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Abstract BiFeO3 (BFO) application in flexible wearable devices is garnering interest because of its unique ferroelectric and magnetic properties. However, the integration of high-quality BFO films onto flexible substrates presents significant technical challenges. Here, we successfully fabricated high-quality BFO films on mica substrates by using pulsed laser deposition, and report the fatigue characteristics of BFO films on flexible substrates for the first time. The results demonstrated that, after 108 bipolar switching cycles, the polarization only degraded by 0.28%, indicating superior fatigue characteristics compared to previously reported BFO films. Additionally, the device ferroelectric properties remained largely unchanged, with a bending radius of 3.5 mm. The fabricated flexible Pt/BFO/La0.65Sr0.35MnO3(LSMO)/SrTiO3(STO)/mica non-volatile memory devices exhibited mechanical flexibility and fatigue resistance. These findings not only highlight the potential of flexible BFO films for wearable electronic devices and flexible memory devices, they also provide valuable insight for the future development of high-performance flexible ferroelectric materials.

Abstract Background Beta‐defensins (BDs) are antimicrobial peptides secreted upon epithelial injury. Both chemotactic and antimicrobial properties of BDs function as initial steps in host defence and prime the adaptive immune system in the body. Psoriasis, a chronic immune‐mediated inflammatory disease, has both visible cutaneous manifestations as well as known associations with higher incidence of cardiometabolic complications and vascular inflammation. Objectives We aimed to investigate the circulating expression of beta‐defensin‐2 (BD2) in psoriasis at baseline compared to control subjects, along with changes in BD2 levels following biologic treatment at 1 year. The contribution of BD2 to subclinical atherosclerosis is also assessed. In addition, we have sought to unravel signalling mechanisms linking inflammation with BD2 expression. Methods Multimodality imaging, as well as inflammatory biomarker assays, were performed in biological naïve psoriasis (n = 71) and non‐psoriasis (n = 53) subjects. A subset of psoriasis patients were followed for 1 year after biological intervention (antitumour necrosis factor‐α [TNF‐α], n = 30; anti‐interleukin17A [IL17A], n = 21). Measurements of circulating BD2 were completed by enzyme‐linked immunosorbent assay (ELISA). Using HaCaT‐transformed keratinocytes, expression of BD2 upon cytokine treatment was assessed by quantitative polymerase chain reaction and ELISA. Results Herein, we confirm that human circulating BD2 levels are associated with psoriasis, which attenuate upon biological interventions (anti‐TNF‐α, anti‐IL‐17A). A link between circulating BD2 and subclinical atherosclerosis markers was not observed. Furthermore, we demonstrate that IL‐17A‐driven BD2 expression occurs in a Phosphatidylinositol 3‐kinase (PI3‐kinase) and Rac1 GTPase‐dependent manner. Conclusions Our findings expand on the potential role of BD2 as a tractable biomarker in psoriasis patients and describe the role of an IL‐17A‐PI3‐kinase/Rac signalling axis in regulating BD2 levels in keratinocytes.

The field of artificial intelligence and neural computing has been rapidly expanding due to the implementation of resistive random-access memory (RRAM) based artificial synaptic. However, the low flexibility of conventional RRAM materials hinders their ability to mimic synaptic behavior accurately. To overcome such limitation, organic-2D composites with high mechanical properties are proposed as the active layer of RRAM. Moreover, we enhance the reliability of the device by ZrO2 insertion layer, resulting in stable synaptic performance. The Ag/PVA:h-BN/ZrO2/ITO devices show stable bipolar resistive switching behavior with an ON/OFF ratio of over 5 × 102, a ∼2 400 cycles endurance and a long retention time (>6 × 103s), which are essential for the development of high-performance RRAMs. We also study the possible synaptic mechanism and dynamic plasticity of the memory device, observing the transition from short-term potentiation (STP) to long-term potentiation (LTP) under the effect of continuous voltage pulses. Moreover, the device exhibits both long-term depression (LTD) and paired-pulse facilitation (PPF) properties, which have significant implications for the design of organic-2D composite material RRAMs that aim to mimic biological synapses, representing promising avenues for the development of advanced neuromorphic computing systems.

Psoriasis (PSO) is a chronic and systemic inflammatory autoimmune disease associated with atherosclerosis and myocardial infarction. Given that atherosclerosis is both inflammation and immune driven, we sought to expand on known immune and inflammatory biomarkers in a PSO cohort. In this study, we focus on oxidized mtDNA (ox-mtDNA), a product of cells undergoing pyroptosis, including keratinocytes, which was quantified in patients with PSO and individuals without PSO by ELISA. Patients with PSO had significantly higher ox-mtDNA levels than healthy subjects (mean ± SD = 9246 ± 2518 pg/ml for patients with PSO vs 7382 ± 2506 pg/ml for those without; P = .006). Importantly, ox-mtDNA was positively associated with IL-17a (β = 0.25; P = .03) and low-density granulocytes (β = 0.37; P = .005) but negatively associated with high-density lipoprotein-cholesterol (β = −0.29; P = .006). After adjusting for traditional cardiovascular risk factors, we found that ox-mtDNA was associated with noncalcified coronary burden, which was measured by coronary computed tomography angiography (β = 0.19; P = .003). Biologic-naïve patients with PSO receiving anti–IL-17a therapy had a 14% decrease in ox-mtDNA (mean ± SD: 10540 ± 614 pg/ml at baseline to 9016 ± 477 pg/ml at 1 year; P = .016) and a 10% reduction in noncalcified coronary artery burden (mean ± SD: 1.06 ± 0.45 at baseline, reducing to 0.95 ± 0.35 at 1 year; P = .0037). In summary, levels of ox-mtDNA in PSO are associated with measures of coronary plaque formation, indicating that this biomarker may be an autoimmune-driven early atherosclerotic feature.

Abstract Background Psoriasis (PSO) is a skin disorder with systemic inflammation and high coronary artery disease risk. A distinct lipid phenotype occurs in psoriasis, which is characterized by high plasma triglycerides (TGs) with typically normal or even low LDL-C. The extent to which cholesterol on LDL subfractions, such as small dense LDL-C (sdLDL-C), are associated with vulnerable coronary plaque characteristics in PSO remains elusive. Methods A recently developed equation for estimating sdLDL-C from the standard lipid panel was utilized in a PSO cohort (n = 200) with 4-year follow-up of 75 subjects. Coronary plaque burden was assessed by quantitative coronary computed tomography angiography (CCTA). Multivariate regression analyses were used for establishing associations and prognostic value of estimated sdLDL-C. Results Estimated sdLDL-C was positively associated with non-calcified burden (NCB) and fibro-fatty burden (FFB), which remained significant after multivariate adjustment for NCB (β = 0.37; P = 0.050) and LDL-C adjustment for FFB (β = 0.29; P

