Daily Events Research Articles

Functional Principal Component Analysis for Continuous Non-Gaussian, Truncated, and Discrete Functional Data.

Mobile health studies often collect multiple within-day self-reported assessments of participants' behavior and well-being on different scales such as physical activity (continuous scale), pain levels (truncated scale), mood states (ordinal scale), and the occurrence of daily life events (binary scale). These assessments, when indexed by time of day, can be treated and analyzed as functional data corresponding to their respective types: continuous, truncated, ordinal, and binary. Motivated by these examples, we develop a functional principal component analysis that deals with all four types of functional data in a unified manner. It employs a semiparametric Gaussian copula model, assuming a generalized latent non-paranormal process as the underlying generating mechanism for these four types of functional data. We specify latent temporal dependence using a covariance estimated through Kendall's bridging method, incorporating smoothness in the bridging process. The approach is then extended with methods for handling both dense and sparse sampling designs, calculating subject-specific latent representations of observed data, latent principal components and principal component scores. Simulation studies demonstrate the method's competitive performance under both dense and sparse sampling designs. The method is applied to data from 497 participants in the National Institute of Mental Health Family Study of Mood Spectrum Disorders to characterize differences in within-day temporal patterns of mood in individuals with the major mood disorder subtypes, including Major Depressive Disorder and Type 1 and 2 Bipolar Disorder. Software implementation of the proposed method is provided in an R-package.

Relationship between Tibetan Plateau Surface Heat Fluxes and Daily Heavy Precipitation in the Middle and Lower Yangtze River Basins (1980–2022)

Variable heat fluxes over the Tibetan Plateau (TP) interact thermally with the atmosphere, affecting weather in surrounding areas, particularly in the Middle and Lower Yangtze River (MLYR). However, the circulation patterns and time-lag effects between TP heat fluxes and MLYR precipitation remain unclear. This study identified 577 large-scale daily heavy precipitation events (LSDHPEs) in the MLYR from 1980 to 2022. We analyzed the weather causation and spatiotemporal correlations between the TP surface heat fluxes and MLYR LSDHPEs using self-organizing map clustering, singular value decomposition, and harmonic analysis of time series. The results found two dominant synoptic patterns of LSDHPEs at 500 hPa: one, driven by anticyclonic and cyclonic circulations coinciding with shifts in the West Pacific subtropical high and South Asian high, increased from 2000 to 2022; the other, influenced by MLYR cyclonic circulation, showed a significant decrease. For the first time, we revealed lagged effects of the latent heat anomalies (with a lag time of 1–10 d and 130–200 d) and sensible heat anomalies (with a lag time of 2–4 months) over the TP during LSDHPEs in the MLYR. The results may enhance our understanding of TP heat flux anomalies as precursor signals for early warning of heavy rainfall and flooding in the MLYR.

Rainfall events and daily mortality across 645 global locations: two stage time series analysis

ObjectiveTo examine the associations between characteristics of daily rainfall (intensity, duration, and frequency) and all cause, cardiovascular, and respiratory mortality.DesignTwo stage time series analysis.Setting645 locations across 34 countries or regions.PopulationDaily...

Unpleasant emotions and task-unrelated thoughts and their associations with amygdala activity during emotional distraction: A functional magnetic resonance imaging study

Previous emotion regulation studies revealed that emotional distraction decreases unpleasant emotions. This study examined whether distraction tasks decrease unpleasant task-unrelated thoughts (TUTs) and unpleasant emotions when recalling stressful daily interpersonal events. Amygdala activity was examined to assess implicit emotional changes using functional magnetic resonance imaging (fMRI). The behavioral data of 20 university students (mean age: 20.35 ± 1.42 years; range: 18–24 years) and fMRI data of 18 students were examined. As an emotion induction procedure, participants initially freely recalled memories of daily stressful interpersonal events and then responded to a series of questions about their recalled memories presented on a monitor. In the distraction experiment, the questions were re-represented as an emotional stimulation; a distraction task (nonconstant or constant finger tapping) or rest condition was then performed, and ratings were given for attentional state, thought types conceived during the tasks, and emotional state. Decreases in unpleasant emotions and TUTs were defined as distraction effects. We found that unpleasant TUTs decreased in the nonconstant relative to rest condition (p < .05). Furthermore, increased right amygdala activation positively correlated with unpleasant emotions, and bilateral amygdala activation correlated with unpleasant TUTs only in the rest condition, indicating the existence of amygdala activation associated with unpleasant emotions and thoughts. However, such associations were not under nonconstant or constant conditions, indicating distraction effects. Notably, this study showed that emotional distraction can decrease the degree of unpleasant emotions and the occurrence of unpleasant thoughts regarding common daily emotions.

