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The objective of this study was to explore an innovative sustained release technology and design a new microporous resin-based polymer device (RPD) for controlled release of glipizide (GZ). Photocurable resin was applied to prepare the resin layer to control GZ release. The impact of formulation parameters consisting of the type and amount of pore formers and pH modifiers, photocurable curing time as well as the weight of resin layer on GZ release were examined. The GZ-RPD was fabricated applying 24 mg of resin layer with PEG400 (100 % of the resin weight) as pore former and 10 mg of Na

Accurate prediction of the large-scale channel fading is fundamental to planning and optimization in 5G millimeter-wave cellular networks. The current prediction methods, which are either too computationally expensive or inaccurate, are unsuitable for city-scale cell planning and optimization. This paper presents FadeNet, a convolutional neural-network enabled alternative for predicting large-scale fading with high computation speed and accuracy. By using carefully designed input features and neural-network architecture to capture topographical information, FadeNet accurately predicts the large-scale fading from a base station to each location in its coverage area. Evaluations on realistic data, derived from millimeter-wave cells across multiple cities, suggest that FadeNet can achieve a prediction accuracy of 5.6 decibels in root mean square error. In addition, by leveraging the parallel processing capabilities of a graphics processing unit, FadeNet can reduce the prediction time by $40X-1000X$ in comparison to industry prevalent methods like ray-tracing. Generalizations of FadeNet, that can handle variable topographies and base station heights, and its use for optimal cell site selection are also explored.

In this paper, we consider the problem of quickly detecting an abrupt change in linear regression models. Specifically, an observer sequentially obtains a sequence of observations, whose underlying linear model changes at an unknown time. Moreover, the pre-change linear model is perfectly known by the observer but the post-change linear model is unknown. The observer aims to design an efficient online algorithm to detect the presence of the change via his sequential observations. Based on different assumptions on the change-point, both non-Bayesian and Bayesian problem formulations are considered. In the non-Bayesian setting, the change-point is modeled as a fixed but unknown constant. Two performance metrics, namely the worst case detection delay and the average run length to false alarm, are adopted to evaluate the performance of detection algorithms. In the Bayesian setting, the change-point is modeled as a geometrically distributed random variable. For this case, the average detection delay and the probability of false alarm are used as performance metrics. We propose a novel algorithm, namely the parallel-sum algorithm, for the purpose of change detection. For both setups, we show that the proposed algorithm has a low computational complexity while still offering a good performance in terms of the performance metrics of the respective setting.

In this paper, we report an experimental observation of the large anomalous Hall effect (AHE) in a hexagonal ferromagnetic $\mathrm{F}{\mathrm{e}}_{5}\mathrm{S}{\mathrm{n}}_{3}$ single crystal with current along the $b$ axis and a magnetic field normal to the $bc$ plane. The intrinsic contribution of the anomalous Hall conductance ${\ensuremath{\sigma}}_{AH}^{\mathrm{int}}$ was approximately $613\phantom{\rule{0.16em}{0ex}}{\mathrm{\ensuremath{\Omega}}}^{\ensuremath{-}1}\phantom{\rule{0.16em}{0ex}}\mathrm{c}{\mathrm{m}}^{\ensuremath{-}1}$, which was more than 3 times the maximum value in the frustrated kagome magnet $\mathrm{F}{\mathrm{e}}_{3}\mathrm{S}{\mathrm{n}}_{2}$ and nearly independent of the temperature over a wide range between 5 and 350 K. The analysis results revealed that the large AHE was dominated by a common, intrinsic term, while the extrinsic contribution, i.e., the skew scattering and side jump, turned out to be small. In addition to the large AHE, it was found that the types of majority carriers changed at approximately 275 and 30 K, consistent with the critical temperatures of the spin reorientation. These findings suggest that the hexagonal ferromagnetic $\mathrm{F}{\mathrm{e}}_{5}\mathrm{S}{\mathrm{n}}_{3}$ single crystal is an excellent candidate to use for the study of the topological features in ferromagnets.

Soybean protein powders obtained by aqueous buffer and reverse micelle extractions were examined and characterized using X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and scanning electron microscopy (SEM). These analysis methods provided detailed information about elemental distributions, surface structure, and secondary and microstructures of the protein, respectively. XPS data revealed that the O and N atomic percentages of soybean protein surfaces obtained with bis(2-ethylhexyl) sodium sulfosuccinate (AOT)/hexane reverse micelles were higher than those obtained with aqueous buffer, whereas the percentage of atomic C was lower. The ratios of nitrogen to carbon (N/C) on the surface of soybean protein obtained through the two extraction methods were similar. The O/C ratio for soybean protein obtained from AOT reverse micelles was large. The obtained results indicated that the reverse micelles could affect the C, O, and N components on the surface of soybean proteins. Moreover, XRD and SEM results also showed the influence of AOT reverse micelles, which lead to more β-sheet and pore structures.

We consider linear regression problems for which the underlying model undergoes multiple changes. Our goal is to estimate the number and locations of change-points that segment available data into different regions, and further produce sparse and interpretable models for each region. To address challenges of the existing approaches and to produce interpretable models, we propose a sparse group Lasso based approach for linear regression problems with change-points. Under certain mild assumptions and a properly chosen regularization term, we prove that the solution of the proposed approach is asymptotically consistent. In particular, we show that the estimation error of linear coefficients diminishes, and the locations of the estimated change-points are close to those of true change-points. We further propose a method to choose the regularization term so that the results mentioned above hold. In addition, we show that the complexity of the proposed algorithm is much smaller than those of existing approaches. Numerical examples are provided to validate the analytical results.

