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Abstract The optical detection methodology stands as a predominant approach for detecting underwater bubbles. Nonetheless, owing to poor underwater imaging conditions, the acquired image depth of field proves inadequate, posing significant challenges for the study and identification of underwater micro bubbles. In this investigation, we present a multi-focus image fusion model tailored for underwater micro bubbles, grounded in the Denoising Diffusion Probabilistic Model. We also propose a multi-focus image fusion metric suitable for underwater scenarios with micro bubbles. Experimental validation on the constructed dataset demonstrates that our model achieves better results than traditional methods. These results substantiate the model’s efficacy in conserving image characteristics and attaining multi-focus fusion. Consequently, this research furnishes substantial empirical support for subsequent endeavors in image-related tasks.

Abstract Wide-bandgap (WBG) perovskite solar cells (PSCs) are employed as top cells of tandem cells to break through the theoretical limits of single-junction photovoltaic devices. However, WBG PSCs exhibit severe open-circuit voltage (V oc) loss with increasing bromine content. Herein, inhomogeneous halogen-phase distribution is pointed out to be the reason, which hinders efficient extraction of carriers. We thus propose to form homogeneous halogen-phase distribution to address the issue. With the help of density functional theory, we construct a double-layer structure (D-2P) based on 2-(9H-Carbazol-9-yl)ethyl]phosphonic acid molecules to provide nucleation sites for perovskite crystallization. Homogeneous perovskite phase is achieved through bottom-up templated crystallization of halogen component. The efficient carrier extraction reduces the Shockley-Read-Hall recombination, resulting in a high V oc of 1.32 V. As a result, D-2P-treated device (1.75 eV) achieves a record power conversion efficiency of 20.80% (certified 20.70%), which is the highest value reported for WBG (more than 1.74 eV) PSCs.

Abstract Background Small-cell lung cancer (SCLC) is a leading cause of cancer-related death. However, the prognostic value of the tumor shrinkage rate (TSR) after chemotherapy for SCLC is still unknown. Methods We performed a retrospective analysis of 235 patients with SCLC. The TSR cutoff was determined based on receiver-operating characteristic curve analysis. The associations of TSR with progression-free survival (PFS) and overall survival (OS) were assessed using univariate and multivariate Cox proportional hazards models. Survival curves were obtained by the Kaplan–Meier method and compared using the log-rank test. Recurrence patterns after first-line treatment were summarized in a pie chart. A nomogram was constructed to validate the predictive role of the TSR in SCLC. Results The TSR cutoff was identified to be − 6.6%. Median PFS and OS were longer in the group with a TSR − 6.6%. Brain metastasis-free survival was better in the group with a TSR

The permeable breakwater is an innovative, eco-friendly coastal protection structure that reduces wave impact while minimizing “dead water” and environmental harm. This study introduces a perforated pipe breakwater design with an increasing pipe diameter from top to bottom, evaluated through physical model tests using transmission coefficient Kt and reflection coefficient Kr serving as the primary parameters. The results indicate that Kt decreases as the relative width (B/L), wave steepness (H/L), and relative water depth (h/L) increase, but rises with a steeper breakwater slope. When B/L exceeds 0.3, H/L surpasses 0.06, or the h/L ratio is greater than 0.3, Kt gradually declines until reaching a stable state, resulting in a more pronounced wave reduction. As B/L and H/L increase, the coefficient Kr initially drops, then rises. The slope ratio of 1:1.5 demonstrates the most effective wave energy dissipation, with primary dissipation occurring on the front slope. The mixed pipe diameter design shows superior wave absorption over a uniform diameter. Compared to a porous horizontal plate, the perforated pipe breakwater exhibits better wave absorption. These findings offer valuable guidance for designing eco-friendly coastal protection projects.

Bubble detection in water plays important roles in human exploration and management of the ocean. This research presents a detection technique based on laser polarization dual-mode fusion, aiming at solving the difficulties of light scattering intensity characteristics that are hard to extract and the small particle size of underwater bubbles that are hard to detect. To increase the precision of bubble identification, an image fusion technique based on bubble polarization degree is first presented. Second, we quantitatively investigate the grayscale undulation of bubbles with different size and number distributions in the image from both statistical and experimental aspects, introduce image grayscale fluctuation (GF) to fuse two modes of laser polarization and the image, establish an a posteriori distribution probability model of discriminating features such as the size and number of bubbles, and realize the bubble small-sample, multi-source data fitting. The findings demonstrate that dynamic bubble detection in the 50–1000 μm and 100–2000 cm−3 ranges can achieve more than 95%, as well as more than a 93%, accuracy in quantity distribution and bubble size change. This technique achieves the continuous perception of bubble features in complicated underwater environments, and offers a possible application scheme for the detection of marine bubble environments.

