AN INVESTIGATION ON THE ERROR OF CALIBRATING EXTERIOR POINTS WITH INTERIOR POINTS

This study was to investigate the accuracy of calibrating exterior points with interior points using a frame with the same structure as Peak frame. Two cameras were used. Some points of the frame were used as control points to calibrate others using the DLT method. When we calibrated exterior points with interior points, the minimal and maximal errors were 0.171 cm and 1.797 cm respectively in the horizontal direction (X), 0.213 cm and 4.856 cm in the horizontal direction (Y), 0.103 cm and 1.608 cm in the vertical direction (Z). When we calibrated the interior points with exterior points, almost all errors were less than 1cm. It was concluded that to get the most accurate 3D reconstruction of human movement, it is necessary to make sure that the space formed by control points contains the objects to be calibrated

ANALYSIS OF VALGUS CHARACT,ERISTICS OF OSSEOUS STRUCTURE OF THE FEET WITH THREE-DIMENSIONAL RECONSTRUCTION TECHNIQUES

Using the advanced MR images scan technique combined with three-dimensional reconstruction software, the study went deep into the research of feet's osseous tissue structure. After an investigation of 37 sUbjects' 10 indexes including valgus index and rear foot angle, the study showed distinct differences between normal foot and flatfoot. The correlation modulus of the X-ray images of flatfoot with valgus index is 0.75, and the correlation modulus with rear foot angle is 0.29. The phenomenon that most people with flatfeet had anklebone moving outside illuminated ,that flatfoot resulted from monstrosity of the navicular, cuneiform and metatarsus. However, rear foot angle only embodyed the relative position between calcaneus and shankbone. It couldn't explain the structure differences between flatfoot and normal foot

Transcriptome Analysis and Ultrastructure Observation Reveal that Hawthorn Fruit Softening Is due to Cellulose/Hemicellulose Degradation

Softening, a common phenomenon in many fruits, is a well coordinated and genetically determined process. However, the process of flesh softening during ripening has rarely been described in hawthorn. In this study, we found that ‘Ruanrou Shanlihong 3 Hao’ fruits became softer during ripening, whereas ‘Qiu JinXing’ fruits remained hard. At late developmental stages, the firmness of ‘Ruanrou Shanlihong 3 Hao’ fruits rapidly declined, and that of ‘Qiu JinXing’ fruits remained essentially unchanged. According to transmission electron microscopy (TEM), the middle lamella of ‘Qiu JinXing’ and ‘Ruanrou Shanlihong 3 Hao’ fruit flesh was largely degraded as the fruits matured. Microfilaments in ‘Qiu JinXing’ flesh were arranged close together and were deep in color, whereas those in ‘Ruanrou Shanlihong 3 Hao’ fruit flesh were arranged loosely, partially degraded and light in color. RNA-Seq analysis yielded approximately 46.72 Gb of clean data and 72,837 unigenes. Galactose metabolism and pentose and glucuronate interconversions are involved in cell wall metabolism, play an important role in hawthorn texture. We identified 85 unigenes related to the cell wall between hard- and soft-fleshed hawthorn fruits. Based on data analysis and real-time PCR, we suggest that β-GAL and PE4 have important functions in early fruit softening. The genes Ffase, Gns, α-GAL, PE63, XTH and CWP, which are involved in cell wall degradation, are responsible for the different textures of hawthorn fruits. Thus, we hypothesize that the different textures of ‘Qiu JinXing’ and ‘Ruanrou Shanlihong 3 Hao’ fruits at maturity mainly result from cellulose/hemicelluloses degradation rather than from lamella degradation. Overall, we propose that different types of hydrolytic enzymes in cells interact to degrade the cell wall, resulting in ultramicroscopic Structure changes in the cell wall and, consequently, fruit softening. These results provide fundamental insight regarding the mechanisms by which hawthorn fruits acquire different textures and also lay a solid foundation for further research

Spin-Current Shot Noise in Mesoscopic Conductors

In this paper, we present a method to investigate the spin-current shot noise in mesoscopic conductors, by using scattering matrix theory and Green's function technique. We first derive a general expression for the spin-current noise at zero-frequency limit, and extract the shot-noise component by discussing it at zero-temperature limit. The expression indicates that the spin-current shot noise in one lead is caused by the transmissions to the spin-resolved states in this lead and the interferences of these transmissions. As an application, we simulate the spin-current shot noise in a spin transistor, and discuss its dependence on the device parameters and the bias voltages applied to the transistor. The knowledge we gain from this study will help researchers to evaluate the spin-current shot noise in the future spintronic devices.Comment: 6 figure

