This comprehensive study focused on the standard taxi sign used in Ireland, its impact on drag production, fuel expenses, and CO2 emissions. Experimental analysis revealed that the conventional taxi sign significantly increased drag, especially when mounted on streamlined vehicles such as saloon cars, due to flow separation issues on the rear roof and rear windshield. Longitudinal reorientation of the sign offered a 14-fold reduction in drag increase compared to the traditional placement. It was found that positioning the sign in the middle of the roof offered the greatest fuel efficiency. Furthermore, the study estimated that implementing longitudinal repositioning on all Irish taxi signs could save drivers approximately 832 per year and reduce national CO2 emissions by a substantial 22,464 tonnes annually. Comparative analyses with international taxi signs demonstrated that the Irish sign had significantly larger drag contributions, emphasizing the need for improved aerodynamics. To address the inherent drag issue, the study explored novel appendable devices and proposed alternative taxi sign designs. Among the tested solutions, a magnet-mounted front ramp proved the most effective, reducing total drag by nearly 30%. Additionally, a motorized flip-up taxi sign design demonstrated a remarkable 40% reduction in drag. Finally, a newly proposed taxi sign design, featuring longitudinal positioning and pointed triangular front and rear faces, resulted in a minimal 4.3% increase in vehicle drag compared to the baseline car.

As a manifestation of technological innovation achievements, patents reflect the frontier of technological development in the field. This paper constructs a multi-entity patent collaboration network and analyzes its evolution patterns to provide a reference for innovation organizations to grasp the general direction of innovation development and select partners. Based on the data of collaboration patents of two and three organizations in China's new energy vehicles (NEV) industry from 2008 to 2021, this paper constructs higher-order interaction collaboration innovation networks in different periods to analyze the spatial evolution of networks and patent cooperation activities. The results show that the generalized degree distribution of nodes and edges conforms to the power-law distribution. The two-dimensional simplex networks gradually form triangle groups centered on the core nodes, and the importance of key edges is beginning to emerge. Key organizations and partners, including State Grid Corporation of China, Tsinghua University, and China Electric Power Research Institute, will largely determine the direction for the future development of cooperation innovation. The study also reveals that Beijing, Jiangsu, Zhejiang, Guangzhou, and Shanghai are in central positions in the cooperative innovation network, based on their cooperation breadth and depth measures. Additionally, key links formed by Beijing as hubs are not only the center of information exchange but also function as bridges that connect to other regions.

The key to ensuring the sustainability of transportation operations on the roads is to manage traffic flows homogeneously. By homogenizing the behavior of various drivers, traffic operation can be optimized, and traffic safety can be improved. However, the advent of autonomous vehicles is expected to have a major impact on the homogeneity of sustainable transportation operations. In this study, a method of driving in harmony with surrounding vehicles was studied to minimize the impact of autonomous vehicles on current traffic operation. In particular, in this study, a methodology was developed to optimize the driving behavior of autonomous vehicles by analyzing the driving behavior of following vehicles using spectrum analysis. Specifically, a method for calculating three indicators that can analyze the driving behavior of a following vehicle, such as reaction time, stimulus adaptation index, and collision risk avoidance index, was proposed. These indices produced consistent and robust results for all traffic conditions. If these indicators are used, it is expected that sustainable traffic management will be possible even when autonomous vehicles and human drivers are mixed on the road.

The Internet of Vehicles (IoV) is an emerging field that has attracted significant attention due to its potential to transform transportation and mobility. IoV enables the development of new services and applications that can improve transportation systems' efficiency, safety, and sustainability. However, ensuring secure and trustworthy communication among the different components of an IoV system is a critical challenge that needs to be addressed. This paper proposes a blockchain-enabled communication framework for secure and trustworthy IoV applications. The proposed framework leverages the security and decentralization features of blockchain technology to provide secure communication channels for different components of the IoV system, including vehicles, infrastructure, and service providers. The proposed framework provides an identity management system to authenticate and authorize users and devices, thereby preventing unauthorized access and data breaches. To evaluate the effectiveness of the proposed framework, we conducted experiments using a real-world IoV scenario, and the results demonstrate that the proposed framework can provide secure and trustworthy communication for IoV applications. The proposed blockchain-enabled communication framework offers a promising approach to address the security and trust challenges in IoV communication systems.

This paper provides a comprehensive overview of recent advancements in autonomous electric vehicle (AEV) within the specified region. It elaborates on the progress and comparative analysis of diverse subsystems, including energy storage, cell balancing for battery systems, vehicle charger layouts, electric vehicle motor mechanisms, and braking systems. Furthermore, this paper showcases several prototype autonomous electric vehicles as conclusive study findings.

Recent empirical work has revealed that drivers have different lane change strategies. These strategies help to understand driver heterogeneity and decision stochasticity, which are both often lacking in microscopic models. In this paper we generalize the lane change strategies in a theory for social interactions. The theory introduces a mechanism by which two new driver traits, ego-speed sensitivity and socio-speed sensitivity, endogenously influence other driver traits that govern lane change behaviour such as desired speed, desired headway and lane change desire. A key concept in this mechanism is that drivers are not just affected by what happens in front of them, but also by what they observe in their rear-view mirrors. The idea is that drivers reduce their headways to exert (social) pressure onto leading drivers (on the same or adjacent lanes), which may force them to increase speed, change lanes, or conversely, to refrain from changing lanes. We refer to this reduction of the headway as tailgating. Through an example implementation of the theory, we demonstrate that these social interactions may have a profound impact on several key (mesoscopic) traffic flow characteristics. Our results show that these new driver interactions influence the number of lane changes, platoon lengths, and headway variance. As such, the theory improves our description and understanding of traffic flow and consequently it paves the path for more realistic traffic models.

In the last decades, technological advances related to RNA manipulation enabled and expanded its application in vaccine development. This approach comprises synthetic single-stranded mRNA molecules that direct the translation of the antigen responsible for activating the desired immune response. The success of RNA vaccines depends on the delivery vehicle employed. Among the systems, yeasts emerge as a new approach to a natural delivery platform. The presence of β-glucans and mannans in its wall is responsible for the adjuvant action of this system. Yeasts are already employed to deliver protein antigens, with success and efficacy demonstrated through pre-clinical and clinical trials. Yeast β-glucan capsules, microparticles, and nanoparticles are capable of modulating host immune responses and have a high capacity to carry RNA and small molecules, with bioavailability upon oral immunization and with targeting to receptors present in anti-gen-presenting cells (APCs). Besides, yeasts are interesting vehicles for the protection and specific delivery of therapeutic vaccines based on shRNA or dsRNA. In this review, we present an overview of the attributes of yeast or its derivatives for the delivery of RNA-based vaccines, discussing their current challenges and prospects for using this promising strategy.

Rapid advancements in the fifth generation (5G) communication technology and mobile edge computing (MEC) paradigm lead to the proliferation of unmanned aerial vehicles (UAV) in urban air mobility (UAM) networks, which provide intelligent services for diversified smart city scenarios. Meanwhile, the widely deployed internet of drones (IoD) in smart cities also brings up new concerns on performance, security, and privacy. The centralized framework adopted by conventional UAM networks is not adequate to handle high mobility and dynamicity. Moreover, it is necessary to ensure device authentication, data integrity, and privacy preservation in UAM networks. Thanks to characteristics of decentralization, traceability, and unalterability, Blockchain is recognized as a promising technology to enhance security and privacy for UAM networks. In this paper, we introduce LightMAN, a lightweight microchained fabric for data assurance and resilience-oriented UAM networks. LightMAN is tailored for small-scale permissioned UAV networks, in which a microchain acts as a lightweight distributed ledger for security guarantees. Thus, participants are enabled to authenticate drones and verify the genuineness of data that is sent to/from drones without relying on a third-party agency. In addition, a hybrid on-chain and off-chain storage strategy is adopted that not only improves performance (e.g,.latency and throughput) but also ensures privacy preservation for sensitive information in UAM networks. A proof-of-concept prototype is implemented and tested on a Micro Air Vehicle Link (MAVLink) simulator. The experimental evaluation validates the feasibility and effectiveness of the proposed LightMAN solution.

The use of cobalt-iron (VaCoFe) core is investigated as an alternative to silicon-iron (FeSi) on the design of interior permanent magnet synchronous motors (IPMSM). A spoke-type IPMSM geometry is optimized considering FeSi and VaCoFe cores for a torque range up to 40 N.m, providing a general comparative analysis between materials, considering the application of a 4-motor competition vehicle’s powertrain. A genetic optimization algorithm is applied over a hybrid analytical/finite-element model of the motor to provide sufficiently accurate electromagnetic and thermal results within a feasible time. VaCoFe can result in an estimated increase of up to 5 % in efficiency for the same torque, or up to 64 % torque increase for the same efficiency level. After optimization, and using a detailed time-dependent model, a potential 3.2 % increase in efficiency, a core weight reduction of 4.1 %, and a decrease of 9.6 % in the motor’s core volume was found for the VaCoFe at 20 Nm. In addition, for the same motor volume, the VaCoFe allows an increase of 51.9 % of torque with an increase of 1.1 % of efficiency, when compared with FeSi.

The copper end paste used in multilayer ceramic capacitors sintered in nitrogen atmosphere will lead to carbon residue of organic vehicle, which will lead to the reduction of electrode conduc-tivity and high scrap rate. With an attempt to leave no residue in the sintering, the compatibility of solvents and thickeners should be improved because it has an important influence on the hi-erarchical volatilization and carbon residue of organic vehicles. In this work, the volatility of different solvents was compared and several solvents were mixed in a definite proportion to prepare an organic vehicle with polyacrylate resins. The hierarchical volatility and solubility parameters of mixed solvents were adjusted effectively by changing proportions of different components, the thermogravimetric curves of resins and organic vehicles were measured by thermogravimetric analyzer, the effect of solubility parameter on the dissolvability of resins in the solvent and the residual of organic vehicles were studied. Results showed that the hierar-chical volatilization of solvents can be obtained by mixing different solvents; the intrinsic vis-cosity of the organic vehicle is higher and the thermal decomposition residue of polyacrylate resins is lower when the solubility parameters of mixed solvents and polyacrylate resins are closer. The low residual sintering of organic vehicles can be achieved by using the mixed solvent with hierarchical volatility and approximate solubility parameters as resins.

Under the goal of carbon peak and carbon neutrality, the carbon emission reduction of the automobile industry has attracted more and more attention in recent years. Electric vehicle has the dual attributes of power load and energy storage unit. With the increase of the number of electric vehicles, reducing carbon emissions through the collaborative interaction between electric vehicle and power network will become an important way to control carbon emissions in the automotive field. In this study, an optimization model of emission reduction benefits based on integrated development of electric vehicle and power grid is proposed, which explores the best technical way of synergy between power grid and electric vehicle, achieves the best carbon reduction effect and provides a model basis for large-scale demonstration application. Numerical simulations based on the real case in Beijing are conducted to validate the effectiveness of the proposed method.

The article presents development of the more electric turbofan engine in distributed architecture with a design thrust in the range from 3 to 7.5 and from 7.5 to 30 kN for small and medium-sized unmanned aerial vehicles. The engine subsystems are considered as separate smart modules with a built-in control system, exchanging data via a digital channel with the central engine control and diagnostics unit. The key smart engine units are combined in the following subsystems: starter and turbine generators, oil pumps, actuator of guide vanes, fuel pumps, fuel metering unit, control and diagnostic unit. All pumps and guide vane actuator are electrically driven. Control and monitoring signals are transmitted via a digital bus. Functional and reliability analysis, technical configuration design of each subsystem are presented. Based on analysis of the architecture of distributed control system for gearbox-free more electric engine, different configurations of described subsystems are proposed.

In this contribution, different lane-keeping control strategies for Autonomous Ground Vehicles (AGV) have been analyzed and compared. The AGV must be oriented and kept within a given reference path using the front wheel steering angle as the control action for a specific longitudinal velocity. While non-linear models can describe the lateral dynamics of the vehicle in an accurate manner, they might lead to difficulties when computing some real-time control laws such as Model Predictive Control (MPC). Linear Parameter Varying (LPV) models can provide a trade-off between computational complexity and model accuracy. Another way to reduce computational complexity is to explore other control strategies, for example, the one based on the Inverse Kinematic Bicycle model (IKIBI). Additionally, AGV sensors typically work at different measurement acquisition frequencies so that Kalman Filters (KF) are usually needed for sensor fusion. If these frequencies are slower than the actuation rate, a multi-rate KF may be needed. The two control strategies (MPC using a LPV model and IKIBI) have been compared in simulations over a circuit path in the presence of process and measurement Gaussian noise. The MPC controller has shown to provide a more accurate lane-keeping behavior than an IKIBI control strategy. Finally, it has been seen that Dual-Rate Extended Kalman Filters (DREKF) constitute an essential tool when only slow and noisy sensor feedback is available in an AGV lane-keeping application.

Manual evaluation of crop injury to herbicides is time-consuming. Unmanned aircraft systems (UAS) and high-resolution multispectral sensors and machine learning classification techniques have the potential to save time and improve precision in the evaluation of herbicide injury in crops, including grain sorghum (Sorghum bicolor L. Moench). The objectives of this research were to (1) evaluate three supervised classification algorithms (support vector machine, maximum likelihood, and random forest) for categorizing high-resolution UAS imagery to aid in data extraction and (2) evaluate the use of vegetative indices (VIs) collected from UAV imagery as an alternative to traditional methods of visual herbicide injury assessment in mesotrione-tolerant grain sorghum breeding trials. An experiment was conducted in a randomized complete block design using a factorial treatment arrangement of three genotypes by four mesotrione doses. Herbicide injury was rated visually on a scale of 0 (no injury) to 100 (complete plant mortality). The UAS flights were flown at 9, 15, 21, 27, and 35 days after treatment. Results show the SVM algorithm to be the most consistently accurate, and high correlations (r = -0.83 to -0.94; p < 0.0001) were observed between the normalized difference vegetative index (NDVI) and ground-measured herbicide injury. Therefore we conclude that VIs collected with UAS coupled with machine learning image classification, has the potential to be an effective method of evaluating mesotrione injury in grain sorghum.

