Sometimes less is more: experience with endoscopic myringoplasty.

A retrospective review of the outcomes of patients who underwent endoscopic myringoplasties in our institution was conducted. The aim was to highlight our results with this procedure. The database of patient records was manually checked, and the patients who had undergone Endoscopic Myringoplasties were identified, and their demographics, admitting notes, operating notes, and discharge summaries were reviewed. Graft failure was considered if the patient had a perforation in the graft during the outpatient follow-up. The information was compiled, and basic statistics were derived. A total of 31 patients were identified who had undergone Endoscopic Myringoplasty. Patients' age ranged from 14-52 years. None of the patients developed any immediate postoperative complications. Follow-up otoscopic examination showed 28 patients with an intact graft and only one patient with graft failure. Two patients were lost to follow up. Our success rate with Endoscopic Myringoplasty is 96.6%, which is comparable to the international standard success rate of 80-95%. The results of this study encourage adopting an endoscopic approach where the expertise is available.

Photocatalytic degradation and electrochemical energy storage properties of CuO/SnO2 nanocomposites via the wet-chemical method.

Integrating semiconducting functional materials is a way to enlarge the photoexcitation, energy range, and charge separation, greatly elongating the photocatalytic efficiency to enhance the chemical and physical properties of the materials. This work depicts and investigates the impact of cuprous oxide (CuO) and tin dioxide (SnO2)-based catalysts with various CuO concentrations on photocatalytic and supercapacitor applications. Moreover, three distinct composites were made with varied ratios of CuO (5, 10, and 15% wt. Are designated as AT-1, AT-2, and AT-3) with SnO2 to get an optimized performance. The photocatalytic properties indicate that the CuO/SnO2 nanocomposite outperformed its bulk equivalents in photocatalysis using Methyl blue (MB) dye in a photoreactor. The results were monitored using a UV-visible spectrometer. The AT-1 ratio nanocomposite displayed 96% photocatalytic degradation compared to pure SnO2 and CuO. CV analysis reveals a pseudocapacitive charge storage mechanism from 0.0 to 0.7 V in a potential window in an aqueous medium. The capacitive performance was also investigated for all electrodes, and we observed that a high capacitance of 260/155 F/g at 1/10 A/g was attained for the AT-1 electrode compared to others, specifying good rate performance.

The field of human building interaction for convergent research and innovation for intelligent built environments.

Human-Building Interaction (HBI) is a convergent field that represents the growing complexities of the dynamic interplay between human experience and intelligence within built environments. This paper provides core definitions, research dimensions, and an overall vision for the future of HBI as developed through consensus among 25 interdisciplinary experts in a series of facilitated workshops. Three primary areas contribute to and require attention in HBI research: humans (human experiences, performance, and well-being), buildings (building design and operations), and technologies (sensing, inference, and awareness). Three critical interdisciplinary research domains intersect these areas: control systems and decision making, trust and collaboration, and modeling and simulation. Finally, at the core, it is vital for HBI research to center on and support equity, privacy, and sustainability. Compelling research questions are posed for each primary area, research domain, and core principle. State-of-the-art methods used in HBI studies are discussed, and examples of original research are offered to illustrate opportunities for the advancement of HBI research.

Fabrication of a lead-free ternary ceramic system for high energy storage applications in dielectric capacitors.

