Left bundle branch pacing set to outshine biventricular pacing for cardiac resynchronization therapy?

The deleterious effects of long-term right ventricular pacing necessitated the search for alternative pacing sites which could prevent or alleviate pacinginduced cardiomyopathy.Until recently,biventricular pacing(BiVP)was the only modality which could mitigate or prevent pacing induced dysfunction.Further,BiVP could resynchronize the baseline electromechanical dssynchrony in heart failure and improve outcomes.However,the high non-response rate of around 20%-30%remains a major limitation.This non-response has been largely attributable to the direct non-physiological stimulation of the left ventricular myocardium bypassing the conduction system.To overcome this limitation,the concept of conduction system pacing(CSP)came up.Despite initial success of the first CSP via His bundle pacing(HBP),certain drawbacks including lead instability and dislodgements,steep learning curve and rapid battery depletion on many occasions prevented its widespread use for cardiac resynchronization therapy(CRT).Subsequently,CSP via left bundle branch-area pacing(LBBP)was developed in 2018,which over the last few years has shown efficacy comparable to BiVP-CRT in small observational studies.Further,its safety has also been well established and is largely free of the pitfalls of the HBP-CRT.In the recent metanalysis by Yasmin et al,comprising of 6 studies with 389 participants,LBBPCRT was superior to BiVP-CRT in terms of QRS duration,left ventricular ejection fraction,cardiac chamber dimensions,lead thresholds,and functional status amongst heart failure patients with left bundle branch block.However,there are important limitations of the study including the small overall numbers,inclusion of only a single small randomized controlled trial(RCT)and a small follow-up duration.Further,the entire study population analyzed was from China which makes generalizability a concern.Despite the concerns,the meta-analysis adds to the growing body of evidence demonstrating the efficacy of LBBP-CRT.At this stage,one must acknowledge that the fact that still our opinions on this technique are largely based on observational data and there is a dire need for larger RCTs to ascertain the position of LBBPCRT in management of heart failure patients with left bundle branch block.

Left bundle branch pacing vs biventricular pacing in heart failure patients with left bundle branch block:A systematic review and meta-analysis

BACKGROUND Left bundle branch pacing(LBBP)is a novel pacing modality of cardiac resynchronization therapy(CRT)that achieves more physiologic native ventricular activation than biventricular pacing(BiVP).AIM To explore the validity of electromechanical resynchronization,clinical and echocardiographic response of LBBP-CRT.METHODS Systematic review and Meta-analysis were conducted in accordance with the standard guidelines as mentioned in detail in the methodology section.RESULTS In our analysis,the success rate of LBBP-CRT was determined to be 91.1%.LBBP CRT significantly shortened QRS duration,with significant improvement in echocardiographic parameters,including left ventricular ejection fraction,left ventricular end-diastolic diameter and left ventricular end-systolic diameter in comparison with BiVP-CRT.CONCLUSION A significant reduction in New York Heart Association class and B-type natriuretic peptide levels was also observed in the LBBP-CRT group vs BiVP-CRT group.Lastly,the LBBP-CRT cohort had a reduced pacing threshold at follow-up as compared to BiVP-CRT.

COMPLETE KAHLER METRICS WITH POSITIVE HOLOMORPHIC SECTIONAL CURVATURES ON CERTAIN LINE BUNDLES(RELATED TO A COHOMOGENEITY ONE POINT OF VIEW ON A YAU CONJECTURE)

In this article,we study Kahler metrics on a certain line bundle over some compact Kahler manifolds to find complete Kahler metrics with positive holomorphic sectional(or bisectional)curvatures.Thus,we apply a strategy to a famous Yau conjecture with a co-homogeneity one geometry.

3D DEM simulation of hard rock fracture in deep tunnel excavation induced by changes in principal stress magnitude and orientation

To achieve the loading of the stress path of hard rock,the spherical discrete element model(DEM)and the new flexible membrane technology were utilized to realize the transient loading of three principal stresses with arbitrary magnitudes and orientations.Furthermore,based on the deep tunnel of China Jinping Underground Laboratory II(CJPL-II),the deformation and fracture evolution characteristics of deep hard rock induced by excavation stress path were analyzed,and the mechanisms of transient loading-unloading and stress rotation-induced fractures were revealed from a mesoscopic perspective.The results indicated that the stressestrain curve exhibits different trends and degrees of sudden changes when subjected to transient changes in principal stress,accompanied by sudden changes in strain rate.Stress rotation induces spatially directional deformation,resulting in fractures of different degrees and orientations,and increasing the degree of deformation anisotropy.The correlation between the degree of induced fracture and the unloading magnitude of minimum principal stress,as well as its initial level is significant and positive.The process of mechanical response during transient unloading exhibits clear nonlinearity and directivity.After transient unloading,both the minimum principal stress and minimum principal strain rate decrease sharply and then tend to stabilize.This occurs from the edge to the interior and from the direction of the minimum principal stress to the direction of the maximum principal stress on theε1-ε3 plane.Transient unloading will induce a tensile stress wave.The ability to induce fractures due to changes in principal stress magnitude,orientation and rotation paths gradually increases.The analysis indicates a positive correlation between the abrupt change amplitude of strain rate and the maximum unloading magnitude,which is determined by the magnitude and rotation of principal stress.A high tensile strain rate is more likely to induce fractures under low minimum principal stress.

