In China, the Ministry of Transport stressed the need to “Strengthen the application of active safety technology”. The transportation of hazardous chemicals represented by LNG, LPG, and liquefied hydrocarbons is the weak link in traffic safety. The aim of this study is to apply digital twin (hereinafter referred to as DT) technology to the whole process of handling (including loading and unloading) and transportation of hazardous chemicals to help improve the anti-risk ability of road networks at all levels. The method is intended to design a monitoring system covering operation visualization, information fusion, cargo tracking, and hazard source monitoring that is based on DT technology and multi-source data acquisition technology. First, DT technology in the areas of hazardous chemicals handling and transportation is discussed. Then, the DT system is designed, including the system construction, functions, and the means of achieving these functions. Finally, taking the procedure in LNG road transportation as an example, we illustrate the application of DT in its four stages. This system is used to present the evolutionary path of accidents that occur in different links and assist in testing the rationality of the comprehensive disposal plan. Full article

Forestry is one of the sectors particularly affected by the threats posed by changing climatic conditions. This is reflected in the deterioration of the health status of stands due to the synergistic effect of numerous abiotic and biotic factors. Current forest health problems are due to dynamic, negative changes in the forest environment. While the amount of precipitation remains at a similar level, its distribution varies throughout the year and, in particular, the lack of soil moisture during the growing season leads to the weakening of trees, including the main forest-forming species in Poland such as Pinus sylvestris. The weakening of trees, in turn, leads to species of insect pests that were previously considered secondary becoming primary pests, such as Ips acuminatus. It is likely that weakening of trees also favours increased occurrence of parasitic plants such as Viscum album ssp. austriacum or Loranthus europaeus. Infestations of the hemiparasitic, xylem-secreting pine mistletoe are of great interest because they are spreading rapidly throughout Europe. Drought in forests is not only a long-term water shortage, but also a situation in which plant-fungal relationships are disrupted. Reduced water availability leads to a number of negative changes in the soil and the mycobiota that live there, affecting entire ecosystems. The effects of climate change and increased international trade are leading to the spread of pathogenic fungi and other harmful organisms whose range was previously restricted to the south of our continent. Unfavourable abiotic and biotic factors leading to weakening of oak stands in the western part of Poland have resulted in activation of new pests like Mediterranean oak borer. Intensification of transport and shortening of its duration, as well as climatic changes, favour the introduction of various organisms, including bark beetles (Scolytinae). In Poland, cyclic insect outbreaks are one of the most important problems in forest protection. Developing methods to monitor, prevent outbreaks and control the density of insect populations below harmful levels can be a challenge to consider. Finding an innovative system for applying insecticides to control spruce bark beetle could also be an interesting solution, where insects attracted to pheromones die after contact with the insecticide. Contact with the insecticide has a dual effect: either directly when the tree is treated, or when the bark beetle attempts to invade the tree. Opportunities for the use of biostimulants in forestry and is an attractive way to regenerate plants after negative stressors such as frost, drought or damage caused by improper use of pesticides, as well as the negative effects of diseases and pests. It acts indirectly by stimulating leaf, stem and root development and improving nutrient uptake. The effects of chemical treatments on fungal biodiversity in forests should be studied using powerful molecular tools such as NGS. Full article

Embedded computing platforms such as neural network accelerators deploying neural network models need to quantize the values into low-bit integers through quantization operations. However, most current embedded computing platforms with a fixed-point architecture do not directly support performing the quantization operation for the LSTM layer. Meanwhile, the influence of sequential input data for LSTM has not been taken into account by quantization algorithms. Aiming at these two technical bottlenecks, a new sequential-characteristics-based operators disassembly quantization method for LSTM layers is proposed. Specifically, the calculation process of the LSTM layer is split into multiple regular layers supported by the neural network accelerator. The quantization-parameter-generation process is designed as a sequential-characteristics-based combination strategy for sequential and diverse image groups. Therefore, LSTM is converted into multiple mature operators for single-layer quantization and deployed on the neural network accelerator. Comparison experiments with the state of the art show that the proposed quantization method has comparable or even better performance than the full-precision baseline in the field of character-/word-level language prediction and image classification applications. The proposed method has strong application potential in the subsequent addition of novel operators for future neural network accelerators. Full article

