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The spatiotemporal evolution of vegetation and its influencing factors is crucial for understanding the relationship between vegetation and climate change, which helps guide the management of regional ecosystems effectively. Utilizing the Fractional Vegetation Cover (FVC) data and various meteorological elements from 1982 to 2021, this research employed methodologies, such as grey relational analysis, path analysis, and the time-lag effect, to examine the impact of climate change on FVC fluctuations. It introduced a comprehensive qualitative and quantitative analysis of the multi-factor climate–vegetation relationship, enhancing the understanding of the interaction between the climate and vegetation growth. The findings indicate that 77.41% of the wetland vegetation cover in the Yellow River Basin (YRB) has significantly decreased. Precipitation and evapotranspiration emerged as the primary factors affecting FVC, with soil moisture and temperature having a lesser impact. Given the crucial influence of climate factors' time lag on vegetation dynamics, especially the notable cumulative lag effects observed in arid regions, such as precipitation accumulating over approximately 1.963 months (on average) and evapotranspiration lagging by about 1.727 months (on average), this study offers valuable theoretical insights on vegetation restoration efforts amidst the challenges posed by climate change. [ABSTRACT FROM AUTHOR]

Climate change is one of the biggest challenges the planet confronts today and is predicted to continue to face in the future. It is one of the greatest threats to humanity, seriously affecting human health, the natural environment, and security. This research aims to investigate the factors related to the perception of Greek citizens regarding climate change and green development and the obstacles that exist in Greece in the transition to enhanced green growth. For this reason, four cases related to communication and education, energy, actions to protect the environment, and each one's responsibility were investigated. Data were collected through a survey (structured questionnaire) of 745 respondents in the regional unit of the Greek city of Larissa with an overall response rate of 69% and analyzed through a combination of factor and path analysis. The results show that communication, actions related to environmental protection, and energy-saving actions are the ones that have significant associations with the goal of green development. [ABSTRACT FROM AUTHOR]

Mercury (Hg) is a highly toxic contaminant posing serious ecological and human health risks. This study investigates the Hg transfer characteristics and prediction models in a soil–lettuce system, employing bioconcentration factors (BCF), path analysis (PA), and Freundlich-type functions. A pot experiment was conducted in a greenhouse, where lettuce was grown in a range of Chinese agricultural soils (n = 21) and deliberately spiked with Hg using Hg(NO3)2 solution. The results indicated that lettuce grown in Hg-spiked acidic soils (pH < 6.5) accumulated total Hg (THg) levels up to 14.01 µg kg−1, surpassing the safe consumption limit of 10 µg kg−1. The BCF for lettuce THg was less than 1.0, suggesting a low transfer of Hg from soil to lettuce. Notably, BCF values were significantly higher in acidic soils (0.02) compared to alkaline soils (0.005). Path analysis accounted for 82% of the variation in lettuce THg content, identifying soil THg, pH, and amorphous (Amo) Al and Fe oxides as primary direct factors. Additionally, soil-available Hg (AvHg), exchangeable Hg (ExHg), clay, and organic matter (OM) were significant indirect factors affecting lettuce THg content. To validate the findings of the path analysis, an extended Freundlich-type equation was developed using stepwise multiple linear regression (SMLR). This model exhibited high predictive accuracy (R2 = 0.82, p ≤ 0.001), with soil pH, THg, and amorphous Al and Fe oxides being the key variables for predicting Hg transfer in the soil–lettuce system. The insights from this study can guide the management of safe lettuce production in Hg-contaminated soils, ensuring the mitigation of Hg exposure through agricultural produce. [ABSTRACT FROM AUTHOR]

The Haihe Plain in China is situated in the world's largest groundwater funnel area, with per capita water resources far below the internationally recognized "extremely water-scarce" standard. To address the issue of water shortage in summer maize-planting areas of the Haihe Plain, we conducted research on the variation of summer maize evapotranspiration using a medium-sized lysimeter. This study aims to provide technical support for water-saving irrigation in summer maize fields. Through path analysis, direct and indirect influencing factors affecting the evapotranspiration of summer maize fields were determined. The results showed that the cumulative evapotranspiration of bare ground and farmland during the entire growth period of summer maize was 173.57 mm and 382.97 mm, respectively, with evapotranspiration intensities of 1.52 mm/d and 3.36 mm/d, respectively. Evapotranspiration during the maturity stage of summer maize was the least, accounting for only 1.82% of total evapotranspiration during the entire growth period. The period from the jointing to milk-ripening stage is when evapotranspiration in maize fields is at its highest. During this period, evapotranspiration in maize fields amounted to 265.58 mm, accounting for 69.35% of total evapotranspiration. The evapotranspiration intensity was 3.59 mm/day, which is 1.34 times higher than that of bare soil. The evapotranspiration intensities during each growth stage were ranked as jointing stage > tasseling-silking stage > seedling stage > milk maturity stage > maturity stage. The daily evapotranspiration of summer maize fields showed a "unimodal" curve with low values in the morning and evening, and high values at noon. Path analysis indicated that daily radiation and maximum daily temperature had the greatest impact on the evapotranspiration of maize fields, with the direct effect of maximum daily temperature being restrictive and the indirect effect being promotive, resulting in an overall promotive effect. [ABSTRACT FROM AUTHOR]

The purpose of this exploratory study was to examine school principals' tendencies and practices that bring forth innovative ideas for school improvement. School principals (N = 124) responded to a survey, which included an open-ended question, on their innovative practices toward school improvement. With the Innovator's DNA framework as a basis for generating innovation for school improvement, path analysis was used to assess how well school principals' thinking and practices aligned with the framework. School principals believed it was important to help generate innovation through idea networking, being open-minded, and challenging the status quo. However, through path analysis, school principals' improvement areas associated with the Innovator's DNA framework were identified. School systems should help principals develop innovative problem-solving skills for school improvement by applying the Innovator's DNA framework in their professional development opportunities. More research is needed that examines if and how school systems foster school innovation leadership for principals. [ABSTRACT FROM AUTHOR]

Utilizing path analysis, we examined the interconnectedness among six meteorological variables. Among these, three pertain to energy conditions—air temperature, net solar radiation, and reference evapotranspiration (ET0)—while the others are associated with hydrological conditions: precipitation, relative humidity, and water deficiency. These variables were assessed across five distinct temporal delay levels to understand their influences on the normalized difference vegetation Index (NDVI) and enhanced vegetation index (EVI) within grassland areas situated in the state of Espírito Santo, southeastern Brazil. The images underwent processing using analytical algorithms and a geographic information system (GIS). The direct and indirect impacts of these variables on the NDVI and EVI exhibited remarkable similarity across varying temporal delays and geographic regions. Meteorological variables explained over 50% of the observed variation in both indices, occasionally even reaching levels of 70%. Temperature and relative humidity primarily exerted direct effects on the indices. Conversely, precipitation exhibited indirect effects on the indices, often in conjunction with other hydrological variables. ET0 demonstrated a direct effect on the vegetation indices, particularly after a delay of 32 days. Solar radiation and water deficiency displayed direct effects up to the 32-day mark, implying that vegetation responds more promptly to these variables. The proposed methodology enabled a consistent and stable assessment of the direct and indirect effects of meteorological variables on vegetation indices. [ABSTRACT FROM AUTHOR]