In this paper, molybdenum disulfide was grown on the surface of iron-containing tailings by hydrothermal method, and a series of highly efficient activated persulfate (PMS) iron-based catalysts were successfully prepared. The results show that in the CTM 1–200/PMS system, the additional ratio of tailings and the hydrothermal temperature have important effects on the catalyst. The catalyst prepared under the conditions of CT:MoS2 (molar ratio 1:1) and hydrothermal temperature of 200 °C (CTM 1–200) had the best degradation effect on BPA, and the degradation effect was increased by four times. The reason for the improvement of degradation efficiency is that the introduction of MoS2 accelerates the REDOX cycle between Fe(II)/Fe(III), and the reduction of Fe(III) is mainly related to Mo(IV), while the reduction capacity of S is relatively weak. Molybdenum disulfide/iron tailing composite material provides a way for tailings to solve the problem of water pollution. HIGHLIGHTS Hydrothermal preparation of iron tailings supported MoS2 catalyst can effectively activate PMS to degrade BPA.; Mo element is harmless, solves resource waste of tailings, degrades BPA in wastewater and realizes ‘pollution control with waste’.; This study explores the synergistic reaction mechanism between MoS2 and iron tailings and proposes a REDOX reaction model in which MoS2 dual pathways accelerate the Fe(II)/Fe(III) cycle.;

Abstract The retina is an important target organ of diabetes mellitus, with increasing evidence from patients and animal models suggesting that retinal pigment epithelium (RPE) may serve as an early marker for diabetes-related damages. However, their longitudinal relationship and the biological underpinnings remain less well understood. Here, we demonstrate that reduced in vivo measurements of RPE thickness (RPET) represents a significant risk factor for future type 2 diabetes mellitus (T2DM) and its microvascular phenotypes. After performing systematic analyses of circulating plasma metabolites using two complementary approaches, we identify a wide range of RPET metabolic fingerprints that are independently associated with reduced RPET. These fingerprints hold their potential to improve predictability and clinical utility for stratifying future T2DM and related microvascular phenotypes beyond traditional clinical indicators, providing insights into the promising role of retinas as a window to systemic health.

Transparent conductive films (TCFs) are crucial components of solar cells. In this study, F, Cl, and Ga co-doped ZnO (FCGZO) TCFs were deposited onto a glass substrate using the sol-gel spin-coating method and rapid thermal annealing. The effects of F-doping content on the structural, morphological, electrical, and optical properties of FCGZO films were examined by XRD, TEM, FE-SEM, PL spectroscopy, XPS, Hall effects testing, and UV–vis–NIR spectroscopy. All prepared ZnO films exhibited a hexagonal wurtzite structure and preferentially grew along the c axis perpendicular to the substrate. Changes in the doping concentration of F changed the interplanar crystal spacing and O vacancies in the film. At a doping ratio of 2% (in mole), the F, Cl, and Ga co-doped ZnO film exhibited the best photoelectric performance, with a carrier concentration of 2.62 × 1020 cm−3, mobility of 14.56 cm2/(V·s), and resistivity of 1.64 × 10−3 Ω·cm. The average transmittance (AT) in the 380–1 600 nm region nearly 90% with air as the reference, and the optical band gap was 3.52 eV.