Antibiotics are emerging pollutants of great concern, due to detrimental effects of their sublethal concentrations on microbial communities. Monitoring of antibiotics’ presence and concentrations in the aquatic environment is of fundamental importance to the management of water resources. This study was aimed at filling the knowledge gap in terms of presence and concentration of antibiotics in surface water and groundwater in one of the mountain regions in southern Poland. The detailed aims included the assessment of whether there are spatial and/or temporal trends in antibiotic occurrence in water and the investigation of causes behind the changes in antibiotic concentrations. The study was conducted in seven sites (two groundwater and five river water) along the Białka river valley. Antibiotics were subjected to solid-phase extraction, followed by UHPLC/MS detection. Clindamycin, erythromycin, ofloxacin and trimethoprim were the most frequently detected, while the highest concentrations were observed for oxytetracycline and clindamycin. No antibiotics were detected in only one of the groundwater sites. Sewage treatment plant effluent was the hotspot of antibiotic contamination of the river downstream. The detection rates of antibiotics in the examined region seem to be driven mainly by the stability of antibiotics in the environment. Full article

In order to investigate the effects of corner set-backs on wind loads and wind-induced responses of rectangular high-rise buildings, pressure measurements were carried out on a benchmark model (CARRC) and four models with different rates (5%, 10%, 15%, 20%) of corner set-backs in a boundary layer wind tunnel. The test results show that the corner set-backs contribute to reducing along-wind loads of the rectangular high-rise building models, and the maximum reduction happens at 10% corner set-back. The across-wind loads decrease as the rate of corner set-back is increasing and the maximum reduction emerges at 20% corner set-back. The RMS accelerations at the top of models also decrease with the increasing of rate of corner set-back in along-wind and across-wind. Through the fitting of test results, empirical formulas for the correlation factors of base moment coefficients of rectangular high-rise buildings with different rates of corner set-back are put forward. Moreover, the correlation factors for the power spectrum densities of base moments are listed at typical frequencies corresponding to the practical tall buildings. The outputs of this paper aim to serve as references for wind-resistant design of similar buildings in strong wind region. Full article

A digital twin is a virtual model to reflect a physical object and helps it by making proper decisions. The decision-making process is based on the same input data that the simulated physical object has access to. Due to exploiting artificial intelligence, the decision-making process of the digital twin is more sophisticated than that of the physical object. In this study, the digital twin is applied to the sports training domain, where it addresses those questions that have arisen during the implementation of interval cycling training sessions. Thus, the digital twin runs on a mobile device (i.e., the Raspberry Pi platform), with which a cycle is equipped and demonstrates user-friendliness, robustness, reliability, and accuracy. The interval training sessions are transferred to the mobile device in the form of the domain-specific language EasyTrain, ensuring higher expressive power and ease of use. During the implementation, the digital twin advises the athlete with predicted information obtained by a sophisticated prediction model via a screen. The results of a huge experimental work showed that the difference in the average efficiency of the interval training implementation between the two cyclists that performed the experiments is prominent, as the efficiency of the professional training surpassed 90%, while the amateur training efficiency barely achieved 70%. Full article

Noise amplitude in original time domain data is usually discrete and sparse. This article presents a digital filter denoising method based on statistical frequencies of the signal values. The effective signal and noise signal are identified by comparing the frequency of the value of each pixelin the original signal with the preset validity discrimination threshold. Signals recognized as valid will be output directly, while noise signals will be replaced by the mean value of their surrounding pixel values. Compared to classical digital filtering methods such as mean filtering and median filtering, this method may improve signal recognition accuracy and has the potential to remove random noise while retaining details. An image noise reduction software based on frequency statistics was developed in the MATLAB environment. Noise reduction based on this algorithm was implemented on a portrait image with a noise density of 5%~40%, and noise reduction efficiency was compared to the classical noise reduction algorithms. The experimental results show that the PSNR of the proposed new method exceeds 41, reaching the same level as switching median filtering and adaptive filtering and preceding mean filtering. The SSIM of the new method exceeds 0.97, which is better than other classical methods. Additionally, the higher the noise density, the more obvious the advantage of this method. Full article

