Time Usage Research Articles

Peran Media Sosial Dalam Meningkatkan Atau Menghambat Produktivitas Mahasiswa

Social media has become an integral part of students' lives, offering various benefits yet also challenges that affect their productivity. This study aims to explore the role of social media in enhancing or hindering student productivity by examining positive aspects such as access to information, collaboration, and social networking, as well as negative impacts like distraction, decreased study quality, and a tendency to procrastinate. The analysis results indicate that social media can boost productivity when used for academic purposes, group discussions, and sharing educational information. However, social media can also become a hindrance when overused, leading to dependency or being utilized solely for entertainment. Factors such as usage duration, purpose, and time management play an important role in determining its positive or negative impacts. With a better understanding of the role of social media, students are expected to use it more wisely to support their academic productivity.

Long-Term Impact of Using Mobile Phones and Playing Computer Games on the Brain Structure and the Risk of Neurodegenerative Diseases: Large Population-Based Study.

Despite the increasing popularity of electronic devices, the longitudinal effects of daily prolonged electronic device usage on brain health and the aging process remain unclear. The aim of this study was to investigate the impact of the daily use of mobile phones/computers on the brain structure and the risk of neurodegenerative diseases. We used data from the UK Biobank, a longitudinal population-based cohort study, to analyze the impact of mobile phone use duration, weekly usage time, and playing computer games on the future brain structure and the future risk of various neurodegenerative diseases, including all-cause dementia (ACD), Alzheimer disease (AD), vascular dementia (VD), all-cause parkinsonism (ACP), and Parkinson disease (PD). All the characteristics of using mobile phones and playing computer games were collected through face-to-face interviews at baseline, and outcomes were extracted from the algorithmic combinations of self-reported medical conditions, hospital admissions, and death registries. In addition, a group of participants underwent magnetic resonance imaging (MRI) at follow-up. Cox regression and linear regression were performed. The study included over 270,000 participants for risk analysis, with a mean baseline age of approximately 55.85 (SD 8.07) years. The average follow-up duration was approximately 13.9 (SD 1.99) years. Lengthy mobile phone use was associated with a reduced risk of ACD (2-4 years: hazard ratio [HR] 0.815, 95% CI 0.729-0.912, P<.001; 5-8 years: HR 0.749, 95% CI 0.677-0.829, P<.001; >8 years: HR 0.830, 95% CI 0.751-0.918, P<.001), AD (5-8 years: HR 0.787, 95% CI 0.672-0.922, P=.003), and VD (2-4 years: HR 0.616, 95% CI 0.477-0.794, P<.001; 5-8 years: HR 0.729, 95% CI 0.589-0.902, P=.004; >8 years: HR 0.750, 95% CI 0.605-0.930, P=.009) compared to rarely using mobile phones. Additionally, lengthy mobile phone use was linked to a decreased risk of ACP (5-8 years: HR 0.747, 95% CI 0.637-0.875, P<.001; >8 years: HR 0.774, 95% CI 0.663-0.904, P=.001) and PD (5-8 years: HR 0.760, 95% CI 0.644-0.897, P=.001; >8 years: HR 0.777, 95% CI 0.660-0.913, P=.002) in participants older than 60 years. However, higher weekly usage time did not confer additional risk reduction compared to lower weekly usage of mobile phones. The neuroimaging analysis involved 35,643 participants, with an average duration of approximately 9.0 years between baseline and neuroimaging scans. Lengthy mobile phone use was related to a thicker cortex in different areas of the brain. Lengthy mobile phone use is associated with a reduced risk of neurodegenerative diseases and improved brain structure compared to minimal usage. Our research provides valuable background knowledge for future studies on the impact of modern electronic devices on brain health.

