Time-lagged Analysis Research Articles

Using SDO/AIA to Understand the Thermal Evolution of Solar Prominence Formation

Abstract We investigated the thermal properties of prominence formation using time series analysis of Solar Dynamics Observatory's Atmospheric Imaging Assembly (SDO/AIA) data. Here, we report the first time-lag measurements derived from SDO/AIA observations of a prominence and its cavity on the solar limb, made possible by AIA's different wave bands and high time resolution. With our time-lag analysis, which tracks the thermal evolution using emission formed at different temperatures, we find that the prominence cavity exhibited a mixture of heating and cooling signatures. This is in contrast to prior time-lag studies of multiple active regions that chiefly identified cooling signatures and very few heating signatures, which is consistent with nanoflare heating. We also computed time lags for the same pairs of SDO/AIA channels using output from a one-dimensional hydrodynamic model of prominence material forming through thermal nonequilibrium (TNE). We demonstrate that the SDO/AIA time lags for flux tubes undergoing TNE are predicted to be highly complex, changing with time and location along the flux tube, and are consistent with the observed time-lag signatures in the cavity surrounding the prominence. Therefore, the time-lag analysis is a sensitive indicator of the heating and cooling processes in different coronal regions. The time lags calculated for the simulated prominence flux tube are consistent with the behavior deduced from the AIA data, thus supporting the TNE model of prominence formation. Future investigations of time lags predicted by other models for the prominence mass could be a valuable method for discriminating among competing physical mechanisms.

Spatiotemporal analysis of COVID-19 risk in Guangdong Province based on population migration

Population migration, especially population inflow from epidemic areas, is a key source of the risk related to the coronavirus disease 2019 (COVID-19) epidemic. This paper selects Guangdong Province, China, for a case study. It utilizes big data on population migration and the geospatial analysis technique to develop a model to achieve spatiotemporal analysis of COVID-19 risk. The model takes into consideration the risk differential between the source cities of population migration as well as the heterogeneity in the socioeconomic characteristics of the destination cities of population migration. It further incorporates a time-lag process based on the time distribution of the onset of the imported cases. In theory, the model will be able to predict the evolutional trend and spatial distribution of the COVID-19 risk for a certain time period in the future and provide support for advanced planning and targeted prevention measures. The research findings indicate the following: (1) The COVID-19 epidemic in Guangdong Province reached a turning point on January 29, 2020, after which it showed a gradual decreasing trend. (2) Based on the time-lag analysis of the onset of the imported cases, it is common for a time interval to exist between case importation and illness onset, and the proportion of the cases with an interval of 1–14 days is relatively high. (3) There is evident spatial heterogeneity in the epidemic risk; the risk varies significantly between different areas based on their imported risk, susceptibility risk, and ability to prevent the spread. (4) The degree of connectedness and the scale of population migration between Guangdong’s prefecture-level cities and their counterparts in the source regions of the epidemic, as well as the transportation and location factors of the cities in Guangdong, have a significant impact on the risk classification of the cities in Guangdong. The first-tier cities — Shenzhen and Guangzhou — are high-risk regions. The cities in the Pearl River Delta that are adjacent to Shenzhen and Guangzhou, including Dongguan, Foshan, Huizhou, Zhuhai, Zhongshan, are medium-risk cities. The eastern, northern, and western parts of Guangdong, which are outside of the metropolitan areas of the Pearl River Delta, are considered to have low risks. Therefore, the government should develop prevention and control measures that are specific to different regions based on their risk classification to enable targeted prevention and ensure the smooth operation of society.

The relationship between stressful events, emotion dysregulation, and anxiety symptoms among youth: longitudinal support for stress causation but not stress generation

