Time Of Day Research Articles

Assessment and treatment of multiply maintained problem behavior dependent on the time of day

ABSTRACT Purpose The current study evaluated treatments derived from two functional analyses (FA) for a 7-year-old student with autism. Method The FA assessment was conducted at different times of the day and each revealed different functions in the morning and the afternoon. Results The morning FA suggested that problem behavior was maintained by positive reinforcement in the form of attention, whereas the afternoon FA showed that problem behavior was maintained by both positive reinforcement in the form of attention and negative reinforcement in the form of escape from task demands. Discussion results of this study suggested that differential reinforcement for appropriate behavior in a multiple schedule arrangement effectively reduced multiply maintained problem behavior across the school day.

Urban street clusters: unraveling the associations of street characteristics on urban vibrancy dynamics in age, time, and day

Understanding urban vibrancy has been considered crucial to promoting human activities and interactions in public open spaces. Recent advancements in urban big data have facilitated the potential to understand and measure vibrancy patterns throughout cities. While streets are considered the center stage of human activity, previous studies have often overlooked their multifaceted nature and their association with urban vibrancy. In this study, we incorporate multi-source big data and combine a set of features that comprehensively describe the scale, function, and topology of street segments in two Seoul districts: Jung-gu and Gangnam-gu. Using these features, we employ a machine learning clustering technique to classify them into five distinct typologies. Then, with street-level aggregated mobile phone tracking data, we investigate whether street typology characteristics are associated with urban vibrancy with respect to age groups, time of day, and day types (weekends/weekdays). The results show varying relationships between street characteristics with age-, time- and day-vibrancy measures by the identified street typology. Further, we contrast the results of the two districts to evaluate urban vibrancy differences in organic and planned urban layouts. This study enables a more nuanced understanding of urban streets to better comprehend their impact on people’s use of street space. The derived novel insights could assist planners and designers to better pinpoint street management solutions for different age- and time-dependent needs based on the complexities in urban vibrancy dynamics.

B-023 Workflow evaluation of the new Siemens Atellica CI Analyzer

Abstract Background The Atellica® CI Analyzer, Model 1900 is an integrated clinical chemistry and immunoassay analyzer that has the same user interface, general workflow, and planned test menu to that of the larger Atellica® Solution. Atellica CI Analyzer also shares the same reagents and consumables as the Atellica Solution. The purpose of this study was to evaluate workflow performance of the Atellica CI Analyzer in a routine-like clinical laboratory setting. Methods The study was conducted at four international laboratory facilities over a four-month period. Basic throughput of the Atellica CI Analyzer was evaluated at each site by testing quality control (QC) and remnant anonymized patient samples using an 8:2 mixture of chemistry (ion selective electrolytes [IMT], clinical chemistry analytes) and immunochemistry assays. Additionally, the impact of interrupting routine testing for STAT high-sensitivity cardiac troponin samples was also evaluated. Daily, weekly, and monthly maintenance activities were observed, and data collected through direct observations, time and motion studies, and system run logs. Results The Atellica CI Analyzer aspirated patient samples in as little as two minutes (mins) with the time to first result for the mixed assay worklist ranging from 1 to 12 mins from the time of first barcode read. Across the four sites, the time to last result for the mixed assay worklist (average n=495 test results per site) ranged from 52 to 65 mins. The average turn around time (TAT) for high-sensitivity troponin was 9 mins from barcode read. Daily maintenance and QC activities for the Atellica CI Analyzer are comprised of both automated and manual activities. The average daily maintenance hands-on time was 3.6 min, ranging from 1.6 to 6.4 mins across the four sites. Daily QC preparation required <5 mins of hands-on time. The total average hands-on time to complete weekly maintenance for the Atellica CI Analyzer was 7.5 min. Conclusions The Atellica CI Analyzer demonstrated consistent system performance across all four study sites. Implementation of the Atellica CI Analyzer has the potential to increase laboratory efficiency given the minimal hands-on time required for daily and weekly maintenance activities and short TATs.

