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High-dynamic-range (HDR) image reconstruction methods are designed to fuse multiple Low-dynamic-range (LDR) images captured with different exposure values into a single HDR image. Recent CNN-based methods mostly perform local attention- or alignment-based fusion of multiple LDR images to create HDR contents. [https://www.selleckchem.com/ selleck chemicals] Depending on a single attention mechanism or alignment causes failure in compensating ghosting artifacts, which can arise in the synthesized HDR images due to the motion of objects or camera movement across different LDR image inputs. In this study, we propose a multi-scale attention-guided non-local network called MSANLnet for efficient HDR image reconstruction. To mitigate the ghosting artifacts, the proposed MSANLnet performs implicit alignment of LDR image features with multi-scale spatial attention modules and then reconstructs pixel intensity values using long-range dependencies through non-local means-based fusion. These modules adaptively select useful information that is not damaged by an object's movement or unfavorable lighting conditions for image pixel fusion. Quantitative evaluations against several current state-of-the-art methods show that the proposed approach achieves higher performance than the existing methods. Moreover, comparative visual results show the effectiveness of the proposed method in restoring saturated information from original input images and mitigating ghosting artifacts caused by large movement of objects. Ablation studies show the effectiveness of the proposed method, architectural choices, and modules for efficient HDR reconstruction.The aim was to analyze the reliability and validity of a low-cost instrument, based on a radar system, to quantify the kicking ball speed in soccer. A group of 153 male soccer players (under-13, n = 53; under-15, n = 54; under-18, n = 46) participated in this study. Each player performed three kicks on the goal in a standardized condition while the ball speed was measured with three different devices one Radar Stalker ATS II® (reference criterion) and two Supido Radar® (Supido-front of the goal and Supido-back of the goal). The standard error of measurement (SEM) expressed as a coefficient of variation (CV) and the intraclass correlation coefficient (ICC) were employed for assessing the reliability of each instrument. Stalker and Supido-back showed very high absolute (CV = 4.0-5.4%) and relative (ICC = 0.945-0.958) reliability, whereas Supido-front resulted in moderate to low reliability scores (CV = 7.4-15%, ICC = 0.134-0.693). In addition, Lin's concordance correlation coefficient (CCC) values revealed an 'almost perfect' agreement between Stalker and Supido-back for the average (r = 0.99) and maximal (r = 0.98) ball speed, regardless of the ball speed range analyzed. However, Supido-front resulted in a poor degree of concordance (CCC = 0.688) and a high magnitude of error (17.0-37.5 km·h-1) with the reference Stalker radar gun. The Supido Radar® placed behind the goal could be considered a reliable and valid device for measuring ball speed in soccer.To improve the detection sensitivity of a porous silicon optical biosensor in the real-time detection of biomolecules, a non-spectral porous silicon optical biosensor technology, based on dual-signal light detection, is proposed. Double-light detection is a combination of refractive index change detection and fluorescence change detection. It uses quantum dots to label probe molecules to detect target molecules. In the double-signal-light detection method, the first detection-signal light is the detection light that is reflected from the surface of the porous silicon Bragg mirror. The wavelength of the detection light is the same as the wavelength of the photonic band gap edge of the porous silicon Bragg mirror. CdSe/ZnS quantum dots are used to label the probe DNA and hybridize it with the target DNA molecules in the pores of porous silicon to improve its effective refractive index and enhance the detection-reflection light. The second detection-signal light is fluorescence, which is generated by the quantum dots in the reactant that are excited by light of a certain wavelength. The Bragg mirror structure further enhances the fluorescence signal. A digital microscope is used to simultaneously receive the digital image of two kinds of signal light superimposed on the surface of porous silicon, and the corresponding algorithm is used to calculate the change in the average grey value before and after the hybridization reaction to calculate the concentration of the DNA molecules. The detection limit of the DNA molecules was 0.42 pM. This method can not only detect target DNA by hybridization, but also detect antigen by immune reaction or parallel biochip detection for a porous silicon biosensor.Cardiac monitoring based on wearable photoplethysmography (PPG) is widespread because of its usability and low cost. Unfortunately, PPG is negatively affected by various types of disruptions, which could introduce errors to the algorithm that extracts pulse rate variability (PRV). This study aims to identify the nature of such artifacts caused by various types of factors under the conditions of precisely planned experiments. We also propose methods for their reduction based solely on the PPG signal while preserving the frequency content of PRV. The accuracy of PRV derived from PPG was compared to heart rate variability (HRV) derived from the accompanying ECG. The results indicate that filtering PPG signals using the discrete wavelet transform and its inverse (DWT/IDWT) is suitable for removing slow components and high-frequency noise. Moreover, the main benefit of amplitude demodulation is better preparation of the PPG to determine