The lower semi-open box (LSOB) girder is widely used in large-span bridges due to its favorable stress performance and cost-effectiveness. The vortex-induced vibration (VIV) of the LSOB girder was studied by using a 1:55 section model wind tunnel test. The test results show that there are obvious vertical and torsional VIV intervals with significant amplitudes at each angle of attack with the damping ratios of about 0.35%. The CFD numerical simulations indicate that VIVs of LSOB girders are mainly induced by two types of vortices: one at the inclined webs of leeward wind nozzles and another at the upstream upper surfaces of the deck. Conventional aerodynamic vibration suppression measures, such as the lower central stabilizing plate and the guide vane at the gantry rail, demonstrate that the lower central stabilizing plate can reduce the VIV response at all wind angles of attack, decreasing vertical amplitude by 40%–50% and torsional amplitude by 10%–25%. Although adding a guide vane further optimizes the VIV performance, its effect is limited. Installing the lower central stabilizing plate helps redistribute vortices below the girder, transforming large vortices into smaller ones, most of which do not detach, thereby reducing vortex shedding intensity in the wake area. The bilateral guide vanes at the maintenance car track further weaken the wake vortices at the diagonal webs on the leeward side.

Abstract Background Retinal structural abnormalities have been found to serve as biomarkers for cardiovascular disease (CVD). However, the association between retinal nerve fiber layer (RNFL) thickness and the incidence of CVD events remains inconclusive, and relevant longitudinal studies are lacking. Therefore, we aimed to examine this link in two prospective cohort studies. Methods A total of 25,563 participants from UK Biobank who were initially free of CVD were included in the current study. Another 635 participants without retinopathy at baseline from the Chinese Guangzhou Diabetes Eye Study (GDES) were adopted as the validation set. Measurements of RNFL thickness in the macular (UK Biobank) and peripapillary (GDES) regions were obtained from optical coherence tomography (OCT). Adjusted hazard ratios (HRs), odd ratios (ORs), and 95% confidence intervals (CI) were calculated to quantify CVD risk. Results Over a median follow-up period of 7.67 years, 1281 (5.01%) participants in UK Biobank developed CVD events. Each 5-μm decrease in macular RNFL thickness was associated with an 8% increase in incident CVD risk (HR = 1.08, 95% CI: 1.01–1.17, p = 0.033). Compared with participants in the highest tertile of RNFL thickness, the risk of incident CVD was significantly increased in participants in the lowest thickness tertile (HR = 1.18, 95% CI: 1.01–1.38, p = 0.036). In GDES, 29 (4.57%) patients developed CVD events within 3 years. Lower average peripapillary RNFL thickness was also associated with a higher CVD risk (OR = 1.35, 95% CI: 1.11–1.65, p = 0.003). The additive net reclassification improvement (NRI) was 21.8%, and the absolute NRI was 2.0% by addition of RNFL thickness over the Framingham risk score. Of 29 patients with incident CVD, 7 were correctly reclassified to a higher risk category while 1 was reclassified to a lower category, and 21 high risk patients were not reclassified. Conclusions RNFL thinning was independently associated with increased incident cardiovascular risk and improved reclassification capability, indicating RNFL thickness derived from the non-invasive OCT as a potential retinal fingerprint for CVD event across ethnicities and health conditions. Trial registration ISRCTN 15853192

Addressing the issues of weak echo signals and strong background interference in the laser detection of ships’ wakes, an analysis of the laser backscatter detection characteristics of ships’ wakes has been conducted. Based on the Monte Carlo method, a simulation model for the dual-mode fusion detection of ship wake bubbles using laser technology was constructed under different target characteristics. A dual-mode fusion detection system for ships’ wakes was designed, and an indoor experimental platform for the dual-mode fusion detection of ship wake bubbles using laser technology was established. To address problems such as a wide range of echo signal intensity changes, severe signal fluctuations, low resolution, poor image contrast, and blurred target edge information, an algorithm based on multi-timescale hierarchical fusion signal processing and temporal difference accumulation image processing was proposed. Verification experiments for ship wake detection were conducted, which revealed that the dual-mode fusion detection method for ship wake bubbles using laser technology can effectively enhance the detection signal-to-background ratio and counter the maneuvering evasion of underwater weapons by ships. It achieved high sensitivity, large dynamic range, high resolution, and a wide field of view detection and real-time signal processing of ship wake bubble targets of different magnitudes against a strong reverberation background. The effectiveness of the dual-mode fusion detection mode was validated, providing theoretical support for the overall system design and parameter settings.

