Markov logic networks for adverse drug event extraction from text

Adverse drug events (ADEs) are a major concern and point of emphasis for the medical profession, government, and society. A diverse set of techniques from epidemiology, statistics, and computer science are being proposed and studied for ADE discovery from observational health data (e.g., EHR and claims data), social network data (e.g., Google and Twitter posts), and other information sources. Methodologies are needed for evaluating, quantitatively measuring and comparing the ability of these various approaches to accurately discover ADEs. This work is motivated by the observation that text sources such as the Medline/Medinfo library provide a wealth of information on human health. Unfortunately, ADEs often result from unexpected interactions, and the connection between conditions and drugs is not explicit in these sources. Thus, in this work, we address the question of whether we can quantitatively estimate relationships between drugs and conditions from the medical literature. This paper proposes and studies a state-of-the-art NLP-based extraction of ADEs from text.     

Polycondensation of structurally divergent tetraamine monomers with dicarboxylic acids to synthesize polybenzimidazole copolymers for polymer electrolyte membranes

In our effort to promote 2,6‐bis(3,4‐diaminophenyl)‐4‐phenylpyridine (Py‐TAB) as an alternative tetraamine monomer to conventionally used 3,3′,4,4′‐tetraaminobiphenyl (TAB) for synthesizing readily processable pyridine bridged polybenzimidazoles (Py‐PBIs), two series of random copolymers (PBI‐co‐Py‐PBI) were synthesized by polymerizing Py‐TAB and TAB with isophthalic acid or terephthalic acid to produce meta (mPBI‐co‐mPy‐PBI) and para (pPBI‐co‐pPy‐PBI) connected copolymers, respectively. For the first time in the PBI literature, copolymers were synthesized by varying the relative compositions of tetraamines (TAB and Py‐TAB) in the polymerization feed with a single dicarboxylic acid (DCA) instead of the traditionally used method where two DCAs with variable compositions were polymerized with a single tetraamine. The solubility and hence the processability of the copolymers were improved significantly upon introduction of Py‐PBI in the copolymer. The detailed characterizations of both meta and para series copolymers compellingly established that thermal, chemical and mechanical stabilities can be easily modulated according to need by altering the relative compositions of PBI and Py‐PBI. The phosphoric acid (PA) loading of the copolymers increased gradually with increasing Py‐PBI content since the bulky pyridine moiety facilitated the absorption of PA. The presence of pyridine functionality and a larger PA loading caused a higher proton conductivity of PA doped copolymer membranes. © 2014 Society of Chemical Industry     

Statistical characterization of Rician multipath effects in a mobile-to-mobile communication channel

A statistical model is developed for a narrowband mobile-to-mobile channel taking into consideration Rician scattering near receiving and transmitting antennas both individually and concomitantly. From the proposed channel model we obtain the probability density function of the received signal envelope, the time correlation function and RF spectrum of the received signal, and level crossing rates and average fade durations. We briefly discuss the impact of these parameters on communication networks supporting an intelligent vehicle highway system (IVHS).     

基于余弦平顶窗的谐波相量测量

In this paper, a Backstepping Global Integral Terminal Sliding Mode Controller (BGITSMC) with the view to enhancing the dynamic stability of a hybrid AC/DC microgrid has been presented. The proposed approach controls the switching signals of the inverter, interlinking the DC-bus with the AC-bus in an AC/DC microgrid for a seamless interface and regulation of the output power of renewable energy sources (Solar Photovoltaic unit, PMSG-based wind farm), and Battery Energy Storage System. The proposed control approach guarantees the dynamic stability of a hybrid AC/DC microgrid by regulating the associated states of the microgrid system to their intended values. The dynamic stability of the microgrid system with the proposed control law has been proved using the Control Lyapunov Function. A simulation analysis was performed on a test hybrid AC/DC microgrid system to demonstrate the performance of the proposed control strategy in terms of maintaining power balance while the system’s operating point changed. Furthermore, the superiority of the proposed approach has been demonstrated by comparing its performance with the existing Sliding Mode Control (SMC) approach for a hybrid AC/DC microgrid.     

