Approaching the quantum limit in two-dimensional semiconductor contacts.

The development of next-generation electronics requires scaling of channel material thickness down to the two-dimensional limit while maintaining ultralow contact resistance1,2. Transition-metal dichalcogenides can sustain transistor scaling to the end of roadmap, but despite a myriad of efforts, the device performance remains contact-limited3-12. In particular, the contact resistance has not surpassed that of covalently bonded metal-semiconductor junctions owing to the intrinsic van der Waals gap, and the best contact technologies are facing stability issues3,7. Here we push the electrical contact of monolayer molybdenum disulfide close to the quantum limit by hybridization of energy bands with semi-metallic antimony ([Formula: see text]) through strong van der Waals interactions. The contacts exhibit a low contact resistance of 42 ohm micrometres and excellent stability at 125 degrees Celsius. Owing to improved contacts, short-channel molybdenum disulfide transistors show current saturation under one-volt drain bias with an on-state current of 1.23 milliamperes per micrometre, an on/off ratio over 108 and an intrinsic delay of 74 femtoseconds. These performances outperformed equivalent silicon complementary metal-oxide-semiconductor technologies and satisfied the 2028 roadmap target. We further fabricate large-area device arrays and demonstrate low variability in contact resistance, threshold voltage, subthreshold swing, on/off ratio, on-state current and transconductance13. The excellent electrical performance, stability and variability make antimony ([Formula: see text]) a promising contact technology for transition-metal-dichalcogenide-based electronics beyond silicon.

Uniform nucleation and epitaxy of bilayer molybdenum disulfide on sapphire.

Two-dimensional transition-metal dichalcogenides (TMDs) are of interest for beyond-silicon electronics1,2. It has been suggested that bilayer TMDs, which combine good electrostatic control, smaller bandgap and higher mobility than monolayers, could potentially provide improvements in the energy-delay product of transistors3-5. However, despite advances in the growth of monolayer TMDs6-14, the controlled epitaxial growth of multilayers remains a challenge15. Here we report the uniform nucleation (>99%) of bilayer molybdenum disulfide (MoS2) on c-plane sapphire. In particular, we engineer the atomic terrace height on c-plane sapphire to enable an edge-nucleation mechanism and the coalescence of MoS2 domains into continuous, centimetre-scale films. Fabricated field-effect transistor (FET) devices based on bilayer MoS2 channels show substantial improvements in mobility (up to 122.6 cm2 V-1 s-1) and variation compared with FETs based on monolayer films. Furthermore, short-channel FETs exhibit an on-state current of 1.27 mA µm-1, which exceeds the 2028 roadmap target for high-performance FETs16.

MEDL-Net: A model-based neural network for MRI reconstruction with enhanced deep learned regularizers.

PURPOSE: To improve the MRI reconstruction performance of model-based networks and to alleviate their large demand for GPU memory. METHODS: A model-based neural network with enhanced deep learned regularizers (MEDL-Net) was proposed. The MEDL-Net is separated into several submodules, each of which consists of several cascades to mimic the optimization steps in conventional MRI reconstruction algorithms. Information from shallow cascades is densely connected to latter ones to enrich their inputs in each submodule, and additional revising blocks (RB) are stacked at the end of the submodules to bring more flexibility. Moreover, a composition loss function was designed to explicitly supervise RBs. RESULTS: Network performance was evaluated on a publicly available dataset. The MEDL-Net quantitatively outperforms the state-of-the-art methods on different MR image sequences with different acceleration rates (four-fold and six-fold). Moreover, the reconstructed images showed that the detailed textures are better preserved. In addition, fewer cascades are required when achieving the same reconstruction results compared with other model-based networks. CONCLUSION: In this study, a more efficient model-based deep network was proposed to reconstruct MR images. The experimental results indicate that the proposed method improves reconstruction performance with fewer cascades, which alleviates the large demand for GPU memory.

Exogenous c-di-GMP inhibited the biofilm formation of Vibrio splendidus.

