bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Improved K-Means Algorithm in Collaborative Recommendation System
Authors: Jing Hui
Published: December 2022

With the explosive growth of information resources in the age of big data, mankind has gradually fallen into a serious “information overload” situation. In the face of massive data, collaborative filtering algorithm plays an important role in information filtering and information refinement. However, the recommendation quality and efficiency of collaborative filtering recommendation algorithms are low. The research combines the improved artificial bee colony algorithm with K-means algorithm and applies them to the recommendation system to form a collaborative filtering recommendation algorithm. The experimental results show that the MAE value of the new fitness function is 0.767 on average, which has good separation and compactness in clustering effect. It shows high search accuracy and speed. Compared with the original collaborative filtering algorithm, the average absolute error value of this algorithm is low, and the running time is only 50 s. It improves the recommendation quality and ensures the recommendation efficiency, providing a new research path for the improvement of collaborative filtering recommendation algorithm.
A Stochastic Model for an Input Control Problem in a Two-Level Supply Chain for Production-Time-Dependent Products with Random Demands
Authors: Kim Woo-Sung , Han Jun-Hee
Published: December 2022

Inspired by the poultry farming process, we studied an input control problem in a two-level supply chain for production-time-dependent products with random demands. Poultry farms deliver chicks in batches, and the raising process begins at timed intervals. Chicks become broilers after a predetermined raising time. The broilers in the process are shipped to manufacturing plants to satisfy the demand. The remaining chicks grow to the next product size to satisfy the demands for larger chickens. This procedure is repeated until the chicks are fully grown. After the chicks are grown to satisfy the demand for the largest size, the remaining chicks are discarded. In this paper, a stochastic model is presented to study an input control problem in the poultry farming process. Because of the production density, feed, and temperature control, one important issue in the operation of a poultry company is the determination of the raising interval and quantity of input (chicks). While existing mathematical models can provide effective information on the production-planning problem of systems, research has not been conducted on cases of random demand. Identifying a recursive structure and Markovian property for the number of raw materials (chicks) and the unfulfilled demand for each product type in the system, we demonstrate that embedded Markov chain models can be obtained. The equilibrium probabilities of the models can be calculated using matrix analytic methods or probability generating functions. Various numerical experiments are conducted to analyze how performance measures such as amount of disposal, unsatisfied demands, and total cost (considering disposal cost and opportunity cost) change with system parameters.
Structural Parameters Optimization of the Steel Bar Straightening Machine Based on the PSO Algorithm
Authors: Zhu Xiaoyan , Liu Yong , Zhang Shibang , Cao Jianzhao , Sun Jinchen , Chen Shanshan , Wang Xiwen , Li Songhua
Published: December 2022

In the process of steel bar straightening processing, the straightening rollers are often damaged by fatigue due to uneven force, which causes frequent replacement of the straightening rollers. Therefore, the structural parameters optimization of the steel bar straightening machine is very important to improve the machining accuracy of the straightening machine and prolong the service life of straightening roller. In this paper, an optimization method based on the particle swarm optimization (PSO) algorithm was proposed and used to optimize the structural parameters of the steel bar straightening machine. First, the main parameters that affect the accuracy of the straightening machine were comprehensively analysed, and the optimization range of each parameter was determined. Second, in order to minimize the fluctuation of the contact stress, the objective function was established by fitting the roller spacing, roller diameter, roller number, and so on. Then, the PSO algorithm was used to find the optimal solution of structural parameters. Finally, the proposed structural optimization method was verified in practice and compared with the single variable algorithm. As a result, the straightness of the steel bar is increased by 2.88%, and the total straightening force is reduced by 16.25%, compared with the single variable algorithm. In conclusion, it was demonstrated that the proposed optimization method based on the PSO algorithm is better than the single variable algorithm in optimizing the structural parameters of the steel bar straightening machine.
Using Network Pharmacology and Molecular Docking to Explore the Mechanism of Qiju Dihuang Pill against Dry Eye Disease
Authors: Zhao Xiaoshuang , Yu Zengfang , Li Dan , Duan Junguo
Published: December 2022

