bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating Reliability, Validity, and Measurement Invariance of the Eight-Item Vocational Rehabilitation Engagement Scale With a Sample of Multilingual Clients
Authors: Torres Ayse , Kaya Cahit , Akinola Olayemi , Gonzalez Rene
Published: March 2023

Vocational rehabilitation (VR) engagement is a vital component for successful rehabilitation outcomes. The purpose of this study is threefold: First, we investigated the item clarity of the Vocational Rehabilitation Engagement Scale (VRES); second, we explored the factorial structure; third, we examined the measurement invariance of the VRES across gender and education level for culturally diverse and bilingual clients in public VR program (i.e., clients speak English as a second language). Given the positive effects of client engagement in health and rehabilitative care on outcomes, it is important to validate this brief instrument to measure VR engagement for culturally diverse and bilingual clients. Data, collected from 16 VR clients who completed the original VRES in the focus group, were subjected to content analysis, and data, collected from 264 clients who completed the eight-item VRES and Working Alliance Inventory Short Form (WAI-S), were subjected to confirmatory and multigroup confirmatory factor analysis (MGCFA). Based on the feedback from the focus group, the first item was revised to increase clarity. However, the preliminary results indicated that the revised item had very low community value, and therefore, we removed the item from the subsequent analysis. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) results provided support for a unidimensional structure for the eight-item VRES. Measurement invariance across gender and education level was achieved after correlating error terms. The scale had strong reliability, and scores from the VRES were significantly moderately correlated with working alliance. The eight-item VRES is a reliable and valid measurement tool to use with culturally diverse and multilingual participants.
Gendered Consequences of Social Mobility: Second-Generation Immigrants’ Work–Care Considerations in High-Status Occupations in Norway
Authors: Nadim Marjan , Midtbøen Arnfinn H
Published: March 2023

Across Europe, children of low-educated migrants are entering high-status occupations. While the research literature has accounted for the determinants of this social mobility, few studies have explored how social mobility affects the lives of second-generation immigrant men and women in different ways. Drawing on in-depth interviews with 62 descendants of migrants in high-status occupations in Norway, this article asks how second-generation women and men experience their gendered opportunities and constraints after achieving upward social mobility. The analyses show how social mobility brings the second generation into social milieus where their majority Norwegian colleagues become their most relevant references for how to do work and family. Both the second-generation women and men share a strong dedication to work, however, while this requires the women to challenge gender-complementary expectations, the men largely rely on gender-complementary arrangements. The analyses thus suggest that social mobility changes the lives of women more than those of men.
Maternal Occupation-Specific Skills and Children’s Cognitive Development
Authors: Barg Katherin , Klein Markus
Published: March 2023

This article hypothesizes that maternal occupation-specific skills are associated with children’s cognitive development over and above parents’ other human, financial and social capital. Data from the UK Millennium Cohort Study on 13,543 children were complemented with occupation-level data (n = 79) from the British Skills Surveys on aggregate measures of mothers’ occupation-specific skills (literacy, numeracy, problem-solving, verbal and physical). We did not find any association between maternal occupation-specific skills and children’s non-verbal ability (inductive reasoning, spatial awareness) at age five when conditioning on covariates. However, mothers’ verbal skills (e.g. presentation skills) were positively associated with children’s verbal ability (Naming Vocabulary) over and above other parental resources. By contrast, mothers’ physical skills (e.g. use of physical strength) were negatively associated with children’s verbal abilities. Albeit effect sizes are small, maternal occupation-specific skills contribute to social stratification in children’s verbal development net of human, financial and social capital.
Empowering Seafarers as Agents of Their Mental Health: The Role of Information and Communication Technology in Seafarers’ Well-Being
Authors: Abila Sanley , Kitada Momoko , Malecosio Serafin , Tang Lijun , Subong-Espina Rhea
Published: March 2023

The academic literature seldom views information and communication technology (ICT) as a means to empower merchant seafarers in terms of their active and positive contributions to their mental health (MH) and overall well-being. Seafarers are often viewed as recipients and not the sources of health interventions. Using mixed methods, this paper examines how seafarers’ MH has not been the top priority among seafarers themselves, and how ICT and formal education might empower seafarers in health promotion. The pervasive culture of “ship first” in the maritime industry is palpable in the findings of this study, where seafarers do not prioritize their MH because the ship’s safe operations take precedence over everything else. Data shows that seafarers perceive MH interventions provided by companies as more useful when these have direct implications or effects on their families. In effect, seafarers may not see a priorities the physical and mental health support directly impacting their well-being. Nevertheless, there are some fundamental changes in the maritime industry in using technology to improve the MH of seafarers and their overall well-being, such as the development of MH applications (“apps”), helplines, or websites, coupled with the growing comfort of seafarers to use ICT.
Between General Strike and Dissensus: W. E. B. Du Bois’s Black Reconstruction
Authors: Feldman J. L.
Published: March 2023

