Current lifestyles and technologies have inspired new ways to manage home appliances free of restrictions previously imposed by distance and time. So-called home automation technologies allow users to control and schedule common home tasks, often without human intervention. Several types of home automation systems have been proposed and classified according to their functionality, mode of user interaction, scheduling systems and cost-effectiveness. This paper reviews proposals in the smart home field from the last five years, considering both technical and functional aspects. The paper seeks to define automated or smart home systems by identifying common aspects of current such systems.

Stretchable electronic devices hold the potential to revolutionize noninvasive healthcare diagnostics and treatments. Current clinical healthcare technologies are of limited use in ambulatory, long-term settings. A new class of epidermal electronics is designed to conform closely to and with the irregular shape of the human body is emerging, providing an improved functional interface even during motion, while being imperceptible to the user. This review discusses challenges associated with long-term interactions between electronic devices and the skin without interfering with its regulatory and protective function. We report on the current state of the art of monitoring devices for the detection of temperature, motion, biopotentials or biomarkers alongside therapeutic approaches for thermal treatment or drug delivery. In particular, focus is brought on the long-term application of such devices with the associated challenges in terms of materials, wearability, communication and energy supply. With a number of obstacles left to tackle, epidermal stretchable electronics represents a powerful tool in the rising field of personalized medicine.

Play in the reading room: Utilizing soft modeling compound to teach musculoskeletal anatomy and pathology.

Abstract To realize that the residual current device can accurately and quickly detect the fault when the fluctuating DC residual current occurs in the system and improve the system’s safety, a DC residual current detection and protection method based on VMD was proposed. Particle Swarm Optimization (PSO) was used to optimize the penalty factor and the number of decomposition layers of VMD. The minimum envelope entropy of the residual current signal is used as the fitness function to obtain the optimal combination. The criterion of fault occurrence is established based on the optimal modal component mutation characteristic of the residual current decomposed by VMD. Experiments show that this method can identify faults quickly and effectively when pulsating DC residual current is generated in the system.

Deep learning (DL) is the basis of many applications of artificial intelligence (AI), and cloud service is the main way of modern computer capabilities. DL functions provided by cloud services have attracted great attention. At present, the application of AI in various fields of life is gradually playing an important role, and the demand and enthusiasm of governments at all levels for building AI computing capacity are also growing. The AI logic evaluation process is often based on complex algorithms that use or generate large amounts of data. Due to the higher requirements for the data processing and storage capacity of the device itself, which are often not fully realized by humans because the current data processing technology and information storage technology are relatively backward, this has become an obstacle to the further development of AI cloud services. Therefore, this paper has studied the requirements and objectives of the cloud service system under AI by analyzing the operation characteristics, service mode and current situation of DL, constructed design principles according to its requirements, and finally designed and implemented a cloud service system, thereby improving the algorithm scheduling quality of the cloud service system. The data processing capacity, resource allocation capacity and security management capacity of the AI cloud service system were superior to the original cloud service system. Among them, the data processing capacity of AI cloud service system was 7.3% higher than the original cloud service system; the resource allocation capacity of AI cloud service system was 6.7% higher than the original cloud service system; the security management capacity of AI cloud service system was 8.9% higher than the original cloud service system. In conclusion, DL plays an important role in the construction of AI cloud service system.

Vascular networks have an important role to play in transporting nutrients, oxygen, metabolic wastes and maintenance of homeostasis. Bioprinting is a promising technology as it is able to fabricate complex, specific multi-cellular constructs with precision. In addition, current technology allows precise depositions of individual cells, growth factors and biochemical signals to enhance vascular growth. Fabrication of vascularized constructs has remained as a main challenge till date but it is deemed as an important stepping stone to bring organ engineering to a higher level. However, with the ever advancing bioprinting technology and knowledge of biomaterials, it is expected that bioprinting can be a viable solution for this problem. This article presents an overview of the biofabrication of vascular and vascularized constructs, the different techniques used in vascular engineering such as extrusion-based, droplet-based and laser-based bioprinting techniques, and the future prospects of bioprinting of artificial blood vessels.

