Residual Space Research Articles

A middle lobe sparing sleeve resection versus bilobectomy for right lower central non-small cell lung cancer: a retrospective propensity score matched cohort study

ObjectivesThe right lower sleeve lobectomy is a rarely performed major lung resection.This study aims to evaluate the safety and effectiveness of this procedure by comparing to right lower bilobectomy in non-small cell lung cancer patients.MethodsWe retrospectively reviewed a prospective database of non-small cell lung cancer patients who underwent right lower sleeve lobectomy (group S) or right lower bilobectomy (group B) from January 2014 to January 2020 in Shanghai Pulmonary Hospital. Propensity score matching method was applied to balance confounders between the two groups, resulting in 41 matched pairs.The analysis was performed to compare perioperative outcomes, long-term survival, and postoperative pulmonary volume between the two groups.ResultsNo significant differences in the characteristics were observed between the two matched groups.Major postoperative complications developed in 31.7% of the patients in group B and 12.1% of the patients in group S (P = 0.032).Intervention rate for surgical residual cavity in group B is significantly higher than those patients in group S(21.9%vs7.3%,p = 0.037).The postoperative right lateral and overall lung volume in group S were both significantly larger than that in group B (P = 0.026,P = 0.001,respectively).ConclusionsCompared to bi-lobectomy, a middle lobe sparing sleeve resection obtains a less prevalence of major complications, smaller postoperative residual air space and similar long-term survival for selected central right lower NSCLC patients.

Research on Genetic Algorithm Optimization with Fusion Tabu Search Strategy and Its Application in Solving Three-Dimensional Packing Problems

Symmetry is an important principle and characteristic that is prevalent in nature and artificial environments. In the three-dimensional packing problem, leveraging the inherent symmetry of goods and the symmetry of the packing space can enhance packing efficiency and utilization.The three-dimensional packing problem is an NP-hard combinatorial optimization problem in the field of modern logistics, with high computational complexity. This paper proposes an improved genetic algorithm by incorporating a fusion tabu search strategy to address this problem. The algorithm employs a three-dimensional loading mathematical model and utilizes a wall-building method under residual space constraints for stacking goods. Furthermore, adaptation of fitness variation strategy, chromosome adjustment, and tabu search algorithm are introduced to balance the algorithm’s global and local search capabilities, as well as to enhance population diversity and convergence speed. Through testing on benchmark cases such as Bischoff and Ratcliff, the improved algorithm demonstrates an average increase of over 3% in packing space utilization compared to traditional genetic algorithms and other heuristic algorithms, validating its feasibility and effectiveness. The proposed improved genetic algorithm provides new insights for solving three-dimensional packing problems and optimizing logistics loading schedules, offering promising prospects for various applications.

Evaluation of the Literature on the Use of Space Underneath Elevated Highways in Urban Leftover Space Renewal

The construction of urban highways within and around the city has resulted in a significant amount of residual spaces, which are rarely incorporated into official planning and design efforts. This literature review paper provides an overview of space underneath elevated highways delivered by urban leftover space: What types of leftover space have been discussed? Which underneath elevated highways have been identified in leftover space? 112 scientific papers were analyzed for their 1) leftover space terms applied, 2) space underneath elevated highways studied, 3) current or potential underneath elevated highways discussed. Through the review, we found that although different types of space have been identified in leftover space, most studies did not consider underneath elevated highways synergies and trade-offs. The literature review highlights two knowledge gaps for future research: Firstly, the existing research on residual space under urban viaducts has been exhaustive in terms of connecting with environmental attributes. Secondly, the content of the social interaction and use of the remaining space under the viaducts can be connected to the content of the environmental attributes. The existing gaps in the research indicate the importance of exploring the potential impacts aimed at utilizing leftover spaces. By highlighting the value of the environmental attributes of under-bridge spaces, the literature study promotes the recognition of the association of social interactions with the environmental attributes of under-bridge spaces and further outlines future research directions for the remaining under-bridge spaces in the urban design process.