Selenium Yeast Dietary Supplement Affects Rumen Bacterial Population Dynamics and Fermentation Parameters of Tibetan Sheep (

Selenium (Se) deficiency is a widespread and seasonally chronic phenomenon observed in Tibetan sheep (Ovis aries) traditionally grazed on the Qinghai–Tibet Plateau (QTP). Effects of the dietary addition of Se-enriched yeast (SeY) on the bacterial community in sheep rumen and rumen fermentation were evaluated with the aim of gaining a better understanding of the rumen prokaryotic community. Twenty-four yearling Tibetan rams [initial average body weight (BW) of 31.0 ± 0.64 kg] were randomly divided into four treatment groups, namely, control (CK), low Se (L), medium Se (M), and high Se (H). Each group comprised six rams and was fed a basic diet of fresh forage cut from the alpine meadow, to which SeY was added at prescribed dose rates. This feed trial was conducted for over 35 days. On the final day, rumen fluid was collected using a transesophageal sampler for analyzing rumen pH, NH3-N content, volatile fatty acid (VFA) level, and the rumen microbial community. Our analyses showed that NH3-N, total VFA, and propionate concentrations in the M group were significantly higher than in the other groups (P < 0.05). Both the principal coordinates analysis (PCoA) and the analysis of similarities revealed that the bacterial population structure of rumen differed among the four groups. The predominant rumen bacterial phyla were found to be Bacteroidetes and Firmicutes, and the three dominant genera in all the samples across all treatments were Christensenellaceae R7 group, Rikenellaceae RC9 gut group, and Prevotella 1. The relative abundances of Prevotella 1, Rikenellaceae RC9 gut group, Ruminococcus 2, Lachnospiraceae XPB1014 group, Carnobacterium, and Hafnia-Obesumbacterium were found to differ significantly among the four treatment groups (P < 0.05). Moreover, Tax4fun metagenome estimation revealed that gene functions and metabolic pathways associated with carbohydrate and other amino acids were overexpressed in the rumen microbiota of SeY-supplemented sheep. To conclude, SeY significantly affects the abundance of rumen bacteria and ultimately affects the rumen microbial fermentation

LogLG: Weakly Supervised Log Anomaly Detection via Log-Event Graph Construction

Fully supervised log anomaly detection methods suffer the heavy burden of annotating massive unlabeled log data. Recently, many semi-supervised methods have been proposed to reduce annotation costs with the help of parsed templates. However, these methods consider each keyword independently, which disregards the correlation between keywords and the contextual relationships among log sequences. In this paper, we propose a novel weakly supervised log anomaly detection framework, named LogLG, to explore the semantic connections among keywords from sequences. Specifically, we design an end-to-end iterative process, where the keywords of unlabeled logs are first extracted to construct a log-event graph. Then, we build a subgraph annotator to generate pseudo labels for unlabeled log sequences. To ameliorate the annotation quality, we adopt a self-supervised task to pre-train a subgraph annotator. After that, a detection model is trained with the generated pseudo labels. Conditioned on the classification results, we re-extract the keywords from the log sequences and update the log-event graph for the next iteration. Experiments on five benchmarks validate the effectiveness of LogLG for detecting anomalies on unlabeled log data and demonstrate that LogLG, as the state-of-the-art weakly supervised method, achieves significant performance improvements compared to existing methods.Comment: 12 page

Cracks as Efficient Tools to Mitigate Flooding in Gas Diffusion Electrodes Used for the Electrochemical Reduction of Carbon Dioxide.

The advantage of employing gas diffusion electrodes (GDEs) in carbon dioxide reduction electrolyzers is that they allow CO2 to reach the catalyst in gaseous state, enabling current densities that are orders of magnitude larger than what is achievable in standard H-type cells. The gain in the reaction rate comes, however, at the cost of stability issues related to flooding that occurs when excess electrolyte permeates the micropores of the GDE, effectively blocking the access of CO2 to the catalyst. For electrolyzers operated with alkaline electrolytes, flooding leaves clear traces within the GDE in the form of precipitated potassium (hydrogen)carbonates. By analyzing the amount and distribution of precipitates, and by quantifying potassium salts transported through the GDE during operation (electrolyte perspiration), important information can be gained with regard to the extent and means of flooding. In this work, a novel combination of energy dispersive X-ray and inductively coupled plasma mass spectrometry based methods is employed to study flooding-related phenomena in GDEs differing in the abundance of cracks in the microporous layer. It is concluded that cracks play an important role in the electrolyte management of CO2 electrolyzers, and that electrolyte perspiration through cracks is paramount in avoiding flooding-related performance drops