Significant Explanatory Variables Research Articles

Assessment of understory vegetation in a plantation forest of the southeastern United States using terrestrial laser scanning

Forests of the southeastern United States are home to large timber industries with substantial contributions to global round wood production and paper products. Despite the success of plantations and the large timber industries in this area, pine growth remains constrained due to the competition between planted pine and the species in the understory. Moreover, effective control of this interspecies competition had shown a significant two- to four-times increase in stand productivity. Thus, this study aims to evaluate the use of laser scanning derived data from Terrestrial Laser Scanner (TLS) to assess understory vegetation biomass, as conventional methods utilizing optical imagery have yet to be effective in quantifying and mapping evergreen understory in the southeastern coastal forests of the United States. For this study, we utilized TLS to scan the entire forest profile within 60 sample plots of an operational loblolly pine plantation in Nassau County, Florida, and collected understory biomass data through destructive sampling. We compared three TLS-based volume estimation methods for predicting understory biomass and applied the Adaptive Least Absolute Shrinkage and Selection Operator (ALASSO) regression method to derive an optimal model by integrating the most efficient volume estimation methods and other TLS-derived standard metrics. Our study identifies the 20th percentile of the echo height and a 3D volume metric based on mean height and understory cover as the most significant explanatory variables for the optimal model. The model exhibits high accuracy, with Adjusted R-squared (Adj. R2) of 0.80 and Root Mean Square Error (RMSE) of 234.8 g per square meter (g/m2). Additionally, the mean height and understory-based volume estimation method outperformed other methods, such as voxel count and three dimensional (3D) alpha hall-based method, with Adj. R2 of 0.79, 0.47, and 0.57, and RMSE values of 288, 448.6, and 413 g/m2, respectively, when used as a single variable in the model. The resulting model successfully predicted and quantified understory vegetation, showcasing TLS's potential to accurately capture biomass variation, particularly in evergreen-dominated pine plantation forests in the southeastern United States coastal regions. As a tool for monitoring understory, TLS can be used to aid plantation forest managers in identifying areas that require control measures for enhanced management practices.

Factors associated with bark beetle infestations of Colorado Plateau ponderosa pine using repeatedly-measured field plots

Decades of research have brought increasing focus to the biotic and abiotic factors associated with bark beetle infestation of North American conifers. Information is lacking, however, regarding beetle-caused mortality for ponderosa pine of the Colorado Plateau. From 1995 to 2019, we installed and periodically remeasured permanent plots in this forest type with a goal of identifying factors related to infestation probability including tree and stand characters, and abiotic factors such as temperature and precipitation. Forty-eight sites were distributed throughout the Colorado Plateau, each with two transects of 10 contiguous ∼ 0.04 ha circular plots. Stand and tree conditions were measured or interpolated for each year from plot establishment in 1995 until the final measurements in 2019. Temperature, precipitation, and other abiotic conditions were estimated from Daymet interpolations. We used a generalized linear mixed model to identify significant explanatory variables resulting in the best accuracy of predicting stem-level bark beetle-caused pine mortality. Tree and stand conditions were found related to the probability of infestation. Pines >15.2 cm dbh were more likely to become infested compared to pines below that threshold; no relationship was found above that breakpoint. Similarly, stems 80–180 years old had elevated probability of infestation compared to stems < 80 years; stems > 180 years were intermediate. Pines with poor crown vigor (low crown volume, suppressed or intermediate canopy position) were more likely to become infested compared to pines with good crown vigor (high crown volume, dominant or open grown canopy position). Pine basal area (BA), a surrogate for intra-species competition, was positively related to probability of infestation. Pine BA infested the previous year, a surrogate for beetle population size, was also positively related to probability of infestation. Several drought- and precipitation-related variables resulted in similar model accuracy. Best model fit among these, by a slight margin, was contemporaneous climate water deficit (CWD), a measure of plant water stress, summed from April-August. Increasing CWD was associated with increased probability of infestation. Finally, counts of days above 16 °C the previous year were negatively related to infestation probability. That is, relatively warm weather during the previous year was associated with reduced beetle success, possibly because it can result in fractional beetle life cycles that disrupt synchronized attacks on new hosts or leave overwintering brood in less cold hardy life stages.

