Distributed Fusion Estimation for Multisensor Multirate Systems with Stochastic Observation Multiplicative Noises

This paper studies the fusion estimation problem of a class of multisensor multirate systems with observation multiplicative noises. The dynamic system is sampled uniformly. Sampling period of each sensor is uniform and the integer multiple of the state update period. Moreover, different sensors have the different sampling rates and observations of sensors are subject to the stochastic uncertainties of multiplicative noises. At first, local filters at the observation sampling points are obtained based on the observations of each sensor. Further, local estimators at the state update points are obtained by predictions of local filters at the observation sampling points. They have the reduced computational cost and a good real-time property. Then, the cross-covariance matrices between any two local estimators are derived at the state update points. At last, using the matrix weighted optimal fusion estimation algorithm in the linear minimum variance sense, the distributed optimal fusion estimator is obtained based on the local estimators and the cross-covariance matrices. An example shows the effectiveness of the proposed algorithms

Magnetic Field Sensor Based on a Combination of a Microfiber Coupler Covered with Magnetic Fluid and a Sagnac Loop

This paper proposes a novel magnetic field sensor based on a microfiber coupler (MFC) combined with a magnetic fluid (MF) in a Sagnac loop formed from a polarization maintaining fiber (PMF). Thanks to the small (~2.6μm) waist diameter of the MFC, the resulting interference is strongly influenced by the presence of the MF and this leads to the desirable high sensitivity of the structure to the applied magnetic field. The maximum magnetic field sensitivities of −100pm/mT and −488pm/mT have been experimentally demonstrated with the PMF lengths of 75cm and 20cm respectively in the range of magnetic field strengths from 0 to 200mT. The dependence of the magnetic field orientation on the performance of the proposed sensor was also examined. The proposed magnetic field sensor is advantageous for applications requiring higher sensitivity over a wide magnetic field range

Magnetic Field Sensor Based on a Tri-Microfiber Coupler Ring in Magnetic Fluid and a Fiber Bragg Grating

In this paper we propose and investigate a novel magnetic field sensor based on a Tri-microfiber coupler combined with magnetic fluid and a fiber Bragg grating (FBG) in a ring. A sensitivity of 1306 pm/mT was experimentally demonstrated in the range of magnetic fields from 0 to 15 mT. The reflection peak in the output spectrum associated with the FBG serves as a reference point allowing to avoid ambiguity in determining the spectral shift induced by the magnetic field. Due to its high sensitivity at low magnetic fields, the proposed structure could be of high interest in low field biosensing applications that involve a magnetic field, such as magnetic manipulation or separation of biomolecules

A Robust Hybrid Approach Based on Estimation of Distribution Algorithm and Support Vector Machine for Hunting Candidate Disease Genes

Microarray data are high dimension with high noise ratio and relatively small sample size, which makes it a challenge to use microarray data to identify candidate disease genes. Here, we have presented a hybrid method that combines estimation of distribution algorithm with support vector machine for selection of key feature genes. We have benchmarked the method using the microarray data of both diffuse B cell lymphoma and colon cancer to demonstrate its performance for identifying key features from the profile data of high-dimension gene expression. The method was compared with a probabilistic model based on genetic algorithm and another hybrid method based on both genetics algorithm and support vector machine. The results showed that the proposed method provides new computational strategy for hunting candidate disease genes from the profile data of disease gene expression. The selected candidate disease genes may help to improve the diagnosis and treatment for diseases

Magnetic Field Sensor Based on a Tri-microfiber Coupler Ring in Magnetic Fluid and a Fiber Bragg Grating

In this paper we propose and investigate a novel magnetic field sensor based on a Tri-microfiber coupler combined with magnetic fluid and a fiber Bragg grating (FBG) in a ring. A sensitivity of 1306 pm/mT was experimentally demonstrated in the range of magnetic fields from 0 to 15 mT. The reflection peak in the output spectrum associated with the FBG serves as a reference point allowing to avoid ambiguity in determining the spectral shift induced by the magnetic field. Due to its high sensitivity at low magnetic fields, the proposed structure could be of high interest in low field biosensing applications that involve a magnetic field, such as magnetic manipulation or separation of biomolecules

Transcriptome response of cassava leaves under natural shade

Cassava is an important staple crop in tropical and sub-tropical areas. As a common farming practice, cassava is usually cultivated intercropping with other crops and subjected to various degrees of shading, which causes reduced productivity. Herein, a comparative transcriptomic analysis was performed on a series of developmental cassava leaves under both full sunlight and natural shade conditions. Gene expression profiles of these two conditions exhibited similar developmental transitions, e.g. genes related to cell wall and basic cellular metabolism were highly expressed in immature leaves, genes involved in lipid metabolism and tetrapyrrole synthesis were highly expressed during the transition stages, and genes related to photosynthesis and carbohydrates metabolism were highly expressed in mature leaves. Compared with the control, shade significantly induced the expression of genes involved in light reaction of photosynthesis, light signaling and DNA synthesis/chromatin structure; however, the genes related to anthocyanins biosynthesis, heat shock, calvin cycle, glycolysis, TCA cycle, mitochondrial electron transport, and starch and sucrose metabolisms were dramatically depressed. Moreover, the shade also influenced the expression of hormone-related genes and transcriptional factors. The findings would improve our understanding of molecular mechanisms of shade response, and shed light on pathways associated with shade-avoidance syndrome for cassava improvement

