A cluster-based multiparametric similarity test for the compartmentalization of crystalline rocks into structural domains

Usually, fracture sampling studies comprise the collection of several fracture samples, which involve many fracture clusters. Grouping fracture samples into structural domains is generally useful for geologists, hydrogeologists, and geomechanicians as a region of fractured rocks is subdivided into sub-regions with similar behavior in terms of their hydromechanical properties. One of the common methods used for grouping fracture samples into structural domains considers the fracture orientation of clusters and ignores several fracture parameters, such as fracture spacing, aperture, and persistence, which are important for fluid circulation in the rock mass.In this study, we proposed a new cluster-based similarity method that considered the orientation of clusters as well as clusters’ aperture, persistence, and fracture spacing. Field investigations were conducted in the Grenville geological province of the Canadian Shield in the Lanaudière region, Quebec, Canada, where fractures were sampled from 30 outcrops and four boreholes. The proposed method is more suitable than other methods, and has applications in hydrogeology, rock mechanics, and especially in studies of fluid circulation in the rock mass. In addition, a method for the compartmentalization of a given study area into structural domains by means of Voronoi diagrams was also proposed.

Understanding User Perceptions of Proactive Smart Speakers

Voice assistants, such as Amazon's Alexa and Google Home, increasingly find their way into consumer homes. Their functionality, however, is currently limited to being passive answer machines rather than proactively engaging users in conversations. Speakers' proactivity would open up a range of important application scenarios, including health services, such as checking in on patient states and triggering medication reminders. It remains unclear how passive speakers should implement proactivity. To better understand user perceptions, we ran a 3-week field study with 13 participants where we modified the off-the-shelf Google Home to become proactive. During the study, our speaker proactively triggered conversations that were essentially Experience Sampling probes allowing us to identify when to engage users. Applying machine-learning, we are able to predict user responsiveness with a 71.6% accuracy and find predictive features. We also identify self-reported factors, such as boredom and mood, that are significantly correlated with users' perceived availability. Our prototype and findings inform the design of proactive speakers that verbally engage users at opportune moments and contribute to the design of proactive application scenarios and voice-based experience sampling studies.

Are Trait–State Fit and State–Situation Fit Informative of Within-Person Processes of Personality State Expression?

Choosing the right behavior can oftentimes be an act of balance between one’s own preferences or tendencies and momentary situational affordances. How do people navigate these potentially different requirements? One way would be to choose the behavior that makes one feel good. Specifically, we argue that fit between personality traits and personality states and fit between personality states and situation characteristics should be associated with positive affect. Thereby, fit may provide feedback to within-person processes of personality state expression. In two experience sampling studies (Study 1: N = 194, 4,244 observations; Study 2: N = 254, 7,667 observations), we employed moderated multilevel polynomial regressions and response surface analysis to examine whether trait–state fit and state–situation fit were associated with state affect. We found a consistent pattern of interactions between personality traits, personality states, and situation characteristics predicting state affect, but did not find evidence for the hypothesized trait–state fit patterns or state–situation fit patterns. These findings have two main implications. First, the results suggest that fit patterns are not involved in associations between personality traits, personality states, situation characteristics, and state affect. However, because theories proposing fit are often imprecise regarding the operationalization of fit, it is difficult to draw concrete conclusions about these theories. Second, the large number of interactions between personality traits, personality states, and situation characteristics suggests that these three constructs should be studied together. The specific role of these interactions for personality processes needs to be further determined in future research.

The Incremental Validity of Average States: A Replication and Extension of Finnigan and Vazire (2018)

States refer to our momentary thoughts, feelings, and behaviors. Average states (aggregates across multiple time points) are discussed as a more accurate and objective measure of personality compared to global self-reports since they do not only rely on people’s general beliefs about themselves. Specifically, Finnigan and Vazire (2018) argued that, if average states better capture what a person is actually like, this should be reflected in their unique association with informant-reports of personality, and tested this idea based on two experience-sampling studies. Their results showed, however, that average self-reported states did not predict global informant-reported personality above and beyond global self-reports. In this research, we aimed at replicating and extending these results. We used data of five studies (total N = 806) that involved global self- and informant-reports and employed a variety of different experience-sampling methods (time-based with different sampling schedules, event-based). Across all studies, the original results (i.e., no incremental effects of average self-reported states) were replicated. Furthermore, as an extension to the original study, we found that average other-reported states (provided by peers, results based on one study) did indeed predict global informant-reports above and beyond global self-reports. These findings highlight the importance of differentiating between method effects (global reports vs. average states) from source of information effects (self vs. other). We discuss these results, focusing on the suitability of using informant-reports as a criterion variable and conceptual differences between assessment methods.