The inter-relationships between the Big Five personality traits, self-esteem, and compulsive buying are supported by strong empirical evidence. What is yet unknown is to what extent self-esteem can channel the influence of personality traits on compulsive buying. The main objective of this study is to explore the possible mediating role of self-esteem in the link between the Big Five personality traits and compulsive buying. Path analysis results, using a sample of 487 university students, generally confirm the suitability of the proposed model in which self-esteem mediated the effects of the Big Five personality traits (neuroticism, extraversion, agreeableness, openness to experience, and conscientiousness) on compulsive buying. Moreover, a direct effect of neuroticism and conscientiousness on compulsive buying was found. Finally, based on the finding that self-esteem acts as a necessary filter in the analysis of the five factors–compulsive buying relationship, several action-oriented guidelines for the prevention or intervention of this behavioral problem are suggested. [ABSTRACT FROM AUTHOR]

This research tests the relationship between aspects of customer influenceability at the time of booking a hotel with the propensity to write a review in electronic word-of-mouth communication. A valid sample of 739 online questionnaires was obtained. An Exploratory Factor Analysis was conducted in order to reduce the dimensions of the two critical variables, and a measurement model was built. Then a Path analysis was carried out. The novelty of this research lies in measuring the evolution from being a passive eWOM reader to a proactive eWOM writer. Results indicate a relationship between being influenced by reading reviews and the propensity to write reviews. The most important underlying motivation to write a review is altruistic. Managers should try to identify the most responsive customers and encourage them to write reviews on altruistic grounds. This study effectively validated the impact of being responsive to reading reviews on the inclination to, in turn, write them. Findings contribute to the evolving research landscape in eWOM within the hospitality and tourism sector, offering practical insights for industry practitioners to formulate more effective strategies in soliciting and managing customer reviews. [ABSTRACT FROM AUTHOR]

Driven by China's long-term energy transition strategies, the construction of large-scale clean energy power stations, such as wind, solar, and hydropower, is advancing rapidly. Consequently, as a green, low-carbon, and flexible storage power source, the adoption of pumped storage power stations is also rising significantly. Operations management is a significant factor that influences the performance of pumped storage power stations in various domains, including environmental protection, economic benefits, and social benefits. While existing studies have highlighted the importance of stakeholder partnering in operations management, a systematic exploration of the causal relationships between partnering, operations management, and the performance of pumped storage power stations—especially from a multi-energy complementarity perspective—remains untouched. This paper strives to shed light on the vital role of stakeholder partnering in augmenting the operations management and overall performance of pumped storage power stations, thereby contributing to China's dual carbon goals. A comprehensive conceptual model was developed by reviewing the relevant literature to empirically examine the causal relationships among partnering, operations management, and power station performance, which was validated using data from the Liaoning Qingyuan Pumped Storage Power Station, which is the largest of its kind in Northeast China. The findings suggest: (1) Effective partnering among stakeholders, particularly with grid companies, significantly influences the operations management of pumped storage power stations, with deficiencies in partnering mainly attributed to the lack of effective communication channels and problem-solving mechanisms. (2) The level of operations management in China's pumped storage power stations is relatively high, averaging a central score around 4.00 (out of a full score of 5) on operations management indicators. However, there is a need to concentrate on enhancing multi-energy complementarity coordination, digital management system development, and profitability. (3) Path analysis further unveils that partnering not only improves operations management but also boosts the performance of pumped storage power stations. These findings suggest a wide range of practical strategies for operations managers at pumped storage power stations to forge partnerships with stakeholders and integrate complementary resources, aiming to achieve excellence in performance. [ABSTRACT FROM AUTHOR]

The ecosystem services (ES) can be influenced by various environmental factors. In order to efficiently allocate resources and manage ecosystems, it is important to understand the mechanisms by which these environmental effects impact the interactions and trade-offs among different ES. While previous studies have primarily examined the impact of individual environmental factors on ES, the intricate mechanisms underlying the effects of multiple environmental factors have been largely overlooked. In this study, we adopted a path analysis approach that considered interactions among explanatory variables. We analyzed multiple geospatial datasets from various sources, including remote sensing and climate data, to examine the main drivers—precipitation, temperature, FVC (fractional vegetation cover), NPP (net primary productivity), human activities, and altitude—affecting five ecosystem services: carbon sequestration service (C), habitat provision service (HP), soil conservation service (SCS), sand-stabilization service (SSS), and water conservation service (WCS) in arid and semi-arid mountainous regions. Our investigation found that all five ES have shown an upward trajectory over the past two decades. The most significant growth was observed in C, which increased by 39.4%. Among the environmental factors examined, precipitation has been identified as the predominant factor influencing the ES and the synergies and trade-offs among ES. The influence of precipitation on SCS reached a coefficient of 0.726. Human activity factors had the greatest influence on HP of the five ES with a path coefficient of 0.262. Conversely, temperature exhibited a suppressive influence on ES. The impact of factors such as NPP and altitude on ES was comparatively modest. Notably, human activities assumed a substantial contributory role in shaping the relationship encompassing WCS. It is worth noting that individual factors exerted differential effects on ES along distinct environmental gradients, including anthropogenic gradients. In this context, the combination of high altitude and substantial FVC demonstrated a notable contribution to WCS. Our study can provide valuable insights for the management of ES which can be utilized to optimize the regulation of the Loess Plateau Ecological Screen (LPES) ecological construction and promote regional sustainable development. [ABSTRACT FROM AUTHOR]

The use of sulfur is an important factor in potato production. At the beginning of this study, a hypothesis was put forward according to which sulfur carrier affects yield (TY) and nitrogen efficiency (EN). The three-year study was conducted in a two-factor system: (1) sulfur fertilization, SF (control—without S, elemental sulfur—S0, calcium sulfate—CS), and (2) nitrogen fertilization level, NF (0, 30, 60, 90, 120, and 150 kg N·ha−1). In addition to TY, the following EN indicators were analyzed: agronomical efficiency (EA), physiological efficiency (EPh), partial factor productivity (PFP), and recovery (R). For both sources of sulfur, an increase in TY was confirmed. After applying CS, the optimum for the maximum yield was 106 kg N·ha−1, while the application of S0 resulted in 134 kg N·ha−1. The impact of SF on the nitrogen economy decreased in the direction of EA = PFP > EF > R and depended on the sulfur carrier. A positive trend was found, associated with the increase in R under the influence of S0 and the clearly higher EPh after the application of CS. A particularly strong effect of CS on EA was evident in the range of lower nitrogen doses. The EN values depended on the meteorological conditions during the research years. The strongest variability was subject to EPh, which, as a result of SF, was significantly higher in relation to the control (without S) during the growing season, with an unfavorable distribution of precipitation. The application of CS reduced the unit nitrogen uptake (UU-N). Using path analysis, a direct relationship of Ca accumulation (controlled by N and S) with TY was demonstrated. The conducted research indicates a significant impact of sulfur fertilizers, related to TY and EN, especially visible under conditions of limited nitrogen supply. [ABSTRACT FROM AUTHOR]

Climate and human activities are the basic driving forces that control and influence the spatial distribution and change of vegetation. Using trend analysis, the Hurst index, correlation analysis, the Moran index, path analysis, residual analysis, and other methods, the effects of human activities and climate factors on vegetation change were analyzed. The results show that: (1) The research area's normalized difference vegetation index (NDVI) exhibited a substantial upward trend from 2001 to 2020, increasing at a rate of 0.003/a, and the vegetation cover was generally healthy. The generally constant NDVI region made up 78.45% of the entire area, and the grassland, cultivated land, and forest land showed the most visible NDVI aggregation features. (2) The Vegetation is mainly promoted by water and heat, particularly precipitation, have a major impact on plants, with the direct influence of precipitation on vegetation growth being much greater than the indirect effect through the temperature. (3) The trend of NDVI residuals showed obvious spatial variability, presenting a distribution characteristic of high in the south and low in the north. The results of this study can provide a basis for the scientific layout of ecological protection and restoration projects in the Yinshanbeilu area. [ABSTRACT FROM AUTHOR]

