A compact temperature sensor based on a fiber loop mirror (FLM) combined with an alcohol-filled high-birefringence photonic crystal fiber (PCF) is proposed and experimentally demonstrated. The output of the FLM is an interference spectrum with many resonant dips, of which the wavelengths are quite sensitive to the change of the refractive index of the filled alcohol for the interference of the FLM. Simulation analysis predicts a high temperature sensitivity, and experimental results show it reaches up to 6.6 nm/°C for the 6.1-cm-long PCF used in the FLM.

Using trimesic acid (TMA) as a model system by means of scanning tunneling microscope (STM) equipped with a temperature controller, here, we report a temperature-assisted method to cooperatively control electric-field-induced supramolecular phase transitions at the liquid/solid interface. Octanoic acid is used as a solvent due to its good solubility for TMA and its less complicated pattern formed under negative STM bias (e.g., only chicken-wire polymorphs existing). At positive substrate bias, STM revealed that TMA assembly based on temperature modulations underwent phase transitions from a porous (22 °C) to a flower (45 °C) and further to a zigzag (68 °C) structure. The transitions are ascribed to the partial deprotonation of the carboxyl groups of TMA. Both the temperature and electrical polarity of the substrate are crucial, i.e., the transitions only take place at positive substrate bias and elevated temperatures. Molecular mechanics simulations were carried out to calculate the temperature and electric field dependence of the adsorption enthalpy and free energy of the chicken-wire assembly of TMA on the two layers of graphene surface. The calculated decrease in adsorption enthalpy with the increase of temperature and electric field values that causes the TMA chicken-wire assembly to be less stable is proposed to promote the occurrence of the phase transition observed by STM. This study paves the way toward program-controlled supramolecular phase switching via the synergic effect of electrical and thermal stimuli.

A temperature-insensitive micro Fabry-Pérot (FP) cavity based on simplified hollow-core (SHC) photonic crystal fiber (PCF) is demonstrated. Such a device is fabricated by splicing a section of SHC PCF with single mode fibers at both cleaved ends. An extremely low temperature sensitivity of ∼0.273 pm∕°C is obtained between room temperature and 900°C. By drilling vertical micro-channels using a femtosecond laser, the micro FP cavity can be filled with liquids and functions as a sensitive refractometer and the refractive index sensitivity obtained is ∼851.3 nm∕RIU (refractive index unit), which indicates an ultra low temperature cross-sensitivity of ∼3. The FBG based RI sensor generally presents a low sensitivity on the order of ∼100 nm∕RIU (refractive index unit), and the FBG should be fabricated in an exposed-core fiber or a microfiber. It has been reported that LPFG can provide a sensitivity as high as 1500 nm∕RIU [3]. However, LPFG typically exhibits large temperature cross-sensitivity and nonlinear response to the surrounding RI. An ultra-high sensitivity, of up to 24; 373 nm∕RIU, is achieved by use of a highly birefringent microfiber loop [6]. By employing selective infiltration techniques of PCFs [7,12,13], embedded coupler, modal interferometer, and photonic band-gap structures can be fabricated, which exhibit even higher RI sensitivity such as 38;000 nm∕RIU [8]. However, such a sensor can only use the liquids with a RI higher than that of silica (∼1.46). To operate at around 1.33 of RI, a liquid-filled PCF sensor based on four-wave mixing has been demonstrated, with a high sensitivity of 8800 nm∕RIU, however, a large length of PCF (∼1 m) has to be used [11].A key issue that existed in the above mentioned configurations is temperature cross-sensitivity because it limits the sensor reliability. One of the solutions to this issue is the use of fiber-optical FP cavity as it exhibits very low temperature sensitivity of ∼1 pm∕°C, due to the small thermo-expansion coefficient of silica. Recently, the micro FP cavity has received increased research attention because of its low temperature cross-sensitivity, high RI and/or strain sensitivities, and convenient reflection mode of detection. The FP cavity fabricated by focused ion beam milling has been used to measure the RI around 1.30 with a high sensitivity of 1731 nm∕RIU [14] however; the temperature crosssensitivity of the device was not reported. By employing a femtosecond laser, micro FP cavity can be fabricated in single mode fiber (SMF) [15,16] and PCF [17], with a temperature sensitivity of larger than 2 pm∕°C, corresponding to a temperature cross-sensitivity of greater than 2 × 10 −6 RIU∕°C. By splicing a section of hollow-core PCF [18] or Er-doped fiber [19] with SMFs, strain sensors have been demonstrated, with further reduced temperature sensitivity of ∼0.81 and 0.65 pm∕°C, respectively.In this Letter, we demonstrate a micro FP cavity based on simplified hollow-core (SHC)-PCF for RI sensing with extremely low temperature cross-sensitivity. The device is ...

