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The Banda Arc in eastern Indonesia has a complex tectonic history involving oceanic and continental subduction, arc‐continent collision and slab rollback. Among these the subduction rollback that began at 16 Ma shaped the regional tectonic configuration, causing notable upper plate extension evidenced by the Banda Sea and Weber Deep. However, the effects of subduction rollback on the lower plate remain less understood. The Aru Trough, part of subducting Australian continental margin, shows strong deformation and high seismicity, making it ideal for studying these effects. Utilizing multibeam bathymetry, seismic reflection profiles, GPS observations, seismicity and focal mechanisms, we investigate the crustal deformation, driving mechanisms and seismic risks in the Aru Trough under the background of Banda slab rollback. The Aru Trough shaped like an inverted triangle narrows from 160 to 40 km southward. It has a fast 53.8 mm/yr extensional rate at present, when combined with its maximum width suggesting a 3 Ma age. High‐angle faults (>60°) are present at its margins and interior. The trough has a high density of seismicity up to 5.9 events per 25 km2, with dominant normal and strike‐slip events, consistent with observed deformational patterns. The low seismic b‐value of 0.82 ± 0.01 suggests a high‐stress state with potential for strong earthquakes (Mw ≥ 6.5). Our findings indicate that lower plate deformation is profoundly influenced by subduction rollback, oblique arc‐continent collision and regional strike‐slip faulting. Understanding deformation in the Aru Trough is crucial for grasping the broader tectonic evolution of the Banda Arc and assessing seismic risks. Key Points: The Aru Trough is deformed by extension as evidenced by high‐angle normal faults and fast present‐day extensional rate of 53.8 mm/yrThe Aru Trough was initiated by slab rollback at 3 Ma with subsequent evolution affected by arc‐continent collision and strike‐slip faultingSeismicity in the Aru Trough shows a high density and low seismic b‐value, indicating high stress and a potential for strong earthquakes [ABSTRACT FROM AUTHOR]

Background: The hybrid strategy of a combination of drug‐eluting stent (DES) and drug‐coated balloon (DCB) is promising for the treatment of de novo diffuse coronary artery disease (CAD). Hypothesis: To investigate the efficacy and functional results of hybrid strategy. Methods: This case series study included patients treated with a hybrid approach for de novo diffuse CAD between February 2017 and November 2021. Postprocedural quantitative flow ratio (QFR) was used to evaluate the functional results. The primary endpoint was procedural success rate. The secondary endpoints were major adverse cardiovascular events (MACE) including cardiac death, myocardial infarction (MI) (including peri‐procedural MI), and target vessel revascularization. Results: A total of 109 patients with 114 lesions were treated. DES and DCB were commonly used in larger proximal segments and smaller distal segments, respectively. The mean QFR value was 0.9 ± 0.1 and 105 patients (96.3%) had values >0.8 in all the treated vessels. Procedural success was achieved in 106 (97.2%) patients. No cases of cardiac death were reported at a median follow‐up of 19 months. Spontaneous MI occurred in three (2.8%) patients and target vessel revascularization in six (5.5%) patients. Estimated 2‐year rate of MACE excluding peri‐procedural MI was higher in the group with lower QFR value (12.1 ± 5.7% vs. 5.6 ± 4.4%, log‐rank p =.035) (cut‐off value 0.9). Conclusion: Hybrid strategy is a promising approach for the treatment of de novo diffuse CAD. Postprocedural QFR has some implications for prognosis and may be helpful in guiding this approach. [ABSTRACT FROM AUTHOR]

