Sustainable versatile chitin aerogels: facile synthesis, structural control and high-efficiency acoustic absorption.

Bio-based materials with excellent acoustic absorption properties are in great demand in architecture, interior, and human settlement applications for efficient noise control. In this study, crayfish shells, a form of kitchen waste, are utilized as the primary material to produce ultralight and multifunctional chitin aerogels, which effectively eliminate noise. Different replacement solvents and freezing rates were employed to regulate the porous structures of chitin aerogels, and their resulting acoustic absorption performance was investigated. Results demonstrate that employing deionized water as the replacement solvent and utilizing a common-freeze mode (frozen via refrigerator at -26 °C) can produce chitin aerogels with larger porosity (96.26%) and apertures, as well as thicker pore walls. This results in superior broadband acoustic absorption performance (with a maximum absorption coefficient reaching 0.99) and higher Young's modulus (28 kPa). Conversely, chitin aerogels solvent-exchanged with tert-butyl alcohol or subjected to quick-freeze mode (frozen via liquid nitrogen) exhibit smaller porosity (92.32% and 94.84%) and apertures, thereby possessing stronger diffuse reflection of visible light (average reflectance of 94.30% and 88.18%), and enhanced low-frequency (500 to 1600 Hz) acoustic absorption properties. Additionally, the acoustic absorption mechanism of fabricated chitin aerogels was predicted using a simple three-parameter analysis Johnson-Champoux-Allard-Lafarge (JCAL) model. This study presents a novel approach to developing multifunctional biomass materials with excellent acoustic absorption properties, which could have a wide range of potential applications.

Visual Strain Sensors Based on Fabry-Perot Structures for Structural Integrity Monitoring.

Strain sensors that can rapidly and efficiently detect strain distribution and magnitude are crucial for structural health monitoring and human-computer interactions. However, traditional electrical and optical strain sensors make access to structural health information challenging because data conversion is required, and they have intricate, delicate designs. Drawing inspiration from the moisture-responsive coloration of beetle wing sheaths, we propose using Ecoflex as a flexible substrate. This substrate is coated with a Fabry-Perot (F-P) optical structure, comprising a "reflective layer/stretchable interference cavity/reflective layer", creating a dynamic color-changing visual strain sensor. Upon the application of external stress, the flexible interference chamber of the sensor stretches and contracts, prompting a blue-shift in the structural reflection curve and displaying varying colors that correlate with the applied strain. The innovative flexible sensor can be attached to complex-shaped components, enabling the visual detection of structural integrity. This biomimetic visual strain sensor holds significant promise for real-time structural health monitoring applications.

Adversarial Robustness Enhancement for Deep Learning-Based Soft Sensors: An Adversarial Training Strategy Using Historical Gradients and Domain Adaptation.

Despite their high prediction accuracy, deep learning-based soft sensor (DLSS) models face challenges related to adversarial robustness against malicious adversarial attacks, which hinder their widespread deployment and safe application. Although adversarial training is the primary method for enhancing adversarial robustness, existing adversarial-training-based defense methods often struggle with accurately estimating transfer gradients and avoiding adversarial robust overfitting. To address these issues, we propose a novel adversarial training approach, namely domain-adaptive adversarial training (DAAT). DAAT comprises two stages: historical gradient-based adversarial attack (HGAA) and domain-adaptive training. In the first stage, HGAA incorporates historical gradient information into the iterative process of generating adversarial samples. It considers gradient similarity between iterative steps to stabilize the updating direction, resulting in improved transfer gradient estimation and stronger adversarial samples. In the second stage, a soft sensor domain-adaptive training model is developed to learn common features from adversarial and original samples through domain-adaptive training, thereby avoiding excessive leaning toward either side and enhancing the adversarial robustness of DLSS without robust overfitting. To demonstrate the effectiveness of DAAT, a DLSS model for crystal quality variables in silicon single-crystal growth manufacturing processes is used as a case study. Through DAAT, the DLSS achieves a balance between defense against adversarial samples and prediction accuracy on normal samples to some extent, offering an effective approach for enhancing the adversarial robustness of DLSS.

Construction of Prediction Model of Foodborne Disease Outbreaks and Its Trend Prediction - Guizhou Province, China, 2023-2025.