The Effect of SiO2 Particle Size on Crystallization Behavior and Space Charge Properties for SiO2/MMT/LDPE Composites.

The matrix material used in this paper was low-density polyethene (LDPE), and the added particles selected were silicon oxide (SiO2) particles and montmorillonite (MMT) particles. The sizes of the SiO2 particles were 1 µm, 30 nm, and 100 nm, respectively; three kinds of SiO2/MMT/LDPE multi-component composites were prepared based on MMT/LDPE composites doped with MMT particles. The effect of the SiO2 particle size on the crystallization behavior and space charge properties of SiO2/MMT/LDPE composites was studied. The crystalline behaviors and crystallinity of the materials were analyzed. At the same time, the changes in the relative dielectric constant εr and loss factor tanδ for each material with the influence of frequency were studied, and the space charge accumulation, residual characteristics, and apparent charge mobility of each material were explored. The results show that the smaller the size of the added particles, the smaller the grain size and the clearer the grain outline for the multi-composite material. After adding 30 nm SiO2 particles, the crystallinity of the material increases significantly. The microstructure formed by the addition of 100 nm SiO2 particles effectively restricts molecular chain movement and makes it difficult to establish the polarization of the composite. The incorporation of large-size particles can reduce the proportion of the crystalline structure for the material as a whole, resulting in the formation of a new structure to promote charge transfer. Among the three kinds of SiO2 particles, the addition of 30 nm SiO2 particles can effectively suppress the space charge, and the composite material has the lowest residual space charge after depolarization. The addition of 100 nm SiO2 particles can cause the accumulation of many homopolar charges near the anode.

Effects of DC bias on evolutions of repetitively pulsed streamer discharge in humid air

Modulation efficiency and mechanisms of repetitively pulsed streamer discharge in humid air are ambiguous with dramatic variations in free electron availability, residual ion mobility, enhanced heat release, etc, caused by water molecules intentionally supplemented or existing in the surrounding environment. The inception and propagation patterns of repetitively pulsed streamer discharge modulated by superimposed DC bias are experimentally investigated in the needle-plane electrode configuration. The inception voltage decreases due to negative ion drift under positive DC bias. The secondary streamer with a bright glowing cloud prolongs towards the plane electrode and the diameter decreases under positive DC bias. The primary streamer tends to propagate along the off-axis direction under negative DC bias. The number of applied pulses before breakdown decreases with the increase in positive DC bias and illustrates an insignificant dependence on the negative DC bias. The effect of air humidity is more pronounced than the DC bias. The streamer inception, propagation, and morphological transition are explained by residual space charge distributions and drift velocity.

ResDiff: Combining CNN and Diffusion Model for Image Super-resolution

Adapting the Diffusion Probabilistic Model (DPM) for direct image super-resolution is wasteful, given that a simple Convolutional Neural Network (CNN) can recover the main low-frequency content. Therefore, we present ResDiff, a novel Diffusion Probabilistic Model based on Residual structure for Single Image Super-Resolution (SISR). ResDiff utilizes a combination of a CNN, which restores primary low-frequency components, and a DPM, which predicts the residual between the ground-truth image and the CNN predicted image. In contrast to the common diffusion-based methods that directly use LR space to guide the noise towards HR space, ResDiff utilizes the CNN’s initial prediction to direct the noise towards the residual space between HR space and CNN-predicted space, which not only accelerates the generation process but also acquires superior sample quality. Additionally, a frequency-domain-based loss function for CNN is introduced to facilitate its restoration, and a frequency-domain guided diffusion is designed for DPM on behalf of predicting high-frequency details. The extensive experiments on multiple benchmark datasets demonstrate that ResDiff outperforms previous diffusion based methods in terms of shorter model convergence time, superior generation quality, and more diverse samples.

Unraveling motion in proteins by combining NMR relaxometry and molecular dynamics simulations: A case study on ubiquitin.

