Linear Model Research Articles

Longitudinal predictors for internalizing and externalizing symptomatology at age 4: KUNO-Kids cohort study

IntroductionNumerous early-life risk factors are thought to significantly contribute to the development of psychological problems in toddlerhood. However, these factors have seldom been investigated concomitantly and longitudinally, and few studies include both mothers and fathers. This study examines the longitudinal impact of early environmental, parental, and child-specific risk factors on children’s internalizing and externalizing symptomatology at age 4.MethodsFamilies were recruited from a perinatal center at birth and completed self-report questionnaires at birth, 4 weeks postpartum, 6 months postpartum, and annually thereafter. The final population-based sample consisted of n = 560 mothers (and fathers) who gave birth after June 2015, with children who turned 4 years old before March 31, 2021. The primary outcomes, children’s internalizing and externalizing symptomatology at age 4, were measured using the Strengthsand Difficulties Questionnaire. Linear mixed effect models were used to estimate growth curves for predictors between 4 weeks and 4 years postpartum, which were subsequently entered into multivariable linear regressions to predict internalizing and externalizing symptomatology at age 4.ResultsThe study identified several key risk factors: environmental (lack of social support, lower parental education, male sex), parental (poor parental mental health, increased parenting stress, parental sleep difficulties) and child-specific (children’s low physical health, children’s reduced sleep quality, temperament).DiscussionThe findings underscore that most identified risk factors are related to children’s temperament, mental and physical health of parents, their experienced stress, and families’ social support networks. These insights highlight the importance of targeted interventions focusing on improving parental mental health, reducing stress, and enhancing social support to mitigate early-life psychological problems in children.

Does the association between physical activity during work and leisure and blood pressure differ across sex? A cross-sectional compositional data analysis in a Danish population-based cohort.

A proposed risk factor for cardiovascular disease is high occupational physical activity (OPA), which seems to increase blood pressure (BP), in contrast to leisure time physical activity. Increased BP may lead to hypertension that increase the risk of cardiovascular disease and premature death. Exposures to OPA differ across sex and also within occupational group. Thus, we aimed to investigate associations between OPA and LTPA and BP among men and women using compositional data analysis. This population-based cross-sectional study, used data from the Copenhagen Aging and Midlife Biobank. OPA and LTPA were self-reported time spent in light physical activity (LPA) during work = standing or walking work; moderate-to-vigorous physical activity (MVPA) during work = heavy manual work; LPA during leisure = light physical activity during leisure; MVPA during leisure = biking or walking as commute to work + daily amount of MVPA during leisure, and sleep. Systolic and diastolic BP (SBP, DBP; mmHg) was measured during sitting rest. We used linear regression models to investigate the association between OPA and LTPA, expressed as isometric log-ratios, and BP. The models were used to predict the BP for reallocated physical activity (PA) compositions (i.e., theoretically 'moving' time from sitting to PA within each domain). Specifically, we predicted the BP for each reallocated PA compositions and calculated the difference in BP between the reallocated compositions and the mean composition. In total, 1,334 women and 2,983 men (mean age 55.1 and 52.5 years, respectively) were included in the analyses. About 50% of the women, and 66% of the men, had hypertension. The linear regressions based on the compositional data analysis, showed no association between OPA and LTPA and SBP among women or men. Among men, less time spent sitting and more time spent in LTPA, compared to the mean composition, was associated with a lower DBP (e.g., 60min less sitting and 60min more LTPA: -0.25, 95% CI: -0.05, -0.45 mmHg). No association between OPA and LTPA and BP was observed across sexes, except between LTPA and DBP among men. This could be due to information bias and lack of precision in self-reported time use data of PA. None.

Survival and Success of 3D-Printed Versus Milled Immediate Provisional Full-Arch Restorations: ARetrospective Analysis.