Real-time biopsychosocial antecedents and correlates of functional neurological symptoms in daily life: A pilot remote monitoring technology study

Functional neurological symptom disorder (FNSD) is a neuropsychiatric diagnosis referring to symptoms resembling those of neurological disorders, occurring without causal neuropathology. FNSD has a complex biopsychosocial aetiology but its mechanisms are poorly understood. Remote monitoring technologies (RMT) could provide critical insights into functional neurological symptoms (FNS) in real-world contexts. We examined the feasibility and acceptability of a novel RMT protocol, to identify psychobiological correlates and antecedents of FNS in everyday life. Seventeen individuals with FNS (seizures/motor) and 17 healthy controls (HC) completed ecological momentary assessments (EMA) eight times daily for 1-week, reporting FNS severity, associated physical and psychological symptoms, and subjectively significant events. Sleep quality was reported daily. Physiological variables were measured using wearable Fitbit 5 devices. Multilevel modelling examined variables associated with FNS variability. Average EMA completion rates were good in both groups (≥80%). At week-level, the FNS group reported significantly greater subjective arousal, pain, fatigue, dissociation, negative affect, daily events, stressful events, and sleep duration, compared to HC. Objective sleep disturbance and duration, and resting heartrate, were also significantly greater in the FNS sample. FNS severity correlated significantly with daily events, affect, subjective arousal, pain, fatigue and sleep disturbance, at day- or within-day levels. Daily events and negative affect were the most prominent time-lagged predictors of within-day moment-to-moment FNS severity. RMTs are feasible and acceptable tools for investigation of FNS in real-world settings, revealing daily events and negative affect as possible triggers of FNS. Interventions targeting affective reactivity and regulation might be beneficial in this group. Larger-scale, longer-term RMT studies are needed in this population.

Verbal attacks on terrorist groups increase violence against civilians

Abstract Terrorists and other transnational extremist groups are responsible for thousands of civilian deaths. In confronting extremists, governments have relied heavily on threats, demands, denunciations, and other forms of verbal conflict. Do these efforts at verbal coercion have any effect on terrorist behavior? This analysis focuses on the Islamic State in Iraq and Syria (ISIS), which continues to be the world's deadliest terrorist group and was responsible for recent high-profile attacks in Baghdad, Vienna, Kabul, and Russia. We use Bayesian structural vector autoregression models to analyze daily event data on interactions between ISIS and foreign governments for the 2014–2020 period. We find that verbal conflict initiated by governments not only failed to deter ISIS but in fact increased the frequency of ISIS's attacks on civilians. Additional empirical analyses, combined with evidence from ISIS's publications and public statements, suggest that this effect resulted from a perceived credibility deficit. Extremists use terror attacks to signal that they have the capabilities and willingness to inflict pain and suffering on civilian targets. Government attempts to coerce extremist groups verbally, rather than militarily, reflect an underestimation of the group's capabilities and resolve. In an effort to solidify their reputations, extremists engage in further violence toward civilians, thus leading to worse humanitarian consequences. We extend the analysis to Al-Qaeda in Iraq and Boko Haram and find similar results.