Nuclear magnetic resonance (NMR) relaxation experiments shine light onto the dynamics of molecular systems in the picosecond to millisecond timescales. As these methods cannot provide an atomically resolved view of the motion of atoms, functional groups, or domains giving rise to such signals, relaxation techniques have been combined with molecular dynamics (MD) simulations to obtain mechanistic descriptions and gain insights into the functional role of side chain or domain motion. In this work, we present a comparison of five computational methods that permit the joint analysis of MD simulations and NMR relaxation experiments. We discuss their relative strengths and areas of applicability and demonstrate how they may be utilized to interpret the dynamics in MD simulations with the small protein ubiquitin as a test system. We focus on the aliphatic side chains given the rigidity of the backbone of this protein. We find encouraging agreement between experiment, Markov state models built in the χ1/χ2 rotamer space of isoleucine residues, explicit rotamer jump models, and a decomposition of the motion using ROMANCE. These methods allow us to ascribe the dynamics to specific rotamer jumps. Simulations with eight different combinations of force field and water model highlight how the different metrics may be employed to pinpoint force field deficiencies. Furthermore, the presented comparison offers a perspective on the utility of NMR relaxation to serve as validation data for the prediction of kinetics by state-of-the-art biomolecular force fields.

Hybrid (Digital/Water Seal) Chest Drainage System - An Innovative Device for Patients with Anticipated Air Leaks.

To date, several chest drainage systems are available, such as digital drainage systems (DDS) and traditional systems with continuous suction or water seal. However, none of these systems were yet shown to be favorable in the treatment of complex situations such as persistent air leaks or residual spaces. We present in-vitro as well as clinical data of a novel hybrid drainage system consisting of an optimized digital drainage system (ODDS) and an underwater seal drainage system (UWSD). For in-vitro analysis, a DDS and an ODDS were connected to a pleural cavity simulator. Different air leaks were produced and data on intrapleural pressure and air flow were analyzed. Furthermore, we tested the hybrid drainage system in 10 patients with potential air leaks after pulmonary surgery. In in-vitro analysis, we could show, that with advanced pump technology, pressure fluctuations caused by the drainage system when trying to maintain a set pressure level in patients with airleaks were much smaller when using an ODDS and could even be eliminated when using a fluid collection canister with sufficient buffer capacity. This minimized air leak boosts caused by the drainage system. Optimizing the auto-pressure regulation algorithms also led to a reduced airflow through the fistula and promoted rest. Switching to a passive UWSD also reduced the amount of airflow. Clinical application of the hybrid drainage system yielded promising results. The novel hybrid drainage system shows promising results in the treatment of patients with complex clinical situations such as persistent air leaks.

Enforcing Fairness in the Traffic Policer Among Heterogeneous Congestion Control Algorithms

Traffic policing is widely used by ISPs to limit their customers’ traffic rates. It has long been believed that a well-tuned traffic policer offers a satisfactory performance for TCP. However, we find this belief breaks with the emergence of new congestion control (CC) algorithms: flows using new CC algorithms can easily occupy the majority of bandwidth, starving traditional TCP flows. We confirm this problem with experiments and reveal its root cause as follows. Without a buffer in traffic policers, congestion only causes packet losses, while new CC algorithms are loss-resilient. When being policed, they will not reduce the sending rate until an unacceptable loss ratio for TCP is reached, resulting in low throughput for competing TCP flows. Simply adding a buffer to the traffic policer improves fairness but incurs high latency. To this end, we propose FairPolicer, which can achieve fair bandwidth allocation without sacrificing latency. FairPolicer regards a token as a basic unit of bandwidth and fairly allocates tokens to active flows in a round-robin manner. To avoid bandwidth waste when flows come and go, FairPolicer puts all available tokens in a global bucket and maintains the amount of residual bucket space rather than the number of available tokens. To scale to massive concurrent flows, FairPolicer uses a Count-Min Sketch structure to maintain per-flow data with a small memory footprint. Testbed experiments show that FairPolicer can allocate bandwidth in a max-min fair manner and achieve much lower latency than other kinds of rate limiters.