Time of day affects MrgD-dependent modulation of cardiomyocyte contractility.

The renin-angiotensin system (RAS) is composed of a series of peptides, receptors, and enzymes that play a pivotal role in maintaining cardiovascular homeostasis. Among the most important players in this system are the angiotensin-II and angiotensin-(1-7) peptides. Our group has recently demonstrated that alamandine (ALA), a peptide with structural and functional similarities to angiotensin-(1-7), interacts with cardiomyocytes, enhancing contractility via the Mas-related G protein-coupled receptor member D (MrgD). It is currently unknown whether this modulation varies along the distinct phases of the day. To address this issue, we assessed the ALA-induced contractility response of cardiomyocytes from mice at four Zeitgeber times (ZTs). At ZT2 (light phase), ALA enhanced cardiomyocyte shortening in an MrgD receptor-dependent manner, which was associated with nitric oxide (NO) production. At ZT14 (dark phase), ALA induced a negative modulation on the cardiomyocyte contraction. β-Alanine, an MrgD agonist, reproduced the time-of-day effects of ALA on myocyte shortening. NG-nitro-l-arginine methyl ester, an NO synthase inhibitor, blocked the increase in fractional shortening induced by ALA at ZT2. No effect of ALA on myocyte shortening was observed at ZT8 and ZT20. Our results show that ALA/MrgD signaling in cardiomyocytes is subject to temporal modulation. This finding has significant implications for pharmacological approaches that combine chronotherapy for cardiac conditions triggered by disruption of circadian rhythms and hormonal signaling.NEW & NOTEWORTHY Alamandine, a member of the renin-angiotensin system, serves critical roles in cardioprotection, including the modulation of cardiomyocyte contractility. Whether this effect varies along the day is unknown. Our results provide evidence that alamandine via receptor MrgD exerts opposing actions on cardiomyocyte shortening, enhancing, or reducing contraction depending on the time of day. These findings may have significant implications for the development and effectiveness of future cardiac therapies.

Efficient Energy Management and Cost Optimization using Multi-objective Grey Wolf Optimization for EV charging/ discharging in Microgrid

The depletion of conventional energy sources coupled with the rising demand for electric vehicles (EVs) has significantly underscored the necessity for electric vehicle supply equipment (EVSE) with advanced energy supply management within microgrids. Effective energy management of EVs and EVSEs is imperative to satisfy EV owners and stabilize microgrids. This paper introduces multi-objective grey wolf optimization (MOGWO) to optimize EVSE and EV charging costs. MOGWO achieves substantial cost savings through dynamic pricing based on time of day, state-of-charge and hour-based scheduling which promotes off-peak charging thereby enhancing system efficiency and reducing costs. The algorithm also provides flexibility for trip interruptions and outperforms other optimization algorithms in minimizing EV charging/discharging costs by achieving reductions of up to ₹488 and obtaining average grid efficiency up to 76.41% during charging and 87.41% during discharging. Integrating Vehicle-to-Grid and Grid-to-Vehicle systems enhances microgrid resilience and delivers economic benefits to EV owners. The cost optimization for EV charging/discharging has been executed using MATLAB 2023a software to determine the most cost-effective charging paths by considering energy availability and grid conditions. The evolving sustainable energy landscape combined with MOGWO paves the way for smarter and more resilient microgrids in the era of electrified transportation.

Evaluation of Direct Sunlight Availability Using a 360° Camera

One important aspect to consider when buying a house or apartment is adequate solar exposure. The same applies to the evaluation of the shadowing effects of existing buildings on prospective construction sites and vice versa. In different climates and seasons, it is not always easy to assess if there will be an excess or lack of sunlight, and both can lead to discomfort and excessive energy consumption. The aim of our project is to design a method to quantify the availability of direct sunlight to answer these questions. We developed a tool in Octave to calculate representative parameters, such as sunlight hours per day over a year and the times of day for which sunlight is present, considering the surrounding objects. The apparent sun position over time is obtained from an existing algorithm and the surrounding objects are surveyed using a picture taken with a 360° camera from a window or other sunlight entry area. The sky regions in the picture are detected and all other regions correspond to obstructions to direct sunlight. The sky detection is not fully automatic, but the sky swap tool in the camera software could be adapted by the manufacturer for this purpose. We present the results for six representative test cases.

