Peculiar near-band-edge emission of polarization-dependent XEOL from a non-polar a-plane ZnO wafer.

Polarization-dependent hard X-ray excited optical luminescence (XEOL) was used to study not only the optical properties but also the crystallographic orientations of a non-polar a-plane ZnO wafer. In addition to a positive-edge jump and extra oscillations in the near-band-edge (NBE) XEOL yield, we observed a blue shift of the NBE emission peak that follows the polarization-dependent X-ray absorption near-edge structure (XANES) as the X-ray energy is tuned across the Zn K-edge. This NBE blue shift is caused by the larger X-ray absorption, generating higher free carriers to reduce the exciton-LO phonon coupling, which causes a decrease in the exciton activation energy. The extra oscillations in XANES and XEOL as the polarization is set parallel to the c-axis is attributed to simultaneous excitations of the Zn 4p - O 2pπ -bond along the c-axis and the bilayer σ-bond, whereas only the σ-bond is excited when the polarization is perpendicular to the c-axis. The polarization-dependent XEOL spectra can be used to determine the crystallographic orientations.

Multiple-site hemodynamic analysis of Doppler ultrasound with an adaptive color relation classifier for arteriovenous access occlusion evaluation.

This study proposes multiple-site hemodynamic analysis of Doppler ultrasound with an adaptive color relation classifier for arteriovenous access occlusion evaluation in routine examinations. The hemodynamic analysis is used to express the properties of blood flow through a vital access or a tube, using dimensionless numbers. An acoustic measurement is carried out to detect the peak-systolic and peak-diastolic velocities of blood flow from the arterial anastomosis sites (A) to the venous anastomosis sites (V). The ratio of the supracritical Reynolds (Re(supra)) number and the resistive (Res) index quantitates the degrees of stenosis (DOS) at multiple measurement sites. Then, an adaptive color relation classifier is designed as a nonlinear estimate model to survey the occlusion level in monthly examinations. For 30 long-term follow-up patients, the experimental results show the proposed screening model efficiently evaluates access occlusion.

Blood leakage detection during dialysis therapy based on fog computing with array photocell sensors and heteroassociative memory model.

Blood leakage and blood loss are serious life-threatening complications occurring during dialysis therapy. These events have been of concerns to both healthcare givers and patients. More than 40% of adult blood volume can be lost in just a few minutes, resulting in morbidities and mortality. The authors intend to propose the design of a warning tool for the detection of blood leakage/blood loss during dialysis therapy based on fog computing with an array of photocell sensors and heteroassociative memory (HAM) model. Photocell sensors are arranged in an array on a flexible substrate to detect blood leakage via the resistance changes with illumination in the visible spectrum of 500-700 nm. The HAM model is implemented to design a virtual alarm unit using electricity changes in an embedded system. The proposed warning tool can indicate the risk level in both end-sensing units and remote monitor devices via a wireless network and fog/cloud computing. The animal experimental results (pig blood) will demonstrate the feasibility.

Bilateral photoplethysmography for arterial steal detection in arteriovenous fistula using a fractional-order decision-making quantizer.

As inflow and outflow stenoses worsen, both flow resistance and pressure increase in the stenotic vascular access. During dialysis, when blood flow decreases, it may retrograde from the peripheral artery through the palmar arch to the arterial anastomosis site. Arterial steal syndrome (ASS) causes distal hypoperfusion, resulting in hand ischemia or extremity pain and edema. Hence, this study proposes the bilateral photoplethysmography (PPG) for ASS detection in arteriovenous fistulas. The decision-making quantizer utilizes the fractional-order feature extraction method and a non-cooperative game (NCG) framework to evaluate the ASS risk level. Bilateral asynchronous PPG signals have significant differences in the rise time and amplitude in relation to the degree of stenosis. The fractional-order self-synchronization error formulation is a feature extraction method used to quantify bilateral differences in blood flow changes between the dexter and sinister PPG signals. The NCG model as a method of decision-making is then employed to evaluate the ASS risk level. Using an acoustic Doppler measurement, the resistive (Res) index is also used to evaluate the vascular access stenosis at the arterial anastomosis site. In contrast with alternative methods including the high-sensitivity C-reactive protein level or Res index, our experimental results indicate that the proposed decision-making quantizer is more efficient in preventing ASS during hemodialysis treatment.

Peripheral arterial disease screening for hemodialysis patients using a fractional-order integrator and transition probability decision-making model.