Left bundle branch area pacing combined with implantable cardioverter-defibrillator treatment for heart failure after myocardial infarction

Left bundle branch area pacing(LBBAP)has emerged as a new physiological pacing mode.Previous studies have confirmed the feasibility and efficacy of LBBAP for cardiac resynchronization therapy(CRT)in heart failure(HF)patients with left bundle branch block(LBBB)and a narrower QRS duration(QRSd)to have a higher percentage of super responders,and lower pacing thresholds than biventricular pacing(BiVP).

A new interacting capillary bundle model on the multiphase flow in micropores of tight rocks

Surfactants are widely used in the fracturing fluid to enhance the imbibition and thus the oil recovery rate. However, current numerical models cannot capture the physics behind capillary imbibition during the wettability alteration by surfactants. Although the interacting capillary bundle(ICB) model shows potential in characterizing imbibition rates in different pores during wettability alteration, the existing ICB models neglect the influence of wettability and viscosity ratio on the imbibition behavior, making it difficult to accurately describe the oil-water imbibition behavior within the porous media. In this work,a new ICB mathematical model is established by introducing pressure balance without assuming the position of the leading front to comprehensively describe the imbibition behavior in a porous medium under different conditions, including gas-liquid spontaneous imbibition and oil-water imbibition.When the pore size distribution of a tight rock is known, this new model can predict the changes of water saturation during the displacement process in the tight rock, and also determine the imbibition rate in pores of different sizes. The water saturation profiles obtained from the new model are validated against the waterflooding simulation results from the CMG, while the imbibition rates calculated by the model are validated against the experimental observations of gas-liquid spontaneous imbibition. The good match above indicates the newly proposed model can show the water saturation profile at a macroscopic scale while capture the underlying physics of the multiphase flow in a porous medium at a microscopic scale. Simulation results obtained from this model indicate that both wettability and viscosity ratio can affect the sequence of fluid imbibition into pores of different sizes during the multiphase flow, where less-viscous wetting fluid is preferentially imbibed into larger pores while more-viscous wetting fluid tends to be imbibed into smaller pores. Furthermore, this model provides an avenue to calculate the imbibition rate in pores of different sizes during wettability alteration and capture the non-Darcy effect in micro-and nano-scale pores.

Fiber Bundle Topology Optimization for Surface Flows

This paper presents a topology optimization approach for the surface flows on variable design domains.Via this approach,the matching between the pattern of a surface flow and the 2-manifold used to define the pattern can be optimized,where the 2-manifold is implicitly defined on another fixed 2-manifold named as the base manifold.The fiber bundle topology optimization approach is developed based on the description of the topological structure of the surface flow by using the differential geometry concept of the fiber bundle.The material distribution method is used to achieve the evolution of the pattern of the surface flow.The evolution of the implicit 2-manifold is realized via a homeomorphous map.The design variable of the pattern of the surface flow and that of the implicit 2-manifold are regularized by two sequentially implemented surface-PDE filters.The two surface-PDE filters are coupled,because they are defined on the implicit 2-manifold and base manifold,respectively.The surface Navier-Stokes equations,defined on the implicit 2-manifold,are used to describe the surface flow.The fiber bundle topology optimization problem is analyzed using the continuous adjoint method implemented on the first-order Sobolev space.Several numerical examples have been provided to demonstrate this approach,where the combination of the viscous dissipation and pressure drop is used as the design objective.

Nonholonomic Theory of Principal-direction Orthonormal Basis for a Layer of Surfaces

In order to carry out tensor analysis in a neighborhood of a reference surface,the principal-direction orthogonal basis accompanying with Lame s coefficients or general curvilinear coordinate systems are widely used.A novel kind of field theory termed as the nonholonomic theory of the Principal-Direction Orthonormal Basis(PDOB)is presented systematically in the present paper,in which the formal Christoffel symbols are related directly to the principal and geodesic curvatures with respect to the principal directions of the surface.Furthermore,a systematic and simple way to determine the curvatures of the surface are presented with some examples.It provides a way to recognize qualitatively the bending property of a surface.

