Fast 3D Content Update for Wide-Angle Holographic Near-Eye Display

Near-eye holographic displays are the holy grail of wear-on 3D display devices because they are intended to project realistic wide-angle virtual scenes with parameters matching human vision. One of the key features of a realistic perspective is the ability to move freely around the virtual scene. This can be achieved by addressing the display with wide-angle computer-generated holograms (CGHs) that enable continuous viewpoint change. However, to the best of our knowledge there is no technique able to generate these types of content. Thus, in this work we propose an accurate and non-paraxial hologram update method for wide-angle CGHs that supports continuous viewpoint change around the scene. This method is based on the assumption that with a small change in perspective, two consecutive holograms share overlapping data. This enables reusing the corresponding part of the information from the previous view, eliminating the need to generate an entirely new hologram. Holographic information for the next viewpoint is calculated in two steps: first, a tool approximating the Angular Spectrum Propagation is proposed to generate the hologram data from previous viewpoint; and second, the efficient Phase Added Stereogram algorithm is utilized for generating the missing hologram content. This methodology offers fast and accurate calculations at the same time. Numerical and optical experiments are carried out to support the results of the proposed method.

SVJAM: Joint Analysis of Structural Variants Using Linked Read Sequencing Data

Linked-read whole genome sequencing methods, such as the 10x Chromium, attach a unique molecular barcode to each high molecular weight DNA molecule. The samples are then sequenced using short-read technology. During analysis, sequence reads sharing the same barcode are aligned to adjacent genomic locations. The pattern of barcode sharing between genomic regions allows the discovery of large structural variants (SVs) in the range of 1 Kb to a few Mb. Most SV calling methods for these data, such as LongRanger, analyze one sample at a time and often produces inconsistent results for the same genomic location across multiple samples. We developed a method, SVJAM, for joint calling of SVs, using data from 152 members of the BXD family of recombinant inbred strains of mice. Our method first collects candidate SV regions from single sample analysis, such as those produced by LongRanger. We then retrieve barcode overlapping data from all samples for each region. These data are organized as a high dimensional matrix. The dimension of this matrix is then reduced using principal component analysis. Samples projected onto a two dimensional space formed by the first two principal components forms two or three clusters based on their genotype, representing the reference, alternative, or heterozygotic alleles. We developed a novel distance measure for hierarchical clustering and rotating the axes to find the optimal clustering results. We also developed an algorithm to decide whether the pattern of sample distribution is best fitted with one, two, or three genotypes. For each sample, we calculate its membership score for each genotype. We compared results produced by SVJAM with LongRanger and few methods that rely on PacBio or Oxford Nanopore data. In a comparison of SVJAM with SV detected using long-read sequencing data for the DBA/2J strain, we found that our results recovered many SVs missed by LongRanger. We also found many SVs called by LongRanger were assigned with an incorrect SV type. Our algorithm also consistently identified heterozygotic regions.

The Effectiveness of Multiplex Teaching Method in Mastering Vocabulary for Deaf Students

<p>This study aims to measure the effectiveness of “multiplex teaching method” in mastering vocabulary for deaf students. Multiplex teaching method consists of picture language, sign language, printed-word language, written language, and spoken language. The research was designed as a single subject research (SSR) with baseline, intervention, and maintenance phase (A-B-A’ design). The research subjects consisted of two deaf students in special school of SLB Bhakti Luhur Malang, Indonesia. In addition, a special education teacher and an observer were involved in this study. The intervention instrument comprised five lesson plans (LP), each containing a vocabulary of four words. The data were analyzed using intra-condition and inter-condition graphical inspection with a focus on data stability, trends, and score changes. The effectiveness was determined by the Percentage of Non-Overlapping data (PND). The change of score from A'/A achieved by Subject-1 was 7.86 points, while Subject-2 obtained 7.68 points. Subject-1 obtained an average PND B/A of 100% and average PND A'/B of 82.5%. Subject-2 achieved an average PND B/A of 99% and PND A’/B of 90%. Thus, multiplex teaching method is very effective in helping deaf students master vocabulary.</p>

The Effect of Core Vocabulary Extension Program for Children with Inconsistent SSD