Objective: Foodborne diseases pose a significant public health concern globally. This study aims to analyze the correlation between disease prevalence and climatic conditions, forecast the pattern of foodborne disease outbreaks, and offer insights for effective prevention and control strategies and optimizing health resource allocation policies in Guizhou Province. Methods: This study utilized the χ2 test and four comprehensive prediction models to analyze foodborne disease outbreaks recorded in the Guizhou Foodborne Disease Outbreak system between 2012 and 2022. The best-performing model was chosen to forecast the trend of foodborne disease outbreaks in Guizhou Province, 2023-2025. Results: Significant variations were observed in the incidence of foodborne disease outbreaks in Guizhou Province concerning various meteorological factors (all P≤0.05). Among all models, the SARIMA-ARIMAX combined model demonstrated the most accurate predictive performance (RMSE: Prophet model=67.645, SARIMA model=3.953, ARIMAX model=26.544, SARIMA-ARIMAX model=26.196; MAPE: Prophet model=42.357%, SARIMA model=37.740%, ARIMAX model=15.289%, SARIMA-ARIMAX model=13.961%). Conclusion: The analysis indicates that foodborne disease outbreaks in Guizhou Province demonstrate distinct seasonal patterns. It is recommended to concentrate prevention efforts during peak periods. The SARIMA-ARIMAX hybrid model enhances the precision of monthly forecasts for foodborne disease outbreaks, offering valuable insights for future prevention and control strategies.

Effects of Freeze-Drying Processes on the Acoustic Absorption Performance of Sustainable Cellulose Nanocrystal Aerogels.

Cellulose aerogels have great prospects for noise reduction applications due to their sustainable value and superior 3D interconnected porous structures. The drying principle is a crucial factor in the preparation process for developing high-performance aerogels, particularly with respect to achieving high acoustic absorption properties. In this study, multifunctional cellulose nanocrystal (CNC) aerogels were conveniently prepared using two distinct freeze-drying principles: refrigerator conventional freezing (RCF) and liquid nitrogen unidirectional freezing (LnUF). The results indicate that the rapid RCF process resulted in a denser CNC aerogel structure with disordered larger pores, causing a stronger compressive performance (Young's modulus of 40 kPa). On the contrary, the LnUF process constructed ordered structures of CNC aerogels with a lower bulk density (0.03 g/cm3) and smaller apertures, resulting in better thermal stability, higher diffuse reflection across visible light, and especially increased acoustic absorption performance at low-mid frequencies (600-3000 Hz). Moreover, the dissipation mechanism of sound energy in the fabricated CNC aerogels is predicted by a designed porous media model. This work not only paves the way for optimizing the performance of aerogels through structure control, but also provides a new perspective for developing sustainable and efficient acoustic absorptive materials for a wide range of applications.

Flexible Strain Sensors Based on Bionic Parallel Vein-like Structures for Human Motion Monitoring.

In recent years, strain sensors have penetrated various fields. The capability of sensors to convert physical signals into electrical signals is of great importance in healthcare. However, it is still challenging to obtain sensors with high sensitivity, large operating range and low cost. In this paper, a stretchable strain sensor made of a double-layer conductive network, including a biomimetic multilayer graphene-Ecoflex (MLG-Ecoflex) substrate and a multilayer graphene-carbon nanotube (MLG-CNT) composite up-layer was developed. The combined action of the two layers led to an excellent performance with an operating range of up to 580% as well as a high sensitivity (gauge factor (GFmax) of 1517.94). In addition, a pressure sensor was further designed using the bionic vein-like structure with a multi-layer stacking of MLG-Ecoflex/MLG-CNT/MLG-Ecoflex to obtain a relatively high deformation along the direction of thickness. The device presented a high sensing performance (up to a sensitivity of 0.344 kPa-1) capable of monitoring small movements of the human body such as vocalizations and gestures. The good performance of the sensors together with a simple fabrication procedure (flip-molding) make it of potential use for some applications, for example human health monitoring and other areas of human interaction.

Surface-Ligand Tuned Reversible Transformations in Aqueous Environments Between CdSe Magic-Size Clusters and Their Precursor Compounds.

