Investigation of a Side-polished Fiber MZI and Its Sensing Performance

A novel all-fiber Mach–Zehnder interferometer (MZI), which consists of lateral core fusion splicing of a short section of side-polished single mode fiber (SMF) between two SMFs was proposed and demonstrated. A simple fiber side-polished platform was built to control the side polished depth through a microscope. The sensitivity of the fiber MZI structure to the surrounding refractive index (RI) can be greatly improved with the increase of the side-polished depth, but has no effect on the temperature sensitivity. The sensor with a polished depth of 44.2 μm measured RI sensitivity up to -118.0 nm/RIU (RI unit) in the RI range from 1.333 to 1.387, which agrees well with simulation results by using the beam propagation method (BPM). In addition, the fiber MZI structure also can achieve simultaneous measurement of both RI and temperature. These results show its potential for use in-line fiber type sensing application

Observer-based fault-tolerant control for a class of networked control systems with transfer delays

Abstract not availableZehui Mao, Bin Jiang, Peng Sh

i-Razor: A Differentiable Neural Input Razor for Feature Selection and Dimension Search in DNN-Based Recommender Systems

Input features play a crucial role in DNN-based recommender systems with thousands of categorical and continuous fields from users, items, contexts, and interactions. Noisy features and inappropriate embedding dimension assignments can deteriorate the performance of recommender systems and introduce unnecessary complexity in model training and online serving. Optimizing the input configuration of DNN models, including feature selection and embedding dimension assignment, has become one of the essential topics in feature engineering. However, in existing industrial practices, feature selection and dimension search are optimized sequentially, i.e., feature selection is performed first, followed by dimension search to determine the optimal dimension size for each selected feature. Such a sequential optimization mechanism increases training costs and risks generating suboptimal input configurations. To address this problem, we propose a differentiable neural input razor (i-Razor) that enables joint optimization of feature selection and dimension search. Concretely, we introduce an end-to-end differentiable model to learn the relative importance of different embedding regions of each feature. Furthermore, a flexible pruning algorithm is proposed to achieve feature filtering and dimension derivation simultaneously. Extensive experiments on two large-scale public datasets in the Click-Through-Rate (CTR) prediction task demonstrate the efficacy and superiority of i-Razor in balancing model complexity and performance.Comment: Accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE

Novel Microfiber Sensor and Its Biosensing Application for Detection of hCG Based on a Singlemode-Tapered Hollow Core-Singlemode Fiber Structure

A novel microfiber sensor is proposed and demonstrated based on a singlemode-tapered hollow core -singlemode (STHS) fiber structure. Experimentally a STHS with taper waist diameter of 26.5 μm has been fabricated and RI sensitivity of 816, 1601.86, and 4775.5 nm/RIU has been achieved with RI ranges from 1.3335 to 1.3395 , from 1.369 to 1.378, and from 1.409 to 1.4175 respectively, which agrees very well with simulated RI sensitivity of 885, 1517, and 4540 nm/RIU at RI ranges from 1.3335 to 1.337, from 1.37 to 1.374, and from 1.41 to 1.414 . The taper waist diameter has impact on both temperature and strain sensitivity of the sensor structure: (1) the smaller the waist diameter, the higher the temperature sensitivity, and experimentally 26.82 pm/°C has been achieved with a taper waist diameter of 21.4 μm; (2) as waist diameter decrease, strain sensitivity increase and 7.62 pm/με has been achieved with a taper diameter of 20.3 μm. The developed sensor was then functionalized for human chorionic gonadotropin (hCG) detection as an example for biosensing application. Experimentally for hCG concentration of 5 mIU/ml, the sensor has 0.5 nm wavelength shift, equivalent to limit of detection (LOD) of 0.6 mIU/ml by defining 3 times of the wavelength variation (0.06 nm) as measurement limit. The biosensor demonstrated relatively good reproducibility and specificity, which has potential for real medical diagnostics and other applications

