Multi-objective and multi constrained task scheduling framework for computational grids

Grid computing emerged as a powerful computing domain for running large-scale parallel applications. Scheduling computationally intensive parallel applications such as scientific, commercial etc., computational grids is a NP-complete problem. Many researchers have proposed several task scheduling algorithms on grids based on formulating and solving it as an optimization problem with different objective functions such as makespan, cost, energy etc. Further to address the requirements/demands/needs of the users (lesser cost, lower latency etc.) and grid service providers (high utilization and high profitability), a task scheduler needs to be designed based on solving a multi-objective optimization problem due to several trade-offs among the objective functions. In this direction, we propose an efficient multi-objective task scheduling framework to schedule computationally intensive tasks on heterogeneous grid networks. This framework minimizes turnaround time, communication, and execution costs while maximizing grid utilization. We evaluated the performance of our proposed algorithm through experiments conducted on standard, random, and scientific task graphs using the GridSim simulator.

Colorful graphene-based wearable e-textiles prepared by co-dyeing cotton fabrics with natural dyes and reduced graphene oxide

In addition to the functionality of electronic textiles (e-textiles), their aesthetic properties should be considered to expand their marketability. In this study, premordanted cotton fabrics were co-dyed with reduced graphene oxide (rGO) and natural dyes to develop ecofriendly and colorful graphene-based wearable e-textiles. The color attributes of the textiles were analyzed in terms of the dyeing conditions, namely, rGO loading, mordant type, and natural dye type. The lightness of the dyed samples increased in the order of cochineal < gardenia blue < rhubarb. Regardless of the natural dye and rGO loading, the lightness of the fabrics mordanted with Fe was lower than that with Al and Cu. Moreover, the rhubarb- and gardenia blue-dyed fabrics exhibited broad chroma and hue dispersions, indicating the strong impact of the dyeing conditions. With increasing rGO loading, the chroma of the rhubarb-dyed fabrics substantially decreased, resulting in decreased color saturation. The initial greenish-blue color of the gardenia blue-dyed fabrics gradually changed to yellowish-green and then yellow. Regardless of the natural dye, drastic overall color changes were observed, with average values of 7.60, 11.14, 12.68, and 13.56 ΔECMC(2:1) at increasing rGO loadings of 1, 3, 5, and 7% owb, respectively.

Development of heart organoid cryopreservation method through Fe3 O4 nanoparticles based nanowarming system

Beyond single cell two-dimensional (2D) culture, research on organoids that can mimic human organs is rapidly developing. However, there are still problems in commercialization and joint research using organoids due to the lack of technology to safely store organoids. Since organoids are 3D complex structures with a certain size (0.1-5 mm) beyond the size of cells, the conventional cell-level cryopreservation method using cryoprotectant (CPA) cannot overcome the damage caused by volume change due to osmotic pressure difference and ice nucleation. Herein, we attempted to solve such limitations by applying a nanowarming system using CPA with high cell permeability and Fe3 O4 nanoparticles. By performing beat rate measurement, histological analysis, contractility analysis, and multi-electrode array, it was verified that the developed method could significantly improve functional recovery and survival of heart organoids after freezing and thawing. In this study, we demonstrated a successful organoid cryopreservation method based on a Fe3 O4 nanowarming system. The developed technology will provide clues to the field of tissue cryopreservation and spur the application of organoids.

Experimental and Numerical Study on the Perforation Behavior of an Aluminum 6061-T6 Cylindrical Shell

The modified Johnson-Cook (MJC) material model is widely used in simulation under high-velocity impact. There was a need to estimate a strain rate parameter for the application to the impact analysis, where the method typically used is the Split Hopkinson bar. However, this method had a limit to the experiment of strain rate. This study proposed to estimate the strain rate parameter of the MJC model based on the impact energy and obtained a parameter. The proposed method of strain rate parameter calculation uses strain parameters to estimate from the drop weight impact and high-velocity impact experiments. Then, the ballistic experiment and analysis were carried out with the target of the plate and cylindrical shape. These analysis results were then compared with those obtained from the experiment. The penetration velocities of plates could be predicted with an error of a maximum of approximately 3.7%. The penetration shape of the cylindrical target has a similar result shape according to impact velocity and had an error of approximately 6%.

