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A new set of BN-MR emitters based on the para B–π–B skeleton have been developed and showed impressive EQEs with low efficiency roll-offs and extended operation stability.

Chip floorplanning has long been a critical task with high computation complexity in the physical implementation of VLSI chips. Its key objective is to determine the initial locations of large chip modules with minimized wirelength while adhering to the density constraint, which in essence is a process of constructing an optimized mapping from circuit connectivity to physical locations. Proven to be an NP-hard problem, chip floorplanning is difficult to be solved efficiently using algorithmic approaches. This article presents GraphPlanner, a variational graph-convolutional-network-based deep learning technique for chip floorplanning. GraphPlanner is able to learn an optimized and generalized mapping between circuit connectivity and physical wirelength and produce a chip floorplan using efficient model inference. GraphPlanner is further equipped with an efficient clustering method, a unification of hyperedge coarsening with graph spectral clustering, to partition a large-scale netlist into high-quality clusters with minimized inter-cluster weighted connectivity. GraphPlanner has been integrated with two state-of-the-art mixed-size placers. Experimental studies using both academic benchmarks and industrial designs demonstrate that compared to state-of-the-art mixed-size placers alone, GraphPlanner improves placement runtime by 25% with 4% wirelength reduction on average.

Fast verification for the extremely large-scale power grid is demanding as CMOS technology advances consistently. In this work, we propose ESPSim, an efficient scalable power grid simulator based on a parallel smoothed aggregation-based algebraic multigrid technique. ESPSim has the ability to do fast DC and transient analysis through MPI and adaptive timestep control mechanism. Thanks to the smoother applied on the prolongation operator, ESPSim copes well with the convergence rate on extremely large-scale power grid transient analysis. Extensive experiments are conducted with a variety of serial/parallel solvers. The runtime of ESPSim is linear with case size. With 16 processors, 1,000 timesteps transient analysis of 63.4M nodes can be completed in 22.1 min. Over 22× speedup compared to the well-known direct solver Cholmod is observed.

The structure of parabolic condensers makes them susceptible to wind load because of their thin and large windward mirrors. In this paper, the wind pressure on a model of a condenser mirror (1:35) on multistorey flat roofs is analysed via pressure measurement in a wind tunnel. The mean wind-pressure distribution law of flat-roof condenser mirrors (including the change law with working conditions and the maximum distribution characteristics) and the distribution law of fluctuating and extreme wind pressure are obtained. Furthermore, by comparison with the ground-based condenser distribution law, similarities and differences between the two are obtained. Research results show that the wind-pressure distribution law of flat-roof parabolic condenser mirrors is the same as those on the ground, but the mean wind-pressure coefficient (absolute value) is generally ~30% smaller. Furthermore, the maximum effect is generally located at the windward mirror edge and the mirror is more susceptible to wind pressure in wind directions of 30° and 135°–150°. The results of this study can provide a theoretical reference for wind-resistant structure design and multistorey flat-roof condenser-related research.

The differential tumor environment guides various antitumor drug delivery strategies for efficient cancer treatment. Here, based on the special bacteria-enriched tumor environment, we report a different drug delivery strategy by targeting bacteria inhabiting tumor sites. With a tissue microarray analysis, it was found that bacteria amounts displayed significant differences between tumor and normal tissues. Bacteria-targeted mesoporous silica nanoparticles decorated with bacterial lipoteichoic acid (LTA) antibody (LTA-MSNs) could precisely target bacteria in tumors and deliver antitumor drugs. By the intravenous administration of bacteria-targeted nanoparticles, we showed in mice with colon cancer, lung cancer, and breast cancer that LTA-MSNs exhibited a high tumor-targeting ability. As a proof-of-concept study, tumor microbes as some of the characteristics of a tumor environment could be utilized as potential targets for tumor targeting. This bacteria-guided tumor-targeting strategy might have great potential in differential drug delivery and cancer treatment.

