Daily Scale Research Articles

Enhancing Evapotranspiration Estimations through Multi-Source Product Fusion in the Yellow River Basin, China

An accurate estimation of evapotranspiration (ET) is critical to understanding the water cycle in watersheds and promoting the sustainable utilization of water resources. Although there are various ET products in the Yellow River Basin, various ET products have many uncertainties due to input data, parameterization schemes, and scale conversion, resulting in significant uncertainties in regional ET data products. To reduce the uncertainty of a single product and obtain more accurate ET data, more accurate ET data can be obtained by fusing different ET data. Addressing this challenge, by calculating the uncertainty of three ET data products, namely global land surface satellite (GLASS) ET, Penman–Monteith–Leuning (PML)-V2 ET, and reliability-affordable averaging (REA) ET, the weight of each product is obtained to drive the Bayesian three-cornered Hat (BTCH) algorithm to obtain higher quality fused ET data, which are then validated at the site and basin scales, and the accuracy has significantly improved compared to a single input product. On a daily scale, the fused data’s root mean square error (RMSE) is 0.78 mm/day and 1.14 mm/day. The mean absolute error (MAE) is 0.53 mm/day and 0.84 mm/day, respectively, which has a lower RMSE and MAE than the model input data; the correlation coefficients (R) are 0.9 and 0.83, respectively. At the basin scale, the RMSE and MAE of the annual average ET of the fused data are 11.77 mm/year and 14.95 mm/year, respectively, and the correlation coefficient is 0.84. The results show that the BTCH ET fusion data are better than single-input product data. An analysis of the fused ET data on a spatiotemporal scale shows that from 2001 to 2017, the ET increased in 85.64% of the area of the Yellow River Basin. Fluctuations in ET were greater in the middle reaches of the Yellow River than in the upstream and downstream regions. The BTCH algorithm has indispensable reference value for regional ET estimation research, and the ET data after BTCH algorithm fusion have higher data quality than the original input data. The fused ET data can inform the development of management strategies for water resources in the YRB and provide a deeper understanding of the regional water supply and demand balance mechanism.

Cross-cultural adaptation of the Avoidance of Daily Activities Photo Scale for Turkish patients with shoulder pain: Reliability and validity assessment according to the COSMIN guideline

ContextPeople with chronic or long-term pain may develop various psychosocial symptoms such as fear and avoidance of behavior due to pain. Reliable and valid quality of life tools must be available in Turkish to specifically assess avoidance of behavior in people with shoulder pain. ObjectivesThis study aimed to translate and culturally adapt the Avoidance of Daily Activities Photo Scale for Patients with Shoulder Pain and to evaluate the psychometric properties of its Turkish version (ADAP-Tr) in patients with shoulder pain. MethodsTranslation, adaptation, and validation were performed according to the COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) guidelines. The internal consistency, reliability, construct validity, and discriminant validity of the ADAP-Tr were tested. The Pain Catastrophizing Scale (PCS), Tampa Scale for Kinesiophobia (TSK), and Shoulder Pain and Disability Index (SPADI) were applied for validation purposes. ResultsThe study included a total of 162 participants with shoulder pain. The internal consistency of the ADAP-Tr showed excellent reliability with a Cronbach's α of 0.94 and a test-retest assessment of 0.88 ICC (95% CI, 0.83-0.91). The standard error of measurement was 1.85 points, and the minimal detectable change was determined 5.12 points. There was a low to high correlation among the ADAP-Tr and PCS (r = 0.481, p < .001), TSK (r = 0.448, p < .001), and SPADI (r = 0.826, p < .001) scores. ConclusionsThe ADAP-Tr was shown to be a valid and strong reliability tool to use in clinical and research settings as a shoulder-specific measurement tool.

Impacts of urbanization on urban-rural VPD disparities across different subregions in China: A quantitative analysis based on station-pairing and partial differential methods

