Have E-cigarette Risk Perception and Cessation Intent of Young Adult Users Changed During the Pandemic?

Emerging evidence indicates that young adults who use e-cigarettes can withhold greater exposure to COVID-19 risk. We examine how young e-cigarette users perceive COVID-19 related threat of e-cigarette use and benefit of cessation as compared to traditional ones, applying the health belief model. We investigate changes of such perceptions during the pandemic and their associations with past attempt and future intent to quit e-cigarette use.

Simulation study of the scaling behavior of top-gated carbon nanotube field effect transistors.

Device simulations on three-dimensional top-gated carbon nanotube field effect transistors (CNTFETs) have been performed by considering the quantum transport described in the framework of non-equilibrium Green's function method. Device characteristics of various top-gated CNTFETs, such as Schottky-barrier CNTFETs, CNTFETs with doped source and drain, and tunnel-FET-like CNTFETs, have been examined, focusing on their scaling behavior as the channel length is ultimately reduced down to a few nanometers. Comparison with coaxially-gated devices is also made.

Detection of atrial fibrillation episodes using multiple heart rate variability features in different time periods.

Circadian variations of cardiac diseases have been well known. For example, atrial fibrillation (AF) episodes show nocturnal predominance. In this study, we have developed multiple formulas that detect AF episodes in different times of the day.

Detection of subjects with higher self-reporting stress scores using heart rate variability patterns during the day.

Heart rate variability (HRV) has been well established to measure instantaneous levels of mental stress. Circadian patterns of HRV features have been reported but their use to estimate levels of mental stress were not studied thoroughly. In this study, we investigated time dependent variations of HRV features to detect subjects under chronic mental stress.

A new approach for overlay text detection and extraction from complex video scene.

Overlay text brings important semantic clues in video content analysis such as video information retrieval and summarization, since the content of the scene or the editor's intention can be well represented by using inserted text. Most of the previous approaches to extracting overlay text from videos are based on low-level features, such as edge, color, and texture information. However, existing methods experience difficulties in handling texts with various contrasts or inserted in a complex background.

Fabrication of thermally stable and cost-effective polymeric waveguide for optical printed-circuit board.

A thermally stable polymeric optical waveguide has been fabricated using ultraviolet (UV)-curable epoxy resins for the core and clad materials. A simple and cost-effective fabrication method that uses reusable polydimethylsiloxane (PDMS) masters has been developed. The 12-channel under-clad layer of the UV-cured epoxy was prepared using a PDMS master whose embossed channels had been fabricated by a polycarbonate (PC) secondary master.

Protein complex prediction based on mutually exclusive interactions in protein interaction network.

The increasing amount of available Protein-Protein Interaction (PPI) data enables scalable methods for the protein complex prediction. A protein complex is a group of two or more proteins formed by interactions that are stable over time, and it generally corresponds to a dense sub-graph in PPI Network (PPIN). However, dense sub-graphs correspond not only to stable protein complexes but also to sets of proteins including dynamic interactions.

Application of RF varactor using Ba(x)Sr(1-x)TiO3/TiO2/HR-Si substrate for reconfigurable radio.

In this paper, the potential feasibility of integrating Ba(x)Sr(1-x)TiO3 (BST) films into Si wafer by adopting tunable interdigital capacitor (IDC) with TiO2 thin film buffer layer and a RF tunable active bandpass filter (BPF) using BST based capacitor are proposed. TiO2 as a buffer layer is grown onto Si substrate by atomic layer deposition (ALD) and the interdigital capacitor on BST(500 nm)/TiO2 (50 nm)/HR-Si is fabricated. BST interdigital tunable capacitor integrated on HR-Si substrate with high tunability and low loss tangent are characterized for their microwave performances.

Association of heart rates with stress response inventory scores in different age groups.

Many studies reported heart rate changes were associated with mental stress. Recently, a Stress Response Inventory (SRI) questionnaire has been devised to score physical, mental, and emotional symptoms related to mental stress occurred during the past two weeks. However, SRI has too many items to be asked routinely in a mobile device such as a cellular phone.

Ultra short term analysis of heart rate variability for monitoring mental stress in mobile settings.