Are the Efficacy and Safety of Chest Tubes in Uniportal Video-Assisted Thoracic Surgery Related to the Level of Intercostal Space Insertion or to the Drain Type? A Prospective Multicenter Study.

The aim of this study is to evaluate if the efficacy and safety of chest tube placement are influenced by the level of intercostal space insertion (uniportal VATS vs. biportal VATS) or by the type of drain employed (standard vs. smart coaxial drain). Data on patients who underwent either uniportal or biportal VATS upper lobectomies with lymphadenectomy were prospectively collected in three European centers. The uniportal VATS group with a 28 Fr standard chest tube (U-VATS standard) was compared with the uniportal VATS group with a 28 Fr smart drain (U-VATS smart), and U-VATS smart was also compared with biportal VATS with a 28 Fr smart drain inserted in the VIII intercostal space (Bi-VATS smart). When comparing the U-VATS standard group with the U-VATS smart, a higher fluid output was recorded in the U-VATS smart (p: 0.004) in the III post-operative day (p.o.) and overall (p: 0.027), with a lower 90-day re-admission in the U-VATS smart (p: 0.04). The Bi-VATS smart group compared to U-VATS smart showed a higher fluid output in the I p.o. (p < 0.001), with no difference in total fluid amount or hospitalization. The Bi-VATS smart recorded a lower incidence (p < 0.001) of residual pleural space or effusion (p: 0.004) at chest X-rays prior to drain removal but a higher level of pain and chronic intercostal neuralgia (p: 0.03). Chest tube insertion through the same incision space in uniportal VATS seems to be safe and effective. Smart drains can improve the fluid output in uniportal VATS, as if the drainage were inserted in a lower space (i.e., biportal VATS), but with less discomfort.

A novel monitoring method based on multi-model information extraction and fusion

Abstract Modern industrial processes are increasingly complex, where multiple characteristics usually coexist in process data. Therefore, traditional monitoring methods based on a single model may ignore other data characteristics and obtain poor monitoring performance. Aiming at this problem, a novel monitoring method based on multi-model information extraction and fusion is proposed in this paper. Firstly, several methods are used to extract different characteristics from process data. For example, principal component analysis, independent component analysis and slow features analysis can be used to extract Gaussian, non-Gaussian and dynamic characteristics respectively. Secondly, features extracted from multiple models are combined into new potential features. Then, Lasso regression models between potential features and process variables are established. In this way, not only are multiple characteristics in process data considered during the reconstruction, but key potential features (KPFs) can be selected for each process variable. The KPFs for each process variable can form a monitoring subspace to enhance the sensitivity for fault detection. Furthermore, cluster analysis is used to reduce the redundancy of monitoring subspaces based on the similarity of each subspace. Process monitoring can be achieved by fusing the monitoring results of finally determined multiple subspaces and residual space. Case studies on three simulation processes and a real industrial process demonstrate the effectiveness and better performance.

Venous Thrombosis Assay in a Mouse Model of Cancer.

This methodology paper highlights the surgical nuances of a rodent model of venous thrombosis, specifically in the context of cancer-associated thrombosis (CAT). Deep venous thrombosis is a common complication in cancer survivors and can be potentially fatal. The current murine venous thrombosis models typically involve a complete or partial mechanical occlusion of the inferior vena cava (IVC) using a suture. This procedure induces a total or partial stasis of blood and endothelial damage, triggering thrombogenesis. The current models have limitations such as higher variability in clot weights, significant mortality rate, and prolonged learning curve. This report introduces surgical refinements using vascular clips to address some of these limitations. Using a syngeneic colon cancer xenograft mouse model, we employed customized vascular clips to ligate the infrarenal vena cava. These clips allow residual lip space similar to a 5-0 polypropylene suture after IVC ligations. Mice with the suture method served as controls. The vascular clip method resulted in a consistent reproducible partial vascular occlusion and greater clot weights with less variability than the suture method. The larger clot weights, greater clot mass, and clot to the IVC luminal surface area were expected due to the higher pressure profile of the vascular clips compared to a 6-0 polypropylene suture. The approach was validated by gray scale ultrasonography, which revealed consistently greater clot mass in the infrarenal vena cava with vascular clips compared to the suture method. These observations were further substantiated with the immunofluorescence staining. This study offers an improved method to generate a venous thrombosis model in mice, which can be employed to deepen the mechanistic understanding of CAT and in translational research such as drug discovery.