The climatic disparities between urban cores and surrounding rural areas have become increasingly pronounced due to rapid urbanization. The vapor pressure deficit (VPD) serves as a critical meteorological indicator reflecting atmospheric aridity, and identifying the contributions of urban and rural climate factors on the urban-rural VPD disparities plays an important role in understanding urban climate and ecosystem development patterns. This study introduces a quantitative method, utilizing partial differential equations, to assess the relative contributions of two crucial meteorological factors—air temperature (T) and relative humidity (RH)—toward urban-rural differences in VPD. Analyzing daily scale data from 116 pairs of urban and rural stations across mainland China for the period 2000–2017, we derived several key findings: Urban areas generally exhibit higher VPD than surrounding rural areas, with a relative difference in annual VPD of about 21.6 %, and the disparity increases over time. Furthermore, the influence of urbanization on VPD responds differently across seasons and geographical conditions. The simulated trends in VPD urban-rural differences using the partial differential method align closely with the actual observed trends, validating the effectiveness of our quantitative analysis approach. The VPD urban-rural disparity shows greater sensitivity to shifts in RH, with sensitivity coefficients exceeding 1.5 times to changes in T in most cases. RH is the primary factor causing VPD urban-rural differences in mainland China, and the relative contribution of RH is about 2.5 times of T. The patterns of sensitivity and the contribution of factors exhibit notable variation among subregions. This study enhances the understanding of how urbanization affects regional climate and provides insights for assessing the environmental impacts of future urban expansion.

Fine particulate matter and ozone variability with regional and local meteorology in Beijing, China

Fine particulate matter (PM2.5) and surface ozone air pollution have severe health consequences. Since China implemented the nationwide Air Pollution Prevention and Control Action Plan (APPCAP) in 2013, annual average PM2.5 concentrations have decreased while O3 concentration have increased in Beijing. It is unclear, however, to the extent that short-term meteorological variability has influenced these trends. To separate the influence of meteorology from long-term emissions-induced changes, we quantify the portion of the long-term PM2.5 and O3 concentration signals associated with short-term meteorological variability. Building off recent literature highlighting the regional nature of pollutant variability, we incorporate both locally observed meteorology and average regional reanalysis. We isolated sub-seasonal variability using the Kolmogorov-Zurbenko filter. Next, we trained and compared the utility of three statistical models of varying complexity (a linear model, a general additive model with splines, and a random forest) in their ability to predict out-of-sample daily concentrations. The random forest model yields the best predictive capability in holdout tests and predicts changing meteorological contributions to PM2.5 and ozone concurrent with changing concentrations across the study period. Results show an overall decrease in meteorology induced PM2.5 concentration variability at daily scales since 2013, but variability from meteorology has increased relative to mean PM2.5 concentrations. In contrast, O3 shows the opposite trend, with increasing meteorology-induced variability (meteorology-induced variability normalized by mean observed O3 has decreased). Our results show the importance of including regional meteorology in explaining local PM2.5 and O3 variability and quantify links between long-term policy implementation and short-term meteorological contributions to pollutant concentrations.

The SMILE scale: a wellness behavioral tool for patients with cancer.

As cancer survivorship increases, there is a need for simple tools to measure and promote healthy behaviors. We created a wellness behavioral tool (the SMILE Scale) to encourage self-monitoring of wellness behaviors. This study aimed to determine the feasibility of collecting daily self-reported SMILE Scale data and weekly quality of life data among patients with cancer. We also aimed to measure the association between SMILE Scale responses and validated health-related quality of life (HRQOL) tools (PROMIS-29 + 2 and SymTrak-8) as a pilot test of the hypothesis that increased wellness behaviors may impact quality of life. We surveyed 100 patients with cancer at the Indiana University Simon Comprehensive Cancer Center. Participants were asked to complete daily SMILE Scale assessments over a two-week period, as well as weekly PROMIS-29 + 2 and SymTrak-8 surveys. The primary endpoint was the SMILE Scale completion rate. Secondary endpoints in this single-arm pilot study included correlations between the SMILE Scale and other HRQOL tools. Daily completion rate of the SMILE Scale ranged from 57% to 65% of participants over a 14-day period. Among the 61% of participants who completed SMILE on day 1, 87% completed SMILE on 10 of 14 days. By end of study, participants who self-reported more wellness behaviors (i.e., higher daily SMILE scores) demonstrated significantly higher PROMIS physical health (p = 0.003), higher PROMIS mental health (p = 0.008), and lower (better) SymTrak total symptom burden (p = 0.006). Further, among those who completed at least 1 of 14 daily SMILE assessments, quality of life significantly improved over the two-week period for PROMIS mental health (p = 0.018) and SymTrak total symptom burden (p = 0.014). The SMILE Scale completion rate did not satisfy our pre-planned ≥70% threshold for feasibility; however, the rate for completing SMILE at least once during the 14 days (77%) met this threshold. Participants with higher average daily SMILE scores had significantly better scores across other validated HRQOL tools. While these results may be correlative and not causative, this suggests a potential physical and mental health benefit for delivering the SMILE Scale in clinical practice to help encourage healthy behaviors and warrants testing the SMILE Scale's impact in future studies.

