Determination of gas dispersion in vapor extraction of heavy oil and bitumen

In this work, a mathematical model is developed and simulated to determine gas dispersion along with solubility during the vapor extraction (Vapex) of live oil from a laboratory scale physical model. The physical model is a rectangular block of homogenous porous medium saturated with heavy oil and bitumen. At a given temperature and pressure, the block is initially exposed on its side to a solvent gas, which diffuses into the medium and gets absorbed. The absorption of gas reduces the viscosity of heavy oil and bitumen causing it to drain under gravity. The low-viscosity “live oil” is produced at the bottom of the porous block. The production of live oil with time is accompanied by the shrinkage of oil in the block as well as its increased exposure to gas from top. These phenomena of Vapex are described by the mathematical model, which is used to calculate live oil production with various values of gas solubility and dispersion. Their optimal values are determined for the vapor extraction of Cold Lake bitumen with butane by matching calculated live oil production with its experimental values published earlier.     

Recent advances in the rheooptical characterization of silicon-containing networks

Recent advances in the various theories of strain-birefringenece of polymer networks are presented. The classical theories as well as the more advanced models are outlined together with some recent theoretical results on poly (dimethylsiloxane). Reference to work on other Si-containing polymers is made. The problems of intermolecular correlations occurring in polymer networks and their effect on the observed optical properties are discussed with reference to the optical-configuration parameter. Conclusions report areas of current research.This review was presented at the Second International Topical Workshop, Advances in Silicon-Based Polymer Science.     

Annotation-based access control for collaborative information spaces

Web 2.0 social platforms (e.g., Flickr, YouTube) and Collaborative Working Environments (e.g., Microsoft SharePoint, BSCW) provide Web-based collaborative information spaces which enable common users and/or professionals to work together and share their online resources. Most of these collaborative information spaces provide role-based or group-based, coarse-grained access control policies which cannot successfully cope with the requirements posed by massive and open collaboration. In this paper, we present an annotation-based access control (AnBAC) model supported by a Collaboration Vocabulary (CoVoc) as a more flexible and user-centric access control approach. Based on this, we developed two tools: Uncle-Share is a gadget that provides annotation-based access control and can be equipped with CoVoc for annotating collaborative relationships. Who-With-Whom uses CoVoc to visualize extended social networks in order to help users to select appropriate contacts to grant access to resources.     

Big data and machine learning: A roadmap towards smart plants

Industry 4.0 aims to transform chemical and biochemical processes into intelligent systems via the integration of digital components with the actual physical units involved. This process can be thought of as addition of a central nervous system with a sensing and control monitoring of components and regulating the performance of the individual physical assets (processes, units, etc.) involved. Established technologies central to the digital integrating components are smart sensing, mobile communication, Internet of Things, modelling and simulation, advanced data processing, storage and analysis, advanced process control, artificial intelligence and machine learning, cloud computing, and virtual and augmented reality. An essential element to this transformation is the exploitation of large amounts of historical process data and large volumes of data generated in real-time by smart sensors widely used in industry. Exploitation of the information contained in these data requires the use of advanced machine learning and artificial intelligence technologies integrated with more traditional modelling techniques. The purpose of this paper is twofold: a) to present the state-of-the-art of the aforementioned technologies, and b) to present a strategic plan for their integration toward the goal of an autonomous smart plant capable of self-adaption and self-regulation for short- and long-term production management.     

ApoA1 Deficiency Reshapes the Phenotypic and Molecular Characteristics of Bone Marrow Adipocytes in Mice

In the present study, we studied the effect of apolipoprotein A-1 (APOA1) on the spatial and molecular characteristics of bone marrow adipocytes, using well-characterized ApoA1 knockout mice. APOA1 is a central regulator of high-density lipoprotein cholesterol (HDL-C) metabolism, and thus HDL; our recent work showed that deficiency of APOA1 increases bone marrow adiposity in mice. We found that ApoA1 deficient mice have greatly elevated adipocytes within their bone marrow compared to wild type counterparts. Morphologically, the increased adipocytes were similar to white adipocytes, and displayed proximal tibial-end localization. Marrow adipocytes from wild type mice were significantly fewer and did not display a bone-end distribution pattern. The mRNA levels of the brown/beige adipocyte-specific markers Ucp1, Dio2, Pat2, and Pgc1a; and the expression of leptin were greatly reduced in the ApoA1 knock-out in comparison to the wild-type mice. In the knock-out mice, adiponectin was remarkably elevated. In keeping with the close ties of hematopoietic stem cells and marrow adipocytes, using flow cytometry we found that the elevated adiposity in the ApoA1 knockout mice is associated with a significant reduction in the compartments of hematopoietic stem cells and common myeloid, but not of the common lymphoid, progenitors. Moreover, the ‘beiging’-related marker osteopontin and the angiogenic factor VEGF were also reduced in the ApoA1 knock-out mice, further supporting the notion that APOA1—and most probably HDL-C—regulate bone marrow microenvironment, favoring beige/brown adipocyte characteristics.     