To evaluate and compare the survival rates of 3D-printed and chairside milled resin polymethylmethacrylate (PMMA) immediate temporary provisional full-arch implant restorations using prosthetic survival as the primary outcome. Records of 335 routine patients receiving 443 temporary six-implant retained maxillary or mandibular prosthetic restorations between January 2019 and January 2022 at a private clinic (Dr Sobczak Clinical Centre, Radosc, Poland) were considered for this retrospective analysis. The analysis compared prosthetic and implant failure rates between printed and milled restorations as primary and secondary outcomes, respectively. Patient-related and treatment-related characteristics between groups were compared using the Chi-square test and Mann-Whitney U-test, respectively. Group-specific cumulative prosthetic survival was qualitatively and quantitively compared using Kaplan-Meier, generalized linear mixed models and univariate cox proportional hazard analyses. Prosthetic survival was set into context to implant survival using Chi-square tests. A multivariable cox proportional hazards model with frailty was used to identify confounding factors affecting prosthetic survival. Prosthetic failure rates of milled and printed temporary restorations were 13.01% and 11.25% over the average follow-up period of 307.7 ± 115.5 days, respectively. The corresponding 180-day cumulative prosthetic survival rates were 92.4% and 93%. Hazard ratios for the prosthetic failure of milled and printed restorations did not show a statistical difference (p = 0.794). Implant failure rates in restorations that experienced prosthetic failure (17.31%) were higher compared to restorations without failures (5.63%), with a 3.2 times significantly higher odds of failure for a prosthesis experiencing implant loss (p = 0.003). Gender, presence of teeth at treatment baseline, smoking, and bone augmentation were identified as confounding factors impacting prosthetic survival. Chairside 3D-printed restorations may represent an equivalent treatment modality to established chairside milled restorations for immediate full-arch therapy. Provisional prosthetic survival may impact implant survival and treatment success.

A Reduced Modeling Approach for Making Predictions with Incomplete Data Having Blockwise Missing Patterns

Incomplete data with blockwise missing patterns are commonly encountered in analytics, and solutions typically entail listwise deletion or imputation. However, as the proportion of missing values in input features increases, listwise or columnwise deletion leads to information loss, whereas imputation diminishes the integrity of the training data set. We present the blockwise reduced modeling (BRM) method for analyzing blockwise missing patterns, which adapts and improves on the notion of reduced modeling proposed by Friedman, Kohavi, and Yun in 1996 as lazy decision trees. In contrast to the original idea of reduced modeling of delaying model induction until a prediction is required, our method is significantly faster because it exploits the blockwise missing patterns to pretrain ensemble models that require minimum imputation of data. Models are pretrained over the overlapping subsets of an incomplete data set that contain only populated values. During prediction, each test instance is mapped to one of these models based on its feature-missing pattern. BRM can be applied to any supervised learning model for tabular data. We benchmark the predictive performance of BRM using simulations of blockwise missing patterns on three complete data sets from public repositories. Thereafter, we evaluate its utility on three data sets with actual blockwise missing patterns. We demonstrate that BRM is superior to most existing benchmarks in terms of predictive performance for linear and nonlinear models. It also scales well and is more reliable than existing benchmarks for making predictions with blockwise missing pattern data. Supplemental Material: The online appendix is available at https://doi.org/10.1287/ijds.2022.9016 .

Association Between Chronic Pain and Fatigue Severity with Weather and Air Pollution Among Females with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

Weather and air quality conditions have been anecdotally reported to be related to symptom fluctuations in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), but this has never been empirically investigated. This exploratory study aims to examine the effects of weather and air quality on daily fluctuations of chronic pain and fatigue in women with ME/CFS. In an intensive longitudinal design, 58 participants with ME/CFS provided daily pain and fatigue ratings for an average of 61 days. Daily weather and air quality data were obtained from the National Oceanic and Atmospheric Administration and the US Environmental Protection Agency for the Birmingham, AL area. Linear mixed models revealed a significant relationship between days with more severe pain and worse Air Quality Indices (AQI, p < 0.001), lower wind speeds (p = 0.009), greater particulate matter (p = 0.037), and lower carbon monoxide (p = 0.004), sulfur dioxide (p = 0.003), and ozone levels (p = 0.015). Greater fatigue was associated with more particulates (p = 0.023) and lower barometric pressure (p = 0.048). These results suggest that air quality and weather can have small effects on ME/CFS symptom severity.