Physical Activity Participation By Intensity & Time Of Day Among Children

Physical Activity Participation By Intensity & Time Of Day Among Children

Livestock guarding dogs shape activity patterns of sympatric mesocarnivores in sheep ranches of the Patagonia region

Predation of livestock by wild carnivores is a source of human-wildlife conflict. Livestock Guarding Dogs (LGDs) are one of the most effective non-lethal methods used. LGDs could impact wildlife due to their possible top predator role; their effect on mesocarnivores has been studied mainly in terms of space use, however, temporal effects may also exist. Our study sought to determine the possible effects of LGD presence on the activity patterns of the native foxes Lycalopex griseus and L. culpaeus in southern Chile. Activity patterns were estimated from fox detections with camera traps set on ranches with and without LGDs in Isla Riesco, Magallanes region, Chile, between 2016 and 2018. We quantified the activity patterns of each fox species in presence/absence of LGDs, and under different conditions including breeding vs non-breeding season, moon phase and vegetation cover. Both species modified their daily activity pattern, avoiding times of day of high LGD activity; nevertheless, these modifications did not change the temporal interaction between the native foxes. Activity patterns of foxes without LGDs did not differ from those in natural areas. The effect of LGDs on fox activity patterns was stronger than other ecological variables (breeding season, moon phase or vegetation cover). Since LGDs change the activity patterns of foxes, they cannot be seen as a totally innocuous predation control tool; however, carnivores’ temporal avoidance of areas with a fear-evoking agent like LGDs would result in fewer livestock-predators encounters, thus reducing sheep predation risk. LGDs appear to exert non-lethal effects upon carnivores that would contribute to reduced predation rates and may help decrease producers’ economic losses, as well as the retaliatory hunting of wild carnivores. Thus, our results support that LGDs could be contributing to the co-existence with native predators in areas destined for livestock production.

A Proposed Method for Assessing the Spatio-Temporal Distribution of Carcharhinus melanopterus (Quoy and Gaimard, 1824) in Shallow Waters Using a UAV: A Study Conducted in Koh Tao, Thailand

In this study, we propose a method for assessing the temporal and spatial distribution of Carcharhinus melanopterus in shallow waters using unmanned aerial vehicles (UAVs). Aerial surveys were conducted in Tien Og Bay (Koh Tao, Thailand) thrice daily (morning, afternoon, evening) along a 360 m transect at a 30 m altitude. Environmental factors, including cloudiness, sea conditions, wind, tide, and anthropogenic disturbance, were recorded for each time slot. We developed a Python/AppleScript application to facilitate individual counting, correlating sightings with GPS data and measuring pixel-based length. Abundance varied significantly across time slots (p < 0.001), with a strong morning preference, and was influenced by tide (p = 0.040), favoring low tide. Additionally, abundance related to anthropogenic disturbance (p = 0.048), being higher when anthropogenic activity was absent. Spatial distribution analysis indicated time-related, sector-based abundance differences (p < 0.001). Pixel-based length was converted to Total Length, identifying juveniles. They exhibited a strong sector preference (p < 0.001) irrespective of the time of day. Juvenile abundance remained relatively stable throughout the day, constituting 94.1% of afternoon observations. Between 2020 and 2022, an underwater video survey was conducted to determine the sex ratio of the individuals. Only females and juveniles were sighted in the bay.