Car parking is a challenging part of urban transportation and the traffic violations around it cause many problems for citizens. In recent years, due to the fast growth and development of urbanization, temporary and unauthorized stopping of cars along the streets, especially in large cities, has led to an increased traffic, urban disorders, dangers for citizens, and violation of rules. Studies have shown that there is a direct relationship between vehicle parking violations and urban places. GIScience capabilities and tools play an important role in analysing the spatial distribution of these violations. In this study, we investigated the spatial distribution of vehicle violations in a region of Tehran, Iran that is suffering from a heavy traffic load and heavily polluted air. Although two dissimilar urban segregations exist in the north and south of the study area, our analysis indicates a similar pattern of car parking violations. In both of the areas, about 70% of all curb parks are legal, while the remaining are illegal. Also, spatial analysis reveals a direct relationship between some POIs and the occurrence of car park violations so that the density of legal curb parks is high near some POIs, and less near some others and vice versa. For example, the number of vehicle park violation around the hospitals is more than the average of the study area. However, the number of park violations around the universities is less than the average. Our findings reveal that co-location of certain POIs, for instance a hotel and a supermarket will lead to an increase in the number of park violations. In other words, there is a strong correlation between the type of POIs and curb-parks violations. Our results also show that POIs have an impact radius that leads to violations occurring in that area. For example, the area of the impact of a hospital on the creation of car park violations was estimated at 125 meters. Our presented approach along with the discussed findings along with conclusions can be useful to a large range of stakeholders including urban planner, traffic police departments, local municipalities, law enforcement agencies, and environmentalists to have a better perspective of infrastructure planning.

This research was conducted to manufacture thermally expandable microspheres (TEMs) for vehicles’ underbody coating and to apply them on an industrial scale. TEMs heat resistance was studied depending on the ratios of a cross-linking agent and an initiator. This research focused on the content of a cross-linking agent and how it affected the results. The TEMs’ outer shell was thickened to solve the problem of the foam expansion ratio’s reduction that occurred due to the shrinkage after the maximum expansion (Tmax) was reached. After foaming, the cross-sectional thickness and surface of the sample with thickened outer shell were observed. The TEMs with the thickened shell showed the least shrinkage, which indicated excellent shrinkage stability, even after prolonged exposure to heat.

Smart cities and smart technologies have been incorporated into several axes to increase the comfort of life. The connected building's concept was introduced for this reason. However, it was utilized in power management for better organizing, greater buildings management, and monetary savings. Cars technologies and the number of vehicles are also involved; Nowadays, each house has at least one car. Technological evolution helped to make those cars intelligent and connected. In the latest versions, the majority of those cars were equipped with several sensors, several communication protocols and a principal electrical control unit (ECU), especially for the electric vehicle model. This type of architecture was an essential element in a smart city, thus, it helps to manage power and decide when a vehicle needs to be charged. Based on the smart city concept and using possible network communication between buildings and vehicles, EVs can share their own information related to the powerful experience on a specific path. This information can be gathered in a gigantic database and used for managing the power inside these vehicles. In this field, we propose in this paper a new approach for power management inside an electric vehicle based on bi-communication between vehicles and buildings. The proposed approach is founded on two essential parts; the first is related to vehicles’ classification and buildings’ recommendation according to different car positions. Two algorithms, related to the SVC and neural network was employed in this work for implementing the final process. Different possibilities and situations were discussed for this approach. The proposed method was tested and validated using Simulink/Matlab application. The state of charge of the used battery was compared at the end of this work, for two specified cases, for showing the contribution of this approach.

Location-Based Services (LBS) have been widely deployed for the connected vehicle (CV) applications such as vehicle navigation,vehicle tracking and location-based augmented reality. The current LBS deployments have limitations in supporting time-critical CV use cases, including vehicle to vehicle (V2V), vehicle to infrastructure (V2I) and vehicle-to-people (V2P) safety applications. The paper presents the new LBS framework based on the publish-subscribe communication paradigm, to enable device-to-device (D2D) connections through use of selected application protocols in the application layer of the TCP/IP layered protocol model. Two publish-subscribe application protocols, Distributed Data Service (DDS) real-time publish and subscribe (DDS-RTPS) and Message Queue Telemetry Transport (MQTT), are introduced to support the LBS D2D applications. A number of test scenarios with Mosquitto MQTT and OpenDDS under 4G-mobile broadband (MBB) services are designed to assess the transmit/receive round-trip time (RTT) and packet-loss rate (PLR) with settings of a publisher to multiple subscribers, to simulate the connections to multiple vehicles. The transmission frequency is set for 10 Hz and the message sizes vary from 100 to 2000 Bytes. The PLRs are defined as the percentages of the delayed messages beyond a delay limit. Static test results with OpenDDS show that for the RTT delay beyond the limit of 100 ms, the total PLRs range between 5.25% and 8.76% for the message size of 50 to 2000 Bytes. Vehicle testing results with Mosquitto show that PLRs for the RTT delays between 200 ms and 1000 ms are 0.63%, 3.58% and 5.77%, for connections with 1, 4 and 10 vehicles, respectively. The results demonstrate the potential of the D2D LBS framework for medium-demanding CV safety applications such as V2P and V2I use cases, taking advantages of the 4G-MBB services and 5G extreme mobile broadband (eMBB) services and mobile devices generally available with all road users.

The abrupt increase of the electric vehicles in Bangladesh needs huge amount of power. As a result, alternative energy sources are emphasized due to limited fossil fuels in order to develop a sustainable energy sector with environment friendly resources. Bangladesh has an enormous potential in the field of renewable resources like biogas and biomass. This paper presents 20 kW electric vehicle charging station (EVCS) utilizing biogas resources where maximum energy requirement is 100 kWh. In this paper, the biogas based EVCS is designed using MATLAB Simulink and HOMER software. Daily 15-20 electric vehicles can be recharged their batteries using the proposed charging station. The proposed system offers lower cost of energy compared to the grid electricity. Moreover, the proposed charging station shows 68.75% reduction in CO₂ emission than grid based charging station. In addition, the proposed EVCS will save monthly $ 16.25 and $ 27.50 respectively for easy bike and auto rickshaw type electric vehicles in Bangladesh.

Analysis of 1382 measures of battery State of Health (SoH) from 283 Nissan Leafs (“Leaf/s”), manufactured between 2011 and 2017, has detected a faster rate of decline in this measure of energy-holding capacity for 30 kWh variants. At two years of age, the mean rate of decline of SoH of 30 kWh Leafs was 9.9% per annum (95% uncertainty interval of 8.7% to 11.1%; n = 82). This was around three times the rate of decline of 24 kWh Leafs which at two years averaged 3.1% per annum (95% uncertainty interval of 2.9% to 3.3%; n = 201). For both variants there was evidence for an increasing rate of decline as they aged, although this was much more pronounced in the 30 kWh Leafs. Higher use of rapid DC charging was associated with a small decrease in SoH. Additionally, while 24 kWh cars with greater distances travelled showed a higher SoH, in 30 kWh cars there was a reduction in SoH observed in cars that had travelled further. The 30 kWh Leafs sourced from United Kingdom showed slower initial decline than those from Japan, but the rate of decline was similar at two years of age. Improvements in the battery health diagnostics, continuous monitoring of battery temperatures and state of charge, and verification of a fundamental model of battery health are needed before causes and remedies for the observed decline can be pinpointed. If the high rate of decline in battery capacity that we observed in the first 2.3 years of a 30 kWh Leaf’s lifetime were to continue, the financial and environmental benefits of this model may be significantly eroded. Despite 30 kWh Leafs accounting for only 14% of all light battery electric vehicles registered for use on New Zealand roads at the end of February 2018, there is also the potential for the relatively poor performance of this specific model to undermine electric vehicle uptake more generally unless remedies can be found.

The technologies influencing alternative ways of transportation are augmenting in recent years as the need for transportation is increasing rapidly due to urbanization and motorization. In this paper, a solar powered electric auto-rickshaw (SPEA) is designed and developed for Indian conditions. The developed vehicle is comprehensively analyzed techno-economically for its viability in the Indian market. The performance analysis of SPEA results in an optimal charging rate of 2 kWh per day with an average solar irradiance of 325 W/m2. The discharging characteristics are studied based on different loading conditions. The vehicle achieved a maximum speed of 21.69 km/h with battery discharge rate of 296W at 90kg load and also reached a maximum discharge rate of 540W at 390kg loading with a maximum speed of 12.11 km/h. The environmental analysis of SPEA displayed yearly CO2 emissions of 1,777 kg, 1,987 kg and 1,938 kg using Compressed Natural Gas, Liquefied Petroleum Gas and gasoline engines respectively can be mitigated using SPEA. The results of financial analysis of SPEA were welcoming as the investor gets 24.44% lesser payback duration compared to gasoline run vehicle. Socio-Economic analysis of SPEA discussed its significant advantages and showed 18.73% and 3.9% increase in yearly income over gasoline driven and battery driven vehicles.

With the great development of intelligent transportation systems (ITS), travel time prediction has attracted the attentions of many researchers and a large number of prediction methods have been developed. However, as an unavoidable topic, the predictability of travel time series is the basic premise for travel time prediction has received less attention than the methodology. Based on the analysis of the complexity of travel time series, this paper defines travel time predictability to express the probability of correct travel time prediction and proposes an entropy-based method to measure the upper bound of travel time predictability. Multiscale entropy is employed to quantify the complexity of travel time series, and the relationships between entropy and the upper bound of travel time predictability are presented. Empirical studies are made with vehicle trajectory data in an express road section. The effectiveness of time scales, tolerance, and series length to entropy and travel time predictability are analysis, and some valuable suggestions about the accuracy of travel time predictability are discussed. Finally, the comparisons between travel time predictability and actual prediction results from two prediction models, ARIMA and BPNN, are conducted. Experimental results demonstrate the validity and reliability of the proposed travel time predictability.

This paper presents a new methodology to derive and analyze strategies for a fully decarbonized urban transport system which combines conceptual vehicle design, a large-scale agent-based transport simulation, operational cost analysis, and life cycle assessment for a complete urban region. The holistic approach evaluates technical feasibility, system cost, energy demand, transportation time and sustainability-related impacts of various decarbonization strategies. In contrast to previous work, the consequences of a transformation to fully decarbonized transport system scenarios are quantified across all traffic segments, considering procurement, operation and disposal. The methodology can be applied to arbitrary regions and transport systems. Here, the metropolitan region of Berlin is chosen as a demonstration case. First results are shown for a complete conversion of all traffic segments from conventional propulsion technology to battery electric vehicles. The transition of private individual traffic is analyzed regarding technical feasibility, energy demand and environmental impact. Commercial goods, municipal traffic and public transport are analyzed with respect to system cost and environmental impacts. We can show a feasible transition path for all cases with substantially lower greenhouse gas emissions. Based on current technologies and today’s cost structures our simulation shows a moderate increase in total systems cost of 13-18%.

Heart failure (HF) is a life-threatening disorder and is treated by drug therapies and surgical interventions such as heart transplantation and left ventricular assist device (LVAD). However, these treatments can lack effectiveness in the long term and are associated with issues such as donor shortage in heart transplantation, and infection, stroke, or gastrointestinal bleeding in LVADs. Therefore, alternative therapeutic strategies are still needed. In this respect, stem cell therapy has been introduced for the treatment of HF and numerous preclinical and clinical studies using various types of stem cells, such as embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) have been shown to improve cardiac function and attenuate left ventricular remodeling. IPSCs, which have a capacity of unlimited proliferation and differentiation to cardiomyocytes, are a promising cell source for myocardial regeneration therapy. This review discusses the current status of cardiac regenerative therapy using iPSCs.

Pluripotent stem cells (PSCs) can differentiate into three germ layers and diverse autolo-gous cell lines. Being among the most commonly used large domesticated hoofed animals and serving as a vital source of food and bioreactors, cattle are among the many species in which PSCs have been developed. Bovine PSCs (bPSCs) are the "seed cells" of regenerative science and have immense potential to advance species propagation, genetic engineering, and disease treatment. Moreover, they can aid in screening new drugs for efficacy and toxicity, model human diseases, and establish a sustainable agricultural system that can cater to the needs of the growing global population. Establishing stable bPSCs in vitro has been a critical scientific challenge, and researchers have made numerous attempts to address this issue. This review primarily delves into the current research progress of bPSCs, the challenges faced, and their potential applications.

During geomagnetic storms, which are a result of solar wind interaction with the Earth’s magnetosphere, geomagnetically induced currents (GICs) begin to flow in the long-distance high-voltage power grids on the Earth’s surface. It causes a number of negative phenomena that affect the normal operation of the entire electric power system. To investigate the nature of the phenomenon and its possible effects on transformers, a GIC monitoring system was created in 2011, the devices of which were installed at five substations of the Kola-Karelian power transit in northwestern Russia. Over 12 years of operating the system a large amount of data has been accumulated, which cannot be analyzed manually within a reasonable amount of time. To analyze the constantly growing volume of recorded data effectively, a method for automatic classification of GIC in autotransformer neutral was proposed. The method is based on a continuous wavelet transform of the neutral current data combined with a convolutional neural network (CNN) to classify the obtained scalogram images. As the result of comparing four CNNs with different architectures, a model that showed excellent GIC classification performance on the validation set (100.00% accuracy and loss of 0.0115) was chosen.

Inflammatory bowel disease (IBD), including ulcerative colitis and Crohn's disease, is a complex gastrointestinal disorder with a multifactorial etiology, including environmental triggers, autoimmune mechanisms, and genetic predisposition. Despite advancements in therapeutic strategies for IBD, its associated mortality rate continues to rise, which is often attributed to unforeseen side effects of conventional treatments. In this context, we explored the potential of Ecklonia cava extract (ECE) derived from an edible marine alga known for its anti-inflammatory and antioxidant properties in mitigating IBD. This study investigated the effectiveness of ECE as a preventive agent in a murine model of dextran sulfate sodium (DSS)-induced colitis. Our findings revealed that pretreatment with ECE significantly ameliorated colitis severity as evidenced by increased colon length, reduced spleen weight, and histological improvements demonstrated by immunohistochemical analysis. Furthermore, ECE significantly attenuated the upregulation of inflammatory cytokines and mediators and the infiltration of immune cells known to be prominent features of colitis in mice. Notably, ECE restored dysbiosis of intestinal microflora and aided in the recovery of damaged intestinal mucosa. Mechanistically, ECE exhibited protective effects against pathogenic colitis by inhibiting the NLRP3/NF-κB pathway known to be pivotal regulators in the inflammatory signaling cascade. These compelling results suggest that ECE holds promise as a potential candidate for IBD prevention. It might be developed into a functional food for promoting gastrointestinal health. This research sheds light on the preventive potential of natural compounds like ECE in the management of IBD, offering a safer and more effective approach to combating this challenging disease.

