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Successfully adjusting to retirement represents a major challenge for many older workers. Following the temporal unfolding of retirement process (i.e., preretirement, transition, and postretirement phases), the present study draws on the resource-based dynamic model of retirement adjustment to investigate how a diverse set of preretirement personal resources (i.e., physical health, mental health, financial well-being, family support, proactive personality, and general cognitive ability) impact postretirement change trajectory of life satisfaction through the pathway of retirement transition experience (i.e., retirees' subjective experience in terms of how well they are adjusting during the transition phase of retirement immediately after the workforce exit). Using multiwave longitudinal data from 667 Chinese older workers transitioning into retirement collected with a prospective design over 2 years, we found positive effects of the levels of preretirement mental health, financial well-being, family support, proactive personality, and cognitive ability on retirement transition experience. We also found positive effects of the changes in physical health, financial well-being, and family support on retirement transition experience. Retirement transition experience, in turn, was associated with older workers' postretirement change trajectory of life satisfaction. Our findings highlight the importance of the transition phase of retirement, as well as the role of retirement transition experience during this critical phase in explaining the relationships between preretirement resources, in terms of both their levels and changes, and postretirement changes in well-being. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Cisplatin-induced hepatotoxicity reduces the liver clearance of AuNPs, which increases AuNP accumulation in the damaged liver than in the normal liver.

As the diversity field evolves, scholars are shifting the attention from mitigating "problems" associated with diversity to searching for ways to leverage the potential value in diversity. We advance this field by studying how an inclusive climate benefits organizational innovation, an important foundation for sustained competitive advantage. Adopting a synergy perspective, we examine the internal (i.e., workplace demographic diversity in terms of age, gender, and region) and external contingencies (i.e., environmental scanning and environmental uncertainty) for an inclusive climate to foster incremental and radical innovation through the mechanism of knowledge management capacity. We tested our research model with a three-wave data collection from multiple sources (i.e., employees, human resource managers, and executives) in 102 organizations. We found that workplace age and regional diversity (but not gender diversity) strengthened the positive effect of inclusive climate on knowledge management capacity, and subsequently incremental and radical innovation. The facilitating effect of environmental scanning was only significant for organizations that experienced higher environmental uncertainty. Our research highlights the importance of considering the synergistic potential of internal human resources and external environments for organizations to capitalize on their inclusive climate for knowledge management and innovation. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Over the past three years, people have suffered from unimaginable psychological stress and anxiety caused by the COVID-19 epidemic. These stresses and anxieties stem from the threat that COVID-19 poses to people’s health and lives, as well as the negative impact of the government’s lockdown and quarantine policies on social economy and development. All these factors may put people in a state of stress and anxiety for a long time. However, any perceived stress can trigger the individual’s self-defense mechanism. To reduce anxiety from the epidemic, the automatic psychological processes are involuntarily activated, and the defense mechanisms are at work. This paper examines the performance of defense mechanisms during the epidemic based on news reports and the theory of defense mechanisms and illustrates the practical role and significance of understanding defense mechanisms for the public. Additionally, this paper also takes into account the potential cultural features of defensive systems.

ConspectusAsymmetric organocatalysis has been considered to be an efficient and reliable strategy for the stereoselective preparation of optically active chemicals. In particular, chiral tertiary amines as Lewis base organocatalysts bearing core structures including quinuclidine, dimethylaminopyridine (DMAP)