Robust analysis for improvement of vowel onset point detection under noisy conditions

Vowel onset point (VOP) is the instant of time at which the vowel region starts in a speech signal. The VOPs are used as anchor points to design various speech based systems. Different algorithms exist in the literature to identify the occurrences of vowels in continuous spoken utterances. The algorithm based on combined evidences derived from source excitation, spectral peaks and modulation spectrum have been used as a baseline system for the present study. The baseline system provides a satisfactory level of performance under clean data condition. However under noisy data condition the performance of the previous system may be improved further by additional pre-processing of the raw speech data and post-processing the detected VOPs. In this paper we propose to use the speech enhancement techniques as pre-processing module to remove the noise from the speech data under different noisy conditions. The pre-processed speech data is then passed through the baseline system to detect the VOPs. It has been observed that there exist several spurious VOPs at the output of the baseline system. We propose to use a post-processing module based on average signal-to-noise ratio and information derived from the glottal closure instant to remove the spurious VOPs. The experiments were carried out on clean, artificially injected noisy, and data collected from the practical noisy environments. The results suggest that the proposed system using pre-processing and post-processing modules is robust and shows an improvement of 28–35 % over the existing baseline system by removing the spurious VOPs under different noisy conditions.     

Controlled release tablet formulation containing natural Δ9-tetrahydrocannabinol

Cannabinoids are increasingly being used in the treatment of chemotherapy-induced nausea and vomiting (CINV) because of their action on the cannabinoid receptors, CB1 and CB2. The currently marketed capsule formulations (sesame oil based and crystalline powder) are required to be administered frequently to maintain therapeutic levels, which leads to non-compliance. In the present study, oral controlled release tablet formulations of Δ⁹-tetrahydrocannabinol (THC) were prepared using the lipids Precirol® and Compritol®. Release profiles using THC-lipid matrices and/or with the lipids in the external phase (blend) were evaluated. The effect of directly compressible diluents lactose mixture (Ludipress®), dicalcium phosphate anhydrous (Emcompress®) and microcrystalline cellulose (Avicel® 102) on tablet characteristics and in vitro drug release was also investigated. Further, in vitro THC release in the presence of a lipase inhibitor, Pluronic® F68, was also studied. A 24 h zero-order THC release profile was obtained with a combination of Precirol® and Compritol® in the compression blend. Addition of Pluronic® F68 did not alter THC release in vitro. These optimized tablets were chemically and physically stable for 3 months, the last time point tested, at 25?°C/60% RH. The overall results demonstrate the feasibility of preparing oral THC tablets for once a day administration which can improve CINV management.     

3D Printing of Textiles: Potential Roadmap to Printing with Fibers

3D printing (3DP) has transformed engineering, manufacturing, and the use of advanced materials due to its ability to produce objects from a variety of materials, ranging from soft polymers to rigid ceramics. 3DP offers the advantage of being able to print at a variety of lengths scales; from a few micrometers to many meters. 3DP has the unique ability to produce customized small lots, efficiently. Yet, one crucial industry that has not been able to adequately explore its potential is textile manufacturing. The research in 3DP of textiles has lagged behind other areas primarily due to the difficulty in obtaining some of the unique characteristics of strength, flexibility, etc., of textiles, utilizing a fundamentally different manufacturing technology. Textiles are their own class of materials due to the specific structural developments that occur during the various stages of textile manufacturing: from fiber extrusion to assembly of the fibers to fabrics. Here, the current 3DP technologies are reviewed with emphasis on soft and anisotropic structures, as well as the efforts toward 3DP of textiles. Finally, a potential pathway to 3DP of textiles, dubbed as printing with fibers to create textile structures is proposed for further exploration.     

ADSORPTION OF WATER VAPOR ON MOLECULAR SIEVE 13X

Adsorption isotherms of water vapor on molecular sieve 13X were obtained at 288, 298, and 308 K. The isotherms were of Type 1 and exhibited hysteresis upon desorption. The heat of adsorption data indicated that water was held on the surface by physical forces and the molecular sieve 13X provided a heterogeneous surface for the water vapor. The equilibrium data were correlated by the Polanyi potential theory and the theory of the pore volume filling proposed by Dubinin and co-workers.