, std = 0.1002s) to no-task (mean = 2.55s, std = 0.1002s). Game scoring followed three profiles/phases: learning, saturation, and decline profile. From the profiles, it is possible to quantify/infer drivers’ engagement with the game task. The paper proposes alternative monitoring that has utility, i.e., entertaining the user. Further experiments AR-Game focusing on real-world car environment will be performed to confirm the performance following the recommendations derived from the current test.

Machine learning (ML) is enabling augmented reality (AR) to gain popularity in various fields, including gaming, entertainment, healthcare, and education. ML enhances AR applications in education by providing accurate visualizations of objects. For AR systems, ML algorithms facilitate the recognition of objects and gestures from kindergarten through university. The purpose of this survey is to provide an overview of various ways in which ML techniques can be applied within the field of AR within education. The first step is to describe the background of AR. In the next step, we will discuss the ML models that are used in AR education applications. Additionally, we discuss how ML is used in AR. Each subgroup’s challenges and solutions can be identified by analyzing these frameworks. In addition, we outline several research gaps and future research directions in ML-based AR frameworks for education.

To determine the metamorphic ages of the accretionary complexes in the Northern Chichibu Belt in SW Japan, K–Ar dating was conducted using weakly metamorphosed sedimentary rocks collected from the Kanto Mountains, Central Japan. Whole-rock ages were obtained for chert and red shale samples, and the mineral ages of fine-grained illite with the grain size less than 4 μm were obtained for chert, red shale, mudstone, acidic tuff, and basic tuff. The K–Ar ages of chert and red shale presented large variations, with systematically older ages compared to those of mudstone and tuff in the same strata. The influence of submarine hydrothermal activities on chert and red shale before subduction is a possible cause of this deviation. The illite samples, which were fractionated into four grain-size classes using a suspension method, yielded older ages and higher illite crystallinity (i.e., smaller values of Kübler’s crystallinity index) for larger grain-size classes. The peak metamorphic ages were determined from the K–Ar ages of the 3–4 μm class illite in mudstone and tuff. The Late Jurassic to the Earliest Cretaceous accretionary complex of the lowest structural unit (Kashiwagi Unit) was dated within a small range between 117–110 Ma, which is distinctly older than the K–Ar ages of white mica reported from the Sanbagawa Belt. The peak metamorphic age of acidic tuff (113 Ma) at the type locality of the Mikabu Greenstones indicates that the subducted Mikabu seamount is a constituent of the Kashiwagi Unit. The peak metamorphic ages of the Manba and Kamiyoshida Units were obtained as 132–107 Ma and 163–144 Ma, respectively. Major structural discontinuity is suggested within the Middle Jurassic accretionary complexes.

Background: We previously found that QNBC tumors are more frequent in African Americans compared to TNBC tumors. To characterize this subtype further, we sought to determine the miRNA-mRNA profile in QNBC patients based on race. Methods: Both miRNA and mRNA expression data were analyzed from TCGA and validated using datasets from the METABRIC, TCGA proteomic, and survival analysis by KMPLOT. Results: miRNA-mRNAs which include FOXA1 and MYC (mir-17/20a targets); GATA3 and CCNG2 (mir-135b targets); CDKN2A, CDK6, and B7-H3 (mir-29c targets); and RUNX3, KLF5, IL1-β, and CTNNB1 (mir-375 targets) were correlated with basal-like and immune subtypes in QNBC patients and associated with a worse survival. Conclusion: Thus, QNBC tumors have an altered gene signature implicated in racial disparity and poor survival.

This report is considered different aspects of the concept of the networked distributed engine control system (DECS) of future air vehicles. These aspects include the following: the structure of multiple networks similar to NATO Generic Vehicle Architecture (NGVA), the role of Artificial Intelligence (AI) in DECS, and the use Augmented Reality (AR) as Human-Machine Interface between AI and pilots. Deployment of AI solutions for monitoring equipment in on-board infrastructure can be provided on physical or virtual servers and in the clouds. In this case, it is possible to use various methods of alerting the pilot and ground personnel on the basis of AR. The use of AI allows covering an unlimited set of scenarios, to provide an assessment of the likelihood of equipment failure, classification alarm is normal, and recognition of the development of defects. To collect Big Data from sensors and the pre-processing of this data before a machine learning (ML) procedure it is proposed to form data sets with the help of the face-splitting matrix product. To decrease the time of reaction of Neural Networks it has been suggested the implementation of advanced tensor-matrix theory on the basis of penetrating face product of matrices. Other important results of the report are a possible version of the AR data format for DECS and a proposal about the use of non-orthogonal frequency discrete multiplexing (N-OFDM) signals to data transfer via fibre optics.