Does sedentary time and physical activity predict chronic back pain and morphological brain changes? A UK biobank cohort study in 33,402 participants

BackgroundThe relationship between sedentary time, physical activity, and chronic back pain remains unclear. The study aims to investigate whether sedentary time and physical activity predict chronic back pain and morphological brain changes.MethodsThis cohort study recruited adults aged 37–73 years enrolled between 2006 and 2010, with follow-up until 2014. The total cohort comprised 33,402 participants (mean age: 54.53). Data were collected on daily sedentary time, physical activity, lifestyle factors, and health outcomes.ResultsAfter nearly 8-year follow-up, 3,006 individuals (9.00%) reported chronic back pain in total. Individuals with daily sedentary time exceeding 6 h had a 33% higher risk of chronic back pain compared to those with sedentary time of 2 h or less (RR, 1.33, 95%CI, 1.17–1.52). Sedentary time was also associated with decreased grey matter volume in several brain regions, including bilateral primary somatosensory cortex (S1), secondary somatosensory cortex, putamen, primary motor cortex (M1), insula, hippocampus, amygdala, as well as right supplementary motor area, left medial frontal cortex, and right anterior cingulate cortex (FDR-corrected p-value < 0.05). Compared to individuals who sat for more than 6 h with light physical activity, those engaging in moderate physical activity with sedentary time of 2 h or less (RR, 0.71, 95%CI, 0.52–0.99) exhibited a significant decrease in chronic back pain risk. In addition, replacing sedentary time with equivalent amount of physical activity also demonstrated a reduction in the risk of chronic back pain (RR, 0.87, 95%CI, 0.77–0.99) and increased the reginal grey matter volumes including the amygdala, insula, M1, putamen and S1.ConclusionsProlonged sedentary time is associated with heightened risks of chronic back pain and deterioration in brain health.

Passive sensing of smartphone use, physical activity and sedentary behavior among adolescents and young adults during the COVID-19 pandemic.

The research that links excessive screen time to adverse health outcomes is based on self-reported screen use. Few studies have documented how passively-sensed smartphone and app use relate to health behaviors like activity and sitting. Furthermore, they have not considered that daily fluctuations in smartphone/app use may have different relationships to these behaviors than a person's usual smartphone/app use. This study evaluated whether physical activity or sedentary (sitting) behavior are associated with either smartphone screen time or specific smartphone app use by adolescents and young adults during the COVID-19 pandemic. Adolescents and young adults aged 13-29 years wore activPAL4 micro activity monitors while their smartphones logged daily screen time and app use durations for nine days. Data were collected in 2020-2021 and analyzed in 2022-2023. Participants (N = 125) had a mean (SD) age of 19.7 (4.3) years. Participants' usual smartphone screen time was negatively associated with daily step counts. Daily deviations in smartphone screen time were negatively associated with daily step counts and moderate-vigorous physical activity durations. Time spent on Instagram, YouTube and, to a lesser extent, TikTok were linked with reduced activity levels. Daily sedentary behavior was not associated with usual or daily screen time. Interventions to promote physical activity during the transition into adulthood may benefit from limiting excessive smartphone screen time. Specific intervention targets could include limiting use of apps with infinite scrolling feeds algorithmically tuned to maintain user engagement, such as Instagram, YouTube and TikTok.

Vegetal/digital: Photogrammetry point-clouds of Australian flowers

Arising out of the heightened sensory perceptions of extended lockdown, this creative investigation began with contemplation of flowering street-trees. Through 262 days of lock down, residents of Melbourne retreated to the hyper-local, often reinforced by a 5-km travel bubble and a one-hour daily time limit outdoors. The sublime ephemeral springtime flowers of street-trees were amplified by the extreme sensory and social constraints of social distancing. Drawing us into a suspended moment of slow encounter, we attuned to the contained glowing pulse of plants. The works were created using photogrammetry, a technique for generating 3D models from a large set of photographs taken from all angles of the botanical specimen. Whilst the point-cloud models remain the central artefact of vegetal/digital, it has been presented in a range of formats throughout 2022–23, including multichannel video loops, augmented reality, webXR, gestural interactive works and still prints. This work invites an embodied experience of attuning to both the vegetal and the digital. This is consistent with my alignment with queer and autistic politics, of siding with the object. Increasingly, queer cultural practices are employing new materialism and posthumanism to interrogate the agency of things and the culturally constituted hierarchies of objects and subjects. The reconfiguration of embodied relations is necessary in order to reconceive a viable future.