Influence of body shape on health-related quality of life in Korean adults: The mediating effect of self-rated health

A Body Shape Index (ABSI) predicts mortality independent of body mass index and had a negative relationship with self-rated health (SRH), which had a positive effect on the EuroQol (EQ)-5D index. This study aimed to investigate the relationship between ABSI and the EQ-5D index and to verify the mediating effect of SRH in Korean adults. This study included 13,381 participants aged ≥20 years from the 7th (2016-2018) Korean National Health and Nutrition Examination Survey (KNHANES). The participants were classified into tertile groups based on the ABSI (T1, T2, and T3 groups). Demographic characteristics, health-related factors, ABSI, SRH, and EQ-5D scores were evaluated. Women (p<0.001), rural areas (p<0.001), married persons (p<0.001), low education level (p<0.001), low income (p<0.001), and older age (p<0.001) were higher in the T3 group. The monthly drinking (p<0.001), current smoking (p<0.001), and mental stress rates (p<0.001) were the highest in the T1 group. The overall average SRH scores and EQ-5D index were 3.08 points and 0.94 points, respectively. ABSI and SRH (r = -0.161, p<0.001) and ABSI and EQ-5D (r = -0.229, p<0.001) showed a negative correlation. However, SRH and EQ-5D scores (r = 0.433, p<0.001) were positively correlated. The overall effect of the independent variable ABSI on the dependent variable EQ-5D was -0.959. SRH partially mediated the effect of ABSI on EQ-5D (indirect effect coefficient = -0.200). These results can be used as basic data to develop strategies and programs to improve health-related quality of life by adjusting ABSI and SRH.

Effectiveness of Chickpeas on Blood Sugar: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Diabetes affects one in eleven adults globally, with rising cases in the past 30 years. Type 1 and type 2 cause blood sugar problems, increasing cardiovascular risks. Dietary control, including chickpeas, is suggested but needs more research. Comprehensive searches were conducted across multiple databases for the randomized controlled trial efficacy of chickpea consumption to lower blood sugar levels to a healthy range, with data extraction and risk of bias assessment performed independently by two researchers. Statistical analysis was performed using RevMan 5.4, expressing continuous data as mean differences and risk ratios with 95% confidence intervals, and a summary of the findings is provided considering the variations in study characteristics. A total of 118 articles were initially identified from seven databases, primarily from Anglo-American countries, resulting in 12 selected studies after the identification and screening processes. These studies involved 182 participants, focusing on healthy or normoglycemic adults, and assessed the effects of chickpeas compared to various foods such as wheat, potatoes, pasta, sauce, cheese, rice, and corn. A meta-analysis involving a subset of studies demonstrated that chickpeas were more effective in reducing blood glucose iAUC compared to potatoes and wheat. Chickpeas offer the potential for blood sugar control through low starch digestibility, high fiber, protein, and hormonal effects. Although insulin benefits are seen, statistical significance varies, supporting their role in diabetic diets focusing on nutrient-rich foods over processed carbs.