Effective mental health services require accurate assessment of psychosocial impairments linked to mental health concerns. Youth who experience these impairments do so within and across various contexts (e.g., school, home). Youth may display symptoms of mental health concerns without co-occurring impairments, and vice versa. Yet, nearly all impairment measures presume that those assessed display mental health concerns. Consequently, we recently developed youth and parent versions of a five-item measure of youth psychosocial impairments (i.e., Work and Social Adjustment Scale for Youth [WSASY]), structured to assess any youth, regardless of mental health status. Across two studies, we developed and tested a WSASY teacher version, in a large sample of 382 student teacher reports (Study 1), and a subsample of 66 youth who, along with their parents and teachers, completed the WSASY and a series of school- and home-based behavioral tasks (Study 2). In Study 1, WSASY teacher reports demonstrated excellent internal consistency and unique relations with teacher reports on well-established measures of psychosocial strengths and difficulties. In Study 2, teacher, youth, and parent WSASY reports demonstrated low correspondence with each other and context-specific relations with criterion variables. This low correspondence allowed us to capitalize on an integrative approach designed to optimize informant-specific variance. Integrative scores demonstrated robust, large-magnitude relations with criterion variables across multiple information sources. These findings provide important psychometric support for use of WSASY teacher reports, and pave the way toward integrating WSASY reports from multiple informants who observe youth psychosocial impairments within different contexts and from different perspectives. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Plants manage the high cost of immunity activation by suppressing the expression of defense genes during normal growth and rapidly switching them on upon pathogen invasion. TGAs are key transcription factors controlling the expression of defense genes. However, how TGAs function, especially in monocot plants like rice with continuously high levels of endogenous salicylic acid (SA) remains elusive. In this study, we characterized the role of OsTGA5 as a negative regulator of rice resistance against blast fungus by transcriptionally repressing the expression of various defense-related genes. Moreover, OsTGA5 repressed PTI responses and the accumulation of endogenous SA. Importantly, we showed that the nucleus-localized casein kinase II (CK2) complex interacts with and phosphorylates OsTGA5 on Ser-32, which reduces the affinity of OsTGA5 for the JIOsPR10 promoter, thereby alleviating the repression of JIOsPR10 transcription and increasing rice resistance. Furthermore, the in vivo phosphorylation of OsTGA5 Ser-32 was enhanced by blast fungus infection. The CK2 α subunit, depending on its kinase activity, positively regulated rice defense against blast fungus. Taken together, our results provide a mechanism for the role of OsTGA5 in negatively regulating the transcription of defense-related genes in rice and the repressive switch imposed by nuclear CK2-mediated phosphorylation during blast fungus invasion.

An important task of meta-analysis is to observe, quantify, and explain the heterogeneity across the reported effect sizes of primary studies. A primary issue that challenges this task is the myriad of subtle factors that could have contributed to the observed heterogeneity. We leveraged the recent advances in theoretical machine learning to develop a novel latent mixture-based method for disentangling effect-size heterogeneity in meta-analysis. Mathematical analysis and simulation studies were carried out to demonstrate that, when the observed heterogeneity stems from more than 1 factor, our method can attain a substantially higher statistical power than the traditional methods for moderator analysis without requiring researchers to make judgment calls on which factors to consider or correct for in analyzing the observed heterogeneity. We also conducted a case study with real-world data to show how our method may be used to address long-standing inconsistencies in the literature. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Findings regarding the mechanism underlying the impact of supervisor incivility on subordinate alcohol misuse remain equivocal. Specifically, some studies indicate that stress mediates the impact of supervisor incivility on subordinate alcohol misuse, while others, find no evidence for such an effect, suggesting the need to investigate other mechanisms. Extending Conservation of Resource (COR) theory and employing a longitudinal study design, this study examines two alternative mechanisms grounded on social isolation. The first suggests drinking as a resource-mobilizing response, with social isolation eliciting the perception of more permissive injunctive drinking norms, thus facilitating problematic drinking. The second suggests problematic drinking as a mode of coping with a negative emotional state elicited by social isolation, namely depression. Findings indicate that supervisor undermining’s association with subsequent subordinate problematic drinking is serially mediated by social isolation and depression, with no support found for the first mechanism. Implications for research, practice and policy are discussed.

Digital technology, broadly defined as all the electronic tools, automatic systems, technological devices, and resources that generate, process, or store information in the form of binary code (Shah, Nogueras, Van Woerden, & Kiparoglou, 2019), has brought great changes to almost all aspects of human life. In particular, the development and the application of various digital technologies have great potential to facilitate successful aging by helping individuals effectively cope with different forms of age-related challenges, though an organizing framework is lacking from the literature. In this paper, we derive a taxonomy for understanding the impacts of digital technology on successful aging by considering the intersections between digital technology types and the age-related applied settings. Based on this taxonomy, we map different types of digital technology to different functions and successful aging outcomes in both non-work and work domains. We also discuss the implications of our taxonomy to research inquiries and practical applications.