Key Debt Drivers of Local Governments: Empirical Evidence on Municipalities in Poland

In the literature, the debt burden in local governments is considered as a main predictor of the fiscal distress. The growing indebtedness of the municipalities may also negatively affect the business sector. Therefore, this paper examines the significance of key financial and non-financial debt drivers of local governments based on the example of the municipalities functioning in Poland in 2010-2021. The article studies the whole population of the above public units and the influence of the financial, economic, demographic, institutional and spatial factors on their indebtedness. Due to the data, methodology and the robustness check, the fixed effects panel models, Arellano and Bond’s two-step generalized method of moments and the Moran I and LISA statistics were applied. Therefore, the final regressions include significant explanatory variables and might contribute to more efficient debt management and its control. The paper also reveals spatial associations in the field of the indebtedness of local governments.

Mobile Assessments of Mood, Cognition, Smartphone-Based Sensor Activity, and Variability in Craving and Substance Use in Patients With Substance Use Disorders in Norway: Prospective Observational Feasibility Study.

Patients with substance use disorders (SUDs) are at increased risk for symptom deterioration following treatment, with up to 60% resuming substance use within the first year posttreatment. Substance use craving together with cognitive and mental health variables play important roles in the understanding of the trajectories from abstinence to substance use. This prospective observational feasibility study aims to improve our understanding of specific profiles of variables explaining SUD symptom deterioration, in particular, how individual variability in mental health, cognitive functioning, and smartphone use is associated with craving and substance use in a young adult clinical population. In this pilot study, 26 patients with SUDs were included at about 2 weeks prior to discharge from inpatient SUD treatment from 3 different treatment facilities in Norway. Patients underwent baseline neuropsychological and mental health assessments; they were equipped with smartwatches and they downloaded an app for mobile sensor data collection in their smartphones. Every 2 days for up to 8 weeks, the patients were administered mobile ecological momentary assessments (EMAs) to evaluate substance use, craving, mental health, cognition, and a mobile Go/NoGo performance task. Repeated EMAs as well as the smartphone's battery use data were averaged across all days per individual and used as candidate input variables together with the baseline measures in models of craving intensity and the occurrence of any substance use episodes. A total of 455 momentary assessments were completed out of a potential maximum of 728 assessments. Using EMA and baseline data as candidate input variables and craving and substance use as responses, model selection identified mean craving intensity as the most important predictor of having one or more substance use episodes and with variabilities in self-reported impulsivity, mental health, and battery use as significant explanatory variables of craving intensity. This prospective observational feasibility study adds novelty by collecting high-intensity data for a considerable period of time, including mental health data, mobile cognitive assessments, and mobile sensor data. Our study also contributes to our knowledge about a clinical population with the most severe SUD presentations in a vulnerable period during and after discharge from inpatient treatment. We confirmed the importance of variability in cognitive function and mood in explaining variability in craving and that smartphone usage may possibly add to this understanding. Further, we found that craving intensity is an important explanatory variable in understanding substance use episodes.

Positive attitudes toward adoption of a multi-component intervention strategy aimed at improving HIV outcomes among adolescents and young people in Nampula, Mozambique: perspectives of HIV care providers

BackgroundService providers' attitudes toward interventions are essential for adopting and implementing novel interventions into healthcare settings, but evidence of evaluations in the HIV context is still limited. This study is part of the CombinADO cluster randomized trial (ClinicalTrials.gov NCT04930367), which is investigating the effectiveness of a multi-component intervention package (CombinADO strategy) aimed at improving HIV outcomes among adolescents and young adults living with HIV (AYAHIV) in Mozambique. In this paper we present findings on key stakeholder attitudes toward adopting study interventions into local health services.MethodsBetween September and December 2021, we conducted a cross-sectional survey with a purposive sample of 59 key stakeholders providing and overseeing HIV care among AYAHIV in 12 health facilities participating in the CombinADO trial, who completed a 9-item scale on attitudes towards adopting the trial intervention packages in health facilities. Data were collected in the pre-implementation phase of the study and included individual stakeholder and facility-level characteristics. We used generalized linear regression to examine the associations of stakeholder attitude scores with stakeholder and facility-level characteristics.ResultsOverall, service-providing stakeholders within this setting reported positive attitudes regarding adopting intervention packages across study clinic sites; the overall mean total attitude score was 35.0 ([SD] = 2.59, Range = [30–41]). The study package assessed (control or intervention condition) and the number of healthcare workers delivering ART care in participating clinics were the only significant explanatory variables to predict higher attitude scores among stakeholders (β = 1.57, 95% CI = 0.34–2.80, p = 0.01 and β = 1.57, 95% CI = 0.06–3.08, p = 0.04 respectively).ConclusionsThis study found positive attitudes toward adopting the multi-component CombinADO study interventions among HIV care providers for AYAHIV in Nampula, Mozambique. Our findings suggest that adequate training and human resource availability may be important in promoting the adoption of novel multi-component interventions in healthcare services by influencing healthcare provider attitudes.