Investigation of the effect of internet addiction on cyberchondria

ABSTRACT This research was conducted to examine the effect of internet addiction on cyberchondria. The research is important to understand how today’s digital technologies contribute to health-related concerns and affect individuals’ perceptions of health. Quantitative research design was used in this research conducted in Konya, a metropolitan city in Turkey. The study was conducted using the convenience sampling method on 403 participants. In the research, ‘Personal Information Form’, ‘Internet Addiction Scale’ and ‘Cyberchondria Scale’ were used. The data were analyzed with the SPSS program. As an analysis method, upon determining that the data were normally distributed, t-test, ANOVA, Pearson correlation and simple linear regression analyzes were applied in independent groups. The majority of participants (69%) were female, 52.9% were between the ages of 18–27 and 53.8% were married. In terms of education level, 44.9% had a bachelor’s degree or higher, and 59.6% earned minimum wage or less. Among the occupational groups, the largest proportion was students (31.5%), and their daily internet use was mostly 2–3 hours (44.4%). Internet is most frequently used for social media (47.4%) and news/agenda follow-up (25.1%). Within the scope of the research, internet addiction varies significantly according to the participants’ age groups, education levels, professions, average daily internet usage time, and internet usage purposes; it was found that the cyberchondria levels of the participants showed significant differences according to the variables of income level, profession, daily internet usage time and internet use purpose. The research revealed a positive and significant relationship between the level of internet addiction and the level of cyberchondria. It has also been observed that internet addiction has a positive and significant effect on cyberchondria. These results show that cyberchondria tendencies become stronger with the increase in internet use among individuals.

Association Between Symptoms of Body Dysmorphia and Social Media Usage: A Cross-Generational Comparison.

Background: The rise of social media parallels a mental health epidemic. The effect of social media usage on rates and severity of body dysmorphic disorder is not well-understood. Objective: To determine if an association exists between social media engagement, body dysmorphia symptoms, and/or interest in cosmetic surgery in a demographically diverse cross-section of the U.S. adult population. Methods: In a Qualtrics platform-based survey study of the general U.S. adult population, responses to demographic information, social media activity questionnaire and the body dysmorphic disorder screening questionnaire, and interest in cosmetic surgery were collected. Descriptive statistics and a multivariate logistic regression model were carried out. Results: A total of 1,013 respondents completed the survey. The average age was 40.9 (SD, 14.8) years, 72% were women. Median time spent on social media (IQR) was 4 (2-7) h/day. Respondents who screened positive for symptoms of body dysmorphia had higher daily mean social media usage time (odds ratio [OR] 1.49), tend to be female (OR 2.17), younger (OR 0.97), identify as Caucasian (OR 1.65), and are more likely considering a cosmetic procedure in the next year (OR 2.98). Conclusion: This study demonstrates a positive association between daily social media usage, self-reported symptoms of body dysmorphia, and interest in cosmetic procedures.

Psychological Impact of Smartphone Use on Nomophobia Among Teenagers

Nomophobia has become an important mental health issue in the digital age. Excessive smartphone use can increase psychological dependence, known as nomophobia, which is the excessive fear or anxiety when one does not have access to their device. This research aims to analyze the psychological impact of smartphone use on nomophobia among adolescents aged 10 to 22 years. The method used was a systematic review of 10 selected journals that discussed the effects of reducing the duration of smartphone use on the level of nomophobia. The results showed that adolescents who used their cell phones for 1-5 hours per day had lower levels of nomophobia, cell phone addiction and loneliness compared to those who used their cell phones for 6-10 hours or more than 11 hours per day. This research provides important implications in designing strategies to reduce cell phone usage time to improve adolescents' mental well-being and recommends further research into the effectiveness of specific interventions.

Gendered time-budgeting, affective wellbeing, and its implication for cognitive health among older adults in India

Studying time usage can comprehensively reveal the pathway for affective wellbeing and cognitive outcomes among older adults. Using unit-level data on 4951 older adults from the World Health Organization’s Study on Global AGEing and Adult Health (WHO-SAGE-1), the paper aims to understand the plausible effect of time-weighted experienced wellbeing on gendered cognitive aging in India. Descriptive statistics and ordinary least squares regression were used to measure the net effects of emotions and experienced utility on cognitive outcomes. Older adults were found to spend the most time at work each day, with males spending 172 min and females spending 141 min. Self-care and household chores/caregiving were next in order. Cognition was positively associated with leisure activity-specific net affect among males and leisure and self-care activity-specific net affect among females. The time-specific effects of leisure and self-care activities were negatively associated with cognition. Strong gender segregation was observed in the type of activities performed and the time allocated to them. The study highlights that older adults with better net affect or satisfaction have better cognitive outcomes. The results suggest a focus on rejuvenating activities while designing programs and policies targeted at older people to promote active and healthy aging.

