Linear Displacement and Straightness Measurement by Fabry-Perot Interferometer Integrated with an Optoelectronic Module

This research develops a three degrees of freedom (DOF) measurement system by integrating Fabry-Perot interferometer and photoelectronic inspection module to determine linear displacement, horizontal and vertical straightness geometric error parameters simultaneously. The interferometer and the photoelectronic inspection module in a three DOF measurement system share the same light source, and the two structures are used to measure linear displacement and straightness errors. The experimental results are utilized to calculate the relevant error parameters according to ISO standards and numerical analysis. They show that after the machine error compensation, the positioning deviation of the system is reduced from 55 μm to 19 μm, corresponding to the reduction of 65%. The accuracy is promoted from 65 μm to 31 μm, about the improvement of 52%. The horizontal and vertical straightness errors of the machine are 4.30 μm and 5.71 μm respectively

The Relationship between Insulin Resistance and Type II Ketosis in Dairy Cows

Background: Cows in perinatal period are prone to ketosis, characterized by increased ketone bodies and decreased blood sugar. Study found that cows with type II ketosis had higher blood glucose levels. This type of ketosis exhibits insulin resistance and impaired glucose tolerance that are similar to type 2 diabetes. The purpose of this study was to investigate the role of insulin resistance(IR) in type II ketosis in dairy cows.Materials, Methods & Results: In one intensive cattle farm, eight cows with ketosis and eight healthy cows that were 14-21 days postpartum were selected. The plasma of experimental dairy cows was collected and tested for the concentration of glucose concentration. Glucose tolerance of blood glucose levels in 120 min was used as the cut-off point to divide the dairy cows into three groups: the abnormal glucose tolerance ketosis group (TH), the normal glucose tolerance ketosis (TL), and the healthy control group. Simultaneously, the indexes of plasma liver function, oxidative stress, and insulin resistance were detected. The results showed that after intravenous glucose injection, there was no significant difference in blood glucose concentration between the TL and control group, while the blood glucose levels in the TH group were always higher than in the other two groups. The insulin sensitivity index (RQUICKI) value was significantly lower in the TH group than in the other two groups. Liver function abnormalities in the TH group were more severe than in the TL and control group. Oxidative stress was higher in the TH group than in the TL and control groups.Discussion: Postpartum dairy cows, with high lactation, consume large amounts of sugar, resulting in a lower blood sugar, and the postnatal dry matter intake peak is later than the peak lactation, which further decreases blood sugar and leads to a negative energy balance in cows. Such ketosis is associated with NEB caused by hypoglycemia, However, a survey of blood glucose concentration in cows with ketosis shows that ketosis can still occur in cows with high blood sugar levels. The pathogenesis of hyperglycemic ketosis is still unclear. Insulin Resistance (IR) refers to tissue sensitivity to insulin decreases, compensatory Islet beta cells secreting insulin thus producing hyperinsulinemia. AST is a typical indicator of liver damage, plasma AST levels in Group TH were significantly higher than the other two groups.The RQUICKI is a key indicator determining whether the body has developed insulin resistance. the plasma insulin sensitivity index of group TH was significantly lower than Group TL and C. BHBA levels in serum is the gold standard for the diagnosis of cow ketosis.The concentration of NEFA and BHBA in the blood is a sign of negative energy balance. The concentration of BHBA and NEFA in the TH group was significantly higher than in the group C, and the concentration of BHBA was higher than the critical value of ketosis. SOD is a metal antioxidant enzyme and its level are key indicators in measuring the removal of oxidizing substances. T-AOC is a measuring indicator for total antioxidant function. The reduction of SOD and T-AOC concentrations in the TH group indicated that the antioxidant capacity of ketone cows with abnormal glucose tolerance was reduced. The above results show that the TH group is severely impaired in liver function, and has a disorder of glucose metabolism, abnormal glucose tolerance and hyperinsulinemi, which also have severe IR. Moreover, the antioxidant capacity of the TH cows with ketosis declined, the body was in a state of oxidative stress. Thus, the occurrence of ketosis in some cows is related to a glucose utilization disorder caused by insulin resistance, and abnormal liver function and oxidative stress are the causes of insulin resistance

Influence of electrode thermal conductivity on resistive switching behavior during reset process

Resistive random access memory (RRAM) is the most promising candidate for non-volatile memory (NVM) due to its extremely low operation voltage, extremely fast write/erase speed, and excellent scaling capability. However, an obstacle hindering mass production of RRAM is the non-uniform physical mechanism in its resistance switching process. This study examines the influence of different electrode thermal conductivity on switching behavior during the reset process. Electrical analysis methods and an analysis of current conduction mechanism indicate that better thermal conductivity in the electrode will require larger input power in order to induce more active oxygen ions to take part in the reset process. More active oxygen ions cause a more complete reaction during the reset process, and cause the effective switching gap (dsw) to become thicker. The effect of the electrode thermal conductivity and input power are explained by our model and clarified by electrical analysis methods. Please click Additional Files below to see the full abstract

A Bayesian Failure Prediction Network Based on Text Sequence Mining and Clustering