Vibrations of plate structures placed in a supersonic flow is considered. The undisturbed fluid flow is parallel to the plate. Two specific problems are treated: in the first one the plate is in the form of an infinite strip and the flow is in the direction of its finite length. Rigid walls extend from the sides of the plate indefinitely. In the second problem, the plate is a finite rectangle and the flow is parallel to one of its sides. The first problem is a limiting case of the second problem. The flow is modeled by piston theory which assumes that the fluid pressure on the plate is proportional to local slope. This approximation is widely used at high speeds, and reduces the interaction between the fluid flow and the vibrations of the plate to an additional term in the vibration equation. The resulting problem can be solved by assumed mode methods. In this study, the solution is also carried out by using the collocation method. The main result is the flutter velocity of the free fluid flow under which the plate vibrations become unstable. Finally, simple expressions are proposed between the various non-dimensional parameters that allows quick estimation of flutter velocity.

The present paper describes a study case of the failure investigation of Duplex stainless steel (UNS S31803) on the tube and tube sheet section of a shell and tube heat exchanger BEM TEMA type with seawater as the cooling medium. Although UNS S31803 offers high strength, high resistance to chloride-induced SCC, and high resistance to pitting attack in chloride environments, in this study case, the heat exchanger experienced some material degradation; 26 tubes were leaked and plugged on both sides, and scales plugged 76 tubes. The examination in this study case revealed the formation of biofilm inside the tubes, XRD examination revealed that the film contained aragonite (CaCO3), and by using microstructural examination on the inner surface of the tube, the austenite grains were preferentially attacked by crevice corrosion. In this case, the failure was caused by crevice corrosion, and crevice corrosion was enhanced by microbiological-induced corrosion (MIC). Recommendations to avoid similar failures are also suggested in this paper.

In recent years, laser engraving has received widespread attention as a convenient, efficient, and programmable method, which has enabled the obtaining of high-quality porous graphene from various precursors. Laser engraving is often used to fabricate the dielectric layer with micro-structure for capacitive pressure sensors, however, the usual choice of electrodes remains poorly flexible metal electrodes, which greatly limits the overall flexibility of the sensors. In this work, we propose a flexible capacitive pressure sensor made entirely of thermoplastic polyurethane (TPU) and laser-induced graphene (LIG) derived from wood. The capacitive pressure sensor consisted of a flexible LIG/TPU electrode (LTE), a LIG/TPU electrode with micro hole array, and dielectric layer of TPU with micro-cone array molded from laser-engraved hole array on wood, which provided high sensitivity (0.11 kPa-1), ultra-wide pressure detection range (100Pa to 1.4MPa), fast response (~300 ms) and good stability (&gt;4000 cycles, at 0-35 kPa). We believe that our research makes a significant contribution to the literature because the easily available materials derived from wood and overall consistent flexibility meet the requirements of flexible electronic devices.

A 3D graphene foam made of interconnected multilayer graphene flakes was produced on optical fibres (OF) by laser-induced transformation of a polyimide (PI) film coated on the OF cladding. This material, known as la-ser-induced graphene (LIG), was explored in the electrochemical detection and quantification of dopamine (DA) at physiologically relevant concentrations in the presence of the most relevant interfering molecules in biological fluids, ascorbic acid (AA) and uric acid (UA). The measured limit of detection is 100 nM, the linear range is 0.1 to 5 μM and a maximum sensitivity of 5.0 µA µM−1 cm−2 was obtained for LIG decorated with Pt nanoparticles (NPs). Moreover, immunity to AA and UA interference and to fouling was attained by decorating the LIG elec-trode with Pt NPs and coating with Nafion. These figures of merit underlines the potential of these sensors for the quantification of physiologically relevant concentrations of DA in biological fluids, paving the way for the development of hybrid electrochemical/optical sensing actuating platforms in a lab-on-fibre configuration, with relevant applications in biomedical engineering. The advantages of this hybrid arrangement include the possi-bility of in-situ counterproofing, extended measuring ranges, photoelectrochemical detection and the probing of inaccessible places. This elegant approach can also provide a simple and cost-effective way to fabricate biomed-ical devices with extended functionality, such as medical optical probes with added electrochemical capabilities, optogenetics combined with local electrochemical detection, among others.

The fall armyworm (FAW), Spodoptera frugiperda, has become one of the most important pests on corn in China since it invaded in 2019. Although FAW has not been reported to cause widespread damage to rice plants in China, it has been sporadically found feeding in the field. If FAW infests rice in China, the fitness of other insect pests on rice may be influenced. However, how FAW and other insect pests on rice interact remains unknown. In this study, we found that the infestation of FAW larvae on rice plants prolonged the developmental duration of the brown planthopper (BPH, Nilaparvata lugens (Stål)) eggs, and plants damaged by gravid BPH females did not induce defenses that influenced the growth of FAW larvae. Moreover, co-infestation by FAW larvae on rice plants did not influence the attractiveness of volatiles emitted from BPH-infested plants to Anagrus nilaparvatae, an egg parasitoid of rice planthoppers. FAW larvae were able to prey on BPH eggs laid on rice plants and grew faster compared to those larvae that lacked available eggs. Studies revealed that the delay in development of BPH eggs on FAW-infested plants was probably related to the increase in levels of jasmonoyl-isoleucine, abscisic acid and the defensive compounds in the rice leaf sheaths on which BPH eggs were laid. These findings indicate that if FAW invades rice plants in China, the population density of BPH may be decreased by intraguild predation and induced plant defenses, whereas the population density of FAW may be increased.

The current study aimed to investigate the antitumor effects and potent mechanism of cytokine-induced killer (CIK) cells combined with irreversible electroporation (IRE) via an in vitro function assay in an in vivo Panc02 cell–bearing mouse model. We established an in vitro culture assay for CIK cells and determined the proportions of different peripheral lymphocytes. The antitumor effect of the combination of IRE and CIK cells in a Panc02 pancreatic-cancer (PC) subcutaneous-xenograft model was investigated; tumor size and mouse survival rates were recorded. We used flow cytometry (FCM) to analyze the proportion of intratumoral lymphocytes, the expression of chemokine receptors, and the proliferative activity of CIK cells. The proportion of cells that were positive for clusters of differentiation 3 and 8 (CD3+CD8+) and the proportion of CD3+CD56+ cells were both significantly increased after 21 days of in vitro culture. Combined IRE/CIK cell treatment significantly inhibited tumor growth and increased the survival rate of Panc02 cell–bearing mice. Furthermore, infiltration of lymphocytes into tumor tissue was significantly increased by this combination therapy compared with the untreated group or monotherapy group. In addition, IRE significantly enhanced the expression of chemokine receptors elicited by, and the proliferative activity of, CIK cells. In conclusion, IRE combined with CIK cells showed superior antitumor efficacy in a PC subcutaneous-xenograft model, which we attributed to the promotion of lymphocytic infiltration, as well as to upregulation of chemokine receptor expression and of regulators of CIK cell proliferation.

Background: Despite the existence of a wide variety of anti-inflammatory drugs, the vast majority are classified as steroidal or non-steroidal. Both classes with many side effects that limit usage. Thus, the search for new molecules with anti-inflammatory potential is still important. Methods: Five phenylbenzohydrazides were synthetized and evaluated in pre-clinical models of acute inflammation in vivo and in vitro. Results: Substances significantly reduced cell migration induced by carrageenan. It was also observed an intense inhibition in protein extravasation and cytokines (IL-6, IL-1β, and TNF-α) production as well as nitric oxide reduction. INL-11 demonstrated to be the most potent since the reduction was significant even when compared with dexamethasone. In vitro INLs also reduced cytokines and NO production and iNOS activity. INL-11 was the most effective in reducing cell migration in vitro. Conclusions: our data suggest that these substances are suitable for further development to new series of compounds that could lead to new hits and future drug prototypes for anti-inflammatory conditions.

Although lithium-ion batteries have extensively been used in various applications because of their high energy capacity, fracture and failure, the by-products of large strains and stresses caused by fast charging and discharging need yet to be addressed. The size effects on the mechanical behavior of the nano-sized structures are significant; however, the classical elasticity theory may not consider such effects. On the other hand, surface stress theory, as a robust and potential theory, is suitable in considering size effects in nano-scale structures. Therefore, in this paper, in order to involve the surface stress effects on the fracture behavior of Li-ion batteries, the following steps are taken. Firstly, a phase-field model is used to determine the evolution of the concentration profile. Subsequently, the stress distribution is obtained by using the surface stress theory combined with chemical equations for a planar electrode. Afterward, by using the weight function method for an edge crack in the plate, the stress intensity factor is derived for all time steps and possible crack lengths during the process. It is found that with increasing phase boundary thickness parameter or decreasing phase-separation phenomenon, the surface mechanics parameters become more influential. Furthermore, in the presence of positive surface stress, the diffusion-induced stress distribution decreases, which in turn reduces the stress intensity factor. In addition, in this paper, the two states of surface stress are compared either for elastic or total strain. Concerning stresses and concentrations, the results indicate a big difference at the beginning of the deintercalation process showing, in particular, 2% for stresses, but the differences diminish gradually.

Arboviruses of medical and veterinary significance have been identified on all 7 continents with every human and animal population at risk for exposure. Like arboviruses, chronic neurodegenerative diseases like Alzheimer’s and Parkinson’s disease are found wherever there are humans. Viral parkinsonism has been documented for a variety of human pathogens though there are few studies that evaluate the effects of viral infection on degenerative neurological diseases. Significant differences in baseline gene and protein expression have been determined between Human Induced Pluripotent Stem Cell lines derived from a non-Parkinson’s disease individual and from an individual with reported Parkinson’s disease. While the organoids generated from each cell line were physically indistinguishable, significant differences were observed in gene and protein expression for neurotransmission and immunity. It was hypothesized that these inherent differences would impact cerebral organoid responses to viral infection. In this preliminary observational study, cerebral organoids from a non-Parkinson’s and Parkinson’s patient were infected with Chikungunya virus and observed for 2 weeks. Parkinson’s organoids lost mass and exhibited a dysfunctional antiviral response. Neurotransmission data from both non-Parkinson’s and Parkinson’s organoids had dysregulation of IL-1, IL-10, IL-6. These cytokines are associated with mood and could be contributing to persistent depression seen in patients following CHIKV infection. Both organoid types had increased expression of CCR5 and CXCL10 which are linked to demyelination, highlighting a potential mechanism for virus-associated parkinsonism. The dysfunctional antiviral response of Parkinson’s organoids highlights the need for more research in neurotropic infections in a neurologically compromised host.

The development of 3D cerebral brain organoids which accurately resemble aspects of the human brain permits a more accurate characterization of physiological processes and neurological diseases. Cerebral organoids can be grown from stem cell lines with various genetic backgrounds allowing multiple neurodegenerative diseases to be modeled. While dysfunction in neurotransmission of patients with neurodegenerative diseases is expected, the impact of chronic neurodegeneration on the response to viral infection of the CNS is poorly understood. For instance, several mosquito-borne viruses like Dengue virus and West Nile Virus cause post-viral parkinsonism. How CNS infection might impact a host with inherent CNS dysfunction such as Parkinson’s Disease in poorly understood. This preliminary, observational study aimed to understand dysfunction in intrinsic and innate expression of a patient with a neurodegenerative disease and a non-affected individual in relation to potential viral infection in the CNS. Cerebral organoids were generated from human induced pluripotent stem cells with a normal genetic background or with idiopathic Parkinson’s Disease. After differentiation and maturation, organoid size, gene expression and immunofluorescence were evaluated to assess neurotransmission and innate immunity. While there was no significant difference in size of the organoids with a normal or Parkinson’s genetic background, gene expression studies identified multiple differences in innate immunity and neurotransmission. Immunofluorescence also identified differences in protein expression related to neurotransmission and innate immunity. Of note, organoids derived from a Parkinson’s patient exhibited endogenous up-regulation of dopamine and muscarinic acetylcholine receptors, GABA, glycine, and glutamate targets, and the majority of cytokines. This expression pattern suggests a chronic state of neuroexcitation and neuroinflammation in this population of organoids.

Introduction: Valproic acid (VPA) is an antiepileptic drug extensively used for treating partial and generalised seizures, acute mania and as prophylaxis for bipolar disorder. Drug-induced liver injury (DILI) persists as a significant issue related to fatal outcomes by VPA. The aim of this study was to increase our knowledge about this condition and to better identify patients affected. Methods: We conducted an observational retrospective case-control study that identified cases of DILI by VPA from the Pharmacovigilance Programme from our Laboratory Signals at La Paz University Hospital from January 2007 to December 2019. From the Therapeutic VPA Monitoring Programme, two control groups were assigned, VPA-tolerant patients and the other with patients who developed mild VPA-related hepatitis but who did not meet the DILI criteria, matched for date, age and sex. Results: A total of 60 patients were included in the study: 15 cases of DILI, 30 VPA-tolerant controls and 15 controls with mild hepatitis. Mean age for the cases was 45.7 years, 4(26.7%) were women and 5(33.34%) were children under 18 years, of them 3(20%) were fatal. Polytherapy with other antiepileptic drugs (p=0.047) and alcohol consumption (p<0.001) were associated with a greater risk of developing DILI by VPA. A diagnosis of epileptic seizure was more frequently related to DILI when compared with the VPA-tolerant controls (p<0.001). The cases developed hepatocellular hepatitis (p<0.001), while the mild hepatitis controls had a higher rate of cholestatic hepatitis (p<0.001). The laboratory lactate dehydrogenase values were statistically higher (even at baseline) in patients with DILI than in both control groups (p= 0.033 and p=0.039). Conclusions: VPA hepatotoxicity remains a considerable problem. This study offers interesting findings for characterising VPA-induced liver injury and at-risk patients.