A structural model of nursing students’ performing communication skills

Purpose: The purpose of this study was to construct and test a structural model of nursing students’ performing communication skills.Methods: The data collection was conducted from October 13 to October 20, 2020. The participants were 286 students from nursing colleges located in three cities. The data analysis method was a covariance structure analysis with using IBM SPSS statistics version 23.0 and AMOS 21.0 statistical programs.Results: The hypothetical model showed a proper fit with the data: root mean square error of approximation=.08, standardized root mean square residual=.06, adjusted goodness of fit=.85, normed fit index=.91, and comparative fit index=.94. The model fit indices were normed to fit index=2.96. Statistically significant explanatory variables for the performing communication skills of nursing students were peer support, emotional intelligence, ethical sensitivity, and communication self-efficacy. The variables accounted for 66.1% of the performing communication skills of nursing students.Conclusion: Based on the above results, it appears necessary to develop strategies for improving the performing communication skills of nursing students, and having positive effects on health outcomes of the subjects by considering the variables of peer support, emotional intelligence, ethical sensitivity, and communication self-efficacy. Such strategies could potentially have positive effects on the health outcomes of the patients.

Exploring the "Insight Paradox" in Treatment-Resistant Schizophrenia: Correlations Between Dimensions of Insight and Depressive Symptoms in Patients Receiving Clozapine.

There remains a lack of clarity as to the possible cross talk of insight into illness and depressive symptoms in treatment-resistant schizophrenia. We therefore set our primary aim to evaluate relationship between insight dimensions and depressive symptoms in patients with treatment-resistant schizophrenia receiving clozapine. This was a cross-sectional, non-interventional study, conducted in daily clinical practice conditions. Patients in outpatient clinics between March 2020 and May 2020 with treatment-resistant schizophrenia (based on Treatment Response and Resistance in Psychosis), with no comorbid psychiatric disorder, and with no body mass index greater than 40.0 kg/m2 were included. We collected sociodemographic variables, scores of insight dimensions (treatment compliance, illness recognition, and symptom relabeling with the Schedule for Assessment of Insight), and depressive symptoms with Calgary Depression Score for Schizophrenia. Linear regression models were used to investigate variables associated with depressive symptoms as the outcome of interest. The final analysis sample comprised 55 patients with treatment-resistant schizophrenia, with a mean age of 42.48 (SD = 9.18) years and a predominance of the male sex (n = 42, 76.9%). Model 1 [Calgary Depression Score for Schizophrenia ~ (Schedule for Assessment of Insight + Positive and Negative Syndrome Scale)] displayed that 48% of the variation in the Calgary Depression Score for Schizophrenia can be explained by Schedule for Assessment of Insight-composite and Positive and Negative Syndrome Scale-composite (P < .001). More effectively, model 2 [Calgary Depression Score for Schizophrenia ~ (Schedule for Assessment of Insight-illness recognition + Positive and Negative Syndrome Scale-general psychopathology)] revealed that 51% of the variation in the Calgary Depression Score for Schizophrenia can be explained by the sub-scales (P < .001). We further designed a new model in which Global Assessment of Functioning scores were the response variable to explore the link between awareness into illness and functionality (Global Assessment of Functioning ~ Schedule for Assessment of Insight-illness recognition). In this model, awareness of illness did not explain a significant proportion of variance in functionality scores (R 2 = 0.045, F(1,52) = 2.48, P = 0.121). The treatment compliance part of insight was not one of the significant explanatory variables of depressive symptoms, but it explained the variance in functioning, in contrast to the illness recognition dimension of insight. If our findings were replicated in treatment-resistant schizophrenia, they would suggest that promoting treatment compliance dimension of insight instead of recognition of illness could not increase depressive symptoms.

