Stepwise Linear Model Research Articles

The authentication of Yanchi tan lamb based on lipidomic combined with particle swarm optimization-back propagation neural network

This study successfully combined widely targeted lipidomic with a back propagation (BP) neural network optimized based on a particle swarm algorithm to identify the authenticity of Yanchi Tan lamb. An electronic nose and gas chromatography–olfactometry-mass spectrometry (GC-O-MS) were used to explore the flavor differences in Tan lamb from various regions. Among the 17 identified volatile compounds, 16 showed significant regional differences (p < 0.05). Lipidomic identified 1080 molecules across 41 lipid classes, with 11 lipids, including Carnitine 15:0, Carnitine 17:1, and Carnitine C8:1-OH, serving as potential markers for Yanchi Tan lamb. In addition, a stepwise linear discriminant model and three types of BP neural networks were used to identify the origin of Tan lamb. The results showed that particle swarm optimization-back propagation (PSO-BP) neural network had the best prediction effect, with 100 % prediction accuracy in both the training and test sets. The established PSO-BP model was able to achieve effective discrimination between Yanchi and non-Yanchi Tan lamb. These results provide a comprehensive perspective on the discrimination of Yanchi Tan lambs and improve the understanding of Tan lamb flavor and lipid composition in relation to origin.

Off-Crop and Off-Season Monitoring, Key Elements to Be Integrated into an Effective Strategy for the Control of Drosophila suzukii (Diptera: Drosophilidae)

Drosophila suzukii is a pest affecting a wide range of host plants, causing severe damage to small fruits, berries, and grapes. This study analyzed environmental factors influencing its population dynamics in regions where temperature is not a limiting factor. Data were collected in the spring–summer seasons of 2018 and 2019 across three vineyards in northwestern Portugal, examining the relationship between captured D. suzukii females, climatic variables, vine phenological stages, and ecological infrastructures. A stepwise linear model and Pearson correlation matrix were used. In 2020, a winter study was conducted in nine vineyards, focusing on landscape composition and its effect on D. suzukii populations. An ecological infrastructure index was created and correlated with captures data. Results show that vine phenological stages and nearby ecological infrastructures significantly affect population dynamics in spring and summer. Vineyards surrounded by complex landscapes, especially with wild hosts, supported higher D. suzukii populations during winter. These findings highlight the importance of ecological infrastructures in managing D. suzukii populations year-round and suggest their consideration in pest control strategies.

Socioeconomic and Racial Disparities in Primary Open-Angle Glaucoma in the US.

Socioeconomic status is a potentially significant, although difficult to isolate, factor in determining glaucoma severity. To analyze the level of glaucoma severity (mild, moderate, or severe) based on demographic factors, including age, gender, ethnicity, insurance profile, and zip code, and to use this data to extrapolate the effect of socioeconomic status (SES) and race on glaucoma severity at the community level in Memphis, TN. 2913 patients from a tertiary care center with three clinic locations in Memphis, TN who had been given the diagnosis of Primary Open Angle Glaucoma (POAG) through use of the ICD-10 codes for mild (H40.1111, H40.1121, H40.1131), moderate (H40.1112, H40.1122, H40.1132) and severe (H40.1113, H40.1123, H40.1133) POAG between January 2016 and July 2021 were included in this study. Diagnoses were made after a complete glaucoma workup consisting of Snellen visual acuity, applanation IOP measurement, gonioscopy, automated Humphreys Visual Fields (10-2 and 24-2), and optic nerve OCT. Demographic information, including age, gender, ethnicity, insurance profile, and zip code, was also collected with disease severity for each patient. SES was approximated using zip code-level census poverty data and insurance profiles. Statistical analyses were performed, including descriptive, multivariable ordinal logistic modeling and stepwise multivariable linear modeling. Glaucoma severity was shown to increase with poverty rate (OR=1.089, P<0.0071), age (OR=1.030, P<0.0001), male sex (OR=1.374, P<0.0001), and Black race (OR=1.896, P<0.0001). Severity was shown to be decreased in patients with private insurance compared to Medicare (OR=0.895, P<0.093) and those from Shelby County compared to other counties (OR=0.703, P<0.0001). Our findings indicate that worsening glaucoma severity was associated with higher poverty rates in our patient population. However, isolating socioeconomic status (SES) as an independent factor influencing the incidence and severity of glaucoma remains challenging, given the strong correlation between race and SES.