It is important to distinguish between natural earthquakes and those induced by CO2 injection at carbon capture and storage sites. For example, the 2004 Mw 6.8 Chuetsu earthquake occurred close to the Nagaoka CO2 storage site during gas injection, but we could not quantify whether the earthquake was due to CO2 injection or not. Here we simulated changes of pore pressure during CO2 injection at the Nagaoka site and compared them with estimated natural seasonal fluctuations of pore pressure due to rainfall and snowmelt as well as estimated pore pressure increases related to remote earthquakes. We clearly distinguished changes of pore pressure due to CO2 injection from those due to rainfall and snowmelt. The simulated local increase in pore pressure at seismogenic fault area was much less than the seasonal fluctuations related to precipitation and increases caused by remote earthquakes, and the lateral extent of pore pressure increase was insufficient to influence seismogenic faults. We also demonstrated that pore pressure changes due to distant earthquakes are capable of triggering slip on seismogenic faults. The approach we developed could be used to distinguish natural from injection-induced earthquakes and will be useful for that purpose at other CO2 sequestration sites.

We report on space-selective crystallization of congruent and polar Sr2TiSi2O8 crystals in a stoichiometric SrO-TiO2-SiO2 glass induced by (1030 nm, 300 fs) femtosecond laser irradiation. This allows us to compare with non-congruent laser induced crystallization of polar LiNbO3, in non stoichiometric Li2O-Nb2O5-SiO2 glass and gain information on the mechanism of nanocrystals orientation with the laser polarization that we pointed out previously. Using scanning electron microscopy (SEM), Second-harmonic generation (SHG) and electron backscattered diffraction (EBSD), we studied the laser induced crystallization according to the laser processing parameters (pulse energy, pulse repetition rate, scanning speed). We found 1) a domain where the laser track is filled with crystals not perfectly textured (low energy), 2) a domain where an amorphous volume remain surrounded by a crystallized shell (high energy). This arises from Sr out-diffusion and may gives rise to crystallization of both SrTiO3 and Sr2TiSi2O8 phases at low speed. In the one-phase domain (at higher speed), it is found the possibility to elaborate a tube with a perfect fresnoite texture. Significant difference in size and morphology whereas crystallization threshold remains similar are discussed based on glases thermal propeties. Contrarily to Li2O-Nb2O5-SiO2 (LNS) glass, no domain of oriented nanocrystallization controlled by the laser polarization has been found in SrO-TiO2-SiO2 (STS) glass, which is attributed to the larger crystallization speed in STS glass. No nanogratings have also been found that is likely due to the congruency of the glass.

Inertial focusing conditions of fluorescent polystyrene spherical particles are studied at the pointwise level along their pathlines. This is accomplished by an algorithm that calculates a de-gree of spreading function of the particles' trajectories taking streaklines images as raw data. Different confinement ratios of the particles and flow rates are studied and the results are pre-sented in state diagrams showing the focusing degree of the particles in terms of their position within a curve of an asymmetric serpentine and the applied flow rate. In addition, together with numerical simulation results, we present empirical evidence that the preferred trajectories of inertially focused spheres are contained within Dean vortices' centerlines. We speculate about the existence of a new force, never postulated before, to explain this fact.

In this paper, we synthesized MC(BeA-co-MMA) copolymer microcapsules through suspension polymerization. The pendent n-behenyl group of BeA is highly crystalline, and it acts as the side-chain in the structure of BeA-co-MMA copolymer. The highly crystalline n-behenyl side-chain provides BeA-co-MMA copolymer thermal-energy-storage capacity. In order to investigate the correlation between thermal properties and crystal structure of BeA-co-MMA copolymer, the effects of monomer ratio, temperature changing and changing rate, as well as synthesis method were discussed. The monomer ratio influenced crystal transition behavior and thermal properties greatly. The DSC results proved that when the monomer ratio of BeA and MMA was 3:1, MC(BeA-co-MMA)3 showed the highest average phase change enthalpy ΔH (105.1 J·g–1). It indicated that the n-behenyl side-chain formed relatively perfect crystal region, which ensured a high energy storage capacity of copolymer. All the DSC and SAXS results proved that the amount of BeA had a strong effect on the thermal-energy-storage capacity of copolymer and the long spacing of crystals, but barely on the crystal lamella. It was found that MMA units worked like defects in the n-behenyl side-chain crystal structure of BeA-co-MMA copolymer. Therefore, a lower fraction of MMA, that is, a higher fraction of BeA contributed to a higher crystallinity of BeA-co-MMA copolymer for providing a better energy storage capacity and thermoregulation property. ST(BeA-co-MMA) copolymer sheets with the same ingredients as microcapsules were also prepared through light-induced polymerization aiming at clarifying the effect of synthesis method. The results proved that synthesis method mainly influenced the copolymer chemical component, but lightly on the crystal packing of n-behenyl side-chain.

Q-switched laser radiation at wavelengths of 355 nm, 532 nm, and 1064 nm from a Nd: YAG laser was used to generate plasma in laboratory air at the target surface made of compressed nano-silver particles of size 95 ± 10 nm. The emitted resonance spectra from the neutral silver at wavelengths of 327.9 nm and 338.2 nm indicate existence of self-reversal in addition to plasma self-absorption. Both lines were identified in emission spectra at different laser irradiation wavelengths with characteristic dips at the un-shifted central wavelengths. These dips are usually associated with self-reversal. Under similar conditions, plasmas at the corresponding bulk silver target were generated. The recorded emission spectra were compared to those obtained from the nano-material target. The comparisons confirm existence of self-reversal of resonance lines that emerge from plasmas produced at nano-material targets. This work suggests a method for recovery of the spectral line shapes and discusses practical examples. In addition, subsidiary calibration efforts that utilize the Balmer series Hα-line reveal that other Ag I lines at 827.35 nm and 768.7 nm are optically thin under variety of experimental conditions and are well-suited as reference lines for measurement of the laser plasma electron density.

In this research, the computational fluid dynamic (CFD) approach that has been used in wind power generation field was applied for the solution of the problems of local strong wind areas in railway fields, and the mechanism of wind generation was discussed. At the same time, the affectivity of the application of computational fluid dynamic approach to railway field was discussed. The problem of local wind that occurs on the railway line in winter was taken up in this research. A computational simulation for the prediction of wind conditions by LES was implemented and it was clarified that the local strong wind area is mainly caused by separated flows originating from the small‐scale terrain positioned at its upstream (at approximately 180.0 m above sea level). Meanwhile, the effects of the size of calculation area and spatial grid resolution on the result of calculation and the effect of atmospheric stability were also discussed. It was clarified that when the air flow characteristic of the separated flow originating from the small‐scale terrain (at altitude of approximately 180.0 m) targeted in this research is reproduced at high accuracy by computational simulation of wind conditions, approximately 10.0 m of spatial resolution of computational grid in horizontal direction is required. As a result of the computational simulation of wind conditions of stably stratified flow (Fr = 1.0), lee waves were excited at the downstream of the terrain over time. As a result, the reverse‐flow region lying behind the terrain that had been observed at a neutral time was inhibited. Consequently, local strong wind area was generated at the downstream of the terrain and the strong wind area passing through the observation mast was observed. By investigating the speed increasing rate of local strong wind area induced at the time of stable stratification, it was found that the wind was approximately 1.2 times stronger than what was generated at a neutral time.

Electrically conductive polymer composites are in high demand for modern technologies, however, the intrinsic brittleness of conducting conjugated polymers and the moderate electrical conductivity of engineering polymer/carbon composites have highly constrained their applications. In this work, super high electrical conductive polymer composites were produced by a novel hot embossing design. The polydimethylsiloxane (PDMS) composites containing short carbon fiber (SCF) exhibited an electrical percolation threshold at 0.45 wt%, and reached a saturated electrical conductivity of 49 S/m at 8 wt% of SCF. When reduced the sample thickness from 1.0 mm to 0.1 mm by the hot embossing process, a compression-induced percolation threshold occurred at 0.3 wt%, while the electrical conductivity was further enhanced to 378 S/m at 8 wt% SCF. Furthermore, the additional of a second nanofiller of 1 wt%, such as carbon nanotube or conducting carbon black further increased the electrical conductivity of the PDMS/SCF (8 wt%) composites to 909 S/m and 657 S/m, respectively. The synergy of the densified conducting filler network by the mechanical compression and the hierarchical micro-/nanoscale filler approach has realize super high electrical conductive yet mechanical flexible polymer composites for modern flexible electronics applications.

This work communicates results from optical emission spectroscopy following laser-induced optical breakdown at or near nanomaterial. Selected atomic lines of silver are evaluated for consistent determination of electron density. Comparisons are presented with Balmer series hydrogen results. Of particular interest are measurements free of self-absorption effects. For several silver lines, asymmetries are observed in the recorded line profiles. Electron densities of interest range from 0.5 to 3 × 10¹⁷ cm^-3, for 5 nanosecond Q-switched Nd:YAG radiation at wavelengths of 1064, 532, and 355 nm, and for selected silver emission lines including 328.0, 338.2, 768.7, and 827.3 nm, and the hydrogen alpha Balmer series line at 656.3 nm. Line asymmetries are presented for the 328.0 nm Ag I line that is measured following generation of the plasma due to multiple photon absorption. This work explores electron density variations for different irradiance levels, and reports spectral line asymmetry of resonance lines for different laser fluence levels.

Direct reprogramming of fibroblasts into induced cardiomyocytes (iCMs) holds a great promise for regenerative medicine and has been studied in several major directions. However, cell-cycle regulation, a fundamental biological process, has not been investigated during iCM-reprogramming. Here, our time-lapse imaging on iCMs, reprogrammed by Gata4, Mef2c, and Tbx5 (GMT) monocistronic retroviruses, revealed that iCM-reprogramming was majorly initiated at late-G1- or S-phase and nearly half of GMT-reprogrammed iCMs divided soon after reprogramming. iCMs exited cell cycle along the process of reprogramming with decreased percentage of EdU⁺/αMHC-GFP⁺ cells. S-phase synchronization post-GMT-infection could enhance cell-cycle exit of reprogrammed iCMs and yield more GFP^high iCMs, which achieved an advanced reprogramming with more expression of cardiac genes than GFP^low cells; however, S-phase synchronization didn’t enhance the polycistronic-MGT reprogramming, in which cell-cycle exit had been accelerated. In conclusion, post-infection synchronization of S-phase facilitated the early progression of GMT-reprogramming through a mechanism of enhanced cell-cycle exit.

For esophageal cancer patients treated with neoadjuvant chemoradiotherapy (nCRT), restaging using F-18-fluorodeoxyglucose (18F-FDG) positron emission tomography computed tomography (PET-CT) following nCRT can detect interval metastases, including liver metastases, in almost 10% of patients. However, in clinical practice, focal FDG liver uptake, unrelated to liver metastases, is observed after chemoradiotherapy. This radiation-induced liver injury (RILI) can potentially lead to overstaging. Liver radiation damage is also a concern during distal esophageal cancer radiotherapy due to proximity to the left liver lobe, typically included in the radiation field. Post-CRT, if FDG activity appears in the left or caudate liver lobes, thorough investigation is needed to confirm or rule out distant metastases. The increased FDG uptake in liver lobes post-CRT often presents a diagnostic dilemma. Distinguishing between radiation-induced liver disease and metastasis is vital for appropriate patient management, necessitating a combination of imaging techniques and an understanding of the factors influencing radiation response. Diagnosis involves identifying new foci of hepatic FDG avidity on PET/CT scans. Geographic regions of hypoattenuation on CT and well-demarcated regions with specific enhancement patterns on contrast-enhanced CT scan and MRI are characteristic of radiation-induced liver disease (RILD). Lack of mass effect on all three modalities (CT, MRI, PET) indicates RILD. Resolution of abnormalities on subsequent examinations also helps in diagnosing RILD. Moreover, it can also help to rule out occult metastases, thereby excluding those patients from further surgery who will not benefit from esophagectomy with curative intent.

The article presents investigations of rail vehicle bogie of Y25 type. The Y25 bogie family is one of the most commonly used freight car bogie designs. In addition to several significant advantages characterising this design, it also has several disadvantages observed since the beginning of more than fifty years of operation in several types of cargo vehicles. One of these defects observed in real systems is "unsatisfactory running stability", particularly at long straight tracks. The article used commercial engineering software VI-Rail to create a model of the gondola car (type 412W Eaos) with two Y25 bogies. The car model was tested empty and loaded (maximum permissible load). Motion along straight and curved tracks with different radii values was analysed. The vehicle velocity was changed from a few m/s to the maximum values for which stable solutions of the model existed. For each route, a non-linear critical velocity was determined, defining the maximum operating velocity of the modelled car. The model solutions were recorded, while just one was selected to present the results - the first wheelset lateral displacement ylw. The opinion about the "imperfect running quality" in curved tracks was confirmed. The possible appearance of self-exciting wheelset vibrations in the modelled car's operating velocity range in the laden state was also observed. The research results on the impact of the bogie suspension parameters change on the vehicle model stability are presented. The crucial parameter in the bogie suspension was indicated. Reducing its value by several percent about the nominal value increases the critical velocity of the car to values higher than the maximum operating velocity of the modelled vehicle.

We propose a novel unsupervised semantic segmentation method for fast and accurate flood area detection utilizing color images acquired from Unmanned Aerial Vehicles (UAVs). To the best of our knowledge, this is the first fully unsupervised method for flood area segmentation in color images captured by UAVs, without the need of pre-disaster images. The proposed framework addresses the problem of flood segmentation based on parameter-free calculated masks and unsupervised image analysis techniques. First, a fully unsupervised algorithm gradually excludes areas classified as non-flood utilizing calculated masks over each component of the LAB colorspace, as well an RGB vegetation index and the detected edges of the original image. Unsupervised image analysis techniques, such as distance transform, are then applied, producing a probability map for the location of flooded areas. Finally, flood detection is obtained by applying the hysteresis thresholding segmentation. The proposed method is tested and compared with variations, and other supervised methods in two public datasets, consisting of 953 color images in total, yielding high-performance results, with 87.4% and 80.9% overall accuracy and F1-Score, respectively. The results and computational efficiency of the proposed method show that it is suitable for on board data execution and decision-making during UAVs flight.