An intercontinental machine learning analysis of factors explaining consumer awareness of food risk

Food safety is a common concern at the household level, with important variations across different countries and cultures. Nevertheless, identifying the factors that best explain similarities and differences in consumer awareness pertaining to this topic is not straightforward. Starting from a questionnaire administered in seven countries from four continents (Argentina, Brazil, Colombia, Ghana, India, Peru, and the United Kingdom), we present an analysis of the answers related to food safety concerns, aimed at identifying possible explanatory factors. As classical statistical approaches can be limited when dealing with complex datasets, we propose an analysis with machine learning techniques, that can take into account both categorical and numerical values. With the questionnaire as a base, we task a machine learning algorithm, Random Forest, with predicting consumers’ answers to the target questions using information from all other answers. Once the algorithm is trained, it becomes possible to obtain a ranking of the questions considered the most important for the prediction, with the top-ranked questions likely representing explanatory factors. Top-ranked questions are then analyzed using a Random Forest regression algorithm, to test possible correlations. The results show that the most significant explanatory variables of safety concerns seem to be estimates of carbon footprints and calories associated with food products, and primarily with beef and chicken meat. These results tend to indicate that people who are most concerned about food safety are also those who are highly aware of environmental and nutritional impacts of food, hinting at differences in food education as a possible underlying explanation for the data.

Effects of Head and Neck Alignment and Pharyngeal Anatomy on Epiglottic Inversion During Swallowing in Dysphagic Patients.

The effects of head and neck alignment and pharyngeal anatomy on epiglottic inversion remain unclear. This study investigated the factors involved in epiglottic inversion, including head and neck alignment and pharyngeal anatomy, in patients with dysphagia. Patients with a chief complaint of dysphagia and who underwent videofluoroscopic swallowing study at our hospital from January to July 2022 were enrolled. They were divided into three groups based on the degree of epiglottic inversion as the complete-inversion (CI), partial-inversion (PI), and non-inversion group (NI) groups. Data were compared among the three groups; a total of 113 patients were analyzed. The median age was 72.0 (IQR: 62.0-76.0) years; 41 (36.3%) and 72 (63.7%) were women and men, respectively. There were in 45 (39.8%) patients in the CI, 39 (34.5%) in the PI, and 29 (25.7%) in the NI groups, respectively. Single-variable analysis revealed significant relation to epiglottic inversion of Food Intake LEVEL Scale score, penetration-aspiration score with 3-mL thin liquid bolus, epiglottic vallecula and pyriform sinus residue, hyoid position and displacement during swallowing, pharyngeal inlet angle (PIA), epiglottis to posterior pharyngeal wall distance, and body mass index. Logistic regression analysis with complete epiglottic inversion as the dependent variable revealed the X coordinate at maximum hyoid elevation position during swallowing and PIA as significant explanatory variables. These results suggest that epiglottic inversion is constrained in patients with dysphagia who have poor head and neck alignment or posture and a narrow pharyngeal cavity just before swallowing.

HIV testing among women of reproductive age in 28 sub-Saharan African countries: a multilevel modelling.

Human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) remains one of the most significant public health challenges globally, particularly in sub-Saharan Africa (SSA). Although HIV testing is a vital step for both prevention and treatment, its uptake is still low in SSA. We therefore examined HIV testing in SSA and its individual/household and community factors among women of reproductive age groups (15-49y). Demographic and Health Survey data collected between 2010 and 2020 from 28 SSA countries were used for this analysis. We analysed the coverage of HIV testing and individual/household and community factors on 384416 women in the reproductive age groups (15-49y). Bivariate and multivariable multilevel binary logistic regression analysis were conducted to select candidate variables and to identify significant explanatory variables associated with HIV testing and the results were presented using adjusted odd ratios (AORs) at 95% confidence intervals (CIs). The pooled prevalence of HIV testing among women of reproductive age in SSA was 56.1% (95% CI 53.7 to 58.4), with the highest coverage found in Zambia (86.9%) and the lowest in Chad (6.1%). Age (45-49y; AOR 0.30 [95% CI 0.15 to 0.62]), women's education level (secondary; AOR 1.97 [95% CI 1.36 to 2.84]) and economic status (richest; AOR 2.78 [95% CI 1.40 to 5.51]) were some of the individual/household factors associated with HIV testing. Similarly, religion (no religion; AOR 0.58 [95% CI 0.34 to 0.97]), marital status (married; AOR 0.69 [95% CI 0.50 to 0.95]) and comprehensive knowledge of HIV (yes; AOR 2.01 [95% CI 1.53 to 2.64]) were significantly associated individual/household factors for HIV testing. Meanwhile, place of residence (rural; AOR 0.65 [95% CI 0.45 to 0.94]) was found to be a significant community-level factor. More than half of married women in SSA have been tested for HIV, with between-country variations. Both individual/household factors were associated with HIV testing. Stakeholders should therefore consider all above-mentioned factors to plan an integrated approach to enhancing HIV testing through health education, sensitization, counselling and empowering older and married women, those with no formal education, those who do not have comprehensive HIV/AIDS knowledge and those in rural areas.

