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Abstract The purpose of this study was to understand the dynamic behaviors of lignin-amended loess. Dynamic properties tests of lignin-amended loess with different contents and strength tests at optimum content were carried out by using a hollow cylinder torsion shear apparatus. Firstly, the effect of lignin fiber content (0%, 0.5%, 1%, 2%, 3% and 4%) on the dynamic properties of improved loess was investigated, and the results showed that the optimal lignin content for improved loess was 1%, at which time compared with pure loess the highest increase of the dynamic shear stress in the skeleton curve of the soil was 73.8%, the increase of dynamic shear modulus was 26%, and the decrease of dynamic damping ratio was 60%; Then, the effects of moisture content (12%, 17%, 21%) and consolidated confining pressure (100 kPa, 200 kPa, 300 kPa) on the dynamic strength of 1% modified loess were studied, and the subsidence characteristics of the improved loess were also focused on, the results indicated that the dynamic strength of the improved loess decreased with the increase of moisture content and increase with the confining pressure, and the seismic characteristics increase with the increase of dynamic shear stress and the number of cycles.

Abstract Freeze–thaw cycles are frequently overlooked as a pivotal factor contributing to leakage and structural failures in clayey soil-impermeable barriers used in landfills or tailings repositories in regions subject to seasonal freezing. This investigation explores the recovery and residual strength properties of Jilin ball clay undergoing six freeze–thaw cycles, and assesses the pore structure characteristics through a series of nuclear magnetic resonance (NMR) tests. The results indicate that normal stress has a greater impact on peak recovery strength than dry density and rest periods. Cohesion increases earlier and more significantly during rest periods compared to internal friction angle. Although the pore diameter remains consistent within the micropores during the freeze–thaw cycles, the soil’s structural integrity undergoes notable changes. The concluding analysis provides valuable insights for the construction and management of impermeable barriers in landfills or tailings repositories within seasonally frozen areas.

Summary: Early detection of left ventricular remodeling (LVR) is crucial. While cardiac magnetic resonance (CMR) provides valuable information, it has limitations. Coronary angiography-derived fractional flow reserve (caFFR) and index of microcirculatory resistance (caIMR) offer viable alternatives. 157 patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention were prospectively included. 23.6% of patients showed LVR. Machine learning algorithms constructed three LVR prediction models: Model 1 incorporated clinical and procedural parameters, Model 2 added CMR parameters, and Model 3 included echocardiographic and functional parameters (caFFR and caIMR) with Model 1. The random forest algorithm showed robust performance, achieving AUC of 0.77, 0.84, and 0.85 for Models 1, 2, and 3. SHAP analysis identified top features in Model 2 (infarct size, microvascular obstruction, admission hemoglobin) and Model 3 (current smoking, caFFR, admission hemoglobin). Findings indicate coronary physiology and echocardiographic parameters effectively predict LVR in patients with STEMI, suggesting their potential to replace CMR.

BackgroundMost existing studies have only investigated the direct effects of the built environment on respiratory diseases. However, there is mounting evidence that the built environment of cities has an indirect influence on public health via influencing air pollution. Exploring the “urban built environment-air pollution-respiratory diseases” cascade mechanism is important for creating a healthy respiratory environment, which is the aim of this study.MethodsThe study gathered clinical data from 2015 to 2017 on patients with respiratory diseases from Tongji Hospital in Wuhan. Additionally, daily air pollution levels (sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter (PM2.5, PM10), and ozone (O3)), meteorological data (average temperature and relative humidity), and data on urban built environment were gathered. We used Spearman correlation to investigate the connection between air pollution and meteorological variables; distributed lag non-linear model (DLNM) was used to investigate the short-term relationships between respiratory diseases, air pollutants, and meteorological factors; the impacts of spatial heterogeneity in the built environment on air pollution were examined using the multiscale geographically weighted regression model (MGWR).ResultsDuring the study period, the mean level of respiratory diseases (average age 54) was 15.97 persons per day, of which 9.519 for males (average age 57) and 6.451 for females (average age 48); the 24 h mean levels of PM10, PM2.5, NO2, SO2 and O3 were 78.056 μg/m3, 71.962 μg/m3, 54.468 μg/m3, 12.898 μg/m3, and 46.904 μg/m3, respectively; highest association was investigated between PM10 and SO2 (r = 0.762, p

