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Abstract The violation of the null energy condition (NEC) may play a crucial role in enabling a scalar field to climb over high potential barriers, potentially significant in the very early universe. We propose a single-field model where the universe sequentially undergoes a first stage of slow-roll inflation, NEC violation, and a second stage of slow-roll inflation. Through the NEC violation, the scalar field climbs over high potential barriers, leaving unique characteristics on the primordial gravitational wave power spectrum, including a blue-tilted nature in the middle-frequency range and diminishing oscillation amplitudes at higher frequencies. Additionally, the power spectrum exhibits nearly scale-invariant behavior on both large and small scales.

Abstract Background Homologous recombination is a robust, broadly error-free mechanism of double-strand break repair, and deficiencies lead to PARP inhibitor sensitivity. Patients displaying homologous recombination deficiency can be identified using ‘mutational signatures’. However, these patterns are difficult to reliably infer from exome sequencing. Additionally, as mutational signatures are a historical record of mutagenic processes, this limits their utility in describing the current status of a tumour. Methods We apply two methods for characterising homologous recombination deficiency in breast cancer to explore the features and heterogeneity associated with this phenotype. We develop a likelihood-based method which leverages small insertions and deletions for high-confidence classification of homologous recombination deficiency for exome-sequenced breast cancers. We then use multinomial elastic net regression modelling to develop a transcriptional signature of heterogeneous homologous recombination deficiency. This signature is then applied to single-cell RNA-sequenced breast cancer cohorts enabling analysis of homologous recombination deficiency heterogeneity and differential patterns of tumour microenvironment interactivity. Results We demonstrate that the inclusion of indel events, even at low levels, improves homologous recombination deficiency classification. Whilst BRCA-positive homologous recombination deficient samples display strong similarities to those harbouring BRCA1/2 defects, they appear to deviate in microenvironmental features such as hypoxic signalling. We then present a 228-gene transcriptional signature which simultaneously characterises homologous recombination deficiency and BRCA1/2-defect status, and is associated with PARP inhibitor response. Finally, we show that this signature is applicable to single-cell transcriptomics data and predict that these cells present a distinct milieu of interactions with their microenvironment compared to their homologous recombination proficient counterparts, typified by a decreased cancer cell response to TNFα signalling. Conclusions We apply multi-scale approaches to characterise homologous recombination deficiency in breast cancer through the development of mutational and transcriptional signatures. We demonstrate how indels can improve homologous recombination deficiency classification in exome-sequenced breast cancers. Additionally, we demonstrate the heterogeneity of homologous recombination deficiency, especially in relation to BRCA1/2-defect status, and show that indications of this feature can be captured at a single-cell level, enabling further investigations into interactions between DNA repair deficient cells and their tumour microenvironment.

Summary: Hematoxylin and eosin (H&E) stained slides are widely used in disease diagnosis. Remarkable advances in deep learning have made it possible to detect complex molecular patterns in these histopathology slides, suggesting automated approaches could help inform pathologists’ decisions. Multiple instance learning (MIL) algorithms have shown promise in this context, outperforming transfer learning (TL) methods for various tasks, but their implementation and usage remains complex. We introduce HistoMIL, a Python package designed to streamline the implementation, training and inference process of MIL-based algorithms for computational pathologists and biomedical researchers. It integrates a self-supervised learning module for feature encoding, and a full pipeline encompassing TL and three MIL algorithms: ABMIL, DSMIL, and TransMIL. The PyTorch Lightning framework enables effortless customization and algorithm implementation. We illustrate HistoMIL’s capabilities by building predictive models for 2,487 cancer hallmark genes on breast cancer histology slides, achieving AUROC performances of up to 85%.

Silicon carbide (Sic) materials find wide-ranging applications in advanced optical systems within the aerospace, astronomical observation, and high-intensity laser fields. The silicon-modified Sic used in this study was created by depositing an amorphous silicon film on the surface of a Sic substrate using electron beam evaporation. Such hard and brittle materials often yield smooth surfaces when subjected to plastic removal. To address the issue of the removal depth of the surface plastic domain for silicon-modified Sic, we propose a method to calculate the indentation depth based on the critical load for the transition from plastic to brittle removal. We conducted a series of nanoindentation and nanoscratching experiments. The critical depth formula was validated through mechanical parameters such as hardness, elastic modulus, and fracture toughness, and the theoretical critical depth of the modified silicon layer was calculated to be 2.71 μm. The research results indicate that the critical load for obtaining the plastic-to-brittle transition point during the nanoindentation experiment is 886 mN, at which point the depth of plastic removal is 2.95 μm, closely matching the theoretical value. The measurements taken with an atomic force microscope near the critical load reveal a scratch depth of 3.12 μm, with a relative error of less than 5% when compared to the calculated value. This study establishes a solid foundation for achieving high-quality surface processing.