Tetra­kis(μ-2,4-difluoro­benzoato)bis­[(2,4-difluoro­benzoato)(1,10-phenanthroline)gadolinium(III)]

In the title compound, [Gd2(C7H3F2O2)6(C12H8N2)2], the asymmetric unit comprises one Gd3+ cation chelated by two 2,4-difluoro­benzoate and one 1,10-phenanthroline ligands. Two cations are linked into a centrosymmetric dimer via three bridging carboxyl­ate groups of 2,4-difluoro­benzoate ligands. Each Gd3+ ion is nine-coordinated by seven O atoms and two N atoms

Human Microbe-Disease Association Prediction With Graph Regularized Non-Negative Matrix Factorization

A microbe is a microscopic organism which may exists in its single-celled form or in a colony of cells. In recent years, accumulating researchers have been engaged in the field of uncovering microbe-disease associations since microbes are found to be closely related to the prevention, diagnosis, and treatment of many complex human diseases. As an effective supplement to the traditional experiment, more and more computational models based on various algorithms have been proposed for microbe-disease association prediction to improve efficiency and cost savings. In this work, we developed a novel predictive model of Graph Regularized Non-negative Matrix Factorization for Human Microbe-Disease Association prediction (GRNMFHMDA). Initially, microbe similarity and disease similarity were constructed on the basis of the symptom-based disease similarity and Gaussian interaction profile kernel similarity for microbes and diseases. Subsequently, it is worth noting that we utilized a preprocessing step in which unknown microbe-disease pairs were assigned associated likelihood scores to avoid the possible negative impact on the prediction performance. Finally, we implemented a graph regularized non-negative matrix factorization framework to identify potential associations for all diseases simultaneously. To assess the performance of our model, cross validations including global leave-one-out cross validation (LOOCV) and local LOOCV were implemented. The AUCs of 0.8715 (global LOOCV) and 0.7898 (local LOOCV) proved the reliable performance of our computational model. In addition, we carried out two types of case studies on three different human diseases to further analyze the prediction performance of GRNMFHMDA, in which most of the top 10 predicted disease-related microbes were verified by database HMDAD or experimental literatures

microRNA-223 Deficiency Exacerbates Acute Inflammatory Response to Monosodium Urate Crystals by Targeting NLRP3

Objective: MicroRNAs were identified as master-switch molecules limiting acute inflammatory response. This study investigated the potential role of microRNA (miR)-223 in the mechanism of gout. Methods: Wild-type (WT) and miR-223 knock-out (KO) mice were used to evaluate the phenotypes of gout models. Inflammatory cytokines were measured in air pouch and peritoneal cavity lavage fluid. In addition to miR-223 level in gout patients, miR-223 and pro-inflammatory genes were examined in bone marrow-derived macrophages (BMDMs) from mice as well as peripheral blood mononuclear cells from healthy controls (HC) treated with monosodium urate (MSU) crystals in vitro. Results: MiR-223 was up-regulated in the early phase in BMDMs from WT mice after MSU challenge and decreased rapidly, and this was not observed in miR-223 KO mice in vitro. In addition, miR-223 was required for macrophages homeostasis. In comparison with WT mice in vivo, miR-223 deficiency exacerbated swelling index of MSU-induced inflammation in foot pad and ankle joint models. MiR-223 deficiency also markedly aggravated inflammatory cells infiltration and cytokines release including interleukin (IL)-1β, IL-6 and monocyte chemotactic protein-1 (MCP-1) in the air pouch and peritonitis models. In the in vitro experiments, miR-223 deficiency promoted the inflammatory response by targeting NLR family pyrin domain containing protein 3 (NLRP3). Besides, miR-223 level was down-regulated in gout patients and in HC exposed to MSU in vitro. Conclusion: MiR-223 was down-regulated in gout patients and miR-223 deficiency exacerbated inflammatory response in diverse murine models, suggesting that up-regulation of miR-223 could be a potential therapeutic strategy for alleviating gouty inflammation