Objectives: The purpose of this study was to determine the effect of the Core Vocabulary Extension Program for establishing speech sound consistency on speech inconsistency and accuracy of children with inconsistent SSD.Methods: Four children with inconsistent SSD aged 3-5 years who exhibited speech sound inconsistency, phonological error patterns, and articulation problems at the same time participated in this study. The program of this study used a core vocabulary approach and a multi-sensory approach, and parental support was provided at the same time. The experimental design used a multiple probe baseline design, with 3-5 baseline evaluations, 10 treatment evaluations, and 3 maintenance evaluations were performed. Data analysis of dependent variables, mean, trend line slope, standard deviation, immediate effect of treatment, and ratio of non-overlapping data (PND) were analyzed.Results: As a result of the study, inconsistency was reduced and articulation ability was improved. Speech inconsistency improvement was effective in all four participating children, but accuracy improvement was only effective in three children.Conclusion: This study is significant in that it confirmed the therapeutic effect of the Core Vocabulary Extension Program which integrated a multisensory approach and parent coaching based on a core vocabulary approach on speech sound inconsistency and accuracy of children with severe speech sound disorder accompanied by intellectual problems and language disorders. In the future, it is necessary to apply a phonological approach to remove the remaining phonological error patterns after speech consistency is established and to confirm the effectiveness of the phonological approach

Effectiveness of Differential Reinforcement of Other Behaviors in Reducing Non-suicidal Self-Injurious Behaviors in Adolescents

Objective: This study aimed to investigate the effectiveness of differential reinforcement of other behaviors in reducing non-suicidal self-injury behaviors in adolescents. Methods: A single-subject A-B-A-B design was used in this study. The statistical population included male adolescents with self-injurious behaviors, the families of whom were seeking treatment for these behaviors. In total, four adolescents were recruited from a psychology clinic in Tehran, Iran, using convenience sampling. Participants were observed at 6, 8, 10, and 12 sessions at baseline phases of A1 and A2, followed by 12 intervention sessions after each baseline phase. The intervention included differential reinforcement of other behaviors. If the participants showed no self-injury behavior within a specific time duration, a reward was provided. Non-suicidal self-injury behaviors included self-harm, hair pulling, severe itching, pinching, wound manipulation, and hand biting. The frequency of these behaviors was assessed during each session. Visual analysis of graphed data, percentage of non-overlapping data, and mean percentage improvement were used for data analysis. Results: The results showed a fairly reliable effect for the intervention on reducing the target behavior, as indicated by a frequency reduction from phase A1 to B1 and A2 to B2 and by a frequency elevation by the intervention withdrawal from B1 to A2. The average percentage reduction across participants was obtained at 56%. However, a low rate of self-injury remained consistent for the participants. Conclusion: The results provided further evidence on the effectiveness of differential reinforcement of other behaviors in reducing self-injury behaviors. Although the intervention could reduce self-injury substantially, it seemed that it could not eliminate the behavior.

Managing overlap of primary study results across systematic reviews: practical considerations for authors of overviews of reviews

Background Overviews often identify and synthesise a large number of systematic reviews on the same topic, which is likely to lead to overlap (i.e. duplication) in primary studies across the reviews. Using a primary study result multiple times in the same analysis overstates its sample size and number of events, falsely leading to greater precision in the analysis. This paper aims to: (a) describe types of overlapping data that arise from the same primary studies reported across multiple reviews, (b) describe methods to identify and explain overlap of primary study data, and (c) present six case studies illustrating different approaches to manage overlap. Methods We first updated the search in PubMed for methods from the MOoR framework relating to overlap of primary studies. One author screened the studies titles and abstracts, and any full-text articles retrieved, extracted methods data relating to overlap of primary studies and mapped it to the overlap methods from the MOoR framework. We also describe six case studies as examples of overviews that use specific overlap methods across the steps in the conduct of an overview. For each case study, we discuss potential methodological implications in terms of limitations, efficiency, usability, and resource use. Results Nine methods studies were found and mapped to the methods identified by the MOoR framework to address overlap. Overlap methods were mapped across four steps in the conduct of an overview – the eligibility criteria step, the data extraction step, the assessment of risk of bias step, and the synthesis step. Our overview case studies used multiple methods to reduce overlap at different steps in the conduct of an overview. Conclusions Our study underlines that there is currently no standard methodological approach to deal with overlap in primary studies across reviews. The level of complexity when dealing with overlap can vary depending on the yield, trends and patterns of the included literature and the scope of the overview question. Choosing a method might be dependent on the number of included reviews and their primary studies. Gaps in evaluation of methods to address overlap were found and further investigation in this area is needed.