Background: Obstructive sleep apnea (OSA) is highly common in patients with coronary artery disease (CAD) and it is a strong predictor of subsequent cardiovascular events. However, whether treatment with continuous positive airway pressure (CPAP) can decrease this risk remains controversial. Methods: PubMed, EMBASE, the Cochrane Library, and ClinicalTrials.gov were systematically searched to identify randomized clinical trials reporting cardiovascular events from database inception to February 12, 2022. Results : Four trials with 3043 participants were included. The median follow-up duration ranged from 3 to 4.75 years. Compared with usual care alone, CPAP was not associated with decreased MACCE risk (RR 0.96, 95% CI 0.77–1.21, P = 0.75), and the results were consistent regardless of CPAP adherence (≥4 hours/night vs.

Abstract The study of histopathological phenotypes is vital for cancer research and medicine as it links molecular mechanisms to disease prognosis. It typically involves integration of heterogenous histopathological features in whole-slide images (WSI) to objectively characterize a histopathological phenotype. However, the large-scale implementation of phenotype characterization has been hindered by the fragmentation of histopathological features, resulting from the lack of a standardized format and a controlled vocabulary for structured and unambiguous representation of semantics in WSIs. To fill this gap, we propose the Histopathology Markup Language (HistoML), a representation language along with a controlled vocabulary (Histopathology Ontology) based on Semantic Web technologies. Multiscale features within a WSI, from single-cell features to mesoscopic features, could be represented using HistoML which is a crucial step towards the goal of making WSIs findable, accessible, interoperable and reusable (FAIR). We pilot HistoML in representing WSIs of kidney cancer as well as thyroid carcinoma and exemplify the uses of HistoML representations in semantic queries to demonstrate the potential of HistoML-powered applications for phenotype characterization.

Abstract Background To study the impact of de-escalation antiplatelet therapy retaining P2Y12 inhibition on major bleeding and ischemic outcomes after percutaneous coronary intervention (PCI) among East Asians and non-East Asians was unclear. Methods We systematically searched PubMed, Embase, and the Cochrane Library for randomized controlled trials through September 2020. Eight trials were included, which studied de-escalation of DAPT (D-DAPT, switching to P2Y12 inhibitor monotherapy, or switching to clopidogrel or dose reduction of the P2Y12 inhibitor after 1 to 3 months) versus 12 months standard DAPT (S-DAPT). The primary outcomes data was conducted using random effects models. Results Among the 8 included trials consisting of 37,775 patients, 62.6% presented with acute coronary syndrome. The median follow-up duration ranged from 12 to 24 months. Compared with S-DAPT, D-DAPT was associated with a lower risk of major bleeding (RR = 0.67, 95% CI 0.48–0.93, p = 0.02); however, this was only observed among East-Asians (RR = 0.61, 95% CI 0.37–0.99, p = 0.048). Among non-East Asians, the rate of major bleeding was similar between the two groups (RR = 0.73, 95% CI 0.46–1.14, p = 0.17, p for interaction = 0.59). There were no significant differences in the major adverse cardiovascular events (MACE) between D-DAPT and S-DAPT treatment among both East Asians (RR = 0.84, 95% CI 0.66–1.08, p = 0.18) and non-East Asians (RR = 0.89, 95% CI 0.79–1.00, p = 0.059, p for interaction = 0.71). Conclusions The De-escalation strategy that retains P2Y12 inhibition after a PCI was associated with reduced risk of bleeding events, which was only demonstrated in East Asians patients, and not in non-East Asian patients.

Introduction. Assessment of axillary lymph nodes in breast carcinoma is an important part of staging to guide appropriate clinical management. Lymph node inclusions of different types, including nevoid, squamous, and glandular, are rare but have been reported in multiple different anatomic locations including the axilla. These can result in diagnostic challenges and pose risks of misdiagnoses. Rarely, malignancies may arise intrinsic to otherwise incidental benign nodal inclusions. Case Presentation. We report a case of ductal carcinoma diagnosed within a squamous epithelial inclusion cyst within an axillary lymph node in a patient with pure ductal carcinoma in situ (DCIS) of the ipsilateral right breast. To our knowledge, this is the fifth report in the literature of breast carcinoma confirmed within an axillary inclusion in a patient with pure DCIS. Evaluation of the primary DCIS and lymph node inclusions, by routine and immunohistochemical stains, was performed for assessment. Discussion. The presence of lymph node inclusions can pose a challenge in assessment of benignity and malignancy, on frozen and permanent histologic sections. Pathologists should carefully evaluate lymph node inclusions to ensure that intrinsic malignancies are not missed within rare otherwise benign appearing incidental epithelial rests.