Rice is an important cereal crop in many countries, but its production in the Senegal River Valley is hampered by adverse climatic conditions. This study was aimed at evaluating the diversity among genotypes and the association between several phenological and yield attributes of irrigated rice to mitigate the consequences of climate change. During the dry season of 2013–2014, 300 irrigated high yielding oryza sativa indica panel were used in an Alpha-lattice experiment at the Ndiaye research station in Senegal. Results revealed considerable differences between genotypes in yield and yield attributes. Grain yields ranged between 1378 and 9776 kg/ha. There were also substantial differences in the genotypic and phenotypic coefficients of variation, broad-sense heritability, genetic advance, and genetic advance as a percentage of the mean between evaluated traits. Days to heading (DH) had a higher broad-sense heritability (67.31%), indicating that the chances of transferring this trait for selection purposes will be higher, and genotypes may be used to generate early or late flowering lines. Significant positive and negative correlations were found between the studied traits and grain yield. Path analysis indicated that the maximum positive direct impact was observed with the harvest index (0.256), and the maximum negative direct effect was observed with the days to heading (−0.142). Results showed that 56 accessions outperformed the local check Giza 178, whose yield was 8987 kg/ha. Using principal component analysis and a dendrogram, genotypes were classified into four groups. The plant materials had significant variability and may be utilized to develop desired features in rice-breeding programs. [ABSTRACT FROM AUTHOR]

Background: Teen dating violence (TDV) is a growing issue among adolescents, leading to several negative behavioral and psychological consequences. Most studies have been carried out in North America, whereas few have been conducted in Europe and Italy. Despite the existence of some studies underlying risk factors for TDV, to the best of our knowledge, none of them have tested a comprehensive model that includes several risk factors (and their interplay) for verbal–emotional and physical TDV such as witnessing IPV, involvement in school bullying and victimization, cyberbullying and cybervictimization, deviant behaviors, and violence against teachers. Methods: A short-term longitudinal study involving 235 students aged 10–14 who filled in an online questionnaire twice. Results: The tested path analysis model showed an excellent fit to data, with a different pattern of risk factors affecting youth involvement as perpetrator and victim in physical and verbal–emotional TDV. Differential paths emerged for females and males. Conclusions: This article includes discussions on practical and policy implications for future research, stressing the need to develop, implement, and evaluate the effectiveness of primary prevention programs addressing and managing youth involvement in violent and aggressive behaviors. [ABSTRACT FROM AUTHOR]

Background: Personality traits, such as neuroticism, that results in vulnerability to stress, and resilience, a measure of stress coping, are closely associated with the onset of depressive symptoms, whereas regular physical activity habits have been shown to reduce depressive symptoms. In this study, the mediating effects of neuroticism and resilience between physical activity duration and depressive symptoms were investigated by a covariance structure analysis. Methods: Between April 2017 and April 2018, 526 adult volunteers were surveyed using self-administered questionnaires. Demographic information, habitual physical activity duration (PAD), neuroticism, and resilience were investigated. The effects of these factors on depressive symptoms were analyzed by a covariance structure analysis. This study was conducted with the approval of the Medical Ethics Committee of Tokyo Medical University. Results: The dose–response curves of physical activity duration and depression scores were U-shaped: the optimal physical activity duration for the lowest depression score was 25.7 h/week. We found that the greater the difference from the optimal PAD, the higher the neuroticism and the lower the resilience, and the more severe the depressive symptoms. Covariance structure analysis demonstrated that neuroticism and resilience significantly and completely mediated the effects of the difference from the optimal PAD on depressive symptoms (coefficient of determination R2 = 0.349). Conclusion: Our study suggests that there is an optimal PAD that reduces depressive symptoms, and that a greater difference from the optimal PAD increases depressive symptoms through neuroticism and resilience. [ABSTRACT FROM AUTHOR]

Oxygenated irrigation can improve soil physical and chemical properties and increase vegetable yields. It provides an effective method for safe and efficient utilization of brackish water, but its growth-promoting pathway is unclear. We investigated the effects of brackish water culture at five dissolved oxygen concentrations (9.5 (CK), 12.5, 15.5, 18.5, and 22.5 mg/L) on pakchoi (Brassica chinensis L.) growth characteristics by hydroponics experiment, and the logistic model to fit and analyze pakchoi growth characteristics. At a brackish water dissolved oxygen concentration of 18.5 mg/L, nitrogen mass fraction was significantly higher than in a control treatment by 43.4%, and pakchoi effective accumulated temperature increment during vigorous plant height and root length growth was significantly lower than other treatments. The logistic model effectively simulated pakchoi plant height and root length growth, and both theoretical maximum plant height and root length reached their maximum values at 18.5 mg/L dissolved oxygen concentration. Path analysis showed that the maximum net photosynthetic rate and nitrogen mass fraction were the main factors affecting aboveground pakchoi fresh weight. In conclusion, a dissolved oxygen concentration of 18.5 mg/L in brackish water is more appropriate for pakchoi to achieve high yield under brackish water hydroponics conditions. Our results provide guidance for the safe and efficient utilization of brackish water in green and efficient vegetable production. [ABSTRACT FROM AUTHOR]

To fully explore the influence mechanism of interactions between different monomer units of proanthocyanidins (PAs) on biological activity, a path analysis model of the PA structure-activity relationship was proposed. This model subdivides the total correlation between each monomer unit and activity into direct and indirect effects by taking into account not only each monomer unit but also the correlation with its related monomer units. In addition, this method can determine the action mode of each monomer unit affecting the activity by comparing the direct and total indirect effects. Finally, the advantage of this model is demonstrated through an influence mechanism analysis of Rhodiola crenulata PA monomer units on antioxidant and anti-diabetes activities. [ABSTRACT FROM AUTHOR]

The timing of primary tooth eruption is critical for children's health planning and the diagnosis of specific growth disorders. The purpose of this study is to assess the relationship between twin pairs' birth weight, gestational age, and gender, which are indicators of prenatal factors; breast-feeding duration, which is an indicator of postnatal factors; type of delivery, which is an indicator of maternal as well as genetic factors; and age of the primary tooth. Twin children aged from 3 to 15 years who applied to the clinic for the first dental examination constituted the sample group. In this twin study, 59 monozygotic (MZ) twin pairs and 143 dizygotic (DZ) twin pairs were included. Genetic (MZ vs. DZ), maternal (type of delivery, gestational age), perinatal (birth weight, gender), and postnatal (duration of breastfeeding) information was obtained, and effects on the children's Eruption Timing of the First Primary Tooth (ETFPT) were examined. Statistical analysis was performed using the consistent partial least squares structural equation model (robust PLSc) technique. As birth weight increased, the age at first eruption became younger, but this change was different between MZ and DZ twins (p < 0.05). While the age at first tooth eruption was older in identical twins who were breastfed for the first 6 months, this increase was not observed in DZ twins. The mean of ETFPT was calculated as 7.31 months in MZ twins and 6.75 months in DZ twins. The effect of breastfeeding and birth weight on ETFPT may differ according to zygosity in twins. MZ twins may tend to take longer to experience the eruption of their first primary teeth. [ABSTRACT FROM AUTHOR]