Association of Modifiable Lifestyle Risk Factors with High-Sensitivity Troponin T and I Concentrations and Clinical Outcomes.

We aimed to investigate the association between the burden of modifiable lifestyle risk factors (modLRF) with high-sensitivity cardiac troponins T and I (hsTnT/I) and clinical outcomes in a contemporary cohort. Patients undergoing coronary angiography with available hsTnT/I concentrations and information about modLRF were included in the current single-centre study. The modLRF investigated were overweight, lack of physical activity, poor adherence to a Mediterranean diet and current smoking. To evaluate the impact of modLRF on hsTnT/I levels, a linear regression model was used. A Cox regression analysis was computed to investigate the association of hsTnT/I levels with clinical outcomes, stratified by the burden of modLRF, and a C-Index was calculated to investigate the additive predictive benefit of the integration of hsTn on top of a base model containing modLRF only. Outcomes of interest were all-cause mortality and major adverse cardiovascular events (MACE). In the overall study population of n=1,716 patients median troponin levels were 15.0 ng/l (IQR 8.0, 29.0) and 7.6 ng/l (IQR 3.3, 18.6) for hsTnT and I, respectively. An increasing number of modLRF was independently associated with elevated hsTnT and I concentrations. Moreover, hsTnT and hsTnI were independently associated with all-cause mortality in patients with 1-2 and ≥3 modLRF, and an incremental value of the integration of hsTnT and hsTnI was noted, especially in the prediction of all-cause mortality was noted. Lastly, an independent association of hsTnI with MACE was documented in patients with 1-2 modLRF, which was not the case for hsTnT. Increasing numbers of modLRF are associated with elevated concentrations of hsTnT and I, whilst the predictive capability of troponins varied according to the presence of modLRF. Further prospective studies are needed to investigate, whether targeting modLRF might result in lower hsTn concentrations and improved outcomes.

Mental Health in China: Social Change in Life Course Trajectories

AbstractKnowledge about life course trajectories and intercohort changes in mental health is limited mainly to Western populations. To address this gap, our study analyzes mental health trajectories in China, drawing on data on depressive symptoms from the China Family Panel Studies over the period 2012–2020 (N = 31,700 individuals aged 16–70; N = 87,787 person‐years). Employing hierarchical linear regression models, our findings reveal moderate increases in depressive symptoms over the life course and across cohorts. Subgroup analyses indicate that women, people with lower educational attainment, and people with rural hukou experienced more depressive symptoms and a more pronounced increase in depressive symptoms with age. These disparities narrowed across cohorts. We discuss these patterns in the context of Chinese cultural dynamics, including son preference, the impact of education and hukou on the accumulation of stress over the life course, family policy and equity policy transitions, and the changing stigma of mental health.

Associations between metabolic score for visceral fat and adult lung functions from NHANES 2007–2012