Diabetic macular edema (DME) is a significant complication of diabetes that impacts the eye and is a primary contributor to vision loss in individuals with diabetes. Early control of the related risk factors is crucial to reduce the incidence of DME. Artificial intelligence (AI) clinical decision-making tools can construct disease prediction models to aid in the clinical screening of the high-risk population for early disease intervention. However, conventional machine learning and data mining techniques have limitations in predicting diseases when dealing with missing feature values. To solve this problem, a knowledge graph displays the connection relationships of multi-source and multi-domain data in the form of a semantic network to enable cross-domain modeling and queries. This approach can facilitate the personalized prediction of diseases using any number of known feature data. In this study, we proposed an improved correlation enhancement algorithm based on knowledge graph reasoning to comprehensively evaluate the factors that influence DME to achieve disease prediction. We constructed a knowledge graph based on Neo4j by preprocessing the collected clinical data and analyzing the statistical rules. Based on reasoning using the statistical rules of the knowledge graph, we used the correlation enhancement coefficient and generalized closeness degree method to enhance the model. Meanwhile, we analyzed and verified these models’ results using link prediction evaluation indicators. The disease prediction model proposed in this study achieved a precision rate of 86.21%, which is more accurate and efficient in predicting DME. Furthermore, the clinical decision support system developed using this model can facilitate personalized disease risk prediction, making it convenient for the clinical screening of a high-risk population and early disease intervention.

Background Studies are limited for family-related events in relation to sustainable working life (i.e., not having long-term periods of unemployment, sickness absence and disability pension). We aimed to investigate the associations between stability and change in family life and sustainable working life and whether these associations were explained by health behaviours, genetic factors, and early life environment.Methods Register data and surveys for family-related events, sustainable working life and health behaviours of 49 611 Swedish twins were used. Cox proportional hazards regressions were applied to estimate the associations between family-related events and sustainable working life, while conditional Cox models for twin pairs accounted for confounding of genetic factors and early life environment. Further, the analyses were stratified by health behaviours.Results Change from being single living without children to married living with children was associated with sustainable working life. Moreover, individuals who experienced divorce and single individuals who changed status of living with children were less likely to experience a sustainable working life. Genetic factors and early life environment played a role in some associations. Also, those with healthy behaviours were more likely to have sustainable working life even though they had changes in family life compared to those with unhealthy behaviours.Conclusions Family formation is associated with sustainable working life whereas divorce seems to decrease the possibility of sustainable working life. Health behaviours as well as genetic factors and early life environment also need to be considered in relation to changes in family life for supporting sustainable working life.

Background Residential regions may impact the possibilities to achieve a sustainable working life (SWL, i.e. not having interruptions due to sickness absence, disability pension or unemployment) due to disparities in social security and labour market. We aimed to investigate concurrent trajectories of regions and SWL among Swedish twins. Methods National register data were used for the degree of SWL in each year, old-age pension, emigration, death and residential regions classified in three categories (cities; towns and suburbs; or rural areas) of Swedish twins in 1998–2016 (n = 80 398). Group-based multi-trajectory modelling and multinomial regression for relative risks with 95% confidence intervals were calculated. Results The six-group solution had the best fit to data with trajectories: stable living in towns and suburbs with SWL (33.8%); stable living in cities with SWL (22.1%); stable living in towns and suburbs with increasing SWL (13.9%); stable living in towns and suburbs with lack of SWL (13.2%); stable living towns and suburbs with decreasing SWL (8.8%); and stable living towns and suburbs with decreasing and ultimately lack of SWL (8.3%). Age and being woman increased and being married and higher education decreased the likelihood of belonging to groups 2–6 (vs. 1). Conclusions The simultaneous assessment of trajectories of three residential regions and SWL indicated that most people in Sweden seem to live continuously over time in towns and suburbs, but the degree of SWL may vary. More fine-grained assessment of residential regions would be needed to clarify the associations with SWL.