In this work, iron was recovered from a kind of iron-rich pickling sludge by an acid leaching process, and the recycled iron was used as a catalyst to activate peroxydisulfate (PS) for the degradation of phenol. Different kinds of sludge catalysts were prepared by different drying methods such as ordinary drying (Ods), freeze drying (Fds) and vacuum drying (Vds). The degradation performance of the different catalysts/PS system under different conditions was explored, the vacuum drying sludge catalyst (Vds) has the best activity in a wide pH range (pH = 3–10) and a wide temperature range (0–40 °C). At the same time, the effect of a series of chelating agents (Oxalic acid (OA), Citric acid (CA), Tartaric acid (TA), Malic acid (DL-MA) and Ethylenediaminetetraacetic acid (EDTA)) on Vds/PS system was verified, and TA was selected as the best chelating agent to promote the degradation of the second stage where the degradation rate is limited. The quenching experiment and electron paramagnetic resonance (EPR) analysis indicated that hydroxyl radical (·OH) and sulfate radical (SO4̇−) were responsible for the abatement of the organic contaminant with ·OH playing a more important role. In summary, this study proposed an environmentally-friendly approach for the application of iron-rich pickling sludge in the remediation of phenol-contaminated water. HIGHLIGHTS An effective method was found to recover iron from pickling sludge to activate persulfate for phenol degradation.; The reaction continued more effectively in the subsequent stage after TA was added.; Vds/PS/TA system has the potential of application in a wide pH range (pH = 3–10) and a wide temperature range (0–40 °C).;

In this paper, the tunnel temperature (air, structure, and rock) and wall heat flow were monitored in-situ for 63 days in cold and warm terms. The in-situ monitoring results reveal that the traffic-induced thermal effect (TTE) is one of the main factors inducing tunnel temperature variation. The tunnel wall temperature change rate caused by traffic-induced thermal effect is 20.53–43.18% in the cold term. A simplified analytical solution for the tunnel wall temperature is proposed based on Green's function and verified by the monitoring data in this study. The influence coefficients of traffic flow formed by different vehicle types on the tunnel wall temperature in the cold and warm terms are obtained using an optimized machine learning method. The impact ratio is LDV:HDV: HDT = 6:1:1 in the cold (that of LDT is minimal); LDV:HDV:LDT: HDT = 1:8:4:10 in the warm. The assumed tunnel heat absorption ratio (THAR) ranges from 0.19 to 2.05% in the cold term and −0.22 to 0.52% in the warm. The thermal loss degree in tunnel lining is lower than that of ignoring the traffic-induced thermal effect in the cold term. TTE increases THAR by about 1.45% and partly delays the heat dissipation of the tunnel wall. Furthermore, a dynamic network model with vehicles as moving heat sources is established to investigate the thermal effect of different vehicle types. The study results provide reference to new ideas and calculation solutions for designing cold-region highway tunnels and implementing new energy utilization systems.

Previous researches have emphasized a trypsin-centered theory of acute pancreatitis (AP) for more than a century. With additional studies into the pathogenesis of AP, new mechanisms have been explored. Among them, the role of immune response bears great importance. Pro-inflammatory substances, especially damage-associated molecular patterns (DAMPs), play an essential role in activating, signaling, and steering inflammation. Meanwhile, activated neutrophils attach great importance to the immune defense by forming neutrophil extracellular traps (NETs), which cause ductal obstruction, premature trypsinogen activation, and modulate inflammation. In this review, we discuss the latest advances in understanding the pathological role of DAMPs and NETs in AP and shed light on the flexible crosstalk between these vital inflammatory mediators. We, then highlight the potentially promising treatment for AP targeting DAMPs and NETs, with a focus on novel insights into the mechanism, diagnosis, and management of AP.