Background. Dry eye disease (DED) is a multifactorial disease of the ocular surface, which affects the quality of life and work efficiency of affected patients. The traditional Chinese medicine formula Qiju Dihuang Pill (QJDHP) has a good therapeutic effect on DED. However, the pharmacological mechanism is not clear. Objective. To explore the mechanism of QJDHP in the treatment of DED based on network pharmacology. Method. The active components in QJDHP were screened in Traditional Chinese Medicine Systems Pharmacology (TCMSP), and putative molecular targets of QJDHP were identified using the SwissTargetPrediction database. DED-related targets were screened by GeneCards and OMIM. We established protein-protein interaction (PPI) and core targets and corresponding active compound network by Cytoscape to identify the core targets and main compounds of QJDHP against DED. DAVID database was utilized for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Molecular docking was used to evaluate the binding activity between key active compounds and core targets. Results. The results of network pharmacology showed that 253 targets of QJDHP were related to DED. PPI network analysis showed the 18 core targets. The binding affinity of docking results ranged from -5.7 to -9.3 kcal/mol, indicating a good docking effect. The results of GO enrichment analysis showed that the mechanism of QJDHP in the treatment of DED mainly involved biological processes such as apoptosis, oxidative stress, response to estrogen, angiogenesis, and the regulation of transcription factors. KEGG analysis showed that QJDHP may be regulated by the TNF signaling pathway, Toll-like receptor signaling pathway, MAPK signaling pathway, and estrogen signaling pathway in the treatment of DED. Conclusion. In this study, we demonstrated the multicomponent, multitarget, and multichannel action mechanism of QJDHP in the treatment of DED and provided a foundation for further drug development research.
Model Lightweighting for Real-time Distraction Detection on Resource-Limited Devices
Authors: Wang Jing , Wu ZhongCheng
Published: December 2022

Detecting distracted driving accurately and quickly with limited resources is an essential yet underexplored problem. Most of the existing works ignore the resource-limited reality. In this work, we aim to achieve accurate and fast distracted driver detection in the context of embedded devices where only limited memory and computing resources are available. Specifically, we propose a novel convolutional neural network (CNN) light-weighting method via adjusting block layers and shrinking network channels without compromising the model’s accuracy. Finally, the model is deployed on multiple devices with real-time detection of driving behaviour. The experimental results for the American University in Cairo (AUC) and StateFarm datasets demonstrate the effectiveness of the proposed method. For instance, for the AUC dataset, the proposed MobileNetV2-tiny model achieves 1.63% higher accuracy with just 78% of the model parameters of the original MobileNetV2 model. The inference speed of the proposed MobileNetV2-tiny model on resource-limited devices is on average 1.5 times that of the original MobileNetV2 model, which can meet real-time requirements.
A Novel Approach for Hybrid Image Segmentation GCPSO: FCM Techniques for MRI Brain Tumour Identification and Classification
Authors: Kavitha P. , Jayagopal Prabhu , Sandeep Kumar M. , Mahamuni Vetri Selvi
Published: December 2022

In recent times, the early detection of brain tumour analysis and classification has become a very vital part of the medical field. The MRI scan image is the most significant tool to study brain tissue for proper diagnosis and efficient treatment planning to detect the early stages. In this research study, the two contributions were executed in the preprocessing mode. (a) Using wavelet transform to apply decomposed sub-bands of a low-frequency signal to control and adapt the spatial and intensity parameters in a bilateral filter and (b) to detect texture regions and block boundary to control and adapt the spatial and intensity parameters in a bilateral filter When compared to other image resolution methods, the adaptive bilateral method restores the original image quality and has a higher accuracy rate. Using the hybrid segmentation method of GCPSO (Guaranteed Convergence Particle Swarm Optimization) -FCM (Fuzzy C-Mean) techniques, the results were compared with various segmentation. The proposed segmentation gives a better accuracy rate of 95.32%.
circPOLR1C Promotes the Development of Esophageal Cancer by Adsorbing miR-361-3p and Regulating Cancer Cell Apoptosis and Metastasis
Authors: Fang Yong , Yin Jun , Shen Yaxing , Wang Hao , Tang Han , Chen Xiaosang
Published: December 2022

