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Project management standards, like PMBOK, have had a considerable role in developing this field of knowledge and promoting it as a professional expertise in project-oriented industries, such as the construction industry. The latest version of PMBOK, seventh edition—2021, has been released with substantial changes, and the conventional process-based system has been converted to a performance-based approach. This study aimed to investigate the recent edition of PMBOK, to explore its application and adaptation regarding the specific characteristics of the construction industry. For this purpose, utilizing a hybrid methodology of text mining and survey method, at first, the content of the text was analyzed by software in combination with experts’ opinions. In a parallel survey, the distinctive attributes of the construction industry were investigated, and in the next step, the way that this sector can benefit from the emerging framework was examined. The results show the construction industry has special peculiarities in the form of four different project types with specific phases in typical lifecycle and reveal the potential applicability of performance domains in the construction projects and the compatibility of project management principles. This study is one of the first attempts to review the novel presented standard of PMBOK seventh edition and contributes to the present knowledge by analyzing the construction industry in relation to this issue.

Over the past years, bridge inspection practices and condition assessments were predicated upon long-established manual and paper-based data collection methods which were generally unsafe, time-consuming, imprecise, and labor-intensive, influenced by the experience of the trained inspectors involved. In recent years, the ability to turn an actual civil infrastructure asset into a detailed and precise digital model using state-of-the-art emerging technologies such as laser scanners has become in demand among structural engineers and managers, especially bridge asset managers. Although advanced remote technologies such as Terrestrial Laser Scanning (TLS) are recently established to overcome these challenges, the research on this subject is still lacking a comprehensive methodology for a reliable TLS-based bridge inspection and a well-detailed Bridge Information Model (BrIM) development. In this regard, the application of BrIM as a shared platform including a geometrical 3D CAD model connected to non-geometrical data can benefit asset managers, and significantly improve bridge management systems. Therefore, this research aims not only to provide a practical methodology for TLS-derived BrIM but also to serve a novel sliced-based approach for bridge geometric Computer-Aided Design (CAD) model extraction. This methodology was further verified and demonstrated via a case study on a cable-stayed bridge called Werrington Bridge, located in New South Wales (NSW), Australia. In this case, the process of extracting a precise 3D CAD model from TLS data using the sliced-based method and a workflow to connect non-geometrical information and develop a BrIM are elaborated. The findings of this research confirm the reliability of using TLS and the sliced-based method, as approaches with millimeter-level geometric accuracy, for bridge inspection subjected to precise 3D model extraction, as well as bridge asset management and BrIM development.

IRE1/XBP-1 activation has a major role in Triple negative breast cancer (TNBC). Here, the authors show that inhibition of IRE1’s RNase activity attenuates autocrine and paracrine signaling of pro-tumorigenic cytokines and synergizes with paclitaxel to confer potent anti-tumor effects in TNBC.

Abstract Proteostasis imbalance is emerging as a major hallmark of cancer, driving tumor aggressiveness. Evidence suggests that the endoplasmic reticulum (ER), a major site for protein folding and quality control, plays a critical role in cancer development. This concept is valid in glioblastoma multiform (GBM), the most lethal primary brain cancer with no effective treatment. We previously demonstrated that the ER stress sensor IRE1α (referred to as IRE1) contributes to GBM progression, through XBP1 mRNA splicing and regulated IRE1‐dependent decay (RIDD) of RNA. Here, we first demonstrated IRE1 signaling significance to human GBM and defined specific IRE1‐dependent gene expression signatures that were confronted to human GBM transcriptomes. This approach allowed us to demonstrate the antagonistic roles of XBP1 mRNA splicing and RIDD on tumor outcomes, mainly through selective remodeling of the tumor stroma. This study provides the first demonstration of a dual role of IRE1 downstream signaling in cancer and opens a new therapeutic window to abrogate tumor progression.

Bridge infrastructures are always subjected to degradation because of aging, their environment, and excess loading. Now it has become a worldwide concern that a large proportion of bridge infrastructures require significant maintenance. This compels the engineering community to develop a robust method for condition assessment of the bridge structures. Here, the simultaneous identification of moving loads and structural damage based on the explicit form of the Newmark-β method is proposed. Although there is an extensive attempt to identify moving loads with known structural parameters, or vice versa, their simultaneous identification considering the road roughness has not been studied enough. Furthermore, most of the existing time domain methods are developed for structures under non-moving loads and are commonly formulated by state-space method, thus suffering from the errors of discretization and sampling ratio. This research is believed to be among the few studies on condition assessment of bridge structures under moving vehicles considering factors such as sensor placement, sampling frequency, damage type, measurement noise, vehicle speed, and road surface roughness with numerical and experimental verifications. Results indicate that the method is able to detect damage with at least three sensors, and is not sensitive to sensors location, vehicle speed and road roughness level. Current limitations of the study as well as prospective research developments are discussed in the conclusion.