Leaf gas exchange, water use, and yield of Marula (S. birrea) and Kei Apple (D. caffra): South African indigenous fruit trees with domestication potential

Conventional crop production is expected to decline in the future in sub-Saharan Africa due to the rising costs of inputs, soil degradation, and increasing water scarcity related to climate variability and change. South Africa has more than 30 species of indigenous fruit trees that are adapted to grow under harsh conditions, yet these species are currently underutilized. Their cultivation is constrained by the lack of detailed ecophysiological information required to develop effective management strategies that optimize tree performance. In this study we investigated how two species with domestication potential namely Marula (Sclerocarya birrea) and Kei apple (Dovyalis caffra) responded to climate and soil factors over a period of two years (2019–2021). Photosynthesis, transpiration, and yield were quantified for mature trees growing in experimental orchards in the Mpumalanga Province of South Africa. Leaf gas exchange data were collected at selected intervals during the growing season using an infrared gas analyser while whole tree transpiration rates were quantified using the heat ratio method of monitoring sap flow. These data were used to parameterize a big leaf Penman-Monteith (PM) model to estimate the transpiration dynamics of individual trees at the daily time step. S. birrea's transpiration responded strongly to both climatic and soil water content variations while the water use of D. caffra was driven mostly by climatic factors. Transpiration rates averaged 0.30 L/m2 of leaf area for S. birrea while that of D. caffra was around 0.45 L/m2. Both species exhibited significant alternate bearing with yield of individual trees fluctuating by more than 50 % between successive years. For the 2019/20 season, water productivity (grams of fruit per litre of water transpired) varied between 6.2 and 17.4 g/L for S. birrea and between 24.3 and 41.7 g/L for D. caffra. Whole tree transpiration by both species were accurately predicted using the PM model albeit with different parameters for each species. This study demonstrates that a simple PM model can accurately estimate the water requirements of these species in other growing regions.

Comparison of Air Fare Prediction Using Various Machine Learning Techniques

Due to a rise in air service links globally, air travel is now a popular, significant, and faster form of transportation. Airline rates are thought to be impacted by several factors and are subject to frequent fluctuation, making estimation of these rates a challenging but essential task. The airline uses a pricing structure for the plane ticket. The cost of airline tickets varies based on the time of day, according to the survey. Even the weekends, the tourist season, and the pageant season have an impact on this. An aircraft ticket's price is influenced by several different elements. The buyer only has access to a limited amount of information, which is truly insufficient to estimate flight pricing, but the seller is aware of all the requirements. In this study, we use machine learning regression approaches such as K Nearest Neighbourhood, Decision Tree, and Random Forest to estimate flight fares based on basic data including source, destination, departure time and date, arrival timings, halts, and airline type. The results of the investigation show that the Random Forest Regression Model yields extremely optimal results.

Workplace Violence against Emergency Medical Services (EMS): a prospective 12-month cohort study evaluating prevalence and risk factors within a large, multistate EMS agency

