Transportation Mode Detection Based on Permutation Entropy and Extreme Learning Machine

With the increasing prevalence of GPS devices and mobile phones, transportation mode detection based on GPS data has been a hot topic in GPS trajectory data analysis. Transportation modes such as walking, driving, bus, and taxi denote an important characteristic of the mobile user. Longitude, latitude, speed, acceleration, and direction are usually used as features in transportation mode detection. In this paper, first, we explore the possibility of using Permutation Entropy (PE) of speed, a measure of complexity and uncertainty of GPS trajectory segment, as a feature for transportation mode detection. Second, we employ Extreme Learning Machine (ELM) to distinguish GPS trajectory segments of different transportation. Finally, to evaluate the performance of the proposed method, we make experiments on GeoLife dataset. Experiments results show that we can get more than 50% accuracy when only using PE as a feature to characterize trajectory sequence. PE can indeed be effectively used to detect transportation mode from GPS trajectory. The proposed method has much better accuracy and faster running time than the methods based on the other features and SVM classifier

A potential brain functional biomarker distinguishing patients with Crohn’s disease with different disease stages: a resting-state fMRI study

BackgroundThe previous studies have demonstrated that patients with Crohn’s disease in remission (CD-R) have abnormal alterations in brain function. However, whether brain function changes in patients with Crohn’s disease in activity (CD-A) and the relationship with CD-R are still unclear. In this study, we aimed to investigate whether the different levels of disease activity may differentially affect the brain function and to find the brain functional biomarker distinguishing patients with different disease stages by measuring the amplitude of low frequency fluctuations (ALFF).Methods121 patients with CD and 91 healthy controls (HCs) were recruited. The clinical and psychological assessment of participants were collected. The criteria for the disease activity were the Crohn’s disease activity index (CDAI) scores. CD-R refers to CD patients in remission which the CDAI score is less than 150. Conversely, CD-A refers to CD patients in activity which the CDAI score is ≥150. The ALFF was compared among three groups by performing one-way analysis of variance, followed by a post hoc two-sample t-test. Differences among the groups were selected as seeds for functional connectivity analyses. We also investigated the correlation among clinical, psychological scores and ALFF. Binary logistic regression analysis was used to examine the unique contribution of the ALFF characteristics of the disease stages.ResultsThere were widespread differences of ALFF values among the 3 groups, which included left frontal pole (FP_L), right supramarginal gyrus (SG_R), left angular gyrus (AG_L), right cingulate gyrus (CG_R), right intracalcarine cortex (IC_R), right parahippocampal gyrus (PG_R), right lingual gyrus (LG_R), right precuneous cortex (PC_R), left occipital fusiform gyrus (OFG_L). Significant brain regions showing the functional connections (FC) increased in FP_L, SG_R, PC_R and OFG_L between CD-A and HCs. The erythrocyte sedimentation rate had a negative correlation with the ALFF values in PC_R in the patients with CD. The phobic anxiety values had a negative correlation with the ALFF values in OFG_L. The psychoticism values had a negative correlation with ALFF values in the IC_R. And the hostility values had a positive correlation with the ALFF values in CG_R. Significant brain regions showing the FC increased in FP_L, SG_R, CG_R, PG_R, LG_R and OFG_L between CD-R and HCs. In binary logistic regression models, the LG_R (beta = 5.138, p = 0.031), PC_R (beta = 1.876, p = 0.002) and OFG_L (beta = 3.937, p = 0.044) was disease stages predictors.ConclusionThe results indicated the significance of the altered brain activity in the different disease stages of CD. Therefore, these findings present a potential identify neuroimaging-based brain functional biomarker in CD. Additionally, the study provides a better understanding of the pathophysiology of CD

Phage vB_PaeS-PAJD-1 Rescues Murine Mastitis Infected With Multidrug-Resistant Pseudomonas aeruginosa

Pseudomonas aeruginosa is a Gram-negative pathogen that causes a variety of infections in humans and animals. Due to the inappropriate use of antibiotics, multi-drug resistant (MDR) P. aeruginosa strains have emerged and are prevailing. In recent years, cow mastitis caused by MDR P. aeruginosa has attracted attention. In this study, a microbial community analysis revealed that P. aeruginosa could be a cause of pathogen-induced cow mastitis. Five MDR P. aeruginosa strains were isolated from milk diagnosed as mastitis positive. To seek an alternative antibacterial agent against MDR, P. aeruginosa, a lytic phage, designated vB_PaeS_PAJD-1 (PAJD-1), was isolated from dairy farm sewage. PAJD-1 was morphologically classified as Siphoviridae and was estimated to be about 57.9 kb. Phage PAJD-1 showed broad host ranges and a strong lytic ability. A one-step growth curve analysis showed a relatively short latency period (20 min) and a relatively high burst size (223 PFU per infected cell). Phage PAJD-1 remained stable over wide temperature and pH ranges. Intramammary-administered PAJD-1 reduced bacterial concentrations and repaired mammary glands in mice with mastitis induced by MDR P. aeruginosa. Furthermore, the cell wall hydrolase (termed endolysin) from phage PAJD-1 exhibited a strong bacteriolytic and a wide antibacterial spectrum against MDR P. aeruginosa. These findings present phage PAJD-1 as a candidate for phagotherapy against MDR P. aeruginosa infection