The importance of electroceramics is well-recognized in applications of high energy storage density of dielectric ceramic capacitors. Despite the excellent properties, lead-free alternatives are highly desirous owing to their environmental friendliness for energy storage applications. Herein, we provide a facile synthesis of lead-free ferroelectric ceramic perovskite material demonstrating enhanced energy storage density. The ceramic material with a series of composition (1-z) (0.94Na0.5Bi0.5TiO3-0.06BaTiO3)-zNd0.33NbO3, denoted as NBT-BT-zNN, where, z = 0.00, 0.02, 0.04, 0.06, and 0.08 are synthesized by the conventional solid-state mix oxide route. Microphases, microstructures, and energy storage characteristics of the as-synthesized ceramic compositions were determined by advanced ceramic techniques. Powder X-ray diffraction analysis reveals pure single perovskite phases for z = 0 and 0.02, and secondary phases of Bi2Ti2O7 appeared for z = 0.04 and 0.08. Furthermore, scanning electron microscopy analysis demonstrates packed-shaped microstructures with a reduced grain size for these ceramic compositions. The coercive field (Ec) and remnant polarization (Pr) deduced from polarization vs. electric field hysteresis loops determined using an LCR meter demonstrate decreasing trends with the increasing z content for each composition. Consequently, the maximum energy storage density of 3.2 J/cm3, the recoverable stored energy of 2.01 J/cm3, and the efficiency of 62.5% were obtained for the z content of 2 mol% at an applied electric field of 250 kV/cm. This work demonstrates important development in ceramic perovskite for high power energy storage density and efficiency in dielectric capacitors in high-temperature environments. The aforementioned method makes it feasible to modify a binary ceramic composition into a ternary system with highly enhanced energy storage characteristics by incorporating rare earth metals with transition metal oxides in appropriate proportions.

Predicting the Response of RC Beam from a Drop-Weight Using Gene Expression Programming.

For structures and load-bearing beams under extreme impact loading, the prediction of the transmitted peak impact force is the most challenging task. Available numerical and soft computing-based methods for finding peak impact force are not very accurate. Therefore, a simple and user-friendly predictive model is constructed from a database containing 126 impact force experiments of the simply supported RC beams. The proposed model is developed using gene expression programming (GEP) that includes the effect of the impact velocity and the impactor weight. Also identified are other influencing factors that have been overlooked in the existing soft computing models, such as concrete compressive strength, the shear span to depth ratio, and the tensile reinforcement quantity and strength. This allows the proposed model to overcome several inconsistencies and difficulties residing in the existing models. A statistical study has been conducted to examine the adequacy of the proposed model compared to existing models. Additionally, a numerical confirmation of the empirical model of the peak impact force is obtained by reference to 3D finite element simulation in ABAQUS. Finally, the proposed model is employed to predict the dynamic shear force and bending moment diagrams, thus rendering it ideal for practical application.

Shear Strength Prediction Model for RC Exterior Joints Using Gene Expression Programming.

Predictive models were developed to effectively estimate the RC exterior joint's shear strength using gene expression programming (GEP). Two separate models are proposed for the exterior joints: the first with shear reinforcement and the second without shear reinforcement. Experimental results of the relevant input parameters using 253 tests were extracted from the literature to carry out a knowledge analysis of GEP. The database was further divided into two portions: 152 exterior joint experiments with joint transverse reinforcements and 101 unreinforced joint specimens. Moreover, the effects of different material and geometric factors (usually ignored in the available models) were incorporated into the proposed models. These factors are beam and column geometries, concrete and steel material properties, longitudinal and shear reinforcements, and column axial loads. Statistical analysis and comparisons with previously proposed analytical and empirical models indicate a high degree of accuracy of the proposed models, rendering them ideal for practical application.

Flexure and shear response of an impulsively loaded rigid-plastic beam by enhanced linear complementarity approach.

The linear complementarity approach has been utilized as a systematic and unified numerical process for determining the response of a rigid-plastic structure subjected to impulsive loading. However, the popular Lemke Algorithm for solving linear complementarity problems (LCP) encounters numerical instability issues whilst tracing the response of structures under extreme dynamic loading. This paper presents an efficient LCP approach with an enhanced initiation subroutine for resolving the numerical difficulties of the solver. The numerical response of the impulsively loaded structures is affected by the initial velocity profile, which if not found correctly can undermine the overall response. In the current study, the initial velocity profile is determined by a Linear Programming (LP) subroutine minimizing the energy function. An example of a uniform impulsively loaded simply supported beam is adduced to show the validity and accuracy of the proposed approach. The beam is approximated with bending hinges having infinite resistance to shear. Comparison of the numerical results to the available closed-form solution confirms the excellent performance of the approach. However, a subsequent investigation into a beam having the same support conditions and the applied loading, but with bending and shear deformation, results in numerical instability despite optimizing the initial velocity profile. Thus a more generic description of kinetics and kinematics is proposed that can further enhance the numerical efficiency of the LCP formulation. The ensuing numerical results are compared with the available close form solution to assess the accuracy and efficiency of the developed approach.