Bacterial protein toxins secreted by foodborne pathogens, such as Staphylococcus aureus and Shiga toxin-producing Escherichia coli (STEC) strains, may cause severe toxicosis in humans if present in foods or water and constitute an important public health problem. These toxins are large biomolecules with negative and positive ions due to the ionizable groups in the residual amino acids. An innovative theoretical model of purifying aqueous flowing solutions from ionic toxins is proposed in this study. The principle of the model is based on the drift of the ionic toxins, under the application of the external electric field, towards the walls of the duct, leaving the largest part of the duct with reduced levels of toxin. Parameters, such as toxin concentration, potential and electric field intensity distributions, and surface charge densities, are studied analytically for various duct widths and various external electric fields. The proposed model succeeded to reduce toxin levels by more than 99%, for duct widths less than 1cm, making it suitable for small-scale water purification. Full article

Breast cancer is the second highest cancer-related death worldwide. The treatment for breast cancer is via chemotherapy; however, occurrences of multidrug resistance, unselective targets, and physicochemical problems suggest that chemotherapy treatment is ineffective. Therefore, there is a need to find better alternatives. Essential oil is a plant secondary metabolite having promising bioactivities and pharmacological effects, including anti-breast cancer capabilities. This review intends to discuss and summarize the effect of essential oils on anti-breast cancer from published journals using keywords in PubMed, Scopus, and Google Scholar databases. Our findings reveal that the compositions of essential oils, mainly terpenoids, have excellent anti-breast cancer pharmacological effects with an IC₅₀ value of 0.195 μg/mL. Hence, essential oils have potential as anti-breast cancer drugs candidates with the highest efficacy and the fewest side effects. Full article

Traffic accidents are caused by man mainly, especially improper driving. The effective way to reduce safety accidents caused by improper driving is to find out the cause and path causing the accident, block the accident formation chain, and then reduce safety accidents. Therefore, using data from 337 road transport safety accidents in operating vehicles caused by improper driving behavior as the initial research sample, this paper uses the fuzzy set qualitative comparative analysis method to conduct a group analysis of typical cases and identifies the cause and path of safety accidents. The research results show that there are mainly four types of paths leading to safety accidents. According to the distribution of their core conditions, safety accidents are highly correlated with passenger transport and the degree of individualization of business models on operating vehicles. The following measures can be taken to prevent safety accidents: strengthen the supervision of operating enterprises (especially individual operations and individual-affiliated operations), carry out detailed safety training, and fully use advanced technology such as big data and high-tech means. The research results will help traffic and road transport management departments to prevent road safety accidents more effectively, which is of great significance to promoting the healthy development of road transport. Full article

Flight control is a key system of modern aircraft. During each flight, pilots use flight control to control the forces of flight and also the aircraft’s direction and attitude. Whether flight control can work properly is closely related to safety such that daily maintenance is an essential task of airlines. Flight control maintenance heavily relies on expert knowledge. To facilitate knowledge achievement, aircraft manufacturers and airlines normally provide structural manuals for consulting. On the other hand, computer-aided maintenance systems are adopted for improving daily maintenance efficiency. However, we find that grass-roots engineers of airlines still inevitably consult unstructured technical manuals from time to time, for example, when meeting an unusual problem or an unfamiliar type of aircraft. Achieving effective knowledge from unstructured data is inefficient and inconvenient. Aiming at the problem, we propose a knowledge-graph-based maintenance prototype system as a complementary solution. The knowledge graph we built is dedicated for unstructured manuals referring to flight control. We first build ontology to represent key concepts and relation types and then perform entity-relation extraction adopting a pipeline paradigm with natural language processing techniques. To fully utilize domain-specific features, we present a hybrid method consisting of dedicated rules and a machine learning model for entity recognition. As for relation extraction, we leverage a two-stage Bi-LSTM (bi-directional long short-term memory networks) based method to improve the extraction precision by solving a sample imbalanced problem. We conduct comprehensive experiments to study the technical feasibility on real manuals from airlines. The average precision of entity recognition reaches $85\%$, and the average precision of relation extraction comes to $61\%$. Finally, we design a flight control maintenance prototype system based on the knowledge graph constructed and a graph database Neo4j. The prototype system takes alarm messages represented in natural language as the input and returns maintenance suggestions to serve grass-roots engineers. Full article