Abstract Background Exosomes as the main therapeutic vectors of mesenchymal stem cells (MSC) for inflammatory bowel disease (IBD) treatment and its mechanism remain unexplored. Tumor necrosis factor-α stimulated gene 6 (TSG-6) is a glycoprotein secreted by MSC with the capacities of tissue repair and immune regulation. This study aimed to explore whether TSG-6 is a potential molecular target of exosomes derived from MSCs (MSCs-Exo) exerting its therapeutic effect against colon inflammation and repairing mucosal tissue. Methods Two separate dextran sulfate sodium (DSS) and 2,4,6-trinitrobenzenesulfonic acid (TNBS)-induced IBD mouse models were intraperitoneally administered MSCs-Exo extracted from human umbilical cord MSC (hUC-MSC) culture supernatant. Effects of MSCs-Exo on intestinal inflammation, colon barrier function, and proportion of T cells were investigated. We explored the effects of MSCs-Exo on the intestinal barrier and immune response with TSG-6 knockdown. Moreover, recombinant human TSG-6 (rhTSG-6) was administered exogenously and colon inflammation severity in mice was evaluated. Results Intraperitoneal injection of MSCs-Exo significantly ameliorated IBD symptoms and reduced mortality rate. The protective effect of MSCs-Exo on intestinal barrier was demonstrated evidenced by the loss of goblet cells and intestinal mucosa permeability, thereby improving the destruction of tight junctions (TJ) structures and microvilli, as well as increasing the expression of TJ proteins. Microarray analysis revealed that MSCs-Exo administration downregulated the level of pro-inflammatory cytokines and upregulated the anti-inflammatory cytokine in colon tissue. MSCs-Exo also modulated the response of Th2 and Th17 cells in the mesenteric lymph nodes (MLN). Reversely, knockdown of TSG-6 abrogated the therapeutic effect of MSCs-Exo on mucosal barrier maintenance and immune regulation, whereas rhTSG-6 administration showed similar efficacy to that of MSCs-Exo. Conclusions Our findings suggested that MSCs-Exo protected against IBD through restoring mucosal barrier repair and intestinal immune homeostasis via TSG-6 in mice.

Background and AimsThis study aimed to develop an interpretable random forest model for predicting severe acute pancreatitis (SAP).MethodsClinical and laboratory data of 648 patients with acute pancreatitis were retrospectively reviewed and randomly assigned to the training set and test set in a 3:1 ratio. Univariate analysis was used to select candidate predictors for the SAP. Random forest (RF) and logistic regression (LR) models were developed on the training sample. The prediction models were then applied to the test sample. The performance of the risk models was measured by calculating the area under the receiver operating characteristic (ROC) curves (AUC) and area under precision recall curve. We provide visualized interpretation by using local interpretable model-agnostic explanations (LIME).ResultsThe LR model was developed to predict SAP as the following function: -1.10-0.13×albumin (g/L) + 0.016 × serum creatinine (μmol/L) + 0.14 × glucose (mmol/L) + 1.63 × pleural effusion (0/1)(No/Yes). The coefficients of this formula were utilized to build a nomogram. The RF model consists of 16 variables identified by univariate analysis. It was developed and validated by a tenfold cross-validation on the training sample. Variables importance analysis suggested that blood urea nitrogen, serum creatinine, albumin, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, calcium, and glucose were the most important seven predictors of SAP. The AUCs of RF model in tenfold cross-validation of the training set and the test set was 0.89 and 0.96, respectively. Both the area under precision recall curve and the diagnostic accuracy of the RF model were higher than that of both the LR model and the BISAP score. LIME plots were used to explain individualized prediction of the RF model.ConclusionsAn interpretable RF model exhibited the highest discriminatory performance in predicting SAP. Interpretation with LIME plots could be useful for individualized prediction in a clinical setting. A nomogram consisting of albumin, serum creatinine, glucose, and pleural effusion was useful for prediction of SAP.

Background and AimsThe aim of this study was to apply machine learning models and a nomogram to differentiate critically ill from non-critically ill COVID-19 pneumonia patients.MethodsClinical symptoms and signs, laboratory parameters, cytokine profile, and immune cellular data of 63 COVID-19 pneumonia patients were retrospectively reviewed. Outcomes were followed up until Mar 12, 2020. A logistic regression function (LR model), Random Forest, and XGBoost models were developed. The performance of these models was measured by area under receiver operating characteristic curve (AUC) analysis.ResultsUnivariate analysis revealed that there was a difference between critically and non-critically ill patients with respect to levels of interleukin-6, interleukin-10, T cells, CD4+ T, and CD8+ T cells. Interleukin-10 with an AUC of 0.86 was most useful predictor of critically ill patients with COVID-19 pneumonia. Ten variables (respiratory rate, neutrophil counts, aspartate transaminase, albumin, serum procalcitonin, D-dimer and B-type natriuretic peptide, CD4+ T cells, interleukin-6 and interleukin-10) were used as candidate predictors for LR model, Random Forest (RF) and XGBoost model application. The coefficients from LR model were utilized to build a nomogram. RF and XGBoost methods suggested that Interleukin-10 and interleukin-6 were the most important variables for severity of illness prediction. The mean AUC for LR, RF, and XGBoost model were 0.91, 0.89, and 0.93 respectively (in two-fold cross-validation). Individualized prediction by XGBoost model was explained by local interpretable model-agnostic explanations (LIME) plot.ConclusionsXGBoost exhibited the highest discriminatory performance for prediction of critically ill patients with COVID-19 pneumonia. It is inferred that the nomogram and visualized interpretation with LIME plot could be useful in the clinical setting. Additionally, interleukin-10 could serve as a useful predictor of critically ill patients with COVID-19 pneumonia.

