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•CO2 was used as an inexpensive feedstock for various fuels and chemicals production.•Explained various utilization approaches and their mechanisms for CO2 mitigation.•Discussed the ...various CO2 conversion processes.•Current status and Scope for further research on CO2 conversion has been discussed.
Carbon dioxide (CO2) is a odourless and colourless gas which plays a noteworthy role in the climate and weather changes. Different natural and anthropogenic activities induces CO2 emission in the environment. Though CO2 causes global warming, it acts as an essential element for photosynthesis process in plants. CO2 can also be used as an inexpensive feedstock for the production of various fuels and chemicals. Many approaches like electrochemical, thermal, biochemical, chemo-enzymatic and photocatalytic methods are available by means of which the harmful CO2 is captured from the environment. Similarly, via different chemical, physical and biological processes, it can be converted into useful products like fuels and chemicals. This review mainly focuses on various utilization approaches and their mechanisms for CO2 mitigation. In addition, CO2 conversion processes like hydrogenation, esterification, methanation, reforming, and reverse water-gas shift (RWGS) reactions, their mechanisms and their current status along with future perspectives were comprehensively discussed.
Technical and non‐technical losses in distribution circuits result in significant economic costs to power utilities. One type of non‐technical loss is energy theft by various means including illegal ...tapping of feeders, bypassing the meter, and billing fraud. These losses are usually hard to detect, and can remain undetected for long periods of time. Machine learning models have been proven effective in detecting these conditions, but rely on the availability of large, good‐quality training data sets. The problem is exacerbated by the imbalanced nature of data related to these conditions—energy theft, though costly, is very rare. The available data sets generally have very few samples of theft with most of the data pertaining to normal operation. Such data sets are generally not suitable to train machine learning models. In this paper, an overview of energy theft detection techniques, the challenges with their data needs, and the limitations of current techniques to bridge such data limitations is presented. A co‐simulation framework is proposed to generate reliable training data for machine learning algorithms for theft detection. An example scenario is presented and a machine learning model is built to detect certain kinds of energy theft.
Background
Drug‐coated balloon (DCB) angioplasty has emerged as a mainstay of therapy for the treatment of peripheral arterial disease (PAD) involving the superficial femoral and popliteal arteries. ...We performed a meta‐analysis including all available randomized controlled trials (RCTs) to date which compare DCB to plain balloon angioplasty (POBA) in femoropopliteal disease (FPD).
Methods
Five databases were analyzed including EMBASE, PubMed, Cochrane, Scopus, and Web‐of‐Science from January 2000 to September 2018 for RCTs comparing DCB to POBA in patients with FPD. Heterogeneity was determined using Cochrane's Q‐statistics. Random effects model was used.
Results
Twenty‐two RCTs, including five trials of in‐stent restenosis (ISR) intervention, with 3,217 patients were included in the analysis. Mean follow‐up was approximately 21.6 ± 14.4 months. Overall, DCB use was associated with a 51% reduction in target vessel revascularization (TLR) when compared to POBA at follow‐up (relative risk RR: 0.49, 95% confidence interval CI: 0.40–0.61, P < 0.0001). Rates of TLR were 45% lower in the DCB group when compared to POBA in patients with ISR (RR: 0.55, 95% CI: 0.37–0.81, P = 0.002). DCB was associated with lower rates of binary stenosis, late lumen loss and higher primary safety endpoints. Major amputation and mortality were not different between DCB and POBA.
Conclusions
Use of DCBs is associated with improved vessel patency and a lower risk of TLR when compared to POBA in patients with FPD, especially in the setting of ISR. There was no difference in mortality between DCB and POBA in our meta‐analysis. Extended follow‐up of the available RCT data will be essential to analyze long‐term device‐related mortality.
