Computational Analysis of the Solid-State and Solvation Properties of Carbamazepine in Relation to its Polymorphism

The solvent-dependent polymorphism of the active pharmaceutical ingredient (API) carbamazepine is interpreted from calculations of the solid-state and API-solvent intermolecular interactions. These simulations suggested that apolar solute-solute interactions could be disrupted by apolar solvents. In contrast, the polar solute-solute interactions were found to be easily disrupted by polar and protic solvents. This is consistent with experimental observations that the crystallization of the metastable form II is more dominant in apolar solvents. The Mercury program remains the gold standard in terms of usability; however, further expansion into more complex simulation techniques could make this package of even greater use in pharmaceutical manufacturing workflows.     

Off-Site Exposure to Respirable Aerosols Produced during the Disk-Incorporation of Class B Biosolids

Field experiments were conducted at a Class B biosolids land application site in central Arizona to measure, model, and source-track the off-site transport of aerosols emitted when biosolids were disk-incorporated into soils. Real-time PM10 monitoring provided time-resolved aerosol information sufficient for verifying both off-site concentration and off-site exposure time model results. Under the conditions considered and at a distance of 165?m from the aerosol source, biosolids disk-incorporation resulted in an intermittent exposure to biosolids-derived aerosol concentration between 15 and 40?μg/m3 and an inhalable biosolids dose between 2 and 8?μg. Transport modeling predicted that these doses will decrease with increasing wind speed. In addition, three DNA sequence-based biosolids source tracking methods were applied to aerosol samples and confirmed the presence of biosolids in aerosols at 5, 65, and 165?m from the aerosol source. Field measurements and modeling indicate that the nature of biosolids-derived aerosol exposure is a series of intermittent high concentration puffs, rather than a continuous low concentration.     

Synergistic Effect of PVDF-Coated PCL-TCP Scaffolds and Pulsed Electromagnetic Field on Osteogenesis

Bone exhibits piezoelectric properties. Thus, electrical stimulations such as pulsed electromagnetic fields (PEMFs) and stimuli-responsive piezoelectric properties of scaffolds have been investigated separately to evaluate their efficacy in supporting osteogenesis. However, current understanding of cells responding under the combined influence of PEMF and piezoelectric properties in scaffolds is still lacking. Therefore, in this study, we fabricated piezoelectric scaffolds by functionalization of polycaprolactone-tricalcium phosphate (PCL-TCP) films with a polyvinylidene fluoride (PVDF) coating that is self-polarized by a modified breath-figure technique. The osteoinductive properties of these PVDF-coated PCL-TCP films on MC3T3-E1 cells were studied under the stimulation of PEMF. Piezoelectric and ferroelectric characterization demonstrated that scaffolds with piezoelectric coefficient d₃₃ = −1.2 pC/N were obtained at a powder dissolution temperature of 100 °C and coating relative humidity (RH) of 56%. DNA quantification showed that cell proliferation was significantly enhanced by PEMF as low as 0.6 mT and 50 Hz. Hydroxyapatite staining showed that cell mineralization was significantly enhanced by incorporation of PVDF coating. Gene expression study showed that the combination of PEMF and PVDF coating promoted late osteogenic gene expression marker most significantly. Collectively, our results suggest that the synergistic effects of PEMF and piezoelectric scaffolds on osteogenesis provide a promising alternative strategy for electrically augmented osteoinduction. The piezoelectric response of PVDF by PEMF, which could provide mechanical strain, is particularly interesting as it could deliver local mechanical stimulation to osteogenic cells using PEMF.     

