linear models
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2022 ◽  
Vol 217 ◽  
pp. 188-203
Fanrong Zhao ◽  
Nan Lin ◽  
Wenjuan Hu ◽  
Baoxue Zhang

Anderson G. Costa ◽  
Eudócio R. O. da Silva ◽  
Murilo M. de Barros ◽  
Jonatthan A. Fagundes

ABSTRACT The quality and price of coffee drinks can be affected by contamination with impurities during roasting and grinding. Methods that enable quality control of marketed products are important to meet the standards required by consumers and the industry. The purpose of this study was to estimate the percentage of impurities contained in coffee using textural and colorimetric descriptors obtained from digital images. Arabica coffee beans (Coffea arabica L.) at 100% purity were subjected to roasting and grinding processes, and the initially pure ground coffee was gradually contaminated with impurities. Digital images were collected from coffee samples with 0, 10, 30, 50, and 70% impurities. From the images, textural descriptors of the histograms (mean, standard deviation, entropy, uniformity, and third moment) and colorimetric descriptors (RGB color space and HSI color space) were obtained. The principal component regression (PCR) method was applied to the data group of textural and colorimetric descriptors for the development of linear models to estimate coffee impurities. The selected models for the textural descriptors data group and the colorimetric descriptors data group were composed of two and three principal components, respectively. The model from the colorimetric descriptors showed a greater capacity to estimate the percentage of impurities in coffee when compared to the model from the textural descriptors.

D. Liliana González-Hernández ◽  
Raúl A. Aguirre-Gamboa ◽  
Erik W. Meijles

AbstractManaging and reducing the impacts of climate change depends on efficient actions from all societal scales. Yet, the household component is often missing from climate research, debate, and policies. This is problematic because households have been found to significantly contribute to of global greenhouse gas emissions and therefore have the potential to be part of a solution to climate change by mitigating climate change. This study seeks to understand which factors drive household-level mitigation actions. We conducted a household survey in Nuevo Leon, located in northeastern Mexico, to explore the extent to which climate change perceptions and the sociodemographic characteristics of households influence their reported mitigation performances and their perceived mitigation efforts. Results from linear regression analyses and generalized linear models revealed that sociodemographic characteristics are key drivers of the households’ perceived mitigation efforts and reported mitigation performances and. We also found that climate change perceptions drive a household’s efforts to mitigate climate change. These results could partly explain why despite the efforts households take to mitigate climate change, achieving an effective reduction of greenhouse gas emissions is challenging without further access to resources such as education and financial support. If governments intend to realize substantial reductions in future emission pathways, then household-level mitigation should be addressed with proper support.

2022 ◽  
Rachel Knight ◽  
Marc Patrick Bennett ◽  
Darren Lee Dunning ◽  
Alan Archer-Boyd ◽  
Sarah-Jayne Blakemore ◽  

Introduction. Decentering describes the ability to voluntarily adopt an objective self-perspective from which to notice internal, typically distressing, stressors (e.g. difficult thoughts, memories, and feelings). The reinforcement of this skill may be an active ingredient through which different psychological interventions accrue reductions in anxiety and/or depression. However, it is unclear if decentering can be selectively trained at a young age and if this might reduce psychological distress. The aim of the current trial is to address this research gap. Methods and analysis. Adolescents, recruited from partnering schools in the UK and the EU (n = 48 per group, age range = 16-19 years), will be randomised to complete of five-weeks of decentering training, or form an active control group that will take part in in light physical exercise and cognitive training. The co-primary training outcomes include a self-reported decentering inventory (i.e. the Experiences Questionnaire) and the momentary use of decentering in response to psychological stressors, using experience sampling. The secondary mental health outcomes will include self-reported inventories of depression and anxiety symptoms, as well as psychological wellbeing. The initial statistical analysis will use mixed-model analysis of variance (ANOVA) to estimate the effect of training condition on self-rated inventories across three timepoints: baseline, mid-intervention and post-intervention. Additionally, experience sampling data will be initially interrogated using hierarchical linear models. Ethics and dissemination. This study was approved by the Cambridge Psychology Research Ethics Committee, University of Cambridge (PRE.2019.109). Findings will be disseminated through typical academic routes including poster/paper presentations at (intern)-national conferences, academic institutes and through publication in peer-reviewed journals.

Viktor Holubec ◽  
Artem Ryabov ◽  
Sarah A. M. Loos ◽  
Klaus Kroy

Abstract Stochastic processes with temporal delay play an important role in science and engineering whenever finite speeds of signal transmission and processing occur. However, an exact mathematical analysis of their dynamics and thermodynamics is available for linear models only. We introduce a class of stochastic delay processes with nonlinear time-local forces and linear time-delayed forces that obey fluctuation theorems and converge to a Boltzmann equilibrium at long times. From the point of view of control theory, such ``equilibrium stochastic delay processes'' are stable and energetically passive, by construction. Computationally, they provide diverse exact constraints on general nonlinear stochastic delay problems and can, in various situations, serve as a starting point for their perturbative analysis. Physically, they admit an interpretation in terms of an underdamped Brownian particle that is either subjected to a time-local force in a non-Markovian thermal bath or to a delayed feedback force in a Markovian thermal bath. We illustrate these properties numerically for a setup familiar from feedback cooling and point out experimental implications.