The Effectiveness of a Multimodal Brain Empowerment Program in Mild Cognitive Impairment: A Single-Blind, Quasi-Randomized Experimental Study

The present study aimed to determine a multimodal brain empowerment (MBE) program to mitigate the modifiable risk factors in mild cognitive impairment (MCI), and its therapeutic effects are unknown. MBE encompassing (1) tDCS, light therapy, computerized cognitive therapy (TLC) and (2) robot-assisted gait training, music therapy, and core exercise (REM) interventions were randomly assigned to 20 healthy young adults and 20 older adults with MCI. The electroencephalography (EEG) power spectrum and topographic event-related synchronization (ERS) analysis were used to assess intervention-related changes in neural activity during the MBE program. Outcome: The EEG results demonstrated that both multimodal TLC and REM decreased delta waves and increased theta, alpha, and beta waves (p < 0.001). ERS showed increased neural activation in the frontal, temporal, and parietal lobes during TLC and REM. Such enhanced neural activity in the region of interest supports potential clinical benefits in empowering cognitive function in both young adults and older adults with MCI.

Fibroblast Growth Factor 11 Inhibits Hepatitis B Virus Gene Expression Through FXRα Suppression

Fibroblast growth factor 11 (FGF11) is a member of the intracellular FGF family, which shows different signal transmission compared with other FGF superfamily members. The molecular function of FGF11 is not clearly understood. In this study, we identified the inhibitory effect of FGF11 on hepatitis B virus (HBV) gene expression through transcriptional suppression. FGF11 decreased the mRNA and protein expression of HBV genes in liver cells. While the nuclear receptor FXRα1 increased HBV promoter transactivation, FGF11 decreased the FXRα-mediated gene induction of the HBV promoter by the FXRα agonist. Reduced endogenous levels of FXRα by siRNA and the dominant negative mutant protein (aa 1-187 without ligand binding domain) of FXRα expression indicated that HBV gene suppression by FGF11 is dependent on FXRα inhibition. In addition, FGF11 interacts with FXRα protein and reduces FXRα protein stability. These results indicate that FGF11 inhibits HBV replicative expression through the liver cell-specific transcription factor, FXRα, and suppresses HBV promoter activity. Our findings may contribute to the establishment of better regimens for the treatment of chronic HBV infections by including FGF11 to alter the bile acid mediated FXR pathway.

Deep learning regressor model based on nigrosome MRI in Parkinson syndrome effectively predicts striatal dopamine transporter-SPECT uptake

PURPOSE

Nigrosome imaging using susceptibility-weighted imaging (SWI) and dopamine transporter imaging using ¹²³I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane (¹²³I-FP-CIT) single-photon emission computerized tomography (SPECT) can evaluate Parkinsonism. Nigral hyperintensity from nigrosome-1 and striatal dopamine transporter uptake are reduced in Parkinsonism; however, quantification is only possible with SPECT. Here, we aimed to develop a deep-learning-based regressor model that can predict striatal ¹²³I-FP-CIT uptake on nigrosome magnetic resonance imaging (MRI) as a biomarker for Parkinsonism.

METHODS

Between February 2017 and December 2018, participants who underwent 3 T brain MRI including SWI and ¹²³I-FP-CIT SPECT based on suspected Parkinsonism were included. Two neuroradiologists evaluated the nigral hyperintensity and annotated the centroids of nigrosome-1 structures. We used a convolutional neural network-based regression model to predict striatal specific binding ratios (SBRs) measured via SPECT using the cropped nigrosome images. The correlation between measured and predicted SBRs was evaluated.

RESULTS

We included 367 participants (203 women (55.3%); age, 69.0 ± 9.2 [range, 39-88] years). Random data from 293 participants (80%) were used for training. In the test set (74 participants [20%]), the measured and predicted ¹²³I-FP-CIT SBRs were significantly lower with the loss of nigral hyperintensity (2.31 ± 0.85 vs. 2.44 ± 0.90) than with intact nigral hyperintensity (4.16 ± 1.24 vs. 4.21 ± 1.35, P < 0.01). The sorted measured ¹²³I-FP-CIT SBRs and the corresponding predicted values were significantly and positively correlated (ρ_c = 0.7443; 95% confidence interval, 0.6216-0.8314; P < 0.01).

CONCLUSION

A deep learning-based regressor model effectively predicted striatal ¹²³I-FP-CIT SBRs based on nigrosome MRI with high correlation using manually-measured values, enabling nigrosome MRI as a biomarker for nigrostriatal dopaminergic degeneration in Parkinsonism.