ABSTRACT Introduction There is a clear bi-directional link between stressful events and depressive symptoms in adolescence, but the directionality of this link for anxiety symptoms remains underexamined. We critically evaluate the longitudinal relationship between stressors and anxiety among youth. Specifically, we examine whether stressors predict anxiety symptoms over a 1.5-year period (stress causation), and whether anxiety symptoms predict stressors over this period (stress generation). We examine potential influencing factors, including stressor type (independent vs. dependent) and emotion dysregulation (nonacceptance; goal-directed difficulty). Methods Social, separation, and physical anxiety symptoms, and frequency and stressor type, were assessed every 3 months for 1.5 years among community youth (n = 528, ages 8–17). Baseline emotion dysregulation was assessed. Time-lagged analyses evaluated the bi-directional relationship of stress and anxiety over time, controlling for previous anxiety and depression. Results Interpersonal stressors predicted subsequent physical and social anxiety symptoms, but anxiety did not predict subsequent stressors. Both nonacceptance and goal-directed difficulties predicted subsequent anxiety symptoms and stressors, but did not moderate the relationship. Conclusion The findings supported the stress causation model for youth anxiety, but not the stress generation model. Nonacceptance and goal-directed difficulty predicted greater subsequent anxiety symptoms and stressors. We discuss implications for prevention and intervention.

ANALISIS PENGARUH INFLASI DAN TINGKAT BUNGA INVESTASI DI INDONESIA

The purpose of this study was to find out and analyze the effect of inflation on investment and interest rates on investment in Indonesia from 2006 to 2015. This type of research is quantitative descriptive and data source retrieval with literature study techniques. The analytical method used in this study is regression time lag analysis. Based on the data analyzed in this study there are several conclusions as follows: 1) inflation has a significant effect on investment 2) interest rates have a significant effect on investment.

Effect of delay time on the combustion instability in a single-element combustor

There are fewer studies on combustion instability (CI) characteristics of non-premixed methane-oxygen flames compared to those of premixed flames. Therefore, this study examined the effect of the total delay time (τtotal), which was calculated using the flame structure and speed, on the CI characteristics of a non-premixed methane-oxygen flame using a coaxial injector. The experiments were repeated by varying the O/F ratio, which is a key parameter of τtotal, and combustor length. Increasing τtotal shifted the CI mode from a high harmonic to the fundamental longitudinal mode. Further, increasing the combustor length shifted the CI mode from the fundamental longitudinal to the third harmonic mode resulted in the pressure perturbation occurring only in particular frequency ranges. The CI strength also changed with varying the combustor length, despite a constant τtotal. In conclusion, this study showed that the time-lag analysis based on τtotal and combustor length might be important for determining the CI characteristics of a non-premixed methane-oxygen flame formed by a single coaxial injector, and thus, τtotal could be the main parameter for determining CI characteristics. Further, the relationship between the flame transfer function and CI frequency was investigated. This study is expected to advance our collective understanding of CI mechanisms and provide a means of avoiding CI by applying time-lag analysis to a non-premixed flame.

MHealth-based experience sampling method to identify fatigue in the context of daily life in haemodialysis patients.

BackgroundFatigue in haemodialysis (HD) patients is a prevalent but complex symptom impacted by biological, behavioural, psychological and social variables. Conventional retrospective fatigue questionnaires cannot provide detailed insights into symptom variability in daily life and related factors. The experience sampling methodology (ESM) overcomes these limitations through repeated momentary assessments in patients’ natural environments using digital questionnaires. This study aimed to gain in-depth understanding of HD patients’ diurnal fatigue patterns and related variables using a mobile Health (mHealth) ESM application and sought to better understand the nature of their interrelationships.MethodsForty HD patients used the mHealth ESM application for 7 days to assess momentary fatigue and potentially related variables, including daily activities, self-reported physical activity, social company, location and mood.ResultsMultilevel regression analyses of momentary observations (n = 1777) revealed that fatigue varied between and within individuals. Fatigue was significantly related to HD treatment days, type of daily activity, mood and sleep quality. Time-lagged analyses showed that HD predicted higher fatigue scores at a later time point (β = 0.22, P = 0.013). Interestingly, higher momentary fatigue also significantly predicted more depressed feelings at a later time point (β = 0.05, P = 0.019) but not the other way around.ConclusionsESM offers novel insights into fatigue in chronic HD patients by capturing informative symptom variability in the flow of daily life. Electronic ESM as a clinical application may help us better understand fatigue in HD patients by providing personalized information about its course and relationship with other variables in daily life, paving the way towards personalized interventions.

Day-to-Day Variability in Subjective Age and Ageist Attitudes and Their Association With Depressive Symptoms.