Background. The effect of circular RNA-RNA polymerase I and III subunit C (circPOLR1C) on esophageal cancer (EC) has not been reported. Herein, this study is designed to unveil the effect and the regulatory mechanism of circPOLR1C on EC. Methods. The expression of circPOLR1C in EC tissues and cells was detected by qRT-PCR. Circular structure, stability, and cell localization of circPOLR1C were confirmed by qRT-PCR, RNase R, actinomycin D, and fluorescence in situ hybridization (FISH) assay. Cell function experiments, nude mouse xenograft, lung transplant model, and HE staining were performed to evaluate the effects of CircPOLR1C on EC in vitro and in vivo. A regulatory relationship between miR-361-3p and circPOLR1C was confirmed by qRT-PCR, circRNA in vivo precipitation, RIP, FISH, CircInteractome database, dual-luciferase reporter assay, and immunohistochemistry. Rescue experiments were applied to assess the effects of miR-361-3p and circPOLR1C on EC cells and tissues. Apoptosis- and epithelial-mesenchymal transformation (EMT)-related gene expressions were quantified by qRT-PCR and Western blot. Results. Highly expressed circPOLR1C in EC was related to tumor differentiation and invasion. circPOLR1C, which mainly exists in the cytoplasm, is a stable circular RNA. circPOLR1C silencing inhibited circPOLR1C expression and EC cell malignant function, while circPOLR1C overexpression promoted the growth of transplanted tumors and lung metastasis. The enrichment of miR-361-3p was higher than that of other targeted miRNAs. circPOLR1C adsorbed miR-361-3p to regulate apoptosis- and EMT-related genes and partially reversed the tumor suppressive effect of miR-361-3p, which was lowly expressed in EC tissues. Silencing the target genes of miR-361-3p also inhibited the malignant development of EC cells. Conclusion. circPOLR1C adsorbs miR-361-3p and regulates apoptosis- and EMT-related gene expressions to promote the development of EC.
Nonlinear Model Order Selection: A GMM Clustering Approach Based on a Genetic Version of EM Algorithm
Authors: Huang Xiaoyi , Xu Haoran , Chu Jizheng
Published: December 2022

Choosing an accurate model order is one of the important sections in system identification. Traditionally, the model order selection of a nonlinear system depends on a predetermined model. However, it requires excess calculation and is impossible to get rid of the trouble of the structural design of the model, once the specific model was determined. A false nearest neighbor (FNN) algorithm that only relies on input-output data to estimate the model order is proposed here. Due to the FNN algorithm is sensitive to its own threshold which is a crucial constant for evaluating the model structure, Gaussian mixture model (GMM) clustering based on a genetic version of the expectation-maximization (EM) algorithm and minimum description length (MDL) criterion is developed in this paper, where the order can be determined without relying on a specific model. The GMM clustering is proposed to calculate the threshold of the FNN. Then, the genetic algorithm and MDL criteria are embedded to optimize the calculation of the EM algorithm as reduce the influence of initial values and not prone to fall into local extreme values as well. Three examples are given here to indicate the superiority of this technique: simulation of a strongly nonlinear system, isothermal polymerization process, and Van der Vusse reaction in relevant reference. Finally, some typical modeling methods are conducted to confirm the validity of this approach.
CircPDIA4 Induces Gastric Cancer Progression by Promoting ERK1/2 Activation and Enhancing Biogenesis of Oncogenic circRNAs
Authors: Shen Yue , Zhang Nasha , Chai Jie , Wang Teng , Ma Chi , Han Linyu , Yang Ming
Published: December 2022

Circular RNAs (circRNA) are a group of noncoding, covalently uninterrupted loop transcripts, most of which remain to be functionally characterized. Here, we identified circPDIA4 as an oncogenic circRNA in gastric cancer. Clinically, circPDIA4 was significantly upregulated in malignant tissues and was associated with poor survival of patients with gastric cancer. The biogenesis of circPDIA4 was mediated by the RNA-binding protein Quaking, which bound introns 2 and 4 of PDIA4 pre-mRNA to promote backsplicing of exons 3 and 4. Elevated expression of circPDIA4 promoted distant metastasis in various mouse xenograft models in vivo and accelerated cancer cell invasion in vitro. CircPDIA4 functioned through distinct oncogenic mechanisms in the cytoplasm and the nucleus. Cytoplasmic circPDIA4 bound to ERK1/2 and sustained hyperactivation of the MAPK pathway by preventing DUSP6-mediated ERK1/2 dephosphorylation. Notably, circPDIA4 depletion enhanced the sensitivity of gastric cancer cells to ERK inhibitors. In the nucleus, circPDIA4 interacted with DHX9 as a decoy and repressed its inhibitory functions on circRNA biogenesis to boost expression of multiple oncogenic circRNAs, which promoted gastric cancer progression. These findings reveal a dual tumor-promoting mechanism for circPDIA4 by regulating oncogenic circRNA biogenesis and increasing MAPK activity. CircPDIA4 should be investigated further as a potential prognostic biomarker and therapeutic target in gastric cancer.