In low-energy networks, energy consumption is a significant concern. The adjustment of transmission power can save considerable energy at nodes during communication. The commonly used power control ...schemes maintain the transmission power based on the received signal strength indicator (RSSI) that depends on the interference in the environment. It is necessary to consider interference for retaining the lowest transmission power since low-energy network signals are vulnerable to interference changes. The earlier investigations suggested only linear models for power prediction in low-power networks. Hence, this paper investigates a classification-based transmission power prediction approach with the presence of interference. The approach works for linear and non-linear models based on RSSI, link quality indicator, neighbour node distance, and receiver power to maintain reliable communication with low energy consumption. The experiments were conducted in natural environments with common interference causes such as the human body, concrete walls, trees, and metallic bodies. The performance of the approach is analyzed with different prediction algorithms such as regression and classification. The investigation results demonstrate that it is possible to build a classification-based power prediction for linear and non-linear models by considering different spatial effects with 99% accuracy.
Background
There is conflicting data as to whether diastolic dysfunction (DD) affects the prognosis of patients with aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR).
...Methods
Consecutive patients undergoing TAVR underwent assessment of DD with preoperative echocardiography and NT‐pro BNP. Long‐term survival was ascertained every 6 months by clinic visits or phone. DD was graded according to the new American Society of Echocardiography recommendations. Health status was assessed at baseline and 30 days post‐procedure using the KCCQ‐12 questionnaire. Long‐term survival was displayed using Kaplan–Meier curves according to NT‐pro BNP levels and DD grades.
Results
We included 222 patients, mean age 78 (±8) years, median STS score 4 (interquartile range = 3–7), median follow‐up time 385 days (IQR = 180–640). DD was absent in 25, Grade I in 13, Grade II in 74, Grade III in 24, and indeterminate in 86 patients. Advanced (Grades II–III) DD was associated with higher pre‐procedural NT‐pro BNP levels (p < .001), worse quality of life (p < .001) but similar surgical risk (p = .43). Advanced and indeterminate DD were associated with increased long‐term mortality (25–28% vs. 5%, p = .02) and elevated NT‐pro BNP levels (26.4% vs. 9.8%, p = .05). Improvements in quality of life measures were seen in all DD groups (median change in KCCQ score no or Grade I DD:14 3–21 vs. Grades II–III DD: 15 16–26; p = .37).
Conclusion
Preoperative NT‐pro BNP levels and echocardiographic indices of indeterminate or advanced DD are associated with increased long‐term mortality after TAVR but similar improvements in quality of life.
The objective of this work is to model the residual stresses that can arise during the production of components using fused deposition modeling (FDM). Thermally induced residual stresses occur during ...the manufacturing process due to unfavorable thermal conductivity of the polymers used. For this purpose, the G‐code of a 3D printer is first imported into a column interpreter which can be rearranged according to given requirements. This is done using a Visual Basic macro. This geometry data is further processed using a CATIA macro to create a geometry in CATIA. For simplification a circular profile is used, which is extruded over polymer lines and stacked on top of one another. In concert, the time‐varying assignment of the boundary conditions over which the printing process is simulated is performed. The calculations are made in ANSYS Workbench using ANSYS APDL commands. The element activation‐deactivation method is used for the simulation. The thermal simulation is first demonstrated and validated on a sample block and then transferred to the CAD part. The results are imported from Transient Analysis and used as load steps for the Static Structural Analysis, where stresses, strains, and deformations are calculated. The results are then studied to finally print the geometry.
The representation and management of product lifecycle information is critical to any manufacturing organization. Different modeling languages are used at different lifecycle stages, for example ...STEP’s EXPRESS may be used at a detailed design stage, while UML may be used for initial design stages. It is necessary to consolidate product information created using these different languages to build a coherent knowledge base. In this paper, we present an approach to enable the translation of STEP schema and its instances to Ontology Web Language (OWL). This gives a model–which we call OntoSTEP–that can easily be integrated with any OWL ontologies to create a semantically rich model. As an example, we combine geometry information represented in STEP with non-geometry information, such as function and behavior, represented using the NIST’s Core Product Model (CPM). A plug-in for Protégé is developed to automate the different steps of the translation. As additional benefits, reasoning, inference procedures, and queries can be performed on enriched legacy CAD models. We describe the rules for the translation from EXPRESS to OWL, and illustrate the benefits of OWL translation with an example. We will also describe how these mapping rules can be implemented through meta-model based transformations, which can be used to map other languages to OWL.