For W. E. B. Du Bois, the tragedy of Reconstruction was that its achievements were overthrown and erased from collective memory. Du Bois’s Black Reconstruction corrects this, claiming enslaved people who fled plantations self-emancipated, thus enacting a “general strike against the slave system.” Yet Du Bois contravenes his general strike thesis when he quotes without rebuttal several Union officials who spoke of the formerly enslaved in degrading, nonagentic terms. I turn to Jacques Rancière’s politics of dissensus to understand why Du Bois quoted such racist views without comment. In Rancière, political actors “stage a scene” of equality that is shared, even among parties in conflict. Recording conflicting perceptions of the strike, highlighting divisions that persist despite momentary advances of equality, Du Bois’s reading of the general strike is dissensual in Rancière’s sense, I argue. But Du Bois also offers a valuable corrective to Rancière, whose account of the first plebeian secession erases a different general strike from memory. Rancière reads the Aventine as an event of confrontation unconnected to the collective action that Du Bois summoned from the archive and named “general strike.”
Breast Tumor Classification using Short-ResNet with Pixel-based Tumor Probability Map in Ultrasound Images
Authors: Wang You-Wei , Kuo Tsung-Ter , Chou Yi-Hong , Su Yu , Huang Shing-Hwa , Chen Chii-Jen
Published: March 2023

Breast cancer is the most common form of cancer and is still the second leading cause of death for women in the world. Early detection and treatment of breast cancer can reduce mortality rates. Breast ultrasound is always used to detect and diagnose breast cancer. The accurate breast segmentation and diagnosis as benign or malignant is still a challenging task in the ultrasound image. In this paper, we proposed a classification model as short-ResNet with DC-UNet to solve the segmentation and diagnosis challenge to find the tumor and classify benign or malignant with breast ultrasonic images. The proposed model has a dice coefficient of 83% for segmentation and achieves an accuracy of 90% for classification with breast tumors. In the experiment, we have compared with segmentation task and classification result in different datasets to prove that the proposed model is more general and demonstrates better results. The deep learning model using short-ResNet to classify tumor whether benign or malignant, that combine DC-UNet of segmentation task to assist in improving the classification results.
Boundary-oriented Network for Automatic Breast Tumor Segmentation in Ultrasound Images
Authors: Zhang Mengmeng , Huang Aibin , Yang Debiao , Xu Rui
Published: March 2023

Breast cancer is considered as the most prevalent cancer. Using ultrasound images is a momentous clinical diagnosis method to locate breast tumors. However, accurate segmentation of breast tumors remains an open problem due to ultrasound artifacts, low contrast, and complicated tumor shapes in ultrasound images. To address this issue, we proposed a boundary-oriented network (BO-Net) for boosting breast tumor segmentation in ultrasound images. The BO-Net boosts tumor segmentation performance from two perspectives. Firstly, a boundary-oriented module (BOM) was designed to capture the weak boundaries of breast tumors by learning additional breast tumor boundary maps. Second, we focus on enhanced feature extraction, which takes advantage of the Atrous Spatial Pyramid Pooling (ASPP) module and Squeeze-and-Excitation (SE) block to obtain multi-scale and efficient feature information. We evaluate our network on two public datasets: Dataset B and BUSI. For the Dataset B, our network achieves 0.8685 in Dice, 0.7846 in Jaccard, 0.8604 in Precision, 0.9078 in Recall, and 0.9928 in Specificity. For the BUSI dataset, our network achieves 0.7954 in Dice, 0.7033 in Jaccard, 0.8275 in Precision, 0.8251 in Recall, and 0.9814 in Specificity. Experimental results show that BO-Net outperforms the state-of-the-art segmentation methods for breast tumor segmentation in ultrasound images. It demonstrates that focusing on boundary and feature enhancement creates more efficient and robust breast tumor segmentation.
Increasing the Impact of Program Evaluation: The Importance of Challenging Assumptions and Incorporating New Perspectives
Authors: Long Bridget Terry
Published: March 2023

These remarks, which were given as the 2022 Recipient of the Peter H. Rossi Award for Contributions to the Theory or Practice of Program Evaluation, emphasize ways to increase the impact of program evaluation. First, is the importance of asking good questions, including ones that challenge the assumptions and models that dominate the field. Relatedly, we need to question the assumption that “one size fits all” and recognize the variation that exists—across contexts, time, and individuals. The key question is what works for whom under what conditions, and this also pushes us to think about why effects differ and what is driving those differences, that is, the underlying mechanisms. It is also important to incorporate new perspectives to improve our questions, models, research design, and interpretation, thus helping to address the aforementioned points. We should both welcome diverse perspectives into the research community and listen carefully to the communities we seek to study and incorporating their insights. Although the examples focus on a career in education research, the implications of the points are relevant for any aspect of social policy.
ICTs, smallholder agriculture and farmers’ livelihood improvement in developing countries: Evidence from Tanzania
Authors: Ndimbo Gabriel Kanuti , Yu Lerong , Ndi Buma Andam Andin
Published: March 2023