When wildlife and motor vehicles collide, the result for the animals is often death (roadkill). A commercial roadkill Virtual Fence (VF) mitigation device (iPTE Traffic Solutions) was used in a field trial to test its effectiveness along a 4.9-km segment of road on Bruny Island, Tasmania. A total of 585 days of monitoring of roadkill by species was conducted, with six sections alternatively switched on or off, according to a variation of a Crossover and Multiple Before-After-Control-Impact (MBACI) experimental designs that divided monitoring into “off-on” then “on-off” blocks of periods with each “on” period followed by a 16 d “wash-out” period. For the six sections over the four periods that exclude wash-outs, the 24 aggregated values of daily counts of roadkill of Tasmanian pademelons (Thylogale billardierii), that gave a total count of 222, were modelled. Other species were killed in insufficient numbers for analysis to be informative. The statistical analysis exploited the MBACI design to estimate the VF effect using a log-odds ratio parameter (LORP) while accounting for local spatio-temporal effects. Both versions of the analysis, either averaging over the three spatial replicates (paired sections) or two temporal replicates (blocks) gave no statistically significant effect of the VF judged as a LORP estimate not sufficiently below zero. Corresponding percentage reduction estimates of 9% and 16% were derived from the LORP estimates and given parameter uncertainty estimates the power to detect as significant a LORP corresponding to a 50% reduction in rate were 0.5 and 0.6, respectively. This study confirms results from a similar field trial carried out in 2018 also in southern Tasmania and adds to the evidence that this VF is likely to give if anything only a minor reduction in roadkill for a commonly killed species for which researchers have the best chance of detecting any practically useful reduction.

Background: Previous investigations have found a correlation between abnormal curvatures and a variety of patient complaints such as cervical pain and disability. However, no study has shown that loss of the cervical curve is a direct result of exposure to a motor vehicle collision (MVC). This investigation presents a retrospective consecutive case series of patients with both a pre-injury cervical lateral radiograph (CLR) and a post-injury CLR after exposure to a MVC. Computer analysis of digitized vertebral body corners on CLRs was performed to investigate the possible alterations in the geometric alignment of the sagittal cervical curve. Methods: Three spine clinic records were reviewed, over a 2-year period, looking for patients where both an initial lateral cervical x-ray and an examination were performed prior to the patient being exposed to a MVC; afterwards an additional exam and radiographic analysis were required. A total of 41 patients met the inclusion criteria. Examination records of pain intensity on numerical pain rating scores (NPRS) and neck disability index (NDI), if available, were analyzed. The CLRs were digitized and modeled in the sagittal plane using curve fitting and the least squares error approach. Radiographic variables included total cervical curve (ARA C2-C7), Chamberlain’s line to horizontal (skull flexion), horizontal translation of C2 relative to C7, segmental translations (retrolisthesis and anterolisthesis), and circular modelling radii. Results: There were 15 males and 26 females with an age range of 8-65 years. Most participants were drivers (28) involved in rear end impacts (30). The pre-injury NPRS was 2.7 while the post injury was 5.0; p &lt; 0.001. The NDI was available on 24 /41 (58.5%) patients and was found to increase following exposure to the MVC: 15.7% to 32.8%, p &lt; 0.001. An altered cervical curvature was identified following exposure to MVC, characterized by an increase in radius of curvature and an approximate 8° reduction of lordosis from C2-C7; p &lt; 0.001. The mid cervical spine (C3-C5) showed the greatest curve reduction with localized mild kyphosis at these levels on average. Several participants developed segmental translations that approached the instability value of translation &gt; 3.5mm. Conclusions: Abnormalities of cervical lordosis occurred following exposure to a MVC. The average loss of cervical curvature was 8° from C2-C7, with mild flexion of the mid cervical segments. Snap through type or dynamic buckling during the MVC may explain our findings. The primary contribution of this study to the motor vehicle collision literature is that altered cervical lordosis may result from MVC exposures and the consequences of an altered cervical alignment, in turn, may lead to future pain, disability and decreased health-related quality of life.

Efficient processing of end-of-life lithium-ion batteries of electric vehicles is important and a pressing challenge for a circular economy. Regardless of whether the processing strategy is recycling, repurposing or remanufacturing, the first processing step would usually involve disassembly. As battery disassembly is a dangerous task, efforts have been made to robotise it. In this paper, a robotic disassembly platform using four industrial robots is proposed to automate the non-destructive disassembly of a plug-in hybrid electric vehicle battery pack into modules. The work was conducted as a case study to demonstrate the concept of autonomous disassembly of an electric vehicle battery pack. A two-step object localisation method based on visual information is used to overcome positional uncertainties from different sources and is validated by experiments. Also, the unscrewing system is highlighted, and its functions, such as handling untightened fasteners, loosening jammed screws, and changing the nutrunner adapters with square drives, are detailed. Furthermore, the time required for each operation is compared with that taken by human operators. Finally, the limitations of the platform are reported and future research directions are suggested.

In the field of engineering, tracked vehicles play a significant role in accessing challenging terrains. Maintaining trafficability is of the utmost importance when it comes to tracked vehicles traversing rugged terrains; it provides stability, traction, and adaptability for a wide range of applications, including deep-sea exploration. The terrain characteristics pertain to the interactions that determine the mobility of tracked vehicles. Traditional Terramechanics models are in-adequate in depicting the correlation between tracks and soil. An important issue is the lack of consideration for the moisture content in the soil and the rate at which sinking occurs in these models. Examining sinkage speed helps describe the ability of tracked vehicles to move at high speeds. The focus is on the critical factors influencing the mobility of tracked vehicles, precisely the sinkage speed and its relationship with pressure. Experimental tests in a soil bin, utilizing Bentonite/Diatom sediment soil, aim to measure these terrain factors. The study introduces a rubber-tracked vehicle, pressure, and moisture sensors to monitor pressure sinkage and moisture, evaluating cohesive soils (Bentonite/Diatom) in combination with sand and gravel mixtures. Findings reveal that higher moisture content in Bentonite soil leads to increased track slippage and sinkage compared to Diatom soil. Regarding soil behavior, diatom soil exhibited notable compaction and sinkage characteristics in contrast to bentonite soil. The distinct behaviors of these soils underscore the complexity of terrains, emphasizing the need for a meticulous understanding of soil properties before applying them in natural environments. Furthermore, this study contributes precision in assessing natural terrains, enhancing tracked vehicle design, and advancing terrain mechanics comprehension for off-road exploration. This knowledge contributes to better vehicle design and a deeper comprehension of terrain mechanics.

This study assesses the applicability of different-resolution multispectral remote sensing images for mapping and estimating the aboveground biomass (AGB) of Carpobrotus edulis, a prominent invasive species in European coastal areas. The performance of three sets of multispectral images with different resolutions was compared: (i) 2.5 cm Ground Sample Distance (GSD), 5 cm GSD and 10 cm GSD images. The images were classified using the supervised classification algorithm Random Forest and later improved applying a sieve filter. The results show that the three tested image resolutions allow constructing reliable coverage maps of C. edulis, with Overall Accuracy values of 89%, 85% and 88% for the classification of the 2.5 cm, 5 cm and 10 cm GSD images, respectively. Samples were also collected, dried and weighed to estimate AGB using the relationship between the Dry Weight and Vegetation Indices (VI). The regressions were evaluated based on their R² and Normalised RMSE. The best-performing VI-DW regression models achieved: R² = 0.87 and NRMSE = 0.09 for the 2.5 cm resolution; R² = 0.77 and NRMSE = 0.12 for the 5 cm resolution; and, R² = 0.64 and NRMSE = 0.15 for the 10 cm resolution. C. edulis area and total AGB were: 3441.10 m² and 28,327.1 kg (with a Relative Error (RE) = 0.08), for the 2.5 cm resolution; 3070.04 m² and 29,170.8 kg (RE = 0.08), for the 5 cm resolution; and, 2305.06 m² and 22,135.7 kg (RE = 0.11), for the 10 cm resolution. Differences were analysed in detail, spatially, to determine their causes. Final analyses suggest that, for C. edulis, multispectral imagery of up to 5 cm GSD is adequate for the estimation of the species’ distribution and biomass.

Tracked vehicles play a vital role in accessing challenging terrains, offering stability, traction, and versatility for various applications, including deep-sea exploration. However, the seafloor and sediment contain valuable but poorly understood resources, making it a significant challenge for tracked vehicles during exploration. Consequently, it is imperative to conduct comprehensive studies before considering these terrains for off-road purposes. In this study, we developed a rigid, flexible track vehicle equipped with various sensors, focusing on monitoring pressure sinkage. Cohesive soils like Bentonite and Diatom soil, particularly when combined with sand and gravel mixtures, were used for the investigation and assessed for ground pressure, bearing capacity, and sinkage in rigid-flexible tracked vehicles on these characterized terrains under varying moisture conditions. Our findings indicated that increased moisture content in bentonite soil resulted in significantly higher track slippage and sinkage compared to diatomaceous earth soil. Regarding soil behavior, diatom soil exhibited notable compaction and sinkage characteristics compared to bentonite soil. These significant variations between these two soil types under changing moisture conditions highlight the complexity of such terrains. Therefore, understanding the soil and its physical properties is crucial before applying them to natural terrains. Furthermore, this study emphasizes the importance of precision in assessing the physical properties of natural terrains for the development of tracked vehicles for off-road exploration. This knowledge contributes to better vehicle design and a deeper comprehension of terrain mechanics.

The rapid growth of equipment tasks in 5G large-scale machine-type communication scenarios presents challenges due to user equipment’s (UE) limited computing power and power constraints. To address these limitations, task offloading to unmanned aerial vehicles (UAVs) has gained attention. However, traditional cloud computing centres far from the UE fail to meet latency requirements. Mobile Edge Computing (MEC) emerges as a solution by deploying computing servers at the edge of the cellular network to enhance service responsiveness. However, traditional MEC solutions need more flexibility. This paper explores the advantages of UAVs, including flexibility and rapid deployment, and considers UAV power constraints. It proposes a joint optimization approach for user offloading strategies and UAV trajectories to minimize the overall energy consumption of UE. By leveraging the benefits of UAVs and MEC, the proposed method aims to improve task execution efficiency in energy-constrained 5G machine-type communication scenarios.

In this work, we propose a Fog-enabled UAV-as-a-Service (FU-Serve) architecture to address the issues of data transmission delay for serving time-critical Internet of Things (IoT) applications. Traditionally, in a UAV-as-a-Service (UaaS) platform, different UAVs host heterogeneous sensors, which sense the physical phenomenon and transmit the sensed data to a centralized entity. Transmission of data from the sensors to the centralized entity and making any decision for an application consumes a significant amount of time. Consequently, the traditional UaaS architecture is unsuitable for serving time-critical IoT applications such as transportation, healthcare, and industries. To address these issues of service latency for time-critical IoT applications, we present the FU-Serve architecture by introducing the concept of fog computing in the UaaS platform. We discuss all the components of FU-Serve elaborately in this paper. Additionally, we architect optimal and dynamic fog node selection mechanisms for FU-Serve, which reduce the transmission delay in the networks. The simulation results show that the FU-Serve outperforms by $75\%$ compared to the traditional UaaS platform.

Traffic congestion and frequent traffic accidents have become main problems affecting urban traffic. Effective location prediction of vehicle trajectory can help alleviate traffic congestion, reduce the occurrence of traffic accidents, and optimize the urban traffic system. Vehicle trajectory is closely related to the surrounding Points of Interest (POI). POI can be considered as the spatial feature and can be fused with trajectory points to improve prediction accuracy. A Local Dynamic Graph Spatiotemporal- Long Short-Term Memory (LDGST-LSTM) is proposed in this paper to extract and fuse the POI knowledge and realize next location prediction. POI semantic information is learned by constructing the traffic knowledge graph, and spatial and temporal features are extracted by combining Graph Attention Network (GAT) and temporal attention mechanism. Moreover, the weights of POI that influence location prediction are visualized to improve the interpretability of the proposed model. The effectiveness of LDGST-LSTM is verified on two datasets, including Chengdu taxi trajectory data in October 2018 and August 2014. The accuracy and robustness of the proposed model are significantly improved compared with the benchmark models.

Traffic signal control plays a key role in managing urban traffic flow, enhancing safety, and minimizing congestion and conflicts. Effective green time allocation is a critical element of this control process. This research explores the utilization of LiDAR sensor technology in the optimization of green time allocation for one phase of a traffic signal at a signalized intersection. LiDAR sensors provide precise and real-time data on vehicle presence and traffic patterns, enabling a data-driven approach to traffic signal control. The study begins with an analysis of the limitations of traditional traffic signal control strategies, which often rely on fixed-time plans or rudimentary vehicle detection systems. These approaches can lead to suboptimal green time allocation, resulting in inefficient traffic management and increased vehicle delays.The integration of LiDAR sensors provides detailed information on vehicle queues, arrival rates, and vehicle types. The research presents a practical framework for green time allocation optimization, considering factors such as intersection geometry, traffic volumes, and signal coordination. An intelligent control algorithm was developed that uses LiDAR data to determine the optimal green time for a specific phase, thereby reducing unnecessary waiting times and enhancing intersection efficiency. The effectiveness of the proposed LiDAR-based green time allocation strategy is demonstrated through extensive field tests. The results indicate significant improvements in intersection throughput, reduced delays, and enhanced traffic safety. In conclusion, this research highlights the transformative potential of LiDAR sensor technology in traffic signal control, specifically in the context of optimizing green time allocation. The findings support the notion that adaptive and data-driven strategies, when integrated with LiDAR sensors, can contribute to more efficient, sustainable, and safe urban traffic management. This research aims to provide valuable insights for transportation engineers, policymakers, and researchers seeking innovative solutions for modern urban traffic control.