Clinical entity augmented retrieval for clinical information extraction

Large language models (LLMs) with retrieval-augmented generation (RAG) have improved information extraction over previous methods, yet their reliance on embeddings often leads to inefficient retrieval. We introduce CLinical Entity Augmented Retrieval (CLEAR), a RAG pipeline that retrieves information using entities. We compared CLEAR to embedding RAG and full-note approaches for extracting 18 variables using six LLMs across 20,000 clinical notes. Average F1 scores were 0.90, 0.86, and 0.79; inference times were 4.95, 17.41, and 20.08 s per note; average model queries were 1.68, 4.94, and 4.18 per note; and average input tokens were 1.1k, 3.8k, and 6.1k per note for CLEAR, embedding RAG, and full-note approaches, respectively. In conclusion, CLEAR utilizes clinical entities for information retrieval and achieves >70% reduction in token usage and inference time with improved performance compared to modern methods.

EyeCare Defender Predicting Vision Health from Digital Insights

In an era dominated by digital devices, prolonged screen time has become a significant factor influencing vision health. The "Eye Care Defender Predicting Vision Health from Digital Insights" project leverages advanced data analytics and machine learning to predict and mitigate vision health issues arising from excessive digital device usage. By collecting and analyzing data on screen time duration, intensity, and usage patterns from smartphones, tablets, and computers, this system aims to identify early signs of eye strain and digital eye syndrome. The predictive model developed in this project utilizes comprehensive data inputs to generate personalized recommendations for users.

Body-centered tetragonal grids for FDTD method with collocated field components and enhanced performance

Abstract We present an alternative finite-difference time-domain (FDTD) scheme that utilizes a body-centered tetragonal (BCT) grid, offering spatially collocated field components and significantly improving computational performance. The update equations for the BCT-FDTD maintain the simplicity and intuitiveness characteristic of the standard FDTD based on the Yee grid, with the key distinction being that the spatial derivative in one direction requires the use of four nearest neighbors instead of two. Our analyses of dispersion and stability reveal that the BCT-FDTD achieves a relaxed stability criterion, along with reduced anisotropy and lower phase velocity errors. Numerical tests indicate that, under equal sampling density conditions, the BCT-FDTD exhibits comparable memory usage and computation time to the standard FDTD. Moreover, our analysis establishes that when using conditions that ensure a phase velocity error of less than 1%, the BCT-FDTD requires approximately 5× less memory and achieves approximately 10× faster computation compared to standard FDTD. This improvement is expected to be even more pronounced in simulations involving anisotropic materials, thanks to the advantages provided by spatially collocated field components. Overall, we believe that the BCT-FDTD serves as a compelling alternative to the standard FDTD.

Usage of time multiplexing super resolution for imaging through scattering medium

Usage of time multiplexing super resolution for imaging through scattering medium

Importance of neural network complexity for the automatic segmentation of individual thigh muscles in MRI images from patients with neuromuscular diseases.

Segmentation of individual thigh muscles in MRI images is essential for monitoring neuromuscular diseases and quantifying relevant biomarkers such as fat fraction (FF). Deep learning approaches such as U-Net have demonstrated effectiveness in this field. However, the impact of reducing neural network complexity remains unexplored in the FF quantification in individual muscles. U-Net architectures with different complexities have been compared for the quantification of the fat fraction in each muscle group selected in the central part of the thigh region. The corresponding performance has been assessed in terms of Dice score (DSC) and FF quantification error. The database contained 1450 thigh images from 59 patients and 14 healthy subjects (age: 47 ± 17years, sex: 36F, 37M). Ten individual muscles were segmented in each image. The performance of each model was compared to nnU-Net, a complex architecture with 4.35 107 parameters, 12.8 Gigabytes of peak memory usage and 167h of training time. As expected, nnU-Net achieved the highest DSC (94.77 ± 0.13%). A simpler U-Net (5.81 105 parameters, 2.37 Gigabytes, 14h of training time) achieved a lower DSC but still above 90%. Surprisingly, both models achieved a comparable FF estimation. The poor correlation between observed DSC and FF indicates that less complex architectures, reducing GPU memory utilization and training time, can still accurately quantify FF.

