scholarly journals Secondary Caries in situ Models: A Systematic Review

2018 ◽  
Vol 52 (6) ◽  
pp. 454-462 ◽  
Author(s):  
Audrey C.C. Hollanders ◽  
Nicolien K. Kuper ◽  
Tamires T. Maske ◽  
Marie-Charlotte D.N.J.M. Huysmans
Keyword(s):  
Systematic Review ◽  
Relevant Literature ◽  
Model Parameters ◽  
Secondary Caries ◽  
Bias Risk ◽  
Microhardness Data ◽  
Intraoral Splint ◽  
Jaw Model ◽  
Research Volunteers

In situ caries research serves as a bridge between clinical research and laboratory studies. In this kind of research, volunteers wear a removable intraoral splint or prosthesis containing research samples. Many different in situ models exist to investigate secondary caries. This systematic review compared currently existing secondary caries models and their lesion progression per day values. Materials and Methods: Three databases (Medline, Embase, and Cochrane) were searched for relevant literature. Bias risk was assessed and model parameters and caries-related outcomes were extracted by 2 independent researchers. Where possible, caries-related outcomes were normalized by estimating lesion progression per day by dividing lesion depth extracted from microradiographic or microhardness data by the number of days the study lasted. Results: The literature search identified 335 articles. After eliminating duplicates and selection, 31 articles were included. The models differed greatly on factors such as sample location, presence of fluoride in the model, and analysis methods. Three main groups could be identified by sample placement; 68% of models placed samples palatally in the upper jaw, and the lower jaw model could be divided into the buccal (26%) and approximal (6%) areas. Average lesion progression in enamel next to composite was 4.3 ± 2.8 µm (range1.1–8.8 µm/day). Discussion: Studies conducted with palatal models showed caries progression rates 2–5 times higher than the estimated clinical progression rates. Lesion progression per day could be a useful tool for future comparison of models and establishing a standardized model.

scholarly journals Mitochondrial transplantation therapy for ischemia reperfusion injury: a systematic review of animal and human studies

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Kei Hayashida ◽  
Ryosuke Takegawa ◽  
Muhammad Shoaib ◽  
Tomoaki Aoki ◽  
Rishabh C. Choudhary ◽  
...  
Keyword(s):  
Systematic Review ◽  
Reperfusion Injury ◽  
Animal Studies ◽  
Ischemia Reperfusion Injury ◽  
Myocardial Dysfunction ◽  
Ischemia Reperfusion ◽  
Meta Analysis ◽  
Relevant Literature ◽  
Human Studies ◽  
Cochrane Library

Abstract Background Mitochondria are essential organelles that provide energy for cellular functions, participate in cellular signaling and growth, and facilitate cell death. Based on their multifactorial roles, mitochondria are also critical in the progression of critical illnesses. Transplantation of mitochondria has been reported as a potential promising approach to treat critical illnesses, particularly ischemia reperfusion injury (IRI). However, a systematic review of the relevant literature has not been conducted to date. Here, we systematically reviewed the animal and human studies relevant to IRI to summarize the evidence for mitochondrial transplantation. Methods We searched MEDLINE, the Cochrane library, and Embase and performed a systematic review of mitochondrial transplantation for IRI in both preclinical and clinical studies. We developed a search strategy using a combination of keywords and Medical Subject Heading/Emtree terms. Studies including cell-mediated transfer of mitochondria as a transfer method were excluded. Data were extracted to a tailored template, and data synthesis was descriptive because the data were not suitable for meta-analysis. Results Overall, we identified 20 animal studies and two human studies. Among animal studies, 14 (70%) studies focused on either brain or heart IRI. Both autograft and allograft mitochondrial transplantation were used in 17 (85%) animal studies. The designs of the animal studies were heterogeneous in terms of the route of administration, timing of transplantation, and dosage used. Twelve (60%) studies were performed in a blinded manner. All animal studies reported that mitochondrial transplantation markedly mitigated IRI in the target tissues, but there was variation in biological biomarkers and pathological changes. The human studies were conducted with a single-arm, unblinded design, in which autologous mitochondrial transplantation was applied to pediatric patients who required extracorporeal membrane oxygenation (ECMO) for IRI–associated myocardial dysfunction after cardiac surgery. Conclusion The evidence gathered from our systematic review supports the potential beneficial effects of mitochondrial transplantation after IRI, but its clinical translation remains limited. Further investigations are thus required to explore the mechanisms of action and patient outcomes in critical settings after mitochondrial transplantation. Systematic review registration The study was registered at UMIN under the registration number UMIN000043347.