Background Research is scarce on the role of familial factors and previous psychiatric care on the association between suicide attempt and future work incapacity as well as deterioration in mental health. We aimed to investigate the associations between suicide attempt and sickness absence, disability pension and psychiatric patient care and to study the influence of previous psychiatric care and familial factors (genetics and shared environment) on the associations. Methods The study included 65 097 twins living in Sweden on 31st of December 2006, aged 19–60 years. The twins were followed 2007–2013 regarding sickness absence, disability pension, inpatient care or specialized outpatient care for a mental diagnosis. Cox regression models were performed for the whole sample, and conditional models for discordant twin pairs. The analyses were also stratified by psychiatric care before 2007. Results We found that suicide attempt predicted sickness absence, disability pension, and future mental diagnosis among the whole sample. The discordant twin pair analyses showed that the association between suicide attempt and sickness absence or disability pension was influenced by familial factors. Stratified analyses of individuals with or without psychiatric care before 2007 showed that previous psychiatric care had some impact on the associations. Conclusions A suicide attempt is a risk factor for work incapacity and psychiatric patient care. Familial factors and previous psychiatric care play a role in the associations between attempting suicide and work incapacity as well as psychiatric patient care. These factors are important when developing measures preventing work incapacity among those with a suicide attempt.

In this paper, the incident beam called high-dimensional circular hollow sinh-Gaussian (HD-CHsG) beam with a novel wavefront is proposed, which is determined by three parameters (m, σ0, σ1). Based on the Richards-wolf vector diffraction theory, it can be focused into a longitudinal polarized optical needle through a high numerical aperture lens. The effects of the three parameters (m, σ0, σ1) on the resolution and depth of focus of the longitudinally polarized optical needle are simulated and analyzed. In the condition of (m, σ0, σ1) = (8, 0.6, 0.125), a super-diffraction longitudinal optical needle with ultra-long focal depth (resolution 0.40λ, focal depth 18.36λ, depth-to-width ratio 45.9:1) is generated. In addition, compared with a radially polarized incident beam whose amplitude distribution is Gaussian and circular hollow sinh-Gaussian (CHsG) distribution, the resolution and depth of focus of the longitudinally polarized optical needle obtained by focusing the HD-CHsG beam are higher. Both simulations and experiments are carried out to demonstrate the availability of our method. Our findings are of great significance to the production, manipulation, and application of longitudinally polarized optical needle.

Monitoring rice planting areas and their phenological phases is crucial for yield estimation and informed decision-making. This study proposed a unified method for mapping rice field and rice phenology with a dynamic time wrapping (DTW) distance-based classifier and its variant sub-DTW algorithm using Sentinel-1’s synthetic aperture radar (SAR) VH band. Field samplings were conducted for broad landcover types in one of the areas of interest (AOIs). We implemented a pixel-wisek-nearest neighbor classification model with DTW distance to identify paddy rice pixels. Standard rice phenological profiles of the SAR VH band were defined by ground monitoring of a sample rice field. Based on rice planting maps and the standard phenological profiles, rice phenological phases were estimated by pattern matching strategy with the sub-DTW algorithm. Experiments on six counties in Northeast China presented promising results. The overall producer and user accuracy reached 92.9 and 91.9% for rice mapping, respectively. The mean root mean square error (RMSE) for phenology estimation was 3.5 days. Rice planting and rice phenology maps were generated for the six AOIs. The phenological variances of the AOIs implied the effects of climate and rice cultivars on phenological development.

The increasing prevalence of aging workforce around the globe renders older worker retention an integral approach for organizations to maintain human capital. In the meantime, the increasing application of digital technologies at work poses new challenges for older workers. Providing digital technology training is therefore considered as a potential approach to retaining older workers. Yet, we have limited knowledge about the role played by digital technology training availability in facilitating older worker retention. Addressing this important research void, we examine the motivation-based (i.e., autonomy need satisfaction at work) and the ability-based (i.e., competence need satisfaction at work) mechanisms that transmit the positive indirect effects of digital technology training availability on older workers’ intention to remain. We also examine the critical roles of the relevance of the training (both the relevance to the situation and to the participant) in shaping the impacts of digital technology training availability. Analyzing data collected from 285 workers aged 40 years or older, we found that when digital technology was perceived to be more (vs. less) useful at work, digital technology training availability indirectly facilitated older workers’ intention to remain via both autonomy and competence needs satisfaction at work. Moreover, the amplifying effects of perceived usefulness of digital technology at work were more (vs. less) pronounced for participants who had higher (vs. lower) growth need. Theoretical and practical implications were also discussed based on our findings.