IntroductionImmune cell infiltration into the tumor microenvironment is generally associated with favorable clinical outcomes in solid tumors. However, the dynamic interplay among distinct immune cell subsets within the tumor-immune microenvironment as it relates to clinical responses to immunotherapy remains unresolved. In this study, we applied multiplex immunofluorescence (MxIF) to spatially characterize tumor-immune interactions within the metastatic melanoma lymph node.MethodsPretreatment, whole lymph node biopsies were evaluated from 25 patients with regionally metastatic melanoma who underwent subsequent anti-PD1 therapy. Cyclic MxIF was applied to quantitatively and spatially assess expression of 45 pathologist-validated antibodies on a single tissue section. Pixel-based single cell segmentation and a supervised classifier approach resolved 10 distinct tumor, stromal and immune cell phenotypes and functional expression of PD1.ResultsSingle cell analysis across 416 pathologist-annotated tumor core regions of interest yielded 5.5 million cells for spatial evaluation. Cellular composition of tumor and immune cell subsets did not differ in the tumor core with regards to recurrence outcomes (p>0.05) however spatial patterns significantly differed in regional and paracrine neighborhood evaluations. Specifically, a regional community cluster comprised of primarily tumor and dendritic cells was enriched in patients that did not experience recurrence (p=0.009). By an independent spatial approach, cell-centric neighborhood analyses identified an enrichment for dendritic cells in cytotoxic T cell (CTL) and tumor cell-centric neighborhoods in the no recurrence patient response group (p

BackgroundAs one of the key criteria to differentiate benign vs. malignant tumors in ovarian and other solid cancers, tumor-stroma reaction (TSR) is long observed by pathologists and has been found correlated with patient prognosis. However, paucity of study aims to overcome subjective bias or automate TSR evaluation for enabling association analysis to a large cohort.Materials and methodsServing as positive and negative sets of TSR studies, H&E slides of primary tumors of high-grade serous ovarian carcinoma (HGSOC) (n = 291) and serous borderline ovarian tumor (SBOT) (n = 15) were digitally scanned. Three pathologist-defined quantification criteria were used to characterize the extents of TSR. Scores for each criterion were annotated (0/1/2 as none-low/intermediate/high) in the training set consisting of 18,265 H&E patches. Serial of deep learning (DL) models were trained to identify tumor vs. stroma regions and predict TSR scores. After cross-validation and independent validations, the trained models were generalized to the entire HGSOC cohort and correlated with clinical characteristics. In a subset of cases tumor transcriptomes were available, gene- and pathway-level association studies were conducted with TSR scores.ResultsThe trained models accurately identified the tumor stroma tissue regions and predicted TSR scores. Within tumor stroma interface region, TSR fibrosis scores were strongly associated with patient prognosis. Cancer signaling aberrations associated 14 KEGG pathways were also found positively correlated with TSR-fibrosis score.ConclusionWith the aid of DL, TSR evaluation could be generalized to large cohort to enable prognostic association analysis and facilitate discovering novel gene and pathways associated with disease progress.

