A Novel Method for Rolling Bearing Fault Diagnosis Based on Gramian Angular Field and CNN-ViT.

Fault diagnosis is one of the important applications of edge computing in the Industrial Internet of Things (IIoT). To address the issue that traditional fault diagnosis methods often struggle to effectively extract fault features, this paper proposes a novel rolling bearing fault diagnosis method that integrates Gramian Angular Field (GAF), Convolutional Neural Network (CNN), and Vision Transformer (ViT). First, GAF is used to convert one-dimensional vibration signals from sensors into two-dimensional images, effectively retaining the fault features of the vibration signal. Then, the CNN branch is used to extract the local features of the image, which are combined with the global features extracted by the ViT branch to diagnose the bearing fault. The effectiveness of this method is validated with two datasets. Experimental results show that the proposed method achieves average accuracies of 99.79% and 99.63% on the CWRU and XJTU-SY rolling bearing fault datasets, respectively. Compared with several widely used fault diagnosis methods, the proposed method achieves higher accuracy for different fault classifications, providing reliable technical support for performing complex fault diagnosis on edge devices.

Vehicle routing problem with time windows and carbon emissions: a case study in logistics distribution.

Logistics and transportation industry is not only a major energy consumer, but also a major carbon emitter. Developing green logistics is the only way for the sustainable development of the logistics industry. One of the main factors of environmental pollution is caused by carbon emissions in the process of vehicle transportation, and carbon emissions of vehicle transportation are closely related to routing, road conditions, vehicle speed, and speed fluctuations. The low-carbon vehicle routing problem with high granularity time-dependent speeds, speed fluctuations, road conditions, and time windows is proposed and formally described. In order to finely evaluate the effects of vehicle speed and speed fluctuations on carbon emissions, a graph convolutional network (GCN) is used to predict the high granularity time-dependent traffic speeds. To solve this complicated low-carbon vehicle routing problem, a hybrid genetic algorithm with adaptive variable neighborhood search is proposed to obtain vehicle routing with low carbon emissions. Finally, this method is validated using a case study with the logistics and traffic data in Jingzhou, China, and also the results show the effectiveness of this proposed method.

Janus layers and electronic structure of 1T-(TiSeS)2.

TiS2-TiSe2 is one of the most studied titanium based solid solution systems. However, so far, all research on it has only focused on its disordered phase. Here, we systematically investigate its ordered phases. Using a structure search method based on the particle swarm optimization (CALYPSO) algorithm, we identify TiSeS-156 and discover a new structure (1T-(TiSeS)2). Based on first principles theory, their phonon spectra, formation energy, mechanical, electronic, thermal, and optical properties, as well as chemical bond analysis and synthetic pathways, have been investigated. The primitive cell of TiSeS-156 has three atoms and has a space group of P3m1 (no. 156). 1T-(TiSeS)2 has six atoms and has P3̄m1 symmetry (no. 164). TiSeS-156 and 1T-(TiSeS)2 are constructed by stacking the S-Ti-Se Janus layer materials. TiSeS-156 and 1T-(TiSeS)2 are narrow-gap semiconductors. The localized nature of the Ti(3d) states of TiSeS-156 and 1T-(TiSeS)2 leads to their semiconductor properties. 1T-(TiSeS)2 and TiSeS-156 have very similar mechanical, electronic, thermal, and optical properties of 1T-TiS2 and 1T-TiSe2, and are members of the 2D hexagonal lattice transition metal dichalcogenide layered material family. However, compared with 1T-TiS2 and 1T-TiSe2, TiSeS-156 and 1T-(TiSeS)2 have a wider range of potential applications, such as photovoltaic devices and photocatalysis, due to their S-Ti-Se Janus layer structure. They also provide a pathway for the preparation of Janus TiSeS monolayer and multi-layer materials. Moreover, our findings provide crucial insights for understanding the rich and complex crystal structures of the TiS2-TiSe2 system, which have broad implications for further exploration of this class of promising materials.