Analysis of Vibration Characteristics of Planetary Gearbox with Broken Sun Gear Based on Phenomenological Model

To investigate the vibration properties in healthy and fault conditions of planetary gearboxes, a phenomenological model is constructed to present the vibration spectrum structure. First, the effects of the base deflection of the gear fillet and the flexibility between the root circle and the base circle on the time-varying meshing stiffness are considered in order to construct an equivalent model of time-varying mesh stiffness and broken tooth faults, exploring the law of variation for meshing stiffness when differently sized faults occur on the sun gear. Then, considering both the effect of the vibration transfer path and the meshing impacts, we establish phenomenological models of planetary gears under healthy and fault conditions. By comparing and analyzing the phenomenological model based on the cosine function to verify the effectiveness of the proposed model. The experimental results show that the error of the proposed model is 1.38% lower than that of the traditional phenomenological model, and the proposed model can accurately analyze the frequency, amplitude, and sideband characteristics of the vibration signals of sun gear with different degrees of broken tooth, which can be used for the local fault diagnosis of planetary gearboxes

Exploratory Research on Knowledge Graph Construction and Attribute Value Extraction for Large-scale Textual Data of Tourism Products

Complexity of tourism products exists in route design and service combination provided by suppliers. Generating reasonable rules by utilizing large-scale textual data of tourism products will be an effective way to explore imitation and competition from product-product relationships thus observing how they respond to consumer demands and market changeable. In this sense, constructing a tourism product knowledge graph (TPKG) will be a key data strategy for a travel agency or e-commerce platform. This paper constructs a knowledge graph of tourism products with seven feature dimensions and creates a structured model to imagine the service details and features. BiLSTM-CRF was used to extract entities from large-scale textual data, while entity-related attributes and attribute values were extracted from Baidu Baike. Furthermore, possibility of correlation between entities using the link prediction algorithm was checked, and entity disambiguation was accomplished. Finally, TPKG was visualized using Neo4j graph to show the validity of ontological structure for tourism products. Our paper provides a new process and method to uncover the imitation and competition relationship among tourism products from a nuanced particle perspective

Fully dense nanocrystalline (La0.2Nd0.2Sm0.2Eu0.2Gd0.2)2Zr2O7 high-entropy ceramics fabricated under ultra-high pressure

In this work, nanocrystalline high-entropy ceramics (HECs) were prepared by the combination of combustion synthesis and ultra-high pressure sintering. The prepared high-entropy (La0.2Nd0.2Sm0.2Eu0.2Gd0.2)2Zr2O7 ceramic powder had the average grain size of 11 nm and displayed the disordered defective fluorite structure. The HECs sintered under ultra-high pressure showed the defective fluorite structure, whereas the control samples fabricated by pressureless sintering showed the ordered pyrochlore structure. The HECs sintered under pressure of 10 GPa possessed much smaller grain size than that obtained by pressureless sintering. In particular, the grain size of ceramics sintered under 10 GPa at 600 °C was not significantly larger than that of raw powder and its Vickers hardness was 11.9 GPa. Ultra-high pressure sintering could remarkably increase the density of ceramics and restrain the growth of grains. The plastic deformation under ultra-high pressure was believed as the main densification mechanism for the grain refinement and performance improvement

Identification of Sanguinarine Metabolites in Rats Using UPLC-Q-TOF-MS/MS

Sanguinarine (SAN), as the main active component of a traditional Chinese veterinary medicine, has been widely used in the animal husbandry and breeding industry. However, the metabolites of SA are still uncertain. Therefore, this research aimed to investigate the metabolites of SA based on rats in vivo. The blood, feces, and urine of rats were collected after the oral administration of 40 mg/kg SAN. Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) was employed to identify the metabolites of SAN. The elemental composition of sanguinarine metabolites was inferred by analyzing their exact molecular weight, and the structures of the metabolites were predicted based on their fragment ions and cleavage pathways. A total of 12 metabolites were identified, including three metabolites in the plasma, four in the urine, and nine in the feces. According to the possible metabolic pathways deduced in this study, SAN was mainly metabolized through reduction, oxidation, demethylation, hydroxylation, and glucuronidation. This present research has summarized the metabolism of SAN in rats, which is helpful for further studying the metabolic mechanism of SAN in vivo and in vitro

