Transmission performance of 90°-bend optical waveguides fabricated in fused silica by femtosecond laser inscription

The L-shape waveguide was written in fused silica using a femtosecond laser with beam shaping. The guiding structure supports good light turning; 0.88 dB/turn was achieved at the silica-air interface. By using the finite-different time-domain method, the turn loss due to the turning structure and refractive index of the L-shape waveguide has been simulated. The results show that the proposed method has unprecedented flexibility in fabricating a 90°-bend waveguide

Case report: A novel case of COVID-19 triggered tumefactive demyelinating lesions in one multiple sclerosis patient

The epidemic of COVID-19 is mainly manifested by respiratory symptoms caused by SARS-CoV-2 infection. Recently, reports of central nervous system diseases caused or aggravated by SARS-CoV-2 infection are also increasing. Thus, the COVID-19 pandemic poses an unprecedented challenge to the diagnosis and management of neurological disorders, especially to those diseases which have overlapping clinical and radiologic features with each other. In this study, a 31-year-old female patient had been diagnosed with relapsing–remitting multiple sclerosis (RRMS) initially and subsequently developed tumefactive demyelinating lesions (TDLs) following an infection with SARS-CoV-2. After immunotherapy (glucocorticoid pulses), a significant improvement was observed in her both clinical and radiological characteristics. The patient was started on disease-modifying therapy (DMT) with teriflunomide after cessation of oral glucocorticoids. Following two months of DMT treatment, the imaging follow-up revealed that the patient’s condition continued to deteriorate. This case was characterized by the transformation of a multiple sclerosis patient (MS) infected with SARS-CoV-2 into TDLs and the ineffectiveness of DMT treatment, which added complexity to its diagnosis and treatment. The case also gave us a hint that SARS-CoV-2 has a potential contributory role in inducing or exacerbating demyelinating diseases of the central nervous system that warrants further investigation

Experimental study and multi–objective optimization for drip irrigation of grapes in arid areas of northwest China

Grapes are the most important cash crop in Xinjiang. However, the effective utilization of agricultural water and fertilizer in this area is relatively low, which is very unfavourable for the development of Xinjiang grape industry. At present, there is a lack of research based on multi-objective water and fertilizer optimization to guide grape production. Field experiments were thus conducted over three consecutive years (2015–2017) to study the effects of water and fertilizer coupling on the yield, fruit quality, water use efficiency (WUE), fertilizer partial productivity (PFP), and net profits of Vitis vinifera cv. “Frey” grapes in northern Xinjiang. The optimum input range of water and fertilizer for multi-objective optimization were determined by using multiple regression and spatial analysis. Five levels of N–P2O5–K2O (180–225–495, 240–300–660, 300–375–825, 360–450–990, 420–525–1155 kg ha−1) were set up in the experiment, designated F60 %, F80 %, F100 %, F120 %, and F140 %, respectively. Three drip irrigation levels were designated W60 %, W80 %, W100 %, accounting for 60 %, 80 %, and 100 % of the ETc (where ETc denotes evapotranspiration under sufficient water supply for crops). The results show that at the same fertilization level, the leaf area index (LAI), vitamin C content, titratable acid, soluble solids content, dry matter yield, grape yield, PFP, and net profit increased with an increase in irrigation. They reached their maximum under full irrigation (W100 %). Compared to W80 % and W60 % irrigation levels, the WUE at a full (W100 %) irrigation was lower, but the PFP was the highest. The maximum grape bunch weight over three years was 407, 383, and 378 g, respectively. The highest harvest index (HI) was 0.460, 0.425, and 0.416, respectively. When the irrigation range was 334–348 mm and the N–P2O5–K2O fertilization range was 320–400–880∼392–490–1077 kg ha−1, the grape yield, net profit, WUE, vitamin C content, titratable acid content, and soluble solids content of the fruits reached more than 90 % of their maximum values simultaneously. The results of this research provide a scientific reference for water and fertilizer management of drip irrigation in Xinjiang vineyards.Grapes are the most important cash crop in Xinjiang. However, the effective utilization of agricultural water and fertilizer in this area is relatively low, which is very unfavourable for the development of Xinjiang grape industry. At present, there is a lack of research based on multi-objective water and fertilizer optimization to guide grape production. Field experiments were thus conducted over three consecutive years (2015–2017) to study the effects of water and fertilizer coupling on the yield, fruit quality, water use efficiency (WUE), fertilizer partial productivity (PFP), and net profits of Vitis vinifera cv. “Frey” grapes in northern Xinjiang. The optimum input range of water and fertilizer for multi-objective optimization were determined by using multiple regression and spatial analysis. Five levels of N–P2O5–K2O (180–225–495, 240–300–660, 300–375–825, 360–450–990, 420–525–1155 kg ha−1) were set up in the experiment, designated F60 %, F80 %, F100 %, F120 %, and F140 %, respectively. Three drip irrigation levels were designated W60 %, W80 %, W100 %, accounting for 60 %, 80 %, and 100 % of the ETc (where ETc denotes evapotranspiration under sufficient water supply for crops). The results show that at the same fertilization level, the leaf area index (LAI), vitamin C content, titratable acid, soluble solids content, dry matter yield, grape yield, PFP, and net profit increased with an increase in irrigation. They reached their maximum under full irrigation (W100 %). Compared to W80 % and W60 % irrigation levels, the WUE at a full (W100 %) irrigation was lower, but the PFP was the highest. The maximum grape bunch weight over three years was 407, 383, and 378 g, respectively. The highest harvest index (HI) was 0.460, 0.425, and 0.416, respectively. When the irrigation range was 334–348 mm and the N–P2O5–K2O fertilization range was 320–400–880∼392–490–1077 kg ha−1, the grape yield, net profit, WUE, vitamin C content, titratable acid content, and soluble solids content of the fruits reached more than 90 % of their maximum values simultaneously. The results of this research provide a scientific reference for water and fertilizer management of drip irrigation in Xinjiang vineyards