E071 Which clinical, ultrasound and OT hand assessments are most useful in predicting hand disability in early rheumatoid arthritis?

Abstract Background/Aims Developing a clear understanding of the features of hand involvement that are associated with future disability will assist in designing future OT clinical intervention studies and will aid in selecting RA patients for intensive hand therapy and early aggressive medical treatment. This study aimed to determine which hand assessments best predicted hand disability in patients with early Rheumatoid arthritis (RA). Methods 63 early RA patients with hand symptoms were identified from Rheumatology clinics in the Belfast Health and Social Care Trust. Assessments were undertaken at baseline and at 1 year. Hand disability outcome was measured using the Sequential Occupational Dexterity Assessment (SODA). Grip Strength (GS), Total Pain Score (PS), Modified Kapandji index (MK), Stanford Health Assessment Questionnaire (HAQ) and Moberg pick up test (MoV) were assessed by trained occupational therapists (OTs); Ultrasound assessments of hand and wrist were undertaken by trained rheumatologists. Summated (Global) hand and wrist Ultrasound activity score (G-UAS), hand and wrist Power Doppler score (G-PD), and ultrasound erosion score were calculated. Hand deformity score (DS), standardised hand X-ray, Das-28, RF and anti-CCP antibody were undertaken at each assessment. Results There was no significant change in the median SODA score after one year. The main static predictor for baseline SODA was HAQ (25% of the variability). DAS28, MK and Grip Average were statistically significant on their own accounting for between 6-10% variability in the model but when all significant explanatory variables were included HAQ was the only significant variable (23%). Regression for year 1 SODA showed that the main static predictor was MK (adjusted R-squared 59%). PS, DAS28 and GS were statistically significant on their own accounting for between 7-23% variability, but when all significant explanatory variables were included, the MK was the only one of significance (58%). Regressing all explanatory variables against SODA resulted in an adjusted R-squared of 61%: MK and G-UAS (although not significant on its own) were the only ones that were significant. When baseline data was used to predict year 1 SODA, HAQ, MK, PS, DAS28 and GS were statistically significant on their own, but when all significant explanatory variables were included only HAQ and MK were significant explaining 57% of the variability. When HAQ was excluded, PS, DAS28 and GS were statistically significant on their own accounting for between 10-19% variability. When all significant explanatory variables were included, MK was the only one that was significant (adjusted R-squared was 50%). Conclusion Amongst the variables assessed, the HAQ showed good overall prediction for SODA as expected. MK was the most reliable time-lag predictor of hand disability at one year in early RA. X-ray, MoV, GS and ultrasound assessments were much less associated but longer follow-up studies would be useful. Disclosure C. Harkness: None. E. Ball: None. S. Wright: None. E. Crone: None. E. Henry: None. L. Foster: None. H. Farmer: None. A. Bell: None.

Cultural competence in critical care nurses and its relationships with empathy, job conflict, and work engagement: a cross-sectional descriptive study

