Qualitative characterization of healthcare wastes

The biological hazard inherent in the clinical wastes should be considered during the management and treatment process as well as the disposal into the environment. In this chapter, the risks associated with the clinical wastes as well as the management of these wastes are discussed. The chapter focused on reviewing the types of healthcare wastes generated from hospitals and clinics as well as the regulations and management practices used for these wastes. Moreover, the health risk associated with the infectious agents which have the potential to be transmitted into the environment. It has appeared that the clinical wastes represent real hazards for the human health and the environment if they were not managed properly

Sensor Fabrication Method for in Situ Temperature and Humidity Monitoring of Light Emitting Diodes

In this work micro temperature and humidity sensors are fabricated to measure the junction temperature and humidity of light emitting diodes (LED). The junction temperature is frequently measured using thermal resistance measurement technology. The weakness of this method is that the timing of data capture is not regulated by any standard. This investigation develops a device that can stably and continually measure temperature and humidity. The device is light-weight and can monitor junction temperature and humidity in real time. Using micro-electro-mechanical systems (MEMS), this study minimizes the size of the micro temperature and humidity sensors, which are constructed on a stainless steel foil substrate (40 μm-thick SS-304). The micro temperature and humidity sensors can be fixed between the LED chip and frame. The sensitivities of the micro temperature and humidity sensors are 0.06 ± 0.005 (Ω/°C) and 0.033 pF/%RH, respectively

Hybrid context enriched deep learning model for fine-grained sentiment analysis in textual and visual semiotic modality social data

Detecting sentiments in natural language is tricky even for humans, making its automated detection more complicated. This research proffers a hybrid deep learning model for fine-grained sentiment prediction in real-time multimodal data. It reinforces the strengths of deep learning nets in combination to machine learning to deal with two specific semiotic systems, namely the textual (written text) and visual (still images) and their combination within the online content using decision level multimodal fusion. The proposed contextual ConvNet-SVMBoVW model, has four modules, namely, the discretization, text analytics, image analytics, and decision module. The input to the model is multimodal text, m ε {text, image, info-graphic}. The discretization module uses Google Lens to separate the text from the image, which is then processed as discrete entities and sent to the respective text analytics and image analytics modules. Text analytics module determines the sentiment using a hybrid of a convolution neural network (ConvNet) enriched with the contextual semantics of SentiCircle. An aggregation scheme is introduced to compute the hybrid polarity. A support vector machine (SVM) classifier trained using bag-of-visual-words (BoVW) for predicting the visual content sentiment. A Boolean decision module with a logical OR operation is augmented to the architecture which validates and categorizes the output on the basis of five fine-grained sentiment categories (truth values), namely ‘highly positive,’ ‘positive,’ ‘neutral,’ ‘negative’ and ‘highly negative.’ The accuracy achieved by the proposed model is nearly 91% which is an improvement over the accuracy obtained by the text and image modules individually

Multi-Segment Foam Flow Field in Ambient Pressure Polymer Exchange Membrane Fuel Cell

In order to produce low-cost flow field plates for polymer electrolyte membrane fuel cells, we used nickel foam in this study rather than conventional flow field. Nickel foam has high electron conductivity, thermal conductivity, and mechanical strength. Electrochemical impedance spectrum analysis is carried out to evidence the use on flow field plates of nickel foam. From the impedance fitting results, the nickel foam cases showed the lower contact resistance than the serpentine. However, such plates have poor performance at low temperatures and ambient pressure. In order to overcome this, a multi-segment foam flow field is designed in this study. This increased the performance of the polarization curve by 70% from 162 to 275.5 mw cm-2 than the original nickel foam design. Also, the mass transfer resistance was reduced, and the Warburg impedance value of the operation voltage decreased by 0.4 V. The numerical analysis results demonstrate that increased segment numbers can increase the performance of the multi-segment foam flow field

Warped Riemannian metrics for location-scale models

The present paper shows that warped Riemannian metrics, a class of Riemannian metrics which play a prominent role in Riemannian geometry, are also of fundamental importance in information geometry. Precisely, the paper features a new theorem, which states that the Rao-Fisher information metric of any location-scale model, defined on a Riemannian manifold, is a warped Riemannian metric, whenever this model is invariant under the action of some Lie group. This theorem is a valuable tool in finding the expression of the Rao-Fisher information metric of location-scale models defined on high-dimensional Riemannian manifolds. Indeed, a warped Riemannian metric is fully determined by only two functions of a single variable, irrespective of the dimension of the underlying Riemannian manifold. Starting from this theorem, several original contributions are made. The expression of the Rao-Fisher information metric of the Riemannian Gaussian model is provided, for the first time in the literature. A generalised definition of the Mahalanobis distance is introduced, which is applicable to any location-scale model defined on a Riemannian manifold. The solution of the geodesic equation is obtained, for any Rao-Fisher information metric defined in terms of warped Riemannian metrics. Finally, using a mixture of analytical and numerical computations, it is shown that the parameter space of the von Mises-Fisher model of $n$-dimensional directional data, when equipped with its Rao-Fisher information metric, becomes a Hadamard manifold, a simply-connected complete Riemannian manifold of negative sectional curvature, for $n = 2,\ldots,8$. Hopefully, in upcoming work, this will be proved for any value of $n$.Comment: first version, before submissio