With the aggressive and amazing scaling of the feature size of semiconductors, hotspot detection has become a crucial and challenging problem in the generation of optimized mask design for better printability. Machine learning techniques, especially deep learning, have attained notable success on hotspot detection tasks. However, most existing hotspot detectors suffer from suboptimal performance due to two-stage flow and less efficient representations of layout features. What is more, most works can only solve simple benchmarks with apparent hotspot patterns like ICCAD 2012 Contest benchmarks. In this paper, we firstly develop a new end-to-end hotspot detection flow where layout feature embedding and hotspot detection are jointly performed. An attention mechanism-based deep convolutional neural network is exploited as the backbone to learn embeddings for layout features and classify the hotspots simultaneously. Experimental results demonstrate that our framework achieves accuracy improvement over prior arts with fewer false alarms and faster inference speed on much more challenging benchmarks.

Stable deep blue multiresonance emitters with small full width at half maximum (FWHM) are attractive for wide color-gamut organic light-emitting diodes (OLEDs). However, the steric repulsion from the spatially close hydrogens would twist the multiresonance skeletons, causing spectral broadening and molecular instability issues. Here, we strategically introduce a mesitylboron locking unit into a carbazole-embedded multiresonance model emitter, alleviating the hydrogen repulsions and also strengthening the para-positioned weak carbon-nitrogen bond in anionic states. An emission peaking at 452 nm with an FWHM of merely 14 nm and nearly BT.2020 blue chromaticity coordinates are obtained in toluene, affording a high maximum external quantum efficiency of 33.9% in a sensitizing device. Moreover, an impressive LT97 (time to decay to 97% of the initial luminance) of 178 hours at a constant current density of 12 mA/cm 2 was achieved in a stable device with a small y coordinate of 0.057, nearly 20 times longer than the model emitter with even a substantially red-shifted emission.

The pursuit of ideal short-delayed thermally activated delayed fluorescence (TADF) emitters is hampered by the mutual exclusion of a small singlet-triplet energy gap (ΔEST) and a large oscillator strength (f). Here, by attaching an multiresonance-acceptor onto a sterically-uncrowded donor, we report TADF emitters bearing hybrid electronic excitations with a main donor-to-acceptor long-range (LR) and an auxiliary bridge-phenyl short-range (SR) charge-transfer characters, balancing a small ΔEST and a large f. Moreover, the incorporation of dual equivalent multiresonance-acceptors is found to double the f value without affecting the ΔEST. A large radiative decay rate over an order of magnitude higher than the intersystem crossing (ISC) rate, and a decent reverse ISC rate of >106 s−1 are simultaneously obtained in one emitter, leading to a short delayed-lifetime of ~0.88 μs. The corresponding organic light-emitting diode exhibits a record-high maximum external quantum efficiency of 40.4% with alleviated efficiency roll-off and extended lifetime.

Porcine epidemic diarrhea virus (PEDV) infection causes lethal watery diarrhea and high mortality in neonatal piglets, leading to huge economic losses in the global swine industry. Currently, the existing commercial vaccines cannot fully control PEDV, so it is urgent to develop effective antiviral agents to complement vaccine therapy. In the present study, we investigated the antiviral effect of Hypericum japonicum extract (HJ) against PEDV in vivo and in vitro. In in vitro assays, HJ could directly inactivate PEDV strains; moreover, it inhibited the proliferation of PEDV strains in Vero or IPI-FX cells at its non-cytotoxic concentrations. Time of addition assays revealed that HJ mainly inhibited PEDV at the later stages of the viral life cycle. In in vivo, compared with the model group, HJ could reduce the viral titers in the intestines of infected piglets, and improve their intestinal pathological, indicating that HJ could protect the newborn piglets from highly pathogenic PEDV variant infection. Furthermore, this effect may be related to the fact that HJ can not only directly inhibit viruses, but also regulate the structure of intestinal microbiota. In conclusion, our results indicate that Hypericum japonicum could inhibit PEDV replication in vitro and in vivo and might possess the potential to develop as the anti-PEDV drug.