The purpose of this paper is to predict failures based on textual sequence data. The current failure prediction is mainly based on structured data. However, there are many unstructured data in aircraft maintenance. The failure mentioned here refers to failure types, such as transmitter failure and signal failure, which are classified by the clustering algorithm based on the failure text. For the failure text, this paper uses the natural language processing technology. Firstly, segmentation and the removal of stop words for Chinese failure text data is performed. The study applies the word2vec moving distance model to obtain the failure occurrence sequence for failure texts collected in a fixed period of time. According to the distance, a clustering algorithm is used to obtain a typical number of fault types. Secondly, the failure occurrence sequence is mined using sequence mining algorithms, such as-PrefixSpan. Finally, the above failure sequence is used to train the Bayesian failure network model. The final experimental results show that the Bayesian failure network has higher accuracy for failure prediction

Quasi-Hermitian extended SSH models

We consider the quasi Hermitian limit of a non-Hermitian extended Su Schrieffer Heeger model, in which the hopping amplitudes obey a specific relation so that the system may be mapped to a corresponding Hermitian one and its energy spectrum is completely real. Analogous to the Hermitian case, one may use the modified winding number to determine the total number of edge states on the boundaries to achieve a modified bulk-boundary correspondence. Due to the skin effect in nonHermitian systems, the spectral winding numbers must be used to classify such systems further. It dictates how the edge states would be distributed over the left and right boundaries. We then naively extend the criteria to the cases that the quasi Hermitian condition is violated. For all the cases that we consider, no inconsistency has been found.Comment: 21 pages, 10 figure

Autocrine, Not Paracrine, Interferon-Gamma Gene Delivery Enhances Ex Vivo Antigen-Specific Cytotoxic T Lymphocyte Stimulation and Killing

The adoptive transfer of antigen-specific cytotoxic T lymphocytes (CTL) shows promise in the treatment of cancer and infectious diseases. We utilize adeno-associated virus-(AAV-) based antigen gene-loaded dendritic cells (DCs) to stimulate such antigen-specific CTL. Yet further improvements in CTL stimulation and killing may result by gene delivery of various Th1-response interferons/cytokines, such as interferon γ (IFN-γ), as the delivered gene can continuously produce that interferon. However which immune cell type should optimally express IFN-γ is unclear as the phenotypes of both DC and T cells are enhanced by it. Here, we used AAV to compare and contrast IFN-γ gene delivery into DC or T cells, and versus the addition of exogenous IFN-γ, for stimulating carcinoembryonic antigen-(CEA-) specific CTL. It was found that AAV/IFN-γ delivery into T cells (autocrine) resulted in T cell populations with the highest CD8(+)/CD4(+) ratio, highest IFN-γ(+)/IL-4(+) ratio, highest CD69(+),CD8(+) levels, and lowest CD4(+)/CD25(+) levels, all consistent with the strongest Th1 response. Most importantly, AAV/IFN-γ transduction of T cells resulted in antigen-specific T cell populations with the highest killing capabilities, 49% above other treatments. These data strongly suggest that AAV/IFN-γ autocrine gene delivery into T cells is worthy of further study towards maximizing the generation of antigen-specific anticancer CTL killers

以數值方法探討卵礫石層的力學行為

Gravel formation involves the mixture of hard gravel and a soil matrix. Knowing the integrated mechanical characteristics of gravel formation is beneficial for engineering constructions and disaster prevention. This study adopts the software PFC2D, which is based on the discrete element method, to investigate the mechanical behavior of gravel formations. First, simulation is carried out through a biaxial test to adjust the micro parameters in PFC2D, and then multiple regression analysis is performed to establish the relationship between macro and micro parameters. Furthermore, with the reasonable micro parameters obtained, the particle size and content of gravel can changed to investigate how they influence mechanical behavior. The results show that the bigger particle size and the greater the content of gravel, the higher the values of shear strength, elastic modulus, Poisson’s ratio and friction angle, but the lower the value of cohesion. In other words, this kind of material has higher shear strength and stronger deformation resistance. These findings correspond with previous research results.卵礫石層是混合堅硬卵礫石與基質土壤之綜合體，了解卵礫石層整體力學性質，對工程建設與災害防治有極大幫助。本研究以台灣中部卵礫石層為對象，運用分離元素法為基礎之軟體PFC2D 探討卵礫石材料力學行為。首先進行雙軸試驗之模擬，校正PFC2D 微觀參數，接著利用複迴歸分析 (multiple regression model)建立宏觀參數與微觀參數間之關係。另外，以得到的合理微觀參數，改變卵礫石粒徑大小與含量，探討粒徑大小和含量對力學性質的影響。結果顯示當卵礫石粒徑越大與含量越多，其剪力強度、彈性模數、柏松比、摩擦角也會越大，但凝聚力略為下降。表示卵礫石粒徑大、含量高之材料，其抗剪強度大，變形性小，此結果與前人研究結果相符

Rikitake dynamo system, its circuit simulation and chaotic synchronization via quasi-sliding mode control

Rikitake dynamo system (1958) is a famous two-disk dynamo model that is capable of executing nonlinear chaotic oscillations similar to the chaotic oscillations as revealed by palaeomagnetic study. First, we detail the Rikitake dynamo system, its signal plots and important dynamic properties. Then a circuit design using Multisim is carried out for the Rikitake dynamo system. New synchronous quasi-sliding mode control (QSMC) for Rikitake chaotic system is studied in this paper. Furthermore, the selection on switching surface and the existence of QSMC scheme is also designed in this paper. The efficiency of the QSMC scheme is illustrated with MATLAB plots