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In response to calls for research on the psychological mechanisms, such as perceptions and attitudes toward corporate citizenship, in promoting positive outcomes at work, this research presents a novel approach by empirically testing a calling conditioned path model from P perception of corporate CSR (P-CSR) to work engagement via meaningfulness under the theoretical framework of self-determination theory. Survey data collected from 224 corporate employees in the US were tested using the PROCESS plugin (version 4.3) in SPSS. The regression results supported the positive direct and indirect paths from employees’ P-CSR to meaningfulness and work engagement but not the conditioning effect of calling work orientation. This study’s unique findings, limitations, future research, and implications are discussed, expanding micro-CSR research and unboxing the management assumptions of employees as purposeful autonomous agents seeking consistent interpretations and authentic perceptions of organizational CSR activities during their sense-making processes. Non-confirming of the calling conditioning the path model shed light on it being a dynamic multi-dimensional and multi-level construct to be further researched. © 2024 by the authors.

Frequency importance functions quantify the contribution of spectral frequencies to perception. Frequency importance has been well-characterized for speech recognition in quiet and steady-state noise. However, it is currently unknown whether frequency importance estimates generalize to more complex conditions such as listening in a multi-talker masker or when targets and maskers are spatially separated. Here, frequency importance was estimated by quantifying associations between local target-to-masker ratios at the output of an auditory filterbank and keyword recognition accuracy for sentences. Unlike traditional methods used to measure frequency importance, this technique estimates frequency importance without modifying the acoustic properties of the target or masker. Frequency importance was compared across sentences in noise and a two-talker masker, as well as sentences in a two-talker masker that was either co-located with or spatially separated from the target. Results indicate that frequency importance depends on masker type and spatial configuration. Frequencies above 5 kHz had lower importance and frequencies between 600 and 1900 Hz had higher importance in the presence of a two-talker masker relative to a noise masker. Spatial separation increased the importance of frequencies between 600 Hz and 5 kHz. Thus, frequency importance functions vary across listening conditions.

Across three online studies, we examined the relationship between the Fear of Missing Out (FoMO) and moral cognition and behavior. Study 1 (N = 283) examined whether FoMO influenced moral awareness, judgments, and recalled and predicted behavior of first-person moral violations in either higher or lower social settings. Study 2 (N = 821) examined these relationships in third-person judgments with varying agent identities in relation to the participant (agent = stranger, friend, or someone disliked). Study 3 (N = 604) examined the influence of recalling activities either engaged in or missed out on these relationships. Using the Rubin Causal Model, we created hypothetical randomized experiments from our real-world randomized experimental data with treatment conditions for lower or higher FoMO (median split), matched for relevant covariates, and compared differences in FoMO groups on moral awareness, judgments, and several other behavioral outcomes. Using a randomization-based approach, we examined these relationships with Fisher Tests and computed 95% Fisherian intervals for constant treatment effects consistent with the matched data and the hypothetical FoMO intervention. All three studies provide evidence that FoMO is robustly related to giving less severe judgments of moral violations. Moreover, those with higher FoMO were found to report a greater likelihood of committing moral violations in the past, knowing people who have committed moral violations in the past, being more likely to commit them in the future, and knowing people who are likely to commit moral violations in the future.

We describe photometry improvements in the La Silla-Quest RR Lyrae star (RRLS) survey that enable it to reach distances from the Sun (d⊙) ∼140 kpc. We report the results of surveying ∼300 deg2 of sky around the large, low-surface-brightness Crater II dwarf spheroidal galaxy. At d⊙ >80 kpc, we find a large overdensity of RRLS that extends beyond the traditional isophotal contours used for Crater II. The majority of these RRLS (34) have a linear distribution on the sky, extending over 15°, that runs through Crater II and is oriented along Crater II’s proper motion vector. We hypothesize that this unlikely distribution traces extended tidal streams associated with Crater II. To test this, we search for other Crater II stellar populations that should be in the streams. Using Gaia proper motion data, we isolate ≈ 17 candidate stars outside of Crater II that are consistent with being luminous stars from the Crater II Red Giant Branch (RGB). Their spatial distribution is consistent with the RRLS one. The inferred streams are long, spanning a distance range ∼80–135 kpc from the Galactic Centre. They are oriented at a relatively small-angle relative to our line of sight (∼25°), which means some stream stars are likely projected onto the main body of the galaxy. Comparing the numbers of RRLS and RGB candidate stars found in the streams to those in the main galaxy, we estimate Crater II has lost $\gtrsim 30~{{\rm per\ cent}}$ of its stellar mass.

