Preparation of hierarchical porous carbon derived from averrhoa bilimbi and its diffusion properties

In this study, a hierarchically porous carbon was prepared from a natural material, Averrhoa bilimbi, also known as bilimbi. The bilimbis were cut into preferred shape and size before drying by freeze drying method. The bilimbis were then subjected to pyrolysis at temperature of 400°C and transformed to porous carbon. Scanning electron microscopy (SEM) revealed that the bilimbis have a hierarchically porous structure in the macro-range. The diameter of the porosity decreased inwards from 30 to 8μm. Different types of motor oil, which were used to represent bulky molecules, were employed to test the diffusivity of these molecules from the bilimbi. It was found that the oils were able to diffuse through the hierarchically porous bilimbi in 2 to 3 hours, depending on the viscosity of the oils. Therefore, it can be concluded that, Averrhoa bilimbi possesses hierarchical porous structure with interconnected pores and capability to diffuse bulky molecules

Yet Another Text Captcha Solver: A Generative Adversarial Network Based Approach

Despite several attacks have been proposed, text-based CAPTCHAs are still being widely used as a security mechanism. One of the reasons for the pervasive use of text captchas is that many of the prior attacks are scheme-specific and require a labor-intensive and time-consuming process to construct. This means that a change in the captcha security features like a noisier background can simply invalid an earlier attack. This paper presents a generic, yet effective text captcha solver based on the generative adversarial network. Unlike prior machine-learning-based approaches that need a large volume of manually-labeled real captchas to learn an effective solver, our approach requires significantly fewer real captchas but yields much better performance. This is achieved by first learning a captcha synthesizer to automatically generate synthetic captchas to learn a base solver, and then fine-tuning the base solver on a small set of real captchas using transfer learning. We evaluate our approach by applying it to 33 captcha schemes, including 11 schemes that are currently being used by 32 of the top-50 popular websites including Microsoft, Wikipedia, eBay and Google. Our approach is the most capable attack on text captchas seen to date. It outperforms four state-of-the-art text-captcha solvers by not only delivering a significant higher accuracy on all testing schemes, but also successfully attacking schemes where others have zero chance. We show that our approach is highly efficient as it can solve a captcha within 0.05 second using a desktop GPU. We demonstrate that our attack is generally applicable because it can bypass the advanced security features employed by most modern text captcha schemes. We hope the results of our work can encourage the community to revisit the design and practical use of text captchas

Remarks on Cone Metric Spaces and Fixed Point Theorems of Contractive Mappings

We discuss the newly introduced concept of cone metric spaces. We also discuss the fixed point existence results of contractive mappings defined on such metric spaces. In particular, we show that most of the new results are merely copies of the classical ones

User-Centric Networks Selection with Adaptive Data Compression for Smart Health

The increasing demand for intelligent and sustainable healthcare services has prompted the development of smart health systems. Rapid advances in wireless access technologies and in-network data reduction techniques can significantly assist in implementing such smart systems through providing seamless integration of heterogeneous wireless networks, medical devices, and ubiquitous access to data. Utilization of the spectrum across diverse radio technologies is expected to significantly enhance network capacity and quality of service (QoS) for emerging applications such as remote monitoring over mobile-health (m-health) systems. However, this imposes an essential need to develop innovative networks selection mechanisms that account for energy efficiency while meeting application quality requirements. In this context, this paper proposes an efficient networks selection mechanism with adaptive compression for improving medical data delivery over heterogeneous m-health systems. We consider different performance aspects, as well as networks characteristics and application requirements, so as to obtain an efficient solution that grasps the conflicting nature of the various users' objectives and addresses their inherent tradeoffs. The proposed methodology advocates a user-centric approach towards leveraging heterogeneous wireless networks to enhance the performance of m-health systems. Simulation results show that our solution significantly outperforms state-of-the-art techniques.Scopu

The spectrum of cutaneous infection in diabetic patients with hepatitis C virus infection: A single-center study from Egypt