An open science resource for establishing reliability and reproducibility in functional connectomics

Efforts to identify meaningful functional imaging-based biomarkers are limited by the ability to reliably characterize inter-individual differences in human brain function. Although a growing number of connectomics-based measures are reported to have moderate to high test-retest reliability, the variability in data acquisition, experimental designs, and analytic methods precludes the ability to generalize results. The Consortium for Reliability and Reproducibility (CoRR) is working to address this challenge and establish test-retest reliability as a minimum standard for methods development in functional connectomics. Specifically, CoRR has aggregated 1,629 typical individuals’ resting state fMRI (rfMRI) data (5,093 rfMRI scans) from 18 international sites, and is openly sharing them via the International Data-sharing Neuroimaging Initiative (INDI). To allow researchers to generate various estimates of reliability and reproducibility, a variety of data acquisition procedures and experimental designs are included. Similarly, to enable users to assess the impact of commonly encountered artifacts (for example, motion) on characterizations of inter-individual variation, datasets of varying quality are included

A Low Power Digital Accumulation Technique for Digital-Domain CMOS TDI Image Sensor

In this paper, an accumulation technique suitable for digital domain CMOS time delay integration (TDI) image sensors is proposed to reduce power consumption without degrading the rate of imaging. In terms of the slight variations of quantization codes among different pixel exposures towards the same object, the pixel array is divided into two groups: one is for coarse quantization of high bits only, and the other one is for fine quantization of low bits. Then, the complete quantization codes are composed of both results from the coarse-and-fine quantization. The equivalent operation comparably reduces the total required bit numbers of the quantization. In the 0.18 µm CMOS process, two versions of 16-stage digital domain CMOS TDI image sensor chains based on a 10-bit successive approximate register (SAR) analog-to-digital converter (ADC), with and without the proposed technique, are designed. The simulation results show that the average power consumption of slices of the two versions are 6 . 47 × 10 - 8 J/line and 7 . 4 × 10 - 8 J/line, respectively. Meanwhile, the linearity of the two versions are 99.74% and 99.99%, respectively