Background Psoriasis is a chronic inflammatory condition associated with coronary artery disease risk. Uptake of oxidized low‐density lipoprotein by the lectin‐like low‐density lipoprotein receptor‐1 triggers release of the soluble extracellular domain of the receptor (sLOX‐1). We sought to characterize the relationship between sLOX‐1, inflammation, and coronary plaque progression in psoriasis. Methods and Results A total of 327 patients with psoriasis had serum sLOX‐1 levels measured at baseline by an ELISA‐based assay. Stratification by high‐sensitivity C‐reactive protein ≥4.0 mg/L (quartile 4), identified 81 participants who had coronary plaque phenotyping at baseline and were followed longitudinally by coronary computed tomography angiography. Subjects within high‐sensitivity C‐reactive protein quartile 4 were middle‐aged (51.47±12.62 years), predominantly men (54.3%) with moderate psoriasis disease severity (6.60 [interquartile range, 3.30–13.40]). In the study cohort, participants with sLOX‐1 above the median displayed increased vulnerable coronary plaque features. At baseline, sLOX‐1 was associated with total burden (rho=0.296; P=0.01), noncalcified burden (rho=0.286; P=0.02), fibro‐fatty burden (rho=0.346; P=0.004), and necrotic burden (rho=0.394; P=0.002). A strong relationship between sLOX‐1, noncalcified burden (β=0.19; P=0.03), and fibro‐fatty burden (β=0.29; P=0.003) was found in fully adjusted models at baseline and 1‐ and 4‐year follow‐up. Finally, coronary plaque features progressed over 1 year regardless of biologic or systemic treatment in subjects with high sLOX‐1. Conclusions Patients with psoriasis with both high sLOX‐1 and high‐sensitivity C‐reactive protein levels have increased coronary plaque burden associated with atherosclerotic plaque progression independent of biologic and systemic treatment. Thus, sLOX‐1 might be considered as a promising marker in coronary artery disease risk estimation beyond traditional risk factors. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT01778569.

BACKGROUND. Oxidized apolipoprotein B (oxLDL) and oxidized ApoA-I (oxHDL) are proatherogenic. Their prognostic value for assessing high-risk plaques by coronary computed tomography angiography (CCTA) is missing.METHODS. In a prospective, observational study, 306 participants with cardiovascular disease (CVD) had extensive lipoprotein profiling. Proteomics analysis was performed on isolated oxHDL, and atherosclerotic plaque assessment was accomplished by quantitative CCTA.RESULTS. Patients were predominantly White, overweight men (58.5%) on statin therapy (43.5%). Increase in LDL-C, ApoB, small dense LDL-C (P < 0.001 for all), triglycerides (P = 0.03), and lower HDL function were observed in the high oxLDL group. High oxLDL associated with necrotic burden (NB; β = 0.20; P < 0.0001) and fibrofatty burden (FFB; β = 0.15; P = 0.001) after multivariate adjustment. Low oxHDL had a significant reverse association with these plaque characteristics. Plasma oxHDL levels better predicted NB and FFB after adjustment (OR, 2.22; 95% CI, 1.27–3.88, and OR, 2.80; 95% CI, 1.71–4.58) compared with oxLDL and HDL-C. Interestingly, oxHDL associated with fibrous burden (FB) change over 3.3 years (β = 0.535; P = 0.033) when compared with oxLDL. Combined Met136 mono-oxidation and Trp132 dioxidation of HDL showed evident association with coronary artery calcium score (r = 0.786; P < 0.001) and FB (r = 0.539; P = 0.012) in high oxHDL, whereas Met136 mono-oxidation significantly associated with vulnerable plaque in low oxHDL.CONCLUSION. Our findings suggest that the investigated oxidized lipids are associated with high-risk coronary plaque features and progression over time in patients with CVD.TRIAL REGISTRATION. ClinicalTrials.gov NCT01621594.FUNDING. National Heart, Lung, and Blood Institute at the NIH Intramural Research Program.

Background: s: Psoriasis is a disease of systemic inflammation associated with increased cardiometabolic risk. Epicardial adipose tissue (EAT) and thoracic adipose tissue (TAT) are contributing factors for atherosclerosis and cardiac dysfunction. We strove to assess the longitudinal impact of the EAT and TAT on coronary and cardiac characteristics in psoriasis. Methods: The study consisted of 301 patients with baseline coronary computed tomography angiography (CTA), of which 139 had four-year follow up scans. EAT and TAT volumes from non-contrast computed tomography scans were quantified by an automated segmentation framework. Coronary plaque characteristics and left ventricular (LV) mass were quantified by CTA. Results: When stratified by baseline EAT and TAT volume quartiles, a stepwise significant increase in cardiometabolic parameters was observed. EAT and TAT volumes associated with fibro-fatty burden (FFB) (TAT: ρ = 0.394, P

Rationale and introductionIt is of significance to assess the severity and predict the mortality of patients with connective tissue disease-associated interstitial lung disease (CTD-ILD). In this double-center retrospective study, we developed and validated a radiomics nomogram for clinical management by using the ILD-GAP (gender, age, and pulmonary physiology) index system.Materials and methodsPatients with CTD-ILD were staged using the ILD-GAP index system. A clinical factor model was built by demographics and CT features, and a radiomics signature was developed using radiomics features extracted from CT images. Combined with the radiomics signature and independent clinical factors, a radiomics nomogram was constructed and evaluated by the area under the curve (AUC) from receiver operating characteristic (ROC) analyses. The models were externally validated in dataset 2 to evaluate the model generalization ability using ROC analysis.ResultsA total of 245 patients from two clinical centers (dataset 1, n = 202; dataset 2, n = 43) were screened. Pack-years of smoking, traction bronchiectasis, and nine radiomics features were used to build the radiomics nomogram, which showed favorable calibration and discrimination in the training cohort {AUC, 0.887 [95% confidence interval (CI): 0.827–0.940]}, the internal validation cohort [AUC, 0.885 (95% CI: 0.816–0.922)], and the external validation cohort [AUC, 0.85 (95% CI: 0.720–0.919)]. Decision curve analysis demonstrated that the nomogram outperformed the clinical factor model and radiomics signature in terms of clinical usefulness.ConclusionThe CT-based radiomics nomogram showed favorable efficacy in predicting individual ILD-GAP stages.