Vibrio splendidus, a gram-negative bacterium that is ubiquitously present in marine environments, has been increasingly deemed an important opportunistic pathogen of marine animals. In this study, the biofilm formation of V. splendidus was quantitatively determined and morphologically characterized. Three stages of biofilm formation, including adhesion, aggregation and maturation were observed in the biofilm formed by V. splendidus. The inhibitory effect of exogenous bis (3',5')-cyclic dimeric guanosine monophosphate (c-di-GMP) on the biofilm formation from the scratch and preformed established biofilms of V. splendidus was determined. When 200 µmol/L c-di-GMP was added, the quantity of biofilm decreased by 88.1% or 66.7% under the two conditions. To explore the preliminary mechanism of exogenous c-di-GMP on the biofilm formed by V. splendidus, proteomic analysis was performed. GO enrichment analysis showed that exogenous c-di-GMP upregulated biological processes, including the tricarboxylic acid cycle, oxidation‒reduction reactions and organonitrogen compound catabolism and significantly downregulated tRNA threonylcarbamoyladenosine modification, protein dephosphorylation, and lactate transmembrane transporter activity. Sequence-specific DNA binding activity was the most markedly downregulated molecular function. KEGG analysis showed that the valine, leucine and isoleucine degradation pathway was the most enriched pathway, followed by nitrogen metabolism, among the 20 upregulated pathways. Among the downregulated pathways, a nonribosomal peptide structure pathway and the streptomycine, polyketide sugar unit, acarbose and validamycin biosynthesis pathways were significantly enriched. Our present study provides basic data for the biofilm formation of V. splendidus and the preliminary inhibitory mechanism of exogenous c-di-GMP on the biofilm formation of V. splendidus.

Proteomic analysis reveals the adaptation of Vibrio splendidus to an iron deprivation condition.

Vibrio splendidus is a ubiquitous Gram-negative marine bacterium that causes diseases within a wide range of marine cultured animals. Since iron deprivation is the frequent situation that the bacteria usually encounter, we aimed to explore the effect of iron deprivation on the proteomic profile of V. splendidus in the present study. There were 425 differentially expressed proteins (DEPs) responded to the iron deprivation condition. When the cells were grown under iron deprivation condition, the oxidation‒reduction processes, single-organism metabolic processes, the catalytic activity, and binding activity were downregulated, while the transport process, membrane cell component, and ion binding activity were upregulated, apart from the iron uptake processes. Kyoto Encyclopedia of Genes and Genomes analysis showed that various metabolism pathways, biosynthesis pathways, energy generation pathways of tricarboxylic acid cycle, and oxidative phosphorylation were downregulated, while various degradation pathways and several special metabolism pathways were upregulated. The proteomic profiles of cells at a OD600 ≈ 0.4 grown under iron deprivation condition showed high similarity to that of the cells at a OD600 ≈ 0.8 grown without iron chelator 2,2'-bipyridine. Correspondingly, the protease activity, the activity of autoinducer 2 (AI-2), and indole content separately catalyzed by LuxS and TnaA, were measured to verify the proteomic data. Our present study gives basic information on the global protein profiles of V. splendidus grown under iron deprivation condition and suggests that the iron deprivation condition cause the cell growth enter a state of higher cell density earlier. KEY POINTS: • Adaptation of V. splendidus to iron deprivation was explored by proteomic analysis. • GO and KEGG of DEPs under different iron levels or cell densities were determined. • Iron deprivation caused the cell enter a state of higher cell density earlier.

Multiple herbicide resistance in a Cyperus difformis population in rice field from China.