Influence of grazing management strategy and data time scales on estimates of sensible heat flux in grasslands

Study regionInner Mongolia Autonomous Region, North China Study focusSensible heat flux (H) quantifies the intensity of water evapotranspiration, making the factors influencing H pivotal to water consumption. North China's semi-arid grasslands are characterized by widespread grazing and strong wind conditions. Grazing strategy modifies surface air heat transfer resistance via vegetation and consequently alters H. Nevertheless, the majority of studies overlook the impact of the observed variables' time scale on H estimation. This paper employs a "big-leaf" model to estimate H, incorporating both grazing management strategy and data time scale, validated using the Bowen ratio, and attempted to analyze the factors that affect H. New hydrological insights for the regionAerodynamic characteristics estimated from daily data typically exceed estimates derived from hourly data. The influence of surface radiative temperature and air temperature on H outweighs that of aerodynamic resistance, whereas aerodynamic resistance accounts for the disparity in estimating H between daily and hourly data. In grazing-prohibited grasslands, the daily H values estimated by the Big Leaf model closely match those obtained from the Bowen ratio. When estimating the hourly H value for grazing prohibited and grazing grasslands, the increase was 25.95 w/m2 and 52.27 w/m2 compared to the daily scale, respectively. For the estimation of water and heat fluxes across different regions, the temporal scale of input data is a pivotal factor.

Pain catastrophizing and trunk co-contraction during lifting in people with and without chronic low back pain: A cross sectional study.

Trunk co-contraction during lifting may reflect a guarded motor response to a threatening task. This work estimated the impact of pain catastrophizing on trunk co-contraction during lifting, in people with and without low back pain. Adults with high pain catastrophizing (back pain: n = 29, healthy: n = 7) and low pain catastrophizing (back pain: n = 20, healthy: n = 11), performed 10 repetitions of a lifting task. Electromyography data of rectus abdominis, erector spinae and external oblique muscles were collected, bilaterally. Co-contraction indices were determined for rectus abdominis/erector spinae and external oblique/erector spinae pairings, bilaterally. Pain catastrophizing was measured using the pain catastrophizing scale and task-specific fear using the Photograph series of daily activities scale. Three-way mixed ANOVAs tested the effects of group (back pain vs. healthy), pain catastrophizing (high vs. low), lifting phase (lifting vs. replacing) and their interactions. There were no main effects of pain catastrophizing, lifting phase, nor any interactions (p > 0.05). Group effects revealed greater co-contraction for bilateral erector spinae/rectus abdominis pairings (but not erector spinae-external oblique pairings) in people with back pain, compared to healthy participants, independent of pain catastrophizing and lifting phase (p < 0.05). Spearman correlations associated greater task-specific fear and greater erector spinae-left external oblique co-contraction, only in people with back pain (p < 0.05). Greater co-contraction in the back pain group occurred independent of pain catastrophizing, as measured with a general questionnaire. A task-specific measure of threat may be more sensitive to detecting relationships between threat and co-contraction. This work contributes evidence that people with back pain commonly exhibit trunk co-contraction when lifting. The lack of a relationship between pain catastrophizing and trunk co-contraction, however, challenges evidence linking psychological factors and guarded motor behaviour in this group. Together, this suggests that other factors may be stronger determinants of co-contraction in people with LBP or that a general construct like pain catastrophizing may not accurately represent this relationship.

Impact of Irrigation Management Decisions on the Water Footprint of Processing Tomatoes in Southern Spain

The water footprint is an increasingly demanded environmental sustainability indicator for certifications and labels in agricultural production. Processing tomatoes are highly water-intensive, and existing studies on water footprint have uncertainties and do not consider the impact of different irrigation configurations (e.g., surface drip irrigation (SDI) and subsurface drip irrigation (SSDI)) and irrigation strategies. This study presents a two-year experimental investigation to determine the water footprint of processing tomatoes grown in southern Spain (Andalusia) and the impact of SSDI and deficit irrigation. Five irrigation treatments were established: SDI1 (surface drip irrigation without water limitation), SDI2 (surface drip irrigation without water limitation adjusted by soil moisture readings), SSDI1 (subsurface drip irrigation without water limitation and a dripline depth of 15 cm), SSDI2 (similar to SSDI1 but with mild/moderate water deficit during the fruit ripening stage), and SSDI3 (subsurface drip irrigation without water limitation and a dripline depth of 35 cm (first year) and 25 cm (second year)). Measurements included crop vegetative growth, leaf water potential, leaf gas exchange, nitrate concentration in soil solution, and crop yield and quality. The soil water balance components (actual evaporation, actual transpiration, deep drainage), necessary for determining the total crop water footprint, were simulated on a daily scale using Hydrus 2D software. Results indicated that SSDI makes more efficient use of irrigation water than SDI. The water footprint of SSDI1 was 20–35% lower than that of SDI1. SSDI2 showed similar water footprint values to SDI1 under highly demanding environmental conditions and significantly lower values (≈40%) in a year with lower evaporative demand. The dripline depth in SSDI was critical to the water footprint. With a 35 cm installation depth, SSDI3 had a significantly higher water footprint than the other treatments, while the values were similar to SSDI1 when the depth was reduced to 25 cm.