In the research of heterogeneous wireless sensor networks, clustering is one of the most commonly used energy-saving methods. However, existing clustering methods face challenges when applied to heterogeneous wireless sensor networks, such as energy balance, node heterogeneity, algorithm efficiency, and more. Among these challenges, a well-designed clustering approach can lead to extended node lifetimes. Efficient selection of cluster heads is crucial for achieving optimal clustering. In this paper, we propose an Enhanced Pelican Optimization Algorithm for Cluster Head Selection (EPOA-CHS) to address these issues and enhance cluster head selection for optimal clustering. This method combines the Levy flight process with the traditional POA algorithm, which not only improves the optimization level of the algorithm, but also ensures the selection of the optimal cluster head. The logistic-sine chaotic mapping method is used in the population initialization, and the appropriate cluster head is selected through the new fitness function. Finally, we utilized MATLAB to simulate 100 sensor nodes within a configured area of 100 × 100 m 2 . These nodes were categorized into four heterogeneous scenarios: m = 0 , α = 0 , m = 0.1 , α = 2 , m = 0.2 , α = 3 , and m = 0.3 , α = 1.5 . We conducted verification for four aspects: total residual energy, network survival time, number of surviving nodes, and network throughput, across all protocols. Extensive experimental research ultimately indicates that the EPOA-CHS method outperforms the SEP, DEEC, Z-SEP, and PSO-ECSM protocols in these aspects. [ABSTRACT FROM AUTHOR]

In a side-pumped laser module, we simulate the pumping power distribution across the cross-section of Nd:YAG rods at varying diameters. The coupled rate equations with the spatial overlap efficiency for a four-level actively Q-switched side-pumped laser are considered complete. After a Q-switched pulse terminates, the expressions of laser output parameters are derived. We assess the single pulse energy, pulse width, and peak power using the analysis function. The 200 Hz Q-switched side-pumped Nd:YAG laser with a peak power of 103 kW and beam quality factors M2 = 1.67 is developed to the validity of theoretical models. [ABSTRACT FROM AUTHOR]

Background: Data regarding the association between sleep apnea (SA) and atrial fibrillation (AF) in hypertrophic cardiomyopathy (HCM) are still limited. We aim to investigate the association of both types of SA, obstructive sleep apnea (OSA) and central sleep apnea (CSA), and nocturnal hypoxemia with AF in HCM. Methods: A total of 606 patients with HCM who underwent sleep evaluations were included. Logistic regression was used to assess the association between sleep disorder and AF. Results: SA was presented in 363 (59.9%) patients, of whom 337 (55.6%) had OSA and 26 (4.3%) had CSA. Patients with SA were older, more often male, had a higher body mass index, and more clinical comorbidities. Prevalence of AF was higher in patients with CSA than patients with OSA and without SA (50.0% versus 24.9% and 12.8%, p < 0.001). After adjustment for age, sex, body mass index, hypertension, diabetes mellitus, cigarette use, New York Heart Association class and severity of mitral regurgitation, SA (OR, 1.79; 95% CI, 1.09–2.94) and nocturnal hypoxemia (higher tertile of percentage of total sleep time with oxygen saturation < 90% [OR, 1.81; 95% CI, 1.05–3.12] compared with lower tertile) were significantly associated with AF. The association was much stronger in the CSA group (OR, 3.98; 95% CI, 1.56–10.13) than in OSA group (OR, 1.66; 95% CI, 1.01–2.76). Similar associations were observed when analyses were restricted to persistent/permanent AF. Conclusion: Both types of SA and nocturnal hypoxemia were independently associated with AF. Attention should be paid to the screening of both types of SA in the management of AF in HCM. [ABSTRACT FROM AUTHOR]

Binocular vision and neural networks (CNNs) are widely seen in modern intelligent vision processing systems, such as robotics, autonomous vehicles, and AR gadgets. However, both the classic semiglobal matching (SGM) and deep CNNs entail substantial computing resource to reach the performance goal. Traditional embedded CPU/graphic processor unit (GPU) cannot simultaneously meet the processing speed and energy requirement, while the specialized circuits dedicated to SGM and CNN processing, respectively, will take considerable hardware and development costs. However, as the popularity of deep learning, neural processing units (NPUs) become prevalent in many embedded and edge devices, which possess high throughput computing power to deal with the matrix operations involved by neural networks. In this work, we attempt to take advantage of the neural processing architectures integrated in SoC chips to accelerate the SGM process, so that the hardware resources will be better utilized instead of investing more resources to create specialized SGM components. Thereby, this letter first deploys SGM on NPU by converting the incompatible operations into the neural-computing flow, and a configurable neural processing element is proposed to flexibly support various vector operation sequences. Then, a hybrid dataflow scheduler and the corresponding hardware modification are introduced to accelerate the cost processing, improving hardware utilization and on-chip memory footprint and access. Our solution runs at 45 fps for an image size of $640\times 480$ , with 128 disparity levels. The speed-energy efficiency is $52\times $ better than the GPU (Jetson TX1) solution with negligible additional hardware overhead and accuracy loss. [ABSTRACT FROM AUTHOR]