Improved Shear Strength Prediction Model of Steel Fiber Reinforced Concrete Beams by Adopting Gene Expression Programming.

In this study, an artificial intelligence tool called gene expression programming (GEP) has been successfully applied to develop an empirical model that can predict the shear strength of steel fiber reinforced concrete beams. The proposed genetic model incorporates all the influencing parameters such as the geometric properties of the beam, the concrete compressive strength, the shear span-to-depth ratio, and the mechanical and material properties of steel fiber. Existing empirical models ignore the tensile strength of steel fibers, which exercise a strong influence on the crack propagation of concrete matrix, thereby affecting the beam shear strength. To overcome this limitation, an improved and robust empirical model is proposed herein that incorporates the fiber tensile strength along with the other influencing factors. For this purpose, an extensive experimental database subjected to four-point loading is constructed comprising results of 488 tests drawn from the literature. The data are divided based on different shapes (hooked or straight fiber) and the tensile strength of steel fiber. The empirical model is developed using this experimental database and statistically compared with previously established empirical equations. This comparison indicates that the proposed model shows significant improvement in predicting the shear strength of steel fiber reinforced concrete beams, thus substantiating the important role of fiber tensile strength.

One-pot hydrothermal synthesis of a double Z-scheme g-C3N4/AgI/ß-AgVO3 ternary nanocomposite for efficient degradation of organic pollutants and DPC-Cr(VI) complex under visible-light irradiation.

The Z-scheme photocatalytic system provides a promising way to achieve significant photodegradation efficiency. The work embodied here describes the synthesis of highly efficient double Z-scheme g-C3N4/AgI/ß-AgVO3 (g-CNAB) ternary nanocomposite using a one-pot hydrothermal route. The optical properties, phase structure, and morphology of the synthesized samples were investigated using UV-visible diffuse-reflectance spectroscopy (UV-Vis DRS), X-ray diffraction, and scanning electron microscopy, respectively. The transmission electron microscopy investigation revealed that synthesized composite material represents close interfacial interactions. X-ray photoelectron spectroscopy analysis confirms the presence of all the elements in the synthesized ternary nanocomposite materials. The photocatalytic performance of as-prepared photocatalysts has been systematically investigated using the photodegradation of a variety of pollutants, including Rhodamine B, Ciprofloxacin, and 1,5-diphenylcarbazide-Cr(VI) [DPC-Cr(VI)] complex under visible-light irradiation. Among all synthesized materials, such as g-C3N4, AgI, ß-AgVO3, and ternary nanocomposites with varying loading of ß-AgVO3 [g-CNAB(0.5, 1.0, 1.5, 2.0)], the photocatalyst g-CNAB(1.5) nanocomposite achieved a remarkably high photocatalytic efficiency. The quenching impact of several scavengers revealed that reactive species such as superoxide anion radical (O2·-) and hydroxyl radical (·OH) are significant in the degradation of various contaminants. Based on the characterization and application, a plausible photocatalytic mechanism has been sketched out to determine the reaction pathways involved in the degradation of pollutants present in the aqueous medium.

Strain assisted magnetoelectric coupling in ordered nanomagnets of CoFe2O4/SrRuO3/(Pb(Mg1/3Nb2/3)O3-PbTiO3) heterostructures.