The Analysis and Suppressing of Non-Uniformity in a High-Speed Spike-Based Image Sensor

In this paper, the non-ideal factors, which include spatial noise and temporal noise, are analyzed and suppressed in the high-speed spike-based image sensor, which combines the high-speed scanning sequential format with the method that uses the interspike time interval to indicate the scene information. In this imager, spatial noise contains device mismatch, which results in photo response non-uniformity (PRNU) and the non-uniformity of dark current. By multiplying the measured coefficient matrix the photo response non-uniformity is suppressed, and the non-uniformity of dark current is suppressed by correcting the interspike time interval based on the time interval of dark current. The temporal noise is composed of the shot noise and thermal noise. This kind of noise can be eliminated when using the spike frequency to restore the image. The experimental results show that, based on the spike frequency method, the standard deviation of the image decreases from 18.4792 to 0.5683 in the uniform bright light by using the calibration algorithm. While in the relatively uniform dark condition, the standard deviation decreases from 1.5812 to 0.4516. Based on interspike time interval method, because of time mismatch and temporal noise, the standard deviation of the image changes from 27.4252 to 27.4977 in the uniform bright light by using the calibration algorithm. While in the uniform dark condition, the standard deviation decreases from 2.361 to 0.3678

Hybrid Soft Computing Approach for Determining Water Quality Indicator: Euphrates River

Recent approaches toward solving the regression problems which are characterized by dynamic and nonlinear pattern such as machine learning modeling (including artificial intelligence (AI) approaches) have proven to be useful and successful tools for prediction. Approaches that integrate predictive model with optimization algorithm such as hybrid soft computing have resulted in the enhancement of the accuracy and preciseness of models during problem predictions. In this research, the implementation of hybrid evolutionary model based on integrated support vector regression (SVR) with firefly algorithm (FFA) was investigated for water quality indicator prediction. The monthly water quality indicator (WQI) that was used to test the hybrid model over a period of 10 years belongs to the Euphrates River, Iraq. The use of the WQI as an application for this research was stimulated based on the fact that WQI is usually calculated using a manual formulation which takes much time, efforts and occasionally may be associated with errors that were not intended during the subindex calculations. The parameters considered during the formulation of the prediction model were water quality parameters as input and WQI as output. The SVR model was used to verify the accuracy of the inspected SVR–FFA model. Different statistical metrics such as best fit of goodness and absolute error measures were used to evaluate the model. The performance of the hybrid model in recognizing the dynamic and nonlinear pattern characteristics was high and remarkable compared to the pure model. The SVR–FFA model was also demonstrated to be a good and robust soft computing technique toward the prediction of WQI. The proposed model enhanced the absolute error measurements (e.g., root mean square error and mean absolute error) over the SVR-based model by 42 and 58%, respectively

Effects of Ti and Cu Addition on Inclusion Modification and Corrosion Behavior in Simulated Coarse-Grained Heat-Affected Zone of Low-Alloy Steels

In this paper, the effects of Ti and Cu addition on inclusion modification and corrosion behavior in the simulated coarse-grained heat-affected zone (CGHAZ) of low-alloy steels were investigated by using in-situ scanning vibration electrode technique (SVET), scanning electron microscope/energy-dispersive X-ray spectroscopy (SEM/EDS), and electrochemical workstation. The results demonstrated that the complex inclusions formed in Cu-bearing steel were (Ti, Al, Mn)-Ox-MnS, which was similar to that in base steel. Hence, localized corrosion was initiated by the dissolution of MnS. However, the main inclusions in Ti-bearing steels were modified into TiN-Al2O3/TiN, and the localized corrosion was initiated by the dissolution of high deformation region at inclusion/matrix interface. With increased interface density of inclusions in steels, the corrosion rate increased in the following order: Base steel ≈ Cu-bearing steel < Ti-bearing steel. Owing to the existence of Cu-enriched rust layer, the Cu-bearing steel shows a similar corrosion resistance with base steel