The current paper presents the results of an experimental study on the application of calcium carbonate precipitation bacteria as a new approach to repairing damaged concrete when exposed to high temperatures. To do so, cylindrical and cubic concrete specimens were initially exposed to heat in a furnace for 1 h, after reaching two different temperatures of 600 and 800 °C. A heat rate of 5.5 °C per minute was used to achieve the target temperatures. Then, two types of bacteria, namely Sporosarcina pasteurii and Bacillus sphaericus, with cell concentration of 107 cells/mL, were utilized externally, to repair the thermal cracks, enhancing the mechanical properties and durability of the damaged concrete. The efficiency of the bacterial remediation technique was then evaluated through compressive strength, ultrasonic pulse velocity (UPV), and electrical conductivity tests on the control specimens (unexposed to heat), and those exposed to high temperature with or without bacterial healing. The experimental results demonstrate that the compressive strength of the test specimens exposed to temperatures of 600 and 800 °C decreased by about 31–44% compared with the control ones. However, compared to those damaged at 600 and 800 °C, the compressive strength of specimens repaired by the S. pasteurii and the B. sphaericus showed increases of 31–93%. This increase is associated with the precipitation of calcium carbonate in the deep and superficial cracks and pores of the damaged specimens. Furthermore, the ultrasonic pulse velocity of the specimens subjected to bacterial remediation had a significant increase of about 1.65–3.47 times compared with the damaged ones. In addition, the electrical conductivity of repaired specimens decreased by 22–36% compared with the damaged specimens.

This study evaluated the axial capacity of cold-formed racking upright sections strengthened with an innovative reinforcement method by finite element modelling and artificial intelligence techniques. At the first stage, several specimens with different lengths, thicknesses and reinforcement spacings were modelled in ABAQUS. The finite element method (FEM) was employed to increase the available datasets and evaluate the proposed reinforcement method in different geometrical types of sections. The most influential factors on the axial strength were investigated using a feature-selection (FS) method within a multi-layer perceptron (MLP) algorithm. The MLP algorithm was developed by particle swarm optimization (PSO) and FEM results as input. In terms of accuracy evaluation, some of the rolling criteria including results showed that geometrical parameters have almost the same contribution in compression capacity and displacement of the specimens. According to the performance evaluation indexes, the best model was detected and specified in the paper and optimised by tuning other parameters of the algorithm. As a result, the normalised ultimate load and displacement were predicted successfully.

This investigated the influence of societal structure and organizational structure on Information and Communication Technology users' beliefs about the environment in the Ugandan context. Environmental sustainability is currently a call for urgent attention around the World. Our study was guided by two specific objectives; to establish the effect of societal structure on ICT users' beliefs about the environment in Uganda and to establish the effect of organizational structure on ICT users' beliefs about the environment in Uganda. The study adopted the belief action outcome (BAO) model of Nigel P. Melville. A cross-sectional quantitative research design, using a post-positivist paradigm with a quantitative analytical survey research methodology was used. We used a self-administered survey, with a questionnaire as the tool for data collection. A sample of 384 respondents was selected using simple random sampling and we obtained back 362 usable questionnaires. Correlations, regressions and structural equation modeling were analyzed using SPSS and AMOS. The results show that societal structure and organizational structure have a positive significant effect on ICT users' beliefs about the environment. We make a contribution by adopting the BAO model in a developing country context, in which literature about beliefs about the environment is limited. We recommend that there should be more deliberate organizational top management support and finances to run environmental conservation initiatives that will ultimately impact individual's beliefs about the environment. Additionally, societal actors who influence other people should be empowered to shape ICT users' beliefs about the environment. [ABSTRACT FROM AUTHOR]