Abstract Background DNA polymerase epsilon (POLE) is encoded by the POLE gene, and POLE-driven tumors are characterized by high mutational rates. POLE-driven tumors are relatively common in endometrial and colorectal cancer, and their presence is increasingly recognized in ovarian cancer (OC) of endometrioid type. POLE-driven cases possess an abundance of TCT > TAT and TCG > TTG somatic mutations characterized by mutational signature 10 from the Catalog of Somatic Mutations in Cancer (COSMIC). By quantifying the contribution of COSMIC mutational signature 10 in RNA sequencing (RNA-seq) we set out to identify POLE-driven tumors in a set of unselected Mayo Clinic OC. Methods Mutational profiles were calculated using expressed single-nucleotide variants (eSNV) in the Mayo Clinic OC tumors (n = 195), The Cancer Genome Atlas (TCGA) OC tumors (n = 419), and the Genotype-Tissue Expression (GTEx) normal ovarian tissues (n = 84). Non-negative Matrix Factorization (NMF) of the mutational profiles inferred the contribution per sample of four distinct mutational signatures, one of which corresponds to COSMIC mutational signature 10. Results In the Mayo Clinic OC cohort we identified six tumors with a predicted contribution from COSMIC mutational signature 10 of over five mutations per megabase. These six cases harbored known POLE hotspot mutations (P286R, S297F, V411L, and A456P) and were of endometrioid histotype (P = 5e−04). These six tumors had an early onset (average age of patients at onset, 48.33 years) when compared to non-POLE endometrioid OC cohort (average age at onset, 60.13 years; P = .008). Samples from TCGA and GTEx had a low COSMIC signature 10 contribution (median 0.16 mutations per megabase; maximum 1.78 mutations per megabase) and carried no POLE hotspot mutations. Conclusions From the largest cohort of RNA-seq from endometrioid OC to date (n = 53), we identified six hypermutated samples likely driven by POLE (frequency, 11%). Our result suggests the clinical need to screen for POLE driver mutations in endometrioid OC, which can guide enrollment in immunotherapy clinical trials.

As semiconductor technology scales, modern microprocessors are more vulnerable to transient faults. Software-level fault tolerance schemes are promising because they can improve reliability effectively without extra hardware. Redundant Multi-threading (RMT) uses off-the-shelf cores as redundancy to achieve error resilience. Latest software RMT fault-tolerance models do not effectively cope with transient faults occurring on multiple components during the application execution, resulting in a large number of silent data corruptions (SDC). To address this challenge, we propose FERNANDO, a software-level RMT runtime fault tolerance scheme which provides enhanced error detection and comprehensive error recovery by Triple-Modular Redundancy (TMR). On an ARM Cortex-A57 like simulated microprocessor, we performed probability model transient fault injection experiments in different components of all cores. The results demonstrate that, compared to the state-of-the-art technique, FERNANDO can reduce the SDC rate by about 86.67 percent and optimize the execution time overhead by about 19.64 percent.

Chronic intermittent hypoxia (CIH) is the main feature of obstructive sleep apnea (OSA) and is known to exaggerate cardiac remodeling after myocardial infarction (MI). However, the specific contribution of CIH to overall OSA-induced pathological complications and the transcriptomic mechanisms underlying CIH-exaggerated post-MI remodeling remains unclear. In this study, we used RNA-sequencing to construct the expression profiles of cardiac mRNAs, microRNAs, and long non-coding RNAs (lncRNA) in four groups of C57BL/6J mice (Sham, CIH, MI, MI + CIH) to evaluate how CIH regulates cardiac remodeling after MI. Compared with the other three groups, the MI + CIH group exhibited 345 lncRNAs, 35 microRNAs, and 5,220 differentially expressed mRNAs. Further analysis showed that CIH led to significant changes in Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of the differentially expressed mRNAs. Co-expression network analysis identified two core lncRNAs (Mirt1 and AC125351.1) and two core microRNAs (miR-466i-5p and miR-574-5p) during the development of CIH-exaggerated post-MI remodeling, and they were verified by quantitative real-time PCR (qRT-PCR). LncRNA-mRNA correlation analysis further showed that lncRNA Mirt1 was positively correlated with Apbb1ip and Lcp2. In addition, microRNA-mRNA correlation analysis showed that microRNA miR-466i-5p was positively correlated with Snai2, Cdc27, and Ngfr. Furthermore, combining with lncRNA-mRNA and miRNA-mRNA networks, 44 RNAs were identified in the competitive endogenous RNA (ceRNA) network. Mirt1 acts as a ceRNA to bind to miR-466i-5p to further regulate the expression levels of the target gene, thereby aggravating cardiac remodeling after MI. In conclusion, our study provides a systematic perspective on the potential functions of mRNAs, microRNAs, and lncRNAs in CIH-exaggerated post-MI cardiac remodeling. Our data suggest that lncRNA Mirt1 may be the most critical regulator of MI aggravated by CIH.