Background: Endothelial cells in the tumor microenvironment play an important role in the development of kidney renal clear cell carcinoma (KIRC). We wanted to further identify the function of endothelial cells in KIRC patients by integrating single-cell and bulk RNA sequencing data.Methods: Online databases provide the original data of this study. An endothelial-related prognostic index (ERPI) was constructed and validated by R version 3.6.3 and relative packages.Results: The ERPI consisted of three genes (CCND1, MALL, and VWF). Patients with high ERPI scores were significantly correlated with worse prognosis than those with low ERPI scores in the TCGA training group, TCGA test group, and GSE29609 group. A positive correlation was identified between the ERPI score and poor clinical features. The results of functional analysis indicated that ERPI was significantly associated with immune-related activities. We suggested that patients with high ERPI scores were more likely to benefit from immunotherapy based on the results of immune checkpoints, tumor microenvironment, stemness index, and TCIA, while patients with low ERPI scores were sensitive to gemcitabine, docetaxel, paclitaxel, axitinib, pazopanib, sorafenib, and temsirolimus according to the results of the “pRRophetic” algorithm. Therefore, this ERPI may help doctors choose the optimal treatment for patients with KIRC.Conclusion: By integrating single-cell and bulk RNA sequencing data from KIRC patients, we successfully identified the key genes from the perspective of endothelial cells in the tumor microenvironment and constructed ERPIs that had positive implications in precision medicine.

In this paper, a novel Asymptotic Probability Estimation (APE) method is proposed to estimate the probability of correlated rare failure events for complex integrated systems containing a large number of replicated cells. The key idea is to approximate the failure rate of the entire system by solving a set of nonlinear equations derived from a general analytical model. An error refinement method based on Look-up Table (LUT) is further developed to improve numerical stability and, hence, reduce estimation error. Furthermore, a statistical algorithm based on re-sampling is developed to accurately estimate the confidence interval of APE. Our numerical experiments demonstrate that compared to the state-of-the-art method, APE can reduce the estimation error by up to 30× without increasing the computational cost.

In this paper, to accurately estimate the rare failure rates for large-scale circuits (e.g., SRAM) where process variations are modeled as truncated normal distributions in high-dimensional space, we propose a novel truncated scaled-sigma sampling (T-SSS) method. Similar to scaled-sigma sampling (SSS), T-SSS distorts the truncated normal distributions by a scaling factor, resulting in an analytical model for failure rate estimation. By drawing random samples from the distorted distribution and estimating a sequence of scaled failure rates, we can solve all unknown model coefficients and predict the original failure rate by extrapolation. The accuracy of T-SSS is further assessed by estimating its confidence interval (CI) based on re-sampling. Our numerical results demonstrate that the proposed T-SSS method can achieve superior accuracy over the state-of-the-art method without increasing the computational cost.

As the circuit feature size continuously shrinks down, hotspot detection has become a more challenging problem in modern DFM flows. Developed deep learning techniques have recently shown their superiorities on hotspot detection tasks. However, existing hotspot detectors can only handle defect detection from one small layout clip each time, thus may be very time-consuming when dealing with a large full-chip layout. In this paper, we develop a new end-to-end framework that can detect multiple hotspots in a large region at a time and promise a better hotspot detection performance. We design a joint auto-encoder and inception module for efficient feature extraction. A two-stage classification and regression framework is designed to detect hotspot with progressive accurate localization, which provides a promising performance improvement. Experimental results show that our framework enables a significant speed improvement over existing methods with higher accuracy and fewer false alarms.