Photocatalytic mineralisation of organic compounds: a comparison of flame-made TiO2 catalysts

A comparative photocatalytic analysis was carried out on TiO₂ made in a Flame Spray Pyrolysis (FSP) process and flame-made Degussa P25. Both have similar crystallinity, phase composition, phase segregation and a non-porous surface. Hence comparison was made based on their difference in specific surface area, organic adsorption and the amount of OH• generated upon illumination. The photocatalytic activity tests were carried out using the following series of organic compounds: sucrose, glucose, fructose, maleic acid, glyoxylic acid, oxalic acid, isobutyric acid, phenol and methanol. FSP-made TiO₂ outperformed P25 for saccharides mineralisation, while for phenol and methanol mineralisation P25 was better than FSP-made TiO₂. Similar mineralisation rates were observed for both FSP-made and P25 TiO₂ for the mineralisation of carboxylic acids. This shows that the relative performance of the photocatalysts depends on the type of organic compounds to be degraded. The high surface area and possibly a more efficient interfacial charge transfer of FSP-made TiO₂ provided an efficient pathway for saccharides mineralisation. As for phenol and methanol, the mineralisation rates were higher when using P25 due to the greater amount of OH• radicals generated by this photocatalyst. The fast mineralisation rates of carboxylic acids made degradation of these organic compounds to be less affected by the TiO₂ photocatalyst properties and conditions tested in this work.     

YCl_3－AECl_2（AE＝Mg，Ca，Sr，Ba）二元相图的研究

用差热分析法测定了ＹＣｌ_３一ＳｒＣｌ_２体系二元相图，并用Ｘ时线衍射法验证了该二元体系中新相的生成。使用ＣＡＬＰＨＡＤ技术评估和优化了ＹＣｌ_３一ＡＥＣｌ_２（ＡＥ＝Ｍｇ，Ｃａ，Ｓｒ，Ｂａ）系列四个二元相图和热力学性质，取得了热力学性质和相图自相一致的结果。     

Object tracking based on an online learning network with total error rate minimization

This paper presents a visual object tracking system which is tolerant to external imaging factors such as illumination, scale, rotation, occlusion and background changes. Specifically, an integration of an online version of total-error-rate minimization based projection network with an observation model of particle filter is proposed to effectively distinguish between the target object and the background. A re-weighting technique is proposed to stabilize the sampling of particle filter for stochastic propagation. For self-adaptation, an automatic updating scheme and extraction of training samples are proposed to adjust to system changes online. Our qualitative and quantitative experiments on 16 public video sequences show convincing performances in terms of tracking accuracy and computational efficiency over competing state-of-the-art algorithms.     

Cancellable biometrics and annotations on BioHash

Lately, the once powerful one-factor authentication which is based solely on either password, token or biometric approach, appears to be insufficient in addressing the challenges of identity frauds. For example, the sole biometric approach suffers from the privacy invasion and non-revocable issues. Passwords and tokens are easily forgotten and lost. To address these issues, the notion of cancellable biometrics was introduced to denote biometric templates that can be cancelled and replaced with the inclusion of another independent authentication factor. BioHash is a form of cancellable biometrics which mixes a set of user-specific random vectors with biometric features. In verification setting, BioHash is able to deliver extremely low error rates as compared to the sole biometric approach when a genuine token is used. However, this raises the possibility of two identity theft scenarios: (i) stolen-biometrics, in which an impostor possesses intercepted biometric data of sufficient high quality to be considered genuine and (ii) stolen-token, in which an impostor has access to the genuine token and used by the impostor to claim as the genuine user. We found that the recognition rate for the latter case is poorer. In this paper, the quantised random projection ensemble based on the Johnson–Lindenstrauss Lemma is used to establish the mathematical foundation of BioHash. Based on this model, we elucidate the characteristics of BioHash in pattern recognition as well as security view points and propose new methods to rectify the stolen-token problem.     

MXene Functionalized,Highly Breathable and Sensitive Pressure Sensors with Multi-Layered Porous Structure