Information and Communication Technologies (ICTs) are among the profound tools to help the poor and marginalized rural smallholder farmers make a difference in their lives. This paper seeks to understand how the recent development of ICTs helps increase agricultural productivity and improve smallholder farmers’ livelihoods in Tanzania. We employed a fuzzy sets Qualitative Comparative Analysis (fsQCA) technique to select the most relevant 24 literature from 2163 literature and analyze the drivers ( conditions) that influence ICT use among the smallholder farmers, which in turn leads to increased agricultural productivity and improved farmers’ livelihoods ( outcomes). In addition, the authors conducted in-depth interviews with some local smallholder farmers in Tanzania's same regions, as shown in the reviewed literature, to understand how ICTs worked in the field. Findings revealed that ICTs had been increasingly used for and directly linked with agricultural transformation, increased agricultural productivity and improved rural livelihoods in Tanzania in the past two decades. Smallholder farmers rely on ICT tools, particularly mobile phones and radios, to access agricultural-related information, which helps them increase agricultural productivity. The limited number of public extension service agents forces most smallholder farmers to opt for ICTs as an alternative source of agricultural information. In this case, the agricultural extension department from the ministry of agriculture should work closely with telecom, broadcasting companies and other stakeholders to strengthen and initiate more appropriate ICT infrastructure and services targeting the smallholder farmers.
The role of the healthcare assistant on a stroke unit: A scoping review
Authors: Wood Sophie , Johansson Jessica Faye , Wray Faye , Forster Anne
Published: March 2023

Objective

This scoping review explores the role of a healthcare assistant on a stroke unit, potential barriers to role fulfilment and whether stroke-specific training could enhance rehabilitative practice.

Data sources

Searches were conducted on CINAHL, MEDLINE and APA PsycInfo in May 2021 and repeated in September 2022.

Methods

This scoping review was guided by Arksey and O’Malley's framework. Article selection and data extraction were conducted by one researcher using a structured proforma. A narrative approach to data synthesis was undertaken following the research questions.

Results

From a combined total of 533 articles, sixty-six full-text articles were assessed for eligibility. Sixteen full articles were included in this review. A healthcare assistants’ role was viewed as caring directly for patients – some individuals felt they contributed to rehabilitation during these tasks, and that they could be undervalued by multidisciplinary team members, patients and their families. The barriers identified to healthcare assistants’ role fulfilment were lack of time, training and staffing shortages. Training was perceived to improve healthcare assistants’ communication, confidence and knowledge but training needed to be flexible, ward based and accommodate staffing shortages. However, it is unclear whether training has any clinical benefit for patients.

Conclusion

Healthcare assistants are well placed to enhance rehabilitative practice with patients; however, there are clear perceived barriers to this occurring. Future research should aim to define the role of healthcare assistants and explore whether further stroke-specific training could cause clinical benefits for patients.
Predicting outcome in dogs with diffuse large B-cell lymphoma with a novel immune landscape signature
Authors: Licenziato Luca , Minoli Lucia , Ala Ugo , Marconato Laura , Fanelli Antonella , Giannuzzi Diana , De Maria Raffaella , Iussich Selina , Orlando Giulia , Bertoni Francesco , Aresu Luca
Published: March 2023

Canine diffuse large B-cell lymphoma (cDLBCL) is characterized by high mortality and clinical heterogeneity. Although chemo-immunotherapy improves outcome, treatment response remains mainly unpredictable. To identify a set of immune-related genes aberrantly regulated and impacting the prognosis, we explored the immune landscape of cDLBCL by NanoString. The immune gene expression profile of 48 fully clinically characterized cDLBCLs treated with chemo-immunotherapy was analyzed with the NanoString nCounter Canine IO Panel using RNA extracted from tumor tissue paraffin blocks. A Cox proportional-hazards model was used to design a prognostic gene signature. The Cox model identified a 6-gene signature ( IL2RB, BCL6, TXK, C2, CDKN2B, ITK) strongly associated with lymphoma-specific survival, from which a risk score was calculated. Dogs were assigned to high-risk or low-risk groups according to the median score. Thirty-nine genes were differentially expressed between the 2 groups. Gene set analysis highlighted an upregulation of genes involved in complement activation, cytotoxicity, and antigen processing in low-risk dogs compared with high-risk dogs, whereas genes associated with cell cycle were downregulated in dogs with a lower risk. In line with these results, cell type profiling suggested the abundance of natural killer and CD8+ cells in low-risk dogs compared with high-risk dogs. Furthermore, the prognostic power of the risk score was validated in an independent cohort of cDLBCL. In conclusion, the 6-gene-derived risk score represents a robust biomarker in predicting the prognosis in cDLBCL. Moreover, our results suggest that enhanced tumor antigen recognition and cytotoxic activity are crucial in achieving a more effective response to chemo-immunotherapy.
Focus of alignment and performance accuracy among wind band musicians in situations of audio-visual asynchrony
Authors: Lorenz Taina , Morrison Steven J
Published: March 2023