Abstract Background To evaluate the effect of stent boost subtract (SBS) imaging on stent underexpansion during percutaneous coronary intervention (PCI) in patients with acute ST-segment elevation myocardial infarction (STEMI) by optical coherence tomography (OCT). Methods One hundred thirty-eight STEMI patients who underwent drug-eluting stent (DES) implantation were prospectively recruited and divided into the SBS group (69 cases) and the CAG group (69 cases) according to whether SBS was used to guide PCI. Finally, OCT was performed on all enrolled patients, and the OCT results were used as the gold standard to evaluate the impact of standard SBS technology on stent underexpansion immediately after DES implantation. Results SBS identified 51 patients (24%) with stent underexpansion while OCT identified 56 patients (27.2%). SBS has a sensitivity of 80%, a specificity of 96%, a positive predictive value of 88%, and a negative predictive value of 93% for identifying stent underexpansion. Conclusion Compared with OCT, SBS technology is a rapid stent imaging evaluation method that can accurately quantify the stent expansion level and is time-saving and economical.

Objective To investigate the effect and underlying mechanism of artesunate (AS) on the expression of interleukin-6 (IL-6) in mouse primary hepatocytes induced by conjugate bile acids. Methods Mouse hepatocytes were isolated and primarily cultured, and then treated with 25 μmol/L conjugated bile acids. CCK-8 assay was used to determine the toxic effects of AS on the liver cells. The mRNA level of IL-6 in the cells was measured by RT-qPCR, and the protein levels of IL-6, p-65 and phosphorylated-p65 (p-p65) were determined by Western blotting. Results Conjugated bile acids of 25 μmol/L significantly promoted the expression of IL-6 at mRNA and protein levels in mouse primary hepatocytes, while, AS reduced the taurocholic acid (TCA)-induced phosphorylation of p65 and IL-6 level. Further studies revealed that AS suppressed the IL-6 expression through inhibiting p-p65 signaling pathway in mouse primary hepatocytes. Conclusion AS reduces IL-6 expression in mouse primary hepatocytes induced by conjugate bile acids via inhibiting the p-p65 signaling pathway.

Despite the high performances achieved using deep learning techniques in biometric systems, the inability to rationalise the decisions reached by such approaches is a significant drawback for the usability and security requirements of many applications. For Facial Biometric Presentation Attack Detection (PAD), deep learning approaches can provide good classification results but cannot answer the questions such as “Why did the system make this decision”? To overcome this limitation, an explainable deep neural architecture for Facial Biometric Presentation Attack Detection is introduced in this paper. Both visual and verbal explanations are produced using the saliency maps from a Grad-CAM approach and the gradient from a Long-Short-Term-Memory (LSTM) network with a modified gate function. These explanations have also been used in the proposed framework as additional information to further improve the classification performance. The proposed framework utilises both spatial and temporal information to help the model focus on anomalous visual characteristics that indicate spoofing attacks. The performance of the proposed approach is evaluated using the CASIA-FA, Replay Attack, MSU-MFSD, and HKBU MARs datasets and indicates the effectiveness of the proposed method for improving performance and producing usable explanations.

Abstract Terahertz applications urgently require high performance and room temperature terahertz sources. The gyrotron based on the principle of electron cyclotron maser is able to generate watt-to-megawatt level terahertz radiation, and becomes an exceptional role in the frontiers of energy, security and biomedicine. However, in normal conditions, a terahertz gyrotron could generate terahertz radiation with high efficiency on a single frequency or with low efficiency in a relatively narrow tuning band. Here a frequency tuning scheme for the terahertz gyrotron utilizing sequentially switching among several whispering-gallery modes is proposed to reach high performance with broadband, coherence and high power simultaneously. Such mode-switching gyrotron has the potential of generating broadband radiation with 100-GHz-level bandwidth. Even wider bandwidth is limited by the frequency-dependent effective electrical length of the cavity. Preliminary investigation applies a pre-bunched circuit to the single-mode wide-band tuning. Then, more broadband sweeping is produced by mode switching in great-range magnetic tuning. The effect of mode competition, as well as critical engineering techniques on frequency tuning is discussed to confirm the feasibility for the case close to reality. This multi-mode-switching scheme could make gyrotron a promising device towards bridging the so-called terahertz gap.