: In recent years, substantial modelling breakthroughs have been achieved in artificial intelligence due to new algorithms, improved computer power, and expanded storage capacity. These factors have made it possible to process large amounts of data in a short amount of time. By using quantum computing in conjunction with deep learning models, it has been possible to explain the characteristics of ligands and their interactions with biological targets. This contributes to the process of ligand identification and ultimately results in the optimization of drug design. This review explains the extensive use of quantum deep learning in the development of drug design from traditional to quantum-powered deep learning neural networks that cover some domains like variational quantum Eigen solver, variational quantum circuits, quantum convolutional deep neural networks, QC-based deep neural networks for QSAR, as well as quantized generative models for the discovery of small drug molecules. Quantum computing can execute incredible computational work tenfold faster than current technology, transforming drug design, development, and post-marketing surveillance. This will reduce the time and resources needed to develop a medicine. Scientific research is moving toward quantum computing since it is anticipated that QC-based deep learning technologies can predict and mimic the characteristics, structures, and activities of molecules more efficiently than different ML techniques or conventional computers.

Machine learning is a relatively new field. With the deepening of people's research in this field, the application of machine learning is increasingly extensive. On the other hand, with the development of science and technology, image has become an indispensable medium of information transmission, and image processing technology is also booming. This paper introduces machine learning into image processing, and studies the image processing technology based on machine learning. This paper summarizes the current popular image processing technology, compares various image technology in detail, and explains the limitations of each image processing method. In addition, on the basis of image processing, this paper introduces machine learning algorithm, applies convolution neural network to feature extraction of image processing, and carries out simulation test. In the test, we select voc2007 dataset for image segmentation, Imagenet dataset for target detection, cifar100 dataset for image classification, and ROC curve for performance evaluation. The results show that the algorithm based on deep learning can achieve high accuracy in image segmentation, classification and target detection. The accuracy of image segmentation is 0.984, the accuracy of image classification is 0.987, and the accuracy of target detection is 0.986. Image processing based on machine learning has great advantages.

Spatial User Interfaces along the Reality-Virtuality continuum heavily depend on accurate depth perception. However, current display technologies still exhibit shortcomings in the simulation of accurate depth cues, and these shortcomings also vary between Virtual or Augmented Reality (VR, AR: eXtended Reality (XR) for short). This article compares depth perception between VR and Video See-Through (VST) AR. We developed a digital twin of an existing office room where users had top erform five depth-dependent tasks in VR and VST AR. Thirty-two participants took part in a user study using a 1 × 4 within-subjects design. Our results reveal higher misjudgment rates in VST AR due to conflicting depth cues between virtual and physical content. Increased head movements observed in participants were interpreted as a compensatory response to these conflicting cues. Furthermore, a longer task completion time in the VST AR condition indicates a lower task performance in VST AR. Interestingly, while participants rated the VR condition as easier and contrary to the increased misjudgments and lower performance with the VST AR display, a majority still expressed a preference for the VST AR experience. We discuss and explain these findings with the high visual dominance and referential power of the physical content in the VST AR condition, leading to a higher spatial presence and plausibility.

We present ProtoColVR, a methodology and a plugin designed for gathering requirements and collaborative rapid prototyping of virtual reality training simulators. Our methodology outlines the utilization of current technologies, the involvement of stakeholders during design and development, and the implementation of simulator creation through multiple iterations. We incorporate open-source tools and freely available environments like Twine and Unity to establish a reference implementation for requirements gathering and rapid prototyping. ProtoColVR is the outcome of our collaboration with a hospital and our Navy, and it has undergone testing in a development Jam. From these tests, we have gained valuable insights, including the ability to create functional prototypes within multidisciplinary teams, enhance communication among different roles, and streamline requirements gathering while improving our understanding of the virtualized environment.

This paper reviews the literature available on the subject of the durability of concrete sewer pipes and the corresponding rehabilitation technologies. An introduction related to the importance of the sewer system in urban life and its durability issues was first discussed as most people did not recognise the scale and complexity of the underground sewer system. Then the recent development of alternative binder materials or filler materials to improve the acid resistance of concrete was specified. For instance, the effects of alternative binders on the hydration products and the mechanism of biogenic corrosion were discussed in detail. The paper ends with the current rehabilitation technologies and the structural performance of rehabilitated sewer pipes. Also, some suggestions associated with future research were made.