In response to the issue of vehicle escape guidance, this manuscript proposes a unified intelligent control strategy synthesizing optimal guidance and Meta Deep Reinforcement Learning (DRL). Optimal control with minor energy consumption is introduced to meet terminal latitude, longitude and altitude. Maneuvering escape is realized by adding longitudinal and lateral direction maneuver overloads. Maneuver command decision model is calculated based on Soft-Actor-Critic (SAC) networks. Meta learning is introduced to enhance autonomous escape capability, which improves generalization performance to time-varying scenarios not encountered in the training process. In order to obtain training samples at a faster speed, this manuscript uses the prediction method to solve reward values, which avoiding a large number of numerical integration. The simulation results manifest that the proposed intelligent strategy can achieve high precise guidance and effective escape.

The application of deep learning in the detection of Synthetic Aperture Radar (SAR) targets has been primarily limited to large objects such as ships and airplanes, with much less popularity in detecting SAR vehicles. The complexities of SAR imaging make it difficult to distinguish small vehicles from the background clutter, creating a barrier to data interpretation and the development of Automatic Target Recognition (ATR) in SAR vehicles. The scarcity of datasets has inhibited progress in SAR vehicle detection in the data-driven era. To address this, we introduce a new synthetic dataset called Mix MSTAR, which mixes target chips and clutter backgrounds with original radar data at the pixel level. Mix MSTAR contains 5,392 objects of 20 fine-grained categories in 100 high-resolution images, predominantly 1478x1784 pixels. The dataset includes various landscapes such as woods, grasslands, urban buildings, lakes, and tightly arranged vehicles, each labeled with Oriented Bounding Box (OBB). Notably, Mix MSTAR presents fine-grained object detection challenges by using the Extended Operating Condition (EOC) as a basis for dividing the dataset. Furthermore, we evaluate 9 benchmark rotated detectors on Mix MSTAR and demonstrate the fidelity and effectiveness of the synthetic dataset. To the best of our knowledge, Mix MSTAR represents the first public multi-class SAR vehicle dataset designed for rotated object detection in large-scale scenes with complex background. Mix MSTAR is available at: https://github.com/TheGreatTreatsby/Mix-MSTAR-mmrotate.

In the computational prediction of bridge vibrations due to high-speed train traffic, the most accurate results can be obtained by considering the interaction dynamics between the train, the superstructure, and the supporting structure. To achieve this, a detailed understanding of the coupling properties of all elements is crucial as they significantly influence the calculated vibrations. The studies in this article investigate the influence of different levels of modeling complexity on the computational acceleration results of single-span girder bridges with a ballasted superstructure. A numerical study on an extensive parameter field of single-span girder bridges is conducted to investigate the influence of modeling the bridge structures as coupling beams, i.e., by considering them as two vertically coupled beams representing the track (rails and sleepers) and the supporting structure. The connection between both beams reflects the stiffness and damping properties of the ballasted superstructure and can reproduce its load-distribution capacity. The excitation is applied as either a moving load or a multi-body model of the train, an Austrian Railjet, to evaluate interdependencies of interaction effects between the vehicle and track, and between track and bridge structure. The reference model is a simply-supported Bernoulli-Euler beam excited by moving axle loads. The comparison of acceleration results allows for identifying critical combinations of structural and train parameters for which the implementation of interaction dynamics has a particularly significant impact on the calculated vibrations and quantifying that impact. These findings provide the possibility of formulating structure-dependent recommendations concerning the targeted application of more complex modeling of the structure (coupling beam model) on the one hand and train (multi-body model) on the other.

This article addresses the problem of contact voltage increase caused by the low frequency oscillation of the train-grid system in the phase-separation process of the EMU. The article establishes the EMU-contact line-traction substation model, reveals the mechanism of low-frequency oscillation, and obtains the relationship between the separation phase angle of the pantograph with line and low-frequency oscillations. Methods to suppress the over-voltage during the low-frequency oscillation are proposed. The study shows that when the power phase angle of the pantograph-line separation is within the range of 60°~90° and 240°~270°, the voltage amplitude in the neutral zone is larger, the maximum amplitude can reach 52.2kV, and low-frequency oscillation will occur in the neutral zone. When low frequency oscillation occurs, the contact line voltage in the neutral zone is mainly 1/3 power frequency (16.7Hz). After installing an RC suppression device in the neutral zone, when the EMU enters the neutral zone, the absolute value of the voltage peak drops to below 20 kV. Compared with the situation where the suppression device is not connected, the absolute value of the voltage peak is reduced by nearly 60%. The study provides a basis for the design of the neutral zone of the contact line and the selection of the high-voltage equipment of the EMU.

In Thailand, parking time violation is a major problem, especially for mini-marts. At present the task of detecting parking time violation is mainly conducted manually using Closed-Circuit Television (CCTV). This method requires additional human labour to track incoming and outgoing vehicles. Therefore, low cost time violation tracking is needed. To the best of our knowledge, there has not been any research for parking violation detection and tracking conducted for parking time limits. This paper introduces a novel parking time violation detection algorithm using the Yolov8 and DeepSORT tracking algorithms to track vehicles in consecutive frames. The presented parking violation tracking algorithm can provide a guideline for research in parking time violation detection.

Vehicle HVAC systems can accumulate and recirculate highly infectious respiratory diseases via aerosols. Integrating UVC to complement automobile HVAC systems can protect occupants from developing allergies, experiencing inflammatory problems, or acquiring respiratory infectious diseases by inactivating pathogenic organisms. UVC can add little to no static pressure with minimal space, unlike mercury lamps which are larger and heavier. Additionally, UVC LEDs are effective at low voltage and have no mercury or glass. While previous experiments have shown UVC LED technology can reduce bacteriophage Phi6 concentrations by 1 log in 5 minutes (selected as the average time to clean the cabin air), those studies had not positioned LED within the HVAC itself or studied the susceptibility of the surrogate at the specific wavelength. This study aimed to assess the disinfection performance of UVC LEDs in automotive HVAC systems and determine the dose-response curve for bacteriophage Phi6, a SARS-CoV-2 surrogate. To achieve this, UVC LEDs were installed in a car HVAC system. To determine inactivation efficacy, a model chamber of 3.5 m3, replicating the typical volume of a car, containing the modified automobile HVAC system was filled with bacteriophage Phi6, and the HVAC was turned on with and without the UVC LEDs being turned on. The results revealed that HVAC complemented with UVC reduced bacteriophage Phi6 levels significantly more than the HVAC alone and reduced the viral concentration in the cabin by more than 1 LRV (90% viral reduction) in less than 5 minutes. The performance after 5 minutes is expected to be significantly better against SARS-CoV-2 because of its higher sensitivity to UVC, especially at lower wavelengths (below 270 nm). HVAC alone could not achieve a 90% viral reduction of bacteriophage Phi6 in 15 minutes. Applying UVC LEDs inside an HVAC system is an effective means of quickly reducing the number of aerosolized viral particles in the chamber, by inactivating microorganisms leading to improved cabin air quality.

This paper focuses on the comparative analysis of lithium-ion batteries (LIB) thermal management with aim to maintain working temperature in the range 15 ℃ – 35 ℃. This is to prevent thermal runaway and high temperature gradients. The proposed approach is to employ the biodiesel, situated inside the diesel/LIB powered hybrid electric vehicle, to supply as fuel and coolant. A 3S2P LIB module is simulated using Ansys-Fluent CFD software tool. The system without a coolant shows that LIB has exceeded the optimum maximum temperature, which leads to shortened life-cycle and poor performance. Four fatty acid methyl ester biodiesels are used as coolants, namely palm, karanja, jatropha, and mahua oils. When compared with conventional methods of cooling, using air and 3M Novec liquid, the palm biodiesel coolant proves to be the best option to maintain LIB temperature within the optimum working range. With the use of palm biodiesel, the system is estimated to lightweight the BTMS by 43%, compared to the case when 3M Novec is used to maintain the same temperature range.

This paper presents a cooperative parallel tabu search meta-heuristic for the vehicle routing problem with time windows. It is based on the scheme in which several search threads cooperate by asynchronously exchanging information on the best solutions identified. The exchanges are performed through a mechanism called adaptive memory which holds and manages a pool of solutions. This enforces the asynchronous strategy of information exchanges and ensures the independence of the individual search threads. Each of these independent threads implements a tabu search meta-heuristic. Comprehensive computational experiments and comparisons to best known solutions show that the proposed cooperative parallel tabu search algorithm is able to achieve 48 new best solutions on VRPTW benchmark instances.

This study provides a thorough review and analysis of the evolution of the Greek vehicle fleet over the last ~30 years, which is next used for the generation of high granularity fleet projections and for the estimation of relevant environmental benefits by 2030. The integrated methodology developed takes also into account vehicle clustering and the Brown’s Double Simple Exponential Smoothing technique that together with the adoption of COPERT based emission factors allow for the estimation of the anticipated emissions in 2030. Expected 2030 emissions levels suggest a reduction across all pollutants in comparison to 2018, ranging from 3.7% for PM10 to 54.5% for NMVOC (and 46% for CO, 14% for SO2, 28% for NOX and 21% for CO2). We find that Greece is on track with national goals concerning the reduction of air pollution from the transportation sector, stressing the positive contribution of EVs and new, "greener" vehicles, and setting new challenges for the further improvement of the sector beyond the 2030 outlook.

This paper investigates the path following control problem for a unmanned surface vehicle (USV) in the presence of unknown disturbances and system uncertainties. The simulation study combines two different types of sliding mode surface based control approaches due to its precise tracking and robustness against disturbances and uncertainty. Firstly, an adaptive linear sliding mode surface algorithm is applied, to keep the yaw error within the desired boundaries and then an adaptive integral non-linear sliding mode surface is explored to keep an account of the sliding mode condition. Additionally, a method to reconfigure the input parameters in order to keep settling time, yaw rate restriction and desired precision within boundary conditions is presented. The main strengths of proposed approach is simplicity, robustness with respect to external disturbances and high adaptability to static and dynamics reference courses without the need of parameter reconfiguration.

In this study, the external magnetic field emitted by a wireless power transfer (WPT) system and the internal electric field induced into human body models during recharging operations of a compact electric vehicle (EV) are evaluated. To this aim an ad-hoc formulation for the source modeling is coupled with a commercial software that performs numerical dosimetry. Specifically, two realistic anatomical models both in a driving position and in a standing posture are considered, and the chassis of the EV is modeled either as a currently employed aluminum alloys and as a futuristic carbon fiber composite panel. Aligned and misaligned coil configurations of the WPT system are considered as well. The analysis of the obtained results shows that the ICNIRP reference levels are exceeded in the driving position, especially for the carbon fiber chassis, whereas no exceedance is observed in terms of basic restrictions, at least for the considered scenarios.

Considering the significant advancements in autonomous vehicle technology, research in this field is of interest to researchers. To drive vehicles autonomously, controlling steer angle, gas hatch, and brakes need to be learned. The behavioral cloning method is used to imitate humans’ driving behavior. We created a dataset of driving in different routes and conditions and using the designed model, the output used for controlling the vehicle is obtained. In this paper, the Learning of Self-driving Vehicles Based on Real Driving Behavior Using Deep Neural Network Techniques (LSV-DNN) is proposed. We designed a convolutional network which uses the real driving data obtained through the vehicle’s camera and computer. The response of the driver is during driving is recorded in different situations and by converting the real driver’s driving video to images and transferring the data to an excel file, obstacle detection is carried out with the best accuracy and speed using the Yolo algorithm version 3. This way, the network learns the response of the driver to obstacles in different locations and the network is trained with the Yolo algorithm version 3 and the output of obstacle detection. Then, it outputs the steer angle and amount of brake, gas, and vehicle acceleration. The LSV-DNN is evaluated here via extensive simulations carried out in Python and TensorFlow environment. We evaluated the network error using the loss function. By comparing other methods which were conducted on the simulator’s data, we obtained good performance results for the designed network on the data from KITTI benchmark, the data collected using a private vehicle, and the data we collected.

This study aims to develop a hybrid approach based on backpropagation Artificial Neural Network (ANN) and spatial analysis techniques to predict particulate matter of size 2.5 µm (PM2.5) from vehicle exhaust emissions in the State of California using Aerosol Optical Depth (AOD) and several climatic indicators (relative humidity, temperature, precipitation, and wind speed). The PM2.5 data were generated using Motor Vehicle Emission Simulator (MOVES), the measured climatic variables and AOD were obtained from the California Irrigation Management Information System (CIMIS), and NASA’s Moderate Resolution Spectroradiometer (MODIS). The data were resampled to a seasonal format and downscaled over grids of 10 by 10 to 150 by 150, and precipitation was determined to be the most important independent variable. Coefficient of determination ( ), Mean Absolute Percentage Error (MAPE), and Root Mean Square Error (RMSE) were used to assess the quality of the ANN prediction model. The model peaked at winter seasons with = 0.984, RMSE = 0.027, and MAPE = 25.311, whereas it had the lowest performance in summer with = 0.920, RMSE = 0.057, and MAPE = 65.214. These results indicate that the ANN model can accurately predict the PM2.5 concentration and can be used to forecast future trends.

Based on the theory of turbulence, equations are derived for estimations of turbulent fluctuations of the longitudinal and transverse components of the wind velocity during ideal hovering of a quadcopter in a turbulent atmosphere. We present the results of experiments which were carried out on the territory of the Geophysical Observatory of Institute of Monitoring of Climatic and Ecological Systems, Siberian Branch, Russian Academy of Sciences, located in Tomsk Akademgorodok on the territory with complex orography, in a parkland zone with buildings of research institutes and motorways. Time series of turbulent fluctuations of the longitudinal and transverse components of wind velocity fluctuations were received with the use of an automated weather station, and time series of estimates of these components, from data of a DJI Phantom 4 Pro quadcopter during hovering. According to the automated weather station data, anisotropy was observed in one experiment during measurements in the atmosphere, but this phenomenon was not observed in the other experiment: the fluctuation spectra of all components of wind speed fluctuations coincide. The spectra of fluctuations of the longitudinal and transverse wind velocity components based on the automated weather station data and UAV telemetry are presented. The fluctuation spectra of these components for the automated weather station data and quadcopter generally coincide. The behavior of the spectra coincides with the spectrum which corresponds to Kolmogorov–Obukhov “–5/3” law within the inertial range. The turbulent spectra of the wind velocity fluctuations obtained with the use of the automatic weather station and with the unmanned aerial vehicle differ in the high-frequency spectral region.

