Sensor-AssistedWeighted Average Ensemble Model for Detecting Major Depressive Disorder

The present methods of diagnosing depression are entirely dependent on self-report ratings or clinical interviews. Those traditional methods are subjective, where the individual may or may not be answering genuinely to questions. In this paper, the data has been collected using self-report ratings and also using electronic smartwatches. This study aims to develop a weighted average ensemble machine learning model to predict major depressive disorder (MDD) with superior accuracy. The data has been pre-processed and the essential features have been selected using a correlation-based feature selection method. With the selected features, machine learning approaches such as Logistic Regression, Random Forest, and the proposedWeighted Average Ensemble Model are applied. Further, for assessing the performance of the proposed model, the Area under the Receiver Optimization Characteristic Curves has been used. The results demonstrate that the proposed Weighted Average Ensemble model performs with better accuracy than the Logistic Regression and the Random Forest approaches

Growth and properties of few-layer graphene prepared by chemical vapor deposition

The structure, and electrical, mechanical and optical properties of few-layer graphene (FLG) synthesized by chemical vapor deposition (CVD) on a Ni coated substrate were studied. Atomic resolution transmission electron microscope (TEM) images show highly crystalline single layer parts of the sample changing to multilayer domains where crystal boundaries are connected by chemical bonds. This suggests two different growth mechanisms. CVD and carbon segregation participate in the growth process and are responsible for the different structural formations found. Measurements of the electrical and mechanical properties on the centimeter scale provide evidence of a large scale structural continuity: 1) in the temperature dependence of the electrical conductivity, a non-zero value near 0 K indicates the metallic character of electronic transport; 2) the Young's modulus of a pristine polycarbonate film (1.37 GPa) improves significantly when covered with FLG (1.85 GPa). The latter indicates an extraordinary Young modulus value of the FLG-coating of TPa orders of magnitude. Raman and optical spectroscopy support the previous conclusions. The sample can be used as a flexible and transparent electrode and is suitable for special membranes to detect and study individual molecules in high resolution TEM

The control of graphene double-layer formation in copper-catalyzed chemical vapor deposition

The growth of graphene during Cu-catalyzed chemical vapor deposition was studied using 12CH4 and 13CH4 precursor gasses. We suggest that the growth begins by the formation of a multilayer cluster. This seed increases its size but the growth speed of a particular layer depends on its proximity to the copper surface. The layer closest to the substrate grows fastest and thus further limits the growth rate of the upper layers. Nevertheless, the growth of the upper layers continues until the copper surface is completely blocked. It is shown that the upper layers can be removed by modification of the conditions of the growth by hydrogen etching.Comment: 17 pages, 4 figure

Rational chemical multifunctionalization of graphene interface enhances targeted cancer therapy

The synthesis of a drug delivery platform based on graphene was achieved through a step‐by‐step strategy of selective amine deprotection and functionalization. The multifunctional graphene platform, functionalized with indocyanine green, folic acid, and doxorubicin showed an enhanced anticancer activity. The remarkable targeting capacity for cancer cells in combination with the synergistic effect of drug release and photothermal properties prove the great advantage of a combined chemo‐ and phototherapy based on graphene against cancer, opening the doors to future therapeutic applications of this type of material

Towards an efficient generalization of the online dosage of hydrogen peroxide in photo-fenton process to treat industrial wastewater

This work addresses the dosage of H2O2 in photo-Fenton processes and the monitoring of Dissolved oxygen (DO) that can be used to drive the dosage of H2O2. The objective of this work is to show that a smarter monitoring of a process variable such as DO (for which on-line measurement can be inexpensively obtained) enables the proposal and implementation of efficient dosage strategies. The work explores the application of a recent proposed strategy consisting of: (i) initial H2O2 addition, (ii) continuous H2O2 addition until a DO set up is reached, and (iii) automatic H2O2 addition by an on-off control system based on DO slope monitoring, and applies it to the treatment of different individual contaminants and their mixtures (paracetamol and sulfamethazine). The assays performed following this dosage strategy showed improved values of TOC removed per H2O2 consumed. For the case of sulfamethazine, this improvement increased up to 25–35% with respect to the efficiency obtained without dosage. Furthermore, a deeper analysis of the results allowed detecting and assessing the opportunity to redesign the dosage scheme and reduce its complexity and the number of control parameters. The promising results obtained are discussed in regard of future research into further increasing the simplicity and robustness of this generalized control strategy that improves the applicability of the photo-Fenton process by reducing its operating costs and increasing automationPeer ReviewedPostprint (published version

Electroweak radiative corrections to e+e−→ttˉhe^+e^- \to t \bar{t} h at linear colliders