Global-scale improvement of the estimation of terrestrial gross primary productivity by integrating optical and microwave remote sensing with meteorological data

Photosynthesis (a key ecological process) is measured based on gross primary productivity (GPP), emphasizing the criticality of accurate GPP estimation to climate change research. The extant remote sensing-based approaches for GPP estimation were typically based on optical remote sensing data, neglecting the potential supplementary information from microwave remote sensing data. Thus, based on the random forest algorithm, we developed a GPP model through the integration of optical and microwave remote sensing with meteorological data (OMM-GPP). The software and tools used for data processing, modeling, and analysis are the standard and third-party libraries based on the Python Language. Our OMM-GPP model was trained and validated using GPP data (referred to as “observed GPP”) retrieved from carbon dioxide fluxes measured at 137 flux towers. The results indicated that GPP estimation by integrating optical and microwave data with meteorological data was more accurate than GPP estimation by integrating single-source remote sensing data (optical or microwave data) with meteorological data across eight vegetation types. The model performed well on daily and monthly scales, with determination coefficients (R2) (root-mean-square errors, RMSE) of 0.85 (1.52 gC m−2 d−1) and 0.83 (1.49 gC m−2 d−1), respectively, which increased (decreased) by 0.17–0.03 (0.58–0.12 gC m−2 d−1) and 0.11–0.02 (0.39–0.10 gC m−2 d−1) compared with the R2 (RMSE) values obtained by integrating single-source remote sensing data with meteorological variables. Further, the OMM-GPP model effectively captured the seasonal variations in daily and monthly GPP across most vegetation types. The eight-day-scale comparison of the model with the VODCA2GPP dataset revealed its enhanced performances, increasing R2 by 0.33 and decreasing RMSE by 0.97 gC m−2 d−1. Overall, the integration of microwave and optical remote sensing data with meteorological data can enhance GPP estimation accuracy, as demonstrated by the established OMM-GPP, across different vegetation types.

Correlation Between Spirituality and The Level of Psychological Well-Being in the Elderly at Banyuwangi Nursing Home

Background: Elderly in nursing homes face various problems such as a decline in body condition and health due to the aging process which has an impact on psychological well- being. Problems in psychological well-being can be addressed through spirituality, which functions as a coping mechanism. Purpose: This study aims to analyze the relationship between spirituality and the level of psychological well-being in elderly at nursing home in Banyuwangi. Methods: This study is a quantitative study, correlational study design with a cross sectional approach. The sample in this study consisted of 42 respondents selected using a total sampling according to inclusion and exclusion criteria. This study used the Daily Spiritual Experience Scale (DSES) questionnaire and the Psychological Well-Being Scale (PWBS) questionnaire. Results: Descriptive analysis showed that the majority of elderly at nursing home in Banyuwangi had a high level of spirituality (50.0%) and a high level of psychological well-being (38.1%). Based on the Kendall's Tau b correlation test, the p-value was 0.001, indicating there is relationship between spirituality and the level of psychological well-being in the elderly at nursing home in Banyuwangi. The results of the r-value was +0.487, show there is a positive correlation which means the higher the level of spirituality in the elderly, the higher the level of psychological well-being. Conclussion: spirituality has an important role in improving the psychological well-being of the elderly, so efforts can be made to improve the psychological well-being in the elderly by increasing spirituality in the elderly.

Edentulism and quality of life in the Salvadoran population: a cross-sectional study