Aiming at the problem of measurement-information abnormal-error and nonlinear filtering in UWB navigation and positioning, an ultra wideband position algorithm based on a maximum cross-correlation entropy unscented Kalman filter is proposed. The algorithm first obtains the predictive state estimate and the covariance matrix through traceless transformation. Then, it reconstructs observation information using the nonlinear regression method based on the maximum cross-correlation entropy criterion, which enhances the robustness of the unscented Kalman filter algorithm for heavy-tailed noise. The simulation and actual test results show that this algorithm has better positioning accuracy and stability than the traditional filter algorithm in a non Gaussian noise environment. This algorithm effectively solves the problem that UWB indoor location is easily affected by indoor environments, resulting in fixed deviation for that location. Full article

The wind-blown sand disaster on the railway has a very important negative influence on the economic development of traffic networks in desert areas. While there are some engineering protection measures for railway sand deposition, they are far from satisfactory in terms of economic efficiency and protection performance. Therefore, it is still of great practical significance to explore novel measures for actively preventing sand deposition on railway tracks in desert areas. In this article, the laws of sand deposition on single and dual tracks were studied with the help of field experiments. On this basis, it can be seen that the deposition of sand on the rear track can be effectively reduced by placing various types of baffles on the track. Field experiments were designed to study the change law of sand deposition ratio in front of the tracks caused by placing baffles of different cross sections. The results show that placing a 45° inclined baffle on the track can reduce the volume of sand deposition by up to 42%. The findings in this paper can provide scientific guidance for the design of new desert railways or novel protective measures for railway sand deposition. Full article

This paper presents a systematic fault analysis and diagnosis method of a PEM fuel cell control system using a model-based approach. With a model-based approach, it is possible to analyze the causal relationship and effect of probable faults in the system, and to diagnose them under the assumption that the model and the process are similar. With a model-based approach, it is possible to analyze the causal relationship and effect of probable faults in the system and diagnose them under the assumption that the model and the process are similar. In this work, a model-based approach was adopted for fault analysis and diagnosis, and its methods are suggested. A PEM fuel cell is mathematically modelled, analyzed, and verified for the analysis and simulations. Relationships among variables are shown using an incidence matrix and with a Dulmage–Mendelsohn decomposition of the matrix. When it is difficult to detect faults due to a deficient degree of redundancy, a bi-partite graph is used to analyze the effect of faults and to assess the possibility of fault detection through the appropriate redundant sensor placement. Thereafter, residuals are obtained based on analytical redundancies of the system, and a fault signature matrix is subsequently constructed. A fault detection and isolation (FDI) algorithm is developed based on a fault signature matrix that describes the connection between faults and residuals. The simulation results demonstrate the validity and effectiveness of the proposed FDI algorithm for diagnosing faults. With the proposed FDI algorithm, eight faults could be diagnosed by FDI algorithm with given sensors in the system. Full article

High pressure processing (HPP) inactivates pathogens and increases the safety of ready-to-eat meat products. The high-pressure lethality and the behavior of the surviving cells after HPP depends on process parameters (pressure and time), microorganism and matrix characteristics. The aim of the present study was to quantify the impact of pressure level, water activity (a_w), and fat content on the behavior of Salmonella spp. and Listeria monocytogenes during refrigerated storage of dry-cured ham after high-pressure processing. Salmonella enterica serotype London CTC1003 and L. monocytogenes CTC1034 were inoculated at ca. 7 log cfu/g in dry-cured ham of different a_w (0.87–0.98), vacuum packaged, pressurized from 300 to 852 MPa for 5 min, and stored at 7 °C for up to 2 months. Salmonella and L. monocytogenes populations were monitored by plate count during the storage of the hams. The gamma concept was used to quantify the individual effects of a_w and storage temperature on the pathogen growth/no-growth behavior in pressurized dry-cured ham. The Weibull (inactivation) or Logistic (growth) primary models were fitted to the log change of pathogen levels during storage of dry-cured ham after pressurization. According to the gamma approach, the refrigeration temperature and a_w were the main factors limiting the growth of Salmonella and L. monocytogenes, respectively, in dry-cured ham. Under conditions not allowing growth, the effect of increasing pressures on the microbial inactivation depended on the a_w of dry-cured ham and the pathogen; dry-cured ham with high fat content with an a_w ≥ 0.95 enhanced the inactivation of Salmonella whereas it reduced that of L. monocytogenes. Under conditions allowing growth of L. monocytogenes, the increase in a_w from 0.96 to 0.98 reduced the lag time with no apparent impact on the growth rate. Full article