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This paper investigates the performance of empirical Bayesian and E-Bayesian estimation of the bathtub-shaped distribution based on the progressive Type-II censored samples. These two estimations overcome the selection of hyperparameters in the Bayesian method. The empirical Bayesian analysis employs the classical approach to determine the hyperparameters. The E-Bayesian estimation uses the prior distribution of hyperparameters to derive the expectation of Bayesian estimates. The estimates of parameters are derived under the squared error loss and LINEX loss functions. The extensive simulations show the results of the empirical Bayesian estimates and the E-Bayesain estimates. Further, the empirical Bayesian estimation is also presented to analyze the parameters of bathtub-shaped distribution based on the general progressive Type-II censored samples. The two datasets from the electromechanical field and medical survival analysis are analyzed using the empirical Bayesian and E-Bayesian methods.

To achieve high-sensitive refractive index (RI) sensing, an Au/Ti3C2Tx-MXene hybrid layered D-shaped photonic crystal fiber (PCF) based on the surface plasmon resonance (SPR) sensor is proposed theoretically. The cladding of the D-shaped PCF has a hexagonal air-hole arrangement. In addition, the two air holes nearest to the metal layer in the first layer of cladding are reduced to enhance the plasma wave and provide an efficient leakage channel. The two air holes second nearest to the metal layer in the same layer are enlarged to limit the light scattering and guide more energy coupled with the surface plasmon polariton (SPP) mode. A thin layer of the Ti3C2Tx-MXene and Au film is applied on the surface of the D-shaped PCF to produce plasmon resonances across a wide range of wavelengths. By using the finite-element method, the optical properties of the proposed PCF-SPR sensor are investigated. The results of the numerical analysis show that this sensor has a significant SPR effect, and the resonance loss peaks can be formed at different positions in the wavelength range of 800–2020 nm. The average RI sensitivity reaches 48120 nm/refractive index unit (RIU), and the maximum sensitivity is up to 64600 nm/RIU in the RI range of 1.390–1.415. The RI sensitivity of the Au/Ti3C2Tx-MXene layered sensor is 2.36 times higher than the sensor with only the Au layer. The proposed structure has unique sensing properties, which can be effectively applied in bio-sensing fields.

Microdialysis (MD) is a versatile and powerful technique for chemical profiling of biological tissues and is widely used for quantification of neurotransmitters, neuropeptides, metabolites, biomarkers, and drugs in the central nervous system as well as in dermatology, ophthalmology, and pain research. However, MD performance is severely limited by fundamental tradeoffs between chemical sensitivity, spatial resolution, and temporal response. Here, by using wafer-scale silicon microfabrication, we develop and demonstrate a nanodialysis (ND) sampling probe that enables highly localized chemical sampling with 100 μm spatial resolution and subsecond temporal resolution at high recovery rates. These performance metrics, which are 100–1000× superior to existing MD approaches, are enabled by a 100× reduction of the microfluidic channel cross-section, a corresponding drastic 100× reduction of flow rates to exceedingly slow few nL/min flows, and integration of a nanometer-thin nanoporous membrane with high transport flux into the probe sampling area. Miniaturized ND probes may allow for the minimally invasive and highly localized sampling and chemical profiling in live biological tissues with high spatiotemporal resolution for clinical, biomedical, and pharmaceutical applications.

The development of new sensing platforms for the rapid, real-time, and onsite detection of metabolic compounds could provide significant opportunities for medical science, and healthcare applications. Microplates are standard tools that are widely used in cell biology, tissue engineering, or medical diagnosis. Here, we demonstrate for the first time the microplate-integrated amperometric biosensors for the rapid and sensitive detection of glucose and lactate. The sensor is constructed by printing carbon-graphite mediator paste as the working electrode, and Ag/AgCl paste as both reference and counter electrodes. The working electrode is then immobilized with glucose oxidase or lactate oxidase. The sensor shows a sensitive and rapid detection of glucose or lactate with a detection range from micromolar to millimolar and a short detection time of about 1 min. It is expected that the methodology can provide rapid, real-time, and onsite platforms for detecting a variety of metabolic compounds, and could provide new avenues for the fundamental studies and practical applications in cell biology, tissue engineering, or medical diagnosis.