We have explored the electric field controlled magnetization in the nanodot CoFe2O4/SrRuO3/PMN-PT (CFO/SRO/PMN-PT) heterostructures. Ordered ferromagnetic CFO nanodots (∼300 nm lateral dimension) are developed on the PMN-PT substrate (ferroelectric as well as piezoelectric) using a nanostencil-mask pattering method during pulsed laser deposition. The nanostructures reveal electric field induced magnetization reversal in the single domain CFO nanodots through transfer of piezostrains from the piezoelectric PMN-PT substrate to the CFO. Further, electric field modulated spin structure of CFO nanomagnets is analyzed by using x-ray magnetic circular dichroism (XMCD). The XMCD analysis reveals cations (Fe3+/Co2+) redistribution on the octahedral and tetrahedral site in the electric field poled CFO nanodots, establishing the strain induced magneto-electric coupling effects. The CFO/SRO/PMN-PT nanodots structure demonstrate multilevel switching of ME coupling coefficient (α) by applying selective positive and negative electric fields in a non-volatile manner. The retention of two stable states ofαis illustrated for ∼106seconds, which can be employed to store the digital data in non-volatile memory devices. Thus the voltage controlled magnetization in the nanodot structures leads a path towards the invention of energy efficient high-density memory devices.

Numerical investigation of the effect of spanwise length and mesh density on flow around cylinder at Re = 3900 using LES model.

Flow around circular cylinder has been extensively studied by researchers for several decades due to its wide range of engineering applications such as in heat exchangers, marine cables, high rise building, chimneys, and offshore structures. The lack of clear understanding of the unsteady flow dynamics in the wake of circular cylinder and high computational cost are still an area of high interest amongst the researchers. The aim of the current study is to investigate the effect of variation in spanwise length and grid resolution in the spanwise direction on the recirculation length, separation angle of wake flow by performing large eddy simulations (LES). This study is an extension to previous work by Khan, NB et al, 2019 in which the spanwise length is restricted to 4D only. In current study, the spanwise length is changed from 0.5D to 8D where D is diameter of cylinder and mesh resolution in the spanwise direction is changed from 1 to 80 elements in the present study. The recirculation length, separation angle and wake characteristics are analyzed in detail. It is concluded that after getting optimize spanwise length, mesh resolution in the spanwise direction is the only parameter contributing toward better result.

Spin reorientation transition and coupled spin-lattice dynamics of Sm0.6Dy0.4FeO3.

In this work, we have presented a solid-solution of Sm0.6Dy0.4FeO3 in the form of nano-particles having spin reorientation transition (SRT) at a temperature interval of 220-260 K. The lattice dynamics of Sm0.6Dy0.4FeO3 have investigated by temperature-dependent x-ray diffraction and Raman spectroscopy. A negative thermal expansion at low temperatures has observed, which might be due to the interaction between Sm3+ and Fe3+ sublattice. Anomalous behavior in lattice parameters, octahedral tilt angle, and bond lengths have observed in the vicinity of SRT, which confirms the existence of magneto-elastic coupling in the system. The strong anomaly has observed in linewidth and phonon frequencies of Raman modes around SRT, which may be related to the spin-phonon coupling in Sm0.6Dy0.4FeO3. The contribution of SRT in lattice change and the presence of spin-phonon coupling can help to understand the correlation between the magnetic and structural properties of orthoferrite.

Facile Synthesis of a Z-Scheme ZnIn2S4/MoO3 Heterojunction with Enhanced Photocatalytic Activity under Visible Light Irradiation.