The aim of this study was to explore the most updated changing trends of non-rheumatic calcific aortic valve disease (nrCAVD) and reveal possible improvements. We analyzed the age-standardized rates (ASRs) of prevalence, incidence, disability-adjusted life-years (DALYs), and mortality trends of nrCAVD from 1990 to 2019 using data from the Global Burden of Disease (GBD) study 2019. The relations between ASRs and socio-demographic index (SDI) were analyzed with Pearson's correlation coefficients. Decomposition and frontier analysis were employed to reveal the contribution proportion of influence factors and regions where improvement can be achieved. In 2019, there were 9.40 million (95% uncertainty interval (UI): 8.07 to 10.89 million) individuals with nrCAVD globally. From 1990 to 2019, the prevalence rate of nrCAVD increased by 155.47% (95% IU: 141.66% to 171.7%), with the largest increase observed in the middle SDI region (821.11%, 95% UI: 709.87% to 944.23%). Globally, there were no significant changes in the mortality rate of nrCAVD (0.37%, 95% UI: −8.85% to 7.99%). The global DALYs decreased by 10.97% (95% UI: −17.94% to −3.46%). The population attributable fraction (PAF) of high systolic blood pressure increased in the population aged 15–49 years, while it declined slightly in population aged 50+ years. Population growth was the main contributing factor to the increased DALYs across the globe (74.73%), while aging was the driving force in the high-SDI region (80.27%). The Netherlands, Finland, Luxembourg, Germany, and Norway could reduce DALY rates of nrCAVD using their socio-demographic resources. According to these results, we revealed that the burden of nrCAVD increased markedly from 1990 to 2019 in high-SDI and high-middle-SDI regions. There was a downward trend in the mortality due to nrCAVD since 2013, which is possibly owing to profound advances in transcatheter aortic valve replacement. Some countries may reduce burdens of nrCAVD using their socio-demographic resources. [ABSTRACT FROM AUTHOR]

(R)-1-[3,5-bis(trifluoromethyl)phenyl]ethanamine, a key chiral intermediate of selective tetrodotoxin-sensitive blockers, was efficiently synthesized by a bienzyme cascade system formed by with R-ω-transaminase (ATA117) and an alcohol dehydrogenase (ADH) co-expression system. Herein, we report that the use of ATA117 as the biocatalyst for the amination of 3,5-bistrifluoromethylacetophenone led to the highest efficiency in product performance (enantiomeric excess > 99.9%). Moreover, to further improve the product yield, ADH was introduced into the reaction system to promote an equilibrium shift. Additionally, bienzyme cascade system was constructed by five different expression systems, including two tandem expression recombinant plasmids (pETDuet-ATA117-ADH and pACYCDuet-ATA117-ADH) and three co-expressed dual-plasmids (pETDuet-ATA117/pET28a-ADH, pACYCDuet-ATA117/pET28a-ADH, and pACYCDuet-ATA117/pETDuet-ADH), utilizing recombinant engineered bacteria. Subsequent studies revealed that as compared with ATA117 single enzyme, the substrate handling capacity of BL21(DE3)/pETDuet-ATA117-ADH (0.25 g wet weight) developed for bienzyme cascade system was increased by 1.50 folds under the condition of 40 °C, 180 rpm, 0.1 M pH9 Tris-HCl for 24 h. To the best of our knowledge, ours is the first report demonstrating the production of (R)-1-[3,5-bis(trifluoromethyl)phenyl]ethanamine using a bienzyme cascade system, thus providing valuable insights into the biosynthesis of chiral amines. [ABSTRACT FROM AUTHOR]