scholarly journals A Systematic Review on the Application of Machine Learning in Exploiting Mineralogical Data in Mining and Mineral Industry

Minerals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 816
Author(s):  
Mohammad Jooshaki ◽  
Alona Nad ◽  
Simon Michaux
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Raw Materials ◽  
Relevant Literature ◽  
Geological Structure ◽  
Subject Area ◽  
Ore Deposits ◽  
Machine Learning Algorithms ◽  
Global Demand ◽  
Ore Grade

Machine learning is a subcategory of artificial intelligence, which aims to make computers capable of solving complex problems without being explicitly programmed. Availability of large datasets, development of effective algorithms, and access to the powerful computers have resulted in the unprecedented success of machine learning in recent years. This powerful tool has been employed in a plethora of science and engineering domains including mining and minerals industry. Considering the ever-increasing global demand for raw materials, complexities of the geological structure of ore deposits, and decreasing ore grade, high-quality and extensive mineralogical information is required. Comprehensive analyses of such invaluable information call for advanced and powerful techniques including machine learning. This paper presents a systematic review of the efforts that have been dedicated to the development of machine learning-based solutions for better utilizing mineralogical data in mining and mineral studies. To that end, we investigate the main reasons behind the superiority of machine learning in the relevant literature, machine learning algorithms that have been deployed, input data, concerned outputs, as well as the general trends in the subject area.

scholarly journals In-Situ Measurement of Power Loss for Crystalline Silicon Modules Undergoing Thermal Cycling and Mechanical Loading Stress Testing

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 72
Author(s):  
Sergiu Spataru ◽  
Peter Hacke ◽  
Dezso Sera
Keyword(s):  
Thermal Cycling ◽  
Power Loss ◽  
Stress Testing ◽  
Series Resistance ◽  
Short Circuit ◽  
In Situ Measurement ◽  
Mechanical Degradation ◽  
Model Parameters ◽  
The Impact

An in-situ method is proposed for monitoring and estimating the power degradation of mc-Si photovoltaic (PV) modules undergoing thermo-mechanical degradation tests that primarily manifest through cell cracking, such as mechanical load tests, thermal cycling and humidity freeze tests. The method is based on in-situ measurement of the module’s dark current-voltage (I-V) characteristic curve during the stress test, as well as initial and final module flash testing on a Sun simulator. The method uses superposition of the dark I-V curve with final flash test module short-circuit current to account for shunt and junction recombination losses, as well as series resistance estimation from the in-situ measured dark I-Vs and final flash test measurements. The method is developed based on mc-Si standard modules undergoing several stages of thermo-mechanical stress testing and degradation, for which we investigate the impact of the degradation on the modules light I-V curve parameters, and equivalent solar cell model parameters. Experimental validation of the method on the modules tested shows good agreement between the in-situ estimated power degradation and the flash test measured power loss of the modules, of up to 4.31 % error (RMSE), as the modules experience primarily junction defect recombination and increased series resistance losses. However, the application of the method will be limited for modules experiencing extensive photo-current degradation or delamination, which are not well reflected in the dark I-V characteristic of the PV module.

scholarly journals Industrial Plume Properties Retrieved by Optimal Estimation Using Combined Hyperspectral and Sentinel-2 Data