ABSTRACT OBJECTIVES To determine the prevalence and associated risk factors of workplace violence (WPV) experienced by emergency medical services (EMS) clinicians across a large, multistate ground/air EMS agency. METHODS We used a prospective cohort study design from 12/1/2022-11/30/2023. A checkbox was added within the electronic medical record (EMR) asking staff to indicate whether WPV occurred. Patient characteristics, encounter (run), and crew factors were abstracted. Potential risk factors for WPV were assessed using logistic regression, with the occurrence of any form of violence as the primary outcome of interest. Models were both univariable, assessing each risk factor individually, and multivariable assessing all risk factors together to identify independent factors associated with higher risk of WPV. Multivariable model results were reported using odds ratios (aORs) and 95% confidence intervals. RESULTS A total of 102,632 runs were included, 95.7% (n= 98,234) included checkbox documentation. There were 843 runs (0.86 per 100 runs, 95% CI 0.80-0.92) identified by EMS clinicians as WPV having occurred, including verbal abuse (n= 482), physical assault (n= 142), and both abuse and assault (n= 219). Risk factors for violence included male patient gender (aOR 1.45, 95% CI 1.24 – 1.70, p <0.001), Richmond Agitation-Sedation Scale (RASS) >1 (aOR 16.97, 95% CI 13.71 – 21.01, p < 0.001), and 9-1-1 runs to include emergent (P1; aOR 1.75, 95% CI: 1.17-2.63, p = 0.007) and urgent (P2; aOR 1.64, 95% CI 1.08-2.50, p = 0.021) priority, compared to P3/scheduled transfer or P4/trip requests. Factors associated with lower risk for violence included older patients (aOR per 10 years = 0.95, 95% CI 0.91 - 0.98, p = 0.007) and run time of day between 0601-1200 hours compared to 0000-0600 hours (aOR 0.67, 95% CI 0.51 - 0.88, p = 0.004). Only 2.7% of violent runs captured through the EMR were reported through official processes. CONCLUSIONS Verbal and/or physical violence is recognized in nearly 1% of EMS runs. We recommend prioritizing WPV prevention and mitigation strategies around identified risk factors and simplifying the WPV reporting process in order to reduce staff administrative burden and encourage optimal capturing of violent events.

The landform Deformation at the Iraq-Iran Border due to Earthquakes in the Period (2017-2018)

The study targets to assess the potential of Interferometric Synthetic Aperture Radar (InSAR) in detecting ground distortion caused by earthquakes. The inSAR technique integrates Synthetic Aperture Radar (SAR) and interferometry to reveal the slightest changes on the earth's surface through a specified period, impregnable to climate or time of day. The research analyses some scholarly articles to demonstrate the interest of InSAR in examining earthquakes and their outcome. These articles demonstrate the practical application of InSAR in enhancing fault slip analysis, ground deformation assessment, and early post-seismic changes in earthquakes. InSAR is beneficial with measurements from other tools, such as GPS and time series analysis, but it still offers valuable insights into earthquake characteristics and associated effects. The insights from these methodologies can help devise solutions to mitigate the impacts of earthquakes. In addition, the paper presents information about three earthquake swarm events and their corresponding fault types. The first event occurred on November 12th, 2017, while the second happened on November 25th, 2018. Despite their differences in magnitude and location, the second event was associated with a strike-slip fault. InSAR provides extensive practical applications, from natural hazard monitoring to infrastructure projects and topographic mapping.

Association of sedentary behavior and physical activity with occurrence of signs and symptoms in participants of a cardiac rehabilitation program

Sedentary behavior (SB) is associated with health impairments, while physical activity (PA) has been a protective factor. It is unclear whether SB and PA are associated with occurrence of signs and/or symptoms (SS) during cardiac rehabilitation program (CRP) exercise sessions. The objective was to evaluate the association between SB and PA with occurrence of SS. Was included 48 patients from a CRP program (64.7 ± 10.4 years-old). Daily time and % of time of SB and weekly time in moderate-to-vigorous-intensity [MVPA], % of MVPA time, steps/day, and steps/minute were accelerometer-measured. Patients were followed-up during 24 CRP sessions, for accompaniment of SS. Age, sex, and comorbidities (hypertension, diabetes, dyslipidemia, obesity) were covariates. Log-transformed values of SB, MVPA and steps/day were also analyzed. As results, 43.7% (n = 21) of participants presented occurrence of signs, 62.5% (n = 30) presented occurrence of symptoms, and 81.2% (n = 39) present occurrence of SS. In fully adjusted model, % of time in MVPA (β: −0.449,p = 0.045) and steps/minute (β: −0.244,p = 0.026) were inversely associated with occurrence of symptoms. No association was observed between SB and PA and occurrence of signs. The occurrence of symptoms and SS among CRP participants was directly associated with SB and inversely associated with variables of PA.