Multiply and accumulate (MAC) composed of a set of multipliers and one reduction dominates the latency and power of convolutional neural network (CNN) accelerators. Existing approximate multipliers reduce latency and power at a tolerable drop in accuracy, without considering the data distribution (implicitly assuming that data are uniformly distributed). This letter discloses that practical CNNs’ activations and weights are usually Gaussian-like distributed, and the bits of quantized activations and weights are typically not with a probability of 0.5. Thus, we propose an approximate MAC unit design by taking into account the statistical features of input data, to achieve a balanced tradeoff among latency, power, and accuracy. The extensive experiments show that our proposed MAC unit design provides much higher accuracy than state-of-the-art approximate circuits, while the latency, area, and power are similar. [ABSTRACT FROM AUTHOR]

Patients with obstructive hypertrophic cardiomyopathy (HOCM) have large papillary and trabecular muscles (PTMs), which are myocardial tissue. PTMs are usually excluded from the myocardium and included in the left ventricular (LV) cavity when determining LV mass (LVM) and volumes using cardiac magnetic resonance (CMR). This conventional method may result in large distortion of LVM and other indices. We investigated 74 patients with HOCM undergoing CMR imaging. LV short-axis cine images were obtained. LV contours were drawn using two different methods: (1) the conventional method, where PTMs were included in the LV cavity; and (2) the mask method, which includes the TPMs in the LV myocardium. The LV end-diastolic volume (LV-EDV), LV end-systolic volume (LV-ESV), LV ejection fraction (LVEF), and the LVM were then calculated. Fasting NT-proBNP and CK-MB levels were measured with ELISA. In patients with HOCM, mass of PTMs (MOPTM) was 47.9 ± 18.7 g, which represented 26.9% of total LVM. Inclusion of PTMs with the mask method resulted in significantly greater LVM and LVM index (both p < 0.0001) in comparison with those measured with the conventional method. In addition, the mask method produced a significant decrease in LV-EDV and LV-ESV. LVEF was significantly increased with the mask method (64.3 ± 7.9% vs. 77.2 ± 7.1%, p < 0.0001). MOPTM was positively correlated with BMI, septal wall thickness, LVM, LV-EDV, and LV-ESV. LVEF was inversely correlated with MOPTM. In addition, MOPTM correlated positively with NT-proBNP (r = 0.265, p = 0.039) and CK-MB (r = 0.356, p = 0.002). In conclusion, inclusion of PTMs in the myocardium has a substantial impact on quantification of the LVM, LV-EDV, LV-ESV, and LVEF in patients with HOCM. The effects of the PTMs in women was greater than that in men. Furthermore, the MOPTM was positively associated with NT-proBNP and CK-MB. The PTMs might be included in the myocardium when measuring the LV volumes and mass of patients with HOCM. At present, the clinical and prognostic meaning and relevance of the PTMs is not clear and should be further studied. [ABSTRACT FROM AUTHOR]

Sparse convolution neural networks (CNNs) are promising in reducing both memory usage and computational complexity while still preserving high inference accuracy. State-of-the-art sparse CNN accelerators can deliver high throughput by skipping zero weights and/or activations. To operate on only nonzero weights and activations, sparse accelerators typically search pairs of nonzero weights and activations for multiplication-accumulation (MAC) operations. However, the conventional search operation results in a severe limitation in the processing element (PE) array scale because of the enormous demands of internal interconnection and memory bandwidth. In this article, we first provide a design principle to free the search process of sparse CNN accelerations. Specifically, the indexes of the static compressed weights access the dynamic activations directly to avoid the search process for MAC operations. We then develop two search-free inference accelerators, called Swan and Swan-flexible, for sparse CNN accelerations. Swan supports search-free sparse convolution accelerations for interconnection and bandwidth saving. Compared with Swan, Swan-flexible not only has the search-free capability but also comprises a configurable architecture for optimum throughput. We formulate a mathematical optimization problem by combining the configurable characterization with the compressive dataflow to optimize the overall throughput. Evaluations based on a place-and-route process show that the proposed designs, in a compact factor of 4096 PEs, achieve 1.5– $2.7\times $ higher speedup and 6.0– $13.6\times $ better energy efficiency than representative accelerator baselines with the same PE array scale. [ABSTRACT FROM AUTHOR]