That magic-size clusters (MSCs) have their counterpart precursor compounds (PCs) has not been generally accepted by expertise circles. Here, experimental evidence to support this new concept is presented. With aqueous-phase CdSe MSCs as a model system, it is shown that when the MSCs are dispersed in water containing a certain amount of L-cysteine (Cys), the MSCs disappear slowly. Upon the addition of CdCl2 , the MSCs recover. It is proposed that after dispersing, the MSCs transform to their quasi-isomeric, non-absorbing PCs upon Cys addition. In the presence of CdCl2 , the PCs transform back to the MSCs due to Cys elimination. The surface ligand Cys of the MSCs plays a significant role in the reversible transformations. The present study provides compelling evidence that absorbing MSCs have their non-absorbing PCs. The study findings suggest that the transformation between two MSCs that display absorption spectral shifts in a stepwise pattern is assisted by their PCs.

Mushroom poisoning outbreaks in Guizhou Province, China: a prediction study using SARIMA and Prophet models.

Mushroom poisoning is a public health concern worldwide that not only harms the physical and mental health of those who are poisoned but also increases the medical and financial burden on families and society. The present study aimed to describe and analyze the current situations and factors influencing mushroom poisoning outbreaks in Guizhou province, Southwest China, between January 2012 and June 2022, and to predict the future trends of its occurrence. Our study provides a basis for the rational formulation of prevention and control and medical resource allocation policies for mushroom poisoning. The epidemiological characteristics and factors influencing mushroom poisoning incidence were analyzed using descriptive epidemiological methods and the chi-squared test, respectively. Then, future occurrence trends were predicted using the SARIMA and Prophet models. In total, 1577 mushroom poisoning incidents were recorded in Guizhou Province, with 7347 exposures, 5497 cases, 3654 hospitalizations, and 93 fatalities. The mortality rate was 4.45% in 1 ~ 6 years higher than other age groups. There were notable geographic and seasonal characteristics, with the number of occurrences much higher in rural areas (1198) than in cities (379), and poisoning cases were more common during the rainy season (June to September). The mortality rate of household poisoning cases was 1.86%, with the most deaths occurring in households. Statistically significant differences were observed in the incidence across various cities, periods, and poisoning locations (P < 0.05). Both models had advantages and disadvantages for prediction. Nevertheless, the SARIMA model had better overall prediction results than the Prophet model (R > 0.9, the residual plot of the prediction results was randomly distributed, and RMSESARIMA < RMSEProphet). However, the prediction result plot of the Prophet model was more explanatory than the SARIMA model and could visualize overall and seasonal trends. Both models predicted that the prevalence of mushroom poisoning would continue to increase in the future; however, the number of fatalities is generally declining. Seasonal patterns indicated that a high number of deaths from gooseberry mushroom poisoning occurred in October. The epidemiological trends of mushroom poisoning remain severe, and health education on related knowledge must be strengthened in rural areas, with June to October as the key prevention and control phase. Further, medical treatment of mushroom poisoning cases with clinical symptoms should pay attention to inquiries to check whether the mushroom is similar in appearance to the Amanita, particularly in October.

Assessment of visual function in blind mice and monkeys with subretinally implanted nanowire arrays as artificial photoreceptors.

Retinal prostheses could restore image-forming vision in conditions of photoreceptor degeneration. However, contrast sensitivity and visual acuity are often insufficient. Here we report the performance, in mice and monkeys with induced photoreceptor degeneration, of subretinally implanted gold-nanoparticle-coated titania nanowire arrays providing a spatial resolution of 77.5 µm and a temporal resolution of 3.92 Hz in ex vivo retinas (as determined by patch-clamp recording of retinal ganglion cells). In blind mice, the arrays allowed for the detection of drifting gratings and flashing objects at light-intensity thresholds of 15.70-18.09 µW mm-2, and offered visual acuities of 0.3-0.4 cycles per degree, as determined by recordings of visually evoked potentials and optomotor-response tests. In monkeys, the arrays were stable for 54 weeks, allowed for the detection of a 10-µW mm-2 beam of light (0.5° in beam angle) in visually guided saccade experiments, and induced plastic changes in the primary visual cortex, as indicated by long-term in vivo calcium imaging. Nanomaterials as artificial photoreceptors may ameliorate visual deficits in patients with photoreceptor degeneration.

