Facility managers usually conduct reactive maintenance or preventive maintenance strategies in building maintenance management. However, there are some limitations that reactive maintenance cannot ...prevent failure, and preventive maintenance cannot predict the future condition of MEP components and repair in advance to extend the lifetime of facilities. Therefore, this study aims to apply a predictive maintenance strategy with advanced technologies to overcome these limitations. Building information modeling (BIM) and Internet of Things (IoT) have the potential to improve the efficiency of facility maintenance management (FMM). Despite the significant efforts that have been made to apply BIM and IoT to the architecture, engineering, construction, and facility management (AEC/FM) industry, BIM and IoT integration for FMM is still at an initial stage. In order to provide a better maintenance strategy for building facilities, a data-driven predictive maintenance planning framework based on BIM and IoT technologies for FMM was developed, consisting of an information layer and an application layer. Data collection and data integration among the BIM models, FM system, and IoT network are undertaken in the information layer, while the application layer contains four modules to achieve predictive maintenance, namely: (1) condition monitoring and fault alarming module, (2) condition assessment module, (3) condition prediction module, and (4) maintenance planning module. Machine learning algorithms, ANN and SVM, are used to predict the future condition of MEP components. Furthermore, the developed framework was applied in an illustrative example to validate the feasibility of the approach. The results show that the constantly updated data obtained from the information layer together with the machine learning algorithms in the application layer can efficiently predict the future condition of MEP components for maintenance planning.
•A data-driven predictive maintenance approach based on BIM and IoT is developed.•Data integration among BIM, IoT networks and FM systems is achieved.•Sensor data are extracted from IoT networks using BACnet communication protocol.•Data-driven models are developed to predict future condition of MEP components.•The framework helps FM staff to perform maintenance tasks in a scientific way.
Mixed lineage kinase domain-like pseudokinase (MLKL) mediates necroptosis by translocating to the plasma membrane and inducing its rupture. The activation of MLKL occurs in a multimolecular complex ...(the 'necrosome'), which is comprised of MLKL, receptor-interacting serine/threonine kinase (RIPK)-3 (RIPK3) and, in some cases, RIPK1. Within this complex, RIPK3 phosphorylates the activation loop of MLKL, promoting conformational changes and allowing the formation of MLKL oligomers, which migrate to the plasma membrane. Previous studies suggested that RIPK3 could phosphorylate the murine MLKL activation loop at Ser345, Ser347 and Thr349. Moreover, substitution of the Ser345 for an aspartic acid creates a constitutively active MLKL, independent of RIPK3 function. Here we examine the role of each of these residues and found that the phosphorylation of Ser345 is critical for RIPK3-mediated necroptosis, Ser347 has a minor accessory role and Thr349 seems to be irrelevant. We generated a specific monoclonal antibody to detect phospho-Ser345 in murine cells. Using this antibody, a series of MLKL mutants and a novel RIPK3 inhibitor, we demonstrate that the phosphorylation of Ser345 is not required for the interaction between RIPK3 and MLKL in the necrosome, but is essential for MLKL translocation, accumulation in the plasma membrane, and consequent necroptosis.
Abstract
SN 2023emq is a fast-evolving transient initially classified as a rare Type Icn supernova (SN), interacting with a H- and He-free circumstellar medium (CSM) around maximum light. Subsequent ...spectroscopy revealed the unambiguous emergence of narrow He lines, confidently placing SN 2023emq in the more common Type Ibn class. Photometrically, SN 2023emq has several uncommon properties regardless of its class, including its extreme initial decay (faster than >90% of Type Ibn/Icn SNe) and sharp transition in the decline rate from 0.20 to 0.07 mag day
−1
at +20 days. The bolometric light curve can be modeled as CSM interaction with 0.32
M
⊙
of ejecta and 0.12
M
⊙
of CSM, with 0.006
M
⊙
of nickel, as expected of fast, interacting SNe. Furthermore, broadband polarimetry at +8.7 days (
P
= 0.55% ± 0.30%) is consistent with spherical symmetry. A discovery of a transitional Type Icn/Ibn SN would be unprecedented and would give valuable insights into the nature of mass loss suffered by the progenitor just before death, but we favor an interpretation that SN 2023emq is a Type Ibn SN that exhibited flash-ionized features in the earliest spectrum, as the features are not an exact match with other Type Icn SNe to date. However, the feature at 5700 Å, in the region of C
iii
and N
ii
emission, is significantly stronger in SN 2023emq than in the few other flash-ionized Type Ibn SNe, and if it is related to C
iii
, it possibly implies a continuum of properties between the two classes.