The Lightweight Anchor Dynamic Assignment Algorithm for Object Detection.

Smart security based on object detection is one of the important applications of edge computing in IoT. Anchors in object detection refer to points on the feature map, which can be used to generate anchor boxes and serve as training samples. Current object detection models do not consider the aspect ratio of the ground-truth boxes in anchor assignment and are not well-adapted to objects with very different shapes. Therefore, this paper proposes the Lightweight Anchor Dynamic Assignment algorithm (LADA) for object detection. LADA does not change the structure of the original detection model; first, it selects an equal proportional center region based on the aspect ratio of the ground-truth box, then calculates the combined loss of anchors, and finally divides the positive and negative samples more efficiently by dynamic loss threshold without additional models. The algorithm solves the problems of poor adaptability and difficulty in the selection of the best positive samples based on IoU assignment, and the sample assignment for eccentric objects and objects with different aspect ratios was more reasonable. Compared with existing sample assignment algorithms, the LADA algorithm outperforms the MS COCO dataset by 1.66% over the AP of the baseline FCOS, and 0.76% and 0.24% over the AP of the ATSS algorithm and the PAA algorithm, respectively, with the same model structure, which demonstrates the effectiveness of the LADA algorithm.

Line Shape Analysis and Dynamic Response of Ballastless Track during Jacking Rectification Fixing.

In order to study the railway line deformation and dynamic response of ballastless track structure under train load during jacking rectification fixing, a three-dimensional numerical model of the CRTS II slab ballastless track on subgrade is established by using the finite element method. The line deformation rule and local damage rule of ballastless track under jacking force are analyzed. The dynamic response laws of track structure and subgrade bed are compared considering four different connection modes between the base plate and subgrade bed under different train speeds in the process of jacking rectification fixing. The results show that jacking force and dissociation length have a small influence on the deviation value and the critical jacking force should be smaller than 375 kN in single point jacking. Under the condition of multi-point jacking, when the jacking loading length equals to 5 slabs, the critical jacking force should be smaller than 275 kN and the maximum lateral deviation value is about 22.11 mm. It is necessary to restrict the speed of passing trains to no more than 150 km/h during the jacking rectification fixing for dissociation condition without temporary restraint. When temporary restraint is applied, the speed of the train can be increased appropriately according to the actual situation. The above study results could be used as a theoretical reference for the ballastless track deviation correction.

Analysis on Damage and Mechanical Properties of Ballastless Track in a Tunnel after a Fire.

In order to explore the damage and mechanical properties of ballastless track after a fire, the uniaxial compressive strength, shear strength, peak strain, and elastic modulus changes due to temperature were obtained through uniaxial compressive and shear tests of concrete after exposure to high temperatures. The test results showed that with increases in temperature, the uniaxial compressive strength, shear strength, and elastic modulus of concrete all presented a decreasing trend, while the peak strain had an increasing trend. Then, based on the classical damage theory model and the strength probability distribution function of concrete micro-units, the high-temperature damage constitutive equation for concrete was established, and the compressive stress-strain curve of concrete after exposure to high temperature was reproduced. Finally, using the CFD numerical simulation software, the temperature field of a ballastless track structure in a tunnel during a fire was obtained, and the temperatures at different positions of ballastless track bed were acquired. Combined with the high-temperature damage constitutive equation for concrete deduced from tests and theoretical analysis, the strength and damage values of the ballastless track bed at different positions after a tunnel fire were obtained.

Prevalence and risk factors of carbapenem-resistant Enterobacterales positivity by active screening in intensive care units in the Henan Province of China: A multi-center cross-sectional study.