The ability of peripheral neurophysiological biomarkers to predict future psychological conditions among geriatric populations

ObjectiveThough the association between peripheral neurophysiological biomarkers and psychological conditions is widely discussed, there is still limited evidence about the ability of peripheral biomarkers to predict psychological outcomes, especially among geriatric populations. MethodsThe study is designed as a prospective cohort study. We collected information from participants aged over 55 years. The participants were evaluated at the start of the study (T0) and 6–9 months later (T1). Information about demographic profiles, peripheral neurophysiological biomarker recordings (including heart rate variability, finger temperature, skin conductance, and electromyogram), and psychological measurements (including Brief Symptom Rating Scale-5, Chinese Happiness Inventory, and Short Portable Mental Status Questionnaire) were collected at T0. At T1, participants reported self-rated questionnaires for psychological outcomes (Patient Health Questionnaire-15, health anxiety questionnaire, Beck Depression Inventory-II, and Beck Anxiety Inventory) and were evaluated with Mini-Mental State Examination by the staff. The association between the peripheral biomarkers and psychological outcomes was evaluated via multiple regression models. ResultsA total of 385 participants were included in the study and the average age was 74.49 ± 7.34 years. Both stepwise multiple linear and logistic models showed a significant association between decreased skin conductance and increased/presence of depression at T1. The receiver operating characteristic (ROC) curve analysis of skin conductance for depression was fair (area under curve = 0.812). ConclusionsThe ability of skin conductance to predict depression among geriatric populations may facilitate the detection of geriatric depression and future research on the pathophysiology.

The influence of parents on children's consciousness of gender equality: a multi-group structural equation modeling approach.

This study aimed to understand the consciousness of gender equality among school-aged children in China and its influencing factors using structural equation modeling to explore the pathways, intensity and group differences among these factors. A cross-sectional survey was conducted using stratified random whole-group sampling of primary school students in grades 1-6 and their parents who met the inclusion and exclusion criteria. In this study, 1,312 valid questionnaires were collected from a total of 1,500 school-aged children in Hunan Province, China (effective response rate of 87.5%). Statistical analysis was conducted using SPSS 26.0 and AMOS 24.0 software. Statistical inference consisted of t-tests, analysis of variance, the LSD test, Pearson correlation analysis, multiple stepwise linear regression analysis and structural equation modeling. School-aged children had the lowest consciousness of gender equality in the area of occupation and relatively higher consciousness in the areas of family and school. Children's age, gender, gender role, parent-child relationship, teacher-student relationship and parents' gender equality consciousness had predictive effects on children's consciousness of gender equality. The structural equation model constructed in this study is applicable to school-aged children of different genders. There was a significant difference in the structural equation modeling for children in different study period groups. In the education process, parents and teachers should attempt to improve their own consciousness of gender equality, integrate the concept of androgynous education, enhance close relationships with children, and adopt appropriate education methods according to the characteristics of different groups of children.