专业Bundles策略护理在骨折合并脾脏损伤护理中的应用价值

目的:探讨与分析专业Bundles策略护理在骨折合并脾脏损伤护理中的应用价值.方法:选择2021年2月—2023年2月我院收治的76例骨折合并脾脏损伤患者为研究对象,根据随机信封抽签1∶1原则将其分为Bundles组与对照组,各38例.对照组在围手术期实施常规护理,Bundles组在对照组基础上给予围手术期专业Bundles策略护理,2组护理观察时间均为14 d.记录2组患者的预后恢复、心理变化、并发症与护理满意度情况.结果:Bundles组术中出血量少于对照组,手术时间、术后肛门排气时间、术后肛门排便时间、术后下床活动时间、术后住院时间均短于对照组,组间差异有统计学意义(P<0.05);护理14 d后,2组SDS、SAS评分均低于护理前,且Bundles组低于对照组,差异有统计学意义(P<0.05);Bundles组并发症发生率低于对照组,差异有统计学意义(P<0.05);Bundles组护理满意度高于对照组,差异有统计学意义(P<0.05).结论:专业Bundles策略护理在骨折合并脾脏损伤护理中的应用能促进患者康复,可减少创伤,缓解患者的焦虑与抑郁情绪,并且还能提高安全性,减少不良事件的发生,患者更加满意.

Principal Equatorial Null Geodesic Congruences in the Kerr Metric, and Their Quantum Propagators

Using the Raychaudhuri equation, we associate quantum probability amplitudes (propagators) to equatorial principal ingoing and outgoing null geodesic congruences in the Kerr metric. The expansion scalars diverge at the ring singularity;however, the propagators remain finite, which is an indication that at the quantum level singularities might disappear or, at least, become softened.

Mechanism of principal stress rotation and deformation failure behavior induced by excavation in roadways

The failure modes of rock after roadway excavation are diverse and complex.A comprehensive investigation of the internal stress field and the rotation behavior of the stress axis in roadways is essential for elucidating the mechanism of roadway failure.This study aimed to examine the spatial relationship between roadways and stress fields.The law of stress axis rotation under three-dimensional(3D)stress has been extensively studied.A stress model of roadways in the spatial stress field was established,and the far-field stress state at different spatial positions of the roadways was analyzed.A mechanical model of roadways under a 3D stress state was established using far-field stress solutions as boundary conditions.The distribution of principal stressesσ1,σ2 andσ3 around the roadways and the variation of the stress principal axis were solved.It was found that the stability boundary of the stress principal axis exhibits hysteresis when compared with that of the principal stress magnitudes.A numerical analysis model for spatial roadways was established to validate the distribution of principal stress and the mechanism of principal axis rotation.Research has demonstrated that the stress axis undergoes varying degrees of spatial rotation in different orientations and radial depths.Based on the distribution of principal stress and the rotation law of the stress principal axis,the entire evolution mechanism of the two stress adjustments to form the final failure form after roadway excavation has been revealed.The on-site detection results also corroborate the findings presented in this paper.The results provide a basis for the analysis of the failure mechanism under a 3D stress state.

Optimized CUDA Implementation to Improve the Performance of Bundle Adjustment Algorithm on GPUs

The 3D reconstruction pipeline uses the Bundle Adjustment algorithm to refine the camera and point parameters. The Bundle Adjustment algorithm is a compute-intensive algorithm, and many researchers have improved its performance by implementing the algorithm on GPUs. In the previous research work, “Improving Accuracy and Computational Burden of Bundle Adjustment Algorithm using GPUs,” the authors demonstrated first the Bundle Adjustment algorithmic performance improvement by reducing the mean square error using an additional radial distorting parameter and explicitly computed analytical derivatives and reducing the computational burden of the Bundle Adjustment algorithm using GPUs. The naïve implementation of the CUDA code, a speedup of 10× for the largest dataset of 13,678 cameras, 4,455,747 points, and 28,975,571 projections was achieved. In this paper, we present the optimization of the Bundle Adjustment algorithm CUDA code on GPUs to achieve higher speedup. We propose a new data memory layout for the parameters in the Bundle Adjustment algorithm, resulting in contiguous memory access. We demonstrate that it improves the memory throughput on the GPUs, thereby improving the overall performance. We also demonstrate an increase in the computational throughput of the algorithm by optimizing the CUDA kernels to utilize the GPU resources effectively. A comparative performance study of explicitly computing an algorithm parameter versus using the Jacobians instead is presented. In the previous work, the Bundle Adjustment algorithm failed to converge for certain datasets due to several block matrices of the cameras in the augmented normal equation, resulting in rank-deficient matrices. In this work, we identify the cameras that cause rank-deficient matrices and preprocess the datasets to ensure the convergence of the BA algorithm. Our optimized CUDA implementation achieves convergence of the Bundle Adjustment algorithm in around 22 seconds for the largest dataset compared to 654 seconds for the sequential implementation, resulting in a speedup of 30×. Our optimized CUDA implementation presented in this paper has achieved a 3× speedup for the largest dataset compared to the previous naïve CUDA implementation.