Significance:

Quaking-regulated circPDIA4 mediates different mechanisms in the nucleus and cytoplasm that coordinate to promote progression and drug resistance in gastric cancer.
Small-molecule PTPN2 Inhibitors Sensitize Resistant Melanoma to Anti-PD-1 Immunotherapy
Authors: Zhu Zhouting , Tang Rachel , Huff Sarah , Kummetha Indrasena Reddy , Wang Lingling , Li Na , Rana Tariq M.
Published: December 2022

Although immune checkpoint inhibitors targeting T-cell immunoregulatory proteins have revolutionized cancer treatment, they are effective only in a limited number of patients, and new strategies are needed to enhance tumor responses to immunotherapies. Deletion of protein tyrosine phosphatase non-receptor type 2 (Ptpn2), a regulator of growth factor and cytokine signaling pathways, has been shown to sensitize murine B16F10 melanoma cells to IFNγ and anti-PD-1 immunotherapy. Here, we investigated the potential therapeutic utility of small-molecule PTPN2 inhibitors. Ten inhibitors were synthesized on the basis of in silico modeling and structure-based design and functionally tested in vitro and in vivo. We show that the inhibitors had little effect on B16F10 cells alone, but effectively sensitized the tumor cells to IFNγ treatment in vitro and to anti-PD-1 therapy in vivo. Under both conditions, Ptpn2 inhibitor cotreatment suppressed B16F10 cell growth and enhanced Stat1 phosphorylation and expression of IFNγ response genes. In vivo, PTPN2 inhibitor cotreatment significantly reduced melanoma and colorectal tumor growth and enhanced mouse survival compared with anti-PD-1 treatment alone, and this was accompanied by increased tumor infiltration by granzyme B+ CD8+ T cells. Similar results were obtained with representative murine and human colon cancer and lung cancer cell lines. Collectively, these results demonstrate that small-molecule inhibitors of PTPN2 may have clinical utility as sensitizing agents for immunotherapy-resistant cancers.

Significance:

To enhance the effectiveness of immunotherapies in resistant or nonresponsive cancers, it is important to develop inhibitors of enzymes that negatively influence the outcome of treatments. We have designed and evaluated small-molecule inhibitors of PTPN2 demonstrating that these compounds may have clinical utility as sensitizing agents for immunotherapy-resistant cancers.
A Large-Scale Observational Analysis of Social Media Data Reveals Major Public Misperception of the Attainability of Drastic Weight Loss by Dieting
Authors: Yom Tov Elad , Hochberg Irit
Published: December 2022

Introduction: Diet forums in social media websites provide an opportunity to glimpse the experience of different weight loss diet strategies reported by tens of thousands of individuals. Methods: We analyzed all postings with weight information from the six major Reddit weight loss diet forums (“subreddits”) as reported by forum participants. Results: Data were collected from January 2011 to April 2020 from all 55,900 users posting weight information. Average start BMI was in the overweight or obese range (26–34 kg/m2), and average goal BMI was in the normal range (21.5–24.5 kg/m2) for all subreddits. There is correlation between start BMI and goal BMI (R2 = 0.63, p < 10−10) and between planned weight loss and reported weight loss (R2 = 0.56, p < 10−10). Approximately 80% of forum participants reported a weight loss that was greater than 5% of their initial body weight. Actual reported weight loss was less than half of goal weight loss. Average reported weight loss and adherence were highest in the keto and loseit subreddits. More upvotes and fewer downvotes were associated with higher reported weight loss in five of the six subreddits. Conclusions: Despite the need for cautious interpretation of these data due to self-selection of users who updated weight loss and the possibility of unreliable weight reports, the study has several findings. Average goal BMI was in the normal weight range, demonstrating a highly unrealistic perception, in a very large lay-public cohort, of the plausibility of losing all excess weight. The success in weight loss and maintenance in self-selected individuals who continued reporting weight for many months may demonstrate the subjective value some individuals can obtain from forum participation.
Peptide Vaccine Against ADAMTS-7 Ameliorates Atherosclerosis and Postinjury Neointima Hyperplasia
Authors: Ma Zihan , Mao Chenfeng , Chen Xiao , Yang Shiyu , Qiu Zhihua , Yu Baoqi , Jia Yiting , Wu Chao , Wang Yiyi , Wang Yuhui , Gu Rui , Yu Fang , Yin Yanhui , Wang Xian , Xu Qingbo , Liu Chuanju , Liao Yuhua , Zheng Jingang , Fu Yi , Kong Wei
Published: December 2022

Background:

The metalloprotease ADAMTS-7 (a disintegrin and metalloproteinase with thrombospondin type 1 motif 7) is a novel locus associated with human coronary atherosclerosis. ADAMTS-7 deletion protects against atherosclerosis and vascular restenosis in rodents.

