Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Employment in Later Life: How Future Time Perspective and Social Support Influence Self-Employment Interest

For older workers, self-employment is an important alternative to waged employment. Drawing on social learning theory and social cognitive career theory we examine how attitudes toward one’s own aging, future time perspective (captured by perceived time left to live) and perceived support from referent individuals predict self-efficacy for entrepreneurship and outcome expectations, influencing self-employment interest. Findings from a sample of professional association members (n = 174, mean age 52.5 years), revealed that an open-ended time perspective relates positively to entrepreneurial self-efficacy, while social support relates positively to outcome expectations. Consistent with social cognitive career theory, entrepreneurial self-efficacy mediated the relationship between future time perspective and interest in self-employment, and outcome expectations mediated the relationship between social support and interest in self-employment. This study extends current career and entrepreneurship theory in several ways. First, the inclusion of age-related psychosocial and sociocultural factors in the study model shed light on the intersection between older age, the contextual environment and development of self-employment interest. Second, the findings support earlier arguments that older entrepreneurship is a social process whereby the social context in which people work and live influences their interest in entrepreneurship, and that entrepreneurial behavior among older people needs to be supported to occur. Finally, the findings suggest the utility of social cognitive career theory in informing the development of self-employment interest in the late career stage. We discuss implications for the career and entrepreneurship literatures as well as practitioners involved in late-career counseling or seeking to promote entrepreneurship for older people.
On a problem of Chowla and some related problems

Let d(m) denote the number of divisors of the integer m. Chowla has conjectured that the integers for which d(m + 1) > d(m) have density ½. In this paper I prove and generalize this conjecture. I prove in § 1 a corresponding result for a general class of functions f(m), and in § 2 the result for d(m) which is not included among the f(m). I employ the method used in my paper: “On the density of some sequences of numbers. ”
Pak1 Kinase Promotes Activated T Cell Trafficking by Regulating the Expression of L-Selectin and CCR7

Normal function of the adaptive immune system requires trafficking of T cells between the blood and lymphoid organs. Lymphocyte homing to lymph nodes requires that they cross endothelial barriers present in blood vessels and lymphatics. This multi-step process requires a remodeling of the lymphocyte plasma membrane, which is mediated by the dynamic re-arrangement of the actin cytoskeleton. Pak1 plays a central role in cell morphology, adhesion and migration in various cell types. Here we demonstrate that Pak1 is required for activated CD4+ T cell trafficking to lymph nodes. Pak1 deficiency in T cells causes a defect in the transcription of CCR7 and L-selectin, thereby altering lymphocyte trafficking. Additionally, we report an increase in L-selectin shedding in Pak1-deficient T cells, which correlates with a decrease in the recruitment of calmodulin to the cytoplasmic tail of L-selectin during T cell activation. Overall, our findings demonstrate that by regulating the expression of two major lymph node homing molecules, L-selectin and CCR7, Pak1 mediates activated CD4+ T cell trafficking.
Prolonged Sitting, Its Combination With Physical Inactivity and Incidence of Lung Cancer: Prospective Data From the HUNT Study

Background: Prolonged sitting as a major sedentary behavior potentially contributes to illness, but its relation with lung cancer risk is unclear. Prolonged sitting can be presented in physically active or inactive individuals. Those who are extendedly seated and also physically inactive may represent the most sedentary people. We therefore aimed to prospectively examine if total sitting time daily itself or in combination with physical activity is associated with lung cancer incidence overall and histologic types. Methods: We included 45,810 cancer-free adults who participated in the second survey of HUNT Study in Norway (1995–97), with a median follow-up of 18.3 years. Total sitting time daily and physical activity were self-reported at baseline. Lung cancer cases were ascertained from the Cancer Registry of Norway. Cox regression was used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). Results: In total, 549 participants developed lung cancer during the follow-up. Total sitting time daily was not associated with the incidence of lung cancer overall and histologic subtypes. Compared with participants sitting < 8 h daily and being physically active, those sitting ≥8 h daily (prolonged sitting) and being physically inactive had an increased incidence of lung cancer (overall: adjusted HR = 1.44, 95% CI: 1.07–1.94; small cell lung cancer: adjusted HR = 2.58, 95% CI: 1.23–5.41). Prolonged sitting only or physical inactivity only was not associated with the incidence of lung cancer. Conclusions: Our study suggested that prolonged sitting was not independently associated with lung cancer incidence. The combination of prolonged sitting and physical inactivity might increase the risk of lung cancer. However, residual confounding by smoking cannot be excluded completely even though smoking was adjusted for with detailed information.
Decreased Response to Positive Facial Affect in a Depressed Cohort in the Dorsal Striatum During a Working Memory Task—A Preliminary fMRI Study

