Development of a ship performance model for power estimation of inland waterway vessels

A ship performance model is an important factor in energy-efficient navigation. It formulates a speed–power relationship that can be used to adjust the engine loads for dynamic energy optimisation. However, currently available models have been developed for sea-going vessels, where the environmental conditions are significantly different from those experienced on inland waterways. Inland waterway shipping has great potential to become a mode of transport that can both improve safety and reduce emissions. Therefore, this paper presents the development of an energy performance model specifically for inland waterway vessels (IWVs). The holistic ship energy system model is based on empirical methods, from resistance to engine performance prediction, established in a modular code architecture. The resistance and propulsion prediction in confined waterways are captured by a newly developed method, considering a superposing of shallow water and bank effect. Verification against model tests and high-fidelity simulations indicate that the selected empirical methods achieved good accuracy for predicting ship performance. The resistance prediction error was 5.2% for single vessels and 8% for pusher-barge convoys based on empirical methods. The results of a case study investigating the performance of a self-propelled vessel under dynamic waterway data, indicate that the developed model could be used for onboard power monitoring and energy optimisation during operation

osmAG: Hierarchical Semantic Topometric Area Graph Maps in the OSM Format for Mobile Robotics

Maps are essential to mobile robotics tasks like localization and planning. We propose the open street map (osm) XML based Area Graph file format to store hierarchical, topometric semantic multi-floor maps of indoor and outdoor environments, since currently no such format is popular within the robotics community. Building on-top of osm we leverage the available open source editing tools and libraries of osm, while adding the needed mobile robotics aspect with building-level obstacle representation yet very compact, topometric data that facilitates planning algorithms. Through the use of common osm keys as well as custom ones we leverage the power of semantic annotation to enable various applications. For example, we support planning based on robot capabilities, to take the locomotion mode and attributes in conjunction with the environment information into account. The provided C++ library is integrated into ROS. We evaluate the performance of osmAG using real data in a global path planning application on a very big osmAG map, demonstrating its convenience and effectiveness for mobile robots.Comment: 7 page

Potential roles of the gut microbiota in the manifestations of drug use disorders

Drug use disorders (DUDs) not only cause serious harm to users but also cause huge economic, security, and public health burdens to families and society. Recently, several studies have shown that gut microbiota (GM) can affect the central nervous system and brain functions. In this review, we focus on the potential role of the GM in the different stages of DUDs. First, the GM may induce individuals to seek novel substances. Second, the gut microbiota is involved in the decomposition and absorption of drugs. Symptoms of individuals who suffer from DUDs are also related to intestinal microorganisms. Third, the effects of the GM and its metabolites on drug relapse are mainly reflected in the reward effect and drug memory. In conclusion, recent studies have preliminarily explored the relationship between GM and DUDs. This review deepens our understanding of the mechanisms of DUDs and provides important information for the future development of clinical treatment for DUDs

Epidemiologic Features of Human Rabies in China from 2015-2021

This study aimed to enhance the current understanding of the epidemiologic characteristics, laboratory diagnostic levels, and changes in pathogenic populations of rabies in China by studying the status of the human rabies epidemic in China from 2015-2021 and provide useful information for guiding rabies disease prevention and control strategies. We analyzed the incidence, distribution, and laboratory testing of human rabies in mainland China using statutory surveillance data from 2015-2021. Based on a literature review, the study summarizes the recent updates of the rabies virus population in each province based on previous monitoring. A total of 3032 rabies cases were reported in China from 2015-2021, with a year-after-year decrease in the total number of cases. Most of the cases (75.19%) were distributed in Hunan, Henan, Guangxi, Guizhou, Hubei, Yunnan, Jiangsu, Anhui, Guangdong, and Sichuan, with 13 counties (districts) reporting > 50 cases in 7 years. The number of reported counties (districts) decreased from 512 in 2015 to 116 in 2021. Farmers accounted for most of the cases (73%), and the highest proportion of cases (54.62%) occurred in individuals 50-75 years of age. No changes in endemic populations were detected in China. The laboratory diagnosis rate of cases increased from 4.74% in 2015 to 22.93% in 2021. The rabies epidemic in China decreased steadily from 2015-2021, with a marked contraction in the geographic scope. In the future it will be necessary to continue to carry out large-scale dog immunization and strengthen the surveillance and laboratory diagnosis of rabies

Estimation of human impedance and motion intention for constrained human-robot interaction

In this paper, a complete framework for safe and efficient physical human-robot interaction (pHRI) is developed for robot by considering both issues of adaptation to the human partner and ensuring the motion constraints during the interaction. We consider the robot’s learning of not only human motion intention, but also the human impedance. We employ radial basis function neural networks (RBFNNs) to estimate human motion intention in real time, and least square method is utilized in robot learning of human impedance. When robot has learned the impedance information about human, it can adjust its desired impedance parameters by a simple tuning law for operative compliance. An adaptive impedance control integrated with RBFNNs and full-state constraints is also proposed in our work. We employ RBFNNs to compensate for uncertainties in the dynamics model of robot and barrier Lyapunov functions are chosen to ensure that full-state constraints are not violated in pHRI. Results in simulations and experiments show the better performance of our proposed framework compared with traditional methods

