Triple condensate halo from water droplets impacting on cold surfaces

Understanding the dynamics in the deposition of water droplets onto solid surfaces is of importance from both fundamental and practical viewpoints. While the deposition of a water droplet onto a heated surface is extensively studied, the characteristics of depositing a droplet onto a cold surface and the phenomena leading to such behavior remain elusive. Here we report the formation of a triple condensate halo observed during the deposition of a water droplet onto a cold surface, due to the interplay between droplet impact dynamics and vapor diffusion. Two subsequent condensation stages occur during the droplet spreading and cooling processes, engendering this unique condensate halo with three distinctive bands. We further proposed a scaling model to interpret the size of each band, and the model is validated by the experiments of droplets with different impact velocity and varying substrate temperature. Our experimental and theoretical investigation of the droplet impact dynamics and the associated condensation unravels the mass and heat transfer among droplet, vapor and substrate, offer a new sight for designing of heat exchange devices

The Acceleration/Deceleration Control Algorithm Based on Trapezoid-Curve Jerk in CNC Machining

Abstract: In this study, we put forward an Acc/Dec control algorithm based on trapezoid-curve jerk in order to avoid step change in jerk curve. Moreover, the motion profile smooth control approach based on continuous jerk is developed in details to decrease machine tools impact according to various kinematics constraint conditions, such as the maximum acceleration, the maximum jerk, the machining program segment displacement, the instruction feed rate and so on; Finally, the developed Acc/Dec approach and the traditional linear Acc/Dec approach are compared in the CNC experimental table. The results reveal that the developed approach can achieve more smooth and flexible motion profile, which is helpful to minish machine tools impact and enhance parts machining surface quality

Optimal Models for Plant Disease and Pest Detection Using UAV Image

The use of deep learning methods to detect plant diseases and pests based on UAV images is an important application of remote sensing technology in modern forestry. This paper uses a CenterNet-based object detection method to construct models for plant disease and pest detection. The accuracy of the models is influenced by parameter alpha, which is used to control the affine transformation in the preprocessing of CenterNet. First, different alphas are sampled for training and testing. Next, the least square method is used to fit the curve between alpha and accuracy measured by mAP (mean average precision). Finally, the equation of the curve is fitted as mAP = -0.22 * alpha2 + 0.32 * alpha + 0.42. In comparison, an automated machine learning (AutoML) method is also conducted to automatically search for the best model. The experiments are done with 5,281 images as the training dataset, 1,319 images as the verification dataset, and 3,842 images as the test dataset. The results show that the best alpha value obtained by the least square method is 0.733, and the accuracy of the corresponding model is 0.536 in mAP@[.5, .95]. In contrast, the accuracy of the AutoML method model is higher with the model accuracy of 0.545 in mAP@[.5, .95]. However, the training time and training resource consumption of the AutoML method are about 3 times that of the least square method. Therefore, in practice, a trade-off should be made according to the accuracy requirements, resource consumption, and task urgency

Biodynamic features Syuantszy Chzhuanti 720°.

Presents the internal parameters and image Syuantszy Chzhuanti 720 ° is shown that in the implementation of the element Syuantszy Chzhuanti 720 °, the center of gravity shifts to 2.94 pm, 1.71 m. and 1.22 m. on the X, Y and Z; rate varies according to X - with 4,22 m/s to 0, Y - to 2,42 m/s to 0, and Z - from 3.68 m/s to 3.86 m/s. Run-time item 1.4 seconds: the first turnover - 0.41 sec., The second turnover-0, 33 sec. At the end of the takeoff run strike force left and right foot of 1147.2 N and 1005 N. Pressing the second, third, fourth, fifth finger and part of the metatarsal of right foot maximum intensity of pressure - 146.1 N; when pressing the first finger and part of the metatarsal maximum intensity of pressure - 280.8 N. The dependence of convergence or remove body parts with a vertical axis of the torque to increase or decrease its speed

Causal associations of gut microbiota and metabolites on sepsis: a two-sample Mendelian randomization study