Herbicide resistance is rapidly emerging in Cyperus difformis in rice fields across China. The response of a C. difformis population GX-35 was tested against five acetolactate synthase (ALS)-inhibiting herbicides, auxin herbicide MCPA and photosynthesis II (PSII)-inhibitor bentazone. Population GX-35 evolved multiple resistance to ALS-inhibiting herbicides (penoxsulam, bispyribac­sodium, pyrazosulfuron-ethyl, halosulfuron-methly and imazapic) and auxin herbicide MCPA, with resistance levels of 140-, 1253-, 578-, 18-, 13-, and 21-fold, respectively, compared to the susceptible population. In this population, ALS gene expression was similar to that of the susceptible population. However, an Asp376Glu mutation in ALS gene was observed, leading to reduced inhibition of in-vitro ALS activities by five ALS-inhibiting herbicides. Furthermore, CYP71D8, CYP77A3, CYP78A5 and three ABC transporter genes (cluster-14412.23067, cluster-14412.25321, and cluster-14412.24716) over-expressed in absence of penoxsulam. On the other hand, an UGT73C1 and an ABC transporter (cluster-14412.25038) were induced by penoxsulam. Additionally, both over-expression and induction were observed for CYP74, CYP71A1, UGT88A1 and an ABC transporter (cluster-14412.21723). The GX-35 population has indeed evolved multiple herbicide resistance in China. Therefore, a diverse range of weed control tactics should be implemented in rice field.

Proteomic analysis of the initial wake up of vibrio splendidus persister cells.

Vibrio splendidus is a ubiquitous pathogen that causes various diseases in aquaculture with a wide range of hosts. In our previous studies, we showed that L-glutamic acid was the optimal carbon source that could revive V. splendidus persister cells. In our present study, single cell observation under microscopy showed that V. splendidus could revive using L-glutamic acid as carbon source. A proteomic analysis was carried out to further illustrate the initial wake up of persister cells with L-glutamic acid. To collect the initially revived cells, SDS-PAGE was used to determine the revived time. The total proteins from the persister cells and the revived cells were analyzed using LC‒MS/MS. A total of 106 proteins, including 42 downregulated proteins and 64 upregulated proteins, were identified. GO analysis of the differentially expressed proteins (DEPs) showed that biological processes, including protein complex assembly, protein oligomerization, and arginine metabolism; cellular components, including extracellular membrane, plasma membrane and ribosome; and molecular functions, including the activities of arginine binding and structural constituent of ribosome, were enriched. KEGG analysis showed that lipopolysaccharide biosynthesis, porphyrin and chlorophyll metabolism, and peptidoglycan biosynthesis were upregulated, while the ribosome was downregulated. This is the first time to study the initial wake up of persister cells based on proteomic analysis, and the results revealed the main pathways involved in the early resuscitation of V. splendidus persister cells.

Methylation-reprogrammed CHRM3 results in vascular dysfunction in the human umbilical vein following IVF-ET†.

Assisted reproductive technology (ART) has been used globally among infertile couples. However, many epidemiological investigations have indicated that ART is associated with a range of long-term adverse health outcomes in offspring, including cardiovascular disease, obesity, and increased plasma lipid levels. Until now, direct evidence has been limited regarding the pathological changes in vascular function in fetuses with ART. In this study, human umbilical cords were collected from healthy normal pregnancies and in vitro fertilization and embryo transfer (IVF-ET) pregnancies. Vascular functional studies involving acetylcholine (ACh), antagonists of its specific receptors, and L-type calcium channel/PKC-MLC20 phosphorylation pathway specific inhibitors were conducted. Quantitative real-time PCR, Western blotting, and methylation analyses were performed on umbilical vein samples. We found that the umbilical vein constriction induced by ACh in the IVF-ET group was significantly attenuated compared with that in the healthy normal pregnancy group, which was not only associated with the hypermethylation of ACh muscarinic receptor subtype 3 (CHRM3) and decreased expression of CHRM3, PKCß, and CaV1.2, but was also related to the reduced phosphorylation of MLC20. This study revealed that the hypermethylation of CHRM3, leading to a reduction in CHRM3 expression and downregulation of the CaV1.2/PKC-MLC20 phosphorylation pathway, was responsible for the decreased sensitivity to ACh observed in the umbilical vein under IVF-ET conditions. The hypermethylation of CHRM3 caused by IVF-ET might play an important role in altered vasoconstriction and impact cardiovascular systems in the long run.