In this two‐part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under ...development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100 km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part 1, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode—with prescribed sea surface temperatures (SSTs) and sea‐ice distribution—is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. The model's Cess sensitivity (response in the top‐of‐atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part 2, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.
Key Points
A description is provided of the AM4.0/LM4.0 model that will serve as a base for a new set of GFDL/NOAA climate and Earth system models
The simulation quality in AMIP mode is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations
The model's Cess sensitivity and effective radiative forcing are presented
The CrackNet, an efficient architecture based on the Convolutional Neural Network (CNN), is proposed in this article for automated pavement crack detection on 3D asphalt surfaces with explicit ...objective of pixel‐perfect accuracy. Unlike the commonly used CNN, CrackNet does not have any pooling layers which downsize the outputs of previous layers. CrackNet fundamentally ensures pixel‐perfect accuracy using the newly developed technique of invariant image width and height through all layers. CrackNet consists of five layers and includes more than one million parameters that are trained in the learning process. The input data of the CrackNet are feature maps generated by the feature extractor using the proposed line filters with various orientations, widths, and lengths. The output of CrackNet is the set of predicted class scores for all pixels. The hidden layers of CrackNet are convolutional layers and fully connected layers. CrackNet is trained with 1,800 3D pavement images and is then demonstrated to be successful in detecting cracks under various conditions using another set of 200 3D pavement images. The experiment using the 200 testing 3D images showed that CrackNet can achieve high Precision (90.13%), Recall (87.63%) and F‐measure (88.86%) simultaneously. Compared with recently developed crack detection methods based on traditional machine learning and imaging algorithms, the CrackNet significantly outperforms the traditional approaches in terms of F‐measure. Using parallel computing techniques, CrackNet is programmed to be efficiently used in conjunction with the data collection software.
Highlights • TBI is associated with a greater occurrence of FTD. • TBI increased TDP-43 proteolysis in rats. • TBI induced impaired behaviors that were associated with TDP-43 and its fragments.
Background Consumption of Chinese herbs that contain aristolochic acid (eg, Mu Tong) has been associated with an increased risk of urinary tract cancer. Methods We conducted a population-based ...case–control study in Taiwan to examine the association between prescribed Chinese herbal products that contain aristolochic acid and urinary tract cancer. All patients newly diagnosed with urinary tract cancer (case subjects) from January 1, 2001, to December 31, 2002, and a random sample of the entire insured population from January 1, 1997, to December 31, 2002 (control subjects), were selected from the National Health Insurance reimbursement database. Subjects who were ever prescribed more than 500 pills of nonsteroidal anti-inflammatory drugs and/or acetaminophen were excluded, leaving 4594 case patients and 174 701 control subjects in the final analysis. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated by using multivariable logistic regression models for the association between prescribed Chinese herbs containing aristolochic acid and the occurrence of urinary tract cancer. Models were adjusted for age, sex, residence in a township where black foot disease was endemic (an indicator of chronic arsenic exposure from drinking water a risk factor for urinary tract cancer), and history of chronic urinary tract infection. Statistical tests were two-sided. Results Having been prescribed more than 60 g of Mu Tong and an estimated consumption of more than 150 mg of aristolochic acid were independently associated with an increased risk for urinary tract cancer in multivariable analyses (Mu Tong: at 61–100 g, OR = 1.6, 95% CI = 1.3 to 2.1, and at >200 g, OR = 2.1, 95% CI = 1.3 to 3.4; aristolochic acid: at 151–250 mg, OR = 1.4, 95% CI = 1.1 to 1.8, and at >500 mg, OR = 2.0, 95% CI = 1.4 to 2.9). A statistically significant linear dose–response relationship was observed between the prescribed dose of Mu Tong or the estimated cumulative dose of aristolochic acid and the risk of urinary tract cancer (P < .001 for both). Conclusions Consumption of aristolochic acid–containing Chinese herbal products is associated with an increased risk of cancer of the urinary tract in a dose-dependent manner that is independent of arsenic exposure.