IntroductionEdentulism is the partial or total loss of teeth, it is irreversible and disabling due to its sequelae in the masticatory, phonetic and aesthetic function that affect the quality of life.ObjectiveTo establish the impact of edentulism and sociodemographic factors on the quality of life of the Salvadoran population.Materials and methodsSecondary cross-sectional analysis of data in 3322 users of the Public Health System of El Salvador, aged 15 to > 60 years. The variables under study were sociodemographic, edentulismo and quality of life. Edentulism was determined by clinical examination using the Oral Impact on Daily Performance scale. The statistical analysis was performed using χ2, OR, multiple regression analysis and set the significance threshold at p < 0.05.ResultsPartial edentulism in the upper jaw was present in 68.24% people, partial edentulism in the lower jaw was present in 72.42% people and complete edentulism was observed in 2.02% people. There were significant sex differences and a relationship between sex and quality of life (p < 0.004); the self-perception of severe/very severe impacts was greater in women. People without education or with primary or secondary education only were the most affected (p < 0.05). Tooth loss increases with age, affecting quality of life in a severe/very severe manner. Complete edentulism had greater impacts on quality of life in terms of eating (25.64%), speaking (21.15%), and socializing/enjoying contact with people (10.90%). A severe/very severe impact on quality of life of teeth lost was reported mainly by those over 60 years of age, with an average of 11 missing posterior teeth, 6 missing anterior teeth and 13 missing teeth per patient. Those missing up to 6 anterior teeth were times more likely to perceive severe/very severe impacts on quality of life than those without any missing teeth (OR:5.788). Edentulism affected the quality of life of those examined, especially the loss of upper anterior teeth.

Multi-time Scale Variation of Atmospheric Ammonia Concentration and Dry Deposition in a Paddy Rice Region in Subtropical China

Meteorological factors and anthropogenic activities significantly affect atmospheric ammonia （NH3） concentration and its dry deposition. Former studies have examined the spatial and temporal variability in atmospheric NH3 concentrations at monthly scales. However, the characteristics of atmospheric concentrations at finer time scales such as hourly and daily scales and the influencing factors remain unclear. In this study, atmospheric NH3 concentration and related meteorological factors were continuously monitored online for one year in a double cropping rice region in subtropical China, and atmospheric NH3 concentration and its meteorological influencing factors as well as dry deposition were analyzed at different time scales （hourly, daily, and monthly）. The main results were as follows： The annual average daily concentration of NH3 in the rice area varied from 0.01 to 58.0 μg·m-3 （in N, same below）, and the annual average concentration was 5.3 μg·m-3. On the hourly scale, the 24-hour dynamics of atmospheric NH3 concentration showed a unimodal pattern, and the time of the NH3 peak appearance in different seasons was different； the time of the peak that appeared in winter lagged behind that in the other seasons. From the perspective of daily scale, NH3 concentration was mainly affected by fertilization in the paddy fields, peaking at 1-3 days after fertilization and then gradually decreasing. On the monthly scale, NH3 concentration peaked at 12.8 μg·m-3 in July and was the lowest in October at 1.6 μg·m-3. On the hourly scale, NH3 concentration varied seasonally due to the influences of meteorological factors, mainly as follows： NH3 concentration showed significant positive correlations with air temperature and solar radiation in all four seasons and with wind speed in spring and summer, whereas it showed significant negative correlations with relative humidity except in winter. On the daily scale, NH3 concentration showed a significant positive correlation with air temperature, rainfall, and solar radiation, whereas it showed a significant negative correlation with relative humidity. On the monthly scale, no significant correlation existed between each meteorological factor and NH3 concentration. The annual dry deposition flux （in N） calculated from the hourly average NH3 concentration was 8.5 kg·（hm2·a）-1, which was 11.6% higher than the annual flux calculated from the daily average and 12.4% higher than the annual flux calculated from the monthly average. In summary, there were significant daily and seasonal variations in atmospheric NH3 concentration in the paddy rice region in subtropical China, and conducting hourly-scale observations of NH3 concentration can help to reveal the multi-time scale variations in NH3 concentration and to quantify NH3 dry deposition more accurately.

Hyperadrenergic Postural Tachycardia Syndrome: Clinical Biomarkers and Response to Guanfacine.

A subset of patients with postural tachycardia syndrome (POTS) are thought to have a primary hyperadrenergic cause. We assessed clinical biomarkers to identify those that would benefit from sympatholytic therapy. We measured sympathetic function (supine muscle sympathetic nerve activity, upright plasma norepinephrine, and blood pressure responses to the Valsalva maneuver) in 28 patients with POTS (phenotyping cohort) to identify clinical biomarkers that are associated with responsiveness to the central sympatholytic guanfacine in a separate uncontrolled treatment cohort of 38 patients that had received guanfacine clinically for suspected hyperadrenergic POTS (HyperPOTS). In the phenotyping cohort, an increase in diastolic blood pressure (DBP) >17 mm Hg during late phase 2 of the Valsalva maneuver identified patients with the highest quartile of resting muscle sympathetic nerve activity (HyperPOTS) with 71% sensitivity and 85% specificity. In the treatment cohort, patients with HyperPOTS, identified by this clinical biomarker, more often reported clinical improvement (85% versus 44% in nonhyperadrenergic; P=0.016), had better orthostatic tolerance (∆Orthostatic Hypotension Daily Activities Scale: -1.9±0.9 versus 0.1±0.5; P=0.032), and reported less chronic fatigue (∆PROMIS Fatigue Short Form 7a: -12.9±2.7 versus -2.2±2.2; P=0.005) in response to guanfacine. These results are consistent with the concept that POTS is caused by a central sympathetic activation in a subset of patients, which can be identified clinically by an exaggerated DBP increase during phase 2 of the Valsalva maneuver and improved by central sympatholytic therapy. These results support further clinical trials to determine the safety and efficacy of guanfacine in patients with POTS enriched for the presence of this clinical biomarker.