Different stereoisomers of phytohormones may have different roles in plants while the quantification for stereoisomers still remains a challenge. The chiral separation method for methyl jasmonate (MeJA) in tea (Camellia sinensis L.) was developed by air-assisted liquid-liquid microextraction (AALLME) with enantioselective gas chromatography-mass spectrometry (Es-GC-MS/MS). The Plackett-Burman factorial design was introduced to optimize the multiple parameters of AALLME. Sensitive Es-GC-MS/MS enabled the quantification of the MeJA stereoisomers, which were separated from each other with resolutions of 3.5, 2.7, and 2.5. The linearities were R2 > 0.9971, the limits of detection were 0.08–0.12 ng/mL, the limits of quantification (LOD) were 0.28–0.39 ng/mL, and the recovery range was 80.60–107.03%. The method was applied to analyze the MeJA stereoisomer profiles in tea plants after geometrid feeding and mechanical wounding. (+)-MeJA appeared to be the main bio-active monomer that responded to injury stress. (+)-MeJA similarly increased in tea shoots at only 30 s after geometrid attack or mechanical wounding. The proposed method is superior as air-assisted liquid-liquid microextraction could induce the loss of volatile MeJA in a much shorter time, compared to the conventional enrichment procedure. A novel assay protocol for relative quantification of MeJA stereoisomers in plants responding to different injuries was applied.

In this paper, we propose a design of a mid-infrared Metamaterial Absorber (MIMA). The MIMA is composed of a thin metamaterial nanostructure of period array of cross-circular structure of Ti with continuum graphene layer and bottom film is Al substrate, the middle dielectric layer is a stack of Si3N4 and SiO2. The coupling of surface plasmon resonance (SPR) of graphene, metal Ti and dielectric layers and the intrinsic absorption of the material enhance broadband absorption. The MIMA maintains 97% average absorption in the 3.8∼6.5 μm in the background refractive index of 1.33. MIMA maintains 80% average absorption within an incidence angle of 50 and it is polarization insensitive. Dynamic tuning of the MIMA absorption bandwidth by changing the Fermi energy level of graphene by applying a voltage to the graphene surface. The absorption bandwidth can broaden in complex environments (water, ice, alcohol). The proposed research shows excellent applications in thermal emitter and photocatalysis, infrared camouflage in complex environment.

In this study, we present a chiral metasurface structure based on graphene-Au elliptical hole arrays. Circular dichroism of up to 0.91 is achieved by varying the rotation angle of the elliptical hole. Circular dichroism (CD) typically expresses the chiral response. The structure has excellent absorption of right circularly polarized light while reflecting left circularly polarized light, and it is theoretically analyzed using the Jones matrix. By incorporating graphene between the gold hole array and the dielectric, the CD can be finely tuned. The CD response decreases from 0.88 to 0.55 when the Fermi energy level of graphene is changed from 0.3 eV to 1.0 eV, as indicated by computational studies. In addition, the periodic cell structure based on this metasurface can realize the digital imaging function and the dynamic modulation of the imaging state can be achieved by adjusting the Fermi energy level, which has potential applications in fields like communication encryption.

BackgroundDifferential diagnosis of primary intestinal lymphoma (PIL) and Crohn’s disease (CD) is a challenge in clinical diagnosis.AimsTo investigate the validity of the nomogram based on clinical and computed tomography (CT) features to identify PIL and CD.MethodsThis study retrospectively analyzed laboratory parameters, demographic characteristics, clinical manifestations, and CT imaging features of PIL and CD patients from two centers. Univariate logistic analysis was performed for each variable, and laboratory parameter model, clinical model and imaging features model were developed separately. Finally, a nomogram was established. All models were evaluated using the area under the curve (AUC), accuracy, sensitivity, specificity, and decision curve analysis (DCA).ResultsThis study collected data from 121 patients (PIL = 69, CD = 52) from Center 1. Data from 43 patients (PIL = 24, CD = 19) were collected at Center 2 as an external validation cohort to validate the robustness of the model. Three models and a nomogram were developed to distinguish PIL from CD. Most models performed well from the external validation cohort. The nomogram showed the best performance with an AUC of 0.921 (95% CI: 0.838–1.000) and sensitivities, specificities, and accuracies of 0.945, 0.792, and 0.860, respectively.ConclusionA nomogram combining clinical data and imaging features was constructed, which can effectively distinguish PIL from CD.

Axillary bud outgrowth, a key factor in ratoon rice yield formation, is regulated by several phytohormone signals. The regulatory mechanism of key genes underlying ratoon buds in response to phytohormones in ratoon rice has been less reported. In this study, GR24 (a strigolactone analogue) was used to analyze the ratooning characteristics in rice cultivar Huanghuazhan (HHZ). Results show that the elongation of the axillary buds in the first seasonal rice was significantly inhibited and the ratoon rate was reduced at most by up to 40% with GR24 treatment. Compared with the control, a significant reduction in the content of auxin and cytokinin in the second bud from the upper spike could be detected after GR24 treatment, especially 3 days after treatment. Transcriptome analysis suggested that there were at least 742 and 2877 differentially expressed genes (DEGs) within 6 h of GR24 treatment and 12 h of GR24 treatment, respectively. Further bioinformatics analysis revealed that GR24 treatment had a significant effect on the homeostasis and signal transduction of cytokinin and auxin. It is noteworthy that the gene expression levels of OsCKX1, OsCKX2, OsGH3.6, and OsGH3.8, which are involved in cytokinin or auxin metabolism, were enhanced by the 12 h GR24 treatment. Taken overall, this study showed the gene regulatory network of auxin and cytokinin homeostasis to be regulated by strigolactone in the axillary bud outgrowth of ratoon rice, which highlights the importance of these biological pathways in the regulation of axillary bud outgrowth in ratoon rice and would provide theoretical support for the molecular breeding of ratoon rice.

The study of DNA binding proteins (DBPs) is of great importance in the biomedical field and plays a key role in this field. At present, many researchers are working on the prediction and detection of DBPs. Traditional DBP prediction mainly uses machine learning methods. Although these methods can obtain relatively high pre-diction accuracy, they consume large quantities of human effort and material resources. Transfer learning has certain advantages in dealing with such prediction problems. Therefore, in the present study, two features were extracted from a protein sequence, a transfer learning method was used, and two classical transfer learning algorithms were compared to transfer samples and construct data sets. In the final step, DBPs are detected by building a deep learning neural network model in a way that uses attention mechanisms.

The regulatory mechanisms of PD-L1 posttranslational modifications are not completely understood. Here the authors show that USP8 negatively regulates PD-L1 protein abundance by removing the K63-linked ubiquitination of PD-L1; while USP8 inhibition increases MHC-I expression and triggers anti-tumour immune responses through activating NF-κB signalling.