Evidence of daily fluctuations in subjective age and their association with older adults' well-being was recently obtained. Yet, neither the simultaneous tracking of two daily views on aging (i.e., daily subjective age and daily ageist attitudes) nor their interactive effect on mental health (i.e., depressive symptoms) has been explored. We hypothesized that (a) at days on which older adults feel older or report high ageist attitudes they would report higher depressive symptoms, (b) combined older subjective age and high ageist attitudes will be associated with the highest daily depressive symptoms. Community-dwelling older adults (N = 134, mean age = 69.66) completed measures of subjective age, ageist attitudes, and depressive symptoms for 10 consecutive days. Daily older subjective age and higher ageist attitudes were related to higher depressive symptoms, but there was no combined effect of both on depressive symptoms. There was a significant three-way interaction between subjective age, ageist attitudes, and chronological age, demonstrating the interactive effect of subjective age and ageist attitudes on depressive symptoms only among the old-old respondents. Time-lagged analyses further showed that ageist attitudes during previous days predicted feeling older and more depressed on following days, but not vice versa. Results suggest that old-old individuals are more susceptible to a combination of negative views on aging on daily basis. Findings further support a daily assimilation process, whereby previous-day stereotypes are assimilated and manifested into one's identity and mental health, so that one feels older and more depressed on subsequent days.

역대 정부의 법률과 시행령 간의 시차 분석

역대 정부의 법률과 시행령 간의 시차 분석

Temporal dynamics of the relationship between change in depressive symptoms and cannabis use in adolescents receiving psychosocial treatment for cannabis use disorder

AimsCannabis use disorder (CUD) and depression frequently co-occur in youth. How depressive symptoms change over the course of CUD treatment and how they impact substance use treatment outcomes is unknown. In the current study, we examine the temporal relationships between cannabis use and depression in adolescents receiving evidence-based treatments for CUD as part of a multisite clinical trial. DesignSix hundred adolescents (age 12–18) with a CUD were randomly assigned to substance use treatment from one of five evidence-based psychosocial interventions. We assessed self-reported cannabis use frequency and depressive symptoms at baseline (BL) and again at 3-, 6-, 9, and 12-months. A bivariate latent change model assessed bidirectional effects of baseline levels and time-lagged changes in depressive symptoms and cannabis use on depression and cannabis use outcomes. FindingsDepressive symptoms (72%) and major depressive disorder (MDD) (18%) were common at BL. Both depression and cannabis use decreased over time and change in cannabis use was significantly associated with change in depressive symptoms (b = 1.22, p = .003). Time-lag analyses showed that within-subject change in depression (from one time point to the next) was predicted by previous depression (b = −0.71, p < .001) but not cannabis use (p = .068), and change (decrease) in cannabis use was predicted by previous (greater) depressive symptoms (b = −1.47, p < .001) but not cannabis use (p = .158), respectively. ConclusionThese findings indicate an enduring relationship between decreasing cannabis use and decreasing depression among adolescents lasting for 9-months after receiving psychosocial interventions for CUD. The presence of depressive symptoms did not appear to interfere with substance use treatment or attenuate improvements in cannabis use frequency. A decrease in cannabis use was not contingent upon a reduction in depressive symptoms. These findings are limited by the possibility of regression to the mean for both cannabis use and depressive symptoms, and the lack of a nonintervention control group.

Functional reorganization of brain networks across the human menstrual cycle

The brain is an endocrine organ, sensitive to the rhythmic changes in sex hormone production that occurs in most mammalian species. In rodents and nonhuman primates, estrogen and progesterone’s impact on the brain is evident across a range of spatiotemporal scales. Yet, the influence of sex hormones on the functional architecture of the human brain is largely unknown. In this dense-sampling, deep phenotyping study, we examine the extent to which endogenous fluctuations in sex hormones alter intrinsic brain networks at rest in a woman who underwent brain imaging and venipuncture for 30 consecutive days. Standardized regression analyses illustrate estrogen and progesterone’s widespread associations with functional connectivity. Time-lagged analyses examined the temporal directionality of these relationships and suggest that cortical network dynamics (particularly in the Default Mode and Dorsal Attention Networks, whose hubs are densely populated with estrogen receptors) are preceded—and perhaps driven—by hormonal fluctuations. A similar pattern of associations was observed in a follow-up study one year later. Together, these results reveal the rhythmic nature in which brain networks reorganize across the human menstrual cycle. Neuroimaging studies that densely sample the individual connectome have begun to transform our understanding of the brain’s functional organization. As these results indicate, taking endocrine factors into account is critical for fully understanding the intrinsic dynamics of the human brain.