Ensemble musicians must navigate a complex sensory environment to produce cohesive performances. The purpose of this study was to examine pulse alignment among performers of different experience levels facing increasingly asynchronous auditory and visual information. Musicians ( N = 51) who were current members of large instrumental ensembles watched a video of a conductor outlining a 4/4 pattern while hearing a multivoiced instrumental ensemble soundtrack and were asked to tap the pulse on a tablet-based pad. Each of nine examples was presented in one of three experimental formats: control (steady audio and video), audio (ensemble) accelerating/video (conductor beat pattern) decelerating, and video accelerating/audio decelerating. Rate of pulse change was ±7.5% with initial tempos of 108, 127, and 146 bpm. Data consisted of (1) deviations (ms) from a consistent IOI (steady pulse) and (2) mean deviations from audio (ensemble) or video (conductor) pulse. In the asynchronous conditions, participants broadly adhered to auditory or visual information rather than to a steady rate of pulse. There was no significant difference between information stream preference. Experience was a significant factor in audio information deviations; more experienced performers found audio information to be a more salient reference point, consistent with results reported for less contextualized timekeeping tasks.
The impact of background music on learners: A systematic review and meta-analysis
Authors: de la Mora Velasco Efrén , Chen Yuting , Hirumi Atsusi , Bai Haiyan
Published: March 2023

This meta-analysis integrates outcomes of experimental and quasi-experimental studies to analyze the effects of background music (BM) on learning. Research articles, dissertations, and conference proceedings published in or before 2021 were examined. Seventy-one effect sizes from 47 studies were integrated using a random-effects model and subgroup analyses. Five key results were found: (a) a small and positive mean effect size ( d = 0.314) in favor of the BM condition, (b) a positive and medium effect size for studies that implemented BM before the learning assessment, (c) a positive and small effect size for factual knowledge retention, (d) a positive and small effect size for classical music compared with other music genres, and (e) individuals’ age can potentially moderate the impact of BM on learning. The results suggest a revised explanation of how the BM may affect learning, refuting existing cognitive load and multimedia learning theories that discourage the use of BM during instruction.
Long-term treatment with lasmiditan in patients with migraine: Results from the open-label extension of the CENTURION randomized trial
Authors: Ashina Messoud , Roos Caroline , Li Lily Qian , Komori Mika , Ayer David , Ruff Dustin , Krege John Henry
Published: March 2023

Background

Following the CENTURION phase 3 randomized controlled trial’s four-month double-blind phase, this 12-month open-label extension collected data for up to one year about dose optimization, patterns of use, migraine-related disability, and quality of life during lasmiditan treatment.

Methods

Migraine patients ≥18 years completing the double-blind phase and treating ≥3 migraine attacks could continue into the 12-month open-label extension. The initial oral lasmiditan dose was 100 mg; the dose could subsequently be adjusted to 50 mg or 200 mg at the investigator’s discretion.

Results

477 patients entered and 321 (72.1%) completed the extension; 445 (93.3%) treated ≥1 attack with lasmiditan. Of 11,327 attacks, 8654 (76.4%) were lasmiditan-treated (84.9% of these involved moderate or severe pain). By study end, 17.8%, 58.7%, and 23.4% of patients were taking lasmiditan 50, 100, and 200 mg, respectively. Mean improvements were observed in disability and quality of life. The most common treatment-emergent adverse event was dizziness (35.7% of patients, 9.5% of attacks).

Conclusions

During this 12-month extension, lasmiditan was associated with a high rate of study completion, most attacks were treated with lasmiditan, and patients reported improvements in migraine-related disability and quality of life. No new safety findings were observed with longer exposure. Trial registration: ClinicalTrials.gov (NCT03670810); European Union Drug Regulating Authorities Clinical Trials Database (EUDRA CT: 2018-001661-17).
Should I Travel by Metro? Analyzing the Service Quality Perception of Elderly and Physically Disabled Passengers in Delhi, India
Authors: Mandhani Jyoti , Nayak Jogendra Kumar , Parida Manoranjan
Published: March 2023

Transit officials worldwide continuously learn from passenger perception surveys to improve service quality and enhance transit ridership. However, many elderly and physically disabled (E&PD) passengers are transit users with special needs whose service requirements have received insufficient attention in the past. In fact, providing satisfactory transit services to E&PD passengers is often a critical challenge for transit officials, since a theory of interrelations among service factors is not yet established from E&PD passengers’ perspectives. Therefore, the present study aims to establish interrelations among service quality factors and identify service improvements for E&PD passengers using satisfaction data from 254 E&PD passengers of Delhi Metro. For this purpose, this study has employed an integrated Bayesian networks and partial least squares path modeling approach. The obtained results have shown some remarkable and meaningful interpretations. For instance, a one-unit increase in satisfaction with the “safety & security” factor would induce a 68% increase in their satisfaction with overall service quality. Besides, importance–performance map analysis showed that Delhi Metro must consider “safety and security,”“passenger ease,” and “seamless connectivity” as high-priority areas needing improvements to promote E&PD-friendly transit services. Overall, the findings of this study suggest several policy measures that would enrich the service quality and achieve universal design standards in metro rail transit systems.
Classification of Impact Echo Signals Using Explainable Deep Learning and Transfer Learning Approaches
Authors: Torlapati Rahul , Azari Hoda , Shokouhi Parisa
Published: March 2023

