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Abstract Self-rectifying memristive devices have emerged as promising contenders for low-power in-memory computing, presenting numerous advantages. However, characterizing the functional behavior of passive crossbar arrays incorporating these devices remains challenging due to sophisticated parasitic currents stemming from rich memristive dynamic behavior. Conventional methods using read margin assessments to evaluate functional behavior in passive crossbars are hindered by the voltage divider effect from the pull-up resistor. In this study, we propose a novel performance metric, $$\Delta$$ Δ SC, harnessing sneak path currents to assess functional behavior. Through the application of a pair of negative rectification factors, $$\text {RF}_\text {n, L}$$ RF n, L and $$\text {RF}_\text {n, H}$$ RF n, H , we comprehensively delineate dynamic rectification behavior in both positive and negative bias regimes, as well as in low-resistance state and high-resistance state, deviating from conventional metrics such as on/off ratios, nonlinearity, and rectifying factors. Notably, $$\Delta$$ Δ SC provides a quantitative evaluation of the interaction between sneak path currents and read margin, demonstrating its efficacy and addressing a pivotal research gap in the field. For instance, employing self-rectifying BiFeO $$_3$$ 3 memristive cells featuring $$\text {RF}_\text {n, L}$$ RF n, L = 1.22E3 and $$\text {RF}_\text {n, H}$$ RF n, H = 9.27, we showcase the successful functional performance of a passive crossbar array, achieving $$\Delta$$ Δ SC < 2.19E−2, while ensuring a read margin > 0.

Abstract Bladder cancer (BC) represents a prevalent and formidable malignancy necessitating innovative diagnostic and therapeutic strategies. Circular RNAs (circRNAs) have emerged as crucial regulators in cancer biology. In this study, we comprehensively evaluated ferroptosis levels in BC cells utilizing techniques encompassing lipid peroxidation assessment, transmission electron microscopy, and malondialdehyde (MDA) measurement. Additionally, we probed into the mechanistic intricacies by which circRNAs govern BC, employing RNA pull-down, RNA immunoprecipitation (RIP), and immunoprecipitation (IP) assays. Our investigation unveiled circSIRT5, which displayed significant downregulation in BC. Notably, circSIRT5 emerged as a promising prognostic marker, with diminished expression correlating with unfavorable clinical outcomes. Functionally, circSIRT5 was identified as an inhibitor of BC progression both in vitro and in vivo. Mechanistically, circSIRT5 exerted its tumor-suppressive activities through the formation of a ternary complex involving circSIRT5, SYVN1, and PHGDH. This complex enhanced the ubiquitination and subsequent degradation of PHGDH, ultimately promoting ferroptosis in BC cells. This ferroptotic process contributed significantly to the inhibition of tumor growth and metastasis in BC. In addition, FUS was found to accelerate the biogenesis of circSIRT5 in BC. These findings provide valuable insights into the pivotal role of circSIRT5 in BC pathogenesis, underscoring its potential as a diagnostic biomarker and therapeutic target for this malignancy.

Abstract Background Keloid is a disease characterized by proliferation of fibrous tissue after the healing of skin tissue, which seriously affects the daily life of patients. However, the clinical treatment of keloids still has limitations, that is, it is not effective in controlling keloids, resulting in a high recurrence rate. Thus, it is urgent to identify new signatures to improve the diagnosis and treatment of keloids. Method Bulk RNA seq and scRNA seq data were downloaded from the GEO database. First, we used WGCNA and MEGENA to co-identify keloid/immune-related DEGs. Subsequently, we used three machine learning algorithms (Randomforest, SVM-RFE, and LASSO) to identify hub immune-related genes of keloid (KHIGs) and investigated the heterogeneous expression of KHIGs during fibroblast subpopulation differentiation using scRNA-seq. Finally, we used HE and Masson staining, quantitative reverse transcription-PCR, western blotting, immunohistochemical, and Immunofluorescent assay to investigate the dysregulated expression and the mechanism of retinoic acid in keloids. Results In the present study, we identified PTGFR, RBP5, and LIF as KHIGs and validated their diagnostic performance. Subsequently, we constructed a novel artificial neural network molecular diagnostic model based on the transcriptome pattern of KHIGs, which is expected to break through the current dilemma faced by molecular diagnosis of keloids in the clinic. Meanwhile, the constructed IG score can also effectively predict keloid risk, which provides a new strategy for keloid prevention. Additionally, we observed that KHIGs were also heterogeneously expressed in the constructed differentiation trajectories of fibroblast subtypes, which may affect the differentiation of fibroblast subtypes and thus lead to dysregulation of the immune microenvironment in keloids. Finally, we found that retinoic acid may treat or alleviate keloids by inhibiting RBP5 to differentiate pro-inflammatory fibroblasts (PIF) to mesenchymal fibroblasts (MF), which further reduces collagen secretion. Conclusion In summary, the present study provides novel immune signatures (PTGFR, RBP5, and LIF) for keloid diagnosis and treatment, and identifies retinoic acid as potential anti-keloid drugs. More importantly, we provide a new perspective for understanding the interactions between different fibroblast subtypes in keloids and the remodeling of their immune microenvironment.

