Molecular follow-up of disease progression and interferon therapy in chronic myelocytic leukemia

We previously reported that the abl promoter (Pa) undergoes de novo DNA methylation in the course of chronic myelocytic leukemia (CML). The clinical implications of this finding are the subject of the present study in which samples of CML patients, including a group treated with interferon alpha (IFNalpha) were surveyed. The methylation status of the abl promoter was monitored by polymerase chain reaction (PCR) amplification of the Pa region after digestion with several site-methylation sensitive restriction enzymes. Some 74% of the DNA samples from blood and marrow drawn in the chronic phase were nonmethylated, similar to control samples from non-CML patients. The remaining 26% were partially methylated in the abl Pa region. The latter samples were derived from patients who were indistinguishable from the others on the basis of clinical presentation. Methylated samples were mostly derived from patients known to have a disease of longer duration (26 months v 7.5 months, P = .01). Samples of 30 IFNalpha-treated patients were sequentially analyzed in the course of treatment. Fifteen patients with no evidence of Pa methylation before treatment remained methylation-free. The remainder, who displayed Pa methylation before treatment, reverted to the methylation-free status. The outcome is attributed to IFNalpha therapy, as the Pa methylation status was not reversed in any of the patients treated with hydroxyurea. Methylation of the abl promoter indicates a disease of long-standing, most likely associated with a higher probability of imminent blastic transformation. It appears to predict the outcome of IFNalpha therapy far better than the cytogenetic response.     

Bi-level fuzzy based advanced reservation of Cloud workflow applications on distributed Grid resources

The increasing demand on execution of large-scale Cloud workflow applications which need a robust and elastic computing infrastructure usually lead to the use of high-performance Grid computing clusters. As the owners of Cloud applications expect to fulfill the requested Quality of Services (QoS) by the Grid environment, an adaptive scheduling mechanism is needed which enables to distribute a large number of related tasks with different computational and communication demands on multi-cluster Grid computing environments. Addressing the problem of scheduling large-scale Cloud workflow applications onto multi-cluster Grid environment regarding the QoS constraints declared by application’s owner is the main contribution of this paper. Heterogeneity of resource types (service type) is one of the most important issues which significantly affect workflow scheduling in Grid environment. On the other hand, a Cloud application workflow is usually consisting of different tasks with the need for different resource types to complete which we call it heterogeneity in workflow. The main idea which forms the soul of all the algorithms and techniques introduced in this paper is to match the heterogeneity in Cloud application’s workflow to the heterogeneity in Grid clusters. To obtain this objective a new bi-level advanced reservation strategy is introduced, which is based upon the idea of first performing global scheduling and then conducting local scheduling. Global-scheduling is responsible to dynamically partition the received DAG into multiple sub-workflows that is realized by two collaborating algorithms: (1) The Critical Path Extraction algorithm (CPE) which proposes a new dynamic task overall critically value strategy based on DAG’s specification and requested resource type QoS status to determine the criticality of each task; and (2) The DAG Partitioning algorithm (DAGP) which introduces a novel dynamic score-based approach to extract sub-workflows based on critical paths by using a new Fuzzy Qualitative Value Calculation System to evaluate the environment. Local-scheduling is responsible for scheduling tasks on suitable resources by utilizing a new Multi-Criteria Advance Reservation algorithm (MCAR) which simultaneously meets high reliability and QoS expectations for scheduling distributed Cloud-base applications. We used the simulation to evaluate the performance of the proposed mechanism in comparison with four well-known approaches. The results show that the proposed algorithm outperforms other approaches in different QoS related terms.     