Surface Geological Evolution in the Chang'e 5 Landing Area (Em4 Unit) Revealed by a New Age‐Retrieving Method From Regression Learning

AbstractThe chronology function and production function have been widely used to derive the model ages of lunar mare regions from crater size‐frequency distributions. Challenges remain in homogenous counting area selection, crater saturation and crater rim identification. Geological unit‐based ages are also difficult to study the continuous surface evolution among adjacent areas. Using regression‐learning models, we have tried a new method on the Em4 unit of the Chang'e 5 landing area to explore a quantitative relationship between ages and surface morphometric expressions using texture features. Four features (Contrast, Energy, Entropy and Homogeneity), together with a stepwise linear model (SL) and a linear support‐vector‐machine model (LS), are well selected to produce a pixel‐level continuous age map of the Em4 unit. Mean age values of 1.75 ± 0.26 Ga and 1.69 ± 0.22 Ga obtained respectively from the two models are consistent with the ages of Chang'e 5 samples returned from this area. Both texture features and age maps are separated along the NW‐SE sinuous rilles (Rima Sharp and Rima Mairan). Comprehensively considering the geology, geomorphology, and newly retrieved ages of the study region, we have proposed a three‐stage evolution process for the Em4 unit. Our new age‐retrieving method is useful for obtaining a pixel‐level high‐resolution age map in the study region and has the potential to be widely used in other lunar mare areas.

Associations between 3D-based Left Atrial Volumetric and Blood Flow Parameters in a Single-Site Cohort of the Multi-Ethnic Study of Atherosclerosis.

Purpose To investigate associations between left atrial volume (LAV) and function with impaired three-dimensional hemodynamics from four-dimensional flow MRI. Materials and Methods A subcohort of participants from the Multi-Ethnic Study of Atherosclerosis from Northwestern University underwent prospective 1.5-T cardiac MRI including whole-heart four-dimensional flow and short-axis cine imaging between 2019 and 2020. Four-dimensional flow MRI analysis included manual three-dimensional segmentations of the LA and LA appendage (LAA), which were used to quantify LA and LAA peak velocity and blood stasis (% voxels < 0.1 m/sec). Short-axis cine data were used to delineate LA contours on all cardiac time points, and the resulting three-dimensional-based LAVs were extracted for calculation of LA emptying fractions (LAEFtotal, LAEFactive, LAEFpassive). Stepwise multivariable linear models were calculated for each flow parameter (LA stasis, LA peak velocity, LAA stasis, LAA peak velocity) to determine associations with LAV and LAEF. Results This study included 158 participants (mean age, 73 years ± 7 [SD]; 83 [52.5%] female and 75 [47.4%] male participants). In multivariable models, a 1-unit increase of LAEFtotal was associated with decreased LA stasis (β coefficient, -0.47%; P < .001), while increased LAEFactive was associated with increased LA peak velocity (β coefficient, 0.21 cm/sec; P < .001). Furthermore, increased minimum LAV indexed was most associated with impaired LAA flow (higher LAA stasis [β coefficient, 0.65%; P < .001] and lower LAA peak velocity [β coefficient, -0.35 cm/sec; P < .001]). Conclusion Higher minimum LAV and reduced LA function were associated with impaired flow characteristics in the LA and LAA. LAV assessment might therefore be a surrogate measure for LA and LAA flow abnormalities. Keywords: Atherosclerosis, Left Atrial Volume, Left Atrial Blood Flow, 4D Flow MRI Supplemental material is available for this article. © RSNA, 2024.

Ecological Risk and Pollution Assessment of Heavy Metals in Farmland Soil Profile with Consideration of Atmosphere Deposition in Central China.

Heavy metals (HMs) in agricultural land have caused serious environmental problems, resulting in severe contamination of the food chain and posing potential health threats. This study aims to investigate the pollution levels and potential ecological risks of HMs in farmland soils in central China, taking into account atmospheric deposition. Several indices were used to assess the status of HMs and compare surface soil with deeper soil. Descriptive statistics, Pearson correlation, and UMAP clustering methods were utilized to identify the characteristics of HMs. Additionally, stepwise linear regression models were employed to quantify the contributions of different variables to the potential ecological risks of HMs. The results showed that the average content of Zn in surface soil (289.41 ± 87.72 mg/kg) was higher than in the deeper soil (207.62 ± 37.81 mg/kg), and similar differences were observed in the mean values of related Igeo (1.622 ± 0.453 in surface soil and 1.183 ± 0.259 in deeper soil) and PEI (0.965 ± 0.292 in surface soil and 0.692 ± 0.126 in deeper soil) indices. This indicates that surface soil is more heavily polluted. The UMAP results confirmed the high variability of HMs in the surface soil, while PCA results suggested the importance of pollution and ecological risk indices. The stepwise linear model revealed that different variable structures contribute differently to the risk. In conclusion, Cr and Zn were found to be the major contaminants in the local farmland soil, with higher concentrations in the surface soil. The geoaccumulation and total potential ecological risk were classified as low risk. High variability of HMs was observed in the surface soil. Therefore, HM-related pollution indices and ecological risk indices are important for assessing the contamination status of local HMs. The local potential ecological risk can be attributed to specific heavy metals, each of which can have different effects on the local ecological risk.