Impact echo (IE) is one of the most frequently used nondestructive evaluation (NDE) techniques for detecting subsurface defects such as delamination, honeycombing, and voids in concrete structures. In the conventional analysis of IE data, the time-domain signal is transformed into the frequency domain and the frequency content is used to estimate the presence and nature of the defect. Machine learning (ML) has been recently applied to the IE signal classification problem. However, because of the scarcity of labeled IE datasets, most existing work relies on relatively small training and test datasets without addressing the generalizability and transferability of the developed models. In this paper, we compare two approaches for automatic classification of IE signals: clustering based on expert-crafted features and deep learning (DL) from automatically extracted features. Next, we use the knowledge gained from a DL model trained on concrete specimens with available ground truth to make predictions about defects in a different specimen with completely different construction and characteristics (transfer learning). Finally, we examine our DL model to gain insights into the model working (explainability) and highlight the attributions that are significant in classifying a particular IE signal. Our findings demonstrate the utility of ML and DL for IE signal classification, but also highlight the need for high-quality labeled datasets for advancing ML and DL in NDE data analysis.
Debating Social Change and the Jewish Nation: The Polish-Jewish Weekly Ewa on Jewish Families and Birth Control (1928–1933)
Authors: Hein-Kircher Heidi
Published: March 2023

The objectives of the debates on birth control and thus of the concepts of family planning had changed in East Central Europe after World War I as a result of the founding of nation states. The respective dominant as well as non-dominant national groups colored them nationally by focusing on the development of their own nation. A particular example of the inherent national coloration of the transnationally effective discourses on birth control is the Polish-Jewish women's weekly Ewa. In the late 1920s, when a nationwide marriage and abortion law was being negotiated under the conditions of an authoritarian regime in Poland, Ewa took up these debates in order to sketch a specific Polish-Jewish image of the family. The publication also embraced birth control as a national challenge, but did so under a Zionist banner. The article assesses Ewa's important contributions to tracing and influencing the understanding of birth control and the images of modern families and women in the Polish-Jewish milieu during the interwar period.
Metamemory and Self-Compassion as Protective Factors in the Relationship Between Benevolent Ageism and Environmental Mastery
Authors: Sublett Jennifer F. , Bisconti Toni L.
Published: March 2023

The present study examined the interrelationships between benevolent ageism, metamemory, self-compassion, and environmental mastery. By assessing older adults’ perceptions of overaccommodative behaviors, we found greater perceptions of benevolent ageist experiences, or well-intended patronage, related to lower levels of environmental mastery, effectively managing one’s own affairs, in a sample of 202 older adults. Additionally, this relationship is mediated by metamemory, or self-perceptions of memory abilities, as greater perceptions of benevolent ageism experiences indirectly predicted less environmental mastery through having decreased metamemory confidence. Finally, this mediated relationship is moderated by self-compassion, or kindness and acceptance towards oneself, in that self-compassion interacts with benevolent ageism to predict metamemory, which in turn predicts environmental mastery. Self-compassion is part of a growing literature on intervening variables that helping professionals can teach older adults to mitigate the relationship between ageism and their overall well-being alongside efforts to diminish the pervasiveness of ageism in society.
Automated Adolescence Scoliosis Detection Using Augmented U-Net With Non-square Kernels
Authors: Wu Yujie , Namdar Khashayar , Chen Chaojun , Hosseinpour Shahob , Shroff Manohar , Doria Andrea S. , Khalvati Farzad
Published: March 2023

Purpose: Scoliosis is a deformity of the spine, and as a measure of scoliosis severity, Cobb angle is fundamental to the diagnosis of deformities that require treatment. Conventional Cobb angle measurement and assessment is usually done manually, which is inherently time-consuming, and associated with high inter- and intra-observer variability. While there exist automatic scoliosis measurement methods, they suffer from insufficient accuracy. In this work, we propose a two-step segmentation-based deep learning architecture to automate Cobb angle measurement for scoliosis assessment using X-Ray images. Methods: The proposed architecture involves two steps. In the first step, we utilize a novel Augmented U-Net architecture to generate segmentations of vertebrae. The second step includes a non-learning-based pipeline to extract landmark coordinates from the segmented vertebrae and filter undesirable landmarks. Results: Our proposed Augmented U-Net architecture achieved a Symmetric Mean Absolute Percentage Error of 9.2%, with approximately 90% of estimations having less than 10 degrees difference compared with the AASCE-MICCAI challenge 2019 dataset ground truths. We further validated the model using an internal dataset and achieved almost the same level of performance. Conclusion: The proposed architecture is robust in providing automated spinal vertebrae segmentations and Cobb angle measurement, and is potentially generalizable to real-world clinical settings.
Profitability and Its Determinants: Operationalizing the ‘Law of the Tendency of the Rate of Profit to Fall’ in the US Economy, 1950–2020
Authors: Watterton Joshua J.
Published: March 2023