Context: Hepatitis-C virus (HCV) infection and diabetes mellitus (DM) have a significant association with skin disorders. Aims: The aim of this study was to assess the impact of HCV infection on the pattern of cutaneous infections among diabetic patients. Methods and Material: A prospective study included diabetic patients who attended Al-Hussein University hospital, Cairo during the period from 2008 to 2010. Patients were examined for skin infections, and investigated for HCV infection. Statistical Analysis Used: SPSS (version 11.5). Results: The study included 163 patients (102 males and 61 females) with a mean age of 46.2 ± 4.83 years. Ninety five patients (58.3%) were HCV+ve (group A) while 68 patients (41.8%) were HCV-ve (group B). Skin infections in group A included fungal (48.4%), viral (26.3%), bacterial (22.1%) and parasitic (3.2%) while in group B, the spectrum included bacterial (41.2%), fungal (39.7%), viral (11.7%) and parasitic (7.4%). Onychomycosis was the commonest infection in group A (25.2%) compared with folliculitis in group B (19.1%). Cutaneous infections in HCV+ patients were more characterized by increased severity, aggressive course, resistance to treatment and rapid relapse. Conclusions: HCV infection has a significant impact in increasing and changing the spectrum of skin infections in diabetic patients. Severe and resistant infections in diabetics could be an important sign of HCV infection

Mobile Target Coverage and Tracking on Drone-Be-Gone UAV Cyber-Physical Testbed

Mobile wireless sensor networks have been extensively deployed for enhancing environmental monitoring and surveillance. The availability of low-cost mobile robots equipped with a variety of sensors makes them promising in target coverage tasks. They are particularly suitable where quick, inexpensive, or nonlasting visual sensing solutions are required. In this paper, we consider the problem of low complexity target tracking to cover and follow moving targets using flying robots. We tackle this problem by clustering targets while estimating the camera location and orientation for each cluster separately through a cover-set coverage method. We also leverage partial knowledge of target mobility to enhance the efficiency of our proposed algorithms. Three computationally efficient approaches are developed: predictive fuzzy, predictive incremental fuzzy, and local incremental fuzzy. The objective is to find a compromise among coverage efficiency, traveled distance, number of drones required, and complexity. The targets move according to one of the following three possible mobility patterns: random waypoint, Manhattan grid, and reference point group mobility patterns. The feasibility of our algorithms and their performance are also tested on a real-world indoor testbed called drone-be-gone, using Parrot AR.Drone quadcopters. The deployment confirms the results obtained with simulations and highlights the suitability of the proposed solutions for real-time applications.Scopu

Role of Cyclooxygenase-2, Ezrin and Matrix metalloproteinase-9 as predictive markers for recurrence of basal cell carcinoma

Context: Recurrence of basal cell carcinoma (BCC) may form a prognostic problem that couldn′t be fully predicted. Although there are different clinical and histologic risk factors for BCC recurrence, few reports are available for the role of biologic markers. Aim: The aim of this study was to assess the value of Cyclooxygenase-2 (COX-2), Ezrin and Matrix metalloproteinase-9 (MMP-9) in recurrence of BCC. Settings and Design: A retrospective controlled study. Materials and Methods: Primary tumors of 22 patients who had recurrent basal cell carcinoma (R-BCC) and 22 matched controls that showed non-recurrent basal cell carcinoma (NR-BCC) were collected. Clinical, histopathological, and immunohistochemical results were recorded and analyzed. Statistical analysis used: SPSS software version 13 and Pearson χ2 test. Results: R-BCC showed COX-2 expression in 20 (90.9%) cases compared to 13 (59.1%) in NR-BCC with a significant difference (P = 0.04). Moderate to strong intensity was recorded in 13 recurrent and two non-recurrent tumors. Higher frequency for Ezrin immunopositivity was noted in R-BCC (72.7%) than NR-BCC (40.9%), but the difference did not reach the level of significance (P = 0.07). Twelve R-BCC and three NR-BCC revealed moderate to strong staining. For MMP-9, there was no statistically significant difference (P = 1) between recurrent cases (63.6%) and controls (68.2%). No correlation was found between marker expressions and clinical or histologic features of R-BCC. Conclusions: Biologic markers may have a promising role in assessment of BCC prognosis and early detection of recurrence. High COX-2 expression could be considered as a risk factor of BCC recurrence that can be added to other clinical and histologic factors