Recent advances and application of liquid chromatography in pharmaceutical industry

Liquid chromatography (LC) and its associated techniques are essential in the pharmaceutical industry for optimizing drug formulations, ensuring product quality, and meeting regulatory standards. Thin Layer Chromatography (TLC) is widely used for rapid screening and chiral separations in early-stage development due to its simplicity and cost-effectiveness. High-Performance Liquid Chromatography (HPLC) remains the gold standard for routine analysis, offering high resolution and reproducibility for complex sample analysis and quantification of active pharmaceutical ingredients (APIs). Ultra-Performance Liquid Chromatography (UPLC) builds on HPLC, providing faster analysis, higher sensitivity, and greater efficiency, making it ideal for high-throughput testing. Supercritical Fluid Chromatography (SFC) is increasingly used for separating thermally labile and polar compounds, offering advantages in solvent usage and analysis time. This review will discuss the evolution of these chromatographic techniques and their critical role in optimizing pharmaceutical processes, ensuring product quality, and facilitating regulatory compliance throughout the drug development lifecycle.

Recycled used cooking oil (UCO) as a rejuvenator in high content reclaimed asphalt pavement (RAP) mixes: A life cycle assessment (LCA).

This study investigates the primary data collected at a used cooking oil (UCO) recycling facility to quantify its environmental impact when used as a rejuvenator in high content reclaimed asphalt pavement (RAP) mixes. Annual energy consumption data sets on transportation, storage, filtration, machinery, and purification are assessed using the life cycle assessment (LCA) methodology with the LCA software Simapro 9.4 to evaluate the influential parameters and processes in reducing emissions. Pearson correlations of the production process show a higher association of carbon footprint with two dominant recycling factors: (1) electricity consumption (r=0.89) and (2) fuel consumption for transportation (r=0.37). A comprehensive LCA conducted on asphalt pavements with various RAP contents shows that a 28.81% reduction of carbon emissions can be achieved during the construction phase by adding 60% rejuvenated RAP. However, the relative uncertainty around RAP moisture content at the time of usage and faster pavement deterioration over the service life when high RAP content is incorporated into asphalt mixes might hinder the environmental advantage of adding RAP during the maintenance phase. Non-properly treated, blended, and rejuvenated RAP can be susceptible to early cracking, thus resulting in increased periodic maintenance. Moreover, the break-even point of economic appraisal suggest over 50% RAP content is beneficiary even at the higher discount rates (12%). Conducted LCA and sensitivity analyses emphasise the importance of collecting primary data from recycling facilities and considering both the construction and maintenance phases for implementing effective sustainable strategies.

Progress of extracorporeal centrifugal pumps for mechanical circulatory supports.

This review traces the evolution of centrifugal blood pumps in mechanical circulatory support (MCS) systems. Initially met with concerns over blood damage and thrombus formation, centrifugal pumps have become crucial components in ventricular assist devices (VADs) and extracorporeal membrane oxygenation (ECMO) due to their simplified drive mechanisms and adaptability. This paper outlines three generations of centrifugal pump development: first-generation pumps with sealing components, second-generation pumps utilizing pivot bearings, and third-generation pumps employing contactless bearings. Each iteration addressed previous limitations, particularly regarding thrombus formation and durability. Current regulatory challenges surrounding the duration of pump use in MCS are examined, highlighting the discrepancy between approved usage times and clinical needs. This paper notes ongoing efforts to extend approved use periods, citing examples of pumps cleared for extended use in various jurisdictions. This historical perspective provides insights into the technological advancements that have enhanced the safety, efficacy, and durability of centrifugal blood pumps in MCS applications.

Developing a Passive Energy Consumption Reduction Solution

This study focuses on optimizing the energy efficiency of polyethylene tunnel greenhouses in Mediterranean climates using Design Builder and EnergyPlus software. The research examines the impact of different greenhouse orientations and opening configurations on energy consumption for heating and cooling. The east-west (90°) orientation was found to be the most effective in reducing cooling needs during summer while slightly increasing winter heating requirements. Various opening configurations were tested, including 0%, 20%, 40%, 60%, 80%, and 100%, with openings positioned at the bottom on one side and the top on the opposite side. The 20% opening configuration was identified as optimal for annual energy management. However, a monthly adaptive planning strategy was developed to further enhance energy efficiency. This planning involves keeping the greenhouse closed during winter, using 100% openings in summer, and 20% openings during transitional months. The proposed monthly planning resulted in a significant reduction in energy consumption, decreasing daytime usage by 27.3%, night time usage by 29%, and overall annual energy consumption by 27.6%. This research demonstrates that strategic orientation and adaptive opening management can substantially improve the energy efficiency of greenhouses in Mediterranean climates.