Gestational exposure to fluoride impairs cognition in C57 BL/6 J male offspring mice via the p-Creb1-BDNF-TrkB signaling pathway.

Fluoride exposure has a detrimental effect on neurodevelopment, while the underlying processes remain unknown. The goal of this study was to investigate how fluoride impacts synaptogenesis, with a focus on the phosphorylation of Creb1 (p-Creb1)-brain-derived neurotrophic factor (BDNF)-tyrosine kinase B (TrkB) pathway. We generated a sodium fluoride (NaF) model using C57 BL/6 J mice exposed to 100 mg/L NaF from gestation day 1 (GD1) to GD20. It was identified that NaF treatment impaired the learning and memory abilities of the male offspring, reduced dendritic spine density, lowered postsynaptic density protein-95 (PSD95) and synaptophysin (SYN) expression in the male offspring's hippocampus, indicating that synaptic dysfunction may contribute to the cognitive impairment in the NaF model. In addition, in vivo experiment demonstrated that the protein abundance of BDNF and the ratio of p-Creb1 to Creb1 were increased in the hippocampus of NaF offspring, while the level of TrkB was reduced. Similarly, PC12 cells treated with NaF also showed increased expression of BDNF and decreased levels of TrkB. Notably, fluoride treatment increased p-Creb1 in vitro, while inhibiting p-Creb1 by 66615 significantly alleviated the effects of NaF exposure, indicating that p-Creb1 exerts a regulatory function in the BDNF-TrkB pathway. Altogether, these results demonstrated prenatal fluoride exposure triggered neurotoxicity in the male offspring hippocampus was linked to synaptogenesis damage caused by activating p-Creb1, which disrupted the BDNF-TrkB pathway.

Multi-Focus Image Fusion Method Based on Multi-Scale Decomposition of Information Complementary.

Multi-focus image fusion is an important method used to combine the focused parts from source multi-focus images into a single full-focus image. Currently, to address the problem of multi-focus image fusion, the key is on how to accurately detect the focus regions, especially when the source images captured by cameras produce anisotropic blur and unregistration. This paper proposes a new multi-focus image fusion method based on the multi-scale decomposition of complementary information. Firstly, this method uses two groups of large-scale and small-scale decomposition schemes that are structurally complementary, to perform two-scale double-layer singular value decomposition of the image separately and obtain low-frequency and high-frequency components. Then, the low-frequency components are fused by a rule that integrates image local energy with edge energy. The high-frequency components are fused by the parameter-adaptive pulse-coupled neural network model (PA-PCNN), and according to the feature information contained in each decomposition layer of the high-frequency components, different detailed features are selected as the external stimulus input of the PA-PCNN. Finally, according to the two-scale decomposition of the source image that is structure complementary, and the fusion of high and low frequency components, two initial decision maps with complementary information are obtained. By refining the initial decision graph, the final fusion decision map is obtained to complete the image fusion. In addition, the proposed method is compared with 10 state-of-the-art approaches to verify its effectiveness. The experimental results show that the proposed method can more accurately distinguish the focused and non-focused areas in the case of image pre-registration and unregistration, and the subjective and objective evaluation indicators are slightly better than those of the existing methods.

Irisin stimulates cell proliferation and invasion by targeting the PI3K/AKT pathway in human hepatocellular carcinoma.

Irisin is a newly identified myokine that may be cancer-associated, and its impact on liver cancer is unclear. To understand the roles of irisin in liver cancer, we investigated its effect in HepG2 and SMCC7721 hepatocellular carcinoma cells, and the underlying mechanisms. We determined irisin levels in liver tissues and serum samples obtained from patients by using real-time polymerase chain reaction and enzyme-linked immunosorbent assay. Irisin levels in cancerous livers were significantly upregulated compared with those in control livers, but serum irisin levels remained unchanged. Additionally, we evaluated the effects of different concentrations of human recombinant modified and active (glycosylated) irisin (IM) or human recombinant nonmodified irisin (INM) on cell migration, proliferation, viability, and invasiveness. CCK8, transwell, and scratching assays demonstrated that irisin significantly increased cell proliferation, invasion, and migration through activation of the PI3K/AKT pathway. Irisin-induced cell proliferation, migration, and invasion were blocked by a PI3K inhibitor (LY294002). Irisin also decreased the cytotoxicity of doxorubicin in HepG2 cells. These data indicate that increased irisin levels may have protective roles in liver cancer cells through partial activation of the PI3K/AKT pathway, which may facilitate liver cancer progression and decrease the sensitivity to chemotherapy.