This analysis seeks to demonstrate the theoretical and empirical salience of the ‘law of the tendency of the rate of profit to fall’ in relation to the concrete evolution of the US economy between 1950 and 2020. The theoretical-methodological approach adopted in this study is based on the work of Shane Mage and Murray E.G. Smith. This approach re-specifies the Marxian value categories and ratios for purposes of empirically operationalizing them as a theory of fundamental capitalist dynamics using national accounting data. Contributions include (1) the treatment of systemically necessary unproductive labour as a ‘constant capital overhead cost’ and (2) a method of managing ‘fictitious profits’ that are imputed into the national accounts and thereby enabling a more realistic estimate of ‘social surplus value’ (the numerator of the Marxian average rate of profit) in what has become an ‘era of fictitious capital’. The empirical findings reveal a persistent rise in the organic composition of capital, as well as a rise in the rate of surplus value, accompanied by a long-term downward trend in the average rate of profit in the postwar US economy.
Scaling of bi-material sandwich panels subjected to impact loadings
Authors: Al-Tamimi Anees
Published: March 2023

Scaling is a widely used concept in impact and explosion engineering which is mainly utilized to predict the response behaviour of large-scale mechanical structures by conducting experiments on scaled trial models. However, the practical application of currently available conventional scaling methodologies for impact and explosive processes are significantly restricted by their inability to properly capture the scale effects of strain rate and strain hardening. Also, they are suffering from an insufficient number of independent degrees of freedom. Furthermore, the zeroth-order finite similitude theory, which can annihilate the non-scalability of rate and hardening effects, doesn’t provide us with efficient scaling methods when the investigated structure is made out of different materials. More precisely, the zeroth-order finite similitude theory and the classical dimensional analysis, which are suffering from a limited number of independent degrees of freedom, cannot scale the elastic-plastic behaviour represented by different parts of a structure made out of different materials. In other words, classical scaling methodologies including dimensional analysis and even the zeroth-order finite similitude theory cannot fix two different features having the same unit using different degrees of freedom, which make them useless for structures made of more than one material such as bi-material sandwich panels. In the presented paper, a new scaling methodology is developed based on the recently proposed first-order finite similitude theory which for the first time enables us to capture the rate dependent plastic behaviour of an impacted structure made out of two different materials. A sandwich panel made of two different materials which is subjected to an impact loading is considered as the case study in order to investigate the efficiency of the proposed first-order based scaling technique. The numerical results are determined using Abaqus finite element software in which the Johnson-Cook constitutive equation is utilized to take into account the rate and hardening effects on the initial yield stress. The results reveal that the behaviour of impacted full-scale bi-material sandwich panels can be predicted with a high accuracy when the extra degree of freedom provided us with the first-order finite similitude (i.e. R1) is set to vary between −1 and 1 (i.e. [Formula: see text]). Furthermore, it is found that the pure mechanical and thermo-mechanical behaviour of the impacted core honeycomb are highly accurately predicted using scaled-down trial models which are made from dissimilar materials and designed based on the zeroth-order finite similitude theory.
Development of a new low-cost computer vision system for human gait analysis: A case study
Authors: Bernal-Torres Mario G. , Medellín-Castillo Hugo I , Arellano-González Juan C
Published: March 2023

Today, human gait analysis is commonly used for clinical diagnosis, rehabilitation and performance improvement in sports. However, although previous research works in the literature address the use of motion capture systems by means of optoelectronic sensors, Inertial Measurement Units (IMUs) and depth cameras, few of them discuss their conception, guidelines and algorithms for measuring and calculating gait metrics. Moreover, commercially available motion capture systems, although efficient, are cost restrictive for most of the low-income institutions. In this research work, a new computer vision-based system (CVS) for gait analysis is developed and proposed. The aim is to close the gap found in the literature about the design and development of such systems by providing the requirements, considerations, algorithms and methodologies used to develop a gait analysis system with acceptable precision and accuracy, and at low cost. For this purpose, a linear computer vision method based on the non-homogeneous solution of the calibration matrix was used. The spatio-temporal and angular gait parameters were implemented in the proposed system, and compared with those reported in the literature. The denoising of the spatial gait trajectories and the strategies to detect gait events, are also presented and discussed. The results have shown that the proposed system is satisfactory for human gait analysis in terms of precision, computational performance and low cost.
Human immunodeficiency virus pre-exposure prophylaxis awareness among people who inject drugs in Portland, Oregon
Authors: Spencer Hunter C , Babiarz Jane , Menza Tim W
Published: March 2023

Background

Pre-Exposure Prophylaxis (PrEP) to prevent transmission of human immunodeficiency virus (HIV) among people who inject drugs (PWID) has demonstrated efficacy yet awareness of PrEP among PWID is low.