Increases of negative affect following daily hassles are not moderated by neuroticism: An ecological momentary assessment study.

The occurrence of daily hassles is associated with increased subsequent levels of negative affect. Neuroticism has been found to exacerbate this effect. So far, most research used single-item measures for the assessment of daily hassles or relied on daily diary studies. This study aimed to examine the interrelations of daily hassles, negative affect reactivity, and neuroticism in daily life employing an extensive inventory of daily hassles. Seventy participants (18-30 years; M = 23.9 years, 59% female) completed a 4-week smartphone-based ecological momentary assessment study reporting the occurrence and perceived strain of daily hassles as well as negative affect at five semi-random signals between 9 a.m. and 8 p.m. Multilevel analyses revealed significant associations between elevated levels of negative affect and higher cumulative daily hassle strain ratings per signal in concurrent and time-lagged analyses. Contrary to our expectations, there was no moderation by neuroticism on these associations. The results suggest that daily hassles can accumulate in their impact on mood in daily life and exert a prolonged effect on negative affect. The absence of a significant moderation by neuroticism may be interpreted in the light of methodological specifics of this study.

Global analysis of time-lag and -accumulation effects of climate on vegetation growth

Climate dominantly controls vegetation over most regions at most times, and vegetation responses to climate change are often asymmetric with temporal effects. However, systematic analysis of the time-lag and time-accumulation effects of climate on vegetation growth, has rarely been conducted, in particular for different vegetation growing phases. Thus, this study aimed to leverage normalized difference vegetation index (NDVI) to determine the spatiotemporal patterns of climatic effects on global vegetation growth considering various scenarios of time-lag and/or accumulation effects. The results showed that (i) climatic factors have time-lag and -accumulation effects as well as their combined effects on global vegetation growth for the whole growing season and its subphases (i.e., the growing and senescent phases). However, these effects vary with climatic factors, vegetation types, and regions. Compared with those of temperature, both precipitation and solar radiation display more significant time-accumulation effects in the whole growing season worldwide, but behave differently in the growing and senescent phases in the middle-high latitudes of the Northern Hemisphere; (ii) compared to the scenario without time effects, considering time-lag and -accumulation effects as well as their combined effects increased by 17 %, 15 %, and 19 % the overall explanatory power of vegetation growth by climate change for the whole growing season, the growing phase, and senescent phase, respectively; (iii) considering the time-lag and -accumulation effects as well as their combined effects, climate change controls 70 % of areas with a significant NDVI variation from 1982 to 2015, and the primary driving factor was temperature, followed by solar radiation and precipitation. This study highlights the significant time-lag and -accumulation effects of climatic factors on global vegetation growth. We suggest that these effects need to be incorporated into dynamic vegetation models to better understand vegetation growth under accelerating climate change.

Mind-Wandering in Adolescents Predicts Worse Affect and Is Linked to Aberrant Default Mode Network–Salience Network Connectivity

Understanding the fluctuating emotional and cognitive states of adolescents with depressive symptoms requires fine-grained and naturalistic measurements. This study used ecological momentary assessment (EMA) to investigate the affective correlates and consequences of mind-wandering in adolescents with anhedonia (AH) and typically developing (TD) controls. In addition, we examined the association between mind-wandering and resting state functional connectivity between the medial prefrontal cortex (mPFC), a core hub of the default mode network (DMN) linked to internally oriented mentation, and networks linked to attentional control (dorsal attention network [DAN]) and affect/salience detection (salience network [SN]). A total of 65 adolescents, aged 12 to 18 years (TD= 36; AH= 29), completed a resting state functional magnetic resonance imaging scan and subsequently used a smartphone application for ecological momentary assessment (EMA) data collection (2-3 times/d for 5 days). Each survey (N= 678) prompted adolescents to report on their current positive and negative affect (PA and NA), cognition, and activity. The frequency of mind-wandering was higher for AH (70.0% of EMA samples) relative to TD (59.2%) participants, and the participants with AH were more likely to mind-wander to unpleasant content. Mind-wandering was associated with higher concurrent NA, even when controlling for plausible confounds (eg, current activity, social companion, rumination). Time-lagged analyses revealed a bidirectional association between mind-wandering and PA. Greater levels of mind-wandering within the AH group were associated with stronger mPFC-SN/DAN connectivity. Rates of mind-wandering were high, especially among adolescents with anhedonia, and predicted worse affect. The relation between mind-wandering and enhanced mPFC-SN coupling may reflect heightened bottom-up influence of affective and sensory salience on DMN-mediated internally oriented thought.