Statistics and Meteorology of Cutoff Lows over South Africa 1970–2023

The meteorology of cutoff lows over South Africa is characterized by statistical analysis of daily field data in the period 1970–2023. An index is formulated by subtracting 500 hPa geopotential height in the mid-latitudes from the subtropics. Cutoff lows (COL) are identified by positive values, mostly in autumn and spring. Statistics indicate that climate forcing is seasonal: La Nina/El Nino favors COL in March–May/September–November. Hemispheric regressions reveal anomalous highs across the southern mid-latitudes when COL are frequent over South Africa. A 14-case composite was formed from the most intense daily COL events in autumn and spring. The composite shows a NW- tilted Rossby wave and jet stream loop around the COL. Maritime easterlies induce a warm east—cool west SST pattern, but composite moist inflows are shallow, so stormy weather hugs the coastal plains. Overturning circulations meet in an upper-level “saddle” over South Africa. 500 hPa sinking motions to the Southwest are of similar strength to rising motions to the Northeast. A COL case study exhibited hourly rain rates &gt;10 mm at Port Alfred 18–20 October 2012 fed by tropical inflow. New insights emerged from this study via composite height sections over South Africa.

A high-resolution dataset for future compound hot-dry events under climate change.

Global climate change is leading to an increase in compound hot-dry events, significantly impacting human habitats. Analysing the causes and effects of these events requires precise data, yet most meteorological data focus on variables rather than extremes, which hinders relevant research. A daily compound hot-dry events (CHDEs) dataset was developed from 1980 to 2100 under various socioeconomic scenarios, using the latest NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) dataset to address this. The dataset has a spatial resolution of 0.25 degrees (approximately 30 kilometres), including three indicators, namely D (the yearly sum of hot-dry extreme days), prI (the intensity of daily precipitation), and tasI (the intensity of daily temperature). To validate the accuracy of the dataset, we compared observational data from China (National Meteorological Information Center, NMIC), Europe (ERA5), and North America (ERA5). Results show close alignment with estimated values from the observational daily dataset, both temporally and spatially. The predictive interval (PI) pass rates for the CHDEs dataset exhibit notably high values. For a 90% PI, D has a pass rate exceeding 85%, whilst prI and tasI respectively show a pass rate above 70% and 95%. These results underscore its suitability for conducting global and regional studies about compound hot-dry events.

Effects and Remedies of Construction Claims in Hydropower Projects: Case Studies of Selected Medium-Scale Hydropower Projects in Nepal

This research aims to analyze the perspectives of various stakeholders involved in hydropower projects, including employers, engineers, and contractors, to identify common challenges and propose strategies for minimizing claims. The data analysis involved a questionnaire survey conducted among representatives of employers, engineers, and contractors across seven selected hydropower projects. Similar questionnaires were distributed to gather insights from all three parties involved in the projects. The responses were compiled and analyzed collectively using a general ranking method, allowing for a comprehensive assessment of the findings related to the thesis objectives. The analysis revealed that claims significantly impact construction projects, manifesting as both cost overruns and time delays. If not addressed promptly, these claims can escalate into disputes that typically require resolution through Alternate Dispute Resolution (ADR) procedures or may lead to complex legal proceedings. The study identified several key factors contributing to claims, including inadequate tender documentation, poor record-keeping of daily site events, and the occurrence of major design changes. To mitigate the risks associated with claims in hydropower projects, it is essential to implement several best practices: preparing clear and unambiguous tender documents, maintaining comprehensive daily records of site activities, minimizing design changes whenever possible, ensuring site possession prior to contractor mobilization, and conducting thorough field investigations before finalizing designs.

Variations and Trends in 115 Years of Graded Daily Precipitation Records at Three Hydrometeorological Stations in Finland

This study investigated the variability and trends in 115 years (1909–2023) of daily precipitation observed at three hydrometeorological stations in southern (Kaisaniemi), central (Kajaani), and northern (Sodankylä) Finland. We also identified the most significant climate teleconnections influencing daily precipitation variability at these three stations during the period 1951–2023. The daily precipitation records were primarily classified into six grades, including very light (≤1 mm), light (1–≤5 mm), moderate (5–≤10 mm), heavy (10–≤15 mm), very heavy (15–≤20 mm), and extreme (&gt;20 mm). On average, the most intense daily precipitation was determined at the Kaisaniemi station in southern Finland. At this station, however, very light and light precipitation showed the lowest frequency, but other graded daily precipitation events were the most frequent. At all three stations, the intensity of very light precipitation significantly declined during the past 115 years, while its frequency increased. The highest rates of such decreases and increases in the intensity and frequency of very light daily precipitation were found at the Sodankylä stations in northern Finland, respectively, but the lowest rates were at the Kaisaniemi station in the south. At the Kajaani station in central Finland, the intensity of light precipitation decreased, but very heavy precipitation intensified. At this station, however, the number of both moderate and heavy precipitation events increased over time. Finally, historical variations in both the intensity and frequency of graded daily precipitation events in Finland showed significant relationships with different climate teleconnections, particularly the Scandinavia (SCAND) and the North Atlantic Oscillation (NAO) patterns.