Snow is one of the important water sources for vegetation growth in the Mongolian Plateau, and temporal and spatial changes to it have a profound impact on terrestrial vegetation phenology. In recent years, due to global climate change, the snow associated with the different vegetation types of the Mongolian Plateau has changed substantially, and the mechanism of the resulting change in the vegetation growth date needs to be studied. To address this issue, we used the modified Carnegie Ames Stanford Approach (CASA) model was to estimate the start of growing season net primary productivity (SOSNPP) for different types of vegetation over the Mongolian Plateau from 2001 to 2019. An extensive study of the spatial changes in the SOSNPP and the responses reflected by the winter snow cover fraction (SCFWinter), spring snow melting date (SMDSpring), and SOSNPP to influencing factors is of great significance for ecosystem maintenance. We observed: (1) Different vegetation types exhibited similar changes; SCFWinter underwent a significant decrease of −0.2%, and SMDSpring followed a slow downward trend of −0.59 day of the year (DOY)/year for the whole study area. (2) In the Mongolia Plateau, SOSNPP showed a trend of significant decrease of −0.53 DOY/year. (3) The local hydrothermal condition coupling relationship effect on different vegetation types. Spring temperature (TEMSpring) has a direct effect on vegetation SOSNPP, with a path coefficient of −0.09 in the Mongolian Plateau. SCFWinter and SMDSpring were shown through a path analysis to employ different effects on vegetation SOSNPP. SMDSpring has a direct effect on vegetation SOSNPP, with a path coefficient of 0.53. (4) The SMDSpring and PRESpring factors have a significant impact on vegetation SOSNPP, and they account for 21.11% and 21.26% of the whole study area SOSNPP, respectively. This study is expected to promote the examination of the snow phonological parameters of different related vegetation types and theoretical research on SOSNPP. [ABSTRACT FROM AUTHOR]

In global greening, biogenic volatile organic compound (BVOC) emissions and their influencing factors have been considered due to their significant roles in the biosphere and atmosphere. Many studies have reported relationships of BVOC emissions with environmental factors and plant ecophysiology. However, the direct and indirect effects of environmental factors on BVOC emissions remain unclear, and the causal relationships between plant ecophysiology and BVOC emissions are ambiguous. We measured the isoprene and monoterpene emissions from dominant greening plants using a dynamic enclosure system and quantified the interactions of environment–-plant and ecophysiology–BVOC emissions using a path analysis model. We found that isoprene emission was directly affected by photosynthetic rate, and indirectly affected by photosynthetically active radiation and air temperature (Tair). Monoterpene emissions were directly affected by atmospheric pressure, relative air humidity and specific leaf weight, and indirectly affected by Tair. [ABSTRACT FROM AUTHOR]

Love addiction is a dysfunctional relational modality that takes on the addiction characteristics and which, for the individuals who suffer from it, can have a negative and pervasive impact on various areas of functioning. The objective of this research was the analysis the factors that can be associated with love addiction, particularly focusing on adult attachment patterns and self-esteem. A sample group of 300 individuals who declared themselves to have a romantic relationship was involved in this research (Mage = 37.83 years, SD = 12.937). They completed an online survey including the Love Addiction Inventory—Short form, Relationship Questionnaire, and Rosenberg Self-Esteem Scale. Results showed significant and positive associations between preoccupied and fearful adult attachment and love addiction. Furthermore, these relationships were totally mediated by self-esteem. Gender and age were controlled as potential covariates and showed significant effects in influencing the levels of self-esteem and love addiction. Such findings may provide useful information for orienting future research and supporting an effective clinical practice. [ABSTRACT FROM AUTHOR]

Infant mortality rate is a proxy measure of population health. Previous studies on the infant mortality rate in Ethiopia did not consider measurement errors in the measured variables and had a one-directional effect; little emphasis was placed on testing multiple causal paths at the same time. We used structural equation modelling for a better understanding of the direct, indirect, and total effects among causal variables in a single model. A path analysis was part of an algorithm providing equations that were relating the variances and covariances of the indicators. From the results, the maternal mortality ratio (MMR) was significantly mediating the influence of out-of-pocket expenditure (OOP) on infant mortality rate (IMR), and the fertility rate (FR) was significantly mediating the influence of GDP to IMR (β = 1.168, p < 0.001). The GDP affects the IMR directly and indirectly while the OOP affects IMR indirectly. This study showed that there was a causal linkage between the World Bank Health and Population Variables for causing IMR in Ethiopia. The MMR and FR were found to be the intermediate indicators in this study. Through the indicators, FR had the highest standardised coefficients for increasing the IMR. We recommended that the existing interventions to reduce IMR be strengthened. [ABSTRACT FROM AUTHOR]

This study explores primary school pupils' knowledge recall and interpretation skills regarding chemical and physical phenomena, in relation to three psychometric variables: logical thinking, field dependence/field independence, and divergent thinking. The participants (N = 375) were in the fifth and sixth grades (aged 11–12) taking an introductory course in science, and they were involved in three tasks related to combustion, dissolution, and mixture separation. The pupils had to complete an instrument, in which they were asked to describe and interpret the phenomena involved in the tasks. Two achievement variables were recorded separately, one relating to knowledge recall and the other to the interpretation of the phenomena. In addition, the participants completed the corresponding psychometric tests. Correlational and multiple linear regression analysis showed that the dependent measures were associated with the cognitive variables, while path and mediation analysis showed the direct and indirect effects of the neo-Piagetian constructs on the dimensions of knowledge and interpretations. The main implications of the findings are theoretical and concern the role of the operationalized mental resources in learning the specific subject matter. Moreover, the results inform teaching practices and curricula designs, and they point out the learning difficulties ascending from the individual differences under study. Further discussion on conceptual change is provided. [ABSTRACT FROM AUTHOR]

To investigate the characteristics of grape transpiration water consumption and its environmental coupling mechanism in a greenhouse growing environment in cold areas of Northeast China, the dynamic monitoring of greenhouse grape sap flow and microenvironmental factors in a greenhouse was carried out for two years. Correlation analysis and path analysis were used to study the characteristics of grape transpiration environmental factors at different temporal scales (instantaneous, daily, and growth period) and the influence mechanisms on greenhouse grape transpiration. The results of correlation analysis by growth period showed that, on the instantaneous scale, the correlation between each meteorological factor and grape transpiration reached a significant level (coefficient of determination R2 ranged from 0.25 to 0.84). On the daily scale, the correlation of solar radiation (Rs) was the best except for the new growth period (R2 ranged from 0.49 to 0.89). The results of the split-fertility path analysis showed that the total effects of Rs on instantaneous transpiration were the largest at all stages of fertility, with decision coefficients (R) ranging from 0.69 to 0.90. On the daily scale, the total and direct effects of Rs on daily transpiration were the largest (R ranged from 0.70 to 0.94), except for the new growth period. The results of the whole growth period path analysis showed that Rs had the greatest effect on instantaneous transpiration, with R of 0.86. On the daily scale, Rs was also the most influential factor in grape transpiration, with R of 0.81. On the growth period scale, only air temperature (Ta) and leaf area index (LAI) were significantly correlated with transpiration (p < 0.05), and Rs had the largest total effect on transpiration with R of 0.68. To sum up, on each time scale, Rs was always the most important factor influencing grape transpiration. However, as the time scale increased, the effects of LAI and soil water content (SW) on transpiration increased while the effects of Rs, Ta, RH, and VPD on transpiration gradually decreased. [ABSTRACT FROM AUTHOR]