Atherosclerosis and resultant peripheral arterial disease (PAD) are common complications in patients with type 2 diabetes mellitus or end-stage renal disease and in elderly patients. The prevalence of PAD is higher in patients receiving haemodialysis therapy. For early assessment of arterial occlusion using bilateral photoplethysmography (PPG), such as changes in pulse transit time and pulse shape, bilateral timing differences could be used to identify the risk level of PAD. Hence, the authors propose a discrete fractional-order integrator to calculate the bilateral area under the systolic peak (AUSP). These indices indicated the differences in both rise-timing and amplitudes of PPG signals. The dexter and sinister AUSP ratios were preliminarily used to separate the normal condition from low/high risk of PAD. Then, transition probability-based decision-making model was employed to evaluate the risk levels. The joint probability could be specified as a critical threshold, < 0.81, to identify the true positive for screening low or high risk level of PAD, referring to the patients' health records. In contrast to the bilateral timing differences and traditional methods, the proposed model showed better efficiency in PAD assessments and provided a promising strategy to be implemented in an embedded system.

Improved performance in differentiating benign from malignant sinonasal tumors using diffusion-weighted combined with dynamic contrast-enhanced magnetic resonance imaging.

BACKGROUND: Differentiating benign from malignant sinonsal lesions is essential for treatment planning as well as determining the patient's prognosis, but the differentiation is often difficult in clinical practice. The study aimed to determine whether the combination of diffusion-weighted (DW) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can improve the performance in differentiating benign from malignant sinonasal tumors. METHODS: This retrospective study included 197 consecutive patients with sinonasal tumors (116 malignant tumors and 81 benign tumors). All patients underwent both DW and DCE-MRI in a 3-T magnetic resonance scanner. Two different settings of b values (0,700 and 0,1000 s/mm 2 ) and two different strategies of region of interest (ROI) including whole slice (WS) and partial slice (PS) were used to calculate apparent diffusion coefficients (ADCs). A DW parameter with WS ADCs b0,1000 and two DCE-MRI parameters (time intensity curve [TIC] and time to peak enhancement [Tpeak]) were finally combined to use in differentiating the benign from the malignant tumors in this study. RESULTS: The mean ADCs of malignant sinonasal tumors (WS ADCs b0,1000 = 1.084 × 10-3 mm 2 /s) were significantly lower than those of benign tumors (WS ADCs b0,1000 = 1.617 × 10-3 mm 2 /s, P < 0.001). The accuracy using WS ADCs b0,1000 alone was 83.7% in differentiating the benign from the malignant tumors (85.3% sensitivity, 81.2% specificity, 86.4% positive predictive value [PPV], and 79.5% negative predictive value [NPV]). The accuracy using DCE with Tpeak and TIC alone was 72.1% (69.1% sensitivity, 74.1% specificity, 77.5% PPV, and 65.1% NPV). Using DW-MRI parameter was superior than using DCE parameters in differentiation between benign and malignant sinonasal tumors (P < 0.001). The accuracy was 87.3% (90.5% sensitivity, 82.7% specificity, 88.2% PPV, and 85.9% NPV) using DW-MRI combined with DCE-MRI, which was superior than that using DCE-MRI alone or using DW-MRI alone (both P < 0.001) in differentiating the benign from the malignant tumors. CONCLUSIONS: Diffusion-weighted combined with DCE-MRI can improve imaging performance in differentiating benign from malignant sinonasal tumors, which has the potential to improve diagnostic accuracy and to provide added value in the management for these tumors.

Bilateral photoplethysmography analysis for arteriovenous fistula dysfunction screening with fractional-order feature and cooperative game-based embedded detector.

The bilateral photoplethysmography (PPG) analysis for arteriovenous fistula (AVF) dysfunction screening with a fractional-order feature and a cooperative game (CG)-based embedded detector is proposed. The proposed detector uses a feature extraction method and a CG to evaluate the risk level for AVF dysfunction for patients undergoing haemodialysis treatment. A Sprott system is used to design a self-synchronisation error formulation to quantify the differences in the changes of blood volume for the sinister and dexter thumbs' PPG signals. Bilateral PPGs exhibit a significant difference in rise time and amplitude, which is proportional to the degree of stenosis. A less parameterised CG model is then used to evaluate the risk level. The proposed detector is also studied using an embedded system and bilateral optical measurements. The experimental results show that the risk of AVF stenosis during haemodialysis treatment is detected earlier.