Estimating visibility and understanding factors influencing its variations at Bangkok airport using machine learning and a game theory-based approach.

In this study, six individual machine learning (ML) models and a stacked ensemble model (SEM) were used for daytime visibility estimation at Bangkok airport during the dry season (November-April) for 2017-2022. The individual ML models are random forest, adaptive boosting, gradient boosting, extreme gradient boosting, light gradient boosting machine, and cat boosting. The SEM was developed by the combination of outputs from the individual models. Furthermore, the impact of factors affecting visibility was examined using the Shapley Additive exPlanation (SHAP) method, an interpretable ML technique inspired by the game theory-based approach. The predictor variables include different air pollutants, meteorological variables, and time-related variables. The light gradient boosting machine model is identified as the most effective individual ML model. On an hourly time scale, it showed the best performance across three out of four metrics with the ρ = 0.86, MB = 0, ME = 0.48km (second lowest), and RMSE = 0.8km. On a daily time scale, the model performed the best for all evaluation metrics with ρ = 0.92, MB = 0.0km, ME = 0.3km, and RMSE = 0.43km. The SEM outperformed all the individual models across three out of four metrics on an hourly time scale with ρ = 0.88, MB = 0.0km, (second lowest), and RMSE = 0.75km. On the daily scale, it performed the best with ρ = 0.93, MB = 0.02km, ME = 0.27km, and RMSE = 0.4km. The seasonal average original (VISorig) and meteorologically normalized visibility (VISnorm) decrease from 2017 to 2021 but increase in 2022. The rate of decrease in VISorig is double than rate of decrease in VISnorm which suggests the effect of meteorology visibility degradation. The SHAP analysis identified relative humidity (RH), PM2.5, PM10, day of the season year (i.e., Julian day) (JD), and O3 as the most important variables affecting visibility. At low RH, visibility is not sensitive to changes in RH. However, beyond a threshold, a negative correlation between RH and visibility is found potentially due to the hygroscopic growth of aerosols. The dependence of the Shapley values of PM2.5 and PM10 on RH and the change in average visibilities under different RH intervals also suggest the effect of hygroscopic growth of aerosol on visibility. A negative relationship has been identified between visibility and both PM2.5 and PM10. Visibility is positively correlated with O3 at lower to moderate concentrations, with diminishing impact at very high concentrations. The JD is strongly negatively related to visibility during winter while weakly associated positively later in summer. Findings from this research suggest the feasibility of employing machine learning techniques for predicting visibility and understanding the factors influencing its fluctuations.

Young Adults' Daily Participation Scale: A measure of objective and subjective participation.

Participation in occupations is considered essential for individuals' health and wellbeing. Participation is a multidimensional construct that encompasses objective and subjective dimensions that transform over the course of life. Nonetheless, there is a lack of comprehensive measures that examine young adults' participation in age-appropriate activities. Therefore, we developed the Young Adults' Daily Participation Scale (YADAPS) and aimed to explore its psychometric properties. In Study 1, the content validity of the YADAPS was established based on nine experts. Its internal consistency, criterion, convergent, and construct validity were explored among 115 typical young adults (21-35 years). Using a different sample, Study 2 examined YADAPS discriminant validity among 33 young adults with developmental coordination disorder (DCD) and 52 typical peers. No consumer and community involvement was included in these studies. The relevance of YADAPS items was sufficient. Internal consistency was acceptable to excellent in most scales (.74 ≤α≤ .89). Criterion validity was supported by correlations between the subjective participation scales and a wellbeing measure. Convergent validity was found for all scales. No gender effect was observed (p≥ .05). However, significant differences (p≤ .05) were found between individuals with and without DCD. The YADAPS appears to be a promising measure of objective and subjective dimensions of participation in young adults. The results support the importance of examining various participation dimensions, including occupational experience. Thus, it may be used for clinical purposes among young adults as well as for occupational science research, to broaden our understanding on the interplay between participation dimensions in various life situations in young adulthood. However, further research is needed on psychometric properties, the most suited scoring method, and to consolidate their robustness among diverse populations of young adults. Participation, or how one engages in daily life activities, greatly affects wellbeing. The activities in one's routine change over the lifespan, in accordance with one's developmental phase. Existing assessments of participation have limitations, like not considering young adults' concerns or only focussing on certain aspects of participation. By focussing on both the objective-observable and subjective-experiential aspects of participation, the Young Adults' Daily Participation Scale (YADAPS) strives to be a comprehensive assessment tool designed specifically for reflecting activities relevant in young adulthood. This manuscript provides preliminary validity and reliability for the YADAPS, a new questionnaire that assesses objective and subjective aspects of participation in activities relevant for individuals in young adulthood. Furthermore, the questionnaire is able to distinguish between young adults with and without participation difficulties; therefore, it is suitable for research and clinical use.

