Route Restoration Method for Sparse Taxi GPS trajectory based on Bayesian Network

In order to improve the availability of taxi GPS big data, we restore the chosen route for the sparse taxi GPS trajectory in this work. A trajectory restoration method based on Bayesian network is proposed. Compared with the traditional research solely based on time-spatial variables, this method additionally considers the characteristics of empty/heavy taxi status, weather conditions, drivers, vehicle running and other factors to carry out route restoration. A field case of grid network in Ningbo is taken to verify the applicability of the method, using the taxi GPS trajectory data from Ningbo Taxi Information Management Platform. The case results show that the accuracy of Bayesian network method based on multiple factors reaches 91.4%. Its performance is superior to the Multivariate logistic regression model. In addition, the proposed method is especially suitable for scenarios with a high missing rate of track data, such as a scene with timespan of about 5 min between neighbour trajectories

Measurement of the relationship between maxillary premolar roots and the maxillary sinus floor using cone beam CT and analysis of the impact on immediate implantation

Objective To analyze the spatial relationship between the roots of maxillary anterior premolars and the maxillary sinus, thus providing an anatomical basis for timing, planning, surgical approaches, and implant selection at this site. Methods Cone beam CT (CBCT) images were collected from 264 patients (aged 20-65 years) who visited the Ruihua Dental Clinic between January 2017 and March 2023. The minimum distance from the apex of the maxillary anterior premolar roots to the lower wall of the maxillary sinus was measured on the coronal plane. The classification of the vertical relationship between the tooth root and the lower wall of the maxillary sinus was performed, and comparisons were made bilaterally, between genders, and among different age groups. Results The minimum distance (Q50) from the apex of the first maxillary premolar root to the lower wall of the maxillary sinus was 7.34 mm for the single-root type, 7.80 mm for the buccal root of the double-root type, and 7.36 mm for the palatal root. For the second maxillary premolar, the median distance was 2.56 mm for the single root type, 1.73 mm for the buccal root type, and 1.23 mm for the palatal root type. There was a significant difference in the shortest distance from the apex of the right second maxillary premolar single root to the lower wall of the maxillary sinus among the different age groups (P<0.05), with the 20-29-year-old group having the smallest median distance (1.52 mm) and the ≥ 40-year-old group having the largest (4.44 mm). There was no significant difference in the effect of sex or laterality on distance (P>0.05). The most common vertical relationship between the apex of the maxillary anterior premolar roots and the lower wall of the maxillary sinus was noncontact. There was no significant difference in the vertical relationship classification between the single-root and double-root types (P>0.05). Conclusion Most maxillary first premolar roots can provide sufficient bone height, which makes it easy to achieve immediate implantation. The maxillary second premolar root frequently involves insufficient bone, which is necessary to make full use of the bone wall of the extraction socket or the sinus floor cortical bone to achieve initial stability. The vertical relationship between the premolar root and maxillary sinus was influenced by age and dental position. Younger age groups often exhibit inadequate bone height, and the indication for immediate implantation should be carefully considered. The number of roots does not significantly affect the relationship between the sinus and root; however, double-rooted premolars offer more support for immediate implantation and socket healing due to the small root diameter and bony separation between the roots

An observational study on the effect of seasonal variation on peritoneal dialysis patients

Background: Seasonal variation has an impact on plants, wild animals, and also human beings. Data have shown seasonal variation has a significant impact on patients’ fluid status, biochemistry results, and outcomes in hemodialysis populations. The relevant data on peritoneal dialysis is scant.Methods: This was a cross sectional study. All patients followed up in our center had a peritoneal equilibration test and PD adequacy test every 6 months. All the peritoneal equilibration test and PD adequacy test data were collected during December 2019 to November 2020. The monthly delivery information of the whole center was collected from 2015 to 2019.Results: There were 366 patients and 604 sets of peritoneal equilibration test and PD adequacy test results in the study. Plasma albumin and phosphate levels were higher in summer. The monthly average outdoor temperature was positively correlated with plasma albumin. There was no seasonal difference in peritoneal dialysis ultrafiltration or urine volume. The percentage of low glucose concentration (1.5%) usage was higher in summer and lower in winter.Conclusion: Plasma albumin and phosphate levels were higher in summer in PD patients. Weaker glucose peritoneal dialysis dialysate was more widely used in summer. Understanding the seasonal variation of peritoneal dialysis is helpful in individualized treatment

Herbal formulas for detoxification and dredging collaterals in treating carotid atherosclerosis: a systematic review and meta-analysis

Objective: To systematically evaluate the efficacy and safety of the Chinese medicine detoxification and dredging collaterals in treating carotid atherosclerosis (CAS).Methods: A systematic and comprehensive search of nine relevant domestic and international databases were conducted from their inception until June 2022. The methodological quality of the included trials was evaluated, and the efficacy and safety were comprehensively analyzed. After applying the inclusion and exclusion criteria to the randomized controlled trials (RCTs), the research quality evaluation and data extraction were conducted, followed by a meta-analysis of the selected articles. The Cochrane’s Bias risk assessment was utilized to evaluate the quality of the evidence.Results: Of the 2,660 studies initially retrieved, 14 studies were included, involving a total of 1,518 patients. The results of the meta-analysis indicated that the clinical efficacy of the Detoxification and Collateral Dredging method in the treatment of CAS was superior to that of western medicine treatment alone, and the difference was statistically significant [RR = 1.23, 95% CI (1.13, 1.34)] Furthermore, carotid intima-media thickness [Mean Difference (MD) = −0.10, 95% CI (−0.13, −0.08)] and Crouse plaque score [MD = −0.54, 95% CI (−0.75, −0.32)] were significantly lower in the Detoxification and Collateral Dredging group compared to the pure western medicine treatment group. The difference was statistically significant. In addition, serum total cholesterol [MD = −0.70, 95% CI (−0.85, −0.55)] and low-density lipoprotein cholesterol [MD = −0.70, 95% CI (−0.85, −0.55)] were lower in the Detoxification and Collateral Dredging group than in the Western medicine group, with all differences being statistically significant. Serum high-density lipoprotein cholesterol was higher in the Detoxification and Collateral Dredging group compared to the pure western medicine group, and the difference was statistically significant [MD = 0.17, 95% CI (0.11, 0.23)].Conclusion: The use of Chinese medicine Detoxification and Collateral Dredging approach in the treatment of CAS may offer benefits in improving carotid atherosclerotic plaque and reducing blood lipid levels, with a safety profile superior to that of western medicine treatment alone