Freezing of gait in Parkinson’s disease with glucocerebrosidase mutations: prevalence, clinical correlates and effect on quality of life

ObjectivesMutations in glucocerebrosidase (GBA1) can change the clinical phenotype of Parkinson’s disease (PD). This study aimed to explore the clinical characteristics of freezing of gait (FOG) in PD patients with GBA1 mutations.MethodsA whole-exome sequencing analysis was used to identify the GBA1 mutations (pathogenic or likely pathogenic) and exclude other PD-related gene mutations. A forward binary logistic regression model was conducted to identify the associated factors of FOG. The stepwise multiple linear regression analysis models were used to explore the effect of FOG on quality of life.ResultsThe prevalence of FOG in patients with GBA1 mutations (30/95, 31.6%) was significantly higher than those in patients without GBA1 mutations (152/760, 20%) (p = 0.009). A higher (i.e., worse) Unified PD Rating Scale part III score (OR = 1.126, 95%CI = 1.061–1.194, p &amp;lt; 0.001) and a lower (i.e., worse) Montreal Cognitive Assessment score (OR = 0.830, 95%CI = 0.713–0.967, p = 0.017) were significantly associated with FOG in PD patients with GBA1 mutations. The presence of FOG was significantly associated with the decreased (i.e., worse) score of PD Questionnaire 39 after adjustment for sex, age, disease duration, motor score, and non-motor score (B = 14.981, p = 0.001).ConclusionFOG is a relatively common disabling symptom in PD patients with GBA1 mutations, which is affected by motor disability and cognitive decline. Quality of life is reduced in patients with FOG and GBA1 mutations.

The Impact of Airway Obstruction on Feno Values in Asthma Patients

Exhaled nitric oxide (Feno) is used as a marker of type-2 airway inflammation in asthma management. Studies with airway challenges demonstrated that a reduction in airway caliber decreases Feno levels. To evaluate the impact of airway caliber reduction occurring spontaneously in patients with asthma on Feno values in daily clinical practice. In this post hoc analysis, Feno, FEV1, and asthma control questionnaire scores were recorded on each visit for 120 (1073 visits) adult patients with asthma. Blood eosinophils were measured intermittently. The intraindividual relationship between Feno and FEV1 was evaluated via a linear mixed model. The determinants of the individual mean Feno were measured by a stepwise multivariate linear model including individual mean FEV1, inhaled corticosteroid dose, asthma control questionnaire score, and blood eosinophils. Variations in the negative Feno-FEV1 relationship within individuals at different times were significantly determined by the individual's mean FEV1. This relationship did not hold for individuals above the 75th and below the 25th quartiles. The best explanatory variables for individual mean Feno were FEV1 (+4.3 parts per billion/10%pred) and blood eosinophil count (+1 part per billion per 100 cells/mm3). In the presence of variable degrees of heterogeneous patterns of airway inflammation, airway caliber is shown to be an independent and significant determinant of Feno when measured in patients with asthma. We would propose a+4-parts-per-billion correction factor to the measured Feno value for each 10% reduction below 100% predicted FEV1. Doing this should improve the rigor of interpretation of Feno as an indicator of type-2 inflammation in patients with low FEV1.