An advanced learning approach for detecting sarcasm in social media posts: Theory and solutions

AbstractObjectiveUsers of social media platforms such as Facebook, Instagram, and Twitter can view and share their daily life events through text, photographs, or videos. These platforms receive many sarcastic posts daily because there were fewer limits on what could be posted. The presence of multiple languages and media types in a single post makes it harder to identify sarcastic messages on the current platform than on posts written solely in English.MethodsThis study provides both the theory and solutions about sarcastic post detection on social platforms. Hindi–English code‐mixed data were used to train and test the automated models for sarcasm detection. The models in this study were constructed using traditional machine learning, deep neural networks, LSTM (long short‐term memory), CNN (convolutional neural network), and the combinations of BERT (Bidirectional Encoder Representations from Transformers) with LSTM.ResultsThe experimental results confirm that in the Hindi–English code‐mixed data set, the CNN, LSTM, and BERT‐LSTM ensemble perform best for sarcasm detection. The proposed model achieved an accuracy of 96.29 percent and outperformed by 2.29 percent compared to the existing models.ConclusionThe performance of the proposed system strengthens the code‐mixed sarcastic post detection on social platforms. The model will help filter not only English but also Hindi‐English code‐mixed sarcastic posts on social platforms.

Affective Responsivity to Daily Stressors is Amplified in Young Females

Despite mounting evidence that young adults experience greater exposure and affective responsivity to daily stressors than middle-aged and older adults, few studies have examined potential sex differences in these daily stress processes in young adults. We tested the hypotheses that young women would experience (1) a greater percentage of days with at least one daily stressor event and (2) exaggerated negative and positive affective responsivity to daily stressors compared to young men. Young adults ( n = 215) completed a daily web-based interview for eight consecutive days to assess multiple dynamic aspects of daily stress processes. Women experienced a greater frequency of daily stressor days. Further, the magnitude of the difference in both negative and positive affect between stressor-free and stressor days were greater in young women compared to young men. Greater exposure and amplified affective responsivity to daily stressors may potentially contribute to increased susceptibility to adverse psychological outcomes in young women.

Presence – Donation – Event

The Helikon Publishing House has published (2006–2018) Sándor Márai’s (1900–1989) diaries in eighteen volumes of eight thousand pages under the title The Complete Diary. After Márai left the country for good in 1948 and went into exile, the communist regime eliminated him from the history of Hungarian literature, and generations grew up without reading his books or hearing about him in their literary studies. The diary is a testament to the existential vulnerability of the writer in exile. This major piece of work has four layers: the first is made up of notes on regular readings, the second is about recent Hungarian history, the third is personal memory, and the fourth is the material for the absorption of the host country’s culture. The Complete Diary changes our view of Márai, whose vision of Hungarian history is disturbing. He sees Hungary as a failed attempt to create a modern bourgeois nation. What is unique about Márai’s diary is the way it fuses memories of the personal past with reflections on the present. The recording of daily events goes beyond the genre of the diary: on the one hand towards the essay, on the other towards the novel.