Background and objectivePsoriasis is a systemic inflammatory condition with poor cholesterol transport measured by cholesterol efflux capacity (CEC) that is associated with a heightened risk of cardiovascular disease (CVD). In psoriasis patients, we sought to characterize the lipoprotein profile by size using a novel nuclear magnetic resonance algorithm in patients with low CEC compared to normal CEC.MethodsLipoprotein profile was assessed using the novel nuclear magnetic resonance LipoProfile-4 deconvolution algorithm. Aortic vascular inflammation (VI) and non-calcified burden (NCB) were characterized via positron emission tomography-computed tomography and coronary computed tomography angiography. To understand the relationship between lipoprotein size and markers of subclinical atherosclerosis, linear regression models controlling for confounders were constructed.ResultsPsoriasis patients with low CEC had higher more severe psoriasis (p = 0.04), VI (p = 0.04) and NCB (p = 0.001), concomitant with smaller high-density lipoprotein (HDL) (p < 0.001) and low-density lipoprotein (LDL) particles (p < 0.001). In adjusted models HDL size (β = −0.19; p = 0.02) and LDL size (β = −0.31; p < 0.001) associated with VI and NCB. Lastly, HDL size strongly associated with LDL size in fully adjusted models (β = −0.27; p < 0.001).ConclusionThese findings demonstrate that in psoriasis, low CEC associates with a lipoprotein profile comprised of smaller HDL and LDL particles which correlates with vascular health and may be driving early onset atherogenesis. Further, these results demonstrate a relationship between HDL and LDL size and provide novel insights into the complexities of HDL and LDL as biomarkers of vascular health.

Coupled mode theory (CMT) is widely used to analyze the coupling relationship of plasmons and metasurfaces. However, some details involving coupled structures remain obscure. Herein, the coefficients in CMT are properly defined to solve the problems of inaccurate fitting from two particles to three or more. The proposed improved coupled mode theory (i‐CMT) can perfectly express both the amplitude and phase of transmission curve of dimeric and trimeric mutual coupled systems. A surface plasmonic structure containing multiple metallic spiral structures is fabricated to experimentally verify the accuracy of the i‐CMT. The experimental results are consistent with the theoretical and simulated values, proving the feasibility of using the i‐CMT to analyze and design asymmetric coupled devices. Moreover, the application of the i‐CMT confirms the presence of additional coupling terms in three or more coupled objects, making the calculation of eigenfrequency more accurate.

BackgroundLow-density lipoprotein cholesterol (LDL-C) is an established marker for cardiovascular disease (CVD) and a therapeutic target. Oxidized LDL (oxLDL) is known to be associated with excessive inflammation and abnormal lipoprotein metabolism. Chronic inflammatory diseases confer an elevated risk of premature atherosclerosis and adverse cardiovascular events. Whether oxLDL may serve as a potential biomarker for CVD stratification in populations with chronic inflammatory conditions remains understudied.ObjectiveTo perform a systematic review and meta-analysis evaluating the relationship between oxLDL and CVD (defined by incident CVD events, carotid intima-media thickness, presence of coronary plaque) in patients with chronic inflammatory diseases.MethodsA systematic literature search was performed using studies published between 2000 and 2022 from PubMed, Cochrane Library, Embase (Elsevier), CINHAL (EBSCOhost), Scopus (Elsevier), and Web of Science: Core Collection (Clarivate Analytics) databases on the relationship between oxLDL and cardiovascular risk on inflamed population. The pooled effect size was combined using the random effect model and publication bias was assessed if P < 0.05 for the Egger or Begg test along with the funnel plot test.ResultsA total of three observational studies with 1,060 participants were ultimately included in the final meta-analysis. The results demonstrated that oxLDL is significantly increased in participants with CVD in the setting of chronic inflammatory conditions. This meta-analysis suggests that oxLDL may be a useful biomarker in risk stratifying cardiovascular disease in chronically inflamed patients.

The crystal structure, band structure, density of states, and optical properties of κ-(Ga1−xInx)2O3 (x = 0, 0.125, 0.25, 0.5) were studied using the first-principles calculation based on the density functional theory. With the increase of In content x, the bandgap of κ-(Ga1−xInx)2O3 decreases, while the light absorption coefficient increases. The spontaneous polarization of κ-(Ga1−xInx)2O3 was calculated qualitatively using the Born effective charge. The results suggested that κ-(Ga1−xInx)2O3 is also a material with spontaneous polarization properties. The spontaneous polarization in the extended c-axis has increased 1.27 times, from 27.31 to 34.58 μC/cm2, with the increase of In content from 0 to 0.5. This work paves the way for modulating spontaneous polarization of wide bandgap semiconductors. It provides a theoretical basis for the potential application of κ-(Ga1−xInx)2O3 in high electron mobility transistors, quantum well-infrared photodetectors, and photovoltaic materials.

Abstract Background RNA secondary structure prediction is an important research content in the field of biological information. Predicting RNA secondary structure with pseudoknots has been proved to be an NP-hard problem. Traditional machine learning methods can not effectively apply protein sequence information with different sequence lengths to the prediction process due to the constraint of the self model when predicting the RNA secondary structure. In addition, there is a large difference between the number of paired bases and the number of unpaired bases in the RNA sequences, which means the problem of positive and negative sample imbalance is easy to make the model fall into a local optimum. To solve the above problems, this paper proposes a variable-length dynamic bidirectional Gated Recurrent Unit(VLDB GRU) model. The model can accept sequences with different lengths through the introduction of flag vector. The model can also make full use of the base information before and after the predicted base and can avoid losing part of the information due to truncation. Introducing a weight vector to predict the RNA training set by dynamically adjusting each base loss function solves the problem of balanced sample imbalance. Results The algorithm proposed in this paper is compared with the existing algorithms on five representative subsets of the data set RNA STRAND. The experimental results show that the accuracy and Matthews correlation coefficient of the method are improved by 4.7% and 11.4%, respectively. Conclusions The flag vector introduced allows the model to effectively use the information before and after the protein sequence; the introduced weight vector solves the problem of unbalanced sample balance. Compared with other algorithms, the LVDB GRU algorithm proposed in this paper has the best detection results.

Background and ObjectivesPsoriasis is a heterogeneous inflammatory disease that involves the skin, joints, liver, heart, and other organs. Psoriatic arthritis (PsA) is associated with cardiovascular disease (CVD), but the relative contributions of inflammatory and metabolic dysregulation to CVD are incompletely understood. We set out to discover novel potential contributors to CVD in PsA patients by comprehensively phenotyping a cohort of PsA patients using these advanced technologies.MethodsIn this cross-sectional analysis of a cohort study, we investigated associations of systemic inflammation and metabolic dysregulation with Coronary CT angiography (CCTA)-proven coronary artery disease (CAD) in 39 subjects with PsA. We measured traditional CVD risk factors [blood pressure, Body Mass Index (BMI), diabetes, age, sex, smoking], serum markers of systemic inflammation (hsCRP, GlycA) and metabolic dysfunction (cholesterol efflux capacity), and inflammatory cytokines (IL-1β, IL-6, IL-12/IL-23, IL-17A, TNF-α, IFN-γ). We also incorporated radiographic measures of metabolic dysfunction (visceral and subcutaneous adipose volume) and tissue-specific inflammation (positron emission tomography-computed tomography, PET-CT). To quantify relative contributions of FDG (fluorodeoxyglucose) uptake and adiposity to coronary plaque, we performed multiple linear regression, controlling for Framingham risk score (FRS) and FRS + visceral adiposity.ResultsCompared with non-psoriatic volunteers, subjects with PsA had elevated markers of metabolic and inflammatory disease, which was more pronounced in subjects with moderate-to-severe skin disease. This included visceral (p = 0.005) and subcutaneous (p = 0.004) adiposity, BMI (p = 0.001), hemoglobin A1C (p = 0.037), high sensitivity C-reactive protein (p = 0.005), IL-6 (p = 0.003), IFN-γ (p = 0.006), and liver FDG uptake (p = 0.03). In subjects with PsA, visceral adiposity correlated significantly with subclinical CAD (standardized β = 0.681, p = 0.002), as did FDG uptake in bone marrow (standardized β = 0.488, p = 0.008), liver (standardized β = 0.619, p < 0.001), spleen (standardized β = 0.523, p = 0.004), and subcutaneous adipose (standardized β = 0.524, p = 0.003).InterpretationTogether, these findings reveal inflammatory and metabolic potential contributors to subclinical CAD in PsA, including adipose inflammation, and suggesting novel targets for CVD prevention and treatment in PsA.