Environmental determinants of vegetation in the drawdown zones of a Columbia River Treaty reservoir: a template for ecosystem enhancement.

Water storage reservoirs alternately inundate and expose the drawdown zones, limiting riparian vegetation that provides wildlife habitats and contributes to the aquatic food-web. To characterize plant distributions and hydrogeomorphic associations, we inventoried quadrats in transects extending from the full-pool (FP) margin, downwards 12 m through the drawdown zones at sites around the Duncan Reservoir in British Columbia, Canada. Among the 69 plant species, black cottonwoods (Populus trichocarpa), willows (primarily Salix sitchensis) and other trees and shrubs occurred sparsely, rarely extending below 2 m below FP. Perennial herbaceous plants, especially horsetail (Equisetum arvense) and sedges (primarily Carex utriculata), were most common, extending down ~5 m below FP, and ruderal annual plants occurred sparsely at greater depths. Vegetation Cover and Species Richness were correlated with environmental factors, with (1) Elevation being highly influential, reflecting inundation duration and depth. (2) Position, longitudinal location, reflected greater vegetation diversity downstream of the reservoir. (3) Finer Substrate texture was favorable to retain moisture, but coarse sediments would resist erosion. (4) Shallow Slope was favorable to reduce drainage and included finer sediments. (5) Distance from the FP shoreline could reflect seed source proximity. Stepwise linear modeling with combined environmental factors accounted for ~30% of the variation in Vegetation Cover and Richness, and Canonical Correspondence Analysis revealed plant groupings relative to the environmental influences. At this and other storage reservoirs, regimes that reduce the frequency and duration of inundation could promote vegetation in locations with suitable environmental conditions in the upper drawdown zones, thus providing ecosystem enhancement.

Differential associations between childhood maltreatment types and borderline personality disorder from the perspective of emotion dysregulation

BackgroundBorderline Personality Disorder (BPD) is characterized by pervasive instability in a range of areas including interpersonal relationships, self-image, and affect. Extant studies have consistently identified significant correlations between childhood maltreatment (CM) and BPD. While exploring this CM-BPD link, a number of cross-sectional studies commonly emphasize the role of emotion dysregulation (ED). A better understanding of the associations between BPD and (1) CM and (2) ED are essential in formulating early, effective intervention approaches, and in addressing varied adverse impacts.MethodsThis cross-sectional study analyzed a subset of baseline data collected for a larger community-based longitudinal study. Given that our current focus on CM and ED, only those participants who completed the baseline CM assessment and ED measure (N = 144) were included for the primary analyses. We conducted stepwise multivariate linear models to examine the differential relationships between BPD features, ED, and multiple CM types. A path analysis with latent factors using the structural equation modeling (SEM) method was performed to test the indirect effect from CM to BPD features via ED.ResultsLinear regression models revealed that only emotional abuse (relative to other trauma types) was significantly associated with high BPD features. The SEM, by constructing direct and indirect effects simultaneously, showed that (1) ED partially mediated the path from CM to BPD features; and (2) CM played an important role in which the direct effect remained significant even after accounting for the indirect effect through ED.ConclusionsOur results highlight a most consistent association between emotional abuse and BPD, indicating its unique role in understanding BPD features in the context of CM. Further, shame-related negative appraisal and ED were found critical when examining the association between CM and BPD, possibly providing promising treatment targets for future practices.

Racial inequality in functional trajectories between Black and White U.S. veterans.