The aim of the study was to investigate the influence of age diversity on organization performance at the Kenya Urban Roads Authority. The study was conducted at Kenya Urban Roads Authority (KURA) Headquarters, in Nairobi and the target population was all categories of employees of KURA. A descriptive research design was used in this study. The method employed was stratified random sampling. The population of the study was 150 and the sample size was 30% of the population which translated to 45 respondents. In order to collect data, structured questionnaires were issued to respondents. A pilot test was done to determine the questionnaire's validity and reliability. Data was analyzed through descriptive and inferential analysis. The multiple regression results showed that age diversity account for up to 41.3% of the variation in organizational performance of KURA. As a result, the study recommends the HR department of KURA to improve age diversity in the organization by increasing the rate of adoption of such practices as mixing the youthful employees' skill with high-tech instruments in order to assist older employees in improving their knowledge of current technologies encouraging the younger employees to take risks in order to contribute to the success of the authority and encouraging the older employees to mentor young employees in acquiring job skills.

The maritime industry is a significant component of the transportation sector. Ships are the major element of the maritime industry, and propulsion power comes from fossil fuels, such as heavy fuel oil or marine diesel oil. These fossil fuels are used in conventional marine diesel engines and result in high levels of harmful emissions. These emissions contribute to the greenhouse effect and global warming, which is why efforts have been made to regulate and limit them within specific boundaries through various rules and regulations. However, with current technology, it is not possible to stay within these regulations. Therefore, the maritime sector has embarked on the quest for alternative power sources, and as a result, alternative fuels and fuel cells have gained importance. Hydrogen, one of these alternative fuels, is a promising solution with a carbon-free structure for the maritime industry to move toward sustainability. However, ships are considered high-risk areas, which is why specific standards need to be established for the use of hydrogen and fuel cell technology in ships. Hydrogen bunkering, onboard storage, and power system design, limits, and operational aspects must be properly elaborated. Although there are several substantial international standards and regulations for gas, liquid, and dangerous cargo, there is a lack of specific and detailed regulations for the use of fuel cells and hydrogen fuel onboard ships. This paper reviews the relevant regulations and standards while showing the regulatory gap concerning hydrogen and fuel cells by discussing the main barriers and highlights the current and future agenda of the industry toward decarbonization vision.

The development of unmanned agricultural tractors (UAT) represents a significant step towards intelligent agricultural equipment. UAT technology is expected to lighten the workload of laborers and enhance the accuracy and efficiency of mechanized operations. Through the investigation of 123 relevant studies in the literature published in recent years, this article reviews three aspects of autonomous navigation technologies for UATs: perception, path planning and tracking, and motion control. The advantages and deficiencies of these technologies in the context of UATs are clarified by analyzing technical principles and the status of current research. We conduct summaries and analyses of existing unmanned navigation solutions for different application scenarios in order to identify current bottleneck issues. Based on the analysis of the applicability of autonomous navigation technologies in UATs, it can be seen that fruitful research progress has been achieved. The review also summarizes the common problems seen in current UAT technologies. The application of research to the sharing and integrating of multi-source data for autonomous navigation has so far been relatively weak. There is an urgent need for high-precision and high-stability sensing equipment. The universality of path planning methods and the efficiency and precision of path tracking need to be improved, and it is also necessary to develop highly reliable electrical control modules to enhance motion control performance. Overall, advanced sensors, high-performance intelligent algorithms, and reliable electrical control hardware are key factors in promoting the development of UAT technology.

