Effects of physical properties on one-dimensional downward smoldering of char: Numerical analysis

Smoldering combustion in a packed bed of carbonaceous material is a very complex process, where numerous physical and chemical parameters are involved. This study was conducted to examine the impact of several physical parameters on the behavior of natural downward smoldering. For that purpose, a one-dimensional homogeneous model has been developed. Due to the fact that drying, pyrolysis or oxidative degradation occurs significantly faster than carbon oxidation, only the latter phenomenon was taken into account. The model was evaluated by comparison of numerical simulation results with experimental observations. Sensitivity analysis calculations of different physical properties of the bed material with respect to smoldering time, smoldering front velocity and front temperature suggest that in future experiments special attention should be devoted to accurate determination of bed shrinkage, bulk carbon density, mean void size, oxygen diffusivity in fuel bed.     

The extent of knowledge of Quick Response Manufacturing principles: an exploratory transnational study

The main goal of this research is to identify whether companies that have implemented the Quick Response Manufacturing (QRM) approach have full knowledge of the QRM principles or have merely applied the elements (principles and tools) that have a close relationship with Lean Manufacturing. Based on a review of the literature regarding the QRM principles, an exploratory survey was conducted for over 20 manufacturing companies from Brazil, Europe and the USA that operate in an Engineer or Make to Order environment system and explicitly have conducted QRM journeys. The results of the present study show that (i) the surveyed companies have difficulty knowing and applying some of the exclusive elements of this approach, even if they started implementing QRM several years ago; (ii) the surveyed companies’ knowledge degree over QRM exclusive elements is apparently higher among US-based companies due to better trained employees and better dissemination and awareness of the QRM exclusive elements; and (iii) a mentality based on productivity, low costs and due date delivery was identified as the main barrier for companies to achieve a higher knowledge degree regarding QRM.     

Introducing functional classification theory to land use planning by means of decision tables

This paper contributes to the conceptualisation and analysis of double-sided matching problems, taking the land use planning problem as an example. It does so by introducing functional classification theory at the knowledge level, the symbol level and the system level of a DSS. This theory explicitly expresses the methodological viewpoint of relational realism. At the knowledge level this implies defining knowledge on the basis of matching the intension and extension of concepts. At the symbol level it deals with knowledge representation and here decision tables are advanced and formally introduced. At the system level the formalism used at the symbol level is implemented to develop a relational matching DSS.     

Parameter analysis of the IWA Anaerobic Digestion Model No. 1 for the anaerobic digestion of blackwater with kitchen refuse.

The IWA anaerobic digestion model No.1 (ADM1) had been successfully applied to the lab-scale mesophilic blackwater anaerobic digestion (BWAD) plant for cases of only blackwater (BW) feeding and of BW plus kitchen refuse (KR) feeding. In this paper, the simulation results of BW + KR anaerobic digestion are presented and discussed, followed by the analyses and discussion of the critical and important parameters as well as the performance of ADM1 based on these results. The raw BW can contain up to 30% short chain fatty acids (SCFA) which severely impact the performance of the model. The model proved that the disintegration/hydrolysis rate of BW is around 4.5 d(-1), which is about ten times higher than that of KR (Kdis,KR = 0.5 d(-1)). ADM1 is not sensitive to the distribution ratio among carbohydrates, proteins and lipids. For BWAD the C4 metabolism can be integrated in the uptake of LCFA. The uptake delay phenomenon was observed and cannot be simulated by ADM1, but it is tolerable. No unique KI,NH3,ac is found out for all investigated ammonia concentration ranges. Meanwhile, ADM1 is not sensitive to KLa and kp1 so they can easily be set up.     

Effectiveness of Semi-Supervised Active Learning in Automated Wound Image Segmentation

Appropriate wound management shortens the healing times and reduces the management costs, benefiting the patient in physical terms and potentially reducing the healthcare system’s economic burden. Among the instrumental measurement methods, the image analysis of a wound area is becoming one of the cornerstones of chronic ulcer management. Our study aim is to develop a solid AI method based on a convolutional neural network to segment the wounds efficiently to make the work of the physician more efficient, and subsequently, to lay the foundations for the further development of more in-depth analyses of ulcer characteristics. In this work, we introduce a fully automated model for identifying and segmenting wound areas which can completely automatize the clinical wound severity assessment starting from images acquired from smartphones. This method is based on an active semi-supervised learning training of a convolutional neural network model. In our work, we tested the robustness of our method against a wide range of natural images acquired in different light conditions and image expositions. We collected the images using an ad hoc developed app and saved them in a database which we then used for AI training. We then tested different CNN architectures to develop a balanced model, which we finally validated with a public dataset. We used a dataset of images acquired during clinical practice and built an annotated wound image dataset consisting of 1564 ulcer images from 474 patients. Only a small part of this large amount of data was manually annotated by experts (ground truth). A multi-step, active, semi-supervised training procedure was applied to improve the segmentation performances of the model. The developed training strategy mimics a continuous learning approach and provides a viable alternative for further medical applications. We tested the efficiency of our model against other public datasets, proving its robustness. The efficiency of the transfer learning showed that after less than 50 epochs, the model achieved a stable DSC that was greater than 0.95. The proposed active semi-supervised learning strategy could allow us to obtain an efficient segmentation method, thereby facilitating the work of the clinician by reducing their working times to achieve the measurements. Finally, the robustness of our pipeline confirms its possible usage in clinical practice as a reliable decision support system for clinicians.     