Objective: In intensive care units (ICUs), carbapenem-resistant Enterobacterales (CRE) pose a significant threat. We aimed to examine the distribution, epidemiological characteristics, and risk factors for CRE positivity in ICUs. Materials and methods: This cross-sectional study was conducted in 96 ICUs of 78 hospitals in Henan Province, China. The clinical and microbiological data were collected. A multivariable logistic regression model was used to analyze the risk factors for CRE positivity. Results: A total of 1,009 patients were enrolled. There was a significant difference in CRE positive rate between pharyngeal and anal swabs (15.16 vs. 19.13%, P < 0.001). A total of 297 carbapenem-resistant Klebsiella pneumoniae (CR-KPN), 22 carbapenem-resistant Escherichia coli (CR-ECO), 6 carbapenem-resistant Enterobacter cloacae (CR-ECL), 19 CR-KPN/CR-ECO, and 2 CR-KPN/CR-ECL were detected. Klebsiella pneumoniae carbapenemase (KPC), New Delhi metallo-beta-lactamase (NDM), and a combination of KPC and NDM were detected in 150, 9, and 11 swab samples, respectively. Multivariable logistic regression analysis determined length of ICU stay, chronic neurological disease, transfer from other hospitals, previous infection, and history of antibiotics exposure as independent risk factors for CRE positivity. Age and cardiovascular diseases were independent risk factors for mixed infections of CRE. The occurrence of CRE in secondary and tertiary hospitals was 15.06 and 25.62%, respectively (P < 0.05). Patients from tertiary hospitals had different clinical features compared with those from secondary hospitals, including longer hospital stays, a higher rate of patients transferred from other hospitals, receiving renal replacement therapy, exposure to immunosuppressive drugs, use of antibiotics, and a higher rate of the previous infection. Conclusion: In ICUs in Henan Province, CRE positive rate was very high, mostly KPC-type CR-KPN. Patients with prolonged ICU stay, chronic neurological disease, transfer from other hospitals, previous infection, and history of antibiotic exposure are prone to CRE. Age and cardiovascular diseases are susceptibility factors for mixed infections of CRE. The CRE positive rate in tertiary hospitals was higher than that in secondary hospitals, which may be related to the source of patients, antibiotic exposure, disease severity, and previous infection.

Indoor Positioning System with UWB Based on a Digital Twin.

Ultra-wideband (UWB) technology is used for indoor positioning, but its positioning accuracy is usually degenerated by various obstacles in the indoor environment because of non-line-of-sight (NLOS). Facing the complex and changeable indoor environment, an indoor positioning system with UWB based on a digital twin is presented in this paper. The indoor positioning accuracy is improved with a perception-prediction feedback of cyber-physics space in this indoor positioning system. In addition, an anchor layout method with virtuality-reality interaction and an error mitigation method based on neural networks is put forward in this system. Finally, a case study is presented to validate this indoor positioning system with a significant improvement in positioning accuracy.

Bulk photovoltaic effect in GaNGeC quaternary compound semiconductors.

Compared to the p-n junction photovoltaic effect, the bulk photovoltaic effect is a potential way to overcome the external limitations of solar energy conversion. It is challenging to find new materials with a bulk photovoltaic effect. In this article, using first-principles calculations and the maximum local Wannier function, we investigated the bulk photovoltaic effect in GaNGeC quaternary compound semiconductors with six different crystal structures (S-1, S-2, S-3, S-4, S-5, and S-6 for short). These semiconductors showed a large effective three-dimensional shift current conductivity, where the maximum absolute value of the shift current conductivity ranges from 10 µA V-2 to 425 µA V-2, indicating that they are promising candidates for photoelectric conversion applications. Furthermore, the electron localization function, difference charge density, and atomic configurations as well as Löwdin population analysis revealed that dimerization of the GaN layer and the GeC layer in S-5 and S-6 induces delocalization of electrons. This delocalization of electrons enhances their shift current conductivities, which provides valuable insight for further design and development of new photovoltaic materials.

Rhythmic Leaf and Cotyledon Movement Analysis.