BackgroundCultural competence is more important than ever for nurses today; therefore, it may be helpful to learn more about it and examine how it relates to empathy, job conflict, and work engagement. The purpose of this study was to determine (a) the level of cultural competence, empathy, job conflict, and work engagement; (b) the relationship between cultural competence, demographic information, and main variables; (c) the predictors of cultural competence among critical care nurses.MethodsA multicenter, descriptive cross-sectional study was conducted in Iran from August to October 2022. Through convenience sampling, 153 critical care nurses from three hospitals participated. The research tool consisted of five parts: Demographic information questionnaire, Cultural Competence Questionnaire, Jefferson Scale Empathy, Dobrin Job Conflict, and Utrecht Work Engagement, which were collected by paper self-report. Descriptive statistics, the correlation between variables, and linear regression were used to analyze the data.ResultsAmong critical care nurses (response rate 79.27%), the mean (SD) scores for cultural competence, empathy, job conflict, and work engagement were 74.05 (7.96), 83.44 (29.17), 11.00 (2.38), and 43.69 (16.33), respectively. There was a significant correlation between cultural competence and age (r = 0.46, p = 0.001), marital status (r = 0.27, p = 0.004), academic degree (r = 0.44, p = 0.001), work experiences (r = 0.43, p = 0.001), empathy (r = 0.50, p = 0.001), and job conflict (r=-0.16, p = 0.049). Academic degree (β = 0.36, p < 0.001) and empathy (β = 0.26, p < 0.001) were significant explanatory variables that predict cultural competence.ConclusionIn Iranian critical care nurses, cultural competence and job conflict were moderate, empathy was good, and work engagement was poor. There was a significant relationship between cultural competence, age, marital status, academic degree, work experiences, empathy, and job conflict. Academic degree and empathy predict cultural competence.

Adjusting design floods for urbanization across groundwater-dominated watersheds of Long Island, NY

The magnitude and variability of floods have increased for many nontidal streams on Long Island (LI), NY since the mid-20th century. One of the most densely populated regions of the United States, LI has experienced amplified floods in step with increases in impervious land cover, storm, and sanitary sewers that have accompanied urban development. To better understand the drivers of observed flood trends and effects of urbanization, a nonstationary flood frequency analysis is conducted, using historical annual peak flow records from 17 gaged watersheds on LI using conditional moments based on physical covariates from a two-stage sequential robust linear regression procedure. Regression results indicate that urban development and precipitation are significant co-predictors of peak flows for LI watersheds that have undergone rapid development during the available peak flow record. In watersheds with less intense urbanization or that were fully developed before the peak flow record began, precipitation alone was a significant explanatory variable. Long-term baseflow patterns identified using a nonparametric smoother explained some patterns of decreasing peak flows and heteroskedasticity in the peak flow records. Fitting a log-Pearson III distribution with these conditional moments, floods corresponding to a 20% annual exceedance probability (AEP) are up to 80% higher under a nonstationary framework compared with stationary under current watershed conditions, and differ significantly (95% confidence) from stationary estimates for 6 out of 17 watersheds. Larger floods corresponding to 1% AEPs do not differ significantly between nonstationary and stationary estimates at a 95% confidence level. Nonmonotonic trends observed in two watersheds indicate that recent stormwater management practices, such as rerouting stormwater outfalls away from the channel, substantially reduce flood frequency. Reduced nonstationary flood quantile estimates at these two watersheds are 20 to 40% lower than stationary estimates when accounting for changing watershed conditions over time. Across LI, stormwater management and water-table fluctuations have increased peak flow variability, characteristic of a late phase urban adjustment period on LI. Results of this study demonstrate that a nonstationary framework is a necessary step forward toward a regional flood-frequency analysis for LI. This nonstationary framework will allow flood managers to update flood discharge estimates to current conditions that reflect altered relationships between urban cover and climate for more targeted planning of flood control, transportation infrastructure, and management of floodplain ecosystems.

The main factors that drive plant dieback under extreme drought differ among Mediterranean shrubland plant biotypes

AbstractQuestionsKnowledge of how extreme drought events induce plant dieback and, eventually, plant mortality, may improve our forecasting of ecosystem change according to future climate projections, especially in Mediterranean drylands. In them, shrublands are the main vegetation communities in transition areas from a subhumid to semi‐arid climate. This study analyzed differences in plant dieback after an unusual drought in 2014 and identified their main underlying factors in relation to three groups of explanatory variables: water availability, soil properties and vegetation structure attributes.LocationFour Mediterranean shrublands along a climatic gradient in SE Spain.MethodsAt each experimental field site, we sampled a pool of vegetation structure characteristics, soil depth and soil surface properties, and we also determined water availability by continuously monitoring soil moisture and the microclimate conditions.ResultsThe climatic analysis showed that there was an extreme drought event in 2014, which was below the first percentile of the driest years. Under such conditions, vegetation dieback occurred at all the study sites. However, plant dieback differed between sites and plant biotypes. Subshrubs were the main affected biotype, with diebacks close to 60% at the driest sites, and up to 40% dieback for shrubs depending on their vertical development. Relative extractable water and bare soil surface cover were the best explanatory variables of plant community dieback but changed between plant biotypes. Vegetation structure variables related to plant vertical development (leaf area index [LAI], plant height, phytovolume) were significant explanatory variables of plant dieback in shrubs, subshrubs and grasses. Consecutive dry days fitted the best model to explain subshrub dieback.ConclusionsWe found that rainfall pattern rather than total annual rainfall was the climatic factor that best determined water availability for plants in Mediterranean drylands. These results also pointed out the relevance of plant structure and soil properties for explaining ecosystem responses to extreme drought.