The ratio of transpiration to evapotranspiration and water use efficiency in an irrigated oasis agroecosystem: Different temporal-scale effects

Agroecosystems play an important role in carbon sequestration and water consumption of global terrestrial ecosystems. However, the magnitude, pattern, and regulation of the ratio of transpiration to evapotranspiration (T/ET), and also water use efficiency at ecosystem (WUEe) and canopy (WUEc) scales, remain unclear in agroecosystems in arid areas. In this study, a six-year synchronous observation of water-carbon fluxes and sap flow by the eddy covariance and sap flow techniques was conducted in an irrigated vineyard in northwest China. We found that T/ET, WUEe, and WUEc changed dynamically at the daily (1.0–98.6%, 0.3–4.9 g C kg–1 H2O, 0.4–5.9 g C kg–1 H2O) and monthly (26.0–71.0%, 0.8–1.8 g C kg–1 H2O, 2.3–3.2 g C kg–1 H2O) scales. At the annual scale, the range was relatively narrow, with mean values of 61.7% ± 3.7%, 1.5 ± 0.1 g C kg–1 H2O, and 2.4 ± 0.3 g C kg–1 H2O, respectively (mean ± standard deviation). Biological and environmental factors regulated their dynamics on different temporal scales. Specifically, leaf area index (LAI) and canopy conductance (gc) mainly determined the seasonal variation of T/ET, WUEe, and WUEc at the daily and monthly scales. However, at the annual scale, vapor pressure deficit (VPD) and air temperature (Ta) became the main influencing factors. These results highlight the complexity of water-carbon coupling in agroecosystems and the necessity of considering specific factors at different temporal scales when modeling and managing agricultural water resources. In addition, there is still great water-saving potential from the perspective of WUE in the cultivation of vines in Northwest China.

Effectiveness of a spiritual adaptation of cognitive behavioural therapy in improving resilience, self-esteem and spirituality among clients with opioid use disorder: A quasi-experimental study.

INTRODUCTION: Opioid use disorder (OUD) is a prevalent problem among Egyptian youth, and achieving recovery and abstinence is challenging. Cognitive behavioural therapy (CBT), a well-known approach, can be particularly beneficial when it addresses psychological aspects such as resilience, self-esteem and spirituality. This study aimed to evaluate the effectiveness of a spiritual adaptation of CBT in enhancing these factors among clients with OUD. A quasi-experimental study with a control group was conducted using a pretest-posttest design. The study included 49 clients with OUD and 46 clients in the control group. The Rosenberg Self-Esteem Scale-Modified Arabic Version, Daily Spiritual Experience Scale, and the Connor-Davidson Resilience Scale were used as measurement tools. CBT was delivered in 60-min group sessions. After 3 months, the questionnaires were re-administered to evaluate the effectiveness of a spiritual adaptation of CBT sessions. The study found a statistically significant increase in the mean scores of resilience, self-esteem and spirituality (p < .001 each) following a spiritual adaptation of CBT sessions compared to the control group. A spiritual adaptation of CBT effectively enhanced resilience, self-esteem and spirituality in clients with OUD. Understanding the effectiveness of a spiritual adaptation of CBT in enhancing resilience, self-esteem and spirituality can enable psychiatrists and nurses to provide more comprehensive and effective care to patients with OUD.

Two sub-annual timescales and coupling modes for terrestrial water and carbon cycles.