The first descriptions of circadian rhythms were of the rhythmic leaf movements of plants. Rhythmic leaf movements offer a sensitive, noninvasive, nondestructive, and non-transgenic assay of plant circadian rhythms that can be readily automated, greatly facilitating genetic studies. Rhythmic leaf movement is particularly useful for the assessment of standing variation in clock function and can be readily applied to a diverse array of dicotyledonous plants, including both wild species and domesticated crops.

Influence of Vehicle Number on the Dynamic Characteristics of High-Speed Train-CRTS III Slab Track-Subgrade Coupled System.

In this paper, a high-speed train-CRTS III slab track-subgrade coupled dynamic model is established. With the model, the influence of vehicle number on the dynamic characteristics of a train-CRTS III slab track-subgrade coupled system with smooth and random track irregularity conditions for conventional and vibration-reduction CRTS III slab tracks are theoretically studied and analyzed. Some conclusions are drawn from the results: (1) the largest dynamic responses of the coupled system for all items and cases are no longer changed when the vehicle number exceeds three, and three vehicles are adequate to guarantee the simulation precision to investigate the dynamic responses of the coupled system. (2) The acceleration of the car body has almost no relation with the vehicle number, and only one vehicle is needed to study the vehicle dynamics using the train-CRTS III slab track-subgrade coupled dynamic model. (3) For the conventional CRTS III slab track on a subgrade, the vehicle number has a negligible influence on the accelerations of the rail, slab, and concrete base, the positive and negative bending moments of the rail, the compressive force of the fastener, and the positive bending stress of slab, but it has a large influence on the tension force of the fastener, and the negative bending stresses of the slab and concrete base. Only one vehicle is needed to study track dynamics without considering the tension force of the fastener, the negative bending stresses of the slab and concrete base, otherwise, two or more vehicles are required. (4) For vibration reduction of the CRTS III slab track on a subgrade, the number of vehicles has some influence on the dynamic responses of all track components, and at least two vehicles are required to investigate the track dynamics.

Robot Motor Skill Transfer With Alternate Learning in Two Spaces.

Recent research achievements in learning from demonstration (LfD) illustrate that the reinforcement learning is effective for the robots to improve their movement skills. The current challenge mainly remains in how to generate new robot motions automatically to perform new tasks, which have a similar preassigned performance indicator but are different from the demonstration tasks. To deal with the abovementioned issue, this article proposes a framework to represent the policy and conduct imitation learning and optimization for robot intelligent trajectory planning, based on the improved locally weighted regression (iLWR) and policy improvement with path integral by dual perturbation (PI2-DP). Besides, the reward-guided weight searching and basis function's adaptive evolving are performed alternately in two spaces, i.e., the basis function space and the weight space, to deal with the abovementioned problem. The alternate learning process constructs a sequence of two-tuples that join the demonstration task and new one together for motor skill transfer, so that the robot gradually acquires motor skill, from the task similar to demonstration to dissimilar tasks with different performance metrics. Classical via-points trajectory planning experiments are performed with the SCARA manipulator, a 10-degree of freedom (DOF) planar, and the UR robot. These results show that the proposed method is not only feasible but also effective.

Genetic and genomic resources to study natural variation in Brassica rapa.

The globally important crop Brassica rapa, a close relative of Arabidopsis, is an excellent system for modeling our current knowledge of plant growth on a morphologically diverse crop. The long history of B. rapa domestication across Asia and Europe provides a unique collection of locally adapted varieties that span large climatic regions with various abiotic and biotic stress-tolerance traits. This diverse gene pool provides a rich source of targets with the potential for manipulation toward the enhancement of productivity of crops both within and outside the Brassicaceae. To expand the genetic resources available to study natural variation in B. rapa, we constructed an Advanced Intercross Recombinant Inbred Line (AI-RIL) population using B. rapa subsp. trilocularis (Yellow Sarson) R500 and the B. rapa subsp. parachinensis (Cai Xin) variety L58. Our current understanding of genomic structure variation across crops suggests that a single reference genome is insufficient for capturing the genetic diversity within a species. To complement this AI-RIL population and current and future B. rapa genomic resources, we generated a de novo genome assembly of the B. rapa subsp. trilocularis (Yellow Sarson) variety R500, the maternal parent of the AI-RIL population. The genetic map for the R500 x L58 population generated using this de novo genome was used to map Quantitative Trait Loci (QTL) for seed coat color and revealed the improved mapping resolution afforded by this new assembly.