As more and more robots enter our life and society, a new era of information technology has begun. The tutorial discusses how to design an efficient circuit and system for Robotics. This brief presents the kinematics, motion planning, perception algorithms and accelerators in robotics and analyzes their advantages, disadvantages, and bottlenecks. In view of the shortcomings of the existing computing system for robotics, we present the potential technique to achieve much higher performance and energy-efficient hardware. [ABSTRACT FROM AUTHOR]

Objectives: Metabolic abnormalities have been associated with long-term cardiac mortality in patients with hypertrophic cardiomyopathy (HCM). Obstructive sleep apnea (OSA) is a risk factor for metabolic abnormalities in general populations, but association between OSA and metabolic abnormalities in HCM is still undefined. This study aimed to investigate the relationship between OSA and metabolic dysfunction in a large series of patients with HCM.Methods: A total of 587 patients with HCM who underwent sleep evaluations at Fuwai Hospital were included. Data from clinical characteristics, polysomnography studies, and metabolic measurements were collected.Results: OSA was present in 344 patients (58.6%). Patients with OSA were older, more often male, and had more clinical comorbidities. Body mass index, blood pressure, fasting glucose, and triglycerides all increased (all P < 0.001) and high-density lipoprotein cholesterol decreased (P = 0.046) with the severity of OSA. In multivariate analysis, moderate to severe OSA and Log (apnea-hypopnea index + 1) were independently associated with obesity (odds ratio [OR], 2.42; 95% CI, 1.48-3.95 and OR, 1.60; 95% CI, 1.31-1.95), elevated blood pressure (OR, 1.99; 95% CI, 1.42-3.26 and OR, 1.31; 95% CI, 1.08-1.60), and elevated triglycerides (OR, 1.71; 95% CI, 1.05-2.78 and OR, 1.24; 95% CI, 1.02-1.51 but not elevated fasting glucose (OR, 0.88; 95% CI, 0.50-1.52 and OR, 1.02; 95% CI, 0.82-1.28) or reduced high-density lipoprotein cholesterol (OR, 1.30; 95% CI, 0.83-2.04 and OR, 1.06; 95% CI, 0.89-1.27).Conclusions: Severity of OSA is independently associated with some profiles of metabolic abnormalities. Clinical trials are required to determine whether OSA treatment improves metabolic abnormalities and long-term outcomes in patients with HCM. [ABSTRACT FROM AUTHOR]

Sparse neural networks (SNNs) are emerging as a promising technique for resource-limited intelligent embedded systems because of the compact model size and the uncompromised accuracy. Recently, most of the dedicated neural network accelerators are beginning to exploit the sparsity of neural network models for performance boost and energy saving. However, existing sparsity-aware accelerators fail to support both sparse weights and activations in neural networks or support them at the same time for both convolutional (Conv) layers and fully connected (FC) layers, which dominate the computational time of neural networks. In this article, we propose a novel sparsity-aware accelerator architecture, called Swallow, to sufficiently improve the inference performance by eliminating ineffectual weights and activations of neural networks. Swallow comprises: 1) a 2-D systolic architecture that fully utilizes the sparsity of both weights and activations in both Conv and FC layers and 2) a sparsity-aware dataflow which is optimized to reuse both weights and activations and to achieve high processing element (PE) utilization by sparse matrix multiplication tiling. Comprehensive evaluations based on a place-and-route process show that Swallow, with 614 GOP/s peak performance and 1.26-W power, outperforms a state-of-the-art sparsity-aware accelerator Cambricon-X by $1.32\times $ in term of energy efficiency. [ABSTRACT FROM AUTHOR]