In order to study the effects of reverse transcriptase inhibitors, protease inhibitors and flavonoids on two target cells infected by HIV in a heterogeneous environment, an HIV mathematical model at the cellular level was established. Research shows that infected cells can be categorized into immature infected cells, latent infected cells, and mature infected cells based on the infection process. The basic reproduction number $ R_{0} $ was established, and it is proved that $ R_{0} $ serves as a threshold parameter: When $ R_{0} < 1 $, the disease-free steady state is globally asymptotically stable, and the disease is extinct; when $ R_{0} > 1 $, the solution of the system is uniformly persistent, and the virus exists. Considering the huge advantages of drug intervention in controlling HIV infection, the optimal control problem was proposed under the condition that the constant diffusion coefficient is positive, so as to minimize the total number of HIV-infected cells and the cost of drug treatment. To illustrate our theoretical results, we performed numerical simulations in which the model parameters were obtained with reference to some medical studies. The results showed that: (1) as $ R_{0} $ increases, the risk of HIV transmission increases; (2) pharmacological interventions are important in early treatment of HIV spread and control of viral load in the body; (3) the treatment process must consider the heterogeneity of medication, otherwise it will not be conducive to suppressing the spread of the virus and will increase costs.

BackgroundFerroptosis, as a novel form of programmed cell death, plays a crucial role in the occurrence and development of bladder cancer (BCa). However, the regulatory mechanisms of ferroptosis in the tumor microenvironment (TME) of BCa remain to be elucidated.MethodsBased on single-cell RNA (scRNA) transcriptomic data of BCa, we employed non-negative matrix factorization (NMF) dimensionality reduction clustering to identify novel ferroptosis-related cell subtypes within the BCa TME, aiming to explore the biological characteristics of these TME cell subtypes. Subsequently, we conducted survival analysis and univariate Cox regression analysis to explore the prognostic significance of these cell subtypes. We investigated the relationship between specific subtypes and immune infiltration, as well as their implications for immunotherapy. Finally, we discovered a valuable and novel biomarker for BCa, supported by a series of in vitro experiments.ResultsWe subdivided cancer-associated fibroblasts (CAFs), macrophages, and T cells into 3-5 small subpopulations through NMF and further explored the biological features. We found that ferroptosis played an important role in the BCa TME. Through bulk RNA-seq analysis, we further verified that ferroptosis affected the progression, prognosis, and immunotherapy response of BCa by regulating the TME. Especially ACSL4+CAFs, we found that high-level infiltration of this CAF subtype predicted worse prognosis, more complex immune infiltration, and less response for immunotherapy. Additionally, we found that this type of CAF was associated with cancer cells through the PTN-SDC1 axis, suggesting that SDC1 may be crucial in regulating CAFs in cancer cells. A series of in vitro experiments confirmed these inferences: SDC1 promoted the progression of BCa. Interestingly, we also discovered FTH1+ macrophages, which were closely related to SPP1+ macrophages and may also be involved in the regulation of BCa TME.ConclusionThis study revealed the significant impact of ferroptosis on bladder cancer TME and identified novel ferroptosis-related TME cell subpopulations, ACSL4+CAFs, and important BCa biomarker SDC1.