Racial inequality in functional trajectories has been well documented in the U.S. civilian population but has not been explored among Veterans. Our objectives were to: (1) assess how functional trajectories differed for Black and White Veterans aged ≥50 and (2) explore how socioeconomic, psychosocial, and health-related factors altered the relationship between race and function. We conducted a prospective, longitudinal analysis using the 2006-2016 Health and Retirement Study. The study cohort included 3700 Veterans who self-identified as Black or White, responded to baseline psychosocial questionnaires, and were community-dwelling on first observation. We used stepwise and stratified linear mixed effects models of biannually assessed functional limitations. The outcome measure was as a count of functional limitations. Race was measured as respondent self-identification as Black or White. Demographic measures included gender and age. Socioeconomic resources included partnership status, education, income, and wealth. Psychosocial stressors included exposure to day-to-day and major discrimination, traumatic life events, stressful life events, and financial strain. Health measures included chronic and mental health diagnoses, smoking, rurality, and use of Veterans Affairs services. Black Veterans developed functional limitations at earlier ages and experienced faster functional decline than White Veterans between the ages of 50 and 70, with convergence occurring at age 85. Once we accounted for economic resources and psychosocial stressors in multivariable analyses, the association between race and the number of functional limitations was no longer statistically significant. Lower wealth, greater financial strain, and traumatic life events were significantly associated with functional decline. Health systems should consider how to track Veterans' function earlier in the life course to ensure that Black Veterans are able to get timely access to services that may slow premature functional decline. Providers may benefit from training about the role of economic resources and psychosocial stressors in physical health outcomes.

Intermediate human activities maximize dryland ecosystem services in the long-term land-use change: Evidence from the Sangong River watershed, northwest China

Human activities cause widespread changes in landscape composition, which can affect ecosystem services produced by these landscapes. It is usually believed that ecosystem services can be maximized only when we eliminate all human activities. However, this belief is not the case, at least in dryland ecosystems. Here, a gradient of human activity intensity was used to investigate changes in the value of ecosystem services over 30-years of land-use change between 1990 and 2020 in the arid Sangong River watershed of northwest China. Spatial analyses were performed to determine how the value of dryland ecosystem services changed with human activity intensity. Stepwise regressions and linear programming models were also performed to examine how to optimize the value of ecosystem services (i.e., regulating services, provisioning services, supporting services, and cultural services). We found that landscapes of the Sangong River watershed became increasingly fragmented and that human activities gradually intensified, but the value of ecosystem services fluctuated rather than linearly decreasing over the past 30 years. Specifically, a unimodal relationship was observed between human activities and ecosystem services. The peak value of ecosystem services was 5799 USD ha−1 yr−1 under intermediate human activity intensity (i.e., human footprint index ranged from 0.2 to 0.4 at a scale of one). Gross domestic product (GDP) per capita, population, and water consumption were the three most important driving factors of human activities and ecosystem services. Our results suggest that intermediate human activities may maximize dryland ecosystem services in long-term land-use change at the watershed scale, and highlight the importance of regulating economic development, population, and water consumption for the management of dryland ecosystem services.

Mental well-being in young people with psychiatric disorders during the early phase of COVID-19 lockdown.

BackgroundMental health and well-being were seriously impacted by the COVID-19 lockdown especially among young people and people with psychiatric disorders. This study aimed to identify factors associated with well-being in young people with psychiatric disorders, during early phase of COVID-19 lockdown in France.MethodsA national cross-sectional online study started on the 8th day of COVID-19 lockdown in France (during March 25–30, 2020). We included young people aged from 16 to 29 who responded to the questionnaire, living and being confined in France, with past or current psychiatric treatment. The questionnaire was accessible online and explored demographics and clinical factors, well-being, stress, situation during lockdown. Well-being was measured by the Warwick-Edinburg Mental Well-Being Scale (WEMWBS). Simple and multiple linear regression analyses were carried out.Results439 individuals were included with 262 (59.7%) previously treated and 177 (40.3%) currently treated. WEMWBS total score were 42.48 (9.05). Feeling of useful was the most affected dimension. Well-being was positively correlated with: currently working on site, physical activity, abilities to cope with difficulties, family and social supports (p<0.05). It was negatively correlated with: elevated stress level, anxious ruminations, dissatisfaction with information, difficulties to sleep or reorganize daily life, feeling supported by medicines (p<0.05). No individual factor was correlated with well-being. The stepwise linear multivariate model had simple R2 coefficient of determination of 0.535.ConclusionIn the specific population of young people with psychiatric disorders, factors associated with well-being at early stage of lockdown were mainly psychosocial and related to brutal disorganisation of daily life.