Predicting NEPSE Index: An ARIMA-Based Model

Purpose: This research aims to employ the Auto Regressive Integrated Moving Average (ARIMA) approach to forecast the Nepal Stock Exchange (NEPSE) index.Methods: Daily univariate time series data were taken from the NEPSE website and other sources for 27 years for a total 6143 daily time series data starting in 1997. The presence of unit roots was identified through an Augmented Dickey-Fuller (ADF) test, which ensures stationarity in data. Thereafter, estimation and evaluation of AR (autoregressive), MA (moving average), and ARIMA models were carried out.Results: The study reveals that the ARIMA (2,1,1) model is well fitted in predicting the NEPSE index, indicating its ability to capture temporal dependence and trends that exist within the data.Conclusion: It concludes the temporal dynamics of series highlighting both the short-term impacts of past shocks and longer-term adjustment towards equilibrium. The research work supports the efficacy of model in capturing and predicting the behaviour of NEPSE index, thereby adding in informed decision making and future projections based on proposed statistical foundations.

Urban family with minor children: resources, moral guidelines and social adaptation of working parents. Part one

The first part of the article presents the results of studying the daily activities of working parents in the field of caring for minor children and their upbringing. Data from monitoring studies of the daily activities and time budget of urban residents carried out during 1986-2020 were used. The composition of families with children is considered and the resource characteristics of parents are analyzed, which turned out to be very similar for fathers and mothers. The relationship of parents' time spent on caring for children and their upbringing with parents' belonging to fathers and mothers, with their age, level of education, religious identity and income level in parents' families, as well as with some value orientations of fathers and mothers, is investigated. The analysis showed that the objective picture of working parents using time resources for activities with children does not agree with their subjective opinion that “activities with their childre n, their upbringing is the most important thing in the life of both spouses”. At the same time, most working fathers and mothers are satisfied with the time spent both on caring for children and on their upbringing as time resources. The characteristics of the provision of fathers and mothers with other resources do not affect their satisfaction with time spent. There is a direct relationship between satisfaction with the time spent on raising children and parents' satisfaction with life in general. An analysis of the moral guidelines of parents, which are the moral basis for the process of socialization of minor children in the family, has shown that more than half of the moral qualities related to virtues are the norm for the vast majority of fathers and to a somewhat lesser extent for mothers. At the same time, there is a tendency to blur parents' ideas about qualities-virtues and anti-virtues as a norm and deviation from it. In addition, a trend is emerging in which, judging by estimates, a considerable part of parents do not see a positive life prospect for their children, in terms of their social adaptation, if children in life are guided by the same virtues as the parents themselves. The first part in the article analyzes the composition and resource potential and the use of time resources of parents for child care and upbringing. The second part will be about the moral guidelines and the results of social adaptation of working parents. The numbering of tables and figures is continuous in both parts.

The Impact of Social Media Use on Students’ Self-Esteem in Higher Education in Eastern Ethiopia

This study aims to assess social media use&amp;apos;s impact on university students&amp;apos; self-esteem. Social media factors that affected the self-esteem of university students were investigated based on the daily time spent on social media. Data were collected using a questionnaire. Self-esteem was measured using the established Rosenberg Self-Esteem Scale. The stratified sampling technique was deployed to select 335 undergraduate university students for this study. Descriptive analysis was performed to analyze the demographic details of the response data collected, including age and social media usage. Correlation and regression analyses were executed using SPSS software to test the correlations between social media factors and self-esteem among undergraduate scholars. As a result, students’ self-esteem among the scholars was significantly affected by their time spent on social media. I recommend that further studies be conducted to investigate the main factors that affect the student’s self-esteem and regard for university scholars.