Ink-printed metal/graphene aerogel for glucose electro-oxidation

Three-dimensional (3D) printing has become one of the promising technologies for the development of bulk-sized nanomaterial composites for electrocatalysis. However, traditional methods such as field deposition modeling and stereolithography are not suitable for the development of functionalized materials for practical use. A large number of studies have focused on the development of the direct ink writing (DIW) printing technique for the fabrication of graphene aerogel (GA)-based electrodes with binders for electrocatalysis. Only a few studies have focused on the synthesis of GA materials from binder-free graphene oxide (GO) using the DIW 3D printing method. Here, we describe the preparation of GA-based electrodes (without size contraction) with different Pd–Pt loadings using the DIW printing method with a commercial 3D food printer. The electron microscopy results showed that a Pd–Pt/GA monolith with a high Pd–Pt loading (59.43 wt%) could be obtained. The DIW-printed Pd–Pt/GA-2 electrode showed good electrochemical performance in glucose electrooxidation (GOR), with a high output current density of 0.94 A g−1 in 0.3 M glucose/1 M NaOH solution at the 3000th cycle operation (60 h). This study shows the potential of DIW-printed binder-free Pd–Pt/GA electrodes for use in fuel cell applications

Seasonal variation and nutrient jointly drive the community structure of macrophytes in lakes with different trophic states

IntroductionMacrophytes are essential for maintaining the health of shallow lake ecosystems, however, the driving and responsive relationship between ecological factors (such as seasonal changes and nutrition, etc.) and plant communities is not yet clear.MethodsIn this study, we conducted seasonal surveys of macrophyte community composition in lakes with different nutrient states, aiming to understand the incidence relation between macrophyte community diversity, seasonal changes and environmental factors.ResultsAccording to the classification criteria of comprehensive nutritional index, there were significant differences in the trophic status of the three lakes. Among them, the Xihu Lake has reached mild eutrophication with a TLI value of 56.33, both Cibi Lake and Haixihai Lake are mesotrophic with TLI value of 36.03 and 33.48, respectively. The results of diversity analysis showed a significant negative correlation between α-diversity (include Species richness, Shannon-Wiener index, Simpson index and Pielou index) and lake nutrient status. Among them, Xihu Lake showed the lowest α-diversity in all seasons, Haixihai Lake exhibited the middle α-diversity, Cibi Lake indicated the highest α-diversity. Non-metric multidimensional ordination showed that there were obvious spatial structures differences among the macrophyte communities in the three lakes. Macrophyte community composition in the three lakes was more similar in summer and autumn, but there was a wider gap in spring and winter. The redundancy analysis indicated distinct differences between diversity index and ecological factors, the eigenvalues of Axis 1 and Axis 2 being, respectively, 36.13% and 8.15%. Environmental factors could explain 44.8% of the total variation in macrophyte communities structure. Among these, nitrogen, phosphorus, water transparency and water temperature contributed 50.2%, 3.5%, 3.8% and 27.5%, respectively.ConclusionsIn summary, the community structure of macrophytes in plateau shallow lakes is co-regulated by seasons and nutrients

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

RGBD Salient Object Detection, Based on Specific Object Imaging

RGBD salient object detection, based on the convolutional neural network, has achieved rapid development in recent years. However, existing models often focus on detecting salient object edges, instead of objects. Importantly, detecting objects can more intuitively display the complete information of the detection target. To take care of this issue, we propose a RGBD salient object detection method, based on specific object imaging, which can quickly capture and process important information on object features, and effectively screen out the salient objects in the scene. The screened target objects include not only the edge of the object, but also the complete feature information of the object, which realizes the detection and imaging of the salient objects. We conduct experiments on benchmark datasets and validate with two common metrics, and the results show that our method reduces the error by 0.003 and 0.201 (MAE) on D3Net and JLDCF, respectively. In addition, our method can still achieve a very good detection and imaging performance in the case of the greatly reduced training data

Research on YOLOv3 model compression strategy for UAV deployment

UAVs are often limited by limited resources when performing flight tasks, especially the contradiction between storage resources and computing resources when the huge YOLOv3 model is deployed on the edge UAVs. In this paper, we tend to compress YOLOv3 model in different aspects to achieve load availability at the edge. In this paper, deep separable convolution is introduced to reduce the computation of the model. Then, PR regularization term is used as the regularization term of sparse training to better distinguish scaling factors, and then the hybrid pruning combining channel pruning and layer pruning is carried out on the model according to scaling factors, in order to reduce the number of model parameters and the amount of calculation. Finally, since the training data is a 32-bit floating point number, DoReFa-Net quantization method is used to quantify the model, so as to compress the storage capacity of the model. The experimental results show that the compression scheme proposed in this paper can effectively reduce the number of parameters by 97.5 % and the calculation amount by 82.3 %, and can maintain the original detection efficiency of UAVs