The existing mobility strategy of the anchor node in wireless sensor network (WSN) has the shortcomings of too long moving path and low positioning accuracy when the anchor node traverses the network voids area.A new mobility strategy of WSN anchor node was proposed based on an improved virtual forces model.The number of neighbor nodes and the distance between the neighbor nodes to the anchor nodes were introduced as their own dense weight attributes.The unknown nodes intensity was used as weights to improve the traditional virtual force model.Meantime the distance-measuring error ε was taken into account.The optimal distribution,direction selection,shift step length and fallback strategy of anchor node could be analyzed by the trilateration.Using the number of virtual beacon received by the unknown node and the distance between the unknown node to the anchor node calculate the virtual force.Then according to the virtual force,the direction was chosen and the anchor nodes were moved.Simulation experiments show that the strategy can make the anchor nodes move according to the specific circumstances of unknown node distribution.It has a high positioning accuracy and strong adaptability.It can successfully shorten the path of the anchor node movement and reduce the number of virtual beacon.Moreover it can effectively avoid the anchor node to enter the network voids area and reduce the number of collinear virtual anchor nodes.

In this paper, we investigate the robust power allocation issue in orthogonal frequency division multiplexing-based cognitive radio networks (CRNs) with unavoidable uncertainties (channel perturbations and variable environment). In this case, to control the performance degradation due to the uncertainties, we maximize the data rate of secondary users (SUs) by considering maximum allowable interference constraints and total power budget of SUs. To solve this problem, we design a controller for a switched affine system with state constraint. This system is based on a distributed projected dynamic system in accordance with the classical distributed convex optimization model for the power allocation and dynamic property of the Nash equilibrium. The robust controller design is on the basis of Lyapunov stability theory and linear matrix inequality to better realize the original power allocation from the control perspective. To the best of our knowledge, we are the first to solve the aforementioned problem by this kind of approach under the control frame, which is more practical for the realization in CRNs. Simulation results are provided to show the validation of the effectiveness of this approach in comparison with iterative water filling algorithm and the worst-case method.

ADP is not only a key substrate for ATP generation, but also a potent inhibitor of mitochondrial permeability transition pore (mPTP). In this study, we assessed how oxidative stress affects the potency of ADP as an mPTP inhibitor and whether its reduction of reactive oxygen species (ROS) production might be involved. We determined quantitatively the effects of ADP on mitochondrial Ca(2+) retention capacity (CRC) until the induction of mPTP in normal and stressed isolated cardiac mitochondria. We used two models of chronic oxidative stress (old and diabetic mice) and two models of acute oxidative stress (ischemia reperfusion (IR) and tert-butyl hydroperoxide (t-BH)). In control mitochondria, the CRC was 344 ± 32 nmol/mg protein. 500 μmol/L ADP increased CRC to 774 ± 65 nmol/mg protein. This effect of ADP seemed to relate to its concentration as 50 μmol/L had a significantly smaller effect. Also, oligomycin, which inhibits the conversion of ADP to ATP by F0F1ATPase, significantly increased the effect of 50 μmol/L ADP. Chronic oxidative stress did not affect CRC or the effect of 500 μmol/L ADP. After IR or t-BH exposure, CRC was drastically reduced to 1 ± 0.2 and 32 ± 4 nmol/mg protein, respectively. Surprisingly, ADP increased the CRC to 447 ± 105 and 514 ± 103 nmol/mg protein in IR and t-BH, respectively. Thus, it increased CRC by the same amount as in control. In control mitochondria, ADP decreased both substrate and Ca(2+)-induced increase of ROS. However, in t-BH mitochondria the effect of ADP on ROS was relatively small. We conclude that ADP potently restores CRC capacity in severely stressed mitochondria. This effect is most likely not related to a reduction in ROS production. As the effect of ADP relates to its concentration, increased ADP as occurs in the pathophysiological situation may protect mitochondrial integrity and function.

In order to associate with using acoustic emission, ultrasonic or other means to locate damage of concrete, based on the concrete CT image information, the research of 3D reconstruction of concrete crack structure was completed by using Amira 5.2.1 3D reconstruction software. Experiments showed that: three dimensional reconstruction of concrete can reflect the real crack structure, and distribution of aggregate concrete of three dimensional model established was basically in accordance with the original CT image, which laid the good foundation to simulate and analysis by using ANSYS finite element software in the future.

CT is one of the effective means to analyze concrete meso-damage. Based on CT image under uniaxial compression, this paper used Amira—three-dimensional reconstruction software to segment the images, extract pores, count and calculate the pore volume .This paper analyzed the corresponding relation between pressure—pore volume diagram and pressure—displacement diagram under cyclic loading. The results showed that: under uniaxial loading condition, pore volume change can be used to describe the change of the meso pore of the concrete specimen, including compaction, initiation, extension and perforation.