Integrating Network Pharmacology and Molecular Docking to Analyse the Potential Mechanism of action of <i>Macleaya cordata (Willd.) R. Br.</i> in the Treatment of Bovine Hoof Disease

Based on network pharmacological analysis and molecular docking techniques, the main components of M. cordata for the treatment of bovine relevant active compounds in M. cordata were searched for through previous research bases and literature databases, and then screened to identify candidate compounds based on physicochemical properties, pharmacokinetic parameters, bioavailability, and drug-like criteria. Target genes associated with hoof disease were obtained from the GeneCards database. Compound−target, compound−target−pathway−disease visualization networks, and protein−protein interaction (PPI) networks were constructed by Cytoscape. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed in R language. Molecular docking analysis was done using AutoDockTools. The visual network analysis showed that four active compounds, sanguinarine, chelerythrine, allocryptopine and protopine, were associated with the 10 target genes/proteins (SRC, MAPK3, MTOR, ESR1, PIK3CA, BCL2L1, JAK2, GSK3B, MAPK1, and AR) obtained from the screen. The enrichment analysis indicated that the cAMP, PI3K-Akt, and ErbB signaling pathways may be key signaling pathways in network pharmacology. The molecular docking results showed that sanguinarine, chelerythrine, allocryptopine, and protopine bound well to MAPK3 and JAK2. A comprehensive bioinformatics-based network topology strategy and molecular docking study has elucidated the multi-component synergistic mechanism of action of M. cordata in the treatment of bovine hoof disease, offering the possibility of developing M. cordata as a new source of drugs for hoof disease treatment

Characterization and evaluation of stable localized corrosion in a 7075-T6 aluminum alloy FSW joint before and after anodizing treatment

The microstructure and corrosion processes of a friction stir welded (FSW) 7075-T6 aluminum alloy joint, before and after anodizing surface treatment, have been characterized by advanced techniques, and the feasibility of anodizing treatment as a corrosion mitigation method has been evaluated. The results showed that different zones of the FSW joint had distinctly different microstructure and consequently different corrosion behavior in NaCl solution. Stable localized corrosion occurred in the transitional regions between the thermo-mechanically affected zone (TMAZ) and heat affected zone (HAZ), and was characterized by intergranular corrosion. The intergranular corrosion was ascribed to the galvanic coupling effect between Cu-rich grain boundary precipitates and the precipitates free zones (PFZs). Although anodizing and the subsequent sealing treatments could greatly improve the corrosion resistance of the base metal, the TMAZ/HAZ transition regions still showed much higher corrosion susceptibility than other regions. The high corrosion susceptibility of the FSW joint after anodizing treatment is not ascribed to the difference of the anodic oxide film in the regions, but the heterogeneous microstructure of the alloy beneath the anodic film. The present paper has shown that the stable localized corrosion in the FSW joint is intrinsically stemmed from the welding process itself and traditional mitigation method such as anodizing treatment cannot solve the problem; more effective corrosion mitigation methods are still awaited

Lateral Vibration Control of Long-Span Small-Radius Curved Steel Box Girder Pedestrian Bridge with Distributed Multiple Tuned Mass Dampers

Curved pedestrian bridges are important urban infrastructure with the desired adaptability to the landscape constraints and with aesthetic benefits. Pedestrian bridges feature thin cross-sections, which provide sufficient load capacities but lead to low natural frequencies that make the bridges susceptible to vibration under pedestrian excitation. This study investigates the lateral vibration of a curved bridge with a small radius down to 20 m, proposes an approach to mitigate the lateral vibration of bridges with large curvatures using distributed multiple tuned mass dampers (MTMD), and conducts in-situ bridge tests to evaluate the vibration mitigation performance. The lateral vibration was investigated through in-situ tests and finite element analysis as well as the code requirements. The key parameters of the distributed MTMD system were improved by strategically selecting the mass ratio, bandwidth, center frequency ratio, and damper number. The results showed that the curved bridge was subjected to significant lateral vibration due to the coupling of torque and moment, and the recommended design parameters for the studied bridge were derived, i.e., the total mass ratio is 0.02, bandwidth is 0.15, center frequency ratio is 1.0, and damper number is 3. The proposed approach effectively improves the deployment of MTMD for lateral vibration control of the curved bridge. The field tests showed that the vibration was reduced by up to 82% by using the proposed approach