Here we introduce lattice defects in WTe2 by Ga+ implantation (GI), and study the effects of defects on the transport properties and electronic structures of the samples. Theoretical calculation shows that Te Frenkel defects is the dominant defect type, and Raman characterization results agree with this. Electrical transport measurements show that, after GI, significant changes are observed in magnetoresistance and Hall resistance. The classical two-band model analysis shows that both electron and hole concentration are significantly reduced. According to the calculated results, ion implantation leads to significant changes in the band structure and the Fermi surface of the WTe2. Our results indicate that defect engineering is an effective route of controlling the electronic properties of WTe2 devices.

The aim of this study was to investigate the ability of mesoporous bioactive glass with ordered nanopores (80S MBG) to adsorb and provide the delayed release of 125I-tagged bone morphogenetic protein-2 (BMP-2). A 50 mg piece of 80S MBG was produced, which comprised SiO2, CaO and P2O5 in a component molar ratio of 80:15:5. Each MBG piece adsorbed 30 μg 125I-BMP-2. Persistent radioactivity in the MBG was periodically measured in simulated body fluid. The total amount of BMP-2 released and the mean amount released per day were calculated. A delayed release curve of BMP-2 was constructed. SPSS 15.0 software was used to perform a statistical analysis. The amount of BMP-2 released in the first two days was one-quarter of the total load. A line equation, y = 490.55×1/2 + 7268.82, was obtained from the square root of protein release doses value at 3–94 days. The total amount of BMP-2 released over 94 days was 11.894 μg, which was ~39.6% of the total load. The half-life of the release time was 248 days. From the second week, the rate of BMP release had stabilized to a mean of 37.42±18.67 ng/day and the difference of the mean amount released per day had no statistical significance (P>0.05). High adsorption and delayed release effects of BMP-2 were observed in 80S MBG. The delayed release conforms to the Higuchi equation, which indicates possible applications in promoting bone healing.

Characterizing the phase transitions of convex optimizations in recovering structured signals or data is of central importance in compressed sensing, machine learning and statistics. The phase transitions of many convex optimization signal recovery methods such as $\ell_1$ minimization and nuclear norm minimization are well understood through recent years' research. However, rigorously characterizing the phase transition of total variation (TV) minimization in recovering sparse-gradient signal is still open. In this paper, we fully characterize the phase transition curve of the TV minimization. Our proof builds on Donoho, Johnstone and Montanari's conjectured phase transition curve for the TV approximate message passing algorithm (AMP), together with the linkage between the minmax Mean Square Error of a denoising problem and the high-dimensional convex geometry for TV minimization., Comment: 6 pages

The aim of this study was to investigate the ability of mesoporous bioactive glass with ordered nanopores (80S MBG) to adsorb and provide the delayed release of 125I-tagged bone morphogenetic protein-2 (BMP-2). A 50 mg piece of 80S MBG was produced, which comprised SiO2, CaO and P2O5 in a component molar ratio of 80:15:5. Each MBG piece adsorbed 30 μg 125I-BMP-2. Persistent radioactivity in the MBG was periodically measured in simulated body fluid. The total amount of BMP-2 released and the mean amount released per day were calculated. A delayed release curve of BMP-2 was constructed. SPSS 15.0 software was used to perform a statistical analysis. The amount of BMP-2 released in the first two days was one-quarter of the total load. A line equation, y = 490.55×1/2 + 7268.82, was obtained from the square root of protein release doses value at 3–94 days. The total amount of BMP-2 released over 94 days was 11.894 μg, which was ~39.6% of the total load. The half-life of the release time was 248 days. From the second week, the rate of BMP release had stabilized to a mean of 37.42±18.67 ng/day and the difference of the mean amount released per day had no statistical significance (P>0.05). High adsorption and delayed release effects of BMP-2 were observed in 80S MBG. The delayed release conforms to the Higuchi equation, which indicates possible applications in promoting bone healing.

Magnesium phosphate cement (MPC) is a kind of novel biodegradable bone adhesive for its distinct performance. However, there is few research work concerning on the systemic biocompatibility and genetic toxicological evaluation of MPC. In this study, the investigation on the inherited toxicology of MPC including gene mutation assay (Ames test), chromosome aberration assay (micronucleus test), and DNA damage assay (unscheduled DNA synthesis test) were carried out. Fracture healing and degradation behavior were explored for the evaluation of the biocompatibility of MPC, using macroscopical histological, histomorphometrical, and scanning electron microscopical methods. The results of mutagenicity and potential carcinogenicity of MPC extracts were negative, and the animal implantation illustrated no toxicity and good resorption. The study suggested that bioresorbable MPC was safe for application and might have potential applications for physiological fracture fixation.

Background Risk factors for delirium following cardiac surgery are incompletely understood. The aim of this study was to investigate whether intra-operative pathophysiological alterations and therapeutic interventions influence the risk of post-operative delirium. Methods This retrospective cohort study was performed in a 12-bed cardiosurgical intensive care unit (ICU) of a university hospital and included patients consecutively admitted after cardiac surgery during a 2-month period. The diagnosis of delirium was made clinically using validated scores. Comparisons between patients with and without delirium were performed with non-parametric tests. Logistic regression was applied to identify independent risk factors. Results are given as number (percent) or median (range). Results Of the 194 consecutive post-cardiac surgery patients, 50 (26 %) developed delirium during their ICU stay. Univariate analysis revealed that significant differences between patients with and without delirium occurred in the following intra-operative variables: duration of cardiopulmonary bypass (184 [72–299] vs 113 (37–717) minutes, p