2021 ◽  
Vol 13 (10) ◽  
pp. 1865
Author(s):  
Gabriel Calassou ◽  
Pierre-Yves Foucher ◽  
Jean-François Léon
Keyword(s):  
Matched Filter ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Model Parameters ◽  
Surface Reflectance ◽  
Sequential Method ◽  
Modal Radius ◽  
Sentinel 2

Stack emissions from the industrial sector are a subject of concern for air quality. However, the characterization of the stack emission plume properties from in situ observations remains a challenging task. This paper focuses on the characterization of the aerosol properties of a steel plant stack plume through the use of hyperspectral (HS) airborne remote sensing imagery. We propose a new method, based on the combination of HS airborne acquisition and surface reflectance imagery derived from the Sentinel-2 Multi-Spectral Instrument (MSI). The proposed method detects the plume footprint and estimates the surface reflectance under the plume, the aerosol optical thickness (AOT), and the modal radius of the plume. Hyperspectral surface reflectances are estimated using the coupled non-negative matrix factorization (CNMF) method combining HS and MSI data. The CNMF reduces the error associated with estimating the surface reflectance below the plume, particularly for heterogeneous classes. The AOT and modal radius are retrieved using an optimal estimation method (OEM), based on the forward model and allowing for uncertainties in the observations and in the model parameters. The a priori state vector is provided by a sequential method using the root mean square error (RMSE) metric, which outperforms the previously used cluster tuned matched filter (CTMF). The OEM degrees of freedom are then analysed, in order to refine the mask plume and to enhance the quality of the retrieval. The retrieved mean radii of aerosol particles in the plume is 0.125 μμm, with an uncertainty of 0.05 μμm. These results are close to the ultra-fine mode (modal radius around 0.1 μμm) observed from in situ measurements within metallurgical plant plumes from previous studies. The retrieved AOT values vary between 0.07 (near the source point) and 0.01, with uncertainties of 0.005 for the darkest surfaces and above 0.010 for the brightest surfaces.

scholarly journals Non-operative orthobiologic use for rotator cuff disorders and glenohumeral osteoarthritis: A systematic review

2020 ◽  
pp. 1-16
Author(s):  
David M. Robinson ◽  
Christine Eng ◽  
Steven Makovitch ◽  
Joshua B. Rothenberg ◽  
Stephanie DeLuca ◽  
...  
Keyword(s):  
Systematic Review ◽  
Rotator Cuff ◽  
Cohort Studies ◽  
Randomized Clinical Trials ◽  
Platelet Rich Plasma ◽  
Inclusion Criteria ◽  
Serious Adverse Events ◽  
Bias Risk ◽  
Glenohumeral Osteoarthritis ◽  
Functional Outcome Measures

BACKGROUND: Shoulder pain from rotator cuff pathology and glenohumeral osteoarthritis is a common entity encountered in musculoskeletal practices. Orthobiologic agents are being increasingly used as a treatment option and understanding their safety and efficacy is necessary. OBJECTIVE: To systematically evaluate the available evidence for orthobiologic use in rotator cuff and glenohumeral pathology. METHODS: A systematic review was undertaken following PRISMA guidelines. Randomized clinical trials (RCTs) and prospective cohort studies evaluating non-operative treatment with prolotherapy, platelet-rich plasma (PRP), or medicinal signaling cells (MSCs) for rotator cuff pathology and glenohumeral osteoarthritis were included. Bias risk assessments used were the Cochrane tool and Newcastle-Ottawa score. RESULTS: The search yielded 852 potential articles, of which 20 met the inclusion criteria with a breakdown of 5 prolotherapy, 13 PRP, and 2 MSC. Sixteen studies were RCTs and 4 were cohort studies. Six studies were deemed “low risk of bias or good quality”. Efficacy results were mixed, and no serious adverse events were reported from orthobiologic treatment. CONCLUSIONS: Orthobiologics offer a relatively safe management option with inconclusive evidence for or against its use for rotator cuff pathology. No studies on glenohumeral osteoarthritis met the inclusion criteria. Adoption of standardized preparation reporting and consistent use of functional outcome measures is imperative for future studies to consider.

