This paper proposes a biometric-based user authentication protocol for wireless sensor networks (WSN) when a user wants to access data from sensor nodes, since WSN are often deployed in an unattended environment. The protocol employs biometric keys and resists the threats of stolen verifier, of which many are logged-in users with the same login identity, guessing, replay, and impersonation. The protocol uses only Hash function and saves the computational cost, the communication cost, and the energy cost. In addition, the user's password can be changed freely using the proposed protocol.

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BackgroundTo study the rules that apparent diffusion coefficient (ADC) changes with time and space in cerebral infarction, and to provide the evidence in defining the infarction stages.Methods117 work-ups in 98 patients with cerebral infarction (12 hyperacute, 43 acute, 29 subacute, 10 steady, and 23 chronic infarctions) were imaged with both conventional MRI and diffusion weighted imaging. The average ADC values, the relative ADC (rADC) values, and the ADC values or rADC values from the center to the periphery of the lesion were calculated.ResultsThe average ADC values and the rADC values of hyperacute and acute infarction lesion depressed obviously. rADC values in hyperacute and acute stage was minimized, and increased progressively as time passed and appeared as "pseudonormal" values in approximately 8 to 14 days. Thereafter, rADC values became greater than normal in chronic stage. There was positive correlation between rADC values and time (P < 0.01). The ADC values and the rADC values in hyperacute and acute lesions had gradient signs that these lesions increased from the center to the periphery. The ADC values and the rADC values in subacute lesions had adverse gradient signs that these lesions decreased from the center to the periphery.ConclusionThe ADC values of infarction lesions have evolution rules with time and space. The evolution rules with time and those in space can be helpful to decide the clinical stage, and to provide the evidence in guiding the treatment or judging the prognosis in infarction.

The present study seeks to observe the preventive effects of doxorubicin-induced cardiomyopathy (DOX-CM) in rats using targeted non-mitogenic acidic fibroblast growth factor (MaFGF) mediated by nanoparticles (NP) combined with ultrasound-targeted MB destruction (UTMD). DOX-CM rats were induced by intraperitoneally injected doxorubicin. Six weeks after intervention, the indices from the transthoracic echocardiography and velocity vector imaging showed that the left ventricular function in the MaFGF-loaded NP (MaFGF-NP) + UTMD group was significantly improved compared with the DOX-CM group. The increased malondialdehyde and decreased superoxide dismutase were observed in the DOX-CM group, while a significant increase in superoxide dismutase and a decrease in malondialdehyde were detected in the groups treated with MaFGF-NP + UTMD. From the Masson staining, the MaFGF-NP + UTMD group showed a significant difference from the DOX-CM group. The cardiac collagen volume fraction and the ratio of the perivascular collagen area to the luminal area number of terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick end labelling positive cells in the MaFGF-NP + UTMD group decreased to 8.9%, 0.55-fold, compared with the DOX-CM group (26.5%, 1.7-fold). From terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick end labelling staining, the results showed the strongest inhibition of apoptosis progress in MaFGF-NP + UTMD group. The immunohistochemical staining of the TGF-β1 in MaFGF-NP + UTMD group reached 3.6%, which was much lower than that of the DOX-CM group (12.6%). These results confirmed that the abnormalities, including left ventricular dysfunction, myocardial fibrosis, cardiomyocytes apoptosis and oxidative stress, could be suppressed by twice weekly MaFGF treatments for 6 consecutive weeks (free MaFGF or MaFGF-NP+/UTMD), with the strongest improvements observed in the MaFGF-NP + UTMD group. Western blot analyses of the heart tissue further revealed the highest pAkt levels, highest anti-apoptosis protein (Bcl-2) levels and strongest reduction in proapoptosis protein (Bax) levels in the MaFGF-NP + UTMD group. This study confirmed the preventive effects of DOX-CM in the rats with MaFGF-NP and UTMD by retarding myocardial fibrosis, inhibiting oxidative stress, and decreasing cardiomyocyte apoptosis.

In general, SO appeared as a smooth marginated multicystic mass with a high attenuation lesion on precontrast scans on CT scans, and signal intensities on T1-weighted images were partly intermediate to high, or high, and those on T2-weighted images were low. The CT and MRI characteristic findings of SO might be of great value for the diagnosis.

Abstract:We present a new external-beam radiation therapy system using very-high-energy (VHE) electron/photon beams generated by a centimeter-scale laser plasma accelerator built in a robotic system. Most types of external-beam radiation therapy are delivered using a machine called a medical linear accelerator driven by radio frequency (RF) power amplifiers, producing electron beams with an energy range of 6-20 MeV, in conjunction with modern radiation therapy technologies for effective shaping of three-dimensional dose distributions and spatially accurate dose delivery with imaging verification. However, the limited penetration depth and low quality of the transverse penumbra at such electron beams delivered from the present RF linear accelerators prevent the implementation of advanced modalities in current cancer treatments. These drawbacks can be overcome if the electron energy is increased to above 50 MeV. To overcome the disadvantages of the present RF-based medical accelerators, harnessing recent advancement of laser-driven plasma accelerators capable of producing 1-GeV electron beams in a 1-cm gas cell, we OPEN ACCESSAppl. Sci. 2015, 5 2 propose a new embodiment of the external-beam radiation therapy robotic system delivering very high-energy electron/photon beams with an energy of 50-250 MeV; it is more compact, less expensive, and has a simpler operation and higher performance in comparison with the current radiation therapy system.

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We address the problem of learning to control an unknown linear dynamical system with time varying cost functions through the framework of online Receding Horizon Control (RHC). We consider the setting where the control algorithm does not know the true system model and has only access to a fixedlength (that does not grow with the control horizon) preview of the future cost functions. We characterize the performance of an algorithm using the metric of dynamic regret, which is defined as the difference between the cumulative cost incurred by the algorithm and that of the best sequence of actions in hindsight. We propose two different online RHC algorithms to address this problem, namely Certainty Equivalence RHC (CE-RHC) algorithm and Optimistic RHC (O-RHC) algorithm. We show that under the standard stability assumption for the model estimate, the CE-RHC algorithm achieves O(T 2/3 ) dynamic regret. We then extend this result to the setting where the stability assumption hold only for the true system model by proposing the O-RHC algorithm. We show that O-RHC algorithm achieves O(T 2/3 ) dynamic regret but with some additional computation.