Study of the Behavior of Air Parcels, using PIXE, Hysplit and Wind Rose in the Metropolitan Zone of Toluca Valley, Mexico

Aim: The objective of this work was to determine the behavior of the trajectories of the air plots in two sites (San Mateo Atenco-(SM) and San Lorenzo Tepaltitlán-(SL)), in the atmosphere of the Metropolitan Zone of the Toluca Valley (MZTV). Methodology: In the atmosphere of the MZTV, using HYSPLIT a Backward trajectory direction analysis was performed from June 29 to July 8, 2021, considering for each day the summertime schedules of the center, indicating its Coordinated Universal Time (UTC). An ANOVA analysis (with a significance level of α=0.05) was performed for the concentrations of SM and SL obtained with PIXE, with the objective of seeing the equality of their behavior. Results: The behavior of the direction of the trajectories of the air plots in both sites is similar and the trajectories for the same day are the same in both sites but different on another day; It was determined that during night-day (19 to 12 h of the following day) the behavior is similar and changes during the remaining time, being variable. In general, the origin of the trajectories of the air plots for both sites of the MZTV is predominantly from the southeast, a situation that was confirmed with Wind Roses. Of the ANOVA analysis, the p-value was in all cases greater than the significance level of 0.05, the null hypothesis was accept, and it is possible to conclude that the elemental chemical composition of PM2.5 have equal means in both sites. Conclusion: Among other, it is possible to consider the behavior of meteorological parameters and thus take them into account for sampling studies of criteria pollutants such as PM2.5.

Measuring motivational relationship processes in experience sampling: A reliability model for moments, days, and persons nested in couples

The investigation of within-person process models, often done in experience sampling designs, requires a reliable assessment of within-person change. In this paper, we focus on dyadic intensive longitudinal designs where both partners of a couple are assessed multiple times each day across several days. We introduce a statistical model for variance decomposition based on generalizability theory (extending P. E. Shrout & S. P. Lane, 2012), which can estimate the relative proportion of variability on four hierarchical levels: moments within a day, days, persons, and couples. Based on these variance estimates, four reliability coefficients are derived: between-couples, between-persons, within-persons/between-days, and within-persons/between-moments. We apply the model to two dyadic intensive experience sampling studies (n1 = 130 persons, 5 surveys each day for 14 days, ≥ 7508 unique surveys; n2 = 508 persons, 5 surveys each day for 28 days, ≥ 47764 unique surveys). Five different scales in the domain of motivational processes and relationship quality were assessed with 2 to 5 items: State relationship satisfaction, communal motivation, and agentic motivation; the latter consists of two subscales, namely power and independence motivation. Largest variance components were on the level of persons, moments, couples, and days, where within-day variance was generally larger than between-day variance. Reliabilities ranged from .32 to .76 (couple level), .93 to .98 (person level), .61 to .88 (day level), and .28 to .72 (moment level). Scale intercorrelations reveal differential structures between and within persons, which has consequences for theory building and statistical modeling.

Autonomy Matters: Experiential and Individual Differences in Chosen and Unchosen Solitary Activities From Three Experience Sampling Studies

Solitude––the absence of social interaction––can bring both positive and negative experiences. Drawing on self-determination theory, we conducted three experience sampling studies to investigate quality of experience and dispositions associated with activities varying on two dimensions––chosenness (chosen/unchosen) and social context (solitary/interactive). Participants (total N = 283) completed surveys 6–7 times each day over a 7-day period (total: 8,769 surveys). Multilevel modeling confirmed that participants reported the lowest quality momentary experiences when engaged in unchosen (vs. chosen) solitary activities. Further, individuals who spent more time on unchosen solitary activities reported lower meaning in life and satisfaction with life. Extraversion was positively associated with time spent on chosen interactive activities but negatively with chosen solitary activities. Post hoc analyses revealed that people low (vs. high) in extraversion reported lower productivity only during unchosen interactive activities. Chosen (vs. unchosen) solitary activities seem to have a relatively benign impact on quality of experience and well-being.