Dynamic modeling and CPG-based trajectory generation for a masticatory rehab robot

Human mastication is a complex and rhythmic biomechanical process which is regulated by a brain stem central pattern generator (CPG). Masticatory patterns, frequency and amplitude of mastication are different from person to person and significantly depend on food properties. The central nervous system controls the activity of muscles to produce smooth transitions between different movements. Therefore, to rehab human mandibular system, there is a real need to use the concept of CPG for development of a new methodology in jaw exercises and to help jaw movements recovery. This paper proposes a novel method for real-time trajectory generation of a mastication rehab robot. The proposed method combines several methods and concepts including kinematics, dynamics, trajectory generation and CPG. The purpose of this article is to provide a methodology to enable physiotherapists to perform the human jaw rehabilitation. In this paper, the robotic setup includes two Gough–Stewart platforms. The first platform is used as the rehab robot, while the second one is used to model the human jaw system. Once the modeling is completed, the second robot will be replaced by an actual patient for the selected physiotherapy. Gibbs–Appell’s formulation is used to obtain the dynamics equations of the rehab robot. Then, a method based on the Fourier series is employed to tune parameters of the CPG. It is shown that changes in leg lengths, due to the online changes of the mastication parameters, occur in a smooth and continuous manner. The key feature of the proposed method, when applied to human mastication, is its ability to adapt to the environment and change the chewing pattern in real-time parameters, such as amplitudes as well as jaw movements velocity during mastication.     

Green synthesis and characterization of RGO/Cu nanocomposites as photocatalytic degradation of organic pollutants in waste-water

Recently, nanocomposite photocatalysts based on semiconductors have attracted much attention due to their suitable bandgap. Combination of tow of several semiconductors can slow down the electron-hole recombination. In this regard, we have depicted an eco-friendly and green fabrication technique to synthesize RGO/Cu nanocomposite by the reduction of graphene oxide and Cu²⁺ ion utilizing spearmint extract as a reductant and capping agent. The sample was identified by FTIR, XRD, FESEM, EDS, HRTEM, and CV. The results of photocatalytic performance revealed that RGO/Cu is an efficient catalyst for degrading organic pollutants. This compound can eliminate Rhodamine B (RhB) and Methylene blue (MB) 91.0% and 72.0%, respectively.     

Biometric human recognition system based on ECG

Multimedia Tools and Applications - The ECG (electrocardiogram) is an emerging technology for biometric human identification. In this paper, the performance of an ECG biometric recognition system...     

Structural/texture evolution of CaO/MCM‐41 nanocatalyst by doping various amounts of cerium for active and stable catalyst: Biodiesel production from waste vegetable cooking oil

In present work, the aim of producing biodiesel from waste cooking oil was pursued by doping the cerium element into the MCM‐41 framework as catalyst with various Si/Ce molar ratio (5, 10, 25, 50, and Ce = 0). The catalytic performance and stability improved by employing the ultrasound irradiation in active phase loading step of catalyst preparation. The physicochemical characteristics of synthesized samples were investigated using various techniques as follows: Brunauer‐Emmett‐Teller (BET), X‐ray powder diffraction (XRD), Fourier transfer infrared (FTIR), energy‐dispersive X‐ray spectroscopy (EDX), transmission electron microscopy (TEM), and field emission scanning electron microscope (FESEM). The XRD patterns along with the results of FTIR and BET analysis revealed the MCM‐41 framework destruction while increasing the Ce content. The FESEM images of the nanocatalysts illustrated a well distribution and uniform morphology for the Ca/CeM (Si/Ce = 25). The particle size and size distribution of the Ca/CeM (Si/Ce = 25) were subsequently determined by TEM and FESEM images. The activity of fabricated nanocatalysts was evaluated by measuring the free acid methyl ester (FAME) content of produced biodiesel. The tests were carried out at constant operational conditions: T = 60°C, catalyst loading = 5 wt%, methanol/oil molar ratio = 9, and 6‐hour reaction time. A superior activity was observed for Ca/CeM (Si/Ce = 25) among other nanocatalysts with 96.8% conversion of triglycerides to biodiesel. The mentioned sample was utilized in five reaction cycles, and at the end of the fifth cycle, the conversion reached to 91.5% which demonstrated its significant stability.