Ancient geograpical barriers drive differentiation among Sonneratia caseolaris populations and recent divergence from S. Ianceolata

Glacial vicariance is thought to influence population dynamics and speciation of many marine organisms. Mangroves, a plant group inhabiting intertidal zones, were also profoundly influenced by Pleistocene glaciations. In this study, we investigated phylogeographic patterns of a widespread mangrove species Sonneratia caseolaris and a narrowly distributed, closely related species S. lanceolata to infer their divergence histories and related it to historical geological events. We sequenced two chloroplast fragments and five nuclear genes for one population of S. lanceolata and 12 populations of S. caseolaris across the Indo-West Pacific (IWP) region to evaluate genetic differentiation and divergence time among them. Phylogenetic analysis based on sequences of nuclear ribosomal internal transcribed spacer and a nuclear gene rpl9 for all Sonneratia species indicate that S. lanceolata individuals are nested within S. caseolaris. We found strong genetic structure among geographic regions (South China Sea, the Indian Ocean, and eastern Australia) inhabited by S. caseolaris. We estimated that divergence between the Indo-Malesia and Australasia populations occurred 4.035 million years ago (MYA), prior to the onset of Pleistocene. BARRIERS analysis suggested that complex geographic features in the IWP region had largely shaped the phylogeographic patterns of S. caseolaris. Furthermore, haplotype analyses provided convincing evidence for secondary contact of the South China Sea and the Indian Ocean lineages at the Indo-Pacific boundary. Demographic history inference under isolation and migration (IM) model detected substantial gene flow from the Sri Lanka populations to the populations in the Java Island. Moreover, multi-locus sequence analysis indicated that S. lanceolata was most closely related to the Indian Ocean populations of S. caseolaris and the divergence time between them was 2.057 MYA, coinciding with the onset of the Pleistocene glaciation. Our results suggest that geographic isolation driven by the Pleistocene ice age resulted in the recent origin of S. lanceolata

Enhancing the Visibility of Vernier Effect in a Tri-Microfiber Coupler Fiber Loop Interferometer for Ultrasensitive Refractive Index and Temperature sensing

In this paper a Vernier effect based sensor is analyzed and demonstrated experimentally in a tri-microfiber coupler (Tri-MFC) and polarization-maintaining fiber (PMF) loop interferometer (Tri-MFC-PMF) to provide ultrasensitive refractive index and temperature sensing. The main novelty of this work is an analysis of parameters of the proposed Tri-MFC-PMF with the objective of determining the conditions leading to a strong Vernier effect. It has been identified by simulation that the Vernier effect is a primary factor in the design of Tri-MFC-PMF loop sensing structure for sensitivity enhancement. It is furthermore demonstrated experimentally that enhancing the visibility of the Vernier spectrum in the Tri-MFC-PMF allows to achieve an ultrahigh refractive index and temperature sensitivity with improved measurement accuracy. Specifically it is shown that small values of the total phase difference (pi/16+Npi)~(pi/4+Npi), where N is an integer, accumulated over the PMF loop and Tri-MFC loop result in a strong Vernier effect. Experimentally an ultrahigh refractive index sensitivity of -20588 nm/RIU and temperature sensitivity of 0.019 nm/C are demonstrated by utilizing the stronger Vernier effect with clear Vernier spectrum. This analysis of the parameters may be useful to future researchers seeking to increase the measurement accuracy of sensors by enhancing the spectral visibility of the Vernier effect in other types of fiber optic interferometers

Transcriptome response of cassava leaves under natural shade

Cassava is an important staple crop in tropical and sub-tropical areas. As a common farming practice, cassava is usually cultivated intercropping with other crops and subjected to various degrees of shading, which causes reduced productivity. Herein, a comparative transcriptomic analysis was performed on a series of developmental cassava leaves under both full sunlight and natural shade conditions. Gene expression profiles of these two conditions exhibited similar developmental transitions, e.g. genes related to cell wall and basic cellular metabolism were highly expressed in immature leaves, genes involved in lipid metabolism and tetrapyrrole synthesis were highly expressed during the transition stages, and genes related to photosynthesis and carbohydrates metabolism were highly expressed in mature leaves. Compared with the control, shade significantly induced the expression of genes involved in light reaction of photosynthesis, light signaling and DNA synthesis/chromatin structure; however, the genes related to anthocyanins biosynthesis, heat shock, calvin cycle, glycolysis, TCA cycle, mitochondrial electron transport, and starch and sucrose metabolisms were dramatically depressed. Moreover, the shade also influenced the expression of hormone-related genes and transcriptional factors. The findings would improve our understanding of molecular mechanisms of shade response, and shed light on pathways associated with shade-avoidance syndrome for cassava improvement