The integration of metal oxides and GaAs semiconductors is quite attractive for its potential applications, but interfacial diffusion and lattice mismatch usually cause huge challenges toward achieving high-performance electronic devices. In this article, we reported a thin layer of epitaxial TiO2 (110) on a GaAs (001) substrate with significant compressive strain, lattice distortion, and oxygen vacancies, where the oxygen vacancies proved to be the critical factor to induce the compressive strain and lattice distortion. In this case, the lattice mismatches between this compressed TiO2 (110) and GaAs (001) surface were calculated to be as small as 1.3 and 0.24% along the [110] and [001] orientations of TiO2, respectively. Further, no Ga-oxides or As-oxides were found at the interface, indicating that the TiO2 layer inhibited the diffusion of Ga and As atoms effectively. In summary, TiO2 film can be grown epitaxially on GaAs (001) substrates with non-negligible compressive strain, lattice distortion, oxygen vacancies, and a high-quality interface. This study also provides an approach to integrate different functional oxides on TiO2-buffered GaAs for various GaAs-based electronic devices with higher reliability and performance.

Theoretical studies of ultra-thin silicon solar cells with cylindrical, conical and parabolic surface nanostructures inherited from natural self-assembled anodic alumina oxide (NSA-AAO) were performed by finite-difference time-domain (FDTD) method. All nanostructured solar cells obtained an optimized efficiency enhancement as high as more than 33% comparing with that of the anti-reflective (AR) one. Numerical results reveal that the range of efficient structural parameters for the nanostructured (e.g., cylindrical) solar cell can be effectively enlarged as the period of the nanostructure changes from 0.1 μm to 0.5 μm. Moreover, the improvements of absorption photocurrent density (Jph) in conical and parabolic nanostructured solar cells are comparable with the cylindrical nanostructured one but less sensitive to the fill factor and structural height in the whole simulation region of 0.1-0.9 and 0-0.25 μm, respectively. Equivalent refractive index models were used to analysis the antireflection performance of surface nanostructures from the point of view of sidewall profiles. Resonance modes induced through nanostructures have greatly improved the absorptance of solar cells in broadening wavelength bands which consequently raised the Jph. This study serves as a way for the practical design and application of AAO nanostructure based high-efficiency ultra-thin solar cells.

In this paper, we propose a multi-channel photonic crystal fiber sensor, which adopts dual-polarization and multiple materials to effectively reduce the mutual interference between channels and enhance the surface plasmon resonance, thus achieving simultaneous detection of a multi-channel with low interference. Four channels are polished around the cylindrical fiber, and then different metal films (gold or silver) and plasmonic materials (titanium dioxide, thallium pentoxide, or graphene) are added to the sensing area of each channel. All channels detect refractive indices in the range of 1.34 to 1.42. The sensing performance of the fiber optic sensor was numerically investigated using the full vector finite element method. After the optimization of structural parameters, the maximum wavelength sensitivity of channel-1, channel-2, channel-3, and channel-4 are 49,800 nm/RIU, 49,000 nm/RIU, 35,900 nm/RIU, and 36,800 nm/RIU, respectively. We have theoretically analyzed the sensor’s capabilities for partial bio-detection and simulated its detection capability with a wavelength sensitivity of 11,500 nm/RIU for normal red blood cells and 12,200 nm/RIU for MCF-7 cancerous cells. Our proposed sensor has a novel design, can detect multiple channels simultaneously, has strong anti-interference capability and high sensitivity, and has good sensing characteristics.

Amino acids are the building blocks of biomacromolecules in organisms, among which isoleucine (Ile) is the precursor of JA-Ile, an active molecule of phytohormone jasmonate (JA). JA is essential for diverse plant defense responses against biotic and abiotic stresses. Botrytis cinerea is a necrotrophic nutritional fungal pathogen that causes the second most severe plant fungal disease worldwide and infects more than 200 kinds of monocot and dicot plant species. In this study, we demonstrated that Ile application enhances plant resistance against B. cinerea in Arabidopsis, which is dependent on the JA receptor COI1 and the jasmonic acid-amido synthetase JAR1. The mutant lib with higher Ile content in leaves exhibits enhanced resistance to B. cinerea infection. Furthermore, we found that the exogenous Ile application moderately enhanced plant resistance to B. cinerea in various horticultural plant species, including lettuce, rose, and strawberry, suggesting a practical and effective strategy to control B. cinerea disease in agriculture. These results together showed that the increase of Ile could positively regulate the resistance of various plants to B. cinerea by enhancing JA signaling, which would offer potential applications for crop protection.

Abstract Background In ab initio protein-structure predictions, a large set of structural decoys are often generated, with the requirement to select best five or three candidates from the decoys. The clustered central structures with the most number of neighbors are frequently regarded as the near-native protein structures with the lowest free energy; however, limitations in clustering methods and three-dimensional structural-distance assessments make identifying exact order of the best five or three near-native candidate structures difficult. Results To address this issue, we propose a method that re-ranks the candidate structures via random forest classification using intra- and inter-cluster features from the results of the clustering. Comparative analysis indicated that our method was better able to identify the order of the candidate structures as comparing with current methods SPICKR, Calibur, and Durandal. The results confirmed that the identification of the first model were closer to the native structure in 12 of 43 cases versus four for SPICKER, and the same as the native structure in up to 27 of 43 cases versus 14 for Calibur and up to eight of 43 cases versus two for Durandal. Conclusions In this study, we presented an improved method based on random forest classification to transform the problem of re-ranking the candidate structures by an binary classification. Our results indicate that this method is a powerful method for the problem and the effect of this method is better than other methods.