Methods:

We designed 3 potential vaccines consisting of distinct B cell epitopic peptides derived from ADAMTS-7 and conjugated with the carrier protein KLH (keyhole limpet hemocyanin) as well as aluminum hydroxide as an adjuvant. Arterial ligation or wire injury was used to induce neointima in mice, whereas
ApoE
-/-
and
LDLR
-/-
(LDLR [low-density lipoprotein receptor]) mice fed a high-fat diet were applied to assess atherosclerosis. In addition, coronary stent implantation was performed on vaccine-immunized Bama miniature pigs, followed by optical coherence tomography to evaluate coronary intimal hyperplasia.

Results:

A vaccine, ATS7vac, was screened out from 3 candidates to effectively inhibit intimal thickening in murine carotid artery ligation models after vaccination. As well, immunization with ATS7vac alleviated neointima formation in murine wire injury models and mitigated atherosclerotic lesions in both hyperlipidemic
ApoE
-/-
and
LDLR
-/-
mice without lowering lipid levels. Preclinically, ATS7vac markedly impeded intimal hyperplasia in swine stented coronary arteries, but without significant immune-related organ injuries. Mechanistically, ATS7vac vaccination produced specific antibodies against ADAMTS-7, which markedly repressed ADAMTS-7–mediated COMP (cartilage oligomeric matrix protein) and TSP-1 (thrombospondin-1) degradation and subsequently inhibited vascular smooth muscle cell migration but promoted re-endothelialization.

Conclusions:

ATS7vac is a novel atherosclerosis vaccine that also alleviates in-stent restenosis. The application of ATS7vac would be a complementary therapeutic avenue to the current lipid-lowering strategy for atherosclerotic disease.
Temporal Mapper: Transition networks in simulated and real neural dynamics
Authors: Zhang Mengsen , Chowdhury Samir , Saggar Manish
Published: December 2022

Characterizing large-scale dynamic organization of the brain relies on both data-driven and mechanistic modeling, which demands a low versus high level of prior knowledge and assumptions about how constituents of the brain interact. However, the conceptual translation between the two is not straightforward. The present work aims to provide a bridge between data-driven and mechanistic modeling. We conceptualize brain dynamics as a complex landscape that is continuously modulated by internal and external changes. The modulation can induce transitions between one stable brain state (attractor) to another. Here, we provide a novel method—Temporal Mapper—built upon established tools from the field of topological data analysis to retrieve the network of attractor transitions from time series data alone. For theoretical validation, we use a biophysical network model to induce transitions in a controlled manner, which provides simulated time series equipped with a ground-truth attractor transition network. Our approach reconstructs the ground-truth transition network from simulated time series data better than existing time-varying approaches. For empirical relevance, we apply our approach to fMRI data gathered during a continuous multitask experiment. We found that occupancy of the high-degree nodes and cycles of the transition network was significantly associated with subjects’ behavioral performance. Taken together, we provide an important first step toward integrating data-driven and mechanistic modeling of brain dynamics.
The Extremely Wet May of 2021 in the United Kingdom
Authors: Christidis Nikolaos , Stott Peter A.
Published: December 2022

Human influence and persistent low pressure are estimated to make extreme May rainfall in the United Kingdom, as in year 2021, about 1.5 and 3.5 times more likely, respectively.
GeroCast: Using podcasting to deliver living cases in gerontology education
Authors: Auais Mohammad , Cameron Julie , Turnnidge Jennifer , Dalgarno Nancy , Kolomitro Klodiana , Pelland Lucie
Published: December 2022

Objective:

To describe the creation of an educational podcast with ‘living cases’ of older adults to support students’ learning on a gerontology course and report on students’ evaluation of the project.

Setting:

Gerontology course in a graduate programme.

Method:

We developed a podcast series based on interviews with older adults in the community following recent guidelines for creating educational podcasts. The podcast episodes were used in a case-based group assignment to work on during the course and to present findings at the end.

Evaluation:

Student experiences were evaluated using a mixed-methods survey.

Results:

From November 2019 to January 2021, case-based podcasts, averaging 17 minutes in length, were created and evaluated. Most students found the content of the podcasts relevant to working with older adults and increased their understanding of the issues facing members of that population. Qualitative analysis of the survey findings found that the overall strengths of the podcasts were that they were well structured, provided an authentic, real-world experience, allowed listeners to experience an innovative teaching