Abstract Introduction: The tumor microenvironment (TME) is a dynamic and multifaceted system that comprises largely myeloid lineage immune cells including monocytes, neutrophils, macrophages, and dendritic cells. Reprogramming the myeloid compartment within the context of cancer therapy presents an attractive strategy to overcome current limitations in solid tumor treatment. We have developed a novel approach that harnesses the natural ability of Myeloid cells to take up mRNA loaded lipid nanoparticles, to reprogram these cells with chimeric antigen receptors (CAR’s) that arm these cells to recognize and kill tumor cells. Methods: Current LNPs technology is sufficient to deliver significant mRNA cargo to numerous cell types, including B cells, T cells and myeloid cells. Leveraging this phenomenon we have developed a new class of chimeric antigen receptors (CARs), using protein biology that imparts targeted immune cell expression and functionality, specifically in Myeloid cells. These CARs harness Immunoreceptor Tyrosine-based Activation Motif (ITAM) signaling adaptors expressed exclusively in immune cells, achieving immune cell-type specific CAR-directed tumor lysis and cytokine responses. With a FcaR I (CD89) based CAR design, we have developed a CAR that is dependent on the common Fc receptor gamma chain, primarily restricted to myeloid cells, for stable expression and function. Results: We have demonstrated specific expression of CD89-based CAR in myeloid cells in mouse and monkey following systemic mRNA/LNP delivery, and in human myeloid cells following in vitro treatment with mRNA/LNPs. Systemic mRNA/LNP delivery of CD89-based CAR has demonstrated robust anti-tumor efficacy against multiple tumor antigens in various xenograft mouse models of human breast cancer, hepatocellular carcinoma, and ovarian cancer. Furthermore, in syngeneic mouse tumor models, robust anti-tumor immune responses, characterized by tumoral infiltration of activated CD8+ T cells, diminished tumor-associated Tregs, systemic enhancement of dendritic cells and anti-tumor IgG production, were observed for treated animals. Conclusions: Taken together, we present CAR designs that achieve expression and function in targeted immune cell populations, capable of eliciting anti-tumor efficacy against multiple target antigens by leveraging innate and adaptive immune responses, and demonstrating a class of novel CAR designs to overcome limitations faced by current in vivo mRNA/LNP delivery strategy. A phase I clinical trial is currently on-going to assess the safety and preliminary efficacy of CD89-based CAR against TROP2+ epithelial malignancies. Citation Format: Shannon Argueta, Franciele K. Melber, Michael Gorgievski, Neha Divangi, Edward Cochran, Thach Chu, Yuxiao Wang, Jian Ding, Daniel Getts. In vivo immune cell programming using mRNA-LNP chimeric antigen receptors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1321.

Life cycle assessment of single cell protein production–A review of current technologies and emerging challenges

There have been significant advances in the flexibility and power of in vitro cell-free translation systems. The increasing ability to incorporate noncanonical amino acids and complement translation with recombinant enzymes has enabled cell-free production of peptide-based natural products (NPs) and NP-like molecules. We anticipate that many more such compounds and analogs might be accessed in this way. To assess the peptide NP space that is directly accessible to current cell-free technologies, we developed a peptide parsing algorithm that breaks down peptide NPs into building blocks based on ribosomal translation logic. Using the resultant data set, we broadly analyze the biophysical properties of these privileged compounds and perform a retrobiosynthetic analysis to predict which peptide NPs could be directly synthesized in augmented cell-free translation reactions. We then tested these predictions by preparing a library of highly modified peptide NPs. Two macrocyclases, PatG and PCY1, were used to effect the head-to-tail macrocyclization of candidate NPs. This retrobiosynthetic analysis identified a collection of high-priority building blocks that are enriched throughout peptide NPs, yet they had not previously been tested in cell-free translation. To expand the cell-free toolbox into this space, we established, optimized, and characterized the flexizyme-enabled ribosomal incorporation of piperazic acids. Overall, these results demonstrate the feasibility of cell-free translation for peptide NP total synthesis while expanding the limits of the technology. This work provides a novel computational tool for exploration of peptide NP chemical space, that could be expanded in the future to allow design of ribosomal biosynthetic pathways for NPs and NP-like molecules.