Batch process monitoring based on sequential phase division multiway sparse weighted neighborhood preserving embedding

Batch processes are often characterized by multiphase and different batch durations, which vary from phase to phase presenting multiple local neighborhood features. In this paper, a sequential phase division-multiway sparse weighted neighborhood preserving embedding method is proposed for monitoring batch processes more sensitively. First, batches with uneven durations are synchronized, and the phases are automatically determined in chronological order. Secondly, the nearest neighbors are computed at each phase and the optimal sparse representation (SR) is obtained based on the nearest neighbors. This improves the robustness of the algorithm to noise and outliers, and solves the problem of computational difficulties associated with global SR based. Thirdly, the distance values of the neighbor elements are considered to fully extract the neighbor structure when the optimal SR is calculated. Finally, after dimension reduction, T 2 and squared prediction error statistics are established in feature space and residual space respectively for fault detection. The effectiveness of the method is verified by a multiphase numerical simulation example and the penicillin fermentation process.

Study of Modified Offset Trajectory for Bonnet Polishing Based on Lifting Bonnet Method.

The inability to converge at the edge of a workpiece during polishing affects the edge profile accuracy and surface quality of the workpiece. In this study, a bias trajectory generation method based on the lifting bonnet method that can maintain the morphology of polished edges is presented. Firstly, by establishing the polishing parameters and the decreasing rule in line with the principles of the lifting bonnet method, we obtained the residual height spacing, the radius of the polishing area, the centre offset position, and the pressing depth for each offset trajectory. Subsequently, the modified bias trajectory algorithm correction coefficients were obtained by fitting the edge trajectories using cubic Bessel curves, which were multiplied with the bias amount to obtain the final modified bias trajectory. Finally, an experiment was designed to compare the edge effect of the modified bias trajectory with the traditional grating trajectory. The experimental findings indicate that the reduction in edge collapse following the implementation of the modified offset trajectory was 1.30 μm. In contrast, the edge collapse after polishing with the traditional grating trajectory amounted to 98.67 μm. Moreover, the edge collapse ensuing traditional polishing trajectory was 75.9 times more pronounced than that observed after using the modified offset trajectory. It is shown that the modified bias trajectory method can not only maintain the original edge morphology of the workpiece but can also promote the convergence of the edge effect to a certain extent.

Alley greening: a tool for enhancing community resilience?

ABSTRACT In many cities across the world alleys are transitioning from residual spaces to hybrid places providing the foundation for new functions, uses, and identities to take root and coincide through a process of “alley greening”. Such manifestations are transforming the relationship between people (local residents) and place (alleyway – local area), most notably during the COVID-19 pandemic when a new urgency for the provision, or repurposing, of safe, social spaces emerged. Yet, the potential of alley greening to affect people-place relationships and engender community resilience has been relatively unexplored. Adopting a mixed-methods approach, including questionnaires, interviews, and case study analyses, this paper critically investigates the experience and perspectives of green alleys from various place-based actors in Belfast, Northern Ireland. The findings reveal that, even in the absence of institutional and policy support, green alley projects have the potential to stimulate positive people-place relationships in various ways and enhance wider community resilience to shocks and stresses. However, barriers prevail, curtailing the reach and purpose of such projects both in Belfast and elsewhere. The paper considers how governance arrangements might best overcome such hurdles and strengthen pro-environmental and pro-social behaviours that are fundamental to community resilience. Key policy highlights Despite their integral form and function in the city, alleyways, nor their potential, are rarely recognised in the policy. The COVID-19 pandemic exposed a policy-implementation gap in the provision of locally accessible greenspace. Policy inertia exacerbated this gap preventing the fulfilment of changing community needs. Alley greening emerged as a tactical urban response. A lack of place-based approaches within policy has polarised institutions from communities. People-place relationships, essential to resilience-building and green alley longevity, are subsequently inadequately engaged with and fostered. An opportunity exists for alley greening to be a place-based policy instrument to stimulate pro-social and pro-environmental behaviours for building community resilience.