부모의 스마트폰 제공 의도와 영유아의 스마트폰 이용 장소가 미디어 과의존에 미치는 영향

This study was conducted by reanalyzing the results of the questionnaire used in “JeongWon Lee, Wonsoon Park, Jiwon Eom (2021) A Study on Policy Measures to Optimize the Media Use of Infants and Young Children, Korea Institute of Child Care and Education.” Through this study, the researchers analyzed the impact of parents' intention to provide smartphones and the places where infants and young children use smartphones on media use time and media overdependence. This study classified parents' intentions to provide smartphones for their young children into four categories: limited provision, child initiative, parent initiative, and overall provision groups. In addition, smartphone use by location could be divided into three categories: low use, high use, and residential use groups. Overall, young children spent more time using smartphones on weekends than on weekdays. The time spent using smartphones was generally higher in the group that provides smartphones according to parents' intention to provide smartphones, the group that parents determine the need for themselves, the cluster that children demand, and the cluster that provides smartphones in a limited manner. In terms of usage by location, the clusters were generally high usage, residential usage, and low usage. In the classification of smartphone overdependence by intention to provide, it was found that the group of child initiative group had a lower tendency to be smartphone overdependent than the limited provision group, which had less usage time than the group of child initiative group.

청소년의 스마트폰 사용 시간과 식생활 행태 관련 요인 간의 관계: 2022~2023년 한국 청소년 건강행태조사 자료를 활용하여

This study analyzed the association between smartphone usage time and dietary behavior, demographic characteristics, physical activity, and mental health among adolescents. Data from 101,051 adolescents participating in the 18th (2022) and 19th (2023) Korea Youth Risk Behavior Surveys were analyzed. Participants were classified into two groups based on daily smartphone usage: normal (&lt;5 hours/day) and risk (≥5 hours/day). Adjusted odds ratios (AORs) were calculated using a complex samples logistic regression after adjusting for demographic characteristics. The risk group had lower frequencies of fruit consumption, water intake, and breakfast eating consumption but higher frequencies of sweetened beverage and fast food consumption compared to the normal group (p&lt;0.001). Group consuming sweetened beverages more than five times per week were significantly more likely to experience sadness and despair (AOR= 1.20, 95% CI= 1.10-1.31) and loneliness (AOR= 1.35, 95% CI= 1.25-1.46) compared to those consuming them less than once per week (p&lt;0.001). Similarly, consuming fast food more than five times per week significantly increased the odds of sadness and despair (AOR= 1.40, 95% CI= 1.28-1.54), loneliness (AOR= 1.34, 95% CI= 1.22- 1.47), and generalized anxiety disorder (AOR= 1.49, 95% CI= 1.32-1.68). Additionally, group consuming breakfast only 1-2 times per week had significantly higher odds of sadness and despair, suicidal ideation, suicide planning, suicide attempts, and loneliness compared to those consuming it five times per week (p&lt;0.001). In conclusion, reducing smartphone usage time among adolescents may be an effective strategy not only for fostering healthy dietary habits but also for improving physical and mental health.