Comprehensive Analysis of Rice Seedling Transcriptome during Dehydration and Rehydration

Drought is a harmful abiotic stress that threatens the growth, development, and yield of rice plants. To cope with drought stress, plants have evolved their diverse and sophisticated stress-tolerance mechanisms by regulating gene expression. Previous genome-wide studies have revealed many rice drought stress-responsive genes that are involved in various forms of metabolism, hormone biosynthesis, and signaling pathways, and transcriptional regulation. However, little is known about the regulation of drought-responsive genes during rehydration after dehydration. In this study, we examined the dynamic gene expression patterns in rice seedling shoots during dehydration and rehydration using RNA-seq analysis. To investigate the transcriptome-wide rice gene expression patterns during dehydration and rehydration, RNA-seq libraries were sequenced and analyzed to identify differentially expressed genes (DEGs). DEGs were classified into five clusters based on their gene expression patterns. The clusters included drought-responsive DEGs that were either rapidly or slowly recovered to control levels by rehydration treatment. Representative DEGs were selected and validated using qRT-PCR. In addition, we performed a detailed analysis of DEGs involved in nitrogen metabolism, phytohormone signaling, and transcriptional regulation. In this study, we revealed that drought-responsive genes were dynamically regulated during rehydration. Moreover, our data showed the potential role of nitrogen metabolism and jasmonic acid signaling during the drought stress response. The transcriptome data in this study could be a useful resource for understanding drought stress responses in rice and provide a valuable gene list for developing drought-resistant crop plants.

FragTracer: Real-Time Fragmentation Monitoring Tool for F2FS File System

Emerging hardware devices (e.g., NVMe SSD, RISC-V, etc.) open new opportunities for improving the overall performance of computer systems. In addition, the applications try to fully utilize hardware resources to keep up with those improvements. However, these trends can cause significant file system overheads (i.e., fragmentation issues). In this paper, we first study the reason for the fragmentation issues on an F2FS file system and present a new tool, called FragTracer, which helps to analyze the ratio of fragmentation in real-time. For user-friendly usage, we designed FragTracer with three main modules, monitoring, pre-processing, and visualization, which automatically runs without any user intervention. We also optimized FragTracer in terms of performance to hide its overhead in tracking and analyzing fragmentation issues on-the-fly. We evaluated FragTracer with three real-world databases on the F2FS file system, so as to study the fragmentation characteristics caused by databases, and we compared the overhead of FragTracer. Our evaluation results clearly show that the overhead of FragTracer is negligible when running on commodity computing environments.

Upregulation of programmed death ligand-1 in tumor-associated macrophages affects chemotherapeutic response in ovarian cancer cells

To better understand the mechanism of chemoresistance in ovarian cancer cells, we aimed to investigate the influence of macrophages on the tumor cell response to carboplatin and identify the genes associated with chemoresistance. We mimicked the tumor microenvironment (TME) using a co-culture technique and compared the proliferation of ovarian cells with and without macrophages. We also examined M1 and M2 marker expression and the expression of key TME genes. Post the co-culture, we treated ovarian cancer cells with carboplatin and elucidated the function of programmed death-ligand 1 (PD-L1) in carboplatin chemoresistance. We investigated CD68 and PD-L1 expression in normal and cancerous ovarian tissues using immunohistochemistry (IHC). Finally, we analyzed the association between CD68 or PD-L1 expression and survival outcomes. Inducible nitric oxide synthase (iNOS) was downregulated, while the gene expression of M2 macrophage markers was increased in ovarian cancer cells. PD-L1, vascular endothelial growth factor (VEGF), Interleukin (IL)-6, IL-10, IL-12, signal transducer and activator of transcription 3 (STAT3), B-cell lymphoma 2 (BCL2), multidrug resistance 1 (MDR1), and colony stimulating factor 1 (CSF-1) were upregulated. Notably, PD-L1 was upregulated in both the ovarian cancer cells and macrophages. Ovarian cancer cells co-cultured with macrophages exhibited statistically significant carboplatin resistance compared to single-cultured ovarian cancer cells. PD-L1 silencing induced chemosensitivity in both types of co-cultured ovarian cancer cells. However, IHC results revealed no correlation between PD-L1 expression and patient survival or cancer stage. CD68 expression was significantly increased in cancer cells compared to normal or benign ovarian tumor cells, but it was not associated with the survival outcomes of ovarian cancer patients. Our study demonstrated that ovarian cancer cells interact with macrophages to induce the M2 phenotype. We also established that PD-L1 upregulation in both ovarian cancer cells and macrophages is a key factor for carboplatin chemoresistance.