Abstract Background RNA secondary structure prediction is an important issue in structural bioinformatics, and RNA pseudoknotted secondary structure prediction represents an NP-hard problem. Recently, many different machine-learning methods, Markov models, and neural networks have been employed for this problem, with encouraging results regarding their predictive accuracy; however, their performances are usually limited by the requirements of the learning model and over-fitting, which requires use of a fixed number of training features. Because most natural biological sequences have variable lengths, the sequences have to be truncated before the features are employed by the learning model, which not only leads to the loss of information but also destroys biological-sequence integrity. Results To address this problem, we propose an adaptive sequence length based on deep-learning model and integrate an energy-based filter to remove the over-fitting base pairs. Conclusions Comparative experiments conducted on an authoritative dataset RNA STRAND (RNA secondary STRucture and statistical Analysis Database) revealed a 12% higher accuracy relative to three currently used methods.

Abstract Background Protein structure prediction has always been an important issue in bioinformatics. Prediction of the two-dimensional structure of proteins based on the hydrophobic polarity model is a typical non-deterministic polynomial hard problem. Currently reported hydrophobic polarity model optimization methods, greedy method, brute-force method, and genetic algorithm usually cannot converge robustly to the lowest energy conformations. Reinforcement learning with the advantages of continuous Markov optimal decision-making and maximizing global cumulative return is especially suitable for solving global optimization problems of biological sequences. Results In this study, we proposed a novel hydrophobic polarity model optimization method derived from reinforcement learning which structured the full state space, and designed an energy-based reward function and a rigid overlap detection rule. To validate the performance, sixteen sequences were selected from the classical data set. The results indicated that reinforcement learning with full states successfully converged to the lowest energy conformations against all sequences, while the reinforcement learning with partial states folded 50% sequences to the lowest energy conformations. Reinforcement learning with full states hits the lowest energy on an average 5 times, which is 40 and 100% higher than the three and zero hit by the greedy algorithm and reinforcement learning with partial states respectively in the last 100 episodes. Conclusions Our results indicate that reinforcement learning with full states is a powerful method for predicting two-dimensional hydrophobic-polarity protein structure. It has obvious competitive advantages compared with greedy algorithm and reinforcement learning with partial states.

To achieve high performance and wide range detection, we propose an ultra-wide range high sensitivity plasmonic fiber optic sensor with a gold (Au) nanowire group array, which has both propagating surface plasmon resonance (PSPR) and local surface plasmon resonance (LSPR) sensing characteristics. The PSPR, LSPR, and PSPR+LSPR are presented as Au thin layers, Au spheres (or Au nanowires), and Au nanowire group arrays, respectively, and their respective properties are analyzed from theoretical, simulated, and numerical aspects. When detection is performed, the presence of both evanescent wave and electric field forces in the Au nanowire group array combines to significantly improve the sensor’s detection capability. Detection simulation analysis was performed using COMSOL Multiphysics software. The range of refractive indices that can be detected is 1.08 to 1.37 in the optical band from 1210 nm to 2140 nm. In the detection range, the maximum sensitivity of the detected wavelength is 13,000 nm/RIU. Our proposed sensor has a broad range, high sensitivity, and low refractive index detection, and has good research value and application prospects.

Based on coupled-mode theory (CMT) and the finite-difference time-domain (FDTD) approach, we propose a graphene metasurface-based and multifunctional polarization beam splitter that is dynamically tunable. The structure, comprising two graphene strips at the top and bottom and four triangular graphene blocks in the center layer, can achieve triple plasma-induced transparency (PIT). In a single polarization state, the computational results reveal that synchronous or asynchronous six-mode electro-optical switching modulation may be performed by modifying the Fermi levels of graphene, with a maximum modulation degree of amplitude (MDA) of 97.6% at 5.148 THz. In addition, by varying the polarization angle, a polarization-sensitive, tunable polarization beam splitter (PBS) with an extinction ratio and insertion loss of 19.6 dB and 0.35 dB at 6.143 THz, respectively, and a frequency modulation degree of 25.2% was realized. Combining PIT with polarization sensitivity provides a viable platform and concept for developing graphene metasurface-based multifunctional and tunable polarization devices.

We investigate a nonparametric, varying coefficient regression approach for modeling and estimating the regression effects caused by two functionally correlated datasets. Due to modern biomedical technology to measure multiple patient features during a time interval or intermittently at several discrete time points to review underlying biological mechanisms, statistical models that do not properly incorporate interventions and their dynamic responses may lead to biased estimates of the intervention effects. We propose a shared parameter change point function-on-function regression model to evaluate the pre- and post-intervention time trends and develop a likelihood-based method for estimating the intervention effects and other parameters. We also propose new methods for estimating and hypothesis testing regression parameters for functional data via reproducing kernel Hilbert space. The estimators of regression parameters are closed-form without computation of the inverse of a large matrix, and hence are less computationally demanding and more applicable. By establishing a representation theorem and a functional central limit theorem, the asymptotic properties of the proposed estimators are obtained, and the corresponding hypothesis tests are proposed. Application and the statistical properties of our method are demonstrated through an immunotherapy clinical trial of advanced myeloma and simulation studies.

Reliability of nonvolatile resistive switching devices is the key point for practical applications of next-generation nonvolatile memories. Nowadays, nanostructured organic/inorganic heterojunction composites have gained wide attention due to their application potential in terms of large scalability and low-cost fabrication technique. In this study, the interaction between polyvinyl alcohol (PVA) and two-dimensional material molybdenum disulfide (MoS2) with different mixing ratios was investigated. The result confirms that the optimal ratio of PVA:MoS2 is 4:1, which presents an excellent resistive switching behavior. Moreover, we propose a resistive switching model of Ag/ZnO/PVA:MoS2/ITO bilayer structure, which inserts the ZnO as the protective layer between the electrode and the composite film. Compared with the device without ZnO layer structure, the resistive switching performance of Ag/ZnO/PVA:MoS2/ITO was improved greatly. Furthermore, a large resistive memory window up to 104 was observed in the Ag/ZnO/PVA:MoS2/ITO device, which enhanced at least three orders of magnitude more than the Ag/PVA:MoS2/ITO device. The proposed nanostructured Ag/ZnO/PVA:MoS2/ITO device has shown great application potential for the nonvolatile multilevel data storage memory.

Surface anti-reflection (AR) with nanometer-scaled texture has shown excellent light trapping performance involving optical devices. In this work, we developed a simple and lithography-free structure replication process to obtain large scale surface cup-shaped nano-pillar (CSNP) arrays for the first time. A method of depositing was used for pattern transfer based on PMMA pre-coated through-hole anodic aluminum oxide (AAO) thin film (~500 nm), and eventually, the uniformity of the transferred nanostructures was guaranteed. From the spectrum (250 nm~2000 nm) dependent measurements, the CSNP nanostructured Si showed excellent AR performance when compared with that of the single-polished Si. Moreover, the CSNP was found to be polarization insensitive and less dependent on incidence angles (≤80°) over the whole spectrum. To further prove the excellent antireflective properties of the CSNP structure, thin film solar cell models were built and studied. The maximum value of Jph for CSNP solar cells shows obvious improvement comparing with that of the cylinder, cone and parabola structured ones. Specifically, in comparison with the optimized Si3N4 thin film solar cell, an increment of 54.64% has been achieved for the CSNP thin film solar cell.