Over the past decade, wireless communication technologies have developed significantly for intelligent applications in road transport. This paper provides an overview of telecommunications-based intelligent transport systems with a focus on ensuring system safety and resilience. In vehicle-to-everything, these problems are extremely acute due to the specifics of the operation of transport networks, which requires the use of special protection mechanisms. In this regard, it was decided to use blockchain as a system platform to support the needs of transport systems for secure information exchange. This paper describes the technological aspects of implementing blockchain technology in vehicle-to-network; the features of such technology are presented, as well as the features of their interaction.

Terrestrial laser scanning (TLS) provides detailed three-dimensional representation of the surrounding forest structure. However, due to close-range hemispherical scanning geometry, the ability of TLS technique to comprehensively characterize all trees and especially the upper parts of forest canopy is often limited. In this study, we investigated how much forest characterization capacity can be improved in managed Scots pine (Pinus sylvestris L.) stands if TLS point cloud is complemented with a photogrammetric point cloud acquired from above the canopy using unmanned aerial vehicle (UAV). In this multisensorial (TLS+UAV) close-range sensing approach, the used UAV point cloud data was considered feasible especially in characterizing the vertical forest structure and improvements were obtained in estimation accuracy of tree height as well as plot-level basal-area weighted mean height (H_g) and mean stem volume (V_mean). Most notably the root mean square error (RMSE) in H_g improved from 0.88 m to 0.58 m and the bias improved from -0.75 m to -0.45 m with the multisensorial close-range sensing approach. However, in managed Scots pine stands the mere TLS captured also the upper parts of the forest canopy rather well. Both approaches were capable of deriving stem number, basal area, V_mean, H_g and basal area-weighted mean diameter with a relative RMSE less than 5.5% for all of the sample plots. Although the multisensorial close-range sensing approach mainly enhanced characterization of forest vertical structure in single-species, single-layer forest conditions, representation of more complex forest structures may benefit more from point clouds collected with sensors of different measurement geometries.

Unmanned Aerial Vehicle (UAV) based remote sensing (RS) studies in glaciology are mainly focusing on obtaining accurate high-resolution data from UAV images. Studies for identifying and minimising the challenges faced during the UAV-based RS data acquisition survey on inaccessible and harsh terrains of mountain glaciers is limited. This study aims to examine the practical challenges faced during UAV surveys of glaciers and derive strategies to minimize them. To the authors' knowledge, this is the first study that addresses such problems over the Himalayan region. Here, the UAV surveys were conducted using a fixed-wing commercial-grade off-the-shelf UAV (eBee plus, SenseFly) on three glacier sites (East Rathong, Hamtah and Panchinala-A) located in different zones and climate regimes lying within the Indian part of Himalayas. From UAV collected photos, the study was able to generate ultra-high-resolution ortho-mosaicked images and Digital Elevation Models (DEMs) at 0.1m GSD. UAV-derived DEMs was able to achieve vertical (horizontal) accuracy of 0.45 and 0.21 m (0.15 and 0.1 m) with 3 and 6 ground control points (GCPs) for an area of 0.75 km2 and 1.38 km2. Accuracy assessment of UAV DEMs generated with and without GCPs indicate that GCPs are must to obtain decimetre level accurate DEM especially on glaciers with steep-valleyed terrains. The utility of the obtained ultra-high-resolution ortho-mosaicked images was demonstrated by generating glacier surface feature maps. Based on the challenges observed during UAV surveys, the study identifies and recommends best-suited locations on a glacier and its adjacent regions for conducting UAV surveys efficiently in the glaciated terrain of Himalayas and possibly beyond. Recommendations reported in this article shall minimise the challenges faced and involved risks for data acquisition and thus enable UAVs to cover more glaciated area successfully.

UAVNs (unmanned aerial vehicle networks) may become vulnerable to threats and attacks due to their characteristic features such as high mobility, highly dynamic network topology, and open-air wireless environments. Since previous work has focused on classical and metaheuristic-based approaches, none of these approaches have a self-adaptive approach. In this article, we examine the challenges of cyber detection methods to secure UAVNs and review exiting security schemes proposed in the current literature. Furthermore, we propose an agent-based self-protective method (ASP-UAVN) for UAVNs that is based on the Human Immune System (HIS). In ASP-UAS, the safest route from the source UAV to the destination UAV is chosen according to a self-protective system. In this method, a multi-agent system using an Artificial Immune System (AIS) is employed to detect the attacking UAV and choose the safest route. In the proposed ASP-UAVN, the route request packet (RREQ) is initially transmitted from the source UAV to the destination UAV to detect the existing routes. Then, once the route reply packet (RREP) is received, a self-protective method using agents and the knowledge base is employed to choose the safest route and detect the attacking UAVs. The method is evaluated here via extensive simulations carried out in the NS-3 environment. The experimental results of four scenarios demonstrated that the ASP-UAS increases the Packet Delivery Rate (PDR) by more than 17.4, 20.8, and 25.91%, and detection rate by more than 17.2, 23.1, and 29.3%, and decreases the Packet Loss Rate (PLR) by more than 14.4, 16.8, and 20.21%, the false-positive and false-negative rate by more than 16.5, 25.3, and 31.21% those of SUAS-HIS, SFA and BRUIDS methods, respectively.

A new variant of two-echelon routing problem is investigated, where the truck and the drone are used to cooperatively complete the deliveries of all parcels. The truck not only acts as a tool for parcel delivery, but also serves as a moving depot for the drone. The drone can carry several parcels and take off from the truck, while returning to the truck after completing the delivery. The energy consumption model for the routing process of the drone is analyzed, when it is utilized to deliver multiple parcels. A two-stage route-based modelling approach is proposed to optimize both the truck’s main route and the drone’s adjoint flying routes. A hybrid heuristic integrating nearest neighbor and cost saving strategies is developed to quickly construct a feasible solution. The simulated annealing algorithm is applied to improve the quality of the solution, where a Tabu list is employed to improve the search efficiency. Random instances at different scales are used to test the performance of the proposed algorithm. A case study based on the practical road network in Changsha, China, is presented, through which the sensitivity analysis is conducted with respect to some critical factors.

Precision agriculture is a farm management technology that involves sensing and then responding to the observed variability in the field. Remote sensing is one of the tools of precision agriculture. The emergence of small unmanned aerial vehicles (sUAV) have paved the way to accessible remote sensing tools for farmers. This paper describes the comparison of two popular off-the-shelf sUAVs: 3DR Iris and DJI Phantom 2. Both units are equipped with a camera gimbal attached with a GoPro camera. The comparison of the two sUAV involves a hovering test and a rectilinear motion test. In the hovering test, the sUAV was allowed to hover over a known object and images were taken every second for two minutes. The position of the object in the images was measured and this was used to assess the stability of the sUAV while hovering. In the rectilinear test, the sUAV was allowed to follow a straight path and images of a lined track were acquired. The lines on the images were then measured on how accurate the sUAV followed the path. Results showed that both sUAV performed well in both the hovering test and the rectilinear motion test. This demonstrates that both sUAVs can be used for agricultural monitoring.

This work targets the development of a mobility control system for high-speed series hybrid electric tracked vehicles, which operate with independent traction motors for each track. The scope of the research encompasses the modeling of the series hybrid powertrain specific to military tracked vehicles, as well as an in-depth analysis of their dynamic behavior. Subsequently, the study conducts a critical review of the mobility control approaches sourced from literature, identifying key techniques relevant to high-inertia vehicular applications. Building on the foundational models, the study puts forward a robust closed-loop mobility control system aimed at ensuring precise and stable off-road vehicle operations. The system's resilience and adaptability to a variety of driving conditions are emphasized, with a particular focus on handling maneuvers such as steering and pivoting, which are challenging operations for tracked vehicle agility. The performance of the proposed mobility control system is tested through a series of simulations, covering a spectrum of operational scenarios. These tests are carried out in both offline simulation settings, which permit meticulous fine-tuning of system parameters, and real-time environments that replicate actual field conditions. The simulation results demonstrate the system's capacity to improve vehicular response and highlight its potential impact on the future designs of mobility control systems for the heavy-duty vehicle sector, particularly in defense applications.

Earthquake-triggered landslides are one of the most significant hazards worldwide. These landslides, involving small or large volumes, can develop in debris flow or avalanche with high mobility and long-runout distance. The motion processes of this kind of landslide also quite complicated. This study reproduced the motion processes of two landslides using the LS-RAPID program. The Aso Bridge landslide occurred on April 16, 2016, with rapid and long-runout distance characteristics. The Kataragai landslide occurred on April 9, 2018, travelling with flow-like behavior. Through field investigations and laboratory experiments, features and mechanical parameters of these two landslides were obtained. In the LS-RAPID program, the pre-failure models and motion processes of these two landslides were established and reproduced. Results indicated that sliding speed and travelling morphology at different intervals were considered as two indicators to describe their motion process. However, while sliding speed of these two landslides have significant differences with sliding speeds of actual landslides, the final morphologies after failure were consistent with those observed in the field investigation.

Familial Mediterranean fever (FMF) is a systemic autoinflammatory disorder caused by inherited mutations in the MEFV (Mediterranean FeVer) gene located on chromosome 16 (16p13.3) and coding pyrin protein. Despite the existing data on MEFV mutations, the exact mechanism of their effect on the development of pathological processes leading to autoinflammation observed in FMF, remains unclear. Induced pluripotent stem cells (iPSCs) are considered an important tool for studying the molecular genetic mechanisms of various diseases due to their ability to differentiate into any cell type, including macrophages, which contribute to the development of FMF. In this study, we developed iPSCs of an Armenian patient with FMF having M694V, p.(Met694Val) (c.2080A&gt;G, rs61752717) pathogenic mutation in exon 10 of the MEFV gene. As a result of direct differentiation, macrophages expressing CD14 and CD45 surface markers were obtained. In addition, we found that the morphology of patient macrophages derived from iPSCs with MEFV mutation was significantly different from that of differentiated from iPSCs of a healthy donor carrying wild-type MEFV gene.

The exceptional performance of graphene has driven the advancement of its preparation technique and application. Laser-induced graphene (LIG), as a novel graphene preparation technique, has been applied in various fields. Graphene periodic structures created by LIG technique exhibit superhydrophobic characteristics and can be used for deicing and anti-icing applications, which are significantly influenced by the laser parameters. The laser surface treatment process was simulated by a finite element software analysis (COMSOL Multiphysics) to optimize the scanning parameter range, and the linear array surface structure were subsequently fabricated by the LIG technique. The generation of graphene was confirmed by Raman spectroscopy, and energy-dispersive X-ray spectroscopy. The periodic linear array structure were observed by Scanning electron microscopy (SEM) and confocal laser imaging (CLSM). In addition, CLSM testings, contact angle measurements, and delayed icing experiments were systematically performed to investigate the effect of scanning speed on surface hydrophobicity. The results show that the high quality and uniform graphene can be achieved using the laser scanning speed of 125 mm/s. The periodic linear array structures can obviously increase the contact angle and suppress delayed icing. Furthermore, these structures have the enhanced ability of the electric heating deicing, which can reach 100°C and 240°C within 15 s and within 60 s under the DC voltage power supply ranging from 3 to 7 V, respectively. These results indicate that the LIG technique can be developed to provide an efficient, economical, and convenient approach for preparing graphene and the hydrophobic surface array structure based on LIG has considerable potential for deicing and anti-icing applications.

The availability of multi-rotor UAVs with lifting capacities of several kilograms, allows for a new paradigm in atmospheric measurement techniques, i.e. the integration of research-grade sonic anemometers for airborne turbulence measurements. With their ability to hover and move very slowly, this approach yields an unrevealed flexibility compared to mast-based sonic anemometers, for a wide range of boundary layer investigations that require an accurate characterization of the turbulent flow. For an optimized sensor placement, potential disturbances by the propeller-induced flow (PIF), as well as the potential impact of the sensor weight and angular momentum on the flight performance in the case of a boom-mounted sensor, have to be considered.

Plant cells are omnipotent and breeding of new varieties can be achieved by protoplast fusion. Such fusions can be achieved by treatment with poly(ethylene glycol) or by applying an electric field. Microfluidic devices allow for controlled conditions and targeted manipulation of small batches of cells down to single cell analysis. To provide controlled conditions for protoplast fusions and achieve high reproducibility, we developed and characterized a microfluidic device to reliably trap few of Arabidopsis thaliana protoplasts and induced a cell fusion by controlled addition of poly(ethylene glycol) (PEG, with a molecular weight of 6000). Experiments were conducted to determine the survival rate of isolated protoplasts in our microfluidic system. Afterwards, PEG induced fusion was studied. Our results indicate that the following fusion parameters had significant impact on the fusion efficiency and duration: PEG concentration, osmolarity of solution, and flow velocity. PEG concentration below 10% led to only partial fusion. Osmolarity of the PEG fusion solution was found to strongly impact the fusion process; complete fusion of two source cells sufficiently took part in slightly hyper osmotic solutions, whereas iso-osmotic solutions led to only partial fusion at 20% PEG concentration. We observed accelerated fusion for higher fluid velocities. Up to this study, it was common sense that fusion is one directional, i.e. once two cells were fused into one cell they stay fused. Here, we present for the first time reversible fusion of protoplasts. Our microfluidic device paves the way to a deeper understanding on the kinetics and processes of cell fusion.

RNA, as an important substance for regulating biological growth and development, has significant implications for visualization research. However, many spontaneously fluorescent substances in plants greatly interfere with the effectiveness of plant bioimaging. Aggregetion- induced emission luminogens (AIEgens), due to their luminescent properties, tunable molecular size, high fluorescence intensity, good photostability, and low cell toxicity, have been widely applied in the animal and medical fields. We have found that AIEgens have great potential as RNA fluorescent probes for efficient imaging in plants. In this review, we first introduce several common RNA labeling forms and point out their pros and cons. We briefly describe the development of AIEgens and the AIE mechanism, and then present various practical applications of AIEgens, including detailed examples of their use as biological markers. To further promote the application of AIE in the field of RNA, we suggest the use of AIEgens to modify target RNA via techniques such as click chemistry or CRISPR/Cas, to achieve RNA visualization in plants. highly possible to modify target RNA with AIEgens in vivo for RNA visualization.