In the current modern era of information and technology, emerging remote advancements have been widely established for detailed virtual inspections and assessments of infrastructure assets, especially bridges. These technologies are capable of creating an accurate digital representation of the existing assets, commonly known as the digital twins. Digital twins are suitable alternatives to in-person and on-site based assessments that can provide safer, cheaper, more reliable, and less distributive bridge inspections. In the case of bridge monitoring, Unmanned Aerial Vehicle (UAV) photogrammetry and Terrestrial Laser Scanning (TLS) are among the most common advanced technologies that hold the potential to provide qualitative digital models; however, the research is still lacking a reliable methodology to evaluate the generated point clouds in terms of quality and geometric accuracy for a bridge size case study. Therefore, this paper aims to provide a comprehensive methodology along with a thorough bridge case study to evaluate two digital point clouds developed from an existing Australian heritage bridge via both UAV-based photogrammetry and TLS. In this regard, a range of proposed approaches were employed to compare point clouds in terms of points’ distribution, level of outlier noise, data completeness, surface deviation, and geometric accuracy. The comparative results of this case study not only proved the capability and applicability of the proposed methodology and approaches in evaluating these two voluminous point clouds, but they also exhibited a higher level of point density and more acceptable agreements with as-is measurements in TLS-based point clouds subjected to the implementation of a precise data capture and a 3D reconstruction model.

Two semi-quantitative, Luminex-based, single-antigen bead (SAB) assays are available to detect anti-HLA antibodies and evaluate their reactivity with complement binding. Sera from 97 patients with positive panel reactive antibody tests (>5%) were analyzed with two SAB tests, Immucor (IC) and One-Lambda (OL), for anti-HLA antibody detection and the evaluation of their complement-binding capacity. IC detected 1608/8148 (mean fluorescent intensity (MFI) 4195 (1995–11,272)) and 1136/7275 (MFI 6706 (2647–13,184)) positive anti-HLA class I and II specificities, respectively. Accordingly, OL detected 1942/8148 (MFI 6185 (2855–12,099)) and 1247/7275 (MFI 9498 (3630–17,702)) positive anti-HLA class I and II specificities, respectively. For the IC assay, 428/1608 (MFI 13,900 (9540–17,999)) and 409/1136 (MFI 11,832 (7128–16,531)) positive class I and II specificities bound C3d, respectively. Similarly, OL detected 485/1942 (MFI 15,452 (9369–23,095)) and 298/1247 (MFI18,852 (14,415–24,707)) C1q-binding class I and II specificities. OL was more sensitive in detecting class I and II anti-HLA antibodies than IC was, although there was no significant difference in the number of class II specificities per case. MFI was higher for complement vs. non-complement-binding anti-HLA antibodies in both assays. Both methods were equal in detecting complement-binding anti-HLA class I antibodies, whereas the C3d assay was more sensitive in detecting complement-binding anti-HLA class II antibodies. [ABSTRACT FROM AUTHOR]

Urticaria is an autoimmune disease and many patients are suffering from it. This research aims to investigate the development and characterization of an Ebastine-loaded transfersomal nanogel for the enhancement of bioavailability in the treatment of urticaria. The flexible transfersomes, consisting of the drug Ebastine, soya lecithin, and edge activator Tween 80, were prepared using the thin-film hydration method. The transfersomal nanogel was formulated by using the dispersion method and a suitable concentration of the gelling agent Carbopol 934. The transfersomes and their gel were evaluated for various parameters. The Ebastine-loaded transfersomes showed the highest entrapment efficiency, up to 79.92%. The polydispersity index (PDI) of the transfersomes was determined to be 0.103, and the zeta potential was determined to be −18.9 mV, indicating that the formulation was stable. The drug content of the transfersome gel was found to be 83.67%. The transfersomal gel formed using 1% Carbopol 934 showed the best results, showing in vitro release for up to 8 h and following a zero-order kinetic model. As per the microbial studies conducted, the Ebastine transfersomal gel has a good anti-microbial effect against S. aureus. These vesicular transfersomes are more flexible than other vesicular systems, making them excellent for skin penetration. In the future, this will be the best possible approach for the delivery of drugs via the transdermal route. [ABSTRACT FROM AUTHOR]

This study evaluates an innovative reinforcement method for cold-formed steel (CFS) upright sections through finite element assessment as well as prediction of the normalized ultimate load and deflection of the profiles by artificial intelligence (AI) and machine learning (ML) techniques. Following the previous experimental studies, several CFS upright profiles with different lengths, thicknesses and reinforcement spacings are modeled and analyzed under flexural loading. The finite element method (FEM) is employed to evaluate the proposed reinforcement method in different upright sections and to provide a valid database for the analytical study. To detect the most influential factor on flexural strength, the “feature selection” method is performed on the FEM results. Then, by using the feature selection method, a hybrid neural network (a combination of multi-layer perceptron algorithm and particle swarm optimization method) is developed for the prediction of normalized ultimate load. The correlation coefficient (R), root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), mean absolute error (MAE) and Wilmot’s index of agreement (WI) are used as the measure of precision. The results show that the geometrical parameters have almost the same contribution in the flexural capacity and deflection of the specimens. According to the performance evaluation indexes, the best model is detected and optimized by tuning other algorithm parameters. The results indicate that the hybrid neural network can successfully predict the normalized ultimate load and deflection.