Selective his bundle pacing eliminates crochetage sign:A case report

BACKGROUND Crochetage sign is a specific electrocardiographic manifestation of ostium secundum atrial septal defects(ASDs),which is associated with the severity of the left-to-right shunt.Herein,we reported a case of selective his bundle pacing(SHBP)that eliminated crochetage sign in a patient with ostium secundum ASD.CASE SUMMARY A 77-year-old man was admitted with a 2-year history of chest tightness and shortness of breath.Transthoracic echocardiography revealed an ostium secundum ASD.Twelve-lead electrocardiogram revealed atrial fibrillation with a prolonged relative risk interval,incomplete right bundle branch block,and crochetage sign.The patient was diagnosed with an ostium secundum ASD,atrial fibrillation with a second-degree atrioventricular block,and heart failure.The patient was treated with selective his bundle pacemaker implantation.After the procedure,crochetage sign disappeared during his bundle pacing on the electrocardiogram.CONCLUSION S-HBP eliminated crochetage sign on electrocardiogram.Crochetage sign may be a manifestation of a conduction system disorder.

Left bundle branch area pacing:A new era of cardiac resynchronization therapy?

The recent systematic review and meta-analysis provided a comprehensive focus on the current state of cardiac resynchronization therapy(CRT).The authors determined the feasibility of physiological left bundle branch area pacing(LBBAP)in patients indicated for CRT through a careful analysis of trials.They found that LBBAP was associated with significant reductions in QRS duration,New York Heart Association functional class,B-type natriuretic peptide levels,and pacing thresholds as well as improvements in echocardiographic parameters compared to biventricular pacing.

Using deep neural networks coupled with principal component analysis for ore production forecasting at open-pit mines

Ore production is usually affected by multiple influencing inputs at open-pit mines.Nevertheless,the complex nonlinear relationships between these inputs and ore production remain unclear.This becomes even more challenging when training data(e.g.truck haulage information and weather conditions)are massive.In machine learning(ML)algorithms,deep neural network(DNN)is a superior method for processing nonlinear and massive data by adjusting the amount of neurons and hidden layers.This study adopted DNN to forecast ore production using truck haulage information and weather conditions at open-pit mines as training data.Before the prediction models were built,principal component analysis(PCA)was employed to reduce the data dimensionality and eliminate the multicollinearity among highly correlated input variables.To verify the superiority of DNN,three ANNs containing only one hidden layer and six traditional ML models were established as benchmark models.The DNN model with multiple hidden layers performed better than the ANN models with a single hidden layer.The DNN model outperformed the extensively applied benchmark models in predicting ore production.This can provide engineers and researchers with an accurate method to forecast ore production,which helps make sound budgetary decisions and mine planning at open-pit mines.

Improving pressure ulcer care in intensive care units:Evaluating the impact of bundled care and silver nanoparticle dressings

BACKGROUND Pressure ulcer(PU)are prevalent among critically ill trauma patients,posing substantial risks.Bundled care strategies and silver nanoparticle dressings offer potential solutions,yet their combined effectiveness and impact on patient satisfaction remain insufficiently investigated.AIM To assess the impact of bundled care along with silver nanoparticle dressing on PUs management and family satisfaction in critically ill trauma patients.METHODS A total of 98 critically ill trauma patients with PUs in intensive care unit(ICU)were included in this study.Patients were randomly assigned to either the control group(conventional care with silver nanoparticle dressing,n=49)or the intervention group(bundled care with silver nanoparticle dressing,n=49).The PU Scale for Healing(PUSH)tool was used to monitor changes in status of pressure injuries over time.Assessments were conducted at various time points:Baseline(day 0)and subsequent assessments on day 3,day 6,day 9,and day 12.Family satisfaction was assessed using the Family Satisfaction ICU 24 ques-tionnaire.RESULTS No significant differences in baseline characteristics were observed between the two groups.In the intervention group,there were significant reductions in total PUSH scores over the assessment period.Specifically,surface area,exudate,and tissue type parameters all showed significant improvements compared to the control group.Family satisfaction with care and decision-making was notably higher in the intervention group.Overall family satisfaction was significantly better in the intervention group.CONCLUSION Bundled care in combination with silver nanoparticle dressings effectively alleviated PUs and enhances family satisfaction in critically ill trauma patients.This approach holds promise for improving PUs management in the ICU,benefiting both patients and their families.