People with depression have shown alterations in processing emotional information and working memory functionality. There is some evidence that emotional content may interact with working memory update processes, however neurological correlates are current unknown. In this preliminary study we utilized a novel version of the emotional variant of the n-back working memory task in fMRI. We examined BOLD response of 14 healthy controls and 13 depressed participants in response to happy, sad, and neutral displays of facial affect. No accuracy or reaction time differences were found between the two groups. The depressed group showed significantly decreased BOLD response to happy faces compared to the control group areas of the dorsal striatum and anterior cingulate. Significant, moderate, positive associations were found between right caudate activation with anxiety score and anterior cingulate activation with depression score in those with depression. Our novel task was able to elicit group level differences in emotional processing during working memory update. These results suggest those with depression fail to differentiate between positive emotional stimuli and stimuli with no emotional content.
Using network analysis to study globalization, regionalization, and multi-polarity—Introduction to special section

Abstract In this introduction to the special section on globalization, regionalization, and multi-polarity, we review network analysis applications to the study of globalization as a complex and multi-dimensional phenomenon and we explore the frontiers of our knowledge about the network properties of global systems. We focus on the global economic (trade and investment), political, and migration systems.
What Color Is Your Anger? Assessing Color-Emotion Pairings in English Speakers

Do English-speakers think about anger as “red” and sadness as “blue”? Some theories of emotion suggests that color(s)—like other biologically-derived signals- should be reliably paired with an emotion, and that colors should differentiate across emotions. We assessed consistency and specificity for color-emotion pairings among English-speaking adults. In study 1, participants (n = 73) completed an online survey in which they could select up to three colors from 23 colored swatches (varying hue, saturation, and light) for each of ten emotion words. In study 2, different participants (n = 52) completed a similar online survey except that we added additional emotions and colors (which better sampled color space). Participants in both studies indicated the strength of the relationship between a selected color(s) and the emotion. In study 1, four of the ten emotions showed consistency, and about one-third of the colors showed specificity, yet agreement was low-to-moderate among raters even in these cases. When we resampled our data, however, none of these effects were likely to replicate with statistical confidence. In study 2, only two of 20 emotions showed consistency, and three colors showed specificity. As with the first study, no color-emotion pairings were both specific and consistent. In addition, in study 2, we found that saturation and lightness, and to a lesser extent hue, predicted color-emotion agreement rather than perceived color. The results suggest that previous studies which report emotion-color pairings are likely best thought of experiment-specific. The results are discussed with respect to constructionist theories of emotion.
The Diversity of Tone Languages and the Roles of Pitch Variation in Non-tone Languages: Considerations for Tone Perception Research

All languages employ consonants and vowels as discrete contrastive subcomponents of the basic timing units of words (syllables). These two classes of phonemes are used to differentiate between words, whosemeanings can be categorically changed by switching even a single vowel or consonant, as in <pat> vs. <cat> or <pet>. They populate the lowest level of the phonological hierarchy, the segmental tier, and both classes are obligatory across spoken languages. But only some languages also make use of lexical tones, contrastive sub-syllabic fundamental frequency (pitch) variations referred to as tonemes (e.g., Jones, 1944), which for those languages comprise a third class of phonemic elements. Perceptual researchers often assume tones to be suprasegmental (e.g., So and Best, 2010, 2011, 2014; Liu et al., 2018; Poltrock et al., 2018), i.e., to extend across the consonants and vowels of the target syllable. While in a phonetic sense tones extend across the voiced segments of a syllable, however, such observations may not straightforwardly reflect the more abstract phonological properties of tones (e.g., see Wang, 1967; Hyman, 2011a,b). Indeed, several tone phonologists claim that lexical tones function as segments in tone languages (e.g., Lin, 1989; Duanmu, 1990, 1994). For the following paragraphs we adopt that phonological view that lexical tones function in tone languages at the segmental level, along with consonants and vowels. However, we return later to consider their phonological status and its relevance for understanding lexical tone perception by native and non-native listeners. Unlike consonants and vowels, lexical tones are optional1. Many languages of Europe, the Americas, Oceania, Africa and even Asia function perfectly well without them. But lexical tones are, nevertheless, a popular option. They are employed in 60–70% of existing languages (Yip, 2002), including many Asian, African and indigenous American languages as well as a few European and South Pacific languages (Maddieson, 2013). It is important to note, nonetheless, that lexical tone
DEBE feedback for large lecture classroom analytics

Learning Analytics (LA) research has demonstrated the potential of LA in detecting and monitoring cognitive-affective parameters and improving student success. But most of it has been applied to online and computerized learning environments whereas physical classrooms have largely remained outside the scope of such research. This paper attempts to bridge that gap by proposing a student feedback model in which they report on the difficult/easy and engaging/boring aspects of their lecture. We outline the pedagogical affordances of an aggregated time-series of such data and discuss it within the context of LA research.
A Passivity-Based Approach to Nash Equilibrium Seeking Over Networks