As the demand for service robots increases, a mobile manipulator robot which can perform various tasks in a dynamic environment attracts great attention. There are some controllers that control mobile platform and manipulator arm simultaneously for efficient performance, but most of them are difficult to apply universally since they are based on only one mobile manipulator model. This lack of versatility can be a big problem because most mobile manipulator robots are made by connecting a mobile platform and manipulator from different companies. To overcome this problem, this paper proposes a simultaneous controller which can be applied not only to one model but also to various types of mobile manipulator robots. The proposed controller has three main characteristics, which are as follows: (1) establishing a pose that motion planning can be carried out in any position, avoiding obstacles and stopping in a stable manner at the target coordinates, (2) preventing the robot from collision with surrounding obstacles while driving, (3) defining a safety area where the manipulator does not hit the obstacles while driving and executing the manipulation accordingly. Our controller is fully compatible with Robot Operating System (ROS) and has been used successfully with three different types of mobile manipulator robots. In addition, we conduct motion planning experiments on five targets, each in two simulation worlds, and two motion planning scenarios using real robots in real-world environments. The result shows a significant improvement in time compared to existing control methods in various types of mobile manipulator and demonstrates that the controller works successfully in the real environment. The proposed controller is available on GitHub. [ABSTRACT FROM AUTHOR]

Soil aggregate stability and erodibility are the influential factors governing soil resistance to water erosion. The interactions among aggregate stability, erodibility, and their influencing factors have not been fully explored. We collected soil samples from 0–10 cm and 10–20 cm layers in the Zhifanggou watershed. Then, the major contributors to aggregate stability and erodibility and how soil properties, environmental factors and land use contributed to them were explored by using partial least-squares regression and path analysis, respectively. The results showed that the major contributors included the slope, soil organic carbon (SOC), elevation, the percentage of landscape area of farmland (PLAND_F) and grassland (PLAND_G), the land surface temperature difference between seasons (ΔLST), topographic wetness index (TWI), pH, amorphous iron (poorly ordered forms of iron, Feo), and calcium carbonate (CaCO3). In which, the slope, SOC, and elevation were the most important contributors to the mean weight diameter (MWD) and the percentage of water-stable aggregates greater than 0.25 mm (WSA>0.25) and had a direct contribution to MWD, WSA>0.25, and K factors. The PLAND_F and PLAND_G had a significant and indirect contribution to those three indices by affecting slope. Meanwhile, the effects of pH, Feo, and CaCO3 on WSA>0.25 should also not be underestimated. For MWD and WSA>0.25, there was a significantly higher effect of the land use types and composition than hydrothermal conditions. For K factors, PLAND's contribution was still higher than ΔLST and TWI, but they were all significant. The other soil properties, including pH, CaCO3, and Feo, indirectly affected them by influencing SOC. However, the direct contributions of soil properties increased as the soil layer deepened. [ABSTRACT FROM AUTHOR]

Rice is an important cereal and drought stress is a critical abiotic stress that negatively influences the performance and productivity of rice crop, particularly under a changing climate scenario. The objectives of this study were to evaluate the impacts of drought stress on grain productivity and water use efficiency of rice cultivars and to assess the genotypic variability among the tested cultivars. Two irrigation treatments including a control and drought stress were applied to the experiments during 2018–2019 and 2019–2020. The statistical evaluation included a comparison of means, genotypic and phenotypic coefficients of variation, path analysis, correlation assessment, hierarchical clustering of tested cultivars and principal component analysis. The results indicated that drought stress negatively affected the grain productivity of the rice cultivars. The grain productivity of the cultivars decreased, ranging between 21–45% and 21–52% in the first and second season, respectively. Similarly, water use efficiency was significantly decreased ranging between 7–53% and 21–55% during the first and the second season, respectively. The broad-sense heritability for grain productivity was differed under control and drought stress treatment, indicating that the chances of the transfer of grain-productivity-related traits could be affected during selection for stress tolerance. The correlation assessment indicated that the intensity of association among the evaluated parameters was higher under the control treatment. A maximum direct effect was observed by water consumption (1.76) under control whereas, by water use efficiency (1.09) under drought stress treatment on grain productivity in path analysis. Considering the water use efficiency as a desired trait for selection in path analysis, a maximum direct effect was observed by grain productivity under the control (0.68) and under drought treatment (0.88). Hom Pathum and Pathum Thani−1 were identified as highly tolerant cultivars in the hierarchical clustering and principal component analysis. It was concluded that the results obtained for the assessment of drought stress on grain productivity, water use efficiency and genotypic variability among these cultivars could be utilized in selection program for stress tolerance and the stress tolerant cultivars could be used for sustaining grain productivity to reduce the impacts of climate change. [ABSTRACT FROM AUTHOR]

Ecosystem water use efficiency (WUE) plays an important role in maintaining the carbon assimilation–water transpiration balance in ecosystems. However, spatiotemporal changes in WUE in the subtropical region of China (STC) and the impact of driving forces remain unclear. In this study, we analyzed the spatiotemporal variation in WUE in the STC and used ridge regression combined with path analysis to identify direct and indirect effects of climate change, vegetation growth, and elevated atmospheric CO2 concentration (Ca) on the interannual trend in WUE. We then quantified the actual and relative contributions of these drivers to WUE change based on the sensitivity of these variables on WUE and the trends of the variables themselves. Results reveal a mean WUE of 1.57 g C/m2/mm in the STC. The annual WUE series showed a descending trend with a decline rate of 0.0006 g C/m2/mm/year. The annual average temperature (MAT) and leaf area index (LAI) had strong positive direct effects on the WUE, while the vapor pressure deficit (VPD) had a strong negative direct effect. Opposite direct and indirect effects offset each other, but overall there was a total positive effect of Ca and VPD on WUE. In terms of actual contribution, LAI, Ca, and VPD were the main driving factors; LAI caused WUE to increase by 0.0026 g C/m2/mm/year, while Ca and VPD caused WUE to decrease by 0.0021 and 0.0012 g C/m2/mm/year, respectively. In terms of relative contribution, LAI dominated the WUE trend, although Ca and VPD were also important factors. Other drivers contributed less to the WUE trend. The results of this study have implications for ecological management and restoration under environmental climate change conditions in subtropical regions worldwide. [ABSTRACT FROM AUTHOR]

Reducing browsing damages from cervids (Cervidae) on economically valuable tree species is a challenging task in many countries. Apart from cervid abundance, landscape characteristics, such as forest composition, land use, forage availability and climatic conditions, may affect the degree of browsing through both direct and indirect effects. A better understanding of basic mechanisms in this complex system is needed to design efficient and convincing management strategies. Focusing on Sweden as a case, which has been widely studied using regression analyses only, we applied path analysis to test the validity of a model on the indirect and direct links between landscape characteristics, cervid populations, and browsing damages on Scots pine (Pinus sylvestris). Our results validated the tested model in which moose (Alces alces) density and pine availability directly influence browsing damages. Increasing amounts of pine forests, preferred deciduous trees, and young forest had positive direct effects on moose densities and thereby indirectly contributed to increased browsing damages. The density of smaller deer species showed no direct effect on browsing damages on pine. Path analysis corroborated our attempt to disentangle direct and indirect potential causal drivers of browsing damages and shows that the choice of statistical method may alter the understanding of mechanistic driving forces. [ABSTRACT FROM AUTHOR]