A novel high birefringent polymer terahertz (THz) fiber with a suspended elliptical core is proposed in this paper. The introduction of an elliptical core can enhance asymmetry to realize high mode birefringence, and a large porous outer cladding effectively isolates the core-guided mode from interacting with the surrounding environment. A full-vector finite element method(FEM) is used to analyze the characteristics of the THz fiber. Simulation results show that the suspended elliptical fiber exhibits high mode birefringence on a level of $10^{-2}$ over a wide frequency range, and an extremely large mode birefringence(${\approx}0.06226$) is obtained when ellipticity is 0.2. Moreover, a suspended hollow elliptical core fiber is also discussed for the purpose of lower loss, however high mode birefringence and low relative absorption loss can not coexist in such a kind of fiber.

Collaborative representation-based detection (CRD) has been developed in hyperspectral anomaly detection tasks and testified to be very effective; however, heterogeneous pixels in the background may affect the accuracy of linear representation and make its performance suboptimal. To address this issue, a background purification framework based on linear representation is proposed, in which an automatic outlier removal strategy based on initial coefficients is designed to purify the background. In the proposed method, the classic least squares technique is firstly adopted to obtain preliminary linear representation coefficients, which are positively correlated with its contribution to a central testing pixel. Then, using statistical analysis of the representation coefficients, purified background pixels are obtained. Furthermore, a saliency weight is applied to fully utilize the spatial information of inner window pixels. Extensive experiments with three real hyperspectral datasets show that the proposed method outperforms state-of-the-art CRD and other traditional detectors.

While droplet microfluidics is becoming an effective tool for biomedical research, sensitive detection of droplet content is still challenging, especially for multiplexed analytes compartmentalized within ultrasmall droplets down to picoliter volumes. To enable such measurements, we demonstrate a silicon-based integrated microfluidic platform for multiplexed analysis of neurochemicals in picoliter droplets via nanoelectrospray ionization (nESI)-mass spectrometry (MS). An integrated silicon microfluidic chip comprising downscaled 7 μm-radius channels, a compact T-junction for droplet generation, and an integrated nESI emitter tip is used for segmentation of analytes into picoliter compartments and their efficient delivery for subsequent MS detection. The developed system demonstrates effective detection of multiple neurochemicals encapsulated within oil-isolated plugs down to low picoliter volumes. Quantitative measurements for each neurochemical demonstrate limits of detection at the attomole level. Such results are promising for applications involving label-free and small-volume detection for monitoring a range of brain chemicals.

Technology adoptions are not always rational. Adoption herding, the adoption that occurs because many others have made the adoption, often occurs due to various reasons (Li, 2004). Traditional rational choice theories cannot accommodate herding and other irrational behaviours associated with technology adoption. Based on imitation theory, this study proposes a model to examine irrational imitation factors underlying the adoption of internet banking (IB). Three imitation factors (frequency-based, outcome-based and trait-based) are incorporated into the model which is tested using survey data from 173 IB users. The results reveal that outcome-based and frequency-based imitations are significant determinants of IB adoption. This study pioneers an analysis of irrational imitations for technology acceptance, in particular the IB adoption, and provides valuable insights for bank managers. The findings suggest that IB adoption is subject to frequency-based and outcome-based imitation.

This study aims to examine how the quality of service alternatives influences Internet Banking (IB)customers' behaviours. Although the newly developed IB is a fast-growing channel, the traditional brick-and mortar face-to-face banking services are still pervasive. Therefore, it is important to understand how the quality of alternatives (traditional banking services) influences customers' behaviours. In the present study, we proposed that quality of alternatives dampens the perception of service quality, value, satisfaction and ultimately customer's intention of using IB. The model was tested using survey data from 156 individuals who were using IB. The results indicated that the quality of alternatives has both direct and indirect influences on IB customers' behaviours.

The development of new sensing platforms for the rapid, real-time, and onsite detection of metabolic compounds could provide significant opportunities for medical science, and healthcare applications. Microplates are standard tools that are widely used in cell biology, tissue engineering, or medical diagnosis. Here, we demonstrate for the first time the microplate-integrated amperometric biosensors for the rapid and sensitive detection of glucose and lactate. The sensor is constructed by printing carbon-graphite mediator paste as the working electrode, and Ag/AgCl paste as both reference and counter electrodes. The working electrode is then immobilized with glucose oxidase or lactate oxidase. The sensor shows a sensitive and rapid detection of glucose or lactate with a detection range from micromolar to millimolar and a short detection time of about 1 min. It is expected that the methodology can provide rapid, real-time, and onsite platforms for detecting a variety of metabolic compounds, and could provide new avenues for the fundamental studies and practical applications in cell biology, tissue engineering, or medical diagnosis.