Establishing an optimal datacenter selection policy within the cloud environment is paramount to maximize the performance of the cloud services. Service broker policy governs the selection of datacenters for user requests. In our research, we introduce an innovative approach incorporating the genetic algorithm with service broker policy to assist cloud services in identifying the most suitable datacenters for specific userbases. The effectiveness of our proposed genetic algorithm was rigorously evaluated through experiments conducted on CloudAnalyst platform. The results clearly indicate that our proposed algorithm surpasses existing service broker policies and previous research works done in this field in terms of reducing response time and data processing time. The results analysis validates its efficacy and potential for enhancing cloud service performance and reducing the cost of overall cloud infrastructure.

Despite being a fundamental concept, the field of supply chain management (SCM) exhibits a significant lack of consensus regarding the definition of supply chain flows (SCFLOWS). Additionally, there has been an over-reliance on three flows – material, information and finance – while various other flows crucial to SCM performance have been overlooked. Hence, the purpose of this study is twofold: (1) to explore the multi-dimensional nature of SCFLOWS and (2) to identify additional flows beyond the commonly acknowledged ones that are vital for SCM performance.,This study employs various qualitative methods as part of the abduction process. The methods include in-depth interviews with logistics professionals, a Delphi study involving SCM scholars and a focus group comprising airline industry practitioners.,Seven SCFLOWS dimensions are identified and presented as SCFLOWS framework. Also, two additional flows, i.e. human and capital equipment, are proposed as vital to SCM performance.,This is the first study to introduce SCFLOWS framework to achieve consensus in the field. By introducing two additional flows, it proposes extending the SCFLOWS boundary to include various flows overlooked previously but pertinent to SCM performance. The SCFLOWS framework serves as a systematic guide to validate additional flows and represents an important step towards building SCM theory.

Marker variables provide an efficacious means of post hoc detection of common method variance (CMV) in data. These variables are measured in the same way as substantive variables, but because they are conceptually unrelated to the variables of interest, they are believed to be a proxy for CMV. Although marker variables have demonstrated effectiveness, questions remain as to what they actually measure, and thus, why they work. This lack of knowledge prevents researchers from choosing appropriate marker variables to include in same source surveys. The purpose of this research is to determine how four different marker variables account for common rater effects which can cause CMV. A metacognitive approach is used to develop an empirical study using two samples, with a focus on the specific rater effects of mood state, transient mood, consistency motif, and illusory correlations. Findings indicate that these marker variables elicit similar respondent reactions and do not create a notable psychological separation between substantive variables. Additionally, there is evidence that respondents’ use of consistency motifs and illusory correlations influence substantive variable relations. Finally, using the confirmatory factor analysis marker technique, data from two samples indicate the presence of CMV, but not bias from CMV, indicating that the problem of artificially inflated results due to CMV may be overstated.

Atomic nuclei are self-organized, many-body quantum systems bound by strong nuclear forces within femtometre-scale space. These complex systems manifest a variety of shapes1–3, traditionally explored using non-invasive spectroscopic techniques at low energies4,5. However, at these energies, their instantaneous shapes are obscured by long-timescale quantum fluctuations, making direct observation challenging. Here we introduce the collective-flow-assisted nuclear shape-imaging method, which images the nuclear global shape by colliding them at ultrarelativistic speeds and analysing the collective response of outgoing debris. This technique captures a collision-specific snapshot of the spatial matter distribution within the nuclei, which, through the hydrodynamic expansion, imprints patterns on the particle momentum distribution observed in detectors6,7. We benchmark this method in collisions of ground-state uranium-238 nuclei, known for their elongated, axial-symmetric shape. Our findings show a large deformation with a slight deviation from axial symmetry in the nuclear ground state, aligning broadly with previous low-energy experiments. This approach offers a new method for imaging nuclear shapes, enhances our understanding of the initial conditions in high-energy collisions and addresses the important issue of nuclear structure evolution across energy scales. © The Author(s) 2024.