Ordos City lies in a semiarid-arid farm pastoral region in north China. In recent years, as an ecological security barrier and ecological vulnerable and sensitive region, the intensification of human activities and climate change in the foreseeable future have aroused people's attention to ecological security issues. Based on the meteorological data of MOD13Q1 and the socioeconomic activity data in the same period, the variation characteristics of annual and seasonal vegetation NDVI, the response of vegetation NDVI to climate change, and the impact of human activities on vegetation NDVI in Ordos City from 2000 to 2020 were obtained by using trend analysis, sustainability analysis, and path analysis. The results showed that: (1) Ordos City vegetation NDVI showed an obvious growth trend, except for the interannual growth rate (0.0075/a), the growth rate in autumn increased faster than in other seasons (0.0067/a); (2) the future trend of vegetation NDVI in Ordos City is mainly anti-continuous improvement. If no effective measures are taken, the vegetation NDVI will degrade in the future; (3) precipitation was the main climate factor in the vegetation growth compared with temperature. An increase in precipitation promoted vegetation growth directly, while an increase in temperature showed a negative effect by reducing precipitation in the whole growing season; (4) the utilization pattern greatly affects the spatial distribution of vegetation NDVI, and stable land use can improve the utilization of vegetation. [ABSTRACT FROM AUTHOR]

Several studies have reported that the COVID-19 pandemic has had deleterious effects on sleep quality and mood, but the mechanisms underlying these effects are not clearly understood. Recently, it has been shown that the acceptance component of mindfulness reduces anxiety, and, in turn, lower anxiety improves sleep quality. The purpose of this cross-sectional study was to assess changes in mindfulness traits, sleep–wake quality, and general distress, before, during, and after the first COVID-19 wave, testing the model in which acceptance influences sleep through anxiety in each period. A total of 250 participants were recruited before (Pre-Lockdown group: 69 participants, 29 females, 33.04 ± 12.94 years), during (Lockdown group: 78 participants, 59 females, 29.174 ± 8.50 years), and after (After-Lockdown group: 103 participants, 86 females, 30.29 ± 9.46 years) the first Italian lockdown. In each group, self-report questionnaires, assessing mindfulness facets, distress, and sleep–wake quality, were administered and assessed. The Lockdown group reported lower acceptance and higher depression, while the After-Lockdown group reported lower sleep–wake quality and higher anxiety. The results of the path analysis confirmed that higher acceptance reduced anxiety and higher anxiety decreased sleep–wake quality in all groups. Our results confirm that acceptance influences sleep through the mediating role of anxiety. [ABSTRACT FROM AUTHOR]

Land use land cover within a watershed influences stream water quality, habitat quality, and biological community structure. As development and associated impervious surface increases in a watershed, changes in storm water and nutrient inputs generally cause declines in habitat conditions and biodiversity. The first goal of our study was to evaluate the water quality in the Charles River watershed, in which our objective (G1O1) was to establish ten 100-meter reach-scale sampling stations and conduct physical, chemical, and biological assessments. The second goal of this study was to better understand the direct and indirect effects of hierarchical variables on water quality in the Charles River watershed. Our first objective of our second goal (G2O1) was to calculate land use land cover percentages at the pour-point subwatershed and local 100-meter buffer scale for each of our ten 100-meter reach sampling stations. Our second objective of our second goal (G2O2) was to use path analysis to determine the direct and indirect effects of land use land cover and impervious surface on water quality in the Charles River watershed. The results of G1O1 were that habitat quality assessments ranged from "marginal" to "optimal" and biological quality assessments ranged from "fair" to "good", indicating overall "fair" or better water quality conditions in the watershed. The results of G2O2 were that our path analysis resulted in differences in effects of development between the buffer and sub-watershed scale. At the buffer scale, water quality was influenced more negatively by the percentage of developed land area versus the percentage of impervious cover. While both buffer development and habitat quality had a direct effect on Streamside Biosurvey Macroinvertebrates, buffer development also directly hindered habitat quality, thus having an indirect effect on Streamside Biosurvey Macroinvertebrates through habitat. Streamside Biosurvey Macroinvertebrate scores were shown to be more sensitive to development within the buffer versus at the sub-watershed scale, where impervious cover was a more important indicator of stream water quality. Through this small case study of 10 stations within the Charles River watershed, we illustrated how citizen-science level water quality assessments can be combined with water chemistry and hierarchical LULC data to provide insights into potential direct and indirect effects on water quality. As the fields of landscape ecology and conservation continue to grow, so does our ability to determine changes in land development and devise management strategies aimed at improving water quality. [ABSTRACT FROM AUTHOR]

The study of the contribution of spatial transformation skills to driving behavior is a research topic substantiated by scarce evidence. In previous studies, we found that mental rotation and perspective-taking skills have an influence on performance in driving tasks by conveying the distal effects of the general cognitive efficiency on the execution of driving maneuvers. Studies have provided evidence on the relevance of the cognitive processes of encoding, imagined rotation, and spatial orientation in the accuracy of both the vehicle management during stressful driving situations and the acquisition of visual information on the traffic scenario. Results can find applications in both the training and the assessment of fitness to drive, as well as in the study of interaction between the drivers and in-vehicle devices. The lack of cross-validations in path analysis models cannot be assumed, a priori, to be capitalizing on chance and as an example of bad science. The non-replicability of a study should be demonstrated before it is proclaimed. The purpose of this reply was to address the questions raised by Kelly et al. (2022)—that is, "Do these results seem replicable?" and "How do these results advance our understanding of brain function and/or human behavior?"—by providing additional information on the study in question. [ABSTRACT FROM AUTHOR]

This study examines the impact of family and neighborhood factors on physical and psychological abuse across three developmental stages of children: early childhood (age 3), young school age (age 5), and middle childhood (age 9). Data from the Fragile Families and Child Wellbeing Study, a longitudinal national cohort study of children from 20 urban U.S. cities, are used. Path analysis is employed to investigate the longitudinal relationships between family and neighborhood context variables and abuse risk, as well as the importance of different factors at key developmental stages. Economic hardship, maternal substance use, intimate partner violence, and exposure to community violence are found to be related to child abuse risk regardless of developmental stage, while maternal depression and neighborhood informal social control are found to have impacts only within certain child development stages. Findings suggest the need for early intervention and prevention strategies that specifically target economic hardship, poverty, intimate partner violence, and exposure to community violence. [ABSTRACT FROM AUTHOR]

Background: Exoskeleton-robot-assisted therapy is known to positively affect the recovery of arm functions in stroke patients. However, there is a lack of evidence regarding which variables might favor a better outcome and how this can be modulated by other factors. Methods: In this within-subject study, we evaluated the efficacy of a robot-assisted rehabilitation system in the recovery of upper limb functions. We performed a path analysis using a structural equation modeling approach in a large sample of 102 stroke patients (age 63.6 ± 13.1 years; 61% men) in the post-acute phase. They underwent 7 weeks of bilateral arm training assisted by an exoskeleton robot combined with a conventional treatment (consisting of simple physical activity together with occupational therapy). The upper extremity section of the Fugl–Meyer (FM-UE) scale at admission was used as a predictor of outcome, whereas age, gender, side of the lesion, days from the event, pain scale, duration of treatment, and number of sessions as mediators. Results: FM-UE at admission was a direct predictor of outcome, as measured by the motricity index of the contralateral upper limb and trunk control test, without any other mediating factors. Age, gender, days from the event, side of lesion, and pain scales were independently associated with outcomes. Conclusions: To the best of our knowledge, this is the first study assessing the relationship between clinical variables and outcomes induced by robot-assisted rehabilitation with a path-analysis model. We define a new route for motor recovery of stroke patients driven by exoskeleton-robot-assisted therapy, highlighting the role of FM-UE at admission as a useful predictor of outcome, although other variables need to be considered in the time-course of disease. [ABSTRACT FROM AUTHOR]