Determinants of physical function in community dwelling old people

Background. Poor physical function is associated with disability and mortality in old people. Objectives. The aim was to find determinants of physical function in old people. Design. Secondary, cross-sectional analysis.Setting. Community in the Reykjavik, Iceland.Participants. 236 old people (73.7 ± 5.7 years, 58.2% female).Measurements. Timed-up-and-go (TUG), six-minute-walk-for-distance (6MWD), anthropometrics, quadriceps strength, dietary intake, mini-mental-state-examination (MMSE), leisure-time physical activity (LTPA) and blood variables were assessed. Descriptive, bivariate and multivariate statistical analyses were used.Results. There were differences between men and women in energy intake, body composition and muscular strength, but physical function did not differ between men and women. In bivariate analysis, most of the assessed variables correlated with 6MWD and TUG. Stepwise linear models showed that age, body composition, strength, medication, LTPA and MMSE were predictors of physical function but not hematological variables. The association between MMSE and function disappeared when corrected for strength/body weight. Results were similar for both 6MWD and TUG and the strongest predictors in the final models were age and quadriceps strength/body weight. Conclusions. In community dwelling old people, physical function decreases with age. However, it is of clinical relevance that there are modifiable determinants of physical function, in particular strength for a given body weight, LTPA and number of medications, which represent potential targets to maintain physical function in this age group. Our results also indicate that neither cognitive function, nor dietary intake nor blood chemical variables were independently associated with physical function.

Combined influence of maximum accumulation and melt rates on the duration of the seasonal snowpack over temperate mountains

The duration of the seasonal snowpack determines numerous aspects of the water cycle, ecology and the economy in cold and mountainous regions, and is a balance between the magnitude of accumulated snow and the rate of melt. The contribution of each component has not been well quantified under contrasting topography and climatological conditions although this may provide useful insights into how snow cover duration could respond to climate change. Here, we examined the contribution of the annual peak snow water equivalent (SWE) and the seasonal melt rate to define the duration of the snowpack over temperate mountains, using snow data for mountain areas with different climatological characteristics across the Iberian Peninsula. We used a daily snowpack database for the period 1980–2014 over Iberia to derive the seasonal peak SWE, melt rate and season snow cover duration. The influence of peak SWE and melt rates on seasonal snow cover duration was estimated using a stepwise linear model approach.The stepwise linear models showed high R-adjusted values (average R-adjusted = 0.7), without any clear dependence on the elevation or geographical location. In general, the peak SWE influenced the snow cover duration over all of the mountain areas analysed to a greater extent than the melt rates (89.1%, 89.2%, 81.6% 93.2% and 95.5% in the areas for the Cantabrian, Central, Iberian, Pyrenees and Sierra Nevada mountain ranges, respectively). At these colder sites, the melt season occurs mostly in the spring and tends to occur very fast. In contrast, the areas where the melt rates dominated snow cover duration were located systematically at lower elevations, due to the high interannual variability in the occurrence of annual peak SWE (in winter or early spring), yielding highly variable melt rates. However, in colder sites the melt season occurs mostly in spring and it is very fast in most of the years. The results highlight the control that the seasonal precipitation patterns, in combination with temperature, exert on the seasonal snow cover duration by influencing the peak SWE and suggest a future increased importance of melt rates as temperatures increase. Despite the high climatological variability of the Iberian mountain ranges, the results showed a consistent behaviour along the different mountain ranges, indicating that the methods and results may be transferrable to other temperate mountain areas of the world.