miRNAFinder: A Comprehensive Web Resource for Plant Pre-microRNA Classification

microRNAs (miRNAs) are known as one of the small non-coding RNA molecules, which control the expressions of genes at the RNA level. They typically range 20-24 nucleotides in length and can be found in the plant and animal kingdoms and in some viruses. Computational approaches have overcome the limitations in the experimental methods and have performed well in identifying miRNAs. Compared to mature miRNAs, precursor miRNAs (pre-miRNAs) are long and have a hairpin loop structure with structural features. Therefore, most in-silico tools are implemented for the pre-miRNAs identification. This study presents a multilayer perceptron (MLP) based classifier implemented using 180 features under sequential, structural, and thermodynamic feature categories for plant pre-miRNA identification. This classifier has a 92% accuracy, 94% specificity, and 90% sensitivity. We have further tested this model with other small non-coding RNA types and obtained 78% accuracy. Furthermore, we introduce a novel dataset to train and test machine learning models, addressing the overlapping data issue in positive training and testing datasets presented in PlantMiRNAPred, a study done by Xuan et al. for the classification of real and pseudo plant pre-miRNAs. The new dataset and the classifier are deployed on a web server which is freely accessible via http://mirnafinder.shyaman.me/.

Performance Analysis of OFDMA vs. NOMA in Cognitive Radio Network

Recent advancements in communication systems have resulted in a new class of multiple access schemes known as non-orthogonal multiple access (NOMA), the primary goal of which is to increase spectrum efficiency by overlapping data from different users in a single time-frequency resource used by the physical layer. NOMA receivers can resolve interference between data symbols from various users, hence increasing throughput. Initially, the combination of SCMA and orthogonal frequency division multiplexing (OFDM) is addressed, establishing a baseline for the overall SER performance of the multiple access strategy. Furthermore, this work suggests the merging of SCMA with generalised frequency division multiplexing (GFDM).GFDM is an intriguing possibility for future wireless communication systems since it is a very flexible non-orthogonal waveform that can imitate various different waveforms as corner cases. This research suggests two methods for integrating SCMA with GFDM.

Implementing Electronic Check-In/Check-Out to Reduce Challenging School Bus Behavior

The purpose of this study was to explore the efficacy of an electronic check-in, check-out (eCICO) intervention. The district’s case manager (i.e., guidance counselor) implemented the eCICO intervention remotely via FaceTime on an iPad in collaboration with the bus driver who facilitated student wireless internet access to a mobile hot spot. Results of the single-case multiple baseline across behaviors study suggest a functional relation between eCICO and the target bus behaviors of two rural students with emotional and behavioral disabilities. Further, low rates of target behaviors were maintained after eCICO was withdrawn. Implications for implementing eCICO interventions, limitations, and future research directions are discussed. Results of the study are reported using visual analysis, Tau-U, and percentage of non-overlapping data points.

Meta-analysis of SNP-environment interaction with heterogeneity for overlapping data

Meta-analysis is a popular method used in genome-wide association studies, by which the results of multiple studies are combined to identify associations. This process generates heterogeneity. Recently, we proposed a random effect model meta-regression method (MR) to study the effect of single nucleotide polymorphism (SNP)-environment interactions. This method takes heterogeneity into account and produces high power. We also proposed a fixed effect model overlapping MR in which the overlapping data is taken into account. In the present study, a random effect model overlapping MR that simultaneously considers heterogeneity and overlapping data is proposed. This method is based on the random effect model MR and the fixed effect model overlapping MR. A new way of solving the logarithm of the determinant of covariance matrices in likelihood functions is also provided. Tests for the likelihood ratio statistic of the SNP-environment interaction effect and the SNP and SNP-environment joint effects are given. In our simulations, null distributions and type I error rates were proposed to verify the suitability of our method, and powers were applied to evaluate the superiority of our method. Our findings indicate that this method is effective in cases of overlapping data with a high heterogeneity.