Heart rate variability (HRV) analysis is commonly used as a quantitative marker depicting the activity of autonomous nervous system (ANS) that may be related to mental stress. For mobile applications, short term ECG measurement may be used for HRV analysis since the conventional five minute long recordings might be inadequately long. Short term analysis of HRV features has been investigated mostly in ECG data from normal and cardiac patients.

Differentiated service in OBS networks using a dynamic FDL bank partitioning algorithm.

In order to solve the differentiated service problem in optical burst switching (OBS) networks, we propose a dynamic fiber delay line (FDL) bank partitioning algorithm, which divides a FDL bank into several groups, using a feed-forward output buffering architecture. In the analysis, three classes and groups are considered for traffic and FDL, respectively, and each group is assigned to each class. This paper shows that the loss differentiation in OBS networks is easily accomplished in Poisson traffic environments when our dynamic algorithm is adopted.

All-optical flip-flop with high on-off contrast ratio using two injection-locked single-mode Fabry-Perot laser diodes.

An all-optical flip-flop with inverted output is presented. The flip-flop is realized based on the optical bistability of an injection-locked single-mode Fabry-Perot laser diode (FP-LD). The operation principle is explained and experimental results are presented in this paper.

Tunable single-mode Fabry-Perot laser diode using a built-in external cavity and its modulation characteristics.

A tunable single-mode laser is obtained by using a weakly coupled cavity structure involved in a coaxially packaged Fabry-Perot laser diode. The cleaved end facet of the coupling fiber becomes an optical reflector and forms an external cavity with a laser facet. The single-mode oscillation condition is controlled and stabilized by tuning the operating temperature.

Inter-species validation for domain combination based protein-protein interaction prediction method.

Domain Combination based Protein-Protein Interaction Prediction (DCPPIP) method is revealed to show outstanding prediction accuracy in Yeast proteins. However, it is not yet apparent whether the method is still valid and can achieve comparable prediction accuracy for the proteins in other species. In this paper, we report the validation results of applying the DCPPIP method for Fly and Human proteins.

Segmenting a low-depth-of-field image using morphological filters and region merging.

We propose a novel algorithm to partition an image with low depth-of-field (DOF) into focused object-of-interest (OOI) and defocused background. The proposed algorithm unfolds into three steps. In the first step, we transform the low-DOF image into an appropriate feature space, in which the spatial distribution of the high-frequency components is represented.

Partially connected feedforward neural networks structured by input types.

This paper proposes a new method to model partially connected feedforward neural networks (PCFNNs) from the identified input type (IT) which refers to whether each input is coupled with or uncoupled from other inputs in generating output. The identification is done by analyzing input sensitivity changes as amplifying the magnitude of inputs. The sensitivity changes of the uncoupled inputs are not correlated with the variation on any other input, while those of the coupled inputs are correlated with the variation on any one of the coupled inputs.

A domain combination based probabilistic framework for protein-protein interaction prediction.

In this paper, we propose a probabilistic framework to predict the interaction probability of proteins. The notion of domain combination and domain combination pair is newly introduced and the prediction model in the framework takes domain combination pair as a basic unit of protein interactions to overcome the limitations of the conventional domain pair based prediction systems. The framework largely consists of prediction preparation and service stages.

PreSPI: design and implementation of protein-protein interaction prediction service system.

With the recognition of the importance of computational approach for protein-protein interaction prediction, many techniques have been developed to computationally predict protein-protein interactions. However, few techniques are actually implemented and announced in service form for general users to readily access and use the techniques. In this paper, we design and implement a protein interaction prediction service system based on the domain combination based protein-protein interaction prediction technique, which is known to show superior accuracy to other conventional computational protein-protein interaction prediction methods.

PreSPI: a domain combination based prediction system for protein-protein interaction.

With the accumulation of protein and its related data on the Internet, many domain-based computational techniques to predict protein interactions have been developed. However, most techniques still have many limitations when used in real fields. They usually suffer from low accuracy in prediction and do not provide any interaction possibility ranking method for multiple protein pairs.

Reuse of imputed data in microarray analysis increases imputation efficiency.

Background: The imputation of missing values is necessary for the efficient use of DNA microarray data, because many clustering algorithms and some statistical analysis require a complete data set. A few imputation methods for DNA microarray data have been introduced, but the efficiency of the methods was low and the validity of imputed values in these methods had not been fully checked.

Results: We developed a new cluster-based imputation method called sequential K-nearest neighbor (SKNN) method.