Association between severe hepatic steatosis examined by Fibroscan and the risk of high-risk colorectal neoplasia

The prevalence of colorectal neoplasm in patients with non-alcoholic fatty liver disease has increased twice as high as that in the general population. FibroScan is a new modality for evaluating hepatic steatosis. This study aimed to investigate the relationship between the risk of high-risk colorectal neoplasia and hepatic steatosis examined using FibroScan. This was a cross sectional study of prospectively enrolled subjects who were scheduled to undergo index colonoscopy as a health screening between March 2018 and February 2019. The severity of steatosis was graded as normal, mild, moderate, or severe using FibroScan. A total of 140 consecutive subjects were enrolled and sequentially examined using FibroScan and colonoscopy. Subjects with hepatic steatosis had more high-risk colorectal neoplasia than those without hepatic steatosis. In addition, tumor size was larger in subjects with hepatic steatosis. In multivariable analysis, severe hepatic steatosis was an independent risk factor for high-risk colorectal neoplasia (adjusted odds ratio: 3.309, confidence interval: 1.043-10.498, p = 0.042). Alcohol consumption was also identified as a risk factor for high-risk colorectal neoplasia. In conclusion, severe hepatic steatosis on FibroScan is associated with the development of high-risk colorectal neoplasia. Thus, physicians should be aware of the association between colorectal neoplasia and hepatic steatosis assessed by FibroScan and its clinical implications.

Analysis of the effect of an artificial intelligence chatbot educational program on non-face-to-face classes: a quasi-experimental study

BACKGROUND

Education and training are needed for nursing students using artificial intelligence-based educational programs. However, few studies have assessed the effect of using chatbots in nursing education.

OBJECTIVES

This study aimed to develop and examine the effect of an artificial intelligence chatbot educational program for promoting nursing skills related to electronic fetal monitoring in nursing college students during non-face-to-face classes during the COVID-19 pandemic.

DESIGN

This quasi-experimental study used a nonequivalent control group non-synchronized pretest-posttest design.

METHODS

The participants were 61 junior students from a nursing college located in G province of South Korea. Data were collected between November 3 and 16, 2021, and analyzed using independent t-tests.

RESULTS

The experimental group-in which the artificial intelligence chatbot program was applied-did not show statistically significant differences in knowledge (t = -0.58, p = .567), clinical reasoning competency (t = 0.75, p = .455), confidence (t = 1.13, p = .264), and feedback satisfaction (t = 1.72, p = .090), compared with the control group; however, its participants' interest in education (t = 2.38, p = .020) and self-directed learning (t = 2.72, p = .006) were significantly higher than those in the control group.

CONCLUSION

The findings of our study highlighted the potential of artificial intelligence chatbot programs as an educational assistance tool to promote nursing college students' interest in education and self-directed learning. Moreover, such programs can be effective in enhancing nursing students' skills in non-face-to face-situations caused by the ongoing COVID-19 pandemic.