Exploring the Spatial Variation of Access/Egress Distances of Subway Stations Using Mobile Phone Positioning Data in Chengdu, China

The distance from the origin or destination to or from the subway station is defined as the access or egress distance, which determines the service coverage of the subway station. However, little literature studies the distances at the station level, and they may vary from station to station. Therefore, this study aims to explore the influencing factors and spatial variation of the distances at the station level by using the mobile phone positioning data of more than 1.2 million anonymous users in Chengdu, China. First, this study proposes a method to extract the access and egress trips of the subway. Next, the ordinary least squares (OLS) regression models are carried out to select the significant explanatory variables. Finally, the geographically weighted regression (GWR) models are used to model the spatial variation relationship between the 85th percentile access/egress distances and the selected explanatory variables. The results show that different stations’ access/egress distances vary significantly in space. Hotel, residence, life, finance, road density, and mixed land use are found to be negatively correlated with distances, while education, 36–45 years old, male, and high education are positively correlated. In addition, the GWR model reveals that the influence of explanatory variables on access/egress distance varies from space to space. The results further promote the understanding of the existing system and provide a relevant reference for planners and transportation departments to optimize land use and public transportation planning.

Effect of neonatal immunoglobulin status on the outcomes of spring-born suckler calves.

Successfully rearing beef calves to weaning and beyond determines the economic performance of a beef farm. As such, it is important to understand the factors influencing performance outcomes. This study recorded the health events, mortality and growth rates of 674 calves born on 50 commercial beef farms in Great Britain using a postsampling questionnaire. All calves had a known postcolostral serum IgG status. Preweaning mortality in the study population was 1.5% (10/674 calves), while the treatment rate was 6.4% (43/674 calves). Serum IgG, calf sex and dystocia were significant predictors of whether a calf died and/or required treatment. Average daily liveweight gain was calculated for calves where weaning weights were provided (n = 513). Serum IgG and calf sex were consistent predictors of calf growth rates, while birthweight and whether the calf was born to a cow or heifer were predictive in a model where average daily liveweight gain was converted to a binary response variable using the mean average daily liveweight gain on the calf's farm of origin. Morbidity and mortality were lower than comparable studies, potentially due to limitations in the study design. Serum IgG and calf sex were significant explanatory variables that affected beef calf average daily liveweight gain. For every 5g/L increase in serum IgG, the odds ratio of dying and/or requiring treatment decreased by 0.86.

Modelling the influence of seiche-events on phosphorous-loading dynamics in three Lake Ontario coastal wetlands

Coastal Wetlands (CWs) provide critical ecosystem services that maintain biogeochemical processes and habitats in the coastal zone of the Great Lakes. When nutrient-laden surface waters flow into CWs from their watersheds, internal physical, chemical, and biological processes can alter the final nutrient loadings to the lake. However, CWs can periodically be inundated with lake water from seiche events, and little is known about the impacts of seiches on nutrient processing and loadings from CWs. To evaluate the influence of lake seiches on CW phosphorous-loading dynamics, we built a multi group structural equation model (SEM) using climatic and wave data, and interannual (2009–2018) estimated sediment and phosphorous loadings from three CWs on the north-shore of central Lake Ontario (Rouge Marsh, Duffin’s Marsh, and Carruthers Marsh). Wind speeds, lake levels, and an increased peak period of wave spectra were significant explanatory variables of seiche events (p-value < 0.001). We identified that seiche events caused significant sediment resuspension (p-value < 0.001) in CWs, which contributed to a significant increase of phosphorous loading to the coastal zone of Lake Ontario (p-value < 0.001). Our results indicate that lake-seiche events can influence CW phosphorous-loadings to Lake Ontario, and should be considered when modelling water quality in the nearshore zone.