Methods

2018 National Behavioral Health Survey data from the Portland, Oregon metropolitan statistical area was analyzed with chi-squared tests and generalized linear models to determine correlates of PrEP awareness among PWID.

Results

80% of the sample had at least one indication for PrEP and 15% of the sample was aware of PrEP. Factors associated with higher PrEP awareness were: higher education level (PR = 1.083, CI = 1.018–1.153, p = .012), reporting transactional sex (PR = 1.154, CI = 1.019–1.307, p = .024), and men who have sex with men reporting condomless sex (PR = 1.376, CI = 1.081–1.752, p = .010). Lack of a usual source of care (PR = 0.884, CI = 0.824–0.949, p < .001) was negatively associated with PrEP awareness.

Conclusions

Interventions to increase PrEP awareness need to target groups with particularly low awareness and be delivered in settings accessible to PWID.
Food Is All Around: How Contexts Create Misbeliefs About the Health–Taste Relationship
Authors: Kunz Sonja , Haasova Simona , Pivecka Niklas , Schmidt Justus , Florack Arnd
Published: March 2023

We investigated a novel cognitive-ecological account for misbeliefs about the relationship between food healthiness and tastiness. We propose that different frequencies of healthy and tasty foods in contrasting contexts can trigger perceptions that health and taste are related in ways that diverge from the actual health–taste correlation in the presented food. To investigate this proposal, we conducted three studies (total N = 369), including a taste test, with adult Prolific academic participants from the United Kingdom and undergraduate psychology students from Austria. Our results showed that different frequencies of healthy and tasty food across contrasting contexts can trigger misbeliefs about the relationship between health and taste. These findings demonstrate that properties of the food ecology combined with basic cognitive processes can help explain the formation of beliefs about food such as that unhealthy food tastes better than healthy food. Our study extends the existing explanations for food beliefs and provides a perspective on how they can be changed.
Hospitalized patients with positive antiphospholipid antibodies who have low complement levels are at increased risk for death—a retrospective cohort study
Authors: Itelman Edward , Perelman Maxim , Bivar Natali , Kent Daniella , Vaisman Adva , Segal Gad , Negru Liat , Dagan Amir
Published: March 2023

Purpose

To investigate whether low complement levels can predict worse outcomes in patients hospitalized with positive anti-phospholipid antibodies.

Methods

This was a retrospective cohort study. We obtained demographics, laboratory, and prognostic data of all consecutive patients hospitalized between 2007 and 2021, for whatever reason, with at least one positively abnormal anti-phospholipid antibody, who were also tested for complement levels (C3 or C4). We then compared the rates of long-term mortality, 1-year mortality, deep vein thrombosis, and pulmonary emboli between groups of low complement and normal complement levels. Multivariate analysis was used to control for levels of clinical and laboratory confounders.

Results

We identified 32,286 patients tested for anti-phospholipid antibodies. Of those patients, 6800 tested positive for at least one anti-phospholipid antibody and had a documented complement level. Significant higher mortality rates were found in the low complement group, with an odds ratio for mortality (OR 1.93 CI 1.63–2.27 p < .001). Deep vein thrombosis and pulmonary emboli rates were similar. Multivariate analysis confirmed that low complement was an independent predictor for mortality after controlling for age, sex, dyslipidemia, chronic heart failure (CHF), chronic kidney disease (CKD), and anemia.

Conclusions

Our study results indicate that low complement is associated with significantly higher mortality rates in admitted patients with elevated levels of anti-phospholipid antibodies. This finding correlates with recent literature suggesting a vital role for complement activation in anti-phospholipid syndrome.
An Examination of Memory Performance in a Fearful Virtual Reality Gaming Context
Authors: Lo L. Y. , Ip C. L.
Published: March 2023

Background

The emotion of fear bears a survival significance enabling animals to be highly vigilant in contexts of uncertainty. Expectedly, not all information available in the environment can be processed. Given that a major goal is to get rid of the source of fear in a fearful situation, the current study therefore hypothesized that information relating to the fear source would be better attended to and recalled than contextual information, which was validated by comparing participants’ recall of different types of information presented in a fearful VR gaming context.

Methodology

Fifty-four participants were divided into two groups and finished a specific segment of a VR game with different fear levels.

Results

No significant difference in recall performance on the questions about the appearance of the fear source and the questions about the interaction with the source was observed between the fear and less-fear groups. Yet, contextual information was better recalled than information related to the fear source in both groups. Regardless of whether the contextual information was provided beforehand or not, participants still tended to focus primarily on the environment in the gameplay. Also, the immersiveness of the gameplay was positively related to participants’ fear level.