In contemporary design practices, there is a disconnect between the design techniques used for early-stage design experimentation and performance analysis, and those used for the manufacture and construction. This study addresses the problems in developing an integrated digital design workflow and provides a research framework for integrating environmental performance requirements with robotic manufacturing processes on a construction site. The proposed method enables the user to import a design surface, identify design parameters, set several environmental performance goals, and thereafter simulate and select a robotic building strategy. Based on these inputs, design alternatives are developed and evaluated, considering their robotically simulated constructibility, in terms of their performance criteria. To validate the proposed method, the design is evaluated in an experiment wherein a double-skin facade perforation is generated using the proposed methodology. The results suggest a heuristic feature to improve the simulated robotic constructibility. Moreover, the functionality of the prototype is demonstrated.

In contemporary design practices, there is a disconnect between the design techniques used for early-stage design experimentation and performance analysis, and those used for the manufacture and construction. This study addresses the problems in developing an integrated digital design workflow and provides a research framework for integrating environmental performance requirements with robotic manufacturing processes on a construction site. The proposed method enables the user to import a design surface, identify design parameters, set several environmental performance goals, and thereafter simulate and select a robotic building strategy. Based on these inputs, design alternatives are developed and evaluated, considering their robotically simulated constructibility, in terms of their performance criteria. To validate the proposed method, the design is evaluated in an experiment wherein a double-skin facade perforation is generated using the proposed methodology. Initial results suggest a heuristic feature to improve the simulated robotic constructibility. Moreover, the functionality of the prototype is demonstrated.

Brain-Computer Interface (BCI) systems can assist physically challenged people to interact with their surroundings and improve the quality of their lives. Decoding human thoughts is a powerful technique that can assist paralyzed people who have lost their speech production ability. Speaking is a combined process involving synchronizing the brain and the oral articulators. This paper proposed a high-accuracy brain wave pattern recognition based on inner speech using a novel feature extraction method. Only eight EEG electrodes were used in this study, and they were set on selected spots on the scalp. Support Vector Machine (SVM) was employed to decode the recorded EEG dataset into four internally spoken words which are: Up, Down, Left, and Right. The proposed approach achieved overall classification accuracy that ranges between 96.20% to 97.5%. In addition, more performance evaluation metrics were estimated to test the reliability of classifying the EEG-based inner speech data, and we obtained 97.61%, 97.50%, and 97.73% for F1-score, recall, and precision respectively. Furthermore, the Area Under Curve of the Receiver Operating Characteristic (AUC-ROC) proved the strength of the proposed approach for classifying the specified inner speech commands by achieving a macro-average amount of 99.32%. The inner speech classification method using electroencephalography proposed in this work can clinically help improve communication for patients with problems including speech disorder, mutism, cognitive development, executive function, and psychopathology.

Despite the proliferation of Blockchain Metaverse projects, the inclusion of physically disabled individuals in the Metaverse remains distant, with limited standards and regulations in place. However, the article proposes a concept of the Metaverse that leverages emerging technologies, such as Virtual and Augmented Reality, and the Internet of Things, to enable greater engagement of disabled creatives. This approach aims to enhance inclusiveness in the Metaverse landscape. Based on the findings, the paper concludes that the active involvement of physically disabled individuals in the design and development of Metaverse platforms is crucial for promoting inclusivity. The proposed framework for accessibility and inclusiveness in Virtual, Augmented, and Mixed realities of decentralised Metaverses provides a basis for the meaningful participation of disabled creatives. The article emphasises the importance of addressing the mechanisms for art production by individuals with disabilities in the emerging Metaverse landscape. Additionally, it highlights the need for further research and collaboration to establish standards and regulations that facilitate the inclusion of physically disabled individuals in Metaverse projects.

: Sputtering of silicon in a Helium magnetron discharge (MS) has been reported as a bottom-up procedure to obtain He-charged silicon films (i.e. He nanobubbles encapsulated in a silicon matrix). The incorporation of heavier noble gases is demonstrated in this work with a synergistic effect producing increased Ne and Ar incorporations when using He-Ne and He-Ar gas mixtures in the MS process. Microstructural and chemical characterizations are reported by ion beam analysis (IBA) and scanning and transmission electron microscopies (SEM and TEM). In addition to gas incorporation, helium promotes the formation of larger nanobubbles. For the case of Ne high resolution X-ray photoelectron and absorption spectroscopies (XPS and XAS) are reported with remarkable dependence of the Ne 1s photoemission and the Ne K-edge absorption on the nanobubbles size and composition. The gas (He, Ne, Ar) charged thin films are proposed as “solid” targets for the characterization of spectroscopic properties of noble gases in a confined state without the need for cryogenics or high-pressure anvils devices. Also their use as targets for nuclear reaction studies is foreseen.

We report a preliminary exploration on the low-pressure Ar-O2 plasma generated by low-frequency alternating current (AC) power supply in the low-temperature Plasma Experimental Power Supply (CTP-2000S) for the first time. The electron density 〖(n〗_e), the electron temperature 〖(T〗_e) and the electron energy distribution function (EEDF) are measured by the single Langmuir probe in this experiment. Experimental results show that the ne increases with gas pressure rising, while the ne decreases with the oxygen concentrations rising. And, a plasma density peak is also observed with the AC power supply increase. A comparison between this work and the previous results by RF source suggests that the low-frequency AC power supply may be very fruitful exploration to generate the low-pressure plasma.