Autophagy, apoptosis, and the unfolded protein response (UPR) are fundamental biological processes essential for manifold cellular functions in health and disease. Idiopathic pulmonary fibrosis (IPF) is a progressive and lethal pulmonary disorder associated with aging that has limited therapies, reflecting our incomplete understanding. We conducted an observational study linking molecular markers of cell stress response pathways (UPR: BiP, XBP1; apoptosis: cleaved caspase-3; autophagy: LC3β) in lung tissues from IPF patients and correlated the expression of these protein markers to each subject’s lung function measures. We hypothesized that changes in lung tissue expression of apoptosis, autophagy, and UPR markers correlate with lung function deficits in IPF. The cell stress markers BiP, XBP1, LC3β puncta, and cleaved caspase-3 were found to be elevated in IPF lungs compared to non-IPF lungs, and, further, BiP and cleaved caspase-3 co-localized in IPF lungs. Considering lung function independently, we observed that increased XBP1, BiP, and cleaved caspase-3 were each associated with reduced lung function (FEV1, FVC, TLC, RV). However, increased lung tissue expression of LC3β puncta was significantly associated with increased diffusion capacity (DLCO), an indicator of alveolar–capillary membrane function. Similarly, the co-localization of UPR (XBP1, BiP) and autophagy (LC3β puncta) markers was positively correlated with increased lung function (FEV1, FVC, TLC, DLCO). However, the presence of LC3β puncta can indicate either autophagy flux inhibition or activation. While the nature of our observational cross-sectional study design does not allow conclusions regarding causal links between increased expression of these cell stress markers, lung fibrosis, and lung function decline, it does provide some insights that are hypothesis-generating and suggests that within the milieu of active UPR, changes in autophagy flux may play an important role in determining lung function. Further research is necessary to investigate the mechanisms linking UPR and autophagy in IPF and how an imbalance in these cell stress pathways can lead to progressive fibrosis and loss of lung function. We conclude by presenting five testable hypotheses that build on the research presented here. Such an understanding could eventually lead to the development of much-needed therapies for IPF.

Bridge infrastructures are continuously subject to degradation due to aging and excess loading, placing users at risk. It has now become a major concern worldwide, where the majority of bridge infrastructures are approaching their design life. This compels the engineering community to develop robust methods for continuous monitoring of bridge infrastructures including the loads passing over them. Here, a moving load identification method based on the explicit form of Newmark-β method and Generalized Tikhonov Regularization is proposed. Most of the existing studies are based on the state space method, suffering from the errors of a large discretization and a low sampling frequency. The accuracy of the proposed method is investigated numerically and experimentally. The numerical study includes a single simply supported bridge and a three-span continuous bridge, and the experimental study includes a single-span simply supported bridge installed by sensors. The effects of factors such as the number of sensors, sensor locations, road roughness, measurement noise, sampling frequency and vehicle speed are investigated. Results indicate that the method is not sensitive to sensor placement and sampling frequencies. Furthermore, it is able to identify moving loads without disruptions when passing through supports of a continuous bridge, where most the existing methods fail.

Abstract Background Spontaneous spinal epidural hematoma during pregnancy is a quite rare event requiring emergent decompressive surgery in the majority of cases to prevent permanent neurological damage. Therefore, there is little data in the literature regarding anesthetic management of cervical localization during pregnancy. The potential for difficult airway management with the patient under general anesthesia is one of the major concerns that needs to be addressed to prevent further cord compression. Anesthetic management should also include measures to maintain the mean arterial pressure to improve spinal cord perfusion. Furthermore, spine surgery in pregnant patients needs special consideration in terms of positioning and in the postoperative period. Case presentation We present a case of a 35-year-old white woman at 21 weeks of gestation with a spontaneous cervical epidural hematoma. Fiberoptic bronchoscope-guided nasal intubation was a safe option to ensure a higher rate of successful endotracheal intubation while minimizing the risk of aggravating the injury. Her care posed other multiples challenges that required a multidisciplinary team approach. Conclusions The case of our patient serves as a reminder of this rare condition and its implications regarding anesthesia.