Disrupting the circadian photo-period alters the release of follicle-stimulating hormone, luteinizing hormone, progesterone, and estradiol in maternal and fetal sheep.

Although a large number of studies show that photo-period disruption potentially affects hormone secretion in mammals, information about the effects of circadian photo-period disruption during pregnancy on fetal blood reproductive hormone levels is scarce. This study used ewes and their fetuses to determine the effects of circadian photo-period disruption (deprivation of darkness) on follicle-stimulating hormone, luteinizing hormone, estradiol, and progesterone in maternal and fetal circulation at late gestation. Pregnant ewes (gestational age: 135 ± 3 days) were randomly placed into control and dark deprivation groups. The control (N = 5) and dark deprivation (N = 5) groups were exposed to a fixed 12 h light/12 h dark cycle and a 24 h constant light cycle, respectively, for 2 days. Dark deprivation up-regulated follicle-stimulating hormone and estradiol levels and down-regulated progesterone levels in both maternal and fetal circulation, and up-regulated luteinizing hormone levels in fetal but not maternal circulation. These results provide new information about how circadian photo-period disruption during pregnancy could alter the release of certain reproductive hormones into fetal blood, which may influence the development of fetal organs in utero, as well as long-term health.

Hypoxia-induced proliferation in mesenchymal stem cells and angiotensin II-mediated PI3K/AKT pathway.

Hypoxia could stimulate proliferation of mesenchymal stem cells (MSCs) under certain conditions. This study determined angiotensin II mechanisms and PI3K/AKT pathway in hypoxia-induced proliferation of MSCs. Hypoxia (3% oxygen) induced cellular proliferation in mouse MSCs and upregulated endogenous angiotensin II and angiotensin-converting enzyme in the cell culture and expression of AT1 receptors. The expressions of Sox2, not Oct4 and Rex1, were significantly increased by the hypoxia. The blockade of AT1 receptors, not AT2 receptors, depressed hypoxia induced the proliferative effects. Both hypoxia and exogenous angiotensin II activated p-AKT. Moreover, AT1 receptor inhibitor blocked the effects of hypoxia-mediated p-AKT upregulation. The data demonstrated that the hypoxia at 3% oxygen level could induce mouse MSC proliferation, probably as a result of the activation of PI3K signalling pathways via AT1 receptors.

Effect of two formulations on the decline curves and residue levels of rotenone in cabbage and soil under field conditions.

The dissipation and residue levels of rotenone with suspension concentrate (SC) as well as water dispersible granule (WDG) formulations in cabbage and soil were investigated under field conditions. The decline curves of rotenone residues in cabbage and soil corresponded with first-order kinetics. The dissipation rate of rotenone in cabbage was faster than that in soil. The half-lives of the SC formulations in cabbage and soil were 1.14d to 1.85d and 2.26d to 3.98d, respectively. For the WDG formulation, the values were 1.33d to 1.96d and 2.41d to 3.38d. Less spraying, lower dosage, and longer pre-harvest intervals could reduce terminal residue levels. Terminal residues below the MRL (0.5mg kg(-1)) were achieved after pre-harvest intervals of 3d at either once (45g a.i. ha(-1)) or twice (90g a.i. ha(-1)) the recommended dosage. The different dissipation processes of rotenone in cabbage and soil under field conditions could be attributed to the different climate and soil properties, and the types of formulation had no apparent effect on half-life. Formulation type affected the initial concentrations and finally led to different terminal residues. Prolonged pre-harvest intervals are necessary to ensure that the products are sufficiently safe for consumption.