Snowfall is an important climatic variable with remarkable impacts on vegetation greenness in the alpine and extra-tropical regions. Central Asia (CA) is located in the middle latitude with high mountains, and the ecosystem is vulnerable to climate change in CA. In this region, the vegetation response to winter snowfall and its interactions with growing season climatic factors on vegetation greenness is still unclear. Thus, this study attempted to examine the impact of winter snowfall on vegetation greenness with remote-sensing vegetation index and reanalysis climatic data, and to investigate the interactions between winter snowfall and growing season climatic factors and their influence on vegetation growth via path analysis. The results showed that there is a generally positive correlation between winter snowfall and vegetation greenness from May to September and during the whole growing season (April to September). This positive correlation was significant in 8% of the study area for the whole growing season. However, the increase in winter snowfall was not beneficial to the regional vegetation growth in April. The vegetation response to winter snowfall also relates to land-cover type and elevation. The vegetation greenness in grassland was depicted to be more sensitive to winter snowfall than that in forestland. The response turned from positive to negative when the elevation increased from below 3000 m to above 3000 m. Moreover, the impact of winter snowfall on vegetation greenness was not regulated by temperature and precipitation in the growing season in more than 70% of CA. The impact relates to the interaction with April temperature in Central Kazakhstan, and is regulated by growing season precipitation in North Kazakhstan where annual precipitation mainly occurs in the growing season. The impact of winter snowfall on vegetation greenness is more important than growing season precipitation and temperature in some areas, since annual precipitation does not concentrate in the growing season or the relative increase of winter snowfall is great in these places. The results of the present study improve the understanding of vegetation response to climate change, and provide a scientific reference for environmental protection in CA and similar regions. [ABSTRACT FROM AUTHOR]

Teacher education must provide the knowledge and skills necessary for technology integration, but also influence attitudes and beliefs. Little research has been conducted on how knowledge, beliefs, and attitudes predict teachers' intentions to use technology. The aim of this study was to identify how perceived knowledge about technology integration, and beliefs and attitudes towards using technology, impact the intention to use technology among student teachers. The sample consisted of 232 student teachers from the University of Tartu. Data were collected using a questionnaire based on elements of two different models. Validating the technology acceptance scale using a confirmatory factor analysis identified that perceived usefulness was split into two constructs: perceived usefulness for students and perceived usefulness for teachers. Path analysis, as a special type of structural equation modelling, was used to test 11 hypotheses. The results showed that both perceived ease of use and attitude to use have direct effects on intention to use. Still, perceived usefulness for teachers and perceived knowledge displayed an indirect influence. Based on these results, it is important that student teachers should be convinced that technology is easy to use in teaching. [ABSTRACT FROM AUTHOR]

Hybrid rigid–flexible mechanisms are a type of compliant mechanism that combines rigid and flexible elements, being that their mobility is due to rigid-body joints and the relative flexibility of bendable rods. Two of the modeling methods of flexible rods are the Cosserat rod model and its simplification, the Kirchhoff rod model. Both of them present a system of differential equations that must be solved in conjunction with the boundary constraints of the rod, leading to a boundary value problem (BVP). In this work, two methods to solve this BVP are applied to analyze the influence of external loads in the movement of hybrid compliant mechanisms. First, a shooting method (SM) is used to integrate directly the shape of the flexible rod and the forces that appear in it. Then, an integration with elliptic integrals (EI) is carried out to solve the workspace of the compliant element, considering its buckling mode. Applying both methods, an algorithm that obtains the locus of all possible trajectories of the mechanism's coupler point, and detects the buckling mode change, is developed. This algorithm also allows calculating all possible circuits of the mechanism. Thus, the performance of this method within the path analysis of mechanisms is demonstrated. [ABSTRACT FROM AUTHOR]

As a result of two crosses among three local varieties of wheat, five populations (P1, P2, F5, F6 and F7) were used as parents and grown during two successive seasons; 2016/2017 and 2017/2018. To estimate five types of gene action (e.g., mean effects, additive, dominance, additive × additive, and dominance × dominance), five formulas were developed from with algebraic solution, algebraic proof, and mathematical proof. Besides, to test adequate of a simple additive-dominance model, three formulas A, B, and C scaling test were developed. The path analysis method by PROCESS Macro, AMOS, and Bootstrapping was employed to assess the relationships between grain yield/plant (GYP) as the dependent variable and each one of the number of spikes (NS) and 1000-grain weight (TW) as the independent variables. The results show that there are eight validated equations used to estimate the scaling test (A, B and C) and five types of gene effects (m, a, D, I and L), respectively. Confidence interval using Bootstrapping results indicate that TW was played as the partial mediator between NS as an exogenous variable and GYP as an endogenous variable. Generation means analysis is a relatively simple and statistically reliable tool suitable for the fundamental estimation of different genetic influences. [ABSTRACT FROM AUTHOR]

Ensuring multiple sclerosis (MS) patients' adherence to therapy is often challenging, but it is crucial to their survival and health-related quality of life (HRQoL). The aim of the present study was to outline connections between adherence, physical and mental HRQoL, levels of psychological readiness to engage in a treatment, levels of social support, anthropometric, socio-demographic and clinical factors in patients suffering from MS. This cross-sectional study involved a sample of 237 Italian MS patients. A survey was conducted with a structured self-administered online questionnaire using validated measures of quality of life, adherence to therapy and anthropometric, socio-demographic, psychological and clinical variables. A path analysis was used to test the overall structure of the associations between the variables. The pathway indicates a positive association between mental health index and a stronger degree of engagement and being or having been in a long-term relationship. Physical health index was positively associated with age, having an occupation, and having a specific form of MS. Having had relapses in the previous year raised the odds of better adherence to therapy, while an increase in Body Mass Index (BMI) reduced them. Our findings could help in the management of MS patients, promoting behavioral interventions that take the psychological and socio-demographic peculiarities of each patient into account with a view to improving their adherence to therapy. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ET0) in the hydrological cycle is one of the processes that is significantly affected by climate change. The Qinghai–Tibet Plateau (QTP) is universally recognized as a region that is sensitive to climate change. In this study, an area elevation curve is used to divide the study area into three elevation zones: low (below 2800 m), medium (2800–3800 m) and high (3800–5000 m). The cumulative anomaly curve, Mann–Kendall test, moving t-test and Yamamoto test results show that a descending mutation occurred in the 1980s, and an ascending mutation occurred in 2005. Moreover, a delay effect on the descending mutation in addition to an enhancement effect on the ascending mutation of the annual ET0 were coincident with the increasing altitude below 5000 m. The annual ET0 series for the QTP and different elevation zones showed an increasing trend from 1961 to 2017 and increased more significantly with the increase in elevation. Path analysis showed that the climate-driven patterns in different elevation zones are quite different. However, after the ascending mutations occurred in 2005, the maximum air temperature (Tmax) became the common dominant driving factor for the whole region and the three elevation zones. [ABSTRACT FROM AUTHOR]