Novel voxelwise residual analysis of [11C]raclopride PET data improves detection of low-amplitude dopamine release

Existing methods for voxelwise transient dopamine (DA) release detection rely on explicit kinetic modeling of the [11C]raclopride PET time activity curve, which at the voxel level is typically confounded by noise, leading to poor performance for detection of low-amplitude DA release-induced signals. Here we present a novel data-driven, task-informed method—referred to as Residual Space Detection (RSD)—that transforms PET time activity curves to a residual space where DA release-induced perturbations can be isolated and processed. Using simulations, we demonstrate that this method significantly increases detection performance compared to existing kinetic model-based methods for low-magnitude DA release (simulated +100% peak increase in basal DA concentration). In addition, results from nine healthy controls injected with a single bolus of [11C]raclopride performing a finger tapping motor task are shown as proof-of-concept. The ability to detect relatively low magnitudes of dopamine release in the human brain using a single bolus injection, while achieving higher statistical power than previous methods, may additionally enable more complex analyses of neurotransmitter systems. Moreover, RSD is readily generalizable to multiple tasks performed during a single PET scan, further extending the capabilities of task-based single-bolus protocols.

Enhancing the accuracy of physics-informed neural network surrogates in flash calculations using sparse grid guidance*

Flash calculations pose a significant performance bottleneck in compositional-flow simulations. While sparse grids have helped mitigate this bottleneck by shifting it to the offline stage, the accuracy of the surrogate model based on physics-informed neural networks (PINN) is still inferior to that of the sparse grid surrogate in many cases. To address this issue, we propose the sparse-grid guided PINN training algorithm. This approach involves rearranging the collocation points using sparse grids at each epoch to capture changes in the residual space. By doing so, the PINN surrogate achieves the required accuracy using the fewest collocation points possible, thereby avoiding potential performance bottlenecks. Moreover, the training time complexity of the sparse-grid guided PINN training is significantly lower compared to the normal training while maintaining the same level of accuracy. Consequently, the sparse-grid guided PINN training method enhances the accuracy of the PINN surrogate with minimal computational overhead. During the experiments, a flash calculation of methane-propane mixture is conducted using a PINN surrogate, guided by the principles of sparse grids. The collective experimental observations underscore the clear advantages of employing sparse-grid guided PINN training, showcasing superior outcomes in terms of convergence, stability, and accuracy.

Discontinuous Urban Growth: A Discussion from the Perspective of Sustainability

Objective: The study analyzes the phenomenon of discontinuity in the growth of the urban fabric directly related to planning, urbanization and the sustainability of municipal management. The analyzes presented are directed to the case study of Vitória da Conquista, in the State of Bahia, Brazil. Theoretical framework: The study brings theoretical reflections on the issue of discontinuity in the city's urban fabric, correlating it to spatial segregation; public policy; optimization of installed infrastructure; the urban voids generated by real estate speculation, the actions of space transforming agents. Method: The Geographic Information System was used as a methodological instrument, with geoprocessing resources, using orbital data in raster format (satellite images) obtained from the National Institute for Space Research (INPE), and vector cartographic bases available at IBGE. Results and conclusion: The growth of the city of Vitória da Conquista over the years resulted in a morphology with the creation of urban voids, with speculative purposes, where residual spaces were created with discontinuous growth, in a logic that restructures spaces in the urban area. Implications of the research: Access to urban rights or the right to the city of an indivisible nature, guaranteed by the 1988 constitution to all inhabitants of the city, of present and future generations. The equity of living, enjoying and participating in the production of fair, inclusive and sustainable cities. Originality/value: This research has academic value, as it supports public policies and urban planning, with the originality of the discussions presented.