P0194UNRAVELING FATIGUE IN HAEMODIALYSIS PATIENTS: A PLEA FOR THE USE OF MOBILE HEALTH EXPERIENCE SAMPLING METHODOLOGY

Abstract Background and Aims Fatigue is one of the most prioritized outcomes among haemodialyis (HD) patients with great impact on health-related quality of life. However, evidence-based therapies are lacking. A better understanding of fatigue symptoms and related behavioral, social and psychological factors in HD patients is of primary importance. Conventionally used fatigue measurement instruments, such as the Fatigue Severity Scale (FSS), only provide a general picture of fatigue severity and are prone to memory bias due to their retrospective nature. However, they cannot provide detailed insight in diurnal variations in fatigue and related factors in daily life. The Experience Sampling Methodology (ESM) overcomes these limitations by repeated “real-time” assessments in patients’ natural environments using digital questionnaires. The aims of this study were (i) to gain in-depth understanding of HD patients’ diurnal fatigue patterns and related variables using a mobile Health (mHealth) ESM application, (ii) to better understand the nature of their interrelationships, and (iii) to explore the relationship between real-time experience of fatigue and its retrospective assessment. Method Forty chronic HD patients used the mHealth ESM application for seven consecutive days to assess momentary fatigue and potentially related variables, including daily activities, self-reported physical activity, social company, location and mood patterns. In addition, patients retrospectively evaluated their fatigue experience over the preceding day and week by means of end-of-day, and end-of-week questionnaires and the FSS. Results Multilevel regression analyses of momentary observations (N=1778) revealed that fatigue varied between and within individuals (Fig.1). Fatigue was significantly related to type of daily activity and mood. Time-lagged analyses showed that HD treatment predicted higher fatigue scores at a later time point, β = 0.22, p = 0.013. Interestingly, higher momentary fatigue also significantly predicted more depressed feelings at a later time point, β = 0.05, p = 0.019, but not the other way around. Retrospective evaluation of fatigue experience over the preceding week was significantly higher than the average of momentary fatigue scores, t(38) = 3.54, p = 0.001. The FSS correlated moderately with the average of momentary fatigue scores, r = 0.63. Conclusion This study demonstrates diurnal variability of fatigue in chronic HD patients. It also corroborates a previous result from our research group showing that fatigue increases as a response to HD treatment (i.e. post-dialysis fatigue) and should, at least partially, be distinguished from a more general fatigue experience. Furthermore, our findings may suggest that depressed mood is secondary to fatigue in HD patients given their temporal relationship. Finally, retrospective fatigue assessment led to overestimation of the real-time fatigue experience. ESM offers novel insights in fatigue in HD patients by capturing informative symptom variability in the flow of daily life, which is not provided by conventional fatigue measures. Moreover, ESM provides personalized information about fatigue symptoms and their relationship with other variables in daily life, paving the way towards personalized interventions for HD patients.

Arrival of Long Ocean Waves and Hourly Sea Level Oscillations in Masan Bay, Korea on 19–22 March 2014

Park, S.J.; Choi, B.-J.; Sim, H.S., and Byun, D.-S., 2020. Arrival of long ocean waves and hourly sea level oscillations in Masan Bay, Korea on 19-22 March 2014. In: Malvarez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1510–1514. Coconut Creek (Florida), ISSN 0749-0208.Calmness and predictability of the sea level in a harbor are essential for safe shipping and cargo-loading on vessels. Masan Bay is an inner bay located on the south coast of Korea where the mean spring tidal range is 174 cm. It has been reported that sea level often fluctuates hourly in Masan Bay in addition to the effect of tides. The cause of the hourly sea level fluctuations have not been explained. The fluctuation periods are close to the natural resonant periods which are determined by the harbor geometry and depth. To find the generating sources of the hourly sea level fluctuations and to examine their characteristics, sea level data measured minutely at Masan harbor and the neighboring 11 tidal stations were analyzed. There were 42 events of long-period sea level oscillations with a maximum height of more than 40 cm in Masan Harbor from 2013 to 2017. Power spectral analysis on the sea level data shows the presence of high energy density in the periods ranging from 48 to 125 min at Masan and neighboring tidal stations. It was found that long ocean waves frequently propagate from the southwestern region of Korea Strait (KS) and enter Masan Bay. Time-lagged correlation analysis between the time series of sea level data along the south coast of Korea in March 2014 suggests that the long waves propagated from the southwestern KS to the eastern KS and entered Masan Bay. It took 2 h 27 min for the waves to propagate from Jeju Island in the southwestern KS to Masan Harbor. The estimated traveling speeds of the long waves using time-lagged correlation analysis were similar to the shallow water wave speed in the region. Oceanic processes that generate the propagating long ocean waves might be tsunami, seismic waves, meteotsunami or internal waves in the open ocean. The long wave events were not related to local winds or air pressure variations.