BackgroundObesity is a significant part of the factors affecting lung function, and the assessment of obesity using the Metabolic Score for Visceral Fat (METS-VF) is more precise than other indicators like waist circumference and body mass index. This study investigated the relationship between lung function and METS-VF in The National Health and Nutrition Examination Survey (NHANES) database from 2007 to 2012.MethodThe data utilized in this study was obtained from National Health and Nutrition Examination Survey spanning the years 2007 to 2012. A multivariate linear regression analysis was employed to investigate the association between METS-VF and lung function, followed by subgroup analysis to identify populations that may exhibit heightened sensitivity. Nonlinear correlations were assessed by fitting a restricted cubic spline, with validation of results conducted via threshold effect analysis.ResultIn a study involving 4,356 participants, a weighted multiple linear regression model revealed a significant negative association between the METS-VF and forced expiratory volume in the first second (FEV1), forced vital capacity (FVC), FEV1/FVC ratio, and forced expiratory flow between 25 and 75% of FVC (FEF25-75%). However, no association was observed with peak expiratory flow rate (PEF). When dividing the METS-VF into thirds, participants in the highest third exhibited significantly decreased levels of FEV1 (β: −342, 95%CI: −440, −245, p < 0.001), FVC (β: −312, 95%CI: −431, −192, p < 0.001), FEV1/FVC (β: −0.020, 95%CI: −0.030, −0.010, p < 0.001), and FEF25-75% (β: −424, 95%CI: −562, −285, p < 0.001). However, there was no significant relationship with PEF (β: −89, 95%CI: −325, 147, p = 0.446). RCS curve indicated a nonlinear negative correlation between METS-VF and FEV1, FVC, and FEV1/FVC. For FEV1, a significant negative correlation was found when the METS-VF < 6.426 (β = −158.595, 95%CI: −228.183, −89.007). This negative association became more pronounced when the METS-VF > 6.426 (β = −314.548, 95%CI: −387.326, −241.770). For FVC, a negative association was observed when the METS-VF < 6.401, (β = −5.477, 95%CI: −91.655, 80.702), but it did not reach statistical significance. However, METS-VF > 6.401, METS VF and lung function show a significant negative correlation (β = −399.288, 95%CI: −486.187, −312.388). FEV1/FVC showed a negative correlation only before the inflection point (METS-VF < 6.263) (β = −0.040, 95%CI: −0.047, −0.032), after the inflection point (METS-VF > 6.263), no correlation was found, but there was no statistical significance (β = 0.000; 95%CI: −0.006, 0.007), and METS-VF had a linear negative correlation with FEF25-75%. Subgroup analysis showed that the association was consistent across a variety of demographic factors, including age, sex, race, hypertension, and coronary heart disease. In addition, we found a stronger association between men under 40 and lung function.ConclusionMETS-VF showed a linear negative correlation with FEF25-75%, and a nonlinear negative correlation with FEV1, FVC, FEV1/FVC, and FEF25-75%, but was not associated with PEF, particularly among males under the age of 40. These findings offer valuable insights into managing lung function by controlling visceral fat.

Associations of circulating T-cell subsets with carotid artery stiffness: the Multi-Ethnic Study of Atherosclerosis.

Background: Arterial stiffness measured by total pulse wave velocity (T-PWV) is associated with increased risk of multiple age-related diseases. T-PWV can be described by structural (S-PWV) and load-dependent (LD-PWV) arterial stiffening. T-cells have been implicated in arterial remodeling, arterial stiffness, and hypertension in humans and animals; however, it is unknown whether T-cells are risk factors for T-PWV or its components. Therefore, we evaluated the cross-sectional associations of peripheral T-cell subpopulations with T-PWV, S-PWV, and LD-PWV. Methods: Peripheral blood T-cells were characterized using flow cytometry, and carotid artery stiffness was measured using B-mode ultrasound to calculate T-PWV at the baseline examination in a participant subset of the Multi-Ethnic Study of Atherosclerosis (MESA, n=1,984). A participant-specific exponential model was used to calculate S-PWV and LD-PWV based on elastic modulus and blood pressure gradients. The associations between five primary (p-significance<0.01) and twenty-five exploratory (p-significance<0.05) immune cell subpopulations, per 1-SD increment, and arterial stiffness measures were assessed using adjusted linear regression models. Results: For the primary analysis, higher CD4+CD28-CD57+, but not CD8+CD28-CD57+, T-cells were associated with higher LD-PWV (β=0.04 m/s, p<0.01) after adjusting for co-variates. None of the remaining T-cell subpopulations in the primary analysis were associated with T-PWV or S-PWV. For the exploratory analysis, several memory and differentiated/senescence-associated CD4+ and CD8+ T-cell subpopulations were associated with greater T-PWV, S-PWV, and LD-PWV after adjusting for co-variates. Conclusions: We highlight novel associations in humans between CD4+ and CD8+ memory and differentiated/senescence-associated T-cell subpopulations and measures of arterial stiffness in MESA. These results warrant longitudinal, prospective studies that examine changes in T-cell subpopulations and arterial stiffness in humans.