Acceptance of COVID-19 boosters among hypertensive patients in China: A multicenter cross-sectional study.

Hypertension, a prevalent chronic disease, has been associated with increased COVID-19 severity. To promote the COVID-19 booster vaccination of hypertensive patients, this study investigated the willingness to receive boosters and the related influencing factors based on the health belief model (HBM model). Between June and October 2022, 453 valid questionnaires were collected across three Chinese cities. The willingness to receive a booster vaccination was 72.2%. The main factors that influenced the willingness of patients with hypertension to receive a booster shot were male (χ2 = 7.008, p = .008), residence in rural (χ2 = 4.778, p = .029), being in employment (χ2 = 7.232, p = .007), taking no or less antihypertensive medication (χ2 = 9.372, p = .025), with less hypertension-related comorbidities (χ2 = 35.888, p < .0001), and did not have any other chronic diseases (χ2 = 28.476, p < .0001). Amid the evolving COVID-19 landscape, the willingness to receive annual booster vaccination was 59.4%, and employment status (χ2 = 10.058, p = .002), and presence of other chronic diseases (χ2 = 14.256, p < .0001) are associated with the willingness of annual booster vaccination. Respondents with higher perceived severity, perceived benefits, perceived self-efficacy, and lower perceived barriers were more willing to receive booster shots. The mean and median value of willingness to pay (WTP) for a dose of booster were 53.17 CNY and 28.31 CNY. Concerns regarding booster safety and the need for professional advice were prevalent. Our findings highlight the importance of promoting booster safety knowledge and health-related management among hypertensive individuals through professional organizations and medical specialists.

Precursor Compound-Assisted Formation of CdS Magic-Size Clusters in Aqueous Solutions.

Investigations of the formation pathway of semiconductor magic-size clusters (MSCs) in aqueous solutions are quite limited. Here, we present our understanding about a precursor compound (PC)-assisted formation pathway of aqueous-phase CdS MSCs exhibiting a characteristic absorption peak at about 360 nm (MSC-360). The reaction uses CdCl2 as the Cd source and thioglycolic acid (TGA) as both the S source and ligand in alkaline aqueous solutions. The mixture remains absorption featureless upon incubation at room temperature but with MSC-360 absorption observed upon adding butylamine. The longer the incubation period of the aqueous solution, the more MSC-360 forms after adding butylamine. We propose that Cd-TGA complexes form first, in which the TGA moieties then decompose partially to form PC of MSC-360 (PC-360) that cannot be observed in the optical absorption spectrum. The resulting PC-360 transforms to MSC-360 via quasi-isomerization in the presence of butylamine. The present study provides an in-depth understanding about the formation of aqueous-phase MSCs.

Two-dimensional ß-noble-transition-metal chalcogenide: novel highly stable semiconductors with manifold outstanding optoelectronic properties and strong in-plane anisotropy.

In this work, five two-dimensional (2D) noble-transition-metal chalcogenide (NTMC) semiconductors, namely ß-NX (N = Au, Ag; X = S, Se, Te), were designed and predicted by first-principles simulations. Structurally, the monolayer ß-NX materials have good energetic, mechanical, dynamical, and thermal stability. They contain two inequivalent noble-transition-metal atoms in the unit cell, and the N-X bond comprises a partial ionic bond and a partial covalent bond. Regarding the electronic properties, the ß-NX materials are indirect-band-gap semiconductors with appropriate band-gap values. They have tiny electron effective masses. The hole effective masses exhibit significant differences in different directions, indicating strongly anisotropic hole mobility. In addition, the coexistence of linear and square-planar channels means that the diffusion and transport of carriers should be anisotropic. In terms of optical properties, the ß-NX materials show high absorption coefficients. The absorption and reflection characteristics reveal strong anisotropy in different directions. Therefore, the ß-NX materials are indirect-band-gap semiconductors with good stability, high absorption coefficients, and strong mechanical, electronic, transport, and optical anisotropy. In the future, they could have great potential as 2D semiconductors in nano-electronics and nano-optoelectronics.

Energy-efficient Online Continual Learning for Time Series Classification in Nanorobot-based Smart Health.