Breathable, flexible, and highly sensitive pressure sensors have drawn increasing attention due to their potential in wearable electronics for body-motion monitoring, human-machine interfaces, etc. However, current pressure sensors are usually assembled with polymer substrates or encapsulation layers, thus causing discomfort during wearing (i.e., low air/vapor permeability, mechanical mismatch) and restricting their applications. A breathable and flexible pressure sensor is reported with nonwoven fabrics as both the electrode (printed with MXene interdigitated electrode) and sensing (coated with MXene/silver nanowires) layers via a scalable screen-printing approach. Benefiting from the multi-layered porous structure, the sensor demonstrates good air permeability with high sensitivity (770.86–1434.89 kPa⁻¹), a wide sensing range (0–100 kPa), fast response/recovery time (70/81 ms), and low detection limit (≈1 Pa). Particularly, this sensor can detect full-scale human motion (i.e., small-scale pulse beating and large-scale walking/running) with high sensitivity, excellent cycling stability, and puncture resistance. Additionally, the sensing layer of the pressure sensor also displays superior sensitivity to humidity changes, which is verified by successfully monitoring human breathing and spoken words while wearing a sensor-embedded mask. Given the outstanding features, this breathable sensor shows promise in the wearable electronic field for body health monitoring, sports activity detection, and disease diagnosis.     

Characterisation of sol–gel method synthesised MgZnFe2 O4 nanoparticles and its cytotoxic effects on breast cancer cell line,MDA MB‐231 in vitro

In this study, nanocrystalline magnesium zinc ferrite nanoparticles were successfully prepared by a simple sol–gel method using copper nitrate and ferric nitrate as raw materials. The calcined samples were characterised by differential thermal analysis/thermogravimetric analysis, Fourier transform infrared spectroscopy and X‐ray diffraction. Transmission electron microscopy revealed that the average particle size of the calcined sample was in a range of 17–41 nm with an average of 29 nm and has spherical size. A cytotoxicity test was performed on human breast cancer cells (MDA MB‐231) and (MCF‐7) at various concentrations starting from (0 µg/ml) to (800 µg/ml). The sample possessed a mild toxic effect toward MDA MB‐231 and MCF‐7 after being examined with MTT (3‐[4, 5‐dimethylthiazol‐2‐yl]‐2, 5 diphenyltetrazolium bromide) assay for up to 72 h of incubation. Higher reduction of cells viability was observed as the concentration of sample was increased in MDA MB‐231 cell line than in MCF‐7. Therefore, further cytotoxicity tests were performed on MDA MB‐231 cell line.Inspec keywords: sol‐gel processing, nanoparticles, nanofabrication, magnesium compounds, zinc compounds, toxicology, biological organs, cancer, cellular biophysics, nanomedicine, calcination, differential thermal analysis, Fourier transform infrared spectra, X‐ray diffraction, transmission electron microscopy, particle size, organic compoundsOther keywords: sol‐gel method, cytotoxic effects, breast cancer cell line, MDA MB‐231 in vitro, nanocrystalline magnesium zinc ferrite nanoparticles, copper nitrate, ferric nitrate, raw materials, calcined samples, differential thermal analysis, thermogravimetric analysis, Fourier transform infrared spectroscopy, X‐ray diffraction, transmission electron microscopy, average particle size, cytotoxicity testing, human breast cancer cells, mild toxic effect, 3‐[4,5‐dimethylthiazol‐2‐yl]‐2,5 diphenyltetrazolium bromide) assay, cell viability, MCF‐7, MDA MB‐231 cell line, size 17 nm to 41 nm     

Classification of focal and nonfocal EEG signals using ANFIS classifier for epilepsy detection

The electroencephalogram (EEG) is the frequently used signal to detect epileptic seizures in the brain. For a successful epilepsy surgery, it is very essential to localize epileptogenic area in the brain. The signals from the epileptogenic area are focal signals and signals from other area of the brain region nonfocal signals. Hence, the classification of focal and nonfocal signals is important for locating the epileptogenic area for epilepsy surgery. In this article, we present a computer aided automatic detection and classification method for focal and nonfocal EEG signal. The EEG signal is decomposed by Dual Tree Complex Wavelet Transform (DT‐CWT) and the features are computed from the decomposed coefficients. These features are trained and classified using Adaptive Neuro Fuzzy Inference System (ANFIS) classifier. The proposed system achieves 98% sensitivity, 100% specificity, and 99% accuracy for EEG signal classification. The experimental results are presented to show the effectiveness of the proposed classification method to classify the focal and nonfocal EEG signals. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 277–283, 2016