Cardiorespiratory Responses to Flywheel-Based Inertial Training Squats With Varying Moments of Inertia.

Mitchinson, CJ, Best, S, Caruso, J, and Bollinger, LM. Cardiorespiratory responses to flywheel-based inertial training squats with varying moments of inertia. J Strength Cond Res XX(X): 000-000, 2024-Flywheel-based inertial training (FIT) has gained popularity as a means to enhance muscle hypertrophy. Other applications, such as aerobic exercise training, remain unexplored. The aim of this study was to determine the cardiorespiratory responses to acute FIT with varying moments of inertia (MOIs). Methods: Overall, 20 (10 M, 10 F) healthy, physically active subjects underwent maximal graded exercise testing and completed 3 bouts of FIT exercise (1 familiarization session and 2 identical data collection sessions). Subjects completed quarter squats (60° peak knee flexion) at a pace of 50 squats·minute-1 until volitional fatigue. Flywheel-based inertial training MOI was increased by 0.005 kg·m2 every 3 minutes until a final workload of 0.020 kg·m2. Heart rate and gas exchange data were collected continuously and averaged over the final 60 s of each stage. Data were analyzed by a linear mixed model. Results: During the final testing session, there was a main effect of MOI to increase heart rate (HR), V̇o2, and RER. Men displayed greater oxygen consumption, but asimilar %V̇o2peak compared with women. We noted a significant inertia × sex interaction where RER tended to be lesser in women at higher MOI. In the final stage of exercise (MOI: 0.020 kg·m2), HR and V̇o2 were approximately 75-80 and 55% of peak, respectively, and RER was approximately 0.95-1.00. Conclusions: FIT quarter squats elicit moderate HR and V̇o2 responses, but near-maximal RER suggests a novel metabolic training stimulus. This exercise may supersede thelactate threshold and may not be sustainable for prolonged times. The physiological and performance effects of training in this manner are unclear.

Changes in quality of life during social isolation in elderly patients with visual impairment

Aim - determination of the nature of changes in the quality of life in social isolation and risk factors associated with it in elderly patients with visual impairment. Material and methods. A clinical group was formed of 115 participants aged 60-74 years who were in conditions of social isolation with visual impairment for a month. In accordance with the Helsinki Declaration, social isolation was determined on the basis of a 15-point scale, the quality of life questionnaire was used to measure changes in the quality of life and in its 4 factors, risk factors included socio-demographic, clinical categories and indicators of functional status. Results. The results of linear mixed models with random intersections comparing quality of life indicators before (3,30) and after social isolation (1,78) were significant (p0,001). During social isolation, 87% of participants with visual impairment had a decrease in quality of life (-2,39), while 13% of participants had an increase in quality of life (0,58). The following risk factors were associated with social isolation: low income (38%, p0,001), lack of higher education (29%, p=0,002), lung disease (25%, p=0,04), functional or sensory disorders, including difficulties with cooking (28%, p=0,004), difficulty passing one quarter (26%, p=0,03), hearing impairment (23%, p=0,02) and visual impairment (24%, p=0,01). Gender (p=0,39), ongoing pain (p=0,75), difficulties with daily activities (p=0,09), urinary incontinence (p=0,82), diabetes mellitus (p=0,87) and cognitive impairment (p=0,06) were insignificant. Conclusion. The period of social isolation led to a very significant decrease in the overall quality of life in the sample of elderly people with visual impairment. The leading risk factors for social exclusion were low income and lack of higher education.