BackgroundSepsis stands as a dire medical condition, arising when the body’s immune response to infection spirals into overdrive, paving the way for potential organ damage and potential mortality. With intestinal flora’s known impact on sepsis but a dearth of comprehensive data, our study embarked on a two-sample Mendelian randomization analysis to probe the causal link between gut microbiota and their metabolites with severe sepsis patients who succumbed within a 28-day span.MethodsLeveraging data from Genome-wide association study (GWAS) and combining it with data from 2,076 European descendants in the Framingham Heart Study, single-nucleotide polymorphisms (SNPs) were employed as Instrumental Variables (IVs) to discern gene loci affiliated with metabolites. GWAS summary statistics for sepsis were extracted from the UK Biobank consortium.ResultsIn this extensive exploration, 93 distinct genome-wide significant SNPs correlated with gut microbial metabolites and specific bacterial traits were identified for IVs construction. Notably, a substantial link between Coprococcus2 and both the incidence (OR of 0.80, 95% CI: 0.68-0.94, P=0.007) and the 28-day mortality rate (OR 0.48, 95% CI: 0.27-0.85, P=0.013) of sepsis was observed. The metabolite α-hydroxybutyrate displayed a marked association with sepsis onset (OR=1.08, 95% CI: 1.02-1.15, P=0.006) and its 28-day mortality rate (OR=1.17, 95% CI: 1.01-1.36, P=0.029).ConclusionThis research unveils the intricate interplay between the gut microbial consortium, especially the genus Coprococcus, and the metabolite α-hydroxybutyrate in the milieu of sepsis. The findings illuminate the pivotal role of intestinal microbiota and their metabolites in sepsis’ pathogenesis, offering fresh insights for future research and hinting at novel strategies for sepsis’ diagnosis, therapeutic interventions, and prognostic assessments

Experimental study on wear failure of spindle hook teeth of cotton picker

Introduction: The wear failure of spindle will lead to a decrease in cotton harvesting rate of the cotton picker during field operation and serious wastage.Method: Three types of spindle samples at different installation positions and working areas were obtained through field experiments to explore the wear failure law of spindle hook teeth of cotton picker during field operation. Hardness of hook tooth coating and substrate of spindles were tested, surface and cross-section microstructure of the spindle hook teeth were characterized, and wear area and width of the spindle hook teeth were extracted.Results: Results showed that the hardness of the hook tooth coating is evidently higher than that of the substrate; the average coating hardness of the No. 3 spindle hook teeth reaches the maximum at 1033.6 HV0.1; defects, such as microcracks and micropores, exist in the coating of the three types of spindle hook teeth; and the thickness of the coating is between 70 and 130 μm. The wear area of spindle hook tooth changes exponentially and the wear width changes linearly with the increase of field operation area at the same installation position. The wear area and width of the spindle hook teeth gradually increase with the decrease of the installation height and the wear change of the hook teeth is negatively correlated with the installation height in the same field operation area.Discussion: The wear failure of spindle hook tooth is mainly caused by abrasive, fatigue, and oxidation wear. The results of this study can provide a reference for improving the wear resistance of spindle hook teeth

Low-mass dark matter search results from full exposure of PandaX-I experiment

We report the results of a weakly-interacting massive particle (WIMP) dark matter search using the full 80.1\;live-day exposure of the first stage of the PandaX experiment (PandaX-I) located in the China Jin-Ping Underground Laboratory. The PandaX-I detector has been optimized for detecting low-mass WIMPs, achieving a photon detection efficiency of 9.6\%. With a fiducial liquid xenon target mass of 54.0\,kg, no significant excess event were found above the expected background. A profile likelihood analysis confirms our earlier finding that the PandaX-I data disfavor all positive low-mass WIMP signals reported in the literature under standard assumptions. A stringent bound on the low mass WIMP is set at WIMP mass below 10\,GeV/c$^2$, demonstrating that liquid xenon detectors can be competitive for low-mass WIMP searches.Comment: v3 as accepted by PRD. Minor update in the text in response to referee comments. Separating Fig. 11(a) and (b) into Fig. 11 and Fig. 12. Legend tweak in Fig. 9(b) and 9(c) as suggested by referee, as well as a missing legend for CRESST-II legend in Fig. 12 (now Fig. 13). Same version as submitted to PR