the duration of pulse cycles and reduce the impact of some other artifacts. Post-processing applied to HRV and PRV indicates that the correction of outliers based on local statistical measures of signals and the autoregressive (AR) model is only important when the PPG is of low quality and has no effect under good signal quality. The main conclusion is that the DWT/IDWT, followed by amplitude demodulation, enables the proper preparation of the PPG signal for the subsequent use of PRV extraction algorithms, particularly at rest. However, post-processing in the proposed form should be applied more in the situations of observed strong artifacts than in motionless laboratory experiments.The adverse health effects of the presence of lead in wastewater streams are well documented, with conventional methods of lead recovery and removal suffering from disadvantages such as high energy costs, the production of toxic sludge, and low lead selectivity. Klebsiella pneumoniae and Paraclostridium bifermentans have been identified as potential lead-precipitating species for use in a lead recovery bioreactor. Electrical impedance spectroscopy (EIS) on a low-cost device is used to determine the potential for the probe-free and label-free monitoring of cell growth in a bioreactor containing these bacteria. A complex polynomial is fit for several reactive equivalent circuit components. A direct correlation is found between the extracted supercapacitance and the plated colony-forming unit count during the exponential growth phase, and a qualitative correlation is found between all elements of the measured reactance outside the exponential growth phase. Strong evidence is found that Pb(II) ions act as an anaerobic respiration co-substrate for both cells observed, with changes in plated count qualitatively mirrored in the Pb(II) concentration. Guidance is given on the implementation of EIS devices for continuous impedance monitoring.In this study, thin films composed of gold nanoparticles embedded in a copper oxide matrix (AuCuO), manifesting Localized Surface Plasmon Resonance (LSPR) behavior, were produced by reactive DC magnetron sputtering and post-deposition in-air annealing. The effect of low-power Ar plasma etching on the surface properties of the plasmonic thin films was studied, envisaging its optimization as gas sensors. Thus, this work pretends to attain the maximum sensing response of the thin film system and to demonstrate its potential as a gas sensor. The results show that as Ar plasma treatment time increases, the host CuO matrix is etched while Au nanoparticles are uncovered, which leads to an enhancement of the sensitivity until a certain limit. Above such a time limit for plasma treatment, the CuO bonds are broken, and oxygen is removed from the film's surface, resulting in a decrease in the gas sensing capabilities. Hence, the importance of the host matrix for the design of the LSPR sensor is also demonstrated. CuO not only provides stability and protection to the Au NPs but also promotes interactions between the thin film's surface and the tested gases, thereby improving the nanocomposite film's sensitivity. The optimized sensor sensitivity was estimated at 849 nm/RIU, which demonstrates that the Au-CuO thin films have the potential to be used as an LSPR platform for gas sensors.A protocol for successfully depositing [001] textured, 2-3 µm thick films of Al0.75Sc0.25N, is proposed. The procedure relies on the fact that sputtered Ti is [001]-textured α-phase (hcp). Diffusion of nitrogen ions into the α-Ti film during reactive sputtering of Al0.75,Sc0.25N likely forms a [111]-oriented TiN intermediate layer. The lattice mismatch of this very thin film with Al0.75Sc0.25N is ~3.7%, providing excellent conditions for epitaxial growth. In contrast to earlier reports, the Al0.75Sc0.25N films prepared in the current study are Al-terminated. Low growth stress (&lt;100 MPa) allows films up to 3 µm thick to be deposited without loss of orientation or decrease in piezoelectric coefficient. An advantage of the proposed technique is that it is compatible with a variety of substrates commonly used for actuators or MEMS, as demonstrated here for both Si wafers and D263 borosilicate glass. Additionally, thicker films can potentially lead to increased piezoelectric stress/strain by supporting application of higher voltage, but without increase in the magnitude of the electric field.In high-temperature environments, the signal-to-noise ratio (SNR) of the signal measured by electromagnetic acoustic transducers (EMAT) is low, and the signal characteristics are difficult to extract, which greatly affects their application in practical industry. Aiming at this problem, this paper proposes the least mean square adaptive filtering interpolation denoising method based on variational modal decomposition (AFIV). Firstly, the high-temperature EMAT signal was decomposed by variational modal decomposition (VMD). Then the high-frequency and low-frequency noises in the signal were filtered according to the excitation center frequency. Following the wavelet threshold denoising (WTD) for the noise component after VMD decomposition was carried out. Afterward, the noise component and signal component were connected by an adaptive filtering process to achieve further noise reduction. Finally, cubic spline interpolation was used to smooth the noise reduction curve and obtain the time information. To verify the effectiveness of the proposed method, it was applied to two kinds of ultrasonic signals from 25 to 700 °C. Compared with VMD, WTD, and empirical mode decomposition denoising, the SNR was increased by 2 times. The results show that this method can better extract the effective information of echo signals and realize the online thickness measurement at high temperature.