Evaluation of airborne total suspended particulates and heavy metals in anodizing and electroplating surface treatment process

This study is to evaluate exposure to harmful substances, such as particulate and heavy metals, by considering various factors, in anodizing and electroplating surface treatment process. Exposure evaluation studies on seven heavy metals (Cr, Zn, Ni, Pb, Cd, Al, and Ba) and total suspended particulates (TSP) were conducted. Heavy metals were analyzed using inductively coupled plasma mass spectrometry (ICP-MS). This study also checked the ventilation volume of the hood with a thermal anemometer. Measurement was conducted for 8 h and 8 days. The sample number, N, of the heavy metals and TSP was 107. Geometric mean (GM) of TSP during Cr plating process was 6.15(GSD, 3.35) mg/m3. GM of Cr during Cr plating was 1.86(GSD, 6.65) mg/m3. GM of TSP and heavy metals differences were statistically significant for each process and date variation. Average ventilation volume for all hoods ranged from 1.20 to 4.98 m3/s. In the hood 30 cm from bath, ventilation was 0.1 times lower. Increasing ventilation volume of the hood was the most influential factor, followed by machine operation time and workload. The high concentration was due to low ventilation suction flow. We can improve health to reduce exposure by resolving the fundamental cause of risk occurrence.

Thin Reinforced Ion-Exchange Membranes Containing Fluorine Moiety for All-Vanadium Redox Flow Battery

In this work, we developed pore-filled ion-exchange membranes (PFIEMs) fabricated for the application to an all-vanadium redox flow battery (VRFB) by filling a hydrocarbon-based ionomer containing a fluorine moiety into the pores of a porous polyethylene (PE) substrate having excellent physical and chemical stabilities. The prepared PFIEMs were shown to possess superior tensile strength (i.e., 136.6 MPa for anion-exchange membrane; 129.9 MPa for cation-exchange membrane) and lower electrical resistance compared with commercial membranes by employing a thin porous PE substrate as a reinforcing material. In addition, by introducing a fluorine moiety into the filling ionomer along with the use of the porous PE substrate, the oxidation stability of the PFIEMs could be greatly improved, and the permeability of vanadium ions could also be significantly reduced. As a result of the evaluation of the charge-discharge performance in the VRFB, it was revealed that the higher the fluorine content in the PFIEMs was, the higher the current efficiency was. Moreover, the voltage efficiency of the PFIEMs was shown to be higher than those of the commercial membranes due to the lower electrical resistance. Consequently, both of the pore-filled anion- and cation-exchange membranes showed superior charge-discharge performances in the VRFB compared with those of hydrocarbon-based commercial membranes.

Preventive Effect of M. cochinchinensis on Melanogenesis via Tyrosinase Activity Inhibition and p-PKC Signaling in Melan-A Cell

Whitening research is of particular interest in the cosmetics market. The main focus of whitening research is on melanogenesis inhibition through tyrosinase activity. The mechanism of melanogenesis is involved with tyrosinase activity and p-PKC signaling. In this study, we used Momordica cochinchinensis (Lour.) spreng, a tropical fruit found throughout Southeast Asia, to investigate the inhibitory effect of melanogenesis. M. cochinchinensis contains a high concentration of polyphenols, flavonoids, and unsaturated fatty acids, which might be related to antioxidant activity. This study aimed to determine whether M. cochinchinensis extracts inhibit melanin synthesis in melan-A cells by inhibiting tyrosinase activity and p-PKC signaling. M. cochinchinensis was divided into pulp and aril and extracted under various conditions, and it was confirmed that all pulp and aril extracts have high contents of both phenols and flavonoids. Melan-A cells were treated with PMA for three days to induce melanin synthesis. After PMA treatment, M. cochinchinensis extracts were added to cultured media in a dose-dependent manner. Melanin contents and MTS were used to determine the amount of melanin in live cells. M. cochinchinensis extracts were evaluated for their effects on tyrosinase activity and p-PKC signaling pathways by Western blotting. It was found that M. cochinchinensis extract treatment decreased the amount of melanin and suppressed p-PKC expression. Additionally, tyrosinase activity was reduced after M. cochinchinensis extract treatment in a dose-dependent manner. Therefore, it was concluded that M. cochinchinensis could be used in antimelanogenesis and functional cosmetic materials to improve whitening.