Coupled Thermo-Hydro-Geochemical Models of Engineered Barrier Systems: The Febex Project

2000 ◽  
Vol 663 ◽  
Author(s):  
J. Samper ◽  
R. Juncosa ◽  
V. Navarro ◽  
J. Delgado ◽  
L. Montenegro ◽  
...  
Keyword(s):  
Large Scale ◽  
Reference Model ◽  
Numerical Models ◽  
Full Scale ◽  
Small Scale ◽  
Model Parameters ◽  
In Situ Test ◽  
Wide Range ◽  
Engineered Barrier

ABSTRACTFEBEX (Full-scale Engineered Barrier EXperiment) is a demonstration and research project dealing with the bentonite engineered barrier designed for sealing and containment of waste in a high level radioactive waste repository (HLWR). It includes two main experiments: an situ full-scale test performed at Grimsel (GTS) and a mock-up test operating since February 1997 at CIEMAT facilities in Madrid (Spain) [1,2,3]. One of the objectives of FEBEX is the development and testing of conceptual and numerical models for the thermal, hydrodynamic, and geochemical (THG) processes expected to take place in engineered clay barriers. A significant improvement in coupled THG modeling of the clay barrier has been achieved both in terms of a better understanding of THG processes and more sophisticated THG computer codes. The ability of these models to reproduce the observed THG patterns in a wide range of THG conditions enhances the confidence in their prediction capabilities. Numerical THG models of heating and hydration experiments performed on small-scale lab cells provide excellent results for temperatures, water inflow and final water content in the cells [3]. Calculated concentrations at the end of the experiments reproduce most of the patterns of measured data. In general, the fit of concentrations of dissolved species is better than that of exchanged cations. These models were later used to simulate the evolution of the large-scale experiments (in situ and mock-up). Some thermo-hydrodynamic hypotheses and bentonite parameters were slightly revised during TH calibration of the mock-up test. The results of the reference model reproduce simultaneously the observed water inflows and bentonite temperatures and relative humidities. Although the model is highly sensitive to one-at-a-time variations in model parameters, the possibility of parameter combinations leading to similar fits cannot be precluded. The TH model of the “in situ” test is based on the same bentonite TH parameters and assumptions as for the “mock-up” test. Granite parameters were slightly modified during the calibration process in order to reproduce the observed thermal and hydrodynamic evolution. The reference model captures properly relative humidities and temperatures in the bentonite [3]. It also reproduces the observed spatial distribution of water pressures and temperatures in the granite. Once calibrated the TH aspects of the model, predictions of the THG evolution of both tests were performed. Data from the dismantling of the in situ test, which is planned for the summer of 2001, will provide a unique opportunity to test and validate current THG models of the EBS.

scholarly journals Systematic review of the factors affecting cat and dog owner compliance with pharmaceutical treatment recommendations

2018 ◽  
Vol 184 (5) ◽  
pp. 154-154 ◽  
Author(s):  
Kathryn Jennifer Wareham ◽  
Marnie Louise Brennan ◽  
Rachel S Dean
Keyword(s):  
Systematic Review ◽  
Data Extraction ◽  
Relevant Literature ◽  
Evidence Base ◽  
Treatment Recommendations ◽  
Social Risk ◽  
Dosing Regimen ◽  
Pharmaceutical Treatment ◽  
Level Of Evidence ◽  
Factors Affecting

The aim of this systematic review is to describe and assess the quality of the existing evidence base concerning factors that influence the compliance of cat and dog owners to pharmaceutical and specifically polypharmacy treatment recommendations. PubMed, CAB Abstracts and Google were searched to identify relevant literature and search results were filtered according to predetermined inclusion and exclusion criteria. Standardised data extraction and critical appraisal were carried out on each included study, and a Centre for Evidence-Based Medicine level of evidence grading was applied. Of the 8589 studies, eight studies were included in the review. Majority (five of eight) of the included studies were examining compliance with short-term antimicrobial therapies and none examined polypharmacy. Multiple definitions of compliance, methods of measurement and different factors potentially affecting compliance were used. Factors reported to have affected compliance in at least one study were dosing regimen, discussion of dosing regimen in light of owners’ circumstances, consultation time, disease, month of consultation/treatment, physical risk, social risk and method of administration. The evidence available regarding factors affecting client compliance with pharmaceutical treatment recommendations in cats and dogs is scarce and of poor quality.