Under the background of high permeability, voltage feedforward control may further weaken the stability of grid-connected inverter (GCI) systems and may cause sub-synchronous oscillation in extreme cases. To solve this problem, this paper firstly considers the influence of the frequency coupling effect and voltage feedforward control, and adopts the harmonic linearization method to construct the L-type GCI sequence admittance model with PI (proportional integral) control and PR (proportional resonant) control, respectively. By comparing the sequence admittance characteristics of the GCI under two control strategies, combined with the sequence admittance model and Nyquist criterion, this paper analyzes the influence of voltage feedforward and control parameters on the stability of the GCI under two control strategies. The results show that the stability of GCI under PR control is slightly better than that under PI control. At the same time, the voltage feedforward control does reduce the stability of the GCI system under the two control strategies. Finally, the accuracy of the theoretical analysis is verified by simulation and experiment.

Based on the paraxial wave equation, this study extends the theory of small-scale self-focusing (SSSF) from coherent beams to spatially partially coherent beams (PCBs) and derives a general theoretical equation that reveals the underlying physics of the reduction in the B-integral of spatially PCBs. From the analysis of the simulations, the formula for the modulational instability (MI) gain coefficient of the SSSF of spatially PCBs is obtained by introducing a decrease factor into the formula of the MI gain coefficient of the SSSF of coherent beams. This decrease can be equated to a drop in the injected light intensity or an increase in the critical power. According to this formula, the reference value of the spatial coherence of spatially PCBs is given, offering guidance to overcome the output power limitation of the high-power laser driver due to SSSF.

Objective: To systematically evaluate the effectiveness and safety of integrated Chinese and Western medicine in the treatment of acute myeloid leukaemia (AML) in elderly people. Method: The Cochrane Library, PubMed, Web of Science, Excerpta Medica Database, China National Knowledge Infrastructure, Chinese Biomedical Literature Database, Wanfang Data and VIP Data databases were systematically searched from database inception to 30 June 2023 to identify cases of AML treatment with and without integrated Chinese and Western medicine. Fixed- and random-effect models were used to pool the main results, and the pooled risk ratio (RR) with a 95 % confidence interval (CI) was used as the effect indicator. Results: Eleven randomized controlled trial (RCT) involving 828 patients were finally included. The meta-analysis results showed that the overall response efficiency of integrated Chinese and Western medicine in treating myeloid leukaemia in elderly people was better than that of Western medicine alone (RR = 1.23, 95 % CI: 1.13, 1.33, p ＜ 0.001). There was significant difference in the complete remission rate between the two groups (RR = 1.38, 95 % CI: 1.15, 1.65, p ＜ 0.001). The incidence of myelosuppression (RR = 0.49, 95 % CI: 0.32, 0.75, p = 0.001), hepatic and renal insufficiency (RR = 0.43, 95 % CI: 0.29, 0.66, p ＜ 0.001), infection (RR = 0.26, 95 % CI: 0.17, 0.40, p ＜ 0.001) and gastrointestinal discomfort (RR = 0.31, 95 % CI: 0.22, 0.46, p ＜ 0.001) of integrated Chinese and Western medicine were significantly lower than that of Western medicine alone. Conclusion: Compared with Western medicine alone, the application of integrated traditional Chinese and Western medicine can improve the total clinical remission rate and reduce adverse effects following chemotherapy. However, more high-quality results of randomised controlled trials and analysis are needed to confirm the findings.

Pelagic sharks are top predators with key role in the structure and functioning of ocean ecosystems. However, little is known on their assemblage-wide trophic ecology. Specifically, fundamental data gaps exist over how trophic niches of pelagic sharks diverge both intra- and inter-specifically. To address this question, multi-tissue stable isotope analysis is a powerful tool that enables the quantification of trophic dynamics of mobile predators throughout ontogeny and across species. In this study, we utilized stable isotope analysis of carbon (δ13C) and nitrogen (δ15N) of tissues with varying turnover rates (muscle, red blood cells, liver, and plasma) to assess individual niche trajectories (i.e., temporal isotopic variation), population isotopic niche width, and isotopic niche overlap across five shark species (n = 155) in the eastern tropical Pacific Ocean: silky (Carcharhinus falciformis), blue (Prionace glauca), smooth hammerhead (Sphyrna zygaena), bigeye thresher (Alopias superciliosus), and the pelagic thresher shark (A. pelagicus). Overall, the relationship between isotopic niche trajectory length and body size was not significant, indicating that the magnitude of ontogenetic dietary variation does not increase in larger individuals. Pelagic sharks had variable feeding strategies over short-long time scales, likely reflecting species-specific responses to seasonality of prey availability and foraging location. Observed interspecific differences in isotope values indicate a degree of trophic niche partitioning across the five pelagic shark species. These data suggest ontogenetic niche shifts in pelagic sharks potentially differ from more coastal tied species and reveal species-specific ecological roles, but further studies on the diet and fine-scale habitat use are required to verify these results.