M2. STRESS IS ASSOCIATED AND PREDICTS SCHIZOTYPIC AND PSYCHOTIC-LIKE EXPERIENCES IN THE FLOW OF DAILY LIFE IN NONCLINICAL AND INCIPIENT PSYCHOSIS INDIVIDUALS

BackgroundDaily-life stressors, specially of a social nature, seem to play an important role in the origin and expression of the continuum of psychosis vulnerability. This study examined whether social stress and social positive appraisals in daily-life were associated, respectively, with the occurrence and the decrease of momentary psychotic-like and paranoid experiences and symptoms across the psychosis continuum.MethodsBoth social stressors and positive appraisals, as well as psychotic and paranoid experiences, were collected by means of Experience Sampling Methodology over a week. Schizotypy was assessed with the Wisconsin Schizotypy Scales. Participants were 206 nonclinical individuals oversampled for schizotypy scores (mean age=19.8) and 113 individuals with at-risk mental states for psychosis and first episode psychosis (74 and 39, respectively; mean age=22.5).ResultsIn the nonclinical sample, appraisals of social stress (but no social contact per se) were associated with psychotic-like and paranoid experiences in daily-life, but not with diminished thoughts or emotions (negative-like symptoms). The association of stress with psychotic and paranoid experiences was moderated by positive, but not negative, schizotypy. In the clinical sample, the positive social appraisal of feeling cared for by others moderated the association between negative self-esteem and the experience of paranoia. Also, they predicted (time-lagged analyses) a decrease of these experiences at subsequent time points—although only feeling cared about did so when the previous level of paranoia was controlled for.DiscussionConsistent with models postulating that stress-sensitivity is a potential mechanistic pathway of, specifically, the positive dimension of psychosis, situational and also social stress predicted psychotic-like and paranoid experiences only in participants with high positive schizotypy. Furthermore, positive social appraisals showed a critical role for buffering the expression of paranoia associated to poor self-esteem in clinical risk for and early psychosis and predicted its amelioration prospectively. Altogether, these findings support the notion that increased sensitivity to social cues is a critical aspect for both risk and resilience mechanisms in the continuum of psychosis. Additionally, they highlight the powerful relevance of positive social identification for dampening the deleterious effects of poor self-esteem and stress.

Time-lag Analysis of Potential Waste Materials as Thermal Insulation in Tropical Climate: A Preliminary Investigation

Energy consumption has shown that residential building is among the main contributors of energy demand. Besides, the harsh climatic conditions have causes substantial amount of energy which contributes indirectly towards the impact on carbon emission to the nations. Hence, this research utilised the potential agricultural wastes materials that is potential for insulate the thermal building performance. The outer and inner surface temperature has been measured on selected seven (7) type of wastes material from agricultural and processing sector every 30 minutes from 0900hr to 1800hr for a day in order to determine the decrement factors (DF), average daily time-lag for heat transfer as one of the thermal insulation properties. Results on the time-lag for all selected potential waste materials as thermal insulation whereas sugarcane bagasse is the lowest 107.5 minutes, followed by both coffee grounds and coconut husk with 130 minutes and wood wool with 132.5 minutes. Meanwhile, empty fruit bunch, coconut fibre and pineapple leave with time-lag of 140 minutes, 142.5 minutes and 145 minutes respectively are the highest time-lag occurred. Generally, the lowest Tis is the better the thermal performance therefore, coconut fibre with smaller DF, larger LT but slightly higher Tis than EFB (32°C) which is 32.2 °C might be the suitable material use as thermal insulation.