Association between ambient air pollution and respiratory health in Kampala, Uganda: Implications for policy and practice

Ambient air pollution and weather have an impact on respiratory diseases. This study analysed effects of fine particulate matter (PM2.5) on monthly respiratory-related healthcare facility visits and admissions (herein referred to as events) in Kampala, whilst considering meteorological factors.Monthly healthcare facility events for neonatal pneumonia, asthma, pneumonia and COPD between 2019 and 2020 were retrospectively extracted from the District Health Information Software 2. PM2.5 and meteorological data were obtained from 45 monitoring stations and 5 weather stations in Kampala. Associations between air pollution and healthcare facility events were examined using generalised additive models (GAM) adjusted for rainfall, temperature and humidity.Multivariate analysis showed positive association between monthly PM2.5 with healthcare facility visits due to asthma (incident rate ratio-IRR = 1.007, 95 % CI: 1.002–1.013; p < 0.05) and admissions due to pneumonia (IRR = 1.007, 95 % CI: 1.001–1.013; p < 05). Healthcare facility events were associated with PM2.5 (IRR = 1.005; 95 % CI: 1.002–1.009; p < 0.05) and relative humidity (EDF = 1.000; p < 0.05).PM2.5 impacted on healthcare facility events in Kampala and association was influenced by meteorological factors. However, lack of data for daily healthcare facility events could have affected accuracy of the impact therefore further analyses are needed. Our characterisation could support facilities in development of early warning tools for air pollution events.

144 Assessing economic implications of thermal stress of Bos indicus and Bos taurus species during finishing in northern Colorado

Abstract The objective of this study was to determine the economic implications of thermal stress on climate adaptive capacity, resiliency, and impact of Bos indicus and Bos taurus finishing steers using common finishing systems. The experimental design was a completely randomized design, with a 2 by 2 factorial arrangement of finishing system (‘natural’ or ‘conventional’) and species of cattle (Bos indicus or Bos taurus). Steers [n = 200; body weight (BW) ~450 kg] were housed in 20 feedlot pens (10 steers/pen) for the first 84 d, where cattle were blocked by initial BW. For the remainder of the 180 d (96 d) finishing period, cattle were moved to four Climate Smart Research Pens (50 steers/pen, 1 pen/ treatment, and species combination). Within each Climate Smart Research Pen, five SmartFeed systems were used to evaluate individual animal feed intake, one GreenFeed emission measurement system was used to evaluate individual animal gas emissions flux of enteric CH4, O2, H2, and CO2, and were equipped for nutrient mass balance of carbon, nitrogen, and phosphorus. Animal BW were collected every 28 d for analysis of average daily gain (ADG) and feed efficiency. Thermal stress behaviors were evaluated by one trained personnel on a subset of 7 steers/treatment via the measurement of respiration rate, open mouth breathing, rumen temperature, number of daily water intake events, lying and standing behavior, and pen surface temperature for the last 96 d of the finishing period. At harvest, carcass characteristics, liver scores, and heart scores were collected. Economic analyses were conducted post-hoc to determine the profitability of each species based on economic implications, tradeoffs, carcass quality and quantity, and time to finish. Selection of cattle for climate adaptive features may involve production tradeoffs (e.g., depressed rate of gain, greater yield risk, lower technical efficiency) and adjustment costs (e.g., re-optimizing feed for a new breed), which affect the adoption of less common breeds into the US cattle supply chain. Adding to the complexity of this evaluation, consumers preferences may not adapt quickly, affecting the prospect of Bos indicus cuts of meat in the market. We also, therefore, explore the supply- and demand-side effects of climate change adaptation through breed selection in the beef industry.

Between gaze and taste: Senses, imaginaries, and the sustainability of culinary heritage in Greek tourist-oriented tavernes

This article examines food tourism events in permanent tourist-oriented food venues, focusing on Greek tavernes. Drawing on ethnographic research in Greece since 2010, we explore how tourists' expectations and sensory experiences in food events influence culinary heritage and social sustainability. We employ Urry's “tourist gaze” concept, integrating it with a comprehensive analytical framework addressing tourists' and local attendees' sensory experiences in daily food events at culturally significant institutions like Greek Tavernes. Our study illuminates the dominance of tourists' expectations, preconceived imaginaries, and sensory engagements, revealing potential challenges to sustained cultural traditions and culinary heritage. While the “tourist gaze” may perpetuate static cultural dynamics, we identify “tourist (and resident) taste” as a counter-mechanism. Our findings reveal that Greek tavernes, catering to tourist expectations and evolving local taste preferences, strike a delicate balance, enhancing eventful and multisensorial experiences to preserve and develop culinary heritage and social sustainability.