ABSTRACTThe Philadelphia (Ph) chromosome results from the formation of breakpoint cluster region (BCR)-Abelson 1 (ABL1) fusion gene (BCR-ABL1). The most common type of adult acute lymphoblastic leukaemia (ALL) is Ph chromosome-positive (Ph+); Ph+ ALL has an incidence of 25%∼30%. Several types of BCR-ABL1 fusion transcripts have been reported, including e1a2, e13a2 and e14a2. In addition, some rare BCR-ABL1 transcripts, such as e1a3, have been reported in chronic myeloid leukaemia. However, until now, the presence of e1a3 BCR-ABL1 fusion transcripts has only been reported in a few cases of ALL. In this study, a rare e1a3 BCR-ABL1 fusion transcript was found in a patient diagnosed with Ph+ ALL. However, the patient also suffered from severe agranulocytosis with pulmonary infection and died after being transferred to the intensive care unit before the significance of the presence of e1a3 BCR-ABL1 fusion transcript could be determined. In conclusion, e1a3 BCR-ABL1 fusion transcripts related to Ph+ ALL cases need to be better identified, and appropriate treatment strategies must be designed for such cases.

Abstract Background Breast cancer (BC) is the most common malignancy affecting women. It is vital to explore sensitive biological markers to diagnose and treat BC patients. Recent studies have proved that long noncoding RNAs (lncRNAs) were involved in breast tumor progression. Nonetheless, whether lncRNA prostate cancer‐associated transcript 19 (PCAT19) impacts BC development remains unknown. Methods We performed various bioinformatic analyses, including machine learning models to identify critical regulatory lncRNAs affecting prognosis in BC. The in situ hybridization (ISH) assay was carried out to confirm the expression levels of lncRNA PCAT19 in tissue specimens. MTT assay, wound healing assay, and transwell assay were performed to investigate PCAT19's impact on proliferation, migration, and invasion of BC cells. Mouse xenografts were used to examine the proliferation‐inhibiting function of PCAT19 in vivo. Results Among the prognosis‐associated lncRNAs, PCAT19 predicted a favorable prognosis in BC. Patients with high expression levels of PCAT19 had a lower clinical stage and less lymph node metastasis. The PCAT19‐related genes were enriched in signaling pathways involved in tumor development, indicating PCAT19 was an essential regulator of BC. Using the ISH assay, we confirmed the expression level of lncRNA PCAT19 in human BC tissues was lower than normal breast tissues. Moreover, the knockdown of PCAT19 further confirmed its inhibiting ability in BC cell proliferation. Correspondingly, overexpressing PCAT19 reduced tumor size in mouse xenografts. Conclusions Our study demonstrated that lncRNA PCAT19 suppressed the development of BC. PCAT19 might be a promising prognostic biomarker, which provides new insights into risk stratification for BC patients.

Electron beam melt superheating treatment (EBMST) is firstly proposed to prepare DZ125 alloy, which opens up a new way to further explore and improve the properties of superalloys. The effects of melt superheating treatment at ultra-high temperature on the composition, microstructure and purity of superalloy were studied. As the melt superheating power increases, the mass loss rate of the alloy increases gradually. A theoretical model for controlling alloy composition was established. The secondary dendrite spacing, the area fraction of the eutectic structure and the size of γ′ phases decrease first and then increase with the increase of the melt superheating power. The sizes of γ′ phases at dendritic core and interdendritic regions have the minimum values of 0.12 μm and 0.16 μm, respectively. As the melt superheating power increases, the segregation coefficients of Co and W increase first and then decrease, while that of Ti and Mo decrease first and then increase. The best purification effect is achieved at 14 kW, where the content of O and N are 1.8 ppmw and 1.2 ppmw, respectively. It means that 78% O and 80% N are removed from the raw materials.