2022 ◽  
Vol 17 (s1) ◽  
Yucheng Wang ◽  
Thomas C. Tsai ◽  
Dustin Duncan ◽  
John Ji

With people restricted to their residences, neighbourhood characteristics may affect behaviour and risk of coronavirus disease 2019 (COVID-19) infection. We aimed to analyse whether neighbourhoods with higher walkability, public transit, biking services and higher socio-economic status were associated with lower COVID-19 infection during the peak of the COVID-19 pandemic in Massachusetts. We used Walk Score®, Bike Score®, and Transit Score® indices to assess the walkability and transportation of 72 cities in Massachusetts, USA based on availability of data and collected the total COVID-19 case numbers of each city up to 10 April 2021. We used univariate and multivariate linear models to analyse the effects of these scores on COVID-19 cases per 100,000 in each city, adjusting for demographic covariates and all covariates, respectively. In the 72 cities studied, the average Walk Score, Transit Score and Bike Score was 48.7, 36.5 and 44.1, respectively, with a total of 426,182 COVID-19 cases. Higher Walk Score, Transit Score, and Bike Score rankings were negatively associated with COVID-19 cases per 100,000 persons (<0.05). Cities with a higher proportion of Hispanic population and a lower median household income were associated with more COVID-19 cases per 100,000 (P<0.05). Higher Walk Score, Transit Score and Bike Score were shown to be protective against COVID-19 transmission, while socio-demographic factors were associated with COVID-19 infection. Understanding the complex relationship of how the structure of the urban environment may constrain commuting patterns for residents and essential workers during COVID-19 would offer potential insights on future pandemic preparedness and response.

PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0261953
Paula Zamorano ◽  
Paulina Muñoz ◽  
Manuel Espinoza ◽  
Alvaro Tellez ◽  
Teresita Varela ◽  

During recent years, multimorbidity has taken relevance because of the impact of causes in the system, people, and their families, which has been a priority in the health care plan. Interventions strategies and their implementation are still an emerging topic. In this context, Centro de Innovación en Salud ANCORA UC, together with Servicio de Salud Metropolitano Sur Oriente, implemented as a pilot study High-Risk Multimorbidity Integrated Care strategy. This study aimed to evaluate the impact of this strategy in terms of health services utilization and mortality. A cohort study was conducted with high-risk patients with multimorbidity, stratified by ACG®, intervened between April 2017 and December 2019. The studied population was 3,933 patients who belonged to similar size and location primary care centers. The impact analysis was performed used generalized linear models. Results showed that intervened patients had a significantly lower incidence in mortality (OR 0.56; 95% CI 0.40–0.77), hospital admissions, length of stay, and the number of hospital emergency consultancies. With the proper barriers and facilitators of a real context intervention, the implementation process allowed the systematization and consolidation of the intervention provided in this study. The training for new roles and the constant implementation support from the Centro de Innovación en Salud ANCORA UC team were essential in the progress and success of the intervention. A complete description of the high-risk intervention strategy is provided to contribute to this emerging topic and facilitate its scale-up. We can conclude that this complex intervention was feasible to be implemented in a real context. The Ministry of Health has taken the systematization and consolidation of the conditions for the national scale-up.

2022 ◽  
Emma Herms ◽  
Amanda Bolbecker ◽  
Krista Wisner

Empathic tendencies (i.e., perspective taking and empathic concern) and emotion regulation (i.e., reappraisal and suppression) are key factors in successful social relationships. Relationships can also be negatively impacted by mental health symptoms, including psychosis. While psychotic-like experiences are often detrimental to social functioning, it is unclear whether certain psychotic-like experiences, such as delusions, are negatively associated with empathetic tendencies after accounting for emotion regulation skills and comorbid dimensions of psychopathology. Linear models were employed to test these associations in an adult community sample (N = 128). Measures of interest included the Interpersonal Reactivity Index, Emotion Regulation Questionnaire, and the Peter’s Delusion Inventory. Results indicated that perspective taking was positively associated with reappraisal and negatively associated with delusional proneness, after controlling for age, sex, race, intelligence, as well as symptoms of anxiety and depression. Furthermore, a significant change in R2 supported the addition of delusion proneness in this model. Specificity analyses demonstrated perspective taking was also negatively associated with suppression, but this relationship did not remain after accounting for the effects of reappraisal and delusion proneness in the same model. Additional specificity analyses found no association between empathic concern and reappraisal or delusion proneness but replicated previous findings that empathic concern was negatively associated with suppression. Taken together, findings highlight that delusion proneness accounts for unique variance in interpersonal perspective taking, beyond that explained by demographics, intelligence, reappraisal skills, and internalizing psychopathology.

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