In this paper, we consider the problem of distributed Nash equilibrium (NE) seeking over networks, a setting in which players have limited local information on the others’ decisions. We start from a continuous-time gradient-play dynamics that converges to an NE under strict monotonicity of the pseudogradient and assumes perfect information. We consider how to modify it in the case of partial, or networked information between players. We propose an augmented gradient-play dynamics with correction, in which players communicate locally only with their neighbors to compute an estimate of the other players’ actions. We derive the new dynamics based on the reformulation as a multiagent coordination problem over an undirected graph. We exploit incremental passivity properties and show that a synchronizing, distributed Laplacian feedback can be designed using relative estimates of the neighbors. Under a strict monotonicity property of the pseudogradient, we show that the augmented gradient-play dynamics converges to consensus on the NE of the game. We further discuss two cases that highlight the tradeoff between properties of the game and the communication graph.
Regional Stabilization for Discrete Time-Delay Systems With Actuator Saturations via A Delay-Dependent Polytopic Approach

This paper is concerned with the regional stabilization problem for discrete time-delay systems with actuator saturations. Different from some existing delay-independent techniques handling the saturation nonlinearity, a delay-dependent polytopic approach is first proposed in a discrete-time framework. Then, by combining with an augmented Lyapunov function, a discrete Wirtinger-based inequality and some novel analysis techniques, improved delay-dependent regional stabilization conditions are established by means of linear matrix inequalities. Finally, it is shown via two numerical examples that the obtained results are less conservative than some existing ones yet providing a larger estimate of an initial condition set.
Characterization of a Ducted Rotor Brushless Doubly Fed Reluctance Machine

This paper investigates different operating points of a ducted rotor brushless doubly fed reluctance machine (BDFRM) in subsynchronous, synchronous, and supersynchronous speed regions. The BDFRM has a ducted rotor and its stator houses two three-phase distributed windings. An example design of the machine is proposed for investigation. A control approach to maximize the torque capability of the given design is introduced. The static structural analysis result of the machine is also presented, which led to the final manufacturing of the machine laminations. Machine assembly and drive implementation steps are discussed. The built machine is experimentally tested in different speed regions.
Disentangling Environmental Drivers of Phytoplankton Biomass off Western Iberia

Phytoplankton are the main primary producers in marine ecosystems, supporting important food webs. They are recognized as important indicators of environmental changes in oceans and coastal waters. Ocean colour remote sensing has been extensively used to study phytoplankton throughout the world, yet there is still much to understand in terms of what influences phytoplankton variability at regional scales. The main aim of this study was to investigate the drivers of phytoplankton variability in the Western Iberian Coast (WIC), for the period 1998-2016. Satellite chlorophyll a (CHL) data was acquired from the Copernicus Marine Environment Monitoring Service (CMEMS). A positive annual trend of CHL was observed at the northern coastal WIC, near Galicia, and a negative trend was observed in southern areas, near the Gulf of Cadiz. An empirical Orthogonal Function (EOF) analysis was implemented to identify regions with similar patterns of CHL variability. Six regions were obtained. A set of climate indices, satellite and model variables were then used as environmental predictors in Generalized Additive Models (GAMs) that explained between 18.0 to 49.3% of the total variance of CHL anomalies calculated from a detrended and deseasoned dataset. In the northern oceanic region positive anomalies were linked to high North Atlantic Oscillation (NAO) values and negative anomalies to high mixed layer depths. In the southern oceanic region, positive CHL anomalies were found to be associated with high concentrations of nitrogen, that may indicate nitrogen limitation. Phytoplankton in coastal areas were found to respond to basin-wide (e.g. Atlantic Multidecadal Oscillation-AMO) and coastal processes (e.g. upwelling and continental runoff), yielding positive anomalies with low salinity values. In very small coastal areas near major rivers, such as Douro and Guadalquivir, the positive response of phytoplankton to increased nitrogen concentrations and decreased salinity was evident. Considering the changes in climate expected for this region, related to the decrease in precipitation and increase in summer temperatures, as well as some apparent weakening of upwelling, possible significant impacts on the phytoplankton community can be anticipated. These results are therefore also relevant for environmental management, especially in the context of the European Marine Strategy Framework Directive (MSFD).
SAR Target Image Classification Based on Transfer Learning and Model Compression