For constrained image-based visual servoing (IBVS) of robot manipulators, a model predictive control (MPC) strategy tuned by reinforcement learning (RL) is proposed in this study. First, model predictive control is used to transform the image-based visual servo task into a nonlinear optimization problem while taking system constraints into consideration. In the design of the model predictive controller, a depth-independent visual servo model is presented as the predictive model. Next, a suitable model predictive control objective function weight matrix is trained and obtained by a deep-deterministic-policy-gradient-based (DDPG) RL algorithm. Then, the proposed controller gives the sequential joint signals, so that the robot manipulator can respond to the desired state quickly. Finally, appropriate comparative simulation experiments are developed to illustrate the efficacy and stability of the suggested strategy.

Abstract With the advent of the Internet of Things, nanoelectronic devices or memristors have been the subject of significant interest for use as new hardware security primitives. Among the several available memristors, BiFe $$\mathrm{O}_{3}$$ O 3 (BFO)-based electroforming-free memristors have attracted considerable attention due to their excellent properties, such as long retention time, self-rectification, intrinsic stochasticity, and fast switching. They have been actively investigated for use in physical unclonable function (PUF) key storage modules, artificial synapses in neural networks, nonvolatile resistive switches, and reconfigurable logic applications. In this work, we present a physics-inspired 1D compact model of a BFO memristor to understand its implementation for such applications (mainly PUFs) and perform circuit simulations. The resistive switching based on electric field-driven vacancy migration and intrinsic stochastic behaviour of the BFO memristor are modelled using the cloud-in-a-cell scheme. The experimental current–voltage characteristics of the BFO memristor are successfully reproduced. The response of the BFO memristor to changes in electrical properties, environmental properties (such as temperature) and stress are analyzed and consistant with experimental results.

Abstract AT‐HOOK MOTIF NUCLEAR LOCALIZED (AHL) proteins occur in all sequenced plant species. They bind to the AT‐rich DNA sequences in chromosomes and regulate gene transcription related to diverse biological processes. However, the molecular mechanism underlying how AHL proteins regulate gene transcription is poorly understood. In this research, we used root hair production as a readout to study the function of two Arabidopsis AHL proteins, AHL17, and its closest homolog AHL28. Overexpression of AHL17 or AHL28 greatly enhanced root hair production by increasing the transcription of an array of genes downstream of RHD6. RHD6 is a key transcription factor that regulates root hair development. Mutation of RHD6 completely suppressed the overproduction of root hairs by blocking the transcription of AHL17‐activated genes. The overexpression of AHL17 or AHL28, however, neither affected the transcription of RHD6 nor the accumulation of RHD6 protein. These two AHL proteins also did not directly interact with RHD6. Furthermore, we found that three members of the Heat Shock Protein70 family, which have been annotated as the subunits of the plant Mediator complex, could form a complex with both AHL17 and RHD6. Our research might reveal a previously unrecognized mechanism of how AHL proteins regulate gene transcription.

The integration of cryptographic algorithms like Advanced Encryption Standard (AES) and Elliptic Curve Cryptography (ECC) is pivotal in bolstering the core attributes of blockchain technology, especially in achieving decentralization, tamper resistance, and anonymization within the realm of medical applications. Despite their widespread utilization, the conventional AES and ECC face significant hurdles in security and efficiency when dealing with expansive medical data, posing a challenge to the effective preservation of patient privacy. In light of these challenges, this study introduces HAE (hybrid AES and ECC), an innovative hybrid cryptographic algorithm that ingeniously amalgamates the robustness of AES with the agility of ECC. HAE is designed to symmetrically encrypt original data with AES while employing ECC for the asymmetric encryption of the initial AES key. This strategy not only alleviates the complexities associated with AES key management but also enhances the algorithm’s security without compromising its efficiency. We provide an in-depth exposition of HAE’s deployment within a framework tailored for medical scenarios, offering empirical insights into its enhanced performance metrics. Our experimental outcomes underscore HAE’s exemplary security, time efficiency, and optimized resource consumption, affirming its potential as a breakthrough advancement for augmenting blockchain applications in the medical sector, heralding a new era of enhanced data security and privacy within this critical domain.