Yearly analysis of peak temperature, thermal amplitude, time lag and decrement factor of a building envelope in tropical climate

Two similar building structures, one is with macrocapsules of PCM called the experimental building structure (EBS), while the other is without macrocapsules of PCM called the reference building structure (RBS) were developed using conventional construction materials. Both the structures were then monitored for one year in the outdoor tropical type of environmental conditions to evaluate the indoor thermal behavior based on indoor peak temperature, indoor thermal amplitude, time lag, and decrement factor. Additionally, the annual average peak heat flux and corresponding cost-savings in peak cooling load were also analyzed. The results depict that EBS shows a reduction in the indoor peak temperature round the year, ranging from 0.2 °C to 4.3 °C and a percentage reduction in indoor thermal amplitude ranging from -2.43% to 51.3%. The annual average time delay of 97.5 min and the annual average percentage reduction of 24.69% in the decrement factor was obtained by the EBS. The annual average peak heat flux reduction of 17.37% and corresponding yearly average cost-saving in peak cooling load of 1.47 rupees/kWh/m2/day was obtained in the EBS.

Initially Negative Affect Predicts Lower Satisfaction With Future Social Contact: A Time-Lagged Analysis Using Ecological Momentary Assessment.

Prior research has linked subjective features of social situations with short-term changes in affect (e.g., across days, hours), but little is known about the directionality of such links. Our study examined the concurrent and lead-lag relationships between social contact satisfaction and affect in the flow of daily life. Using ecological momentary assessment (EMA), wherein 78 late-middle-aged and older adults reported on 2,739 social contacts (average 5.02 per day, SD = 2.95) across seven consecutive days, we examined how the level of social contact satisfaction was concurrently and prospectively associated with affect (high-arousal and low-arousal positive affect [PA], high-arousal and low-arousal negative affect [NA]). Higher contact satisfaction was concurrently associated with more high- and low-arousal PA and less high- and low-arousal NA. The influence of contact satisfaction remains for predicting greater low-arousal PA (quietness, calmness) during the next social contact. NA (either high- or low-arousal) predicted lower satisfaction during the next social contact, but such sustainable influence was not observed for PA. The study reveals a cycle in which elevated NA may trigger unsatisfactory social contact, which subsequently predicted less low-arousal PA such as quietness and calmness. Our study provided a more nuanced and differentiated picture of the temporal sequencing of everyday social contact and momentary affect. Practitioners may gain insights from our study into the development of just-in-time adaptive interventions that aim for the betterment of affective well-being in old age.

Contributions of climatic and anthropogenic drivers to vegetation dynamics indicated by NDVI in a large dam-reservoir-river system

With the cascade hydropower stations (CHSs) development and climate change in a large dam-reservoir-river (DRR) system, distinguishing the impact of climatic and anthropogenic factors on vegetation dynamics is vital for a sustainable watershed ecosystem management. In this study, a Breaks for Additive Seasonal and Trend (BFAST) algorithm was adopted to detect the breakpoints (BP) and trend change of climatic factors (CFs) and vegetation dynamics at the pixel scale in the DRR system. The partial correlation and time lag analysis methods were chosen to examine the relationship between vegetation dynamics and CFs (i.e., temperature and precipitation). The multiple linear regression analysis method was adopted to separate the impacts of climatic and anthropogenic factors on vegetation dynamics in multiple periods (i.e., from 1999 to 2013, before BP (BBP), and after BP (ABP)). The most significant results indicated that the area fraction of the BP of vegetation dynamics was 19% of the basin, and the trend BP mainly occurred in 2008. The trend of BP mainly was positive BBP and negative ABP in the basin, and its area fraction was 53.01%. For the eight CHSs, the vegetation dynamics around Ludila and Guanyinyan were more affected by their constructions than that around the other hydropower stations. For the CFs, the vegetation dynamics was mainly affected by precipitation. The lag periods of temperature and precipitation on vegetation dynamics were four months and one month, respectively. Most of the vegetation dynamics appeared to have been impacted by anthropogenic factors in the DRR system. For the eight CHSs, the impact degree of anthropogenic factors on vegetation dynamics BBP was more severe than that ABP, especially around Ludila and Guanyinyan hydropower stations. These results are beneficial for sustainable watershed ecosystem management in the DRR system and ecological development planning around the CHSs.