Point-of-care monitoring of small molecules in biofluids is crucial for clinical diagnosis and treatment. However, the inherent low degree of recognition of small molecules and the complex composition of biofluids present significant obstacles for current detection technologies. Although nanopore sensing excels in the analysis of small molecules, the direct detection of small molecules in complex biofluids remains a challenge. In this study, we present a method for sensing the small molecule drug gentamicin in whole blood based on the mechanosensitive channel of small conductance in Pseudomonas aeruginosa (PaMscS) nanopore. PaMscS can directly detect gentamicin and distinguish its main components with only a monomethyl difference. The 'molecular sieve' structure of PaMscS enables the direct measurement of gentamicin in human whole blood within 10 min. Furthermore, a continuous monitoring device constructed based on PaMscS achieved continuous monitoring of gentamicin in live rats for approximately 2.5 h without blood consumption, while the drug components can be analyzed in situ. This approach enables rapid and convenient drug monitoring with single-molecule level resolution, which can significantly lower the threshold for drug concentration monitoring and promote more efficient drug use. Moreover, this work also lays the foundation for the future development of continuous monitoring technology with single-molecule level resolution in the living body.

A neurovascular conflict (NVC) is considered the cause of trigeminal neuralgia (TN) in 75% of cases, and if so, a microvascular decompression (MVD) can lead to significant pain relief. A reliable preoperative detection of NVC is essential for clinical decision-making and surgical planning, making detailed neuroradiologic imaging an important component. We present our experiences and clinical outcomes with preoperative planning of the MVD procedure in a virtual reality (VR) environment, based on magnetic resonance imaging (MRI) including magnetic resonance angiography (MRA) and magnetic resonance venography (MRV) sequences. We analyzed the data of 30 consecutive MVDs in patients treated for TN, in a retrospective single-surgeon (R.A. Kockro) study. Out of the 30 cases, 26 were included. Preoperatively, MRA/MRV and MRI series were fused and three dimensionally reconstructed in a VR environment. All critical structures such as the trigeminal nerve as well as the arteries and veins of the cerebellopontine angle, the brainstem, the neighboring cranial nerves, and the transverse and sigmoid sinus were segmented. The NVC was visualized and a simulation of a retrosigmoid approach, with varying trajectories, to the NVC was performed. The intraoperative findings were then compared with the data of the simulation. The clinical outcome was assessed by a detailed review of medical reports, and follow-up-interviews were conducted in all available patients (20/26). The VR planning was well integrated into the clinical workflow, and imaging processing time was 30 to 40 minutes. There was a sole arterial conflict in 13 patients, a venous conflict in 4 patients, and a combined arteriovenous conflict in 9 patients. The preoperative simulations provided a precise visualization of the anatomical relationships of the offending vessels and the trigeminal nerves as well as the surrounding structures. For each case, the approach along the most suitable surgical corridor was simulated and the exact steps of the decompression were planned. The NVC and the anatomy of the cerebellopontine angle as seen intraoperatively matched with the preoperative simulations in all cases and the MVC could be performed as planned. At follow-up, 92.3% (24/26) of patients were pain free and all the patients who completed the questionnaire would undergo the surgery again (20/20). The surgical complication rate was zero. Current imaging technology allows detailed preoperative visualization of the pathoanatomical spatial relationships in cases of TN. 3D interactive VR technology allows establishing a clear dissection and decompression strategy, resulting in safe vascular microsurgery and excellent clinical results.

Abstract3D inkjet printing is a fast, reliable, and non‐contact bottom–up approach to printing small and large models and is one of the fastest additive manufacturing technologies available. These attributes position inkjet printing as a promising tool for the additive manufacturing of biomaterials, for example, tissue engineering scaffolds. However, due to the stringent technical rheological requirements of current inkjet technologies, there is a lack of photopolymer resins suitable for the inkjet printing of biomaterials. Hence, a novel ink engineered for 3D piezoelectric inkjet printing of biomaterials is designed and developed. The novel resin leverages a biodegradable amino acid phosphorodiamidate matrix copolymerized with a dialkyne ether to modulate the viscosity. Copolymerization with commercially available thiols facilitates the photochemical thiol‐yne curing reaction. The ink exhibits optimal viscosity, eliminating the need for solvents, as well as reliable jetting and sufficiently swift curing kinetics. Furthermore, the formulation is successfully demonstrated in an industrial inkjet printhead. Notably, the resulting materials have low cytotoxicity and, hence, have significant promise in advancing the applications of 3D inkjet printing of biological scaffolds.