Sign language production aims to automatically generate coordinated sign language videos from spoken language. As a typical sequence to sequence task, the existing methods are mostly to regard the skeletons as a whole sequence, however, those do not take the rich graph information among both joints and edges into consideration. In this paper, we propose a novel method named Spatial-Temporal Graph Transformer (STGT) to deal with this problem. Specifically, according to kinesiology, we first design a novel graph representation to achieve graph features from skeletons. Then the spatial-temporal graph self-attention utilizes graph topology to capture the intra-frame and inter-frame correlations, respectively. Our key innovation is that the attention maps are calculated on both spatial and temporal dimensions in turn, meanwhile, graph convolution is used to strengthen the short-term features of skeletal structure. Finally, due to the generated skeletons are based on the form of skeleton points and lines so far. In order to visualize the generated sign language videos, we design a sign mesh regression module to render the skeletons into skinned animations including body and hands posture. Comparing with states of art baseline on RWTH-PHONEIX Weather-2014T in Experiment Section, STGT can obtain the highest values on BLEU and ROUGE, which indicates our method produces most accurate and intuitive sign language videos.

Purpose. To evaluate refractive outcomes, intraocular lens (IOL) power calculation, and IOL position following a novel conjunctiva-sparing transscleral fixation technique. Methods. Forty-one eyes of 40 patients managed with a flapless transscleral-sutured technique were included. Preoperative and postoperative refractive errors (spherical equivalents, SE) were compared. IOL position was assessed on the Scheimpflug images. IOL power was calculated by SRK/T, Holladay 1, and Hoffer Q formulas. Results. The mean age was 57.39 ± 14.83 years (range: 26 to 79 years), and the mean follow-up was 7.46 ± 6.42 months (range: 1 to 24 months). Surgical indications were aphakia (n = 14), subluxated lenses (n = 3), and IOL dislocation (n = 24). The SE was 4.50 ± 6.38 diopter (D) (range: −3.75 to 13.75 D) preoperatively and −1.68 ± 1.57 D (range: −5.50 to 1.13 D) postoperatively (P

Immunogenic cell death (ICD) is a form of regulated cell death that elicits immune response. Common inducers of ICD include cancer chemotherapy and radiation therapy. A better understanding of ICD might contribute to modify the current regimens of anti-cancer therapy, especially immunotherapy. This study aimed to identify ICD-related prognostic gene signatures in breast cancer (BC). An ICD-based gene prognostic signature was developed using Lasso-cox regression and Kaplan-Meier survival analysis based on datasets acquired from the Cancer Genome Atlas and Gene Expression Omnibus. A nomogram model was developed to predict the prognosis of BC patients. Gene Set Enrichment Analysis (GESA) and Gene Set Variation Analysis (GSVA) were used to explore the differentially expressed signaling pathways in high and low-risk groups. CIBERSORT and ESTIMATE algorithms were performed to investigate the difference of immune status in tumor microenvironment of different risk groups. Six genes (CALR, CLEC9A, BAX, TLR4, CXCR3, and PIK3CA) were selected for construction and validation of the prognosis model of BC based on public data. GSEA and GSVA analysis found that immune-related gene sets were enriched in low-risk group. Moreover, immune cell infiltration analysis showed that the immune features of the high-risk group were characterized by higher infiltration of tumor-associated macrophages and a lower proportion of CD8+ T cells, suggesting an immune evasive tumor microenvironment. We constructed and validated an ICD-based gene signature for predicting prognosis of breast cancer patients. Our model provides a tool with good discrimination and calibration abilities to predict the prognosis of BC, especially triple-negative breast cancer (TNBC).

A new type of Ni–Co based superalloy was prepared by vacuum induction melting (VIM), and the effects of superheat on element distribution, dendrite segregation, and solidification microstructure refinement of the new Ni–Co based superalloy are revealed. The effect of solidification structure treatment under different conditions was quantitatively studied by differential scanning calorimetry (DSC), scanning electron microscope (SEM), and electron probe micro analyzer (EPMA). The results indicated that the nucleation undercooling increased and the crystallization temperature interval decreased with the rise of the melt temperature; As the superheat temperature rised, the size of the phase was refined; the secondary dendrite arm spacing of the alloy decreased continuously; and the dendritic segregation of the alloy decreased. It was found that the critical temperature of melting energy for the new Ni–Co based superalloy clusters is about 1550 °C. The maximum positive segregation element of the new Ni–Co-based superalloy is Ti, and the maximum negative segregation element is W; When the temperature increased from 1450 °C to 1600 °C, the segregation coefficient of Ti increased from 0.54 to 0.63, and the segregation coefficient of W decreased from 1.9 to 1.5. When the superheat was increased, the atomic cluster size decreases, and the effect of refining the solidification structure of the new Ni–Co-based superalloy is more significant.