Mediating induced abscisic acid (ABA) biosynthesis is important for enhancing plant stress tolerance. Here, we found that rice (Oryza sativa L.) osa–miR2105 (miR2105) and the Stress/ABA-activated protein kinase (OsSAPK10) coordinately regulate the rice basic region-leucine zipper transcription factor (bZIP TF; OsbZIP86) at the posttranscriptional and posttranslational levels to control drought-induced ABA biosynthesis via modulation of rice 9-cis-epoxycarotenoid dioxygenase (OsNCED3) expression. OsbZIP86 expression is regulated by miR2105-directed cleavage of the OsbZIP86 mRNA. OsbZIP86 encodes a nuclear TF that binds to the promoter of the ABA biosynthetic gene OsNCED3. OsSAPK10 can phosphorylate and activate OsbZIP86 to enhance the expression of OsNCED3. Under normal growth conditions, altered expression of miR2105 and OsbZIP86 displayed no substantial effect on rice growth. However, under drought conditions, miR2105 knockdown or OsbZIP86 overexpression transgenic rice plants showed higher ABA content, enhanced tolerance to drought, lower rates of water loss, and more stomatal closure of seedlings, compared with wild-type rice Zhonghua 11; in contrast, miR2105 overexpression, OsbZIP86 downregulation, and OsbZIP86 knockout plants displayed opposite phenotypes. Collectively, our results show that the “miR2105-(OsSAPK10)-OsbZIP86-OsNCED3” module regulates the drought-induced ABA biosynthesis without penalty on rice growth under normal conditions, suggesting candidates for improving drought tolerance in rice.

Radiotherapy is widely applied for multiple malignant tumors ablation in the clinic. However, redundant doses of X-rays might destroy normal tissue in the periphery of tumor sites. Here, we developed an integrated nanosystem (Bac@BNP) composed of engineered bacteria (Bac) and Bisub2/subSsub3/subnanoparticles (BNPs) for sensitizing radiotherapy. Bac could target and colonize in tumor sites alternatively, which overexpressed cytolysin A (ClyA) protein to regulate the cell cycle from a radioresistant phase to a radiosensitive phase. Simultaneously, peptide-modified BNPs, as a radiosensitizer with a high-Z element, was released from the surface of Bac owing to the matrix metalloproteinase-2 (MMP-2) response in the tumor microenvironment. Under X-ray irradiation, BNPs could enhance the radiotherapy sensitivity by triggering the intracellular generation of reactive oxygen species (ROS), coupled with DNA damage. In this constructed nanosystem, the combination of Bac@BNP and X-ray irradiation led to significant suppression of breast carcinoma in murine models with reduced side effects.

An advanced concept of using ultra-narrowband emitters to improve the stability of deep-blue OLEDs is proposed and two proof-of-concept deep-blue emitters are developed.

Mitogen-activated protein kinase kinase kinase 4 (MAP3K4) is a multifunctional mediator of the conserved MAPK signaling pathway that plays essential roles in the regulation of immune responses in mammals. However, the function of teleost MAP3K4s in innate immunity, especially in the intestinal immune system, is still poorly understood. In the current study, we identified a fish MAP3K4 homolog (CiMAP3K4) in Ctenopharyngodon idella as well as its immune function in intestine following bacterial infection in vivo and in vitro. The open reading frame (ORF) of CiMAP3K4 encodes putative peptide of 1544 amino acids containing a predicted serine/threonine protein kinase (S_TKc) domain with high identity with other fish MAP3K4s. Phylogenetic analysis revealed the CiMAP3K4 belonged to the fish cluster and showed the closest relationship to Pimephales promelas. Quantitative real-time PCR (qRT-PCR) analysis revealed that CiMAP3K4 transcripts were widely distributed in all tested tissues, especially with high expression in the muscle and intestine of healthy grass carp. In vitro, CiMAP3K4 gene expression was upregulated by bacterial PAMPs (lipolysaccharide (LPS), peptidoglycan (PGN), L-Ala-γ-D-Glu-meso-diaminopimelic acid (Tri-DAP) and muramyl dipeptide (MDP)) and pathogens (Aeromonas hydrophila and Aeromonas veronii) in primary intestinal cells. In vivo, the mRNA expression levels of CiMAP3K4 in the intestine were significantly induced by bacterial MDP challenge in a time-dependent manner; however, this effect could be inhibited by the bioactive dipeptides β-alanyl- l -histidine (carnosine) and alanyl-glutamine (Ala-Gln). Moreover, CiMAP3K4 was located primarily in the cytoplasm, and its overexpression increased the transcriptional activity of AP-1 in HEK293T cells. Collectively, these results suggested that CiMAP3K4 might play an important role in the intestinal immune response to bacterial infections, which paves the way for a better understanding of the intestinal immune system of grass carp.