Background: Protoporphyrin IX (PpIX) and its derivatives are widely used in photodynamic therapy (PDT) to kill cancer cells. Studies showed that the application of these drugs could cause systemic toxic effects in human. However, the molecular pathways involved in PpIX-induced cytotoxicity are not well-defined. Macrophages represent the primary system for protecting tissues from toxicants and initiating the resolution of inflammation. Thus, this study aims to investigate the toxicity of PpIX on macrophages and provide strategies to prevent the toxic effects. Methods: THP-1 macrophages were incubated with PpIX and cell death was measured by MTT assay and Annexin V-PI staining. Intracellular reactive oxygen species (ROS) were evaluated by 2', 7'-Dichlorodihydrofluorescin diacetate (DCFH-DA) and MitoSOX® Red staining and mitochondrial membrane potential (ΔΨm) was detected by tetramethylrhodamine methyl ester (TMRM) staining. Mitogen-activated protein (MAP) kinase activation was assayed by western blotting. Mitochondrial permeability transition pore (mPTP) opening was measured by calcein loading/Co2+ quenching technique and evaluating the release of mitochondrial content. Results: PpIX reduced cell viability in a dose- and time-dependent manner. The cell death was characterized by increasing PI-positive cells, ATP depletion, LDH releasing and rapid ΔΨm loss favoring necrotic features. In addition, PpIX successively induced ROS production, c-Jun N-terminal protein kinase (JNK) activation and mPTP opening. ROS scavengers, N-acetylcysteine (NAC) and deferoxamine (DFX), JNK inhibitor, SP600125, and mPTP inhibitor, cyclosporin A (CsA), all significantly rescued this cell death. Furthermore, mPTP opening was directly regulated by ROS/JNK pathway. Conclusion: PpIX induces a necrotic cell death in THP-1 macrophages through ROS production, JNK activation, and mPTP opening. It is tempting to speculate that blocking the pathways involved in the cytotoxic effects of PpIX will alleviate its side effects. © 2015 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

The electric arc furnace (EAF) contributes to almost one-third of the global iron and steel industry, and its harmonic pollution has drawn attention. An accurate EAF harmonic model is essential to evaluate the harmonic pollution of EAF. In this paper, a data-driven compartmental modeling method (DCMM) is proposed for the multi-mode EAF harmonic model. The proposed DCMM considers the coupling relationship among different frequencies of harmonics to enhance the modeling accuracy, meanwhile, the dimensions of the harmonic dataset are reduced to improve computational efficiency. Furthermore, the proposed DCMM is applicable to establish a multi-mode EAF harmonic model by dividing the multi-mode EAF harmonic dataset into several clusters corresponding to the different modes of the EAF smelting process. The performance evaluation results show that the proposed DCMM is adaptive in terms of establishing the multi-mode model, even if the data volumes, number of clusters, and sample distribution change significantly. Finally, a case study of EAF harmonic data is conducted to establish a multi-mode EAF harmonic model, showing that the proposed DCMM is effective and accurate in EAF modeling. [ABSTRACT FROM AUTHOR]

Intercropping system influences the endophytic microbial abundance, hormone balance, nutrient metabolism and yield, but the molecular mechanism of yield advantage in Camellia oleifera intercropping with peanut is not clear. In this study, the C. oleifera monoculture (CK) and C. oleifera-peanut intercropping (CP) treatments in purple soil were conducted, and the physicochemical properties, gene expressions, signal pathways and crucial microbial abundances were investigated to reveal the molecular mechanism of the yield advantage of intercropped C. oleifera. The results showed that the intercropping system increased in contents of pigment, carbohydrate, available nitrogen and phosphorus in leaf and root, as well as the abundances of Burkholderia, Ralstonia, Delftia, Pseudoalteromonas and Caulobacter, enhanced the relative expression levels of CoSPS, CoGBE, CoGlgP, CoGBSS/GlgA genes to promote sugar metabolism, decreased the relative expression levels of CoASA, CoTSB, CoPAI, CoTDC and CoCYP71A13 genes for inhibiting IAA biosynthesis and signal transduction, as well as microbial diversity, Fusarium, Albifimbria and Coniosporium abundances in root, ultimately improved the fruit yield of C. oleifera. These findings indicate that intercropping system improves the fruit yield by enhancing the nutrient metabolism capability and crucial microbial abundances in root of C. oleifera in purple soil., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this work., (Copyright © 2024 Elsevier Masson SAS. All rights reserved.)