I-PACE 모델에 기반한 간호대학생의 스마트폰 사용 조절 시도 경험

Objectives This study is a qualitative descriptive study that attempted to deeply explore nursing students’ experiences of trying to control their smartphone usage time based on the I-PACE model from the perspectives of personal characteristics and the interaction between emotions and behaviors. Based on the integrated aspects of the I-PACE addiction model, this study attempted to identify vulnerable factors contributing to smartphone addiction in nursing students in order to control long-term smartphone usage time and to contribute to the utilization of evidence for intervention methods for comprehensive intervention strategies to control smartphone usage time. Methods According to the research purpose, 15 nursing students who have used smartphones for more than 5 years and have tried to control their smartphone usage time were selected through purposive sampling from October to December 2023. Data were collected through focus group interviews and individual in-depth interviews, and this is a qualitative descriptive study using content analysis. Results The results of the nursing students’ experience of trying to control their smartphone usage time were derived into three themes and seven subthemes. First, the category of ‘beginning of new awareness of smartphone moderation’ was diagrammed as ‘feelings before and after smartphone use’ and ‘use as a tool of escape’. Second, the category of ‘promoting smartphone moderation behavior in various dimensions’ was diagrammed as ‘environmental settings’ and ‘critical evaluation and judgment of smartphone use’. Third, the category of ‘continuous mediation of self-control and responsibility’ was diagrammed as ‘forming stable lifestyle habits’, ‘improving psychological resilience and adaptability’, and ‘freedom found through delayed gratification’. During the process of trying to control their smartphone usage time, the research participants acknowledged their smartphone dependency and formed critical thinking through repeated failures in moderation. After acknowledging that they could not control their smartphone usage with willpower alone, they prioritized correcting their lifestyle habits and learning constructive stress methods beyond simply trying to control their smartphone usage. This became the beginning of postponing immediate rewards and consciously controlling their impulses. Conclusions Based on the individual emotional aspect of the I-PACE model, as an intervention method to resolve smartphone addiction, the emotions of nursing students are carefully assessed, including states such as stress, loneliness, and depression according to the individual characteristics of nursing students. Based on the cognitive and practical aspects of the I-PACE model, cognitive factors such as expectations and beliefs of nursing students are closely examined to identify cognitive factors that may affect smartphone dependence. Cognitive behavioral intervention is provided to correct irrational beliefs and cognitive biases related to smartphones, strategies are provided to consciously control internal impulses, and the ability to monitor one's own smartphone usage patterns is expanded. In the interactive and integrated aspect of the I-PACE model, in order to control long-term smartphone usage time rather than short-term environmental settings, it is necessary to identify individual vulnerabilities that contribute to smartphone addiction in nursing students and to establish a constructive stress coping method that enhances psychological resilience in daily life.

Efficient quantum circuit contraction using tensor decision diagrams

Simulating quantum circuits efficiently on classical computers is crucial given the limitations of current noisy intermediate-scale quantum devices. This paper adapts and extends two methods used to contract tensor networks within the fast tensor decision diagram (FTDD) framework. The methods, called iterative pairing and block contraction, exploit the advantages of tensor decision diagrams to reduce both the temporal and spatial cost of quantum circuit simulations. The iterative pairing method minimizes intermediate diagram sizes, while the block contraction algorithm efficiently handles circuits with repetitive structures, such as those found in quantum walks and Grover’s algorithm. Experimental results demonstrate that, in some cases, these methods significantly outperform traditional contraction orders like sequential and cotengra in terms of both memory usage and execution time. Furthermore, simulation tools based on decision diagrams, such as FTDD, show superior performance to matrix-based simulation tools, such as Google tensor networks, enabling the simulation of larger circuits more efficiently. These findings show the potential of decision diagram-based approaches to improve the simulation of quantum circuits on classical platforms.

Variants of RSA and Rabin Cryptosystems modulo p^rq^s

Cryptography is the technique to protect sensitive information from unauthorized persons by encryption. Cryptographers have invented various systems of cryptography to make it befitting. In the age of modern science, the use of mathematical theories has added a new dimension to cryptography. Prime factorization-based cryptography is widely used and effective. In 1977, Rivest, Shamir, and Adlerman proposed the first practical public key cryptosystem based on the prime factorization of large numbers known as the RSA cryptosystem. Later in 1979, Michael Oser Rabin developed a technique based on prime-factorization known as Rabin Cryptosystem. Several variants of these systems have been developed further by many famous mathematicians and computer scientists, aiming to increase security, reduce cost, time, and memory usage, and enhance overall performance. Tsuyoshi Takagi and Hugh C. Williams proposed such two famous variants. In this paper, we have first analyzed the traditional cryptosystems and existing variants. Identifying the security strength and field of improvement of these systems and their variants, we have proposed two new variants. The encryption-decryption techniques are described by employing them in several applications. The effectiveness of the proposed variants is demonstrated by a comparative analysis of these variants with others. Numerical experiments show that the proposed Rabin’s variant performs almost the same as the base algorithm. However, the proposed variant of RSA algorithm reduces computational time significantly, approximately 91% reduction from traditional RSA and 90% reduction from multi-prime RSA. J. Bangladesh Math. Soc. 44.2 (2024) 01–16