The pursuit of ideal narrowband yellow multi-resonance (MR) emitters is hampered by the mutual constraints of effective spectral redshift and maintaining a small full width at half maximum (FWHM) value. Here, we report a novel multiple fusion molecular design strategy to break this trade-off. Compared with the selected narrowband parent core, the specific multiple MR effects in target molecules can simultaneously extend the π-conjugation length, increase the rigidity of the structure, and reduce the vibrational frequency. Proof-of-concept emitters BN-DICz and DBN-ICz show bright yellowish green to yellow emissions in dilute toluene solutions with peaks at 533-542 nm and extremely small FWHMs of ≤ 20 nm. Notably, BN-DICz based electroluminescent device exhibits excellent efficiencies of 37.4%, 136.6 cd/A, and 119.2 lm/W with an FWHM of merely 23 nm, representing the best performance for yellow MR organic light-emitting diodes. This article is protected by copyright. All rights reserved.

Altered glycan levels in serum have been associated with increased risk of cancer. In this study, we have developed and validated a HPLC-based method to analyze monosaccharide composition (D-mannose, Glucosamine, Galactosamine, Glucuronic acid, D-glucose, D-galactose, D-xylose, L-fucose) in human serum, with L-rhamnose, being used as internal standard. Monosaccharides obtained from hydrolyzed serum samples were derivatized by 1-Phenyl-3-methyl-5-pyrazolone. A ZORBAX XDB-C18 column(150×4.6mm) was used for chromatographic separation with 100 mM ammonium acetate buffer (NH4Ac-HAc, PH=5.5, solvent A), acetonitrile (ACN, solvent B) as a mobile phase. The calibration standard curves for the eight monosaccharides showed good linearity over the range of 2.5-500μg/mL with R2 > 0.995. The relative standard deviation values for intra-day and inter-day precision were ≤ 5.49%. Recovery was 69.01-108.96%. We observed that this column exhibited high specificity and selectivity to separate monosaccharides from serum. This method was then applied to quantitatively analyze the serum monosaccharide levels in 30 patients with endometrial cancer and 30 matched healthy controls. Statistical analysis indicated that the serum monosaccharide levels were significantly higher in patients compared with healthy controls (P value< 0.0001). Overall, we report here a simple, reliable, low-cost, and reproducible HPLC method for the separation and quantification monosaccharides in the human serum, which has potential value to serve as a screening marker for endometrial cancer.

The pursuit of ideal thermally activated delayed fluorescent (TADF) emitters is hampered by the mutual exclusion of a small singlet-triplet energy gap (ΔEST) and a large oscillator strength (f). Here, we report a novel donor-multiresonance bridge-acceptor (D-MR-A) molecular design strategy to break this trade-off. The incorporation of a MR-bridged acceptor onto a sterically-uncrowded donor creates a hybrid orbital distribution combining a short-range MR charge transfer (CT) on the bridge and a long-range donor-to-acceptor CT, thus leading to a small ΔEST and a large f simultaneously. Moreover, incorporating dual MR-A groups is found to double the f value without affecting ΔEST. A large radiative decay rate over an order of magnitude higher than the intersystem crossing (ISC) rate, and a decent reverse ISC rate of > 106 s− 1 are thereafter obtained in a proof-of-concept emitter, leading to a short-delayed lifetime(τD) of only 0.88 µs. The corresponding organic light-emitting diode exhibits a record high maximum external quantum efficiency of 41.2% with alleviated efficiency roll-off and extended lifetime.