Science and technology innovation are crucial components underpinning agriculture. We constructed an evaluation framework including 4 pillars and 21 indicators, taking 31 provinces in China as examples to examine the level of agriculture science and technology development from a regional perspective. We found that there is an obvious gap between east and west nationwide, and that only about half of the provinces have reached the high and medium levels. It was worth noting that the innovation conditions in Shanghai and Beijing presented huge advantages, of vital importance to a first-class talent team, a complete innovation system, a stable and prosperous market, and active exchanges and cooperation. In addition, to maximize the transformation of agricultural science and technology achievements into real productivity, local government should also strengthen the construction of agricultural research and innovation platforms, technology transfer, and transformation of results. The findings advance understanding of the strengths and weaknesses of the evaluation subjects’ agricultural science and technology development from a regional perspective and are expected to provide some basis for the government and stakeholders to make relevant decisions.

We modified the PEDOT:PSS anode buffer layer in P3HT:PCBM bulk heterojunction polymer solar cells by spin-coating the solvent N,N-dimethylacetamide (DMAC). This modification significantly enhanced the efficiency of the ITO/PEDOT:PSS/DMAC/P3HT:PCBM/LiF/Al solar cells. The DMAC-treated device spin-coated at 3000 rpm exhibited a power conversion efficiency (PCE) of 3.74%, a 59% improvement over that of an untreated cell. To study the mechanism of improving the conversion efficiency, we characterized many parameters, including the light and dark I-V curves, external quantum efficiency, active layer absorption spectrum, transmission spectrum of ITO:PEDOTPSS, PEDOT:PSS surface morphology, and electrical conductivity. Modifying the PEDOT:PSS film increased conductivity, making it more conducive to hole extraction and collection. Our findings suggest that modifying the anode buffer layer can improve photoelectric conversion efficiency.

The effects of liquid crystal (LC) reflectors on semitransparent polymer solar cells (PSCs) were investigated in this paper. By improving the cathode, we manufactured semitransparent PSCs based on the conventional PSCs. We then incorporated the LC reflector into the semitransparent PSCs, which increased the power conversion efficiency (PCE) from 2.11% to 2.71%. Subsequently adjusting the concentration and spinning speed of the active layer material changed its thickness. The maximum light absorption for the active layer was obtained using the optimum thickness, and the PCE eventually reached 3.01%. These results provide a reference for selecting LC reflectors that are suitable for different active layer materials to improve the PCE of semitransparent PSCs.

Aims To investigate the association between the choriocapillaris flow deficit percentage (CC FD%) and the 1-year incidence of referable diabetic retinopathy (RDR) in participants with type 2 diabetes mellitus (DM). Methods This prospective cohort study included participants with type 2DM. The DR status was graded based on the ETDRS-7 photography. The CC FD% in the central 1mm area, inner circle (1.5mm to 2.5mm), outer circle (2.5mm to 5.0mm) and the entire area in the macular region were measured using swept-source optical coherence tomography angiography (SS-OCTA). Logistic regression analysis was used to examine the association between baseline CC FD% and 1-year incident RDR. Results A total of 1222 patients (1222 eyes, mean age: 65.1±7.4 years) with complete baseline and 1-year follow-up data were included. Each 1% increase in baseline CC FD% was significantly associated with a 1.69 times (relative risk 2.69; 95% CI 1.53 to 4.71; p=0.001) higher odds for development of RDR after 1-year follow-up, after adjusting for other confounding factors. Conclusions A greater baseline CC FD% detected by SS-OCTA reliably predicted higher risks of RDR in participants with type 2DM. Thus, CC FD% may act as a novel biomarker for predicting the onset and progression of DR. [ABSTRACT FROM AUTHOR]