In this paper, the cylindrical, conical and parabolic nanostructures inherited from self-organized anodic aluminum oxide (AAO) are applied to silicon-based ultra-thin solar cells aiming for a new design concept for low-cost, high-efficiency double-grating solar cells. Numerical results reveal that the optimal bottom metal grating can enhance the absorption capacity of ultra-thin solar cell at 0.5 µm–1.1 µm waveband with a very small parasitic absorption. Meanwhile the surface grating with a period of 0.1 µm can strongly enhance the absorption of solar cell in 0.3 µm–0.5 µm waveband. Consequently, the silicon-based ultra-thin solar cell inherited their characteristics very well when both the optimal silicon surface grating and bottom metal grating are applied at the same time, thereby increasing the absorption rate of the solar cell in the entire waveband. Compared to the solar cell with single surface grating and the one with single bottom metal grating, the photocurrent density increments of the double-grating nanostructured solar cells can reach as high as 75.47% and 40.69%, respectively. Further results show that the conical and parabolic nanostructured gratings have higher light absorption efficiency and lower structure morphology-dependent sensitivity than the cylindrical nanostructured one, which is more conducive to the application of high efficiency ultra-thin solar cells.

Surface anti-reflection (AR) with micrometer or nanometer scaled surface texture has been studied extensively and showed excellent light extraction (or harvest) performance in corresponding opto-electronic devices. In this paper, a 2-inch anodized aluminum oxide (AAO) template with nano/micro hybrid structure was obtained directly through a simple lithography-free aluminum anodization process for the first time. This new nano/micro hybrid structure combines the advantages of sub-100 nm sub-wavelength structure (SWS) and micrometer scaled surface roughening. Aluminum grains were found to rearrange the distribution of the penetrated surface current during the anodization and eventually induced the micrometer scaled fluctuation underneath. The ultra-thin AAO replication scheme was introduced to fabricate and study the spectrum (300 nm to 800 nm) dependent AR performance of the nano/micro hybrid PDMS structure, which obtained an AR enhancement fraction of more than 42% higher than that of the nano-patterned one. Thin film and GaN based light-emitting diode (LED, 450 nm) models were built and studied. Compared to the flat LED, the AR enhancement of the nano/micro structured one can reach as high as more than 3 folds. These results suggest the nano/micro hybrid structure could be a good alternative for the applications of surface AR structure.

Nonalcoholic steatohepatitis (NASH), the advanced stage of nonalcoholic fatty liver disease (NAFLD), is emerging as a leading cause of progressive liver fibrosis and end-stage liver disease. Liver macrophages, mainly composed of Kupffer cells (KCs) and monocyte-derived macrophages (MoMFs), play a vital role in NASH progression and regression. Recent advances suggest that cell–cell communication is a fundamental feature of hepatic microenvironment. The reprogramming of cell–cell signaling between macrophages and surrounding cells contributes to the pathogenesis of NASH. In this review, we summarize the current knowledge of NASH regarding the composition of liver macrophages and their communication with surrounding cells, which are composed of hepatocytes, hepatic stellate cells (HSCs), liver sinusoidal endothelial cells (LSECs) and other immune cells. We also discuss the potential therapeutic strategies based on the level of macrophages.

Indium tin oxide (ITO) has been studied for applications at normal high temperatures, below 600°C, due to its excellent electrical characteristics. In an attempt to further match the needs of electronics for use in extremely harsh environments, the changes in the conductive properties of ITO films and their mechanism were investigated at special high-temperatures above 1,000°C. ITO films were prepared by pulsed laser deposition (PLD) onto lanthanum gallium silicate (LGS) substrates. Furthermore, the as-deposited samples were annealed with different temperature-time treatments, and we investigated the effects of annealing on the electrical, structure, surface morphology and chemical properties of the ITO films by X-ray diffraction analysis, scanning electron microscopy (SEM), resistance measurements, and X-ray photoelectron spectroscopy (XPS). The experimental results showed that the decreased resistance of the ITO films was mainly attributed to the increase in the crystalline size and the increased amount of Sn4+ ions during the heating period (0–1,000°C). Generally, the ITO films showed stable electrical properties when they were heated at 1,000°C for at least 2.5 h. As expected, the ITO films that remained steady above 1,000°C have potential applications as electrodes working in special high-temperature environments.

The positive bias temperature instability (PBTI) reliability of buried InGaAs channel n-MOSFETs with an InP barrier layer and Al2O3 gate dielectric under medium field (2.7 MV/cm) and high field (5.0 MV/cm) are investigated in this paper. The Al2O3/InP interface of the insertion of an InP barrier layer has fewer interface and border traps compared to that of the Al2O3/InGaAs interface. The subthreshold slope, transconductance, and shift of Vg are studied by using the direct-current Id-Vg measurements under the PBTI stress. The experimental results show that the degradation of positive ΔVg under the medium field stress is mainly caused by the acceptor trap, while the donor trap under the high field stress become dominant in the subthreshold region, which leads to the negative shift in Vg. The medium field stress-induced acceptor traps are attributed by the InP barrier layer in the subthreshold region, resulting that the low leakage current can be achieved in the buried InGaAs channel n-MOSFETs with an InP barrier layer compared to the surface InGaAs channel n-MOSFETs.

A novel SiC/Si heterojunction lateral double-diffused metal-oxidesemiconductor (LDMOS) with a reversed L-shaped field plate and a stepped oxide layer has been proposed to improve the tradeoff between the breakdown voltage (BV) and specific on-resistance (Ron,sp). The reversed L-shaped field plate is applied to modulate electric field distribution to make the breakdown occur in the low electric field area (SiC/Si interface), which increases the BV and decreases the Ron,sp of the device. Furthermore, a stepped oxide layer is used to cover the Si drift region and reshape the lateral electric field distribution by introducing a new electric field peak, which consequently enhances the BV. The simulated results have indicated that the BV of this proposed SiC/Si LDMOS increased from 226 V and 720 V to 992 V compared with the conventional Si LDMOS and SiC LDMOS, respectively, while maintaining a low Ron,sp of 27.62 mΩ·cm2.