An elastic competitive and discriminative collaborative representation method for image classification.

Collaborative representation-based (CR) methods have become prevalent for pattern classification tasks, achieving formidable performance. Theoretically, we expect the learned class-specific representation of the correct class to be discriminative against others, with the representation of the correct class contributing dominantly in CR. However, most existing CR methods focus on improving discrimination while having a limited impact on enhancing the representation contribution of the correct category. In this work, we propose a novel CR approach for image classification called the elastic competitive and discriminative collaborative representation-based classifier (ECDCRC) to simultaneously strengthen representation contribution and discrimination of the correct class. The ECDCRC objective function penalizes two key terms by fully incorporating label information. The competitive term integrates the nearest subspace representation with corresponding elastic factors into the model, allowing each class to have varying competition intensities based on similarity with the query sample. This enhances the representation contribution of the correct class in CR. To further improve discrimination, the discriminative term introduces an elastic factor as a weight in the model to represent the gap between the query sample and the representation of each class. Moreover, instead of focusing on representation coefficients, the designed ECDCRC weights associated with representation components directly relate to the representation of each class, enabling more direct and precise discrimination improvement. Concurrently, sparsity is also enhanced through the two terms, further boosting model performance. Additionally, we propose a robust ECDCRC (R-ECDCRC) to handle image classification with noise. Extensive experiments on seven public databases demonstrate the proposed method's superior performance over related state-of-the-art CR methods.

CGFTrans: Cross-Modal Global Feature Fusion Transformer for Medical Report Generation.

Medical report generation, as a cross-modal automatic text generation task, can be highly significant both in research and clinical fields. The core is to generate diagnosis reports in clinical language from medical images. However, several limitations persist, including a lack of global information, inadequate cross-modal fusion capabilities, and high computational demands. To address these issues, we propose cross-modal global feature fusion Transformer (CGFTrans) to extract global information meanwhile reduce computational strain. Firstly, we introduce mesh recurrent network to capture inter-layer information at different levels to address the absence of global features. Then, we design feature fusion decoder and define 'mid-fusion' strategy to separately fuse visual and global features with medical report embeddings, which enhances the ability of the cross-modal joint learning. Finally, we integrate shifted window attention into Transformer encoder to alleviate computational pressure and capture pathological information at multiple scales. Extensive experiments conducted on three datasets demonstrate that the proposed method achieves average increments of 2.9%, 1.5%, and 0.7% in terms of the BLEU-1, METEOR and ROUGE-L metrics, respectively. Besides, it achieves average increments -22.4% and 17.3% training time and images throughput, respectively.

BMA-based Mendelian randomization identifies blood metabolites as causal candidates in pregnancy-induced hypertension.

Pregnancy-induced hypertension (PIH), a prominent determinant of maternal mortality and morbidity worldwide, is hindered by the absence of efficacious biomarkers for early diagnosis, contributing to suboptimal outcomes. Here, we explored potential causal relationships between blood metabolites and the risk of PIH using Mendelian randomization (MR). We employed a two-sample univariable MR approach to empirically estimate the causal relationships between 249 circulating metabolites and PIH. Inverse variance weighted, MR-egger, weight median, simple mode, and weighted mode methods were used for causal estimates. The exposure-to-outcome directionality was confirmed with the MR Steiger test. The Bayesian model averaging MR (MR-BMA) method was applied to detect the predominant causal metabolic traits with alignment for pleiotropy effects. In the primary analysis, analyzing 249 metabolites, we identified 25 causally linked to PIH, including 11 lipid-related traits and 6 associated with fatty acid (un)saturation. Importantly, MR-BMA analyses corroborated the total concentration of branched-chain amino acids(total-BCAA) to be the highest rank causal metabolite, followed by leucine (Leu), phospholipids to total lipids ratio in medium LDL (M-LDL-PL-pct), and Val (all P < 0.05). The directionality of causality predicted by univariable MR and MR-BMA for these metabolites remained consistent. This study highlights the causal connection between metabolites and PIH risk. It highlighted BCAAs as the strongest causal candidates warranting further investigation. Since PIH typically occurs in the second and third trimesters, extending these findings could inform earlier strategies to reduce its risk. Directed acyclic graph of the MR framework investigating the causal relationship between metabolites and PIH. MR: Mendelian randomization; GIVs: genetic instrument variables; SNPs: single-nucleotide polymorphism; IVW: inverse variance weighted; WM: weighted median; PIH: pregnancy-induced hypertension; SM: significant metabolite; MR-BMA: Bayesian model averaging MR.