A Hybrid Optimization Approach of Single Point Incremental Sheet Forming of AISI 316L Stainless Steel Using Grey Relation Analysis Coupled with Principal Component Analysiss

We investigated the parametric optimization on incremental sheet forming of stainless steel using Grey Relational Analysis(GRA) coupled with Principal Component Analysis(PCA). AISI 316L stainless steel sheets were used to develop double wall angle pyramid with aid of tungsten carbide tool. GRA coupled with PCA was used to plan the experiment conditions. Control factors such as Tool Diameter(TD), Step Depth(SD), Bottom Wall Angle(BWA), Feed Rate(FR) and Spindle Speed(SS) on Top Wall Angle(TWA) and Top Wall Angle Surface Roughness(TWASR) have been studied. Wall angle increases with increasing tool diameter due to large contact area between tool and workpiece. As the step depth, feed rate and spindle speed increase,TWASR decreases with increasing tool diameter. As the step depth increasing, the hydrostatic stress is raised causing severe cracks in the deformed surface. Hence it was concluded that the proposed hybrid method was suitable for optimizing the factors and response.

Rock strength weakening subject to principal stress rotation:Experimental and numerical investigations

During the construction and operation of gas storage reservoirs,changes in the principal stress direction can induce fracture propagation under conditions of lower differential stress,potentially leading to failure in the surrounding rock.However,the weakening of strength due to pure stress rotation has not yet been investigated.Based on fracture mechanics,an enhanced Mohr-Coulomb strength criterion considering stress rotation is proposed and verified with experimental and numerical simulations.The micro-damage state and the evolution of the rock under the pure stress-rotation condition are analyzed.The findings indicate that differential stress exceeding the crack initiation stress is a prerequisite for stress rotation to promote the development of rock damage.As the differential stress increases,stress rotation is more likely to induce rock damage,leading to a transition from brittle to plastic failure,characterized by wider fractures and a more complex fracture network.Overall,a negative exponential relationship exists between the stress rotation angle required for rock failure and the differential stress.The feasibility of applying the enhanced criterion to practical engineering is discussed using monitoring data obtained from a mine-by tunnel.This study introduces new concepts for understanding the damage evolution of the surrounding rock under complex stress paths and offers a new theoretical basis for predicting the damage of gas storage reservoirs.

Robust Principal Component Analysis Integrating Sparse and Low-Rank Priors

Principal Component Analysis (PCA) is a widely used technique for data analysis and dimensionality reduction, but its sensitivity to feature scale and outliers limits its applicability. Robust Principal Component Analysis (RPCA) addresses these limitations by decomposing data into a low-rank matrix capturing the underlying structure and a sparse matrix identifying outliers, enhancing robustness against noise and outliers. This paper introduces a novel RPCA variant, Robust PCA Integrating Sparse and Low-rank Priors (RPCA-SL). Each prior targets a specific aspect of the data’s underlying structure and their combination allows for a more nuanced and accurate separation of the main data components from outliers and noise. Then RPCA-SL is solved by employing a proximal gradient algorithm for improved anomaly detection and data decomposition. Experimental results on simulation and real data demonstrate significant advancements.

A Modified Principal Component Analysis Method for Honeycomb Sandwich Panel Debonding Recognition Based on Distributed Optical Fiber Sensing Signals

The safety and integrity requirements of aerospace composite structures necessitate real-time health monitoring throughout their service life.To this end,distributed optical fiber sensors utilizing back Rayleigh scattering have been extensively deployed in structural health monitoring due to their advantages,such as lightweight and ease of embedding.However,identifying the precise location of damage from the optical fiber signals remains a critical challenge.In this paper,a novel approach which namely Modified Sliding Window Principal Component Analysis(MSWPCA)was proposed to facilitate automatic damage identification and localization via distributed optical fiber sensors.The proposed method is able to extract signal characteristics interfered by measurement noise to improve the accuracy of damage detection.Specifically,we applied the MSWPCA method to monitor and analyze the debonding propagation process in honeycomb sandwich panel structures.Our findings demonstrate that the training model exhibits high precision in detecting the location and size of honeycomb debonding,thereby facilitating reliable and efficient online assessment of the structural health state.