Expressive Writing About One's Trauma Increases Accessibility of Cannabis Information in Memory Among Trauma-Exposed Individuals

Objective: Trauma survivors are more likely than others to use cannabis, and post-traumatic stress disorder (PTSD) commonly co-occurs with cannabis use disorder (CUD). Automatic memory associations between trauma reminders and cannabis use have been suggested as contributing mechanisms. These associations can be studied experimentally by manipulating trauma cue exposure in a cue-reactivity paradigm (CRP) and examining effects on the accessibility of cannabis information in memory in trauma survivors with and without PTSD. Method: Cannabis users with trauma histories (N = 202) completed a PTSD measure (PTSD Checklist-5) and were randomized to a trauma or neutral expressive writing task as an online CRP. Next, participants completed a cue-behavior word association task, which involved presentation of a series of ambiguous cue words to which participants provided the first word that came to mind. Some of these ambiguous cues pertained to cannabis (e.g., weed, pot) and some to other substances (e.g., blow, shot). This task was scored by two independent raters. Linear regression models tested the hypothesized main and interactive effects of CRP condition (trauma, neutral) and PTSD group (probable PTSD, no PTSD) on the number of cannabis and other substance responses generated. Results: Main effects of CRP condition were found for cannabis responses (b = 0.41, p = 0.048; trauma &gt; neutral) but not other substance responses. Unexpectedly, no main effects or interactions of PTSD group were observed for either outcome. Conclusions: In cannabis users with trauma histories, writing about one’s trauma specifically activates greater accessibility of cannabis-related information in memory, regardless of PTSD.

Comparing spiritual wellbeing and illness perceptions between cancer patients from culturally and linguistically diverse and those from mainstream backgrounds in Australia.

Cancer presents a significant health challenge, particularly within culturally and linguistically diverse (CALD) populations. Religious, spiritual, and personal beliefs regarding illness may mitigate its psychological and physical impacts, varying with CALD status. This study aims to assess illness perceptions in Australian cancer patients from both CALD and Anglo-Australian backgrounds and to explore the associations between spiritual wellbeing and illness perceptions within these groups. Cross-sectional study, involving 119 cancer patients from CALD backgrounds (Arabic, Chinese, and Greek) and 50 Anglo-Australians. Spiritual wellbeing and cancer perception were assessed using the World Health Organization Quality of Life-Spirituality, Religiousness, and Personal Beliefs questionnaire and the revised Illness Perception Questionnaire, respectively. Linear regression models analyzed associations. CALD patients perceived their cancer as less enduring (β - 4.74, 95%CI - 6.16, - 3.31) and symptoms as less predictable (- 4.96, 95%CI - 6.12, - 3.86) compared to Anglo-Australians. They had lower confidence in medical interventions (- 2.96, 95%CI - 3.36, - 1.22) and poorer illness understanding (- 4.66, 95%CI - 5.83, - 3.49). In Greek-speaking patients, an increase in spiritual wellbeing was associated with less favourable perceptions of treatment controllability (β - 2.25, 95%CI - 4.39, - 0.09). Conversely, for Chinese-speaking patients, an increase in spiritual wellbeing was associated with improved illness perception across all domains except for consequences and emotional representation. However, no significant association was observed for Arabic patients. Differences in illness perceptions exist among CALD and Anglo-Australians. Spiritual wellbeing appears linked to more favourable perceptions; however, differential effects emerged among groups, emphasizing the need for culturally tailored interventions to improve outcomes.

Predictive Modeling in IoT-Driven Agriculture: A Comparative Study of Regression and Classification with LIME Interpretability

Abstract. This study aims to compare the performance of regression and classification machine learning models in crop prediction by analyzing data from IoT-driven agriculture. Linear regression and random forest regression models were used to predict the percentage of root growth dry matter, while logistic regression and support vector machines were employed to classify crop production regions. To enhance model interpretability, the LIME tool was applied to analyze feature importance. The experimental results demonstrate that the models perform well in terms of prediction accuracy, and LIME provided clear feature explanations, helping identify the variables with the greatest impact on prediction outcomes. This research offers data-driven insights for optimizing resource management in smart agricultural systems.