Employing a visible-light-driven direct Z-scheme photocatalytic system for the abatement of organic pollutants has become the key scientific approach in the area of photocatalysis. In this study, a highly efficient Z-scheme ZnIn2S4/MoO3 heterojunction was prepared through the hydrothermal method, followed by the impregnation technique that facilitates the formation of an interface between the two phases for efficient photocatalysis. The structural, optical, and surface elemental composition and morphology of the prepared samples were characterized in detail through X-ray diffraction, UV-vis diffuse reflectance spectra, X-ray photoelectron spectroscopy, scanning electron microscopy, and transmission electron microscopy. The results indicate that the composite materials have a strong intimate contact between the two phases, which is beneficial for the effective separation of photoinduced charge carriers. The visible-light-mediated photocatalytic activity of the samples was tested by studying the degradation of methyl orange (MO), rhodamine B (RhB), and paracetamol in aqueous suspension. An optimum loading content of 40 wt % ZnIn2S4/MoO3 exhibits the best degradation efficiency toward the above pollutants compared to bare MoO3 and ZnIn2S4. The improved photocatalytic activity could be ascribed to the efficient light-harvesting property and prolonged charge separation ability of the Z-scheme ZnIn2S4/MoO3 catalyst. Based on reactive species determination results, the Z-scheme charge transfer mechanism of ZnIn2S4/MoO3 was discussed and proposed. This study paves the way toward the development of highly efficient direct Z-scheme structures for a multitude of applications.

Metal- and Carbon-Based Materials as Heterogeneous Electrocatalysts for CO2 Reduction.

Climate change caused by continuous rising level of CO2 and the depletion of fossil fuels reserves has made it highly desirable to electrochemically convert CO2 into fuels and commodity chemicals. Implementing this approach will close the carbon cycle by recycling CO2 providing a sustainable way to store energy in the chemical bonds of portable molecular fuels. In order to make the process commercially viable, the challenge of slow kinetics of CO2 electroreduction and low energy efficiency of the process need to be addressed. To this end, this review summarizes the progress made in the past few years in the development of heterogeneous electrocatalysts with a focus on nanostructured material for CO2 reduction to CO, HCOOH/HCOO-, CH2O, CH4, H2C2O4/HC2O-4, C2H4, CH3OH, CH3CH2OH, etc. The electrocatalysts presented here are classified into metals, metal alloys, metal oxides, metal chalcogenides and carbon based materials on the basis of their elemental composition, whose performance is discussed in light of catalyst activity, product selectivity, Faradaic efficiency (FE), catalytic durability and in selected cases mechanism of CO2 electroreduction. The effect of particle size, morphology and solution-electrolyte type and composition on the catalyst property/activity is also discussed and finally some strategies are proposed for the development of CO2 electroreduction catalysts. The aim of this article is to review the recent advances in the field of CO2 electroreduction in order to further facilitate research and development in this area.

Comparative photocatalytic activity of sol-gel derived rare earth metal (La, Nd, Sm and Dy)-doped ZnO photocatalysts for degradation of dyes.

Rare earth metal doping into semiconductor oxides is considered to be an effective approach to enhance photocatalytic activity due to its ability to retard the electron-hole pair recombination upon excitation. Herein, we report the synthesis of different rare earth metal (La, Nd, Sm and Dy)-doped ZnO nanoparticles using a facile sol-gel route followed by evaluation of their photocatalytic activity by studying the degradation of methylene blue (MB) and Rhodamine B (RhB) under UV-light irradiation. Different standard analytical techniques were employed to investigate the microscopic structure and physiochemical properties of the prepared samples. The formation of the hexagonal wurtzite structure of ZnO was established by XRD and TEM analyses. In addition, the incorporation of rare earth metal into ZnO is confirmed by the shift of XRD planes towards lower theta values. All metal doped ZnO showed improved photocatalytic activity toward the degradation of MB, of which, Nd-doped ZnO showed the best activity with 98% degradation efficiency. In addition, mineralization of the dye was also observed, indicating 68% TOC removal in 180 min with Nd-doped ZnO nanoparticles. The influence of different operational parameters on the photodegradation of MB was also investigated and discussed in detail. Additionally, a possible photocatalytic mechanism for degradation of MB over Nd-doped ZnO nanoparticles has been proposed and involvement of hydroxyl radicals as reactive species is elucidated by radical trapping experiments.

PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models.