Real-time UVMS torque distribution algorithm based on weighting matrix

This study presents a real-time algorithm for even distributing the torque burden on the parallel manipulator with an autonomous underwater vehicle (AUV) through the cooperation of the AUV and manipulator. For the redundant resolution of the underwater vehicle manipulator system (UVMS), we used the weighting matrix of the weighted pseudo inverse for kinematic and dynamic modeling. We made dynamic and kinematic modeling using the force distribution characteristics of parallel manipulators. Using the parallel manipulator’s model, the weighting matrix was changed every second to share the manipulator torque with the AUV. The Taguchi method was used to reduce the calculation time for real-time calculation and to perform valve rotation operations with as little torque as possible even in an underwater environment where it is difficult to determine any cause of errors. To demonstrate the effectiveness of this algorithm, we experimented with valve rotation in water using the UVMS. Analysis of the experimental results revealed that the manipulator torque load was greatly reduced due to the AUV load distribution.

Neural correlates of episodic memory modulated by temporally delayed rewards

When a stimulus is associated with an external reward, its chance of being consolidated into long-term memory is boosted via dopaminergic facilitation of long-term potentiation in the hippocampus. Given that higher temporal distance (TD) has been found to discount the subjective value of a reward, we hypothesized that memory performance associated with a more immediate reward will result in better memory performance. We tested this hypothesis by measuring both behavioral memory performance and brain activation using functional magnetic resonance imaging (fMRI) during memory encoding and retrieval tasks. Contrary to our hypothesis, both behavioral and fMRI results suggest that the TD of rewards might enhance the chance of the associated stimulus being remembered. The fMRI data demonstrate that the lateral prefrontal cortex, which shows encoding-related activation proportional to the TD, is reactivated when searching for regions that show activation proportional to the TD during retrieval. This is not surprising given that this region is not only activated to discriminate between future vs. immediate rewards, it is also a part of the retrieval-success network. These results provide support for the conclusion that the encoding-retrieval overlap provoked as the rewards are more delayed may lead to better memory performance of the items associated with the rewards.

Controlling your contents with the breath: Interactive breath interface for VR, games, and animations

In this paper, we propose a new interface to control VR(Virtual reality) contents, games, and animations in real-time using the user’s breath and the acceleration sensor of a mobile device. Although interaction techniques are very important in VR and physically-based animations, UI(User interface) methods using different types of devices or controllers have not been covered. Most of the proposed interaction techniques have focused on screen touch and motion recognition. The direction of the breath is calculated using the position and angle between the user and the mobile device, and the control position to handle the contents is determined using the acceleration sensor built into the mobile device. Finally, to remove the noise contained in the input breath, the magnitude of the wind is filtered using a kernel modeling a pattern similar to the actual breath. To demonstrate the superiority of this study, we produced real-time interaction results by applying the breath as an external force of VR contents, games, and animations.

Review on the Computational Genome Annotation of Sequences Obtained by Next-Generation Sequencing

Next-Generation Sequencing (NGS) has made it easier to obtain genome-wide sequence data and it has shifted the research focus into genome annotation. The challenging tasks involved in annotation rely on the currently available tools and techniques to decode the information contained in nucleotide sequences. This information will improve our understanding of general aspects of life and evolution and improve our ability to diagnose genetic disorders. Here, we present a summary of both structural and functional annotations, as well as the associated comparative annotation tools and pipelines. We highlight visualization tools that immensely aid the annotation process and the contributions of the scientific community to the annotation. Further, we discuss quality-control practices and the need for re-annotation, and highlight the future of annotation.