Characterization of MHz pulse repetition rate femtosecond laser-irradiated gold-coated silicon surfaces

In this study, MHz pulse repetition rate femtosecond laser-irradiated gold-coated silicon surfaces under ambient condition were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction analysis (XRD), and X-ray photoelectron spectroscopy (XPS). The radiation fluence used was 0.5 J/cm2 at a pulse repetition rate of 25 MHz with 1 ms interaction time. SEM analysis of the irradiated surfaces showed self-assembled intermingled weblike nanofibrous structure in and around the laser-irradiated spots. Further TEM investigation on this nanostructure revealed that the nanofibrous structure is formed due to aggregation of Au-Si/Si nanoparticles. The XRD peaks at 32.2°, 39.7°, and 62.5° were identified as (200), (211), and (321) reflections, respectively, corresponding to gold silicide. In addition, the observed chemical shift of Au 4f and Si 2p lines in XPS spectrum of the irradiated surface illustrated the presence of gold silicide at the irradiated surface. The generation of Si/Au-Si alloy fibrous nanoparticles aggregate is explained by the nucleation and subsequent condensation of vapor in the plasma plume during irradiation and expulsion of molten material due to high plasma pressure

Fully gapped topological surface states in Bi2_2Se3_3 films induced by a d-wave high-temperature superconductor

Topological insulators are a new class of materials, that exhibit robust gapless surface states protected by time-reversal symmetry. The interplay between such symmetry-protected topological surface states and symmetry-broken states (e.g. superconductivity) provides a platform for exploring novel quantum phenomena and new functionalities, such as 1D chiral or helical gapless Majorana fermions, and Majorana zero modes which may find application in fault-tolerant quantum computation. Inducing superconductivity on topological surface states is a prerequisite for their experimental realization. Here by growing high quality topological insulator Bi$_2$Se$_3$ films on a d-wave superconductor Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ using molecular beam epitaxy, we are able to induce high temperature superconductivity on the surface states of Bi$_2$Se$_3$ films with a large pairing gap up to 15 meV. Interestingly, distinct from the d-wave pairing of Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$, the proximity-induced gap on the surface states is nearly isotropic and consistent with predominant s-wave pairing as revealed by angle-resolved photoemission spectroscopy. Our work could provide a critical step toward the realization of the long sought-after Majorana zero modes.Comment: Nature Physics, DOI:10.1038/nphys274

Asymptotic Regge Trajectories of Non-strange Mesons

We analyze the asymptotic behavior of Regge trajectories of non-strange mesons. In contrast to an existing belief, it is demonstrated that for the asymptotically linear Regge trajectories the width of heavy hadrons cannot linearly depend on their mass. Using the data on masses and widths of rho_J, omega_J, a_J and f_J mesons for the spin values J \leq 6, we extract the parameters of the asymptotically linear Regge trajectory predicted by the finite width model of quark gluon bags. As it is shown the obtained parameters for the data set B correspond to the cross-over temperature lying in the interval 170.9-175.3 MeV which is consistent with the kinetic freeze-out temperature of early hadronizing particles found in relativistic heavy ion collisions at and above the highest SPS energy.Comment: 14 pages, 3 figure

Antiferromagnetic spintronics

Antiferromagnetic materials are magnetic inside, however, the direction of their ordered microscopic moments alternates between individual atomic sites. The resulting zero net magnetic moment makes magnetism in antiferromagnets invisible on the outside. It also implies that if information was stored in antiferromagnetic moments it would be insensitive to disturbing external magnetic fields, and the antiferromagnetic element would not affect magnetically its neighbors no matter how densely the elements were arranged in a device. The intrinsic high frequencies of antiferromagnetic dynamics represent another property that makes antiferromagnets distinct from ferromagnets. The outstanding question is how to efficiently manipulate and detect the magnetic state of an antiferromagnet. In this article we give an overview of recent works addressing this question. We also review studies looking at merits of antiferromagnetic spintronics from a more general perspective of spin-ransport, magnetization dynamics, and materials research, and give a brief outlook of future research and applications of antiferromagnetic spintronics.Comment: 13 pages, 7 figure

MicroRNAs in pulmonary arterial remodeling

Pulmonary arterial remodeling is a presently irreversible pathologic hallmark of pulmonary arterial hypertension (PAH). This complex disease involves pathogenic dysregulation of all cell types within the small pulmonary arteries contributing to vascular remodeling leading to intimal lesions, resulting in elevated pulmonary vascular resistance and right heart dysfunction. Mutations within the bone morphogenetic protein receptor 2 gene, leading to dysregulated proliferation of pulmonary artery smooth muscle cells, have been identified as being responsible for heritable PAH. Indeed, the disease is characterized by excessive cellular proliferation and resistance to apoptosis of smooth muscle and endothelial cells. Significant gene dysregulation at the transcriptional and signaling level has been identified. MicroRNAs are small non-coding RNA molecules that negatively regulate gene expression and have the ability to target numerous genes, therefore potentially controlling a host of gene regulatory and signaling pathways. The major role of miRNAs in pulmonary arterial remodeling is still relatively unknown although research data is emerging apace. Modulation of miRNAs represents a possible therapeutic target for altering the remodeling phenotype in the pulmonary vasculature. This review will focus on the role of miRNAs in regulating smooth muscle and endothelial cell phenotypes and their influence on pulmonary remodeling in the setting of PAH