Instability of corticotropin during long-term storage – myth or reality?

Objectives Corticotropin is notorious for its instability. Whereas several studies have investigated its short-term stability in plasma following venous blood sampling, studies on long-term stability are lacking. Here we investigated the long-term storage stability of corticotropin in ethylenediaminetetraacetic acid containing plasma. Methods Specimens from healthy volunteers (neat, spiked) were stored in polypropylene microcentrifuge tubes with socket screw-caps at −20 °C and −70 °C for up to one and a half years. Corticotropin in plasma was measured using an Abbott research only immunoassay. Separately, specimens from patients were collected during diagnostic routine testing and stored in polystyrene tubes with push-caps at −20 °C for up to 6 years. In these samples corticotropin hormone was measured using the Diasorin corticotropin immunoassay. Results Storage of specimens at −20 °C or −70 °C for up to one and a half years showed minimal changes (<11%) in corticotropin levels, while storage of patient samples at −20 °C for up to 6 years showed a significant (54%) reduction in corticotropin levels. Conclusions Corticotropin levels are stable in plasma when stored at −20 °C for one and a half years using the Abbott research only assay, but with longer storage time a significant reduction in corticotropin levels can be expected. Once specimens are stored for future corticotropin measurements, one should consider storage time, storage temperature and assay differences.

Affect Dysregulation in Context: Implications and Future Directions of Experience Sampling Research on Affect Regulation Models of Loss of Control Eating

Loss of control eating is a core, transdiagnostic eating disorder symptom associated with psychological distress, functional impairment, and reduced quality of life. However, the factors that contribute to persistent loss of control eating despite negative consequences are not fully understood. Understanding the mechanisms that maintain loss of control eating is crucial to advance treatments that interrupt these processes. Affect regulation models of loss of control eating hypothesize that negative emotions trigger loss of control eating, and that loss of control eating is negatively reinforced because it temporarily decreases negative affect. Several variations on this basic affect regulation model have been proposed, including theories suggesting that negative affect decreases during loss of control eating rather than afterwards (escape theory), and that loss of control eating replaces one negative emotion with another that is less aversive (trade-off theory). Experience sampling designs that measure negative affect and eating behavior multiple times per day are optimally suited to examining the nuanced predictions of these affect regulation models in people's everyday lives. This paper critically reviews experience sampling studies examining associations between negative affect and loss of control eating, and discusses the implications for different affect regulation models of loss of control eating. The review concludes by proposing an expanded affect-focused model of loss of control eating that incorporates trait-level individual differences and momentary biological and environmental variables to guide future research. Clinical implications and recommendations are discussed.

Inverse heavy enzyme isotope effects in methylthioadenosine nucleosidases

Heavy enzyme isotope effects occur in proteins substituted with 2H-, 13C-, and 15N-enriched amino acids. Mass alterations perturb femtosecond protein motions and have been used to study the linkage between fast motions and transition-state barrier crossing. Heavy enzymes typically show slower rates for their chemical steps. Heavy bacterial methylthioadenosine nucleosidases (MTANs from Helicobactor pylori and Escherichia coli) gave normal isotope effects in steady-state kinetics, with slower rates for the heavy enzymes. However, both enzymes revealed rare inverse isotope effects on their chemical steps, with faster chemical steps in the heavy enzymes. Computational transition-path sampling studies of H. pylori and E. coli MTANs indicated closer enzyme–reactant interactions in the heavy MTANs at times near the transition state, resulting in an improved reaction coordinate geometry. Specific catalytic interactions more favorable for heavy MTANs include improved contacts to the catalytic water nucleophile and to the adenine leaving group. Heavy bacterial MTANs depart from other heavy enzymes as slowed vibrational modes from the heavy isotope substitution caused improved barrier-crossing efficiency. Improved sampling frequency and reactant coordinate distances are highlighted as key factors in MTAN transition-state stabilization.