This paper deals with the automatic classification of customers on the basis of their movements around a sports shop center. We start by collecting coordinates from customers while they visit the store. Consequently, any costumer's path through the shop is formed by a list of coordinates, obtained with a frequency of one measurement per minute. A guess about the trajectory is constructed, and a number of parameters are calculated before performing a Clustering Process. As a result, we can identify several types of customers, and the dynamics of their behavior inside the shop. We can also monitor the state of the shop, identify different situations that appear during limited periods of time, and predict peaks in customer traffic. [ABSTRACT FROM AUTHOR]

Mitigating high air temperatures and heat waves is vital for decreasing air pollution and protecting public health. To improve understanding of microscale urban air temperature variation, this paper performed measurements of air temperature and relative humidity in a field of Wuhan City in the afternoon of hot summer days, and used path analysis and genetic support vector regression (SVR) to quantify the independent influences of land cover and humidity on air temperature variation. The path analysis shows that most effect of the land cover is mediated through relative humidity difference, more than four times as much as the direct effect, and that the direct effect of relative humidity difference is nearly six times that of land cover, even larger than the total effect of the land cover. The SVR simulation illustrates that land cover and relative humidity independently contribute 16.3% and 83.7%, on average, to the rise of the air temperature over the land without vegetation in the study site. An alternative strategy of increasing the humidity artificially is proposed to reduce high air temperatures in urban areas. The study would provide scientific support for the regulation of the microclimate and the mitigation of the high air temperature in urban areas. [ABSTRACT FROM AUTHOR]

Data were collected for this study early in the school year to analyze the direct and indirect effects of word-level literacy skills (word recognition, spelling, and written vocabulary use) and handwriting fluency on writing quality across three genres of typewritten papers. We further explored whether typing fluency and text generation fluency mediated the effects. Finally, we examined whether there was any difference in the effects across three writing genres. Fourth and fifth graders (N = 175) from 21 typical classrooms in 12 different Midwestern U.S. schools participated. Regression path analyses were employed and revealed that word-level literacy skills had both significant direct and serial indirect effects on quality, via typing fluency and then text generation fluency (text length) when controlling for handwriting fluency. Further, handwriting fluency had no direct effect when controlling for word-level literacy skills but did have a significant serial indirect effect on writing quality via typing fluency then text generation fluency. Results indicate that handwriting fluency matters, even when composing on the computer. Stronger transcription fluency, particularly by hand, leads to higher quality writing, likely because less cognitive effort is devoted to transcription. This study adds to limited research on the cross-modal effects of transcription on writing quality. [ABSTRACT FROM AUTHOR]

Cyanobacterial blooms are considered a major threat to global water security with documented impacts on lake ecosystems and public health. Given that cyanobacteria possess highly adaptive traits that favor them to prevail under different and often complicated stressor regimes, predicting their abundance is challenging. A dataset from 822 Northern European lakes is used to determine which variables better explain the variation of cyanobacteria biomass (CBB) by means of stepwise multiple linear regression. Chlorophyll-a (Chl-a) and total nitrogen (TN) provided the best modelling structure for the entire dataset, while for subsets of shallow and deep lakes, Chl-a, mean depth, TN and TN/TP explained part of the variance in CBB. Path analysis was performed and corroborated these findings. Finally, CBB was translated to a categorical variable according to risk levels for human health associated with the use of lakes for recreational activities. Several machine learning methods, namely Decision Tree, K-Nearest Neighbors, Support-vector Machine and Random Forest, were applied showing a remarkable ability to predict the risk, while Random Forest parameters were tuned and optimized, achieving a 95.81% accuracy, exceeding the performance of all other machine learning methods tested. A confusion matrix analysis is performed for all machine learning methods, identifying the potential of each method to correctly predict CBB risk levels and assessing the extent of false alarms; random forest clearly outperforms the other methods with very promising results. [ABSTRACT FROM AUTHOR]

Tipburn (calcium (Ca) deficiency disorder) is a major problem in the production of lisianthus cultivars. However, few studies have investigated the influence of different Ca concentrations in nutrient solution on tipburn incidence and Ca acquisition and distribution. Thus, it remains unclear why some cultivars exhibit tipburn under high Ca concentrations. To address this, we used three lisianthus cultivars 'Azuma-no-Kaori' (AK), 'Celeb Wine' (CW), and 'Voyage Yellow' (VY) and compared tipburn incidence and Ca acquisition and distribution under different Ca concentrations in a nutrient solution (low (40 ppm), moderate (80 ppm), and high (120 ppm) Ca). Tipburn severity and incidence in AK and VY significantly decreased with increasing nutritional Ca concentrations; the Ca concentrations in each organ and Ca acquisition competence (RGRCa) increased at higher nutritional Ca concentrations. In contrast, tipburn incidence in CW was 100% for all treatments. In CW, Ca acquisition competence and Ca concentrations in most organs increased with increasing nutritional Ca concentrations, but the Ca concentrations in the tips of the upper leaves did not differ significantly between treatments. Thus, our results suggest that the cause of tipburn under sufficient Ca conditions is an inability of the plant to distribute Ca to the tips of its upper leaves. [ABSTRACT FROM AUTHOR]

The objective of this study was to estimate the direct and indirect effects of agricultural, morphological, physiological, and root traits of popcorn lines, under two conditions of water supply: full irrigation (FI) and drought stress (DS). A complete randomized block design with three replications was used to evaluate the following traits: expanded popcorn volume per hectare (EPV), 100-grain weight (100GW), mean ear length, mean ear diameter, number of grains per row (NGR), prolificacy (PRO), anthesis to silking interval, tassel length, number of tassel branches, plant height, shoot dry matter, green index (SPAD), and canopy temperature depression (CTD), root angle (RA), tap root volume (TRV), and crown root volume (CRV). Analyses of variance and path analysis, and subsequent partitioning of direct and indirect effects were performed. For the traits EPV, PRO, CTD, RA, CRV and TRV, the genotype x environment interaction was significant. Drought stress had significant effects on EPV (−7.15%), 100GW (−23.52%), SPAD (−29.31%), CTD (87.15%), RA (24.54%), and CRV (44.89%). The traits NGR and SPAD were found to be decisive for the expression of EPV. The exploitation of these traits by indirect selection is expected to induce increments in EPV in environments under DS and FI. [ABSTRACT FROM AUTHOR]

Generating 3D path models (with textures) from indoor paths is a good way to improve the visualization performance of 3D indoor path analysis. In this paper, a quaternion-based piecewise 3D modeling method is proposed to automatically generate highly recognizable 3D models for indoor path networks. To create such models, indoor paths are classified into four types of basic elements: corridor, stairs, elevator and node, which contain six kinds of edges and seven kinds of nodes. A quaternion-based method is devised to calculate the coordinates of the designed elements, and a piecewise 3D modeling method is implemented to create the entire 3D indoor path models in a 3D GIS scene. The numerical comparison of 3D scene primitives in different visualization modes indicates that the proposed method can generate detailed and irredundant models for indoor path networks. The result of 3D path analysis shows that indoor path models can improve the visualization performance of a 3D indoor path network by displaying paths with different shapes, textures and colors and that the models can maintain a high rendering efficiency (above 50 frames per second) in a 3D GIS scene containing more than 50,000 polygons and triangles. [ABSTRACT FROM AUTHOR]