Mechanism and sensing applications of antiresonant reflecting guidance in an alcohol-filled simplified hollow-core (SHC) photonic crystal fiber (PCF) are demonstrated. By filling one air hole in the air cladding of the PCF with alcohol, anti-resonant reflecting guidance of light can be achieved and energy leakage of the core modes can be induced at resonant wavelengths of the Fabry-Pérot (F-P) resonator formed by the alcohol-filled layer combined with the silica cladding in the cross-section of the PCF. The proposed structure exhibits periodic lossy dips in the transmission spectrum, of which the visibilities are sensitive to the refractive index of surrounding medium due to the reflectivity variation of the F-P resonator. Water level sensing is experimentally realized with this principle and the lossy dip exhibits a linear decrease against water level with a sensitivity of 1.1 dB/mm. The sensor is also sensitive to environmental temperature and a temperature sensitivity of -0.48 nm/°C is obtained between room temperature and 60 °C.

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Background: Metagenomic sequencing is becoming a powerful technology for exploring micro-ogranisms from various environments, such as human body, without isolation and cultivation. Accurately identifying genes from metagenomic fragments is one of the most fundamental issues. Results: In this article, we present a novel gene prediction method named MetaGUN for metagenomic fragments based on a machine learning approach of SVM. It implements in a three-stage strategy to predict genes. Firstly, it classifies input fragments into phylogenetic groups by a k-mer based sequence binning method. Then, proteincoding sequences are identified for each group independently with SVM classifiers that integrate entropy density profiles (EDP) of codon usage, translation initiation site (TIS) scores and open reading frame (ORF) length as input patterns. Finally, the TISs are adjusted by employing a modified version of MetaTISA. To identify protein-coding sequences, MetaGun builds the universal module and the novel module. The former is based on a set of representative species, while the latter is designed to find potential functionary DNA sequences with conserved domains.

The C++ source code is freely available under the GNU GPL license via http://mech.ctb.pku.edu.cn/MetaTISA/.

BackgroundMetagenomic sequencing is becoming a powerful technology for exploring micro-ogranisms from various environments, such as human body, without isolation and cultivation. Accurately identifying genes from metagenomic fragments is one of the most fundamental issues.ResultsIn this article, we present a novel gene prediction method named MetaGUN for metagenomic fragments based on a machine learning approach of SVM. It implements in a three-stage strategy to predict genes. Firstly, it classifies input fragments into phylogenetic groups by a k-mer based sequence binning method. Then, protein-coding sequences are identified for each group independently with SVM classifiers that integrate entropy density profiles (EDP) of codon usage, translation initiation site (TIS) scores and open reading frame (ORF) length as input patterns. Finally, the TISs are adjusted by employing a modified version of MetaTISA. To identify protein-coding sequences, MetaGun builds the universal module and the novel module. The former is based on a set of representative species, while the latter is designed to find potential functionary DNA sequences with conserved domains.ConclusionsComparisons on artificial shotgun fragments with multiple current metagenomic gene finders show that MetaGUN predicts better results on both 3' and 5' ends of genes with fragments of various lengths. Especially, it makes the most reliable predictions among these methods. As an application, MetaGUN was used to predict genes for two samples of human gut microbiome. It identifies thousands of additional genes with significant evidences. Further analysis indicates that MetaGUN tends to predict more potential novel genes than other current metagenomic gene finders.