Background: Rapid progression of coronary non-target lesions is essential for the determination of future cardiovascular events. Clinical factors that predict rapid progression of non-target lesions are unclear. The purpose of this study was to identify the clinical predictors of rapid progression and revascularization of coronary non-target lesions., Methods: Consecutive patients with coronary heart disease who had undergone two serial coronary angiograms were enrolled. All coronary non-target lesions were identified and evaluated at both procedures. Multivariable Cox regression analysis was used to investigate the clinical risk factors associated with rapid progression or revascularization of coronary non-target lesions., Results: A total of 1255 patients and 1670 lesions were enrolled. In this cohort of patients, 239 (19%) had rapid progression and 186 (14.8%) underwent revascularization. At the lesion level, 251 (15.0%) had rapid progression and 194 (11.6%) underwent revascularization. The incidence of lesion revascularization and myocardial infarction was significantly higher in patients with rapid progression. In multivariable analyses, hypertension (hazard ratio [HR], 0.76; 95% confidence interval [95% CI], 0.58-1.00; p = 0.049), ST-segment elevation myocardial infarction (STEMI) (HR, 1.46; 95% CI, 1.03-2.07; p = 0.035), glycosylated hemoglobin (HR, 1.16; 95% CI, 1.01-1.33; p = 0.039) and lesion classification (B2/C versus A/B1) (HR, 1.73; 95% CI, 1.27-2.35; p = 0.001) were significant factors associated with rapid progression. The level of triglycerides (HR, 1.10; 95% CI, 1.00-1.20; p = 0.040) and lesion classification (B2/C versus A/B1) (HR, 1.53; 95% CI, 1.09-2.14; p = 0.014) were predictors of lesion revascularization., Conclusions: Hypertension, STEMI, glycosylated hemoglobin and lesion classification may be used as predictors of rapid progression of coronary non-target lesions. The level of triglyceride and lesion classification may predict the revascularization of non-target lesions. In order to prevent future cardiovascular events, increased attention should be paid to patients with these factors., Competing Interests: The authors declare no conflict of interest., (Copyright: © 2024 The Author(s). Published by IMR Press.)

Droplets on nanotextured oil-impregnated surfaces have high mobility due to record-low contact angle hysteresis (∼1-3°), attributed to the absence of solid-liquid contact. Past studies have utilized the ultralow droplet adhesion on these surfaces to improve condensation, reduce hydrodynamic drag, and inhibit biofouling. Despite their promising utility, oil-impregnated surfaces are not fully embraced by industry because of the concern for lubricant depletion, the source of which has not been adequately studied. Here, we use planar laser-induced fluorescence (PLIF) to not only visualize the oil layer encapsulating the droplet (aka wrapping layer) but also measure its thickness since the wrapping layer contributes to lubricant depletion. Our PLIF visualization and experiments show that (a) due to the imbalance of interfacial forces at the three-phase contact line, silicone oil forms a wrapping layer on the outer surface of water droplets, (b) the thickness of the wrapping layer is nonuniform both in space and time, and (c) the time-average thickness of the wrapping layer is ∼50 ± 10 nm, a result that compares favorably with our scaling analysis (∼50 nm), which balances the curvature-induced capillary force with the intermolecular van der Waals forces. Our experiments show that, unlike silicone oil, mineral oil does not form a wrapping layer, an observation that can be exploited to mitigate oil depletion of nanotextured oil-impregnated surfaces. Besides advancing our mechanistic understanding of the wrapping oil layer dynamics, the insights gained from this work can be used to quantify the lubricant depletion rate by pendant droplets in dropwise condensation and water harvesting.