PhenoLines is a visual analysis tool for the interpretation of disease subtypes, derived from the application of topic models to clinical data. Topic models enable one to mine cross-sectional patient comorbidity data (e.g., electronic health records) and construct disease subtypes-each with its own temporally evolving prevalence and co-occurrence of phenotypes-without requiring aligned longitudinal phenotype data for all patients. However, the dimensionality of topic models makes interpretation challenging, and de facto analyses provide little intuition regarding phenotype relevance or phenotype interrelationships. PhenoLines enables one to compare phenotype prevalence within and across disease subtype topics, thus supporting subtype characterization, a task that involves identifying a proposed subtype's dominant phenotypes, ages of effect, and clinical validity. We contribute a data transformation workflow that employs the Human Phenotype Ontology to hierarchically organize phenotypes and aggregate the evolving probabilities produced by topic models. We introduce a novel measure of phenotype relevance that can be used to simplify the resulting topology. The design of PhenoLines was motivated by formative interviews with machine learning and clinical experts. We describe the collaborative design process, distill high-level tasks, and report on initial evaluations with machine learning experts and a medical domain expert. These results suggest that PhenoLines demonstrates promising approaches to support the characterization and optimization of topic models.

Supporting Handoff in Asynchronous Collaborative Sensemaking Using Knowledge-Transfer Graphs.

During asynchronous collaborative analysis, handoff of partial findings is challenging because externalizations produced by analysts may not adequately communicate their investigative process. To address this challenge, we developed techniques to automatically capture and help encode tacit aspects of the investigative process based on an analyst's interactions, and streamline explicit authoring of handoff annotations. We designed our techniques to mediate awareness of analysis coverage, support explicit communication of progress and uncertainty with annotation, and implicit communication through playback of investigation histories. To evaluate our techniques, we developed an interactive visual analysis system, KTGraph, that supports an asynchronous investigative document analysis task. We conducted a two-phase user study to characterize a set of handoff strategies and to compare investigative performance with and without our techniques. The results suggest that our techniques promote the use of more effective handoff strategies, help increase an awareness of prior investigative process and insights, as well as improve final investigative outcomes.

Synthesis of iron and copper cluster-grafted zinc oxide nanorod with enhanced visible-light-induced photocatalytic activity.

Design of visible-light-responsive photocatalyst employing simple and cost-effective method is of great importance from commercial point of view. Herein, we report the synthesis of visible-light-sensitive ubiquitous nanoclusters of Fe3+/Cu2+-grafted ZnO nanorod using impregnation technique, which showed excellent photocatalytic activity towards the decomposition of Rhodamine B (RhB), 4-nitrophenol (4-NP) and paracetamol in aqueous suspension under atmospheric oxygen. Fe-grafted ZnO nanorod exhibited pronounced effect for the degradation of the above-mentioned pollutants compared to pure ZnO and Cu-grafted ZnO nanorod. The better activity could be due to the more positive redox potential of surface grafted Fe3+ species resulting in the generation of more hydroxyl radicals thereby, leading to higher photodegradation rate.

Annotation Graphs: A Graph-Based Visualization for Meta-Analysis of Data Based on User-Authored Annotations.

User-authored annotations of data can support analysts in the activity of hypothesis generation and sensemaking, where it is not only critical to document key observations, but also to communicate insights between analysts. We present annotation graphs, a dynamic graph visualization that enables meta-analysis of data based on user-authored annotations. The annotation graph topology encodes annotation semantics, which describe the content of and relations between data selections, comments, and tags. We present a mixed-initiative approach to graph layout that integrates an analyst's manual manipulations with an automatic method based on similarity inferred from the annotation semantics. Various visual graph layout styles reveal different perspectives on the annotation semantics. Annotation graphs are implemented within C8, a system that supports authoring annotations during exploratory analysis of a dataset. We apply principles of Exploratory Sequential Data Analysis (ESDA) in designing C8, and further link these to an existing task typology in the visualization literature. We develop and evaluate the system through an iterative user-centered design process with three experts, situated in the domain of analyzing HCI experiment data. The results suggest that annotation graphs are effective as a method of visually extending user-authored annotations to data meta-analysis for discovery and organization of ideas.