Shape-Scale Co-Awareness Network for 3D Brain Tumor Segmentation.

The accurate segmentation of brain tumor is significant in clinical practice. Convolutional Neural Network (CNN)-based methods have made great progress in brain tumor segmentation due to powerful local modeling ability. However, brain tumors are frequently pattern-agnostic, i.e. variable in shape, size and location, which can not be effectively matched by traditional CNN-based methods with local and regular receptive fields. To address the above issues, we propose a shape-scale co-awareness network (S2CA-Net) for brain tumor segmentation, which can efficiently learn shape-aware and scale-aware features simultaneously to enhance pattern-agnostic representations. Primarily, three key components are proposed to accomplish the co-awareness of shape and scale. The Local-Global Scale Mixer (LGSM) decouples the extraction of local and global context by adopting the CNN-Former parallel structure, which contributes to obtaining finer hierarchical features. The Multi-level Context Aggregator (MCA) enriches the scale diversity of input patches by modeling global features across multiple receptive fields. The Multi-Scale Attentive Deformable Convolution (MS-ADC) learns the target deformation based on the multiscale inputs, which motivates the network to enforce feature constraints both in terms of scale and shape for optimal feature matching. Overall, LGSM and MCA focus on enhancing the scale-awareness of the network to cope with the size and location variations, while MS-ADC focuses on capturing deformation information for optimal shape matching. Finally, their effective integration prompts the network to perceive variations in shape and scale simultaneously, which can robustly tackle the variations in patterns of brain tumors. The experimental results on BraTS 2019, BraTS 2020, MSD BTS Task and BraTS2023-MEN show that S2CA-Net has superior overall performance in accuracy and efficiency compared to other state-of-the-art methods. Code: https://github.com/jiangyu945/S2CA-Net.

CTNet: Contrastive Transformer Network for Polyp Segmentation.

Segmenting polyps from colonoscopy images is very important in clinical practice since it provides valuable information for colorectal cancer. However, polyp segmentation remains a challenging task as polyps have camouflage properties and vary greatly in size. Although many polyp segmentation methods have been recently proposed and produced remarkable results, most of them cannot yield stable results due to the lack of features with distinguishing properties and those with high-level semantic details. Therefore, we proposed a novel polyp segmentation framework called contrastive Transformer network (CTNet), with three key components of contrastive Transformer backbone, self-multiscale interaction module (SMIM), and collection information module (CIM), which has excellent learning and generalization abilities. The long-range dependence and highly structured feature map space obtained by CTNet through contrastive Transformer can effectively localize polyps with camouflage properties. CTNet benefits from the multiscale information and high-resolution feature maps with high-level semantic obtained by SMIM and CIM, respectively, and thus can obtain accurate segmentation results for polyps of different sizes. Without bells and whistles, CTNet yields significant gains of 2.3%, 3.7%, 3.7%, 18.2%, and 10.1% over classical method PraNet on Kvasir-SEG, CVC-ClinicDB, Endoscene, ETIS-LaribPolypDB, and CVC-ColonDB respectively. In addition, CTNet has advantages in camouflaged object detection and defect detection. The code is available at https://github.com/Fhujinwu/CTNet.

Two-dimensional semiconductor transistors and integrated circuits for advanced technology nodes.

This Perspective aims to provide a concise survey of current progress and outlook future directions in high-performance transistors and integrated circuits (ICs) based on 2D semiconductors.