Appropriate locations of fixed bearings of continuous beams considering rail-bridge thermal interaction.

Due to the rail-bridge thermal interaction, the high additional axial force in continuously welded rails on continuous bridges may lead to rail buckling or breaking. However, there is little research on the influence of the location of the fixed bearing of continuous beam on the additional force of rail. In order to study the influence of bridge bearing arrangement on the additional longitudinal force of CWR, the thermal interaction model is established for rail, and simple and continuous beams considering nonlinear stiffness and the methods are proposed to determine the locations of fixed bearings of continuous beams corresponding to the maximum additional forces in rail reaching minimum values. Multiple continuous beams with several different lengths and simple beams with three types of bearing arrangements are taken into account to find the effect laws of the locations of the fixed bearings of continuous beams on the maximum additional forces in rail. The results show that as long as the same number of continuous beams, the ratios of the distances of adjacent two fixed bearings to the distance between the two fixed bearings of the simple beams neighbour to the first and last continuous beams respectively are approximately equal to each other. Furthermore the appropriate locations of the fixed bearings of continuous beams are recommended. The results can guide designing the location of the fixed bearing of continuous railway bridge while reducing the additional axial force in continuously welded rails due to bridge thermal effect.

Expansion of the circadian transcriptome in Brassica rapa and genome-wide diversification of paralog expression patterns.

An important challenge of crop improvement strategies is assigning function to paralogs in polyploid crops. Here we describe the circadian transcriptome in the polyploid crop Brassica rapa. Strikingly, almost three-quarters of the expressed genes exhibited circadian rhythmicity. Genetic redundancy resulting from whole genome duplication is thought to facilitate evolutionary change through sub- and neo-functionalization among paralogous gene pairs. We observed genome-wide expansion of the circadian expression phase among retained paralogous pairs. Using gene regulatory network models, we compared transcription factor targets between B. rapa and Arabidopsis circadian networks to reveal evidence for divergence between B. rapa paralogs that may be driven in part by variation in conserved non-coding sequences (CNS). Additionally, differential drought response among retained paralogous pairs suggests further functional diversification. These findings support the rapid expansion and divergence of the transcriptional network in a polyploid crop and offer a new approach for assessing paralog activity at the transcript level.

Like animals, plants have internal biological clocks that allow them to adapt to daily and yearly changes, such as day-night cycles or seasons turning. Unlike animals, however, plants cannot move when their environment becomes different, so they need to be able to weather these changes by adjusting which genes they switch on and off. To do this, plants keep track of how long days are using external cues such as light or temperature. One of the effects of climate change is that these cues become less reliable, making it harder for plants to adapt to their environment and survive. This is a potential problem for crop species, like Brassica rapa. This plant has many edible forms, including Chinese cabbage, oilseed, pak choi, and turnip. It is also a close relative of the well-studied model plant, Arabidopsis. Since evolving away from Arabidopsis, the genome of B. rapa tripled, meaning it has one, two, or three copies of each gene. This has allowed the extra gene copies to mutate and adapt to different purposes. The question is, what impact has this genome expansion had on the plant's biological clock? One way to find out is to perform RNA-sequencing experiments, which record the genes a plant is using at any one time. Here, Greenham, Sartor et al. report the results of a series of RNA-sequencing experiments performed every two hours across two days. Plants were first exposed to light-dark or temperature cycles and then samples were taken when the plants were in constant light and temperature. This revealed which genes B. rapa turned on and off in response to signals from the internal biological clock. It turns out that the biological clock of B. rapa controls close to three quarters of its genes. These genes showed distinct phases, increasing or decreasing in regular patterns. But the different copies of duplicated and triplicated genes did not necessarily all behave in the same way. Many of the copies had different rhythms, and some increased and decreased in patterns totally opposite to their counterparts. Not only did the daily patterns differ, but responses to stressors like drought were also altered. Comparing these patterns to the patterns seen in Arabidopsis revealed that often, one B. rapa gene behaved just like its Arabidopsis equivalent, while its copies had evolved new behaviors. The different behaviors of the copies of each gene in B. rapa relative to its biological clock allow this plant to grow in different environments with varying temperatures and day lengths. Understanding how these adaptations work opens new avenues of research into how plants detect and respond to environmental signals. This could help to guide future work into targeting genes to improve crop growth and stress resilience.