When convolutional neural networks (CNNs) are applied to the synthetic aperture radar (SAR) image classification, they are prone to overfitting due to scarce SAR image data, and CNNs require a large amount of storage and long computing time, so it is difficult to deploy them on resource constrained devices. This letter proposes a simple and feasible approach that can effectively solve these problems. First, the convolutional layers of the pretrained model on the ImageNet data set are transferred, and a new convolutional layer and global pooling layer are added afterward. Then, fine-tuning is performed on the new network from the SAR image data set. Finally, a filter-based pruning method is used on the convolutional layers to obtain a compact network. Compared with the all-convolutional network (A-ConvNets) which is the state-of-the-art method on the moving and stationary target acquisition and recognition data set, our method achieves about <inline-formula> <tex-math notation="LaTeX">$3.6\times $ </tex-math></inline-formula> speedup during forward propagation and <inline-formula> <tex-math notation="LaTeX">$3.7\times $ </tex-math></inline-formula> compression of the parameters, with only a 1.42% decrease in the accuracy.
High Step-Up DC–DC Converter With Active Switched LC-Network for Photovoltaic Systems

A high step-up DC–DC converter with active switched LC-network is proposed in this paper, which can be used in the photovoltaic system as the front-end stage to generate the required DC bus voltage. Based on the transformerless DC–DC converter with an active switched inductor (ASL) network, this proposed converter introduces an active switched capacitor (ASC) network, where only one capacitor and one diode are added, while the voltage gain is efficiently increased by a compound of ASL and ASC networks. The structure of the proposed converter is simple and voltage stresses on the additional diode and capacitor are low. In addition, unlike other voltage-boosting structures that utilized switched capacitor, the proposed converter avoids the extreme instantaneous currents of capacitor. The detailed analysis of the proposed converter and performance comparison with recently published ASL network-based converters are presented. Finally, a 100 W, 20/200 V prototype circuit is operated to verify its performance.
Couples Dealing With Pediatric Blood Cancer: A Study on the Role of Dyadic Coping

Objective: Pediatric cancer is a life-threatening disease that poses significant challenges to the ill child and his/her parents. Among the studies investigating risk and protective factors for the individual and relationship adjustment of parents being confronted with pediatric cancer, couple factors – such as dyadic coping – gained little research attention. Therefore, the aim of the current study was to explore the association between dyadic coping and individual/relationship outcomes of parents in the context of pediatric cancer. Methods: Participants were 59 couples of children diagnosed with leukemia or Non-Hodgkin lymphoma. Time since diagnosis varied from diagnosis to 20 months. Both parents completed the DCI-short, DASS21, PIP, and MMQ. Results: Positive dyadic coping (i.e., supportive and common dyadic coping) and negative dyadic coping proved to be related to individual and relational outcomes of parents facing cancer in their child. In addition, while men and women reported to be equally satisfied with their partner and their sexual relationship, women reported higher levels of individual maladjustment. Conclusion: Our findings led to the conclusion that dyadic coping is important for both individual as well as relationship outcomes of parents when facing a diagnosis of cancer in their child. When meeting with families, both partners should be invited as a unit in order to best capture couple level experiences. Also, clinicians should be sensitive to relational and sexual issues besides individual issues, taking into account evidence-based standards for psychosocial care in pediatric oncology.
Computer-Based Executive Function Training for Combat Veterans With PTSD: A Pilot Clinical Trial Assessing Feasibility and Predictors of Dropout

Background: While evidence-based PTSD treatments are often efficacious, 20–50% of individuals continue to experience significant symptoms following treatment. Further, these treatments do not directly target associated neuropsychological deficits. Here, we describe the methods and feasibility for computer-based executive function training (EFT), a potential alternative or adjunctive PTSD treatment. Methods: Male combat veterans with full or partial PTSD (n = 20) and combat-exposed controls (used for normative comparison; n = 20) completed clinical, neuropsychological and functional neuroimaging assessments. Those with PTSD were assigned to EFT (n = 13) or placebo training (word games; n = 7) at home for 6 weeks, followed by repeat assessment. Baseline predictors of treatment completion were explored using logistic regressions. Individual feedback and changes in clinical symptoms, neuropsychological function, and neural activation patterns are described. Results: Dropout rates for EFT and placebo training were 38.5 and 57.1%, respectively. Baseline clinical severity and brain activation (i.e., prefrontal-insula-amygdala networks) during an emotional anticipation task were predictive of treatment completion. Decreases in clinical symptoms were observed following treatment in both groups. EFT participants improved on training tasks but not on traditional neuropsychological assessments. All training completers indicated liking EFT, and indicated they would engage in EFT (alone or as adjunctive treatment) if offered. Conclusion: Results provide an initial framework to explore the feasibility of placebo-controlled, computerized, home-based executive function training (EFT) on psychological and neuropsychological function and brain activation in combat veterans with PTSD. Clinical severity and neural reactivity to emotional stimuli may indicate which veterans will complete home-based computerized interventions. While EFT may serve as a potential alternative or adjunctive PTSD treatment, further research is warranted to address compliance and determine whether EFT may benefit functioning above and beyond placebo interventions.