In this paper, the flat roof Trough Condenser (FRTC) model is studied using a wind tunnel high frequency dynamic force measurement experiment. The Trough Condenser’s (TC) wind (torque) coefficients were obtained in six azimuths. The regularity and features of the wind coefficient when changing within a horizontal wind azimuth angle of 0°~360° and tilt angle of 0°~90° were analyzed. In addition, the TC on the flat roof and the TC installed on the ground were compared and analyzed. The results showed that the FRTC’s resistance coefficient, lift coefficient and fundament tilting torque coefficient are all much greater than the side force coefficient, side torque coefficient and azimuth torque coefficient. When designing the TC’s structure, the main consideration is the influence of resistance, fundament tilting torque and lift force. The maximal value of the resistance coefficient is 0.938, the maximal fundament tilting torque coefficient is 0.869, and the maximal value of the lift coefficient is −0.620. In addition, compared with the TC on the ground, the roof’s resistance coefficient is 67.39% lower, the lift coefficient is 130.65% lower and the fundament tilting torque coefficient is 68.01% lower. Furthermore, as the wind field on the roof is different from that on the ground, while the height of the condenser is lower, and the parapet shields the condenser to a certain extent, the maximum wind (torque) coefficient is also different when under different working conditions. Finally, the effect of the cone vortex on the roof’s edge also impacts these results.

BackgroundTuberculosis (TB) caused byMycobacterium tuberculosis(M. tb) remains a global health issue. The characterized virulentM. tbH37Rv, avirulentM. tbH37Ra and BCG strains are widely used as reference strains to investigate the mechanism of TB pathogenicity. Here, we attempted to determine metabolomic signatures associated with the Mycobacterial virulence in human macrophages through comparison of metabolite profile in THP-1-derived macrophages following exposure to theM. tbH37Rv,M. tbH37Ra and BCG strains.ResultsOur findings revealed remarkably changed metabolites in infected macrophages compared to uninfected macrophages. H37Rv infection specifically induced 247 differentially changed metabolites compared to H37Ra or BCG infection. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed H37Rv specifically induces tryptophan metabolism. Moreover, quantitative PCR (qPCR) results showed that indoleamine 2,3-dioxygenase 1 (IDO1) and tryptophan 2,3-dioxygenase 2 (TDO2) which converts the tryptophan to a series of biologically second metabolites were up-regulated in H37Rv-infected macrophages compared to H37Ra- or BCG-infected macrophages, confirming the result of enhanced tryptophan metabolism induced by H37Rv infection. These findings indicated that targeting tryptophan (Trp) metabolism may be a potential therapeutic strategy for pulmonary TB.ConclusionsWe identified a number of differentially changed metabolites that specifically induced in H37Rv infected macrophages. These signatures may be associated with the Mycobacterial virulence in human macrophages. The present findings provide a better understanding of the host response associated with the virulence of theMtbstrain.

Polycyclo-heteraborin multi-resonance (MR) emitters are promising for high color-purity organic light-emitting diodes (OLEDs). Here, unlike the most common heteroatom ternary-doped (X/B/N) frameworks, a binary-doped (B/N) skeleton is reported with a large energy band for wide-range color tunability. Based on this parent-segment, a "one-pot" catalyst-free borylation method is developed which generates deep blue to pure green MR emitters from readily available starting materials, with peaks at 426-532 nm and full-width-at-half-maxima of 27-38 nm. Impressively, a maximum external quantum efficiency of nearly 40 % is recorded for the corresponding device with Commission Internationale de l'Eclairage coordinates of (0.14, 0.16), representing the state-of-the-art performances. This work presents a new paradigm and synthesis of B/N-doped MR emitters and will motivate the study of other novel frameworks.