[Progress in the mechanisms of response to different oxygen concentrations in Caenorhabditis elegans].

Oxygen levels are unequal in different living geographical locations of human and related to normal physiology of health. The reduction of oxygen level in the body can lead to a variety of diseases, such as stroke caused by cerebral ischemia and hypoxia. In the recent years, many studies have elucidated the molecular and cellular mechanisms of organism response to different oxygen concentrations by using the nematode Caenorhabditis elegans (C. elegans) as model organism. C. elegans can escape hypoxia or hyperoxia and adapt to the ambient oxygen environments, and there are different response and regulation mechanisms in different degrees of hypoxia environment. In this paper, recent advances in the reaction of nematodes to different oxygen concentrations and the underlying mechanism were reviewed.

A Data-driven Adaptive Sampling Method Based on Edge Computing.

The rise of edge computing has promoted the development of the industrial internet of things (IIoT). Supported by edge computing technology, data acquisition can also support more complex and perfect application requirements in industrial field. Most of traditional sampling methods use constant sampling frequency and ignore the impact of changes of sampling objects during the data acquisition. For the problem of sampling distortion, edge data redundancy and energy consumption caused by constant sampling frequency of sensors in the IIoT, a data-driven adaptive sampling method based on edge computing is proposed in this paper. The method uses the latest data collected by the sensors at the edge node for linear fitting and adjusts the next sampling frequency according to the linear median jitter sum and adaptive sampling strategy. An edge data acquisition platform is established to verify the validity of the method. According to the experimental results, the proposed method is more effective than other adaptive sampling methods. Compared with constant sampling frequency, the proposed method can reduce the edge data redundancy and energy consumption by more than 13.92% and 12.86%, respectively.

GeC/GaN vdW Heterojunctions: A Promising Photocatalyst for Overall Water Splitting and Solar Energy Conversion.

Two-dimensional van der Waals (vdW) heterojunctions have been regarded as promising candidates for photocatalytic water splitting and solar energy conversion. Here, we propose a two-dimensional GeC/GaN vdW heterostructure, where the GaN monolayer and the GeC monolayer are stacked. The binding energy, phonon spectrum, and elastic constants demonstrate this material's high dynamic and mechanical stability. Most notably, the GW band structure, GW + Bethe-Salpeter equation (BSE) optical absorption spectrum, and the band alignment of the density functional theory (DFT) scheme and empirical formula reveal that the GeC/GaN vdW heterostructures have a dramatically high optical absorption coefficient (∼105 cm-1) in the visible region and a suitable band edge with sufficiently large kinetic overpotentials of the hydrogen evolution reaction (ΔEc ≥ 1.945 eV) and the oxygen evolution reaction (ΔEv ≥ 1.244 eV). Photogenerated electrons and holes aggregate on the GeC monolayer and GaN monolayer surfaces, respectively, which could make this heterojunction a promising candidate for photocatalytic water splitting and solar energy conversion.