Hydrogen energy has become an important way to solve energy crises owing to its non-pollution, high level of efficiency, and wide application. Proton exchange membrane fuel cells (PEMFCs) have received wide attention as an energy conversion device for hydrogen energy. The hydrogen concentration in the PEMFC anode directly determines the output voltage of the stack. The performance of the PEMFC gradually decreases due to the accumulation of nitrogen. However, the continuous circulation of anode gas and the nitrogen accumulation at the anode due to transmembrane diffusion lead to difficulties in estimating the anode gas concentration. The relationship between anode nitrogen concentration and voltage variation characteristics was studied by increasing the anode hydrogen concentration through the method of increasing nitrogen concentration and conducting experiments on a 16-cell stack. In this paper, an estimation method for nitrogen concentration in the anode is proposed to evaluate the nitrogen concentration in the anode on the basis of voltage variation characteristics, and the method was recalibrated and validated using experimental data. Due to the inhomogeneity of the gas distribution within the PEMFC stack, the mean cell voltage can provide a more accurate estimation of the anode nitrogen concentration compared to a single cell voltage. It is shown that the proposed approach can offer a new method to estimate anode nitrogen concentration. Compared with the conventional method, the new method is simpler as it does not require additional equipment or complex algorithms. In this paper, the anode nitrogen concentration was estimated by applying this method with a maximum error of only 0.35%.

Background: Shenfu injection is a traditional Chinese medicine formulation that alleviates ischemia-reperfusion injury through multiple pharmacologic effects. However, no data are available regarding its efficacy in patients with myocardial infarction. We aimed to examine the effects of Shenfu injection on infarct size in patients with ST segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI).Methods: From April 2016 to February 2018, 40 patients with first-time anterior STEMI undergoing primary PCI within 6 h of symptom onset were randomized 1:1 to intravenous Shenfu injection (80 ml Shenfu injection + 70 ml 5% glucose injection) or placebo (150 ml 5% glucose injection) before reperfusion. Treatment started before PCI and maintained for 5 days after PCI. The primary end point was infarct size assessed by CK-MB area under the curve (AUC) over 72 h and cardiac magnetic resonance (CMR) imaging 4 ± 1 days after PCI.Results: Infarct size by area under the curve for CK-MB over 72 h did not differ between the Shenfu injection and placebo groups (5602.5 [3539.4–7526.4] vs. 6403.2 [2234.4–8340.6] ng·h/ml, P = 0.82). Among 32 patients who underwent CMR Imaging, a nominal reduction in infarct size was observed in the Shenfu injection group compared with the placebo group (23.9 [15.2–28.5] % vs. 27 [21.9–31.9] %, P = 0.42). After excluding patients with no or minimal infarct, there was a trend toward reduction in infarct size in the Shenfu injection group (24.1 [20.3–29.3] % vs. 29.1 [24.5–32] %, P = 0.18). Incidence of adverse events was similar between the groups.Conclusions: This pilot study showed that the use of Shenfu injection was safe but did not reduce infarct size by CMR Imaging and CK-MB release kinetics in reperfused patients with STEMI. Larger studies (confining to patients with extensive infarct size) to evaluate the efficacy of Shenfu injection on reperfusion injury are warranted.Clinical Trail Registration:clinicaltrials.gov, identifier: NCT02709798.

We report here a patient with stage IV mucosal melanoma treated with dual immune checkpoint inhibitor (ICI) therapy (Nivolumab/Ipilimumab) who experienced rapid disease progression and metastatic spread within three weeks of first infusion. Surprisingly, this patient also developed fulminant myocarditis within the same time frame. Immunohistochemical staining of the primary tumor and a metastatic omental lesion revealed robust CD8+ PD-1+ T cell infiltration after ICI treatment, as would be expected following immune activation. However, the CD8+ T cell infiltrate was largely negative for both Granzyme B and TIA-1, suggesting these T cells were not capable of effective tumor lysis. We discuss the possibility that heightened pro-inflammatory T cell activity (rather than tumor-directed cytolytic activity) was induced by anti-PD-1 and anti-CTLA-4, which could have provoked both rapid tumor resistance mechanisms and myocarditis. This case highlights the fact that the mere presence of tumor infiltrating lymphocytes (TILs) does not necessarily correlate to ICI response and that additional functional markers are necessary to differentiate between inflammatory and cytolytic CD8+ TILs.