Incipient Fault Detection in a Hydraulic System Using Canonical Variable Analysis Combined with Adaptive Kernel Density Estimation.

Incipient fault detection in a hydraulic system is a challenge in the condition monitoring community. Existing research mainly monitors abnormal working conditions in hydraulic systems by separately detecting the key working parameter, which often causes a high miss warning rate for incipient faults due to the oversight of parameter dependence. A principal component analysis provides an effective method for incipient fault detection by taking the correlation of multiple parameters into consideration, but this technique assumes the systems are Gaussian-distributed, making it invalid for a dynamic non-Gaussian system. In this paper, we combine a canonical variable analysis (CVA) and adaptive kernel density estimation (AKDE) for the early fault detection of nonlinear dynamic hydraulic systems. The collected hydraulic system data set was used to construct the typical variable space, and the state space and residual space are divided to represent the characteristics of different correlations between the two variables, which are quantitatively described using Hotelling's T2 and Q. In order to investigate the proper upper control limits, AKDE was utilised to estimate the underlying probability density functions of T2 and Q by taking the nonlinearity of the hydraulic system variables into consideration. The advantages of the proposed approach for incipient fault detection are illustrated via a marine power plant lubrication system.

Lung Volume Reduction Surgery (Clinical Cases)

Emphysema is a chronic lung disease in which the walls of the alveoli in the lungs weaken and collapse; leaving abnormally large residual spaces filled with air even when the patient exhales. The most common symptoms of emphysema are shortness of breath (dyspnea); cough; fatigue; and weight loss. Emphysema often coexists with chronic obstructive pulmonary disease. The treatment of emphysema requires a multidisciplinary approach; including education; exercise; tobacco cessation; oral and inhaled medications; oxygen therapy; and lung transplantation. Lung volume reduction surgery (LVRS) may be an option for patients who experience shortness of breath and whose pulmonary function tests show severe obstruction and enlarged lungs. The surgery aims to remove the least functional part of the lung to improve airflow; diaphragm; and chest wall mechanics; as well as alveolar gas exchange in the remaining lung. Objective — to familiarize doctors with the clinic’s experience in reducing lung volume in patients with bullous emphysema. Materials and methods. Our clinic performed the following surgical interventions to reduce lung volume: VATS resection of large (giant) lung bullae — 14 (77.7 %) cases; VATS lo­­bec­tomy — 2 (11.1 %); lobectomy through thoracotomy — 1 (5.6 %); VATS sublobar resection — 1 (5.6 %). Results and discussion. There were no fatalities. The following postoperative complications were recorded: prolonged under-expansion of the operated lung in 5 (27.7 %) cases; empyema of the residual pleural cavity with bronchial fistula in 1 (5.6 %). The overall incidence of postoperative complications was 33.3 %. Two patients with prolonged underdistension of the operated lung required reoperation (VATS revision of the pleural cavity and redilation). The patient who developed pleural empyema with a bronchial fistula underwent bronchial blockage with a satisfactory result. In all cases of LVRS; a positive clinical effect was recorded in the first 3 months after surgery. During the follow-up period of up to 2 years; only 2 (11.1 %) patients showed no clinical effect and signs of progression of chronic obstructive pulmonary disease and respiratory failure were observed. Conclusions. Lung volume reduction surgery is a method of treating bullous lung disease that allows achieving overall treatment effectiveness in the follow-up period of up to 3 months in 100 % of cases; and in the follow-up period of up to 2 years — in 89.9 %. The high rate of postoperative complications in LVRS requires a physician to carefully select patients for surgery and monitor their condition daily in the postoperative period.