Functional Connectivity and Speech Entrainment Speech Entrainment Improves Connectivity Between Anterior and Posterior Cortical Speech Areas in Non-fluent Aphasia

Background Speech entrainment (SE), the online mimicking of an audio-visual speech model, has been shown to increase speech fluency in individuals with non-fluent aphasia. One theory that may explain why SE improves speech output is that it synchronizes functional connectivity between anterior and posterior language regions to be more similar to that of neurotypical speakers. Objectives The present study tested this by measuring functional connectivity between 2 regions shown to be necessary for speech production, and their right hemisphere homologues, in 24 persons with aphasia compared to 20 controls during both free (spontaneous) speech and SE. Methods Regional functional connectivity in participants with aphasia were normalized to the control data. Two analyses were then carried out: (1) normalized functional connectivity was compared between persons with aphasia and controls during free speech and SE and (2) stepwise linear models with leave-one-out cross-validation including normed functional connectivity during both tasks and proportion damage to the left hemisphere as independent variables were created for each language score. Results Left anterior–posterior functional connectivity and left posterior to right anterior functional connectivity were significantly more similar to connectivity of the control group during SE compared to free speech. Additionally, connectivity during free speech was more associated with language measures than connectivity during SE. Conclusions Overall, these results suggest that SE promotes normalization of functional connectivity (i.e., return to patterns observed in neurotypical controls), which may explain why individuals with non-fluent aphasia produce more fluent speech during SE compared to spontaneous speech.

Analyzing the Contribution of Human Mobility to Changes in Air Pollutants: Insights from the COVID-19 Lockdown in Wuhan

During the COVID-19 lockdown in Wuhan, transportation, industrial production and other human activities declined significantly, as did the NO2 concentration. In order to assess the relative contributions of different factors to reductions in air pollutants, we implemented sensitivity experiments by Random Forest (RF) models, with the comparison of the contributions of meteorological conditions, human mobility, and emissions from industry and households between different periods. In addition, we conducted scenario analyses to suggest an appropriate limit for control of human mobility. Different mechanisms for air pollutants were shown in the pre-pandemic, pre-lockdown, lockdown, and post-pandemic periods. Wind speed and the Within-city Migration index, representing intra-city mobility intensity, were excluded from stepwise multiple linear models in the pre-lockdown and lockdown periods. The results of sensitivity experiments show that, in the COVID-19 lockdown period, 73.3% of the reduction can be attributed to decreased human mobility. In the post-pandemic period, meteorological conditions control about 42.2% of the decrease, and emissions from industry and households control 40.0%, while human mobility only contributes 17.8%. The results of the scenario analysis suggest that the priority of restriction should be given to human mobility within the city than other kinds of human mobility. The reduction in the NO2 concentration tends to be smaller when human mobility within the city decreases by more than 70%. A limit of less than 40% on the control of the human mobility can achieve a better effect, especially in cities with severe traffic pollution.

Optimal surgical component alignment minimizes TKR wear – An in silico study with nine alignment parameters

Currently, preclinical mechanical wear testing of total knee replacements (TKRs) is done using ideally aligned components using standardized TKR level walking under either force or displacement-control regimes. To understand the influence of implant alignment and testing control regime, we studied the effect of nine component alignment parameters on TKR volumetric wear in silico. We used a computational framework combining Latin Hypercube sampling design of experiments, finite element analysis, and a numerical model of polyethylene wear, to create a predictive model of how component alignment affects wear rate for each control regime. Nine component alignment parameters were investigated, five femoral variables and four tibial variables. To investigate perturbations of the nine implant alignment variables, two separate 300-point designs were executed, one for each control regime. The results were then used to generate surrogate statistical models using stepwise multiple linear regression. Wear at the neutral position was 4.5mm3/million cycle and 8.6mm3/million cycle for displacement and force-control, respectively. Stepwise multiple linear regression surrogate models were highly significant for each control regime, but force-control generated a stronger predictive model, with a higher R2, more included terms, and a lower RMSE. Both models predicted transverse plane rotational mismatch can lead to large changes in predicted wear; a transverse plane alignment mismatch of 15° can elicit a change in wear of up to 5mm3/million cycle, almost double that of neutral alignment. Therefore, transverse plane alignment is particularly important when considering failure of the implant due to wear.