Due to its multifaceted impact in various applications, icing and ice dendrite growth has been the focus of numerous studies in the past. Dendrites on wetting (hydrophilic) and nonwetting (hydrophobic) surfaces are sharp, pointy, branching, and hairy. Here, we show a unique dendrite morphology on state-of-the-art micro/nanostructured oil-impregnated surfaces, which are commonly referred to as slippery liquid-infused porous surfaces or liquid-infused surfaces. Unlike the dendrites on traditional textured hydrophilic and hydrophobic surfaces, the dendrites on oil-impregnated surfaces are thick and lumpy without pattern. Our experiments show that the unique ice dendrite morphology on lubricant-infused surfaces is due to oil wicking into the porous dendritic network because of the capillary pressure imbalance between the surface texture and the dendrites. We characterized the shape complexity of the ice dendrites using fractal analysis. Experiments show that ice dendrites on textured oil-impregnated surfaces have lower fractal dimensions than those on traditional lotus leaf-inspired air-filled porous structures. Furthermore, we developed a regime map that can be used as a design guideline for micro/nanostructured oil-impregnated surfaces by capturing the complex effects of oil chemistry, oil viscosity, and wetting ridge volume on dendrite growth and morphology. The insights gained from this work inform strategies to reduce lubricant depletion, a major bottleneck for the transition of micro/nanostructured oil-impregnated surfaces from bench-top laboratory prototypes to industrial use. This work will assist the development of next-generation depletion-resistant lubricant-infused ice-repellent surfaces.

A 5 kHz sub-nanosecond master oscillator power amplifier (MOPA) laser system was reported in this paper. The master oscillator was an electro-optically Q-switched Nd:YVO 4 laser directly pumped at 879 nm, yielding a pulse energy of 520 µJ and a pulse width of 900 ps at 5 kHz. With two Nd:YVO 4 amplifiers directly pumped at 914 nm, the pulse energy was further scaled up. Under the absorbed pump energy of 11.0 mJ, the pulse energy was amplified to 4.2 mJ, corresponding to a peak power of 4.7 MW. The optical-to-optical efficiency of the amplifiers reached 33.5%.

Background: Cardiovascular comorbidities (CVCs) affect the overall survival (OS) of patients with colorectal cancer (CRC). However, a prognostic evaluation system for these patients is currently lacking., Objectives: This study aimed to develop and validate a nomogram, which takes CVCs into account, for predicting the survival of patients with CRC., Methods: In total, 21,432 patients with CRC were recruited from four centers in China between January 2011 and December 2017. The nomogram was constructed, based on Cox regression, using a training cohort (19,102 patients), and validated using a validation cohort (2,330 patients). The discrimination and calibration of the model were assessed by the concordance index and calibration curve. The clinical utility of the model was measured by decision curve analysis (DCA). Based on the nomogram, we divided patients into three groups: low, middle, and high risk., Results: Independent risk factors selected into our nomogram for OS included age, metastasis, malignant ascites, heart failure, and venous thromboembolism, whereas dyslipidemia was found to be a protective factor. The c-index of our nomogram was 0.714 (95% CI : 0.708-0.720) in the training cohort and 0.742 (95% CI : 0.725-0.759) in the validation cohort. The calibration curve and DCA showed the reliability of the model. The cutoff values of the three groups were 68.19 and 145.44, which were also significant in the validation cohort ( p < 0.001)., Conclusion: Taking CVCs into account, an easy-to-use nomogram was provided to estimate OS for patients with CRC, improving the prognostic evaluation ability., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wang, Liu, Liang, Ba, Ma, Xu, Wang, Wang, Tian, Yang, Gao, Qiao, Qu, Yang, Guo, Zhao, Ao, Zheng, Yuan and Yang.)