Discussion

The tendency of attending to contextual information was speculated to be unconditional, in line with the risk calculation observed in prey when situated in less familiar contexts. It was suggested to further validate the present primarily findings by adopting VR headset with eye-tracking function in future studies. Lastly, an understanding of fear’s effect on memorization might also provide some information for developing future survival horror games.
A unifying method-based classification of robot swarm spatial self-organisation behaviours
Authors: Hénard Aymeric , Rivière Jérémy , Peillard Etienne , Kubicki Sébastien , Coppin Gilles
Published: March 2023

Self-organisation in robot swarms can produce collective behaviours, particularly through spatial self-organisation. For example, it can be used to ensure that the robots in a swarm move collectively. However, from a designer’s point of view, understanding precisely what happens in a swarm that allows these behaviours to emerge at the macroscopic level remains a difficult task. The same behaviour can come from multiple different controllers (ie the control algorithm of a robot) and a single controller can give rise to multiple different behaviours, sometimes caused by slight changes in self-organisation. To grasp the causes of these differences, it is necessary to investigate the relationships between the many methods of self-organisation that exist and the various behaviours that can be obtained. The work presented here addresses self-organisation in robot swarms by focusing on the main behaviours that lead to spatial self-organisation of the robots. First, we propose a unified definition of the different behaviours and present an original classification system highlighting ten self-organisation methods that each allow one or more behaviours to be performed. An analysis, based on this classification system, links the identified mechanisms with behaviours that could be considered as obtainable or not. Finally, we discuss some perspectives on this work, notably from the point of view of an operator or designer.
Episode Payment Models and Provider Consolidation: Evidence From the Comprehensive Care for Joint Replacement Model
Authors: He Fang
Published: March 2023

A possible unintended consequence of episode payment models is provider consolidation, which can, in turn, increase prices for commercially insured enrollees. We assess the effect of Medicare’s Comprehensive Care for Joint Replacement (CJR) model on provider consolidation. Hospitals in randomly assigned metropolitan statistical areas were mandated to participate during the first 2 years of the model and a subset of hospitals were mandated for later years. We used a difference-in-differences approach to assess whether CJR affected consolidation, as measured by hospital ownership of practices, the number and size of practices, the Herfindahl–Hirschman Index, and the four-firm concentration ratio. Given limited sample sizes, our results are only suggestive that CJR was not associated with changes in consolidation. Our strongest results suggest null effects for changes in hospital ownership and practice size. These findings suggest that concerns regarding the role alternative payment models play in consolidation may have been overstated.
Intimate Partner Violence Against Women and Labor Productivity: The Mediating Role of Morbidity
Authors: Asencios-Gonzalez Zaida B. , Vara-Horna Arístides A. , Brad McBride J.
Published: March 2023

This study determines that morbidity presents a mediating impact between intimate partner violence against women and labor productivity in terms of absenteeism and presenteeism. Partial least squares structural equation modeling (PLS-SEM) was used on a nationwide representative sample of 357 female owners of micro-firms in Peru. The resulting data reveals that morbidity is a mediating variable between intimate partner violence against women and absenteeism (β = 0.213; p < .001), as well as between intimate partner violence against women and presenteeism (β = 0.336; p < .001). This finding allows us to understand how such intimate partner violence against women negatively affects the workplace productivity in the context of a micro-enterprise, a key element in many economies across the world.
Dress is a Fundamental Component of Person Perception
Authors: Hester Neil , Hehman Eric
Published: March 2023

Academic Abstract

Clothing, hairstyle, makeup, and accessories influence first impressions. However, target dress is notably absent from current theories and models of person perception. We discuss three reasons for this minimal attention to dress in person perception: high theoretical complexity, incompatibility with traditional methodology, and underappreciation by the groups who have historically guided research in person perception. We propose a working model of person perception that incorporates target dress alongside target face, target body, context, and perceiver characteristics. Then, we identify four types of inferences for which perceivers rely on target dress: social categories, cognitive states, status, and aesthetics. For each of these, we review relevant work in social cognition, integrate this work with existing dress research, and propose future directions. Finally, we identify and offer solutions to the theoretical and methodological challenges accompanying the psychological study of dress.

Public Abstract

Why is it that people often agonize over what to wear for a job interview, a first date, or a party? The answer is simple: They understand that others’ first impressions of them rely on their clothing, hairstyle, makeup, and accessories. Many people might be surprised, then, to learn that psychologists’ theories about how people form first impressions of others have little to say about how people dress. This is true in part because the meaning of clothing is so complex and culturally dependent. We propose a working model of first impressions that identifies four types of information that people infer from dress: people’s social identities, mental states, status, and aesthetic tastes. For each of these, we review existing research on clothing, integrate this research with related work from social psychology more broadly, and propose future directions for research.