To bridge the knowledge gap between (a) our (instantaneous-to-seasonal-scale) process understanding of plants and water and (b) our projections of long-term coupled feedbacks between the terrestrial water and carbon cycles, we must uncover what the dominant dynamics are linking fluxes of water and carbon. This study uses the simplest empirical dynamical systems models-two-dimensional linear models-and observation-based data from satellites, eddy covariance towers, weather stations, and machine-learning-derived products to determine the dominant sub-annual timescales coupling carbon uptake and (normalized) evaporation fluxes. We find two dominant modes across the Contiguous United States: (1) a negative correlation timescale on the order of a few days during which landscapes dry after precipitation and plants increase their carbon uptake through photosynthetic upregulation. (2) A slow, seasonal-scale positive covariation through which landscape drying leads to decreased growth and carbon uptake. The slow (positively correlated) process dominates the joint distribution of local water and carbon variables, leading to similar behaviors across space, biomes, and climate regions. We propose that vegetation cover/leaf area variables link this behavior across space, leading to strong emergent spatial patterns of water/carbon coupling in the mean. The spatial pattern of local temporal dynamics-positively sloped tangent lines to a convex long-term mean-state curve-is surprisingly strong, and can serve as a benchmark for coupled Earth System Models. We show that many such models do not represent this emergent mean-state pattern, and hypothesize that this may be due to lack of water-carbon feedbacks at daily scales.

Responses of sap flow in Larix principis-rupprechtii to environment under different weather conditions.

This study was conducted in Liupanshan Forest Ecological Positioning Station of the National Forestry and Grassland Administration. We monitored sap flow of Larix principis-rupprechtii plantation in the Xiangshui River sub-basin throughout the 2019 growing season (from May 17 to October 12), as well as the meteorological conditions and soil environment (soil temperature and soil water content), to analyze the comprehensive environmental responses of sap flow in L. principis-rupprechtii under different weather conditions. The results showed that sap flow rate increased and then decreased on the daily scale, with the highest rate on sunny days, followed by overcast days and then rainy days. Sap flow rate had a single peak on sunny days and multiple peaks on overcast and rainy days. Sunny days had earlier and longer sap flow compared to overcast and rainy days. Dominant factors driving sap flow differed across different weather. Vapor pressure deficit was the dominant factor influencing sap flow in sunny and overcast days, while solar radiation was dominant one in rainy days. The contribution rates of main factors to sap flow on sunny, overcast and rainy days were 31.1%, 27.4% and 40.1%, respectively. Results of the principal component analysis showed the factors affecting sap flow on sunny days could be classified into hydrothermal complex factors (air temperature, soil temperature, and volumetric soil moisture), water vapor transpiration factors (relative humidity and vapor pressure deficit), and radiation factor (solar radiation). The factors affecting sap flow on overcast and rainy days were combined into transpiration (relative humidity, solar radiation, and vapor pressure deficit), heat (air temperature and soil temperature), and soil water factor volumetric (volumetric soil moisture). On sunny days, sap flow reached the peak value 110, 80, 70 min after the hydrothermal, water vapor transpiration, and radiation factors, respectively. On overcast and rainy days, sap flow reached its peak in 10, 20, 30 min and 140, 60, 150 min, respectively before the peaks of transpiration, heat, and soil water factors.

Drought Characterization With GPS: Insights Into Groundwater and Surface‐Reservoir Storage in California

AbstractDrought intensity is commonly characterized using meteorologically‐based metrics that do not provide insight into water deficits within deeper hydrologic systems. In contrast, global positioning system (GPS) displacements are sensitive to both local and regional hydrologic‐storage fluctuations. While a few studies have leveraged this sensitivity to produce geodetic drought indices, hydrologic drought characterization using GPS is not commonly accounted for in drought assessment and management. To motivate this application, we produce a new geodetic drought index (GDI) and quantify its ability to characterize hydrologic drought conditions in key surface and sub‐surface hydrologic reservoirs/pools across California. In northern California, the GDI exhibits a strong regional association with surface‐reservoir storage at the 1‐month time scale (correlation coefficient: 0.83) and groundwater levels at the 3‐month time scale (correlation coefficient: 0.87), along with moderate associations with stream discharge at the daily (instantaneous) time scale (correlation coefficient: 0.50). Groundwater in southern California is best characterized with a 12‐month GDI (correlation coefficient: 0.77), and surface‐reservoir storage is optimized with the 3‐month GDI (correlation coefficient: 0.72). Two sigma uncertainties are ±0.03. Differences between northern and southern California reveal that the GDI is sensitive to unique aquifer and drainage basin characteristics. In addition to capturing long‐term hydrologic trends, rapid changes in the GDI initiate during clusters of large atmospheric river events that closely mirror fluctuations in traditional hydrologic and meteorological observations. We show that GPS‐based hydrologic drought indices provide a significant opportunity to improve drought assessment, in California and beyond, by improving our understanding of the hydrologic cycle.