BackgroundEnergy metabolism has been considered as one of the novel features of neoplasms. This study aimed to establish the prognostic signature for pancreatic cancer (PC) based on metabolism-related genes (MRGs).MethodsWe obtained MRGs from the Molecular Signatures Database (MSigDB) and gene sequence data in the Cancer Genome Atlas (TCGA) databases. Then, differentially expressed MRGs (DE-MRGs) were identified utilizing the R software. We built the prognostic model via multivariate Cox regression. Moreover, external validation of the prognostic signature was also performed. Nomogram was created to predict the overall survival (OS). Next, this study analyzed the prognostic value, clinical relationship, and metabolism-related signaling pathways of the prognostic signature. The role in tumor infiltration was further evaluated. Eventually, the expression level of the three MRGs along with the function of NT5E was validated.ResultsTwenty-two MRGs were chosen, eight of which were identified to be most significantly correlated with the prognosis of PC. Meanwhile, a 3-MRG prognostic signature was established, and we verified this prognostic model in two separate external cohorts. What is more, the nomogram was used to predict 1-/2-/3-year OS of PC patients. In addition, the immune cell infiltration and expression of immune checkpoint were significantly influenced by the risk score. Finally, three MRGs were highly expressed in PC cell lines, and NT5E was associated with the proliferation and migration ability of PC.ConclusionTo sum up, the study established and validated a 3-MRG prognostic signature for PC, and the signature could be utilized to predict the prognosis and assist the individualized clinical management of patients with PC.

Memristive devices based on the Valence Change Mechanism (VCM) are promising devices for storage class memory, neuromorphic computing and logic-in-memory (LIM) applications. They are suited for such a wide range of applications, due to their possibility for extreme dense integration, low power consumption and multilevel capabilities. Through LIM concepts, Boolean logic operations can be performed directly in memory. In many of these concepts, the resistance state of the device is interpreted as the logical input and output of the logic function, which is why these concepts are called ‘stateful’ logic. Most of the proposed ideas, however, are defined based on only binary switching VCM devices and neglect their multi-level capabilities. Extending LIM concepts towards multinary logic, e.g. a ternary logic, would increase the data density inside the memory array and reduce the number of devices required to perform a certain operation. In this work, we discuss two possibilities of realizing a ternary logic based on the analog switching in the RESET or in the SET direction. For both directions we verify the logic functionality by showing the basic operations of implication, negation and false operation, which together form a functionally complete logic. Additionally, for both switching directions, we discuss a 41-Trit ( ${\approx}$ 64-Bit) addition. For all investigations the physics-based compact model JART VCM v1b is used, which has been verified on the RESET direction multilevel properties of the TaO $_{\mathrm{x}}$ devices.

As a typical sequence to sequence task, sign language production (SLP) aims to automatically translate spoken language sentences into the corresponding sign language sequences. The existing SLP methods can be classified into two categories: autoregressive and non-autoregressive SLP. The autoregressive methods suffer from high latency and error accumulation caused by the long-term dependence between current output and the previous poses. And non-autoregressive methods suffer from repetition and omission during the parallel decoding process. To remedy these issues in SLP, we propose a novel method named Pyramid Semi-Autoregressive Transformer with Rich Semantics (PSAT-RS) in this paper. In PSAT-RS, we first introduce a pyramid Semi-Autoregressive mechanism with dividing target sequence into groups in a coarse-to-fine manner, which globally keeps the autoregressive property while locally generating target frames. Meanwhile, the relaxed masked attention mechanism is adopted to make the decoder not only capture the pose sequences in the previous groups, but also pay attention to the current group. Finally, considering the importance of spatial-temporal information, we also design a Rich Semantics embedding (RS) module to encode the sequential information both on time dimension and spatial displacement into the same high-dimensional space. This significantly improves the coordination of joints motion, making the generated sign language videos more natural. Results of our experiments conducted on RWTH-PHOENIX-Weather-2014T and CSL datasets show that the proposed PSAT-RS is competitive to the state-of-the-art autoregressive and non-autoregressive SLP models, achieving a better trade-off between speed and accuracy.