Optimisation of dry sliding wear characterisation of as-cast and T6 treated hypereutectic aluminium alloy (AlSiCuCe) by Taguchi technique

ABSTRACT To find the optimum levels of controlling and dominating factors on the wear behaviour and COF of as-cast and T6-heat-treated Al.18Si.3.6Cu.0.34Ce composites, the Taguchi technique was applied. A pin-on-disc setup was used for the wear study by considering the controlling variables like speed(m/s) and load(N) at four levels. An analysis of variance was performed to identify the controlling process parameters and their influence on the objective function. From ANOVA analyses of wear, based on the S/N ratio, the load dominates both the VWR and temperature, while the frictional force is influenced by the speed. Linear regression models are developed and are used for confirmation tests. A good agreement was found between the experimental and predicted values, and the error is within 10%.

Starch intake and caries increment: A longitudinal study in Finnish adults.

To evaluate whether changes in starch intake (in terms of amount and food sources) were associated with increments in dental caries among adults. 11-year longitudinal study (2000-2011) with duplicate assessments for all variables. A 128-item food frequency questionnaire was used to estimate intake of starch (g/day) and six starch-rich food groups (potatoes, potato products, roots and tubers, pasta, wholegrains, and legumes). Dental caries was assessed through clinical examinations and summarised using the number of decayed, missing and filled teeth (DMFT score). The relationship between quintiles of starch intake and DMFT score was tested in linear hybrid models adjusting for confounders. Northern and Southern regions of Finland. 922 adults, aged 30-88 years. Mean starch intake was 127.6 (SD: 47.8) g/day at baseline and 120.7 (55.8) g/day at follow-up. Mean DMFT score was 21.7 (6.4) and 22.4 (6.2) at baseline and follow-up. Starch intake was inversely associated with DMFT score cross-sectionally (rate ratio for highest versus lowest quintile of intake: -2.73, 95%CI: -4.64, -0.82) but not longitudinally (0.32, 95%CI: -0.12, 0.76). By food sources, the intakes of pasta (-2.77, 95%CI: -4.21, -1.32) and wholegrains (-1.91, 95%CI: -3.38, -0.45) were negatively associated with DMFT score cross-sectionally but not longitudinally (0.03, 95%CI: -0.33, 0.39 and -0.10, 95%CI: -0.44, 0.24, respectively). Changes in the amount and sources of starch intake were not associated with changes in dental caries. Further studies should be conducted in different settings and age groups while focusing on starch digestibility and specific sources of starch.

The Approaches to Predict Stock Prices by Random Forest

Abstract. People are always curious about how to predict the stock prices, various type of prediction tools are introduced to help people explore the trend of the stock price movement. With the development of the machine learning, there are more and more models and methods that we can use to predict the stock prices, while Random Forest, a typical machine learning algorithm, will be discussed in this article to examine its performance in the stock market. The data utilized in this study is sourced from Yahoo Finance, with several additional indicators computed and incorporated into feature set of the Random Forest model. To evaluate its performance, a comparison between the Random Forest model and the simple linear regression model is going to be conducted, which is a considerably basic model and serves as a benchmark for the minimum returns individuals can expect. The RMSE and MAPE will be compared firstly, which can help us assess which model demonstrates superior predictive accuracy, while the ROI derived from the strategy based on these models predictions will serve as a measure of their practical performance in the stock market. Collectively, this data will substantiate that Random Forest is indeed an effective model that is capable of assisting individuals in achieving greater profits.

Physical Activity Declines over a 12-Month Period in Parkinson's Disease: Considerations for Longitudinal Activity Monitoring.