Seed ageing has an important effect on germination and productivity. During natural ageing, seed vigour decreases rapidly but, to date, the molecular mechanisms underlying this decrease have not been ...fully elucidated. Using omics, some of the details regarding seed vigour decline during natural ageing might be elucidated through integrated analysis.
Safflower seed germination and physio‐biochemical changes during natural ageing (stored for 4, 16 and 28 months) were determined. Proteome and lipidome profiling during natural seed ageing was performed, and the differentially expressed proteins and lipid metabolite species analysed. The surface and internal structures of cotyledons were observed. An integrating analysis of the proteome and lipidome was also carried out.
Natural seed ageing significantly decreased safflower seed germination and vigour. 4,184 proteins and 1,193 lipids were quantified, both of which show huge differences among the different naturally aged seeds. The surface of the cotyledons collapsed and cracked, and the oil bodies become looser during natural ageing. The total content of DAG and PA increased, while the content of TAG and PL (PC, PE, PS, PI and PL) significantly decreased during seeds ageing. Two lipase genes (HH‐026818‐RA and HH‐025320) likely participated in this degradation of lipids.
We conclude that the enzymes that participate in glycerolipid metabolism and fatty acid degradation probably lead to the degradation of oil bodies (TAG) and membrane lipids (PC, PE, PS, PI, PG) and, ultimately, destroy the structure, causing a decline in seed vigour during natural seed ageing.
Enzymes probably led to the degradation of oil bodies and membrane lipids, devastated the seed structure, and caused a decline in seed vigour.
Aliment Pharmacol Ther 2011; 34: 994–1004
Summary
Background The diagnosis of gastro‐oesophageal reflux disease (GERD) is based on reflux symptoms. Although metabolic syndrome has been linked to ...erosive oesophagitis (EO), the impact of insulin resistance, the core of the metabolic syndrome, on reflux symptoms remains to be elucidated.
Aim To assess the effects of insulin resistance on GERD, including both endoscopic findings and symptoms.
Methods A total of 743 sonographic noncirrhotic adult subjects, who underwent an upper gastrointestinal endoscopic examination, completed a gastro‐oesophageal reflux questionnaire and had available fasting insulin data were included. Endoscopic findings were classified according to the Los Angeles classification. Homeostatic model assessment‐insulin resistance (HOMA‐IR) index was used to evaluate the status of insulin resistance. Univariate and multivariate approaches were used to evaluate the associations between insulin resistance and GERD.
Results Older age, male gender, smoking and alcohol consumption increased the prevalence of EO, but not GERD symptoms. A large waist circumference, high fasting blood glucose levels and high number of metabolic syndrome components were associated with increased prevalence of both EO and GERD symptoms, while high blood pressure was associated with increased prevalence of EO only. Moreover, higher scores in the gastro‐oesophageal reflux questionnaire were associated with higher HOMA‐IR index, and higher HOMA‐IR index was associated with increased prevalence of EO (adjusted odds ratio 1.14, 95% CI 1.03–1.26, P = 0.012).
Conclusions Our findings demonstrate clear associations between insulin resistance, metabolic syndrome and GERD. Whether reducing insulin resistance may improve GERD symptoms or EO deserves prospective study.
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