Background: Pakistan is a densely populated South Asian country. It is facing numerous health challenges, as well as problems of the digital divide. The government of Pakistan established e-libraries as a pilot project in 2018. These libraries are functioning through community centers/public libraries in the largest province of the country. Objective: This paper examines the role of Pakistani e-libraries in creating health awareness and providing health information to the public. Methods: The qualitative research design was based on focus group discussions with the head librarians of all 13 of the 20 e-libraries contacted. Results: The findings revealed that e-libraries actively create health-related awareness and connect the public to health advisors. The e-libraries were engaged in four types of health-related activities (seminars, awareness campaigns, open health camps, and special health day celebrations) with high attendance from the public. Attendees of these programs returned to librarians with additional health-related queries. Conclusions: The study suggests a need for more liaison between the community and local healthcare institutions. This approach can make these programs more effective in helping individuals manage their health. The results of this study can serve as a useful guide for other developing nations in developing similar services. © 2024 Health Libraries Group.

This chapter calls for urgent institutional changes to address structural inequalities through advocacy and legislative action. The authors discuss macro practice methods to address racial injustice through advocacy efforts such as fostering policies eliminating anti-Asian hate and violence, advocating for nondiscriminative policies, improving language access, campaigning for narrative change, building coalitions with social justice groups, encouraging civic engagement, strengthening links with social justice organizations, and promoting policies and programs on Asian American, Native Hawai’ian, and Pacific Islander history education and awareness. Policy advocacy to protect Asian Americans against racial hate crimes is lacking but much needed. Macro social workers’ efforts can pressure policymakers to directly address anti-Asian racism and violence, provide targeted assistance, and call on national, state, and local organizations to ensure investments in culturally appropriate services to Asian American communities.

This chapter begins with a review of the history of anti-Asian racism in the United States. Beginning in the mid-19th century, Asian immigrants played a vital role in the development of the country. However, Asian Americans have faced a long legacy of exclusion and inequality, particularly during periods of economic recession, disease outbreaks, or war throughout US history. Adopting the framework of “othering,” this chapter analyzes the major events in US history related to Asian Americans, such as the Chinese Exclusion Act of 1882, the Immigration Act of 1924, the Japanese internment camps during World War II, and the anti-Asian immigration policies adopted by the Trump administration. Through this, the authors illustrate how historic racism and xenophobia at both individual and institutional levels have operated to marginalize Asian Americans and reproduce inequality, and they demonstrate the common roots of racism that lie in White supremacy.

We measure the absolute proper motion of Andromeda III (And III) using Advanced Camera for Surveys/Wide Field Channel and WFPC2 exposures spanning an unprecedented 22 yr time baseline. The WFPC2 exposures have been processed using a deep-learning centering procedure recently developed as well as an improved astrometric calibration of the camera. The absolute proper motion zero point is given by 98 galaxies and 16 Gaia EDR3 stars. The resulting proper motion is (μ α , μ δ ) = (−10.5 ± 12.5, 47.5 ± 12.5) μas yr−1. We perform an orbit analysis of And III using two estimates of M31's mass and proper motion. We find that And III’s orbit is consistent with dynamical membership to the Great Plane of Andromeda system of satellites although with some looser alignment compared to the previous two satellites NGC 147 and NGC 185. And III is bound to M31 if M31's mass is M vir ≥ 1.5 × 1012 M ⊙.

States and districts share an obligation to provide Multilingual Learners (MLLs) with access to high quality language programs that are proven to be effective in minimizing opportunity gaps between MLLs and non-MLLs. This article reviews how local education agencies (LEAs) allocated their state-issued funding to improve MLL language programs and increase student outcomes. Findings reveal that of the total state-issued MLL funding, LEAs used 88.7% on teacher salaries and benefits, 5.1% on teacher professional development, 4.9% on language program implementation, 0% on language program evaluation, and a small percentage of funding remained unspecified. Collectively, these findings indicate that LEAs did not adhere to the state's funding policies, nor did the state follow their own policies to regulate the LEAs' expenditures. We close with a discussion on how the state can improve their function as an organizational leader and serve as a model for other stakeholders in the shared obligation of the education of MLLs.

