A soft computing approach for privacy requirements engineering: The PriS framework

Soft computing continuously gains interest in many fields of academic and industrial domain; among the most notable characteristics for using soft computing methodological tools is the ability to handle with vague and imprecise data in decision making processes. Similar conditions are often encountered in requirements engineering. In this paper, we introduce the PriS approach, a security and privacy requirements engineering framework which aims at incorporating privacy requirements early in the system development process. Specifically, PriS provides a set of concepts for modelling privacy requirements in the organisation domain and a systematic way-of-working for translating these requirements into system models. The conceptual model of PriS uses a goal hierarchy structure. Every privacy requirement is either applied or not on every goal. To this end every privacy requirement is a variable that can take two values [0,1] on every goal meaning that the requirements constraints the goal (value 1) or not (value 0). Following this way of working PriS ends up suggesting a number of implementation techniques based on the privacy requirements constraining the respective goals. Taking into account that the mapping of privacy variables to a crisp set consisting of two values [0,1] is constraining, we extend also the PriS framework so as to be able to address the degree of participation of every privacy requirement towards achieving the generic goal of privacy. Therefore, we propose a fuzzification of privacy variables that maps the expression of the degree of participation of each privacy variable to the [0,1] interval. We also present a mathematical framework that allows the concurrent management of combined independent preferences towards the necessity of a privacy measure; among the advantages of the presented extended framework is the scalability of the approach in such a way that the results are not limited by the number of independent opinions or by the number of factors considered while reasoning for a specific selection of privacy measures.     

Investigation of biofilm growth and attrition in a three‐phase airlift bioreactor using 35SO42− as a radiolabelled tracer

The growth and biomass loss pattern for immobilized cells growing on diatomaceous earth particles in a three‐phase airlift bioreactor (TPALB) is studied using ³⁵S as a radiolabelled tracer. A monoculture of Beneckea natriegens was grown immobilized on support particles in a 3 L TPALB. Sterile conditions were maintained during the experiments, and n‐propanol was used as the sole carbon source. After the system reached steady state, the unlabelled sulfate (SO₄^2?) in the feed tank was substituted by a radioactive grade (³⁵SO₄^2?), and the assimilation of ³⁵S in the immobilized and in the suspended cells was monitored. The results indicated that the growth rate of immobilized biomass was not uniform throughout the biofilm. More specifically, it was concluded that cells growing closer to the external biofilm layer exhibit a higher growth rate, and that biomass loss from the biofilm was through attrition at the outer biofilm surface rather than by sloughing off of whole sections of biofilm. Copyright © 2006 Society of Chemical Industry     

On performance of slowly varying systems

In this paper we present a result on the performance of slowly time varying systems. In particular we show that the performance of such systems cannot be much worse than that of the frozen-time systems which are time invariant. We also demonstrate via an example that optimal frozen-time design may in general result to far from optimal performance even though the time variations of the system can be arbitrarily slow.     

The addition of paclitaxel to continuous infusion 5-fluorouracil is an active regimen for metastatic breast cancer

We investigated tissue staining for Bcl-2 and Bax proteins, which regulate apoptosis, as indicators of chemotherapeutic effect in patients with gastric cancer. In 23 patients with gastric carcinoma biopsy specimens were obtained endoscopically prior to chemotherapy and stained immunohistochemically with anti-Bcl-2 and anti-Bax antibodies. Patients then were treated with continuous infusion of 5-FU and cisplatin. No correlation was seen between chemotherapeutic effect and Bcl-2 or Bax alone. However, among the Bax-positive cases, the patients with Bcl-2-positive tumors were significantly more chemoresistant (p = 0.036) and had worse prognoses (p = 0.008) than Bcl-2-negative cases. Therefore, immunohistochemical staining for Bcl-2 protein may predict chemotherapeutic efficacy or guide specific therapeutic choices in treating Bax-positive tumors.     

Numerical stability and convergence criteria for equations for dynamic fracture in DCB composite specimens

The stability and convergence criteria for numerical solutions of the governing equations for dynamic crack propagation in DCB unidirectional composite specimens are determined. The stability criteria are given explicitly and it is concluded that the convergence requirements will be met automatically by solutions which satisfy the stability criteria.     

Effect of high-pressure treatment at various temperatures on indigenous proteolytic enzymes and whey protein denaturation in bovine milk

The objective of the present study was to determine the effect of high pressure (HP) processing (200, 450 and 650 MPa) at various temperatures (20, 40 and 55 degrees C) on the total plasmin plus plasminogen-derived activity (PL), plasminogen activator(s) (PA) and cathepsin D activities and on denaturation of major whey proteins in bovine milk. Data indicated that transfer of both PL and PA from the casein micelles to milk serum occurred at all pressures utilized at room temperature (20 degrees C). In addition to the transfer of PL and PA from micelles, there were reductions in activities of PL (16-18%) and PA (38-62%) for the pressures 450 and 650 MPa, at room temperature. There were synergistic negative effects between pressure and temperature on residual PL activity at 450 and 650 MPa and on residual PA activity only at 450 MPa. Cathepsin D activity in the acid whey from HP-treated milk was in general baroresistant at room temperature. The residual activity of cathepsin D decreased significantly at 650 MPa and 40 degrees C and at the pressures 450 and 650 MPa at 55 degrees C. Synergistic negative effects on the amount of native beta-lactoglobulin were observed at 450 and 650 MPa and on the amount of native alpha-lactalbumin at 650 MPa. There were significant correlations between enzymatic activities (PL, PA and cathepsin D) and the residual native beta-lactoglobulin and alpha-lactalbumin in bovine milk. In conclusion, HP significantly affected the activity of indigenous proteolytic enzymes and whey protein denaturation in bovine milk. Reduction in activity of indigenous enzymes (PL, PA and cathepsin D) and transfer of PL and PA from the casein to milk serum induced by HP is expected to have a profound effect on cheese yield, proteolysis during cheese ripening and quality of UHT milk during storage.     