Nanorobots have been used in smart health to collect time series data such as electrocardiograms and electroencephalograms. Real-time classification of dynamic time series signals in nanorobots is a challenging task. Nanorobots in the nanoscale range require a classification algorithm with low computational complexity. First, the classification algorithm should be able to dynamically analyze time series signals and update itself to process the concept drifts (CD). Second, the classification algorithm should have the ability to handle catastrophic forgetting (CF) and classify historical data. Most importantly, the classification algorithm should be energy-efficient to use less computing power and memory to classify signals in real-time on a smart nanorobot. To solve these challenges, we design an algorithm that can Prevent Concept Drift in Online continual Learning for time series classification (PCDOL). The prototype suppression item in PCDOL can reduce the impact caused by CD. It also solves the CF problem through the replay feature. The computation per second and the memory consumed by PCDOL are only 3.572M and 1KB, respectively. The experimental results show that PCDOL is better than several state-of-the-art methods for dealing with CD and CF in energy-efficient nanorobots.

Evolution of Aqueous-Phase CdTe Magic-Size Clusters from Their Precursor Compounds.

Aqueous-phase semiconductor CdTe magic-size clusters (MSCs) have not been reported. Here, we report the first synthesis of aqueous-phase CdTe MSCs and propose that they evolve from their nonabsorbing precursor compounds (PCs). CdCl2 and Na2TeO3 are used as the respective Cd and Te sources, with l-cysteine as a ligand and NaBH4 as a reductant. When a 5 °C reaction mixture is dispersed in butylamine (BTA), CdTe MSCs evolve. We argue that the self-assembly of the Cd and Te precursors followed by the formation of the Cd-Te covalent bond inside each assembly results in one CdTe PC, which quasi-isomerizes to one CdTe MSC in the presence of BTA. At higher temperatures such as 25 °C, the PCs fragmentize, assisting the nucleation and growth of CdTe quantum dots. We introduce a novel synthetic approach to aqueous-phase CdTe PCs, which transform to CdTe MSCs in the presence of primary amines.

LncRNA expression analysis by comparative transcriptomics among closely related poplars and their regulatory roles in response to salt stress.

Long noncoding ribonucleic acids (lncRNAs) play crucial roles in regulating key biological processes; however, our knowledge of lncRNAs' roles in plant adaptive evolution is still limited. Here, we determined the divergence of conserved lncRNAs in closely related poplar species that were either tolerant or sensitive to salt stress by comparative transcriptome analysis. Among the 34,363 identified lncRNAs, ~3% were shared among poplar species with conserved sequences but diversified in their function, copy number, originating genomic region and expression patterns. Further cluster analysis revealed that the conserved lncRNAs showed more similar expression patterns within salt-tolerant poplars (Populus euphratica and P. pruinosa) than between salt-tolerant and salt-sensitive poplars. Among these lncRNAs, the antisense lncRNA lncERF024 was induced by salt and the differentiated expression between salt-sensitive and salt-tolerant poplars. The overexpression of lncERF024 in P. alba var. pyramidalis enhanced poplar tolerance to salt stress. Furthermore, RNA pull-down and RNA-seq analysis showed that numerous candidate genes or proteins associated with stress response and photosynthesis might be involved in salt resistance in PeulncERF024-OE poplars. Altogether, our study provided a novel insight into how the diversification of lncRNA expression contributes to plant adaptation traits and showed that lncERF024 may be involved in the regulation of both gene expression and protein function conferring salt tolerance in Populus.

The C2 H2 -type zinc finger transcription factor OSIC1 positively regulates stomatal closure under osmotic stress in poplar.