Early prediction of milk yield from Holstein-Friesian cow lactation in Querétaro, Mexico

Objective: To obtain a machine learning (ML) model to predict the milk yield adjusted to 305 d (MY305) from the same lactation period. Design/methodology/approach: A database of test days (TD) was used, made up by 11,892 records of daily milk production from cows with more than 150 days in milk (DIM), from 19 barns in Querétaro, Mexico. The milk production was standardized to specific DIMs (5, 10, 20, 30 and 40) and estimations of MY305 were obtained with these, using ML models. The following were incorporated as explicative variables of the herd: month of birth of the cow, month of start of lactation, number of lactation, number of days for three daily milking events, and the two first linear scores of somatic cells. Results: The best goodness of fit was achieved with ensemble models, obtaining a deviance of 1503584 in the training with 80% of data chosen randomly, while with 20% of the data reserved to evaluate the deviance model it was 1576776. The rate between data observed and predictions of MY305 of the ensemble models had a coefficient of determination of r2 = 0.79 and RMSE of 1256. In the best individual model (deviance of 2281420) of ‘deep learning’ type, the most important variables were daily milk production of 30, 10, 5 and 20 DIM (19.9, 16.6, 16.2 and 12.8%, respectively). Limitations on study/implications: The value of RMSE is high, although the TD databases are generated systematically and usually there are not many barns represented. Findings/conclusions: For the database examined, milk production in the early phase of lactation together with a set of automatic learning models resulted in an adequate prediction of MY305.

Reduce negative life events to Increase satisfaction: A daily diary study on the relationship between negative life events and life satisfaction

Life satisfaction refers to an individual’ s cognitive evaluation of the overall quality of their life considering the various aspects therein. Although the existing research has demonstrated the between-person relationship between negative life events and life satisfaction based on retrospective measures, less is known about this relationship at the within-person level. A daily diary method could examine this within-person relationship and decrease systematic recall biases. Therefore, this study investigated the link between daily negative life events and daily life satisfaction, as well as the mediating role of perceived stress and the moderating role of trait rumination in 146 young adults (Mage = 20.75, SD = 1.35) using a 14-day daily diary design. Multilevel regression analysis showed that daily negative life events had negative predictive effects on daily life satisfaction. In addition, the multilevel 1-1-1 mediation analysis indicated that daily perceived stress mediated the association between daily negative life events and daily life satisfaction. More importantly, the mediating effect of perceived stress was moderated by trait rumination, with the within-person mediating effect being stronger for individuals with higher than those with lower trait rumination tendencies. These findings contribute to the understanding of the underlying pathways in the relationship between daily negative life events and daily life satisfaction and provide a new perspective for improving individuals’ life satisfaction.

The Everyday Wellbeing Appraisal Scale: Assessing a type of subjective well-being uniquely associated with health behavior in people with hypertension.

Everyday well-being appraisals are judgments about the goodness of recent daily life events. These appraisals are expected to be distinct from other types of well-being involving traits, affect, and psychological distress and expected to be uniquely important for understanding health behavior such as exercise, diet, and treatment adherence for people with medical conditions. To develop and test a new Everyday Wellbeing Appraisal Scale, two studies were conducted in which a total of 718 people with hypertension completed online questionnaires. In Study 1, to achieve maximum validity with the fewest number of items, an empirical analysis was used to select a set of six items with high discrimination that incorporated multiple types of response-option formats. In Study 2, the scale's unidimensional factor structure and high discrimination were confirmed, and the new scale outperformed several existing types of well-being scales in its ability to explain unique variance in health behavior criterion variables. Specifically, it explained unique variance in health behavior after controlling for a widely used measure assessing trait-level reflections of well-being, as well as measures of positive affect and two types of psychological distress. Also, when compared to the trait-level measure of well-being, the new scale demonstrated less overlap with affect and psychological distress. These results suggest that this brief, new scale is valuable for assessing a distinct construct that is especially salient for understanding health behavior. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Daily Goal-Disruptive Events Increase Truck Drivers’ Fuel Consumption via Anger and Happiness

Daily Goal-Disruptive Events Increase Truck Drivers’ Fuel Consumption via Anger and Happiness