Emerging brain-inspired neuromorphic computing paradigms require devices that can emulate the complete functionality of biological synapses upon different neuronal activities in order to process big data flows in an efficient and cognitive manner while being robust against any noisy input. The memristive device has been proposed as a promising candidate for emulating artificial synapses due to their complex multilevel and dynamical plastic behaviors. In this work, we exploit ultrastable analog BiFeO3 (BFO)-based memristive devices for experimentally demonstrating that BFO artificial synapses support various long-term plastic functions, i.e., spike timing-dependent plasticity (STDP), cycle number-dependent plasticity (CNDP), and spiking rate-dependent plasticity (SRDP). The study on the impact of electrical stimuli in terms of pulse width and amplitude on STDP behaviors shows that their learning windows possess a wide range of timescale configurability, which can be a function of applied waveform. Moreover, beyond SRDP, the systematical and comparative study on generalized frequency-dependent plasticity (FDP) is carried out, which reveals for the first time that the ratio modulation between pulse width and pulse interval time within one spike cycle can result in both synaptic potentiation and depression effect within the same firing frequency. The impact of intrinsic neuronal noise on the STDP function of a single BFO artificial synapse can be neglected because thermal noise is two orders of magnitude smaller than the writing voltage and because the cycle-to-cycle variation of the current–voltage characteristics of a single BFO artificial synapses is small. However, extrinsic voltage fluctuations, e.g., in neural networks, cause a noisy input into the artificial synapses of the neural network. Here, the impact of extrinsic neuronal noise on the STDP function of a single BFO artificial synapse is analyzed in order to understand the robustness of plastic behavior in memristive artificial synapses against extrinsic noisy input.

We study the recovery of the underlying graphs or permutations for tensors in the tensor ring or tensor train format. Our proposed algorithms compare the matricization ranks after down-sampling, whose complexity is O(d log d) for dth-order tensors. We prove that our algorithms can almost surely recover the correct graph or permutation when tensor entries can be observed without noise. We further establish the robustness of our algorithms against observational noise. The theoretical results are validated by numerical experiments. [ABSTRACT FROM AUTHOR]

We study the convergences of three projected Sobolev gradient flows to the ground state of the Gross--Pitaevskii eigenvalue problem. They are constructed as the gradient flows of the Gross--Pitaevskii energy functional with respect to the H1 0 -metric and two other equivalent metrics on H1 0, including the iterate-independent a0-metric and the iterate-dependent au-metric. We first prove the energy dissipation property and the global convergence to a critical point of the Gross--Pitaevskii energy for the discrete-time H1 and a0-gradient flow. We also prove local exponential convergence of all three schemes to the ground state. [ABSTRACT FROM AUTHOR]

Aims: The search for new antibiotics is an ongoing effort and has expanded to pristine niche areas in the Antarctic in recent years due to the emergence of multi-drug resistant pathogens that outpaced the discovery of new antibiotics. We have recently isolated two new actinomycetes strains, INACH3013a and INACH3013b, which displayed antimicrobial properties from soil samples collected from Ardley Island, Antarctica. Hence, an investigation was carried out to identify them and to characterise the antimicrobial compounds produced. Methodology and results: Strains, INACH3013a and INACH3013b were identified based on their 16S rDNA sequence alignment to those in the GenBank. The results showed that strain INACH3013a was closest to Streptomyces spp. while strain INACH3013b was closest to Streptomyces corallincola and Streptomyces bullii. The extracellular compounds they produced were extracted using various solvents and the extracted compounds were tested against the test pathogens. The dichloromethane extracts from strains, INACH3013a and INACH3013b inhibited mainly Gram-positive pathogens that include Listeria monocytogenes, Staphylococcus aureus, Staphylococcus haemolyticus, Staphylococcus equorum, Bacillus cereus K3 and Enterococcus faecalis while extracts from strain INACH3013b also inhibited a Gram-negative pathogen, Klebsiella pneumonia 14x. Predominantly non-polar constituents seem responsible for antibacterial effects, with dichloromethane extracts proving most efficacious, followed by chloroform and ethyl acetate. Conclusion, significance and impact of study: The research highlights the potential of Streptomyces spp. INACH3013a and INACH3013b as a source of potential novel antibiotics. This research explores Antarctic Streptomyces strains' antimicrobial capabilities, enabling the potential for the discovery of novel antibiotics and revealing how these compounds may have helped them to compete and survive in nutrient-deficient Antarctic niches. [ABSTRACT FROM AUTHOR]