A multilevel sampled‐data approach for resilient navigation and control of autonomous systems

Autonomous systems are rapidly becoming an integrated part of the modern life. Safe and secure navigation and control of these systems present significant challenges in the presence of uncertainties, physical failures, and cyber attacks. In this paper, we formulate a navigation and control problem for autonomous systems using a multilevel control structure, in which the high‐level reference commands are limited by a saturation function, whereas the low‐level controller tracks the reference by compensating for disturbances and uncertainties. For this purpose, we consider a class of nested, uncertain, multiple‐input–multiple‐output systems subject to reference command saturation, possibly with nonminimum phase zeros. A multirate output‐feedback adaptive controller is developed as the low‐level controller. The sampled‐data (SD) design of this controller facilitates the direct implementation on digital computers, where the input/output signals are available at discrete time instances with different sampling rates. In addition, stealthy zero‐dynamics attacks become detectable by considering a multirate SD formulation. Robust stability and performance of the overall closed‐loop system with command saturation and multirate adaptive control are analyzed. Simulation scenarios for navigation and control of a fixed‐wing drone under failures/attacks are provided to validate the theoretical findings.     

Exploiting IP‐layer traffic prediction analytics to allocate spectrum resources using swarm intelligence

Elastic optical networks emerge as a reliable backbone platform covering the next‐generation connectivity requirements. It consists of advanced enabling components that provide the ability for extensive configuration leading to performance improvement in many areas of interest. Higher layer analytics like data from IP traffic prediction can assist in the process of allocating resources at the optical layer. This way, light connections are established more efficiently while targeting specific performance goals. For that purpose, an algorithm is designed and evaluated that exploits traffic prediction of data transfers between nodes of an optical metro or backbone network. Next, it utilizes adaptive functionality based on particle swarm optimization to find paths with available spectrum resources. These resources can facilitate more efficiently the future traffic demand, since traffic prediction data are considered when finding the related paths. The innovative resource allocation method is evaluated using small and very large real topologies. It scales (in execution time and resource usage) according to node increase, executes in feasible time frames, and reduces transponder utilization resulting to increased energy efficiency.     

Fibro/chondrogenic differentiation of dental stem cells into chitosan/alginate scaffolds towards temporomandibular joint disc regeneration

Tissue engineering (TE) may provide effective alternative treatment for challenging temporomandibular joint (TMJ) pathologies associated with disc malpositioning or degeneration and leading to severe masticatory dysfunction. Aim of this study was to evaluate the potential of chitosan/alginate (Ch/Alg) scaffolds to promote fibro/chondrogenic differentiation of dental pulp stem cells (DPSCs) and production of fibrocartilage tissue, serving as a replacement of the natural TMJ disc. Ch/Alg scaffolds were fabricated by crosslinking with CaCl2 combined or not with glutaraldehyde, resulting in two scaffold types that were physicochemically characterized, seeded with DPSCs or human nucleus pulposus cells (hNPCs) used as control and evaluated for cell attachment, viability, and proliferation. The DPSCs/scaffold constructs were incubated for up to 8 weeks and assessed for extracellular matrix production by means of histology, immunofluorescence, and thermomechanical analysis. Both Ch/Alg scaffold types with a mass ratio of 1:1 presented a gel-like structure with interconnected pores. Scaffolds supported cell adhesion and long-term viability/proliferation of DPSCs and hNPCs. DPSCs cultured into Ch/Alg scaffolds demonstrated a significant increase of gene expression of fibrocartilaginous markers (COLI, COL X, SOX9, COM, ACAN) after up to 3 weeks in culture. Dynamic thermomechanical analysis revealed that scaffolds loaded with DPSCs significantly increased storage modulus and elastic response compared to cell-free scaffolds, obtaining values similar to those of native TMJ disc. Histological data and immunochemical staining for aggrecan after 4 to 8 weeks indicated that the scaffolds support abundant fibrocartilaginous tissue formation, thus providing a promising strategy for TMJ disc TE-based replacement.

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Automated reference-free detection of motion artifacts in magnetic resonance images

Objectives

Our objectives were to provide an automated method for spatially resolved detection and quantification of motion artifacts in MR images of the head and abdomen as well as a quality control of the trained architecture.

Materials and methods

T1-weighted MR images of the head and the upper abdomen were acquired in 16 healthy volunteers under rest and under motion. Images were divided into overlapping patches of different sizes achieving spatial separation. Using these patches as input data, a convolutional neural network (CNN) was trained to derive probability maps for the presence of motion artifacts. A deep visualization offers a human-interpretable quality control of the trained CNN. Results were visually assessed on probability maps and as classification accuracy on a per-patch, per-slice and per-volunteer basis.

Results

On visual assessment, a clear difference of probability maps was observed between data sets with and without motion. The overall accuracy of motion detection on a per-patch/per-volunteer basis reached 97%/100% in the head and 75%/100% in the abdomen, respectively.

Conclusion

Automated detection of motion artifacts in MRI is feasible with good accuracy in the head and abdomen. The proposed method provides quantification and localization of artifacts as well as a visualization of the learned content. It may be extended to other anatomic areas and used for quality assurance of MR images.