Salt and drought impair plant osmotic homeostasis and greatly limit plant growth and development. Plants decrease stomatal aperture to reduce water loss and maintain osmotic homeostasis, leading to improved stress tolerance. Herein, we identified the C2 H2 transcription factor gene OSMOTIC STRESS INDUCED C2 H2 1 (OSIC1) from Populus alba var. pyramidalis to be induced by salt, drought, polyethylene glycol 6000 (PEG6000) and abscisic acid (ABA). Overexpression of OSIC1 conferred transgenic poplar more tolerance to high salinity, drought and PEG6000 treatment by reducing stomatal aperture, while its mutant generated by the CRISPR/Cas9 system showed the opposite phenotype. Furthermore, OSIC1 directly up-regulates PalCuAOζ in vitro and in vivo, encoding a copper-containing polyamine oxidase, to enhance H2 O2 accumulation in guard cells and thus modulates stomatal closure when stresses occur. Additionally, ABA-, drought- and salt-induced PalMPK3 phosphorylates OSIC1 to increase its transcriptional activity to PalCuAOζ. This regulation of OSIC1 at the transcriptional and protein levels guarantees rapid stomatal closure when poplar responds to osmotic stress. Our results revealed a novel transcriptional regulatory mechanism of H2 O2 production in guard cells mediated by the OSIC1-PalCuAOζ module. These findings deepen our understanding of how perennial woody plants, like poplar, respond to osmotic stress caused by salt and drought and provide potential targets for breeding.

[Rapid screening of 84 pesticide residues in dendrobium by Sin-QuEChERS Nano purification column with gas chromatography-tandem mass spectrometry].

A rapid screening method for 84 pesticide residues in dendrobium perfringens parent material with different polarities was developed using a Sin-QuEChERS Nano clean-up column combined with gas chromatography-tandem mass spectrometry (GC-MS/MS). The differences in extraction efficiency of the targets were compared with different extraction solvents (acetonitrile containing 1% acetic acid, acetone) and methods (immersion with or without water). The purification effect and extraction recoveries of Sin-QuEChERS Nano method and classical dispersive solid-phase extraction (dSPE), solid-phase extraction (SPE) and QuEChERS were systematically compared using Dendrobium nobile samples. The differences in matrix effects between the Sin-QuEChERS Nano method, which was more effective in purification, and the dSPE method were also analyzed. The purification effects of three commercially available Sin-QuEChERS Nano purification columns (simple matrix purification column, complex matrix purification column and herbal purification column) were compared. The applicability of the purification methods were also verified by using different parts of Dendrobium nobile samples (stems, leaves and flowers). From the results, it could be concluded that weighing 2.00 g and the samples in 5 mL of water for 20 min, followed by extraction with acetonitrile containing 1% acetic acid was more effective. The average extraction recovery of the target components by Sin-QuEChERS Nano purification method was 90.5%, which further identified Sin-QuEChERS Nano-Chinese medicine purification column as the preferred purification column for dendrobium purification. The target components were separated by a DB-1701MS quartz capillary column (30 m×0.25 mm×0.25 µm) with programmed temperature rise, detected by multiple reaction monitoring (MRM) mode, and quantified by matrix-matched solution external standard method. The GC-MS/MS assay was used for the methodological validation of the 84 representative pesticides within Dendrobium officinale and Dendrobium nobile was carried out by GC-MS/MS detection method. The results indicated that the targets showed excellent linear correlation in different scopes with correlation coefficients (r2) >0. 990. The limits of detection (LODs, S/N=3) of the method were 1.5 to 5.8 µg/kg, and the limits of quantification (LOQs, S/N=10) ranged from 5.0 to 15.0 µg/kg. The spiked recoveries of the target pesticides under different spiked levels were 68.7%-116.2%, and the relative standard deviations (RSDs, n=6) were less than 15%. Compared to other typical pretreatment methods, the Sin-QuEChERS Nano method provided better performance in terms of purification. The method not only effectively removed pigments, organic acids, and alkaline interferents, but also saved preparation time. Losses due to solvent transfer were also avoided and no further vortexing or centrifugation was required, making it a simplified and effective extraction and purification procedure. The method was sensitive, rapid, simple and reliable. It effectively improved the detection efficiency during the rapid screening of pesticides in dendrobium and presented a strong practical application value. In addition, the developed method could further expand the types of target pesticides and could be used to detect more pesticide residues in foods and Chinese herbal medicine. The established Sin-QuEChERS Nano method was used for the analysis of authentic samples. The applicability of the method was evaluated by analyzing a total of 80 samples collected from Anlong, Libo, Dushan, and Yanhe County in Guizhou Province. The types of samples included dendrobium maple, Dendrobium nobile (flowers, stems, leaves) and Dendrobium officinale (flowers, stems, leaves, powder, tablets). At least one pesticide residue was detected in 12 samples, with a detection rate of 15%. The five pesticides with higher detection rates and residues were chlorpyrifos (0.08-0.5 mg/kg), chlorothalonil (0.06-3.2 mg/kg), propanil zinc (0.03-0.15 mg/kg), methyl parathion (0.04-0.23 mg/kg) and cyhalothrin (0.10-2.68 mg/kg). Except for the pesticides in maximum residue limits (MRLs), the pesticide residues detected from dendrobium samples were below the limits set by Chinese national standard (GB 2763-2021) and local standard DBS 52/048-2020.