Background. Obstructive sleep apnea (OSA) is closely related to the incidence and progression of coronary artery disease (CAD), and the mechanisms linking OSA and CAD are multifactorial. C1q/TNF-related protein-9 (CTRP9) is a novel adipokine that protects the heart against ischemic injury and ameliorates cardiac remodeling. We aimed to ascertain the clinical relevance of CTRP9 with OSA prevalence in patients with CAD. Methods. From August 2016 to March 2019, consecutive eligible patients with CAD (n=154; angina pectoris, n=88; acute myocardial infarction [AMI], n=66) underwent cardiorespiratory polygraphy. OSA was defined as an apnea-hypopnea index (AHI) ≥15 events·h−1. Plasma CTRP9 concentrations were measured by ELISA method. Results. Moderate/severe OSA was present in 89 patients (57.8%). CTRP9 levels were significantly decreased in the moderate/severe OSA group than in the no/mild OSA group (4.7 [4.1-5.2] ng/mL vs. 4.9 [4.4-6.0] ng/mL, P=0.003). The difference between groups was only observed in patients with AMI (3.0 [2.3-4.9] vs. 4.5 [3.2-7.9], P=0.009). Correlation analysis showed that CTRP9 levels were negatively correlated with AHI (r=−0.238, P=0.003) and oxygen desaturation index (r=−0.234, P=0.004) and positively correlated with left ventricular ejection fraction (r=0.251, P=0.004) in all subjects. Multivariate analysis showed that male gender (OR 3.099, 95% CI 1.029-9.330, P=0.044), BMI (OR 1.148, 95% CI 1.040-1.268, P=0.006), and CTRP9 levels (OR 0.726, 95% CI 0.592-0.890, P=0.002) were independently associated with the prevalence of moderate/severe OSA. Conclusions. Plasma CTRP9 levels were independently related to the prevalence of moderate/severe OSA in patients with CAD, suggesting that CTRP9 might play a role in the pathogenesis of CAD exacerbated by OSA.

Background: Serous borderline ovarian tumor (SBOT) and high-grade serous ovarian cancer (HGSOC) are two distinct subtypes of epithelial ovarian tumors, with markedly different biologic background, behavior, prognosis, and treatment. However, the histologic diagnosis of serous ovarian tumors can be subjectively variable and labor-intensive as multiple tumor slides/blocks need to be thoroughly examined to search for these features. Materials and Methods: We developed a novel informatics system to facilitate objective and scalable diagnosis screening for SBOT and HGSOC. The system was built upon Groovy scripts and QuPath to enable interactive annotation and data exchange. Results: The system was used to successfully detect cellular boundaries and extract an expanded set of cellular features representing cell- and tissue-level characteristics. The performance of cell-level classification for both tumor and stroma cells achieved >90% accuracy. The performance of differentiating HGSOC versus SBOT achieved 91%–95% accuracy for 6485 imaging patches which have sufficient tumor and stroma cells (minimum of ten each) and 97% accuracy for classifying patients when aggregating the results to whole-slide image based on consensus. Conclusions: Cellular features digitally extracted from pathological images can be used for cell classification and SBOT v. HGSOC differentiation. Introducing digital pathology into ovarian cancer research could be beneficial to discover potential clinical implications. A larger cohort is required to further evaluate the system.

In advanced industrial automation, industrial robots have been widely utilized on assembly lines in order to reduce labor dependence. However, many related layout design approaches proposed are prone to generating unsafe layouts: there generally lacks a consideration regarding robots’ heights and assembly range, which will lead to costly collisions in the operation stage. In order to address the problem, we propose a three-dimensional (3D) optimization approach to a safe layout design for an assembly line with robots. We define modeling rules for robots to judge assembly ranges. A quantitative safety indicator is employed as a trigger for 3D collision detection in order to determine the positional relationship and status of the safe assembly collaboration. The optimization goals are established for minimizing the logistical cost and layout area in the model. A combined algorithm of differential evolution and nondominated sequencing genetic II is applied, which effectively enhances the poor diversity and convergence of the mainstream optimization method when solving this model. The benchmark tests and validation proved that our approach yields excellent convergence and distribution performance. The case study verifies that the safe layout model is valid and our approach can generate a safe layout in order to optimize economics and safety.

Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP) is proposed.Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints), the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency.Findings: In the process of the sub-problems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub-problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality.Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop.Originality/value: The research provides an efficient scheduling method for the large-scale job shops, and will be helpful for the discrete manufacturing industry for improving the production efficiency and effectiveness.