This study developed a framework for predicting usability factors through an understanding of how cognitive traits relate to human interaction with a computer system. Specifically, this study examined the relationship of field-independence, spatial visualization, logical reasoning, and integrative reasoning to interaction process and outcome. The research hypothesis was tested through correlation to determine the relationships among variables. As a post hoc analysis, multiple regression analysis was used to examine the predictive power of four cognitive variables on interaction outcome. The results of the study emphasize the importance of considering cognitive variables as important predictors to human interaction process and outcome. © 2024 IEEE.

As the population of Aotearoa New Zealand ages, informal family carers will play an increasingly important role in caring for older adults at home. Multi-generational living arrangements are a growing trend, particularly among Māori communities, where caring for older relatives within the family home is widespread. This article uses in-depth, semi-structured interviews with Māori whānau (extended family members) caring for kaumātua (older family members) at home to explore how carers experienced care coordination in the broader care collective. The findings centred on three interconnected factors that described the collective organisation of care: (1) whānau care as normal; (2) whānau care as collective coordination; and (3) whānau carer knowledge and needs as unseen. The findings show that although whānau care of kaumātua is highly valued, ‘structural holes’ within care systems contribute to challenges in care coordination. Despite extensive whānau support for kaumātua, primary carers often felt that their knowledge, preferences and self-care needs remained unseen and not translatable to those outside the everyday care situation. Rather than assuming an artificial binary difference between ‘collective’ and ‘individually oriented’ care contexts and cultures, analysing the cultural norms surrounding whānau care-giving confirms that collective care system members face similar and different challenges to carers with smaller caring capacities. © The Author(s), 2024.

We report multi-differential measurements of strange hadron production ranging from mid- to target-rapidity in Au+Au collisions at a center-of-momentum energy per nucleon pair of sNN = 3 GeV with the STAR experiment at RHIC. KS0 meson and Λ hyperon yields are measured via their weak decay channels. Collision centrality and rapidity dependences of the transverse momentum spectra and particle ratios are presented. Particle mass and centrality dependence of the average transverse momenta of Λ and KS0 are compared with other strange particles, providing evidence of the development of hadronic rescattering in such collisions. The 4π yields of each of these strange hadrons show a consistent centrality dependence. Discussions on radial flow, the strange hadron production mechanism, and properties of the medium created in such collisions are presented together with results from hadronic transport and thermal model calculations. © The Author(s) 2024.

The Individuals with Disabilities Education Improvement Act of 2004 ensured millions of American students had a legal right to free and appropriate physical education. Yet, there is confusion about who delivers appropriate adapted physical education (APE). This article reflects on the half century of legally defined APE and a country’s response to preparing teachers for the disability-related demands of the job. A critical perspective is offered with the hope of improving physical educational outcomes for students with disabilities.

College student mental health has been a critical concern for professional counselors. Anxiety and depressive disorders have become increasingly prevalent over the past decade. Utilizing machine learning, a subset of artificial intelligence (AI), we developed predictive models (i.e., eXtreme Gradient Boosting [XGBoost], Random Forest, Decision Tree, and Logistic Regression) to identify US college students at heightened risk of diagnosable anxiety and depressive disorders. The dataset included 61,619 students from 133 US higher education institutions and was partitioned into a 90:10 ratio for training and testing the models. We employed hyperparameter tuning and cross-validation to optimize model performance and examined multiple measures of predictive performance (e.g., area under the receiver operating characteristic curve [AUC], accuracy, sensitivity). Results revealed strong discriminative power in our machine learning predictive models with AUC of 0.74 and 0.77, indicating current financial situation, sense of belonging on campus, disability status, and age as the top predictors of anxiety and depressive disorders. This study provides a practical tool for professional counselors to proactively identify students for anxiety and depressive disorders before these conditions escalate. Application of machine learning in counseling research provides data-driven insights that help enhance the understanding of mental health determinants, guide prevention and intervention strategies, and promote the well-being of diverse student populations through counseling.

Alice Wieland and Amy Jansen explore the intersection of how power, adverse incentives, and gender bias combine to perpetuate gender inequity in higher education.