Laser-induced periodic surface structures (LIPSS) have gained significant attention due to their ability to modify the surface morphology of materials at the micro-nanoscale and show great promise for surface functionalization application. In this study, we specifically investigate the formation of LIPSS in silicon substrates and explore their impact on Surface-Enhanced Raman Spectroscopy (SERS) applications. This study reveals a stepwise progression of LIPSS formation in silicon, involving three distinct stages of LIPSS: 1) integrated Low-Spatial-Frequency LIPSS (LSFL) and High-Spatial-Frequency LIPSS (HSFL), 2) principally LSFL and 3) LSFL at the edge of the irradiated spot, elucidating the complex interplay between laser fluence, pulse number, and resulting surface morphology. Furthermore, from an application standpoint, these high-quality multi-scale periodic patterns lead to the next step of texturing the entire silicon surface with homogeneous LIPSS for SERS application. The potential of LIPSS-fabricated silicon substrates for enhancing SERS performance is investigated using thiophenol as a test molecule. The results indicate that the Au-coated combination of LSFL and HSFL substrate showcased the highest enhancement factor (EF) of 1.38 × 10^6. This pronounced enhancement is attributed to the synergistic effects of Localized Surface Plasmon Resonance (LSPR) and Surface Plasmon Polaritons (SPPs), intricately linked to HSFL and LSFL characteristics. These findings contribute to understanding LIPSS formation in silicon and their applications in surface functionalization and SERS, paving the way for sensing platforms.

The theory of electron spin has been proposed for a century, but the study of quantum effects in biological molecules is still in its infancy. Chirality-induced spin selectivity (CISS) is a very modern theory that can explain many biochemical phenomena. In this paper, we propose a new theoretical model based on CISS theory and quantum chemistry theory, which can well explain the theoretical explanation of the chiral selectivity of chiral proteins. Moreover, this theory can predict the spin state of corresponding chiral molecules. Taking L-DOPA and AADC enzyme as examples, this theoretical model solves the theoretical explanation of AADC enzyme's chiral catalysis selectivity problem and successfully predicts the spin state of L-DOPA and D-DOPA's valence electrons.

Laser additively manufactured (LAM) Ti–6Al–4V alloy has huge application potential in aerospace structural parts such as turbine blades. However, there are few studies on the fatigue properties of such LAM parts under vibration loading, particularly with regard to anisotropy. In this paper, vibration fatigue properties of LAM Ti-6Al-4V by laser melted deposition process were investigated along the transversely deposited (TD) direction and parallelly deposited (PD) direction. Through the first-order bending vibration experiments, LAM Ti-6Al-4V alloy exhibits obvious anisotropic fatigue properties and significant dispersion in fracture position. The fracture morphology analysis reveals that the vibration fatigue failure was mainly dominated by the LAM process-induced defects and the microstructure. For the LAM samples without defects at crack initiation sites, the fatigue behavior is controlled by the prior β columnar grains with preferential orientation, which leads to enhanced fatigue crack propagation resistance for the PD samples. For the LAM samples with defects at initiation sites, having lower fatigue lives, the fatigue anisotropy strongly depends on the projection area of the lack-of-fusion defects relative to the loading direction, resulting in better fatigue performance for the TD samples.

Human induced pluripotent stem cell (hiPSC)-derived neural cells have been used at the preclinical stage of drug development. As previously reported, hiPSC-derived neurons exhibit greater tolerance to excitotoxicity than that of primary cultures of rodent neurons; however, the underlying mechanisms remain unknown. We therefore investigated the functions of L-glutamate (L-Glu) transporters, the most important machinery used to maintain low extracellular L-Glu concentrations, in hiPSC-derived neural cells. We also clarified the contribution of each L-Glu transporter subtype. At 63 days in vitro (DIV), we detected neuronal circuit functions in hiPSC-derived neural cells by a microelectrode array system (MEA). Exposure to 100 μM L-Glu for 24 hrs did not affect the viability of these 63 DIV neural cells. Pharmacological inhibition of excitatory amino acid transporter 1 (EAAT1) and EAAT2 blocked almost 100% of L-Glu uptake. In this condition, L-Glu exposure dramatically decreased cell viability. These results suggest that in hiPSC-derived neural cells, EAAT1 and EAAT2 are predominant L-Glu transporters, and their uptake potentials are stronger than those of primary cultures of rodent neurons. Furthermore, hiPSC-derived neural cells may be useful for screening drugs that target L-Glu transporters.

Abstract: Arranged patterns obtained by ultrafast laser processing on the surface of Ti/Cu/Ti/Si and Ti/Zr/Ti/Si thin film systems are reported. Two differently designed multilayer thin films, Ti/Cu/Ti/Si and Ti/Zr/Ti/Si, were deposited on silicon by the ion sputtering method. The bioactive surfaces on these systems involve the formation of laser-induced periodic surface structures (LIPSS) in each of the laser-written lines of mesh patterns on 5x5 mm areas. The formation of nano- and micro-patterns with an ultra-thin oxide film on the surfaces was used to observe the effects of morphology and proliferation of the MRC-5 cell culture line. To determine whether Ti-based thin films have a toxic effect on living cells, an MTT assay was performed. The relative cytotoxic effect as a percentage of surviving cells showed that there was no difference in cell number between the Ti-based thin films and the control cells. There was also no difference in the viability of the MRC-5 cells, except for the Ti/Cu/Ti/Si system, where there was a slight 10% decrease in cell viability.

The primary cilium plays critical roles in homeostasis and development of neurons. Recent studies demonstrate that cilia length is regulated by the metabolic state of cells, as dictated by processes such as glucose flux and O-GlcNAcylation (OGN). The study of cilia length regulation during neuron development, however, has been an area left largely unexplored. This project aims to elucidate the roles of O-GlcNAc in neuronal development through its regulation of the primary cilium. Here, we present findings suggesting that OGN levels negatively regulate cilia length on differentiated cortical neurons derived from human-induced pluripotent stem cells. In neurons, cilia length increased significantly during neurons maturation (after day 35), while OGN levels began to drop. Long-term perturbation of OGN via drugs, which inhibit or promote its cycling, during neuron development also have varying effects. Diminishing OGN levels increases cilia length until day 25, when neural stem cells expand and undergo early neurogenesis, before causing cell cycle exit defects and multinucleation. Elevating OGN levels induces greater primary cilia assembly but ultimately results in the development of premature neurons, which have higher insulin sensitivity. These results indicate that OGN levels and primary cilia length are jointly critical in proper neuron development and function. Understanding the interplays between these two nutrient sensors, O-GlcNAc and the primary cilium, during neuron development is important in paving connections between dysfunctional nutrient-sensing and early neurological disorders.

Viroids are known the smallest plant pathogens, and although their genome sequences do not encode proteins, they can cause disease in economically important crops. In order to control viroid diseases and mitigate their damage, genetic resources used for breeding of the viroid-resistant crop have been searched, but the practical resistant trait has not been found in almost all viroid-crop combinations, as well as the tolerant trait. Due to the difficulty in exploiting naturally occurring resistance or tolerance, various effective strategies have been devised to control viroid diseases using non-transforming or transforming techniques. Meanwhile, extensive findings related to viroid resistance and tolerance may lead to confer resistance or tolerance to viroid infection by combining with the recently emerged new technologies (e.g., spray-induced gene silencing and genome-editing technologies), which are believed to be more environmentally viable and acceptable to the general public than previously reported approaches. In particular, some genome-modified crops produced by the latter technology are already on the market. In this review, we comprehensively summarize the current status about investigation of naturally occurring genetic traits for viroid resistance and tolerance, accumulating knowledge about host factors involved in viroid pathogenicity, and various basic technologies developed to try to possible viroid disease control strategies. Furthermore, we discuss prospects and challenges for the achievement of more effective, practical, and sustainable disease control of viroid.

Limb girdle muscular dystrophies (LGMD), caused by mutations in 29 different genes, are the fourth most prevalent group of genetic muscle diseases, leading to progressive weakness and atrophy of the skeletal muscles. Although the link between LGMD and their genetic origins has been determined, LGMD still represent an unmet medical need. In this paper, we describe a platform for modeling LGMD based on the use of human induced pluripotent stem cells (hiPSC). Thanks to the self-renewing and pluripotency properties of hiPSC, this platform provides an alternative and renewable source of skeletal muscle cells (skMC) to primary, immortalized or overexpressing cells. We report that skMC derived from hiPSC express the majority of the genes and proteins causing LGMD. As a proof of concept, we demonstrate the importance of this cellular model for studying LGMDR9 by evaluating disease-specific phenotypes in skMC derived from hiPSC obtained from four patients.

Phytophthora. infestans is a well known late blight causing oomycetes pathogen. It evolves and adapts to the host background and new fungicide molecules rapidly within a few years of their release, may be due to the predominance of transposable elements in its genome. Frequent and huge applications of fungicides cause environmental concerns. Here we developed target specific RNA interference based molecules, that are capable of effectively reducing the late blight infection. cDNA microarray expression data was used for the selection of genes involved in the early stage of infection process, sporulation etc. The in vitro synthesis of double stranded RNA molecule, targeting SDH, EF-1α, GPI-HAM344, PLD-3 and HSP-90 encoding genes revealed the reduction in growth, sporulation and symptom expression, which were subsequently assessed by culture bioassay, detached leaf assay and topical application methods. The multiple genes targeted dsRNA nano clay sprayed plants showed enhanced disease resistance (4% disease severity) and least sporulation (<1x103), compared to naked dsRNA spray. Use of nano clay was assumed to be involved in the effective delivery, protection and boosting the action of RNAi in potato plants. A significant difference in the growth, sporulation count, disease severity and reduced expression of the genes and confocal microscopy imaging authenticates the effects of SIGS on late blight disease progression. Our research demonstrated that topical dsRNA nano clay spray under the open-air environment could be an alternative to chemical fungicides and transgenic approaches as a novel plant protection strategy for late blight in an environmentally friendly manner.

Objective: To assess the functionality of the affected upper limb in children diagnosed with hemiplegia aged between 4 and 8 years after applying low-intensity modified constraint-induced movement therapy(mCIMT). Methods: Prospective case series study. A mCIMT protocol was applied for five weeks, with two hours of containment per day. The study variables were: quality of movement of the upper limb, spontaneous use, participation of the affected upper limb in activities of daily living, dynamic joint position, grasp-release action, grasp strength, supination and extension elbow movements. Four measurements were performed, using the QUEST scale, the SHUEE Evaluation, a hand dynamometer and a goniometer. Results: The sample was composed of 8 children with moderate manual ability. Statistically significant differences were detected in all the studied variables (p&lt;0.05). The greatest increase occurred in spontaneous use from assessment 1-4 (p = 0.01), reaching 88.87% active participation in bimanual tasks. The quality of movement of the upper limb obtained a significant value due to the increase in dissociated movements and grasp (p = 0.01). Conclusion: A low dose (50 hours) of mCIMT increased the functionality of children diagnosed with congenital hemiplegia between 4 and 8 years of age with moderate manual ability.

Aberrant neutrophil extracellular trap (NET) formation and the loss of barrier integrity in inflamed intestinal tissues have long been associated with inflammatory bowel disease (IBD). However, whether NETs alter intestinal epithelium permeability during colitis remains elusive. Here, we demonstrated that NETs promote the breakdown in intestinal barrier function for the pathogenesis of intestinal inflammation in mouse models of colitis. NETs were abundant in the colon of mice with colitis experimentally induced by dextran sulfate sodium (DSS) or 2,4,6-trinitrobenzene sulfonic acid (TNBS). Analysis of the intestinal barrier integrity revealed that NETs impaired gut permeability, enabling the initiation of luminal bacterial translocation and inflammation. Furthermore, NETs induced the apoptosis of epithelial cells and disrupted the integrity of tight junctions and adherens junctions. Intravenous administration of DNase I, an enzyme that dissolves the web-like DNA filaments of NETs, during colitis restored the mucosal barrier integrity which reduced the dissemination of luminal bacteria, and attenuated intestinal inflammation in both DSS and TNBS models. We conclude that NETs serve a detrimental factor in the gut epithelial barrier function leading to the pathogenesis of mucosal inflammation during acute colitis.

Globally 30% of landslides occur in the northeastern part of India [1]. One of the major earthquake events in Sikkim, India occurred on 18th September 2011 (Mw 6.9) led to over 300 landslides and 122 human deaths [2]. These landslides not only controlled by natural disasters but initiated due to human activities. The present study considered Lungchok landslide occurred in south district of Sikkim due to 2011 seismic event. The study focused on the failure mechanism of the landslide based on finite element analysis by adopting eight different cases. The deformation characteristic was investigated for dry and saturated slope conditions under static and dynamic behavior considering vehicle loads using GeoStudio software. The FEM analysis has been carried out using load deformation and linear elastic. The analysis shows that the failure of the slope was not sudden due to the 2011 earthquake event, but progressive failure was observed with time and construction activity. The paper demonstrates that, an increase in infrastructure development including construction by hill cutting increased the initiation of landslide with soil erosion. The cracks developed after 2011 earthquake event led to further deformations during future disasters required effective stabilization measures.

The human degenerative cartilage has low regenerative potential. Chondrocyte transplantation offers a promising strategy for cartilage treatment and regeneration. Currently chondrogenesis using human pluripotent stem cells are accomplished using human recombinant growth factors. Here, we differentiated human induced pluripotent stem cells (hiPSCs) into chondrocytes and cartilage pellet using minicircle vectors. Minicircles are used as a non-viral gene delivery system for gene therapy in various diseases. Non-viral gene delivery can produce growth factors without integrating into the host genome. Minicircle vectors containing bone morphogenetic protein 2 (BMP2) and transforming growth factor, beta 3 (TGFβ3) were successfully generated and delivered to hiPSC-derived outgrowth (OG) cells. Cell pellets generated using minicircle-transfected OG cells successfully differentiated into chondrogenic lineage. Chondrogenic pellets transfected with growth factor-encoding minicircles effectively recovered osteochondral defect in rat models. Taken together, this work shows the potential application of minicircles in cartilage regeneration using hiPSCs.