Event-trigger-based resilient distributed energy management against FDI and DoS attack of cyber-physical system of smart grid

To address the false data injection (FDI) and denial of service (DoS) attack, this article proposes an event-trigger-based resilient distributed energy management approach for cyber–physical system of smart grid. Here, an event-trigger-based resilient consensus algorithm (ERCA) is proposed with the attack identification and compensation mechanism. The event-triggered mechanism is improved within distributed optimization combined with reliable acknowledgment (ACK) signals technique to mitigate the impact of data loss or transmission delay, and trust nodes-based compensation approach is proposed during resilient coordinated optimization for state correction to ensure the stability and security of power grid system. The optimality and convergence of the proposed method are proved theoretically that the proposed method can approximate to optimal solution well and achieve consensus by ensuring the proactive involvement of all participants under coordinated cyber attack. According to those obtained simulation results, it reveals that the proposed algorithm can effectively solve the energy management issue under coordinated DoS and FDI attack.https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6221021hj2024Electrical, Electronic and Computer EngineeringSDG-07:Affordable and clean energ

Magneto-Orientation of Magnetic Double Stacks for Patterned Anisotropic Hydrogels with Multiple Responses and Modulable Motions

Reported here is a multi‐response anisotropic poly(N‐isopropylacrylamide) hydrogel developed by using a rotating magnetic field to align magnetic double stacks (MDSs) that are fixed by polymerization. The magneto‐orientation of MDSs originates from the unique structure with γ‐Fe(2)O(3) nanoparticles sandwiched by two silicate nanosheets. The resultant gels not only exhibit anisotropic optical and mechanical properties but also show anisotropic responses to temperature and light. Gels with complex ordered structures of MDSs are further devised by multi‐step magnetic orientation and photolithographic polymerization. These gels show varied birefringence patterns with potentials as information materials, and can deform into specific configurations upon stimulations. Multi‐gait motions are further realized in the patterned gel through dynamic deformation under spatiotemporal light and friction regulation by imposed magnetic force. The magneto‐orientation assisted fabrication of hydrogels with anisotropic structures and additional functions should bring opportunities for gel materials in biomedical devices, soft actuators/robots, etc

Study on the Self-Repairing Effect of Nanoclay in Powder Coatings for Corrosion Protection

Powder coatings are a promising, solvent-free alternative to traditional liquid coatings due to the superior corrosion protection they provide. This study investigates the effects of incorporating montmorillonite-based nanoclay additives with different particle sizes into polyester/triglycidyl isocyanurate (polyester/TGIC) powder coatings. The objective is to enhance the corrosion-protective function of the coatings while addressing the limitations of commonly employed epoxy-based coating systems that exhibit inferior UV resistance. The anti-corrosive and surface qualities of the coatings were evaluated via neutral salt spray tests, electrochemical measurements, and surface analytical techniques. Results show that the nanoclay with a larger particle size of 18.38 µm (D50, V) exhibits a better barrier effect at a lower dosage of 4%, while a high dosage leads to severe defects in the coating film. Interestingly, the coating capacitance is found, via electrochemical impedance spectroscopy, to decrease during the immersion test, indicating a self-repairing capability of the nanoclay, arising from its swelling and expansion. Neutral salt spray tests suggest an optimal nanoclay dosage of 2%, with the smaller particle size (8.64 µm, D50, V) nanoclay providing protection for 1.5 times as many salt spray hours as the nanoclay with a larger particle size. Overall, incorporating montmorillonite-based nanoclay additives is suggested to be a cost-effective approach for significantly enhancing the anti-corrosive function of powder coatings, expanding their application to outdoor environments

The protective role of DOT1L in UV-induced melanomagenesis

The DOT1L histone H3 lysine 79 (H3K79) methyltransferase plays an oncogenic role in MLL-rearranged leukemogenesis. Here, we demonstrate that, in contrast to MLL-rearranged leukemia, DOT1L plays a protective role in ultraviolet radiation (UVR)-induced melanoma development. Specifically, the DOT1L gene is located in a frequently deleted region and undergoes somatic mutation in human melanoma. Specific mutations functionally compromise DOT1L methyltransferase enzyme activity leading to reduced H3K79 methylation. Importantly, in the absence of DOT1L, UVR-induced DNA damage is inefficiently repaired, so that DOT1L loss promotes melanoma development in mice after exposure to UVR. Mechanistically, DOT1L facilitates DNA damage repair, with DOT1L-methylated H3K79 involvement in binding and recruiting XPC to the DNA damage site for nucleotide excision repair (NER). This study indicates that DOT1L plays a protective role in UVR-induced melanomagenesis