Design of Ultra-High Extinction Ratio TM- and TE-Pass Polarizers Based on Si-Sc0.2Sb2Te3 Hybrid Waveguide.

The selective polarizers play an important role in silicon-based integrated circuits. The previous polarizers based on silicon waveguides have the defects of large scale and low extinction ratio. In this work, TM- and TE-pass polarizers only 10 µm long were developed based on phase-change material of Sc0.2Sb2Te3 (SST) hybrid silicon waveguide, where several SST bars with a varied distance was designed. Because of the excellent characteristics of the refractive index of the material, ultra-high extinction ratios (ERs) were achieved. A 3-D finite element simulation was carried out to optimize the structure of the polarizers, and the distribution of light field, as well as the transmission behavior of TE and TM modes in the two polarizers, was further demonstrated in detail. When the SST is crystalline, the unwanted mode can be attenuated, while the wanted mode can pass through with low loss. Compared with the GST-based polarizers, the proposed ones achieved high extinction ratios of ~43.12 dB (TM-pass one) and ~44.21 dB (TE-pass one), respectively; at the same time, ILs for the wanted modes could be negligible. The design of high-performance polarizers paves a new way for applications of all-optical integrated circuits.

Tuning the Electronic and Optical Properties of the Novel Monolayer Noble-Transition-Metal Dichalcogenides Semiconductor ß-AuSe via Strain: A Computational Investigation.

The strain-controlled structural, electronic, and optical characteristics of monolayer ß-AuSe are systematically studied using first-principles calculations in this paper. For the strain-free monolayer ß-AuSe, the structure is dynamically stable and maintains good stability at room temperature. It belongs to the indirect band gap semiconductor, and its valence band maximum (VBM) and conduction band minimum (CBM) consist of hybrid Au-d and Se-p electrons. Au-Se is a partial ionic bond and a partial polarized covalent bond. Meanwhile, lone-pair electrons exist around Se and are located between different layers. Moreover, its optical properties are anisotropic. As for the strained monolayer ß-AuSe, it is susceptible to deformation by uniaxial tensile strain. It remains the semiconductor when applying different strains within an extensive range; however, only the biaxial compressive strain is beyond -12%, leading to a semiconductor-semimetal transition. Furthermore, it can maintain relatively stable optical properties under a high strain rate, whereas the change in optical properties is unpredictable when applying different strains. Finally, we suggest that the excellent carrier transport properties of the strain-free monolayer ß-AuSe and the stable electronic properties of the strained monolayer ß-AuSe originate from the p-d hybridization effect. Therefore, we predict that monolayer ß-AuSe is a promising flexible semiconductive photoelectric material in the high-efficiency nano-electronic and nano-optoelectronic fields.

Fusion prior gene network for high reliable single-cell gene regulatory network inference.

Single-Cell RNA sequencing technology provides an opportunity to discover gene regulatory networks(GRN) that control cell differentiation and drive cell type transformation. However, it is faced with the challenge of high loss and high noise of sequencing data and contains many pseudo-connections. To solve these problems, we propose a framework called Fusion prior gene network for Gene Regulatory Network inference Accuracy Enhancement(FGRNAE) to infer a high reliable gene regulatory network. Specifically, based on the Single-Cell RNA-sequencing Network Propagation and network Fusion(scNPF) preprocessing framework, we employ the Random Walk with Restart on the prior gene network to interpolate the missing data. Furthermore, we infer the network using the Random Forest algorithm with the results achieved above. In addition, we apply data from the Co-Function Network to build a meta-gene network and select the regulatory connection with the Markov Random Field. Extensive experiments based on datasets from BEELINE validate the effectiveness of our framework for improving the accuracy of inference.