The purpose of this project was to evaluate trends in daily steps in individuals with Parkinson's disease (PD) over a 12-month period using continuous activity monitoring. Environmental (temperature) and cultural factors (represented by day of the week) were evaluated as potential external sources of variability. It was hypothesized that participants daily step counts would decline over the course of 12 months. Further, it was hypothesized that participants would take more steps on warmer days and that the day of the week would have minimal impact on step count as many participants were no longer in the workforce. Participants were part of the Usual and Customary Care arm (N = 119) of the CYClical Lower Extremity Exercise Trial for Parkinson's disease - II (CYCLE-II) at the Cleveland Clinic and University of Utah. Participants wore a Garmin Vivofit4® device daily for 12-months. A linear mixed effects model was created to model daily steps over 12-months. Participants wore their activity monitors 93% of study days. Steps per day declined by 6.1% over 12 months (95% CI 12.6% decline, 0.9% increase, p = 0.09). Steps per day were greater with warmer temperatures (p < 0.001), plateauing and declining around 75-85 degrees Fahrenheit (24-29 degrees Celsius). Participants took fewer steps on Sundays; this difference was more pronounced for Utah participants, who took 25% fewer steps on Sundays compared to other weekdays (p < 0.001). Most individuals live with PD for decades, and interventions should address the expected decline of 6% in daily step count. Environmental and cultural factors impact daily step count and should be adjusted for in short- and long-term monitoring of physical activity in individuals with PD.

The green marine waste collector routing optimization with puma selectison-based neighborhood search algorithm

AbstractImproper waste disposal by humans has created significant environmental issues in the marine ecosystem, including endangering aquatic life and accelerating the extinction of certain marine species. Due to the floating nature of the marine debris, the coordinates for collecting activities must be estimated in advance. In this article, GNOME software is used to estimate the coordinates of debris, and then a fleet of several ships is used to collect them. Also, a mixed integer linear programming model is presented for the routing optimization of debris collection fleets. The proposed optimization model formulates the objective function based on numerous factors, including labor cost, rent, and ship insurance, and considers constraints on fuel tank capacity, the time window, and the ship’s cargo capacity. A new hybrid algorithm combining the Puma algorithm and neighborhood search is proposed to address the problem. Metropolis acceptance is used in the simulated annealing algorithm to avoid the local optima and greedy selection. Numerical examples of the marine survey and the port of Rotterdam are used to test the proposed approach, which has been proven effective in several scenarios. Results achieved from the proposed hybrid method demonstrate considerable performance improvement in solving the problem. This approach has decreased total fuel and labor costs by 10–15% compared to conventional methods, with minimized time window violation reaching 25%. These results show a significant reduction in total operational costs with proper scheduling and route planning.

Elevated serum interferon-α2 associates with activity and flare risk in Juvenile-onset Systemic Lupus Erythematosus.

This study investigated serum IFN-α2 as a putative marker of disease activity and predictor of disease flares in juvenile systemic lupus erythematosus (jSLE). 222 serum samples were analysed, including 28 healthy controls (HCs), 88 JSLE (159 samples), and 35 juvenile idiopathic arthritis (JIA) patients. IFN-α2 levels were determined using Single-molecule array (Simoa). Cross-sectionally, median IFN-α2 levels were compared between patient groups and disease activity state sub-groups. Time to flare was analysed by linear regression. Longitudinally, the ability of the IFN-α2 and other traditional biomarkers (erythrocyte sedimentation rate/ESR, low C3 and anti-dsDNA antibodies) to detect and predict flares was assessed via a generalised linear mixed model. Cross-sectional analysis showed higher median IFN-α2 levels in the active/intermediate group (median 3,185 fg/mL, IQR 48-13,703) compared to the LDAS (571 fg/mL, IQR 57-1,310 fg/mL, p = 0.04) and remission sub-groups (271 fg/mL, IQR 3-56, p < 0.001). IFN-α2 was higher in all JSLE patients (median 587 fg/mL, IQR 11-2,774) as compared to JIA patients (median 7 fg/mL, IQR 3-236, p = 0.0017) and HCs (p = 0.017). JSLE patients in remission or LDAS with abnormal IFN-α2 levels had a shorter time to flare over the subsequent six months compared to those with normal IFN-α2 levels (p = 0.022). Longitudinally, multivariable analysis demonstrated high IFN-α2 to be the only predictor of an ongoing flare (p = 0.028). Serum IFN-α2 levels associate with disease activity and can predict ongoing and future flares in jSLE. These findings suggest that quantification of IFN-α2 may support risk stratification and disease monitoring in these patients.