The intriguing properties of the toroidal mode (TM) resonance can potentially promote a low-loss light–matter interaction. This study proposes an electromagnetically induced transparency (EIT) resonance with a high quality factor, which can reach 7798, and low mode volume can reach 0.009 μ m ^3 , high contrast ratio can reach nearly 100%, in the near-infrared region, which is generated by the magnetic TM in a reverse-symmetric coupling spiral metasurface. A two-oscillator model can only explain the influence of near-field coupling at the EIT point for weak coupling. Moreover, a multipole decomposition method shows that the excitation mechanism of EIT resonances originates from the destructive interference between the subradiant modes (magnetic toroidal dipole-electric quadrupole) and magnetic dipole resonance. Consequently, a new general extinction spectrum interference model is applied to fit all coupling conditions for both weak and strong coupling results that perfectly correspond to the multipole decomposition method. The results of this study could be useful in the analysis and understanding of the electromagnetic coupling characteristics of nanoparticles and provide a design approach for novel metasurfaces for low-loss optical applications.

A novel silicon-on-insulator (SOI) lateral double-diffused metal-oxide-semiconductor (LDMOS) structure has been proposed. The new structure features a substrate field plate (SFP) and a variable-k dielectric buried layer (VKBL). The SFP and VKBL improve the breakdown voltage by introducing new electric field peaks in the surface electric field distribution. Moreover, the SFP reduces the specific ON-resistance through an enhanced auxiliary depletion effect on the drift region. The simulation results indicate that compared to the conventional SOI LDMOS structure, the breakdown voltage is improved from 118 V to 221 V, the specific ON-resistance is decreased from 7.15 mΩ·cm2 to 3.81 mΩ·cm2, the peak value of surface temperature is declined by 38 K. Keywords: SOI LDMOS, Field plate, Variable-k dielectric, Breakdown voltage, Specific ON-resistance

Abstract Background Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins. Results We design four different deep learning architectures to predict protein torsion angles. The architectures including deep neural network (DNN) and deep restricted Boltzmann machine (DRBN), deep recurrent neural network (DRNN) and deep recurrent restricted Boltzmann machine (DReRBM) since the protein torsion angle prediction is a sequence related problem. In addition to existing protein features, two new features (predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments) are used as input to each of the four deep learning architectures to predict phi and psi angles of protein backbone. The mean absolute error (MAE) of phi and psi angles predicted by DRNN, DReRBM, DRBM and DNN is about 20–21° and 29–30° on an independent dataset. The MAE of phi angle is comparable to the existing methods, but the MAE of psi angle is 29°, 2° lower than the existing methods. On the latest CASP12 targets, our methods also achieved the performance better than or comparable to a state-of-the art method. Conclusions Our experiment demonstrates that deep learning is a valuable method for predicting protein torsion angles. The deep recurrent network architecture performs slightly better than deep feed-forward architecture, and the predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments are useful features for improving prediction accuracy.

Abstract We experimentally demonstrate a highly efficient, broadband linear polarization converter functioning at terahertz frequencies. The linear polarization converter is composed of three metasurfaces and two dielectric layers interlaced with each other. The neighboring unit cells of the central metasurface layer of the linear polarization converter exhibit strong electromagnetic coupling, which increases the number of resonances and results in significant bandwidth broadening. The simulation and experimental results show that in the frequency range of 0.2 to 0.4 THz, the proposed polarization converter has a flat transmission curve and exhibits a transmission efficiency that is higher than 80%. High performance terahertz polarization conversion is desirable in many fields, such as terahertz spectroscopy, imaging, and communications.

In this article, we demonstrated novel methods to improve the performance of p-i-n photodetectors (PDs) on a germanium-on-insulator (GOI). For GOI photodetectors with a mesa diameter of 10 μm, the dark current at −1 V is 2.5 nA, which is 2.6-fold lower than that of the Ge PD processed on Si substrates. This improvement in dark current is due to the careful removal of the defected Ge layer, which is formed with the initial growth of Ge on Si. The bulk leakage current density and surface leakage density of the GOI detector at −1 V are as low as 1.79 mA/cm2 and 0.34 μA/cm, respectively. GOI photodetectors with responsivity of 0.5 and 0.9 A/W at 1550 and 1310 nm wavelength are demonstrated. The optical performance of the GOI photodetector could be remarkably improved by integrating a tetraethylorthosilicate (TEOS) layer on the oxide side due to the better optical confinement and resonant cavity effect. These PDs with high performances and full compatibility with Si CMOS processes are attractive for applications in both telecommunications and monolithic optoelectronics integration on the same chip.

Herein, we propose a tunable plasmonic sensor with Fano resonators in an inverted U-shaped resonator. By manipulating the sharp asymmetric Fano resonance peaks, a high-sensitivity refractive index sensor can be realized. Using the multimode interference coupled-mode theory and the finite element method, we numerically simulate the influences of geometrical parameters on the plasmonic sensor. Optimizing the structure parameters, we can achieve a high plasmonic sensor with the maximum sensitivity for 840 nm/RIUand figure of merit for 3.9 × 105. The research results provide a reliable theoretical basis for designing high sensitivity to the next generation plasmonic nanosensor.

In this paper, a multi-parameter integrated detection photonic crystal fiber (PCF) sensor based on surface plasmon resonance (SPR) is proposed for its application in detecting temperature, magnetic field, and refractive index. The air holes on both sides of the fiber core were coated with gold film and introduced to the temperature-sensitive medium (PDMS) and magnetic fluid (MF), detecting temperature and magnetic field, respectively. The graphene layer is also presented on the gold film of the D-type side polished surface to improve the sensor sensitivity. The sensor’s critical parameters’ influence on its performance is investigated using a mode solver based on the finite element method (FEM). Simulation results show when the samples refractive index (RI) detection is a range of 1.36~1.43, magnetic field detection is a range of 20~550 Oe, and the temperature detection is a range of 5~55 °C; the maximum sensor’s sensitivity obtains 76,000 nm/RIU, magnetic field intensity sensitivity produces 164.06 pm/Oe, and temperature sensitivity obtains −5001.31 pm/°C.

The optical properties and band structure evolution from amorphous to crystalline Ga2O3 films was investigated in this work. Amorphous and crystalline Ga2O3 films were obtained by changing the growth substrate temperatures of pulsed laser deposition and the crystallinity increase with the rising of substrate temperature. The bandgap value and ultraviolet emission intensity of the films increase with the rising of crystallinity as observed by means of spectrophotometer and cathodoluminescence spectroscopy. Abrupt bandgap value and CL emission variations were observed when amorphous to crystalline transition took place. X-ray photoelectron spectroscopy core level spectra reveal that more oxygen vacancies and disorders exist in amorphous Ga2O3 film grown at lower substrate temperature. The valence band spectra of hard X-ray photoelectron spectroscopy present the main contribution from Ga 4sp for crystalline film deposited at substrate temperature of 500 oC, while extra subgap states has been observed in amorphous film deposited at 300 oC. The oxygen vacancy and the extra subgap density of states are suggested to be the parts of origin of bandgap and CL spectra variations. The experimental data above yields a realistic picture of optical properties and band structure variation for the amorphous to crystalline transition of Ga2O3 films.