We calculate the ${\cal O}(\alpha_{{\rm ew}})$ electroweak radiative corrections to $e^+ e^- \to t \bar{t} h$ at a electron-positron linear collider (LC) in the standard model. We analyze the dependence of the ${\cal O}(\alpha_{{\rm ew}})$ corrections on the Higgs boson mass $m_{h}$ and colliding energy $\sqrt{s}$, and find that the corrections significantly decrease or increase the Born cross section depending on the colliding energy. The numerical results show that the ${\cal O}(\alpha_{{\rm ew}})$ relative correction is strongly related to the Higgs boson mass when $\sqrt{s}=500 GeV$, and for $m_h = 150 GeV$ the relative correction ranges from -31.3% to 2.3% as the increment of the colliding energy from 500 GeV to 2 TeV.Comment: 16 pages, 7 figure

Emotion AI-Driven Sentiment Analysis: A Survey, Future Research Directions, and Open Issues

The essential use of natural language processing is to analyze the sentiment of the author via the context. This sentiment analysis (SA) is said to determine the exactness of the underlying emotion in the context. It has been used in several subject areas such as stock market prediction, social media data on product reviews, psychology, judiciary, forecasting, disease prediction, agriculture, etc. Many researchers have worked on these areas and have produced significant results. These outcomes are beneficial in their respective fields, as they help to understand the overall summary in a short time. Furthermore, SA helps in understanding actual feedback shared across di erent platforms such as Amazon, TripAdvisor, etc. The main objective of this thorough survey was to analyze some of the essential studies done so far and to provide an overview of SA models in the area of emotion AI-driven SA. In addition, this paper o ers a review of ontology-based SA and lexicon-based SA along with machine learning models that are used to analyze the sentiment of the given context. Furthermore, this work also discusses di erent neural network-based approaches for analyzing sentiment. Finally, these di erent approaches were also analyzed with sample data collected from Twitter. Among the four approaches considered in each domain, the aspect-based ontology method produced 83% accuracy among the ontology-based SAs, the term frequency approach produced 85% accuracy in the lexicon-based analysis, and the support vector machine-based approach achieved 90% accuracy among the other machine learning-based approaches.Ministerio de Educación (MOE) en Taiwán N/

Enhancement of non-equilibrium thermal quantum discord and entanglement of a three-spin XX chain by multi-spin interaction and external magnetic field

We investigate the non-equilibrium thermal quantum discord and entanglement of a three-spin chain whose two end spins are respectively coupled to two thermal reservoirs at different temperatures. In the three-spin chain, besides the XX-type nearest-neighbor two-spin interaction, a multi-spin interaction is also considered and a homogenous magnetic field is applied to each spin. We show that the extreme steady-state quantum discord and entanglement of the two end spins can always be created by holding both a large magnetic field and a strong multi-spin interaction. The results are explained by the thermal excitation depression due to switching a large energy gap between the ground state and the first excited state. The present investigation may provide a useful approach to control coupling between a quantum system and its environment.Comment: 16 pages, 10 figure

Size-dependent decoherence of excitonic states in semiconductor microcrystallites

The size-dependent decoherence of the exciton states resulting from the spontaneous emission is investigated in a semiconductor spherical microcrystallite under condition $a_{B}\ll R_{0}\leq\lambda$. In general, the larger size of the microcrystallite corresponds to the shorter coherence time. If the initial state is a superposition of two different excitonic coherent states, the coherence time depends on both the overlap of two excitonic coherent states and the size of the microcrystallite. When the system with fixed size is initially in the even or odd coherent states, the larger average number of the excitons corresponds to the faster decoherence. When the average number of the excitons is given, the bigger size of the microcrystallite corresponds to the faster decoherence. The decoherence of the exciton states for the materials GaAs and CdS is numerically studied by our theoretical analysis.Comment: 4 pages, two figure

Technology ready use of single layer graphene as a transparent electrode for hybrid photovoltaic devices

Graphene has been used recently as a replacement for indium tin oxide (ITO) for the transparent electrode of an organic photovoltaic device. Due to its limited supply, ITO is considered as a limiting factor for the commercialization of organic solar cells. We explored the use of large-area graphene grown on copper by chemical vapor deposition (CVD) and then transferred to a glass substrate as an alternative transparent electrode. The transferred film was shown by scanning Raman spectroscopy measurements to consist of >90% single layer graphene. Optical spectroscopy measurements showed that the layer-transferred graphene has an optical absorbance of 1.23% at a wavelength of 532 nm. We fabricated organic hybrid solar cells utilizing this material as an electrode and compared their performance with ITO devices fabricated using the same procedure. We demonstrated power conversion efficiency up to 3.98%, higher than that of the ITO device (3.86%), showing that layer-transferred graphene promises to be a high quality, low-cost, flexible material for transparent electrodes in solar cell technology.Comment: 6 pages, 3 figure