Impact of Freeze-Drying on Cord Blood (CB), Serum (S), and Platelet-Rich Plasma (CB-PRP) Preparations on Growth Factor Content and In Vitro Cell Wound Healing

Blood-based preparations are used in clinical practice for the treatment of several eye disorders. The aim of this study is to analyze the effect of freeze-drying blood-based preparations on the levels of growth factors and wound healing behaviors in an in vitro model. Platelet-rich plasma (PRP) and serum (S) preparations from the same Cord Blood (CB) sample, prepared in both fresh frozen (FF) and freeze-dried (FD) forms (and then reconstituted), were analyzed for EGF and BDNF content (ELISA Quantikine kit). The human MIO-M1 glial cell line (Moorfield/Institute of Ophthalmology, London, UK) was incubated with FF and FD products and evaluated for cell migration with scratch-induced wounding (IncuCyte S3 Essen BioScience), proliferation with cyclin A2 and D1 gene expression, and activation with vimentin and GFAP gene expression. The FF and FD forms showed similar concentrations of EGF and BDNF in both the S and PRP preparations. The wound healing assay showed no significant difference between the FF and FD forms for both S and PRP. Additionally, cell migration, proliferation, and activation did not appear to change in the FD forms compared to the FF ones. Our study showed that reconstituted FD products maintained the growth factor concentrations and biological properties of FF products and could be used as a functional treatment option.     

Reverse logistics network design with stochastic lead times

This work is concerned with the efficient design of a reverse logistics network using an extended version of models currently found in the literature. Those traditional, basic models are formulated as mixed integer linear programs (MILP-model) and determine which facilities to open that minimize the investment, processing, transportation, disposal and penalty costs while supply, demand and capacity constraints are satisfied. However, we show that they can be improved when they are combined with a queueing model because it enables to account for (1) some dynamic aspects like lead time and inventory positions, and (2) the higher degree of uncertainty inherent to reverse logistics. Since this extension introduces nonlinear relationships, the problem is defined as a mixed integer nonlinear program (MINLP-model). Due to this additional complexity, the MINLP-model is presented for a single product-single-level network. Several examples are solved with a genetic algorithm based on the technique of differential evolution.     

Should a bicuspid aortic valve be replaced in the presence of subvalvar or supravalvar aortic stenosis?

BACKGROUND: A bicuspid aortic valve is commonly associated with other levels of left ventricular outflow tract obstruction. Providing the bicuspid aortic valve is competent and nonobstructive, repair of subvalvar or supravalvar stenosis usually focuses on the obstructive lesions, leaving the valve in situ. The aim of this report was to examine the impact of a bicuspid aortic valve on the risk of reoperation for patients undergoing operation for subvalvar or supravalvar aortic stenosis. METHODS: Since 1976, 47 patients with supravalvar or subvalvar aortic stenosis have undergone repair. The median follow-up is 5.1 years (range, 2 months to 20.1 years). Sixteen patients (34%) had a bicuspid aortic valve that was competent and nonobstructive, and 31 (66%) had a tricuspid aortic valve. RESULTS: Reoperation was required in 9 patients (56%) with a bicuspid aortic valve, in each involving aortic valve replacement with an autograft (3), homograft (2), or prosthesis (4). Six patients (19%) with a tricuspid aortic valve required reoperation, yet only 1 required aortic valve replacement. The freedom from valve replacement was 43% (70% confidence interval, 31% to 55%) in the bicuspid aortic valve group versus 100% (70% confidence interval, 94% to 99.5%) in the tricuspid group at 5 years (p = 0.0001). The freedom from any reoperation at 5 years was 43% (70% confidence interval, 31% to 55%) in patients with a bicuspid aortic valve versus 86% (70% confidence interval, 80% to 93%) in the tricuspid group (p = 0.02). CONCLUSIONS: The data suggest that patients with subvalvar or supravalvar aortic stenosis and a bicuspid valve may be better palliated with a more definitive operation such as the Ross or Ross-Konno procedure.