A structured methodology for assessing and improving e-services in digital cities

Many cities all over the world are making large investments for the construction of big network infrastructures, in order to offer to local public organizations, businesses and citizens high speed connectivity, and on top of them useful e-services, aiming to achieve various social and economic objectives. The value generated from these costly ‘digital city’ investments is actually the value provided to the citizens and businesses by the e-services that will be developed and run on these network infrastructures. This paper proposes and validates a structured methodology for assessing and improving e-services developed in digital cities. The proposed methodology assesses the various types of value generated by an e-service, and also the relations among them, allowing a more structured evaluation, a deeper understanding of the value generation process and also identification and prioritization of the improvements that should be made in the e-service with the usually scarce resources in municipalities. This methodology is applied for the evaluation of an e-learning service developed in the Greek city of Karlovassi for young citizens, and also for the prioritization of the necessary improvements in it. The above application provided positive and encouraging evidence concerning the validity, usefulness and applicability of the proposed method.     

Smart Surfaces: Heterogeneous Photo-Catalysis on TiO2 Based Coatings for De-pollution Purposes in Indoor and Outdoor Environments

Topics in Catalysis - Heterogeneous photocatalysis using semiconductors, e.g. TiO2 as photocatalyst is a promising technology for the degradation of environmental pollutants. Preliminary evidence...     

Shikonin‐loaded liposomes as a new drug delivery system: Physicochemical characterization and in vitro cytotoxicity

Alkannin and shikonin are naturally occurring hydroxynaphthoquinones with a well‐established spectrum of wound healing, antimicrobial, anti‐inflammatory, and antioxidant activities. Recently, extensive scientific effort has been focused on their effectiveness on several tumors and mechanism(s) of antitumor activity. Liposomes have been proved as adequate drug carriers offering significant advantages over conventional formulations, such as controlled release and targeted drug delivery, leading to the appearance of several liposomal formulations in the market, some of them concerning anticancer drugs. The aim of the present study was to prepare shikonin‐loaded liposomes for the first time in order to enhance shikonin therapeutic index. An optimized technique based on the thin film hydration method was developed and liposomes characterization was performed in terms of their physicochemical characteristics, drug entrapment efficiency, and release profile. Results indicated the successful incorporation of shikonin into liposomes, using both 1,2‐dipalmitoylphosphatidylcholine and egg phosphatidylcholine lipids. Liposomes presented good physicochemical characteristics, high entrapment efficiency and satisfactory in vitro release profile. In vitro cytotoxicity of liposomes was additionally tested against three human cancer cell lines (breast, glioma, and non‐small cell lung cancer) showing a moderate growth inhibitory activity. Practical applications: Shikonin is a naturally occurring hydroxynaphthoquinone and extensive scientific research (in vitro, in vivo, and clinical trials) has been conducted during the last years, focusing on its effectiveness on several tumors and mechanism(s) of antitumor action. The purpose of this work was to prepare and characterize shikonin‐loaded liposomes as a new drug delivery system for shikonin. Liposomal formulations provide significant advantages over conventional dosage forms, such as controlled release and targeted drug delivery for anticancer agents. Thus, liposomes could reduce shikonin's side effects, enhance selectivity to cancer cells and protect shikonin from internal biotransformations and instability matters (oxidization and polymerization). Furthermore, liposomal delivery helps overcome the low aqueous solubility of shikonin, which is the major barrier to its oral and internal administration, since it cannot be dissolved and further absorbed from the receptor.     

A Role for Human Renal Tubular Epithelial Cells in Direct Allo-Recognition by CD4+ T-Cells and the Effect of Ischemia-Reperfusion

Direct allorecognition is the earliest and most potent immune response against a kidney allograft. Currently, it is thought that passenger donor professional antigen-presenting cells (APCs) are responsible. Further, many studies support that graft ischemia-reperfusion injury increases the probability of acute rejection. We evaluated the possible role of primary human proximal renal tubular epithelial cells (RPTECs) in direct allorecognition by CD4+ T-cells and the effect of anoxia-reoxygenation. In cell culture, we detected that RPTECs express all the required molecules for CD4+ T-cell activation (HLA-DR, CD80, and ICAM-1). Anoxia-reoxygenation decreased HLA-DR and CD80 but increased ICAM-1. Following this, RPTECs were co-cultured with alloreactive CD4+ T-cells. In T-cells, zeta chain phosphorylation and c-Myc increased, indicating activation of T-cell receptor and co-stimulation signal transduction pathways, respectively. T-cell proliferation assessed with bromodeoxyuridine assay and with the marker Ki-67 increased. Previous culture of RPTECs under anoxia raised all the above parameters in T-cells. FOXP3 remained unaffected in all cases, signifying that proliferating T-cells were not differentiated towards a regulatory phenotype. Our results support that direct allorecognition may be mediated by RPTECs even in the absence of donor-derived professional APCs. Also, ischemia-reperfusion injury of the graft may enhance the above capacity of RPTECs, increasing the possibility of acute rejection.