“Sintering” Models and In-Situ Experiments: Data Assimilation for Microstructure Prediction in SLS Additive Manufacturing of Nylon Components

MRS Advances ◽  
2020 ◽  
Vol 5 (29-30) ◽  
pp. 1593-1601
Author(s):  
W. Steven Rosenthal ◽  
Francesca C. Grogan ◽  
Yulan Li ◽  
Erin I. Barker ◽  
Josef F. Christ ◽  
...  
Keyword(s):  
Adaptive Sampling ◽  
Selective Laser Sintering ◽  
Phase Field Model ◽  
Estimation Algorithm ◽  
Model Parameters ◽  
Multiple Data ◽  
In Situ Experiments ◽  
Parameter Estimation Algorithm ◽  
Microstructure Prediction

ABSTRACTSelective laser sintering methods are workhorses for additively manufacturing polymer-based components. The ease of rapid prototyping also means it is easy to produce illicit components. It is necessary to have a data-calibrated in-situ physical model of the build process in order to predict expected and defective microstructure characteristics that inform component provenance. Toward this end, sintering models are calibrated and characteristics such as component defects are explored. This is accomplished by assimilating multiple data streams, imaging analysis, and computational model predictions in an adaptive Bayesian parameter estimation algorithm. From these data sources, along with a phase-field model, bulk porosity distributions are inferred. Model parameters are constrained to physically-relevant search directions by sensitivity analysis, and then matched to predictions using adaptive sampling. Using this feedback loop, data-constrained estimates of sintering model parameters along with uncertainty bounds are obtained.

scholarly journals The lifecycle of heuristics as managerial proverbs

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Radu Atanasiu
Keyword(s):  
Systematic Review ◽  
Process Model ◽  
Empirical Studies ◽  
Relevant Literature ◽  
Theory Approach ◽  
Process Step ◽  
Content Type ◽  
Management Framework ◽  
Conceptual Paper ◽  
Practical Implications

PurposeThis paper proposes a theory-based process model for the generation, articulation, sharing and application of managerial heuristics, from their origin as unspoken insight, to proverbialization, to formal or informal sharing, and to their adoption as optional guidelines or policy.Design/methodology/approachA conceptual paper is built using systematic and non-systematic review of literature. This paper employs a three-step approach to propose a process model for the emergence of managerial heuristics. Step one uses a systematic review of empirical studies on heuristics in order to map extant research on four key criteria and to obtain, by flicking through this sample in a moving-pictures style, the static stages of the process; step two adapts a knowledge management framework to yield the dynamic aspect; step three assembles these findings into a graphical process model and uses insights from literature to enrich its description and to synthesize four propositions.FindingsThe paper provides insights into how heuristics originate from experienced managers confronted with negative situations and are firstly expressed as an inequality with a threshold. Further articulation is done by proverbialization, refining and adapting. Sharing is done either in an informal way, through socialization, or in a formal way, through regular meetings. Soft adoption as guidelines is based on expert authority, while hard adoption as policy is based on hierarchical authority or on collective authority.Research limitations/implicationsThe findings are theory-based, and the model must be empirically refined.Practical implicationsPractical advice for managers on how to develop and share their portfolio of heuristics makes this paper valuable for practitioners.Originality/valueThis study addresses the less-researched aspect of heuristics creation, transforms static insights from literature into a dynamic process model, and, in a blended-theory approach, considers insights from a distant, but relevant literature – paremiology (the science of proverbs).

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