Exploring Individual Preferences on Protecting Environment: A Binominal Logistic Regression

Validity of Environmental Kuznets Curve (EKC) hypothesis has been tested by several researchers. While macro approaches towards EKC hypothesis are largely discussed in the literature, microeconomic approaches are quite scarce. This paper, in this respect, aims to provide individual insights on the environmental preferences. Using individual priority towards environmental protection rather than economic growth as an environmental indicator, I investigate individual factors affecting this preference. To the best of my knowledge, this study is the first attempt that explains individual environmental preferences by a wide range of individual characteristics exploiting individual observations from more than a hundred countries for the period of 1995-2020. The findings indicate that there is no clear evidence to support EKC hypothesis. However, significant effects of age, gender, education, unemployment, along with further significant explanatory variables are expected to be useful to make appropriate policies for a greener future.

Factors related to masticatory performance in patients with removable dentures for jaw defects following oral tumor surgery.

Purpose In the treatment of oral tumors, extensive jaw defects due to surgical resection can reduce masticatory performance. Herein, we aimed to clarify the factors related to masticatory performance in patients with jaw defects.Methods In total, 76 patients (42 male and 34 female) underwent prosthetic treatment with a removable denture for a jaw defect following oral tumor surgery. Data on history of radiation therapy, period of time since surgery, period of use of the present denture, number of remaining teeth, and site of the jaw defect were collected. Masticatory performance was evaluated using test gummy jelly. In addition, maximum bite force, tongue pressure, tongue-lip motor function (oral diadochokinesis /pa/, /ta/, /ka/), and oral dryness were evaluated. Logistic regression analysis was performed with lower masticatory performance scores as the dependent variable. Since multicollinearity was suspected between the oral diadochokinesis /ta/ and /ka/ syllables, two logistic regression analyses were conducted: Model 1 with the /ta/ syllable as an explanatory variable, and Model 2 with the /ka/ syllable as an explanatory variable.Results In Model 1, a history of radiation therapy, maximum bite force, number of remaining teeth, tongue pressure, and oral diadochokinesis /ta/ were significant explanatory variables. In Model 2, a history of radiation therapy, maximum bite force, number of remaining teeth, and tongue pressure were significant explanatory variables.Conclusions A history of radiation therapy, maximum bite force, tongue pressure, number of remaining teeth, and motor function of the proglossis are related to decreased masticatory performance in patients with jaw defects.

Effect of helicobacter pylori positivity and dyspepsia on depression and somatosensory amplification

Helicobacter pylori gastritis is an infection frequently observed around the world. In our research, the effect of Helicobacter pylori positivity on depression and somatosensory amplification was investigated. The research included a total of 112 patients with dyspeptic complaints, 52 Helicobacter pylori positive and 60 Helicobacter pylori negative, and a healthy control group of 54 cases without any complaints. Participants completed the Beck Depression Inventory and the Somatosensory Amplification Scale. There was no effect of Helicobacter pylori positivity on depression levels (p=0.116), while Helicobacter pylori positivity had a significant effect on somatosensory amplification (F=6.794; p=0.010; η2=0.40). There were significant effects of dyspeptic complaints on depression levels (F=6.695; p=0.011; η2=0.039) and somatosensory amplification (F=7.554; p=0.007; η2=0.044). It was identified that somatosensory amplification, sex and family history were each statistically significant explanatory variables for depression (p=0.001 β2=0.255; p=0.038 β2=0.150; p=0.002 β2=0.230). There was a 0.269 increase in depression for each 1-unit increase in somatosensory amplification, the female sex increased depression by 2.463 units and positive family history increased it by 4.949 units. Helicobacter pylori positivity was not found to be a significant explanatory variable for depression (p=0.412). While Helicobacter pylori positivity did not have an effect on depression, it was found to be effective in somatosensory amplification. The presence of dyspeptic complaints was effective on both depression and somatosensory amplification. Somatosensory amplification was one of the factors predicting depression in patients with dyspeptic complaints. Somatosensory amplification is an important factor in patients with Helicobacter pylori positivity and dyspeptic complaints. Mental diseases should not be ignored during the monitoring and treatment of this patient group.