Mitogen-activated protein kinase kinase kinase 3 (MEKK3) is an evolutionarily conserved Ser/Thr protein kinase of the MEKK family that is essential for the host immune response to pathogen challenges in mammals. However, the immune function of MEKK3s in lower vertebrate species, especially in bony fish, remains largely unknown. In this study, a fish MEKK3 (designated CiMEKK3) gene was cloned and identified from grass carp (Ctenopharyngodon idella). The present CiMEKK3 cDNA encoded a 620 amino acid polypeptide containing a conserved S-TKc domain and a typical PB1 domain. Several potential immune-related transcription factor-binding sites, including activating protein 1 (AP-1), nuclear factor kappa B (NF-κB) and signal transducer and activator of downstream transcription 3 (STAT3), were observed in the 5’ upstream DNA sequence of CiMEKK3. A phylogenetic tree showed that CiMEKK3 exhibits a close evolutionary relationship with MEKK3s from Cyprinus carpio and Carassius auratus. Quantitative real-time PCR analysis revealed that CiMEKK3 transcripts were widely distributed in all selected tissues of healthy grass carp, with a relatively high levels observed in the gill, head kidney and intestine. Upon in vitro challenge with bacterial pathogens (Aeromonas hydrophila and Aeromonas veronii) and pathogen-associated molecular patterns (PAMPs) (lipopolysaccharide (LPS), peptidoglycan (PGN), L-Ala-γ-D-Glu-mDAP (Tri-DAP) and muramyl dipeptide (MDP)), the expression levels of CiMEKK3 in the intestinal cells of grass carp were shown to be significantly upregulated in a time-dependent manner. In vivo injection experiments revealed that CiMEKK3 transcripts were significantly induced by MDP challenge in the intestine; however, these effects could be inhibited by the nutritional dipeptides carnosine and Ala-Gln. Moreover, subcellular localization analysis and luciferase reporter assays indicated that CiMEKK3 could act as a cytoplasmic signal-transducing activator involved in the regulation of NF-κB and MAPK/AP-1 signaling cascades in HEK293T cells. Taken together, these findings strongly suggest that CiMEKK3 plays vital roles in the intestinal immune response to bacterial challenges, which will aid in understanding the pathogenesis of inflammatory bowel disease in bony fish.

Silicon carbide (SiC) is regarded as a promising semiconductor owing to its wide band gap and high thermal conductivity. Meanwhile, it possesses issues such as interface properties, which may affect the performance of SiC substrate power devices (e.g. MOSFET), especially when compared with similarly structured silicon appliances. Given that the development of SiC semiconductor devices has a number of commonalities with conventional silicon-based semiconductors, titanium dioxide (TiO2), a material that has a great track record in Si-based semiconductor devices, has been chosen for investigation in this work. Although TiO2 is not capable of being a gate dielectric alone on the SiC substrate because of its relatively narrow band gap, it can be adopted into composite or multilayer gate dielectrics to reach satisfying characteristics. As such, the interfacial state and heterostructure between TiO2 and SiC remain worthy being researched. In the present study, the properties of atomic layer deposited (ALD) TiO2 films on silicon substrates were compared with those on 4H-SiC substrates via x-ray photoelectron spectroscopy, atomic force microscopy, and x-ray reflectometry. It is shown that the interface state between ALD TiO2 film and both types of substrates as-deposited have similar chemical conditions, whereby TiO2 layer barely react with substrates, containing great amount of oxygen vacancies. According to band alignment calculations, heterostructure of both samples are type-II heterojunctions with negatively shifted conduction band. Although the large bandwidth of 4H-SiC hinders the use of TiO2 as a gate dielectric in power devices, this structure has the potential for other semiconductor products.

Layout hotspot detection is of great importance in the physical verification flow. Deep neural network models have been applied to hotspot detection and achieved great successes. The layouts can be viewed as binary images. The binarized neural network (BNN) can thus be suitable for the hotspot detection problem. In this article, we propose a new deep learning architecture based on BNNs to speed up the neural networks in hotspot detection. A new binarized residual neural network is carefully designed for hotspot detection. Experimental results on ICCAD 2012 and 2019 benchmarks show that our architecture outperforms previous hotspot detectors in detecting accuracy and has an $8\times $ speedup over the best deep learning-based solution. Since the BNN-based model is quite computationally efficient, a good tradeoff can be achieved between the efficiency and performance of the hotspot detector by applying ensemble learning approaches. Experimental results show that the ensemble models achieve better hotspot detection performance than the original with acceptable speed loss.

Here, a methacrylate-modified pyridone derivative (mPYR) was loaded into a porphyrin nanoscale metal–organic framework (porphyrin-nMOF). Then, the loaded mPYR was further polymerized to obtain poly...