► This paper describes a scheme to translate STEP EXPRESS models to OWL. ► A plug-in for the Protégé OWL editor is developed to automate the translation. ► Product models in OWL can be semantically enriched by applying the logical reasoning. ► A more formal translation scheme based on meta-modeling approach is also presented.
Removable partial dentures (RPDs) significantly influence the mechanical stress characteristics of the entire dental arch. Unlike normal teeth, they are not anchored firmly in the jaws and hence are ...prone to denture slippage. The aim of this study is to examine numerically using finite element (FE) method, the role of denture adhesive creams in the stress response of the dental structures, and to understand its impact on the oral health of denture wearers. For this purpose, computer tomography data of the jawbone and RPDs are utilized to develop corresponding 3D models, which are further used for FE simulations. The partial denture system is bonded onto the surface of the oral mucosa with the help of a viscoelastic adhesive layer and is also supported by three abutment teeth. The application of bite forces on the denture generates varying contact mechanical response to the stimulus, across the partial denture, which are compared with the clinical pressure pain threshold (PPT) value for soft tissue, which potentially lowers the risk of pain. The model with the denture adhesive shows better retention and are within the PPT and hence can potentially lower the risks associated with denture slippage.
With the rapid industrialization and urbanization worldwide, air quality levels are deteriorating at an unprecedented rate and posing a substantial threat to humans and the environment. This brings ...the concern to effectively monitor and forecast air quality levels in real-time. Conventional air quality monitoring stations are built based on centralized architectures involving high latency, communication technologies demanding high power, sensors involving high costs and decision making with moderate accuracy. To address the limitations of the existing systems, we propose a smart and distinct Air Quality Monitoring and Forecasting system embracing Fog Computing with IoT and Deep Learning (DL). The system is a three-layered architecture with the Sensing layer first, Fog Computing layer in between, and Cloud Computing layer at the end. Fog Computing is a powerful new generation paradigm that brings storage, computation, and networking at the edge of the IoT network and reduce network latency. A DL based BiLSTM (Bidirectional Long Short-Term Memory) model is deployed in the Fog Computing layer. The proposed system aims at real-time monitoring and accurate air quality forecasting to support decision making and aid timely prevention and control of pollutant emissions by alerting the stakeholders when a dangerous Air Quality Index (AQI) is expected. Experimental results show that the BiLSTM model has a better predictive performance considering the meteorological parameters than the baseline models in terms of MAE and RMSE. A proof of concept realizing the proposed system is elaborated in the paper.
The introduction of a removable partial denture onto the dental arch significantly influences the mechanical stress characteristics of both the jawbone and oral mucosa. The aim of this study was to ...analyze the stress state caused by biting forces upon insertion of partial dentures into the assembly, and to understand the influence of the resulting contact pressure on its retention behavior. For this purpose, a numerical model of a removable partial denture is proposed based on 3D models developed using computer tomography data of the jawbone and the removable partial denture. The denture system rests on the oral mucosa surface and three abutment teeth. The application of bite forces on the denture generated a stick condition on the loaded regions of the denture‐oral mucosa interface, which indicates positive retention of the denture onto the oral mucosa surface. Slip and negative retention were observed in the regions of the contact space that were not directly loaded. The contact pressures observed in the regions of the oral mucosa in contact with the denture were below the clinical pressure pain threshold value for soft tissue, which potentially lowers the risk of pain being experienced by denture users. Further, the variation of the retention behavior and contact pressures across different regions of the denture assembly was observed. Thus, there is a need for adhesives or restraining mechanisms for the denture system in order to avoid bending and deformation of sections of the denture as a consequence of the applied bite force.
The aim of this study was to numerically analyze the stress state caused by biting following insertion of partial dentures into the dental arch, and to understand its influence on denture retention in situ. Numerical results demonstrate the generation of stick condition on the loaded regions of denture‐oral mucosa interface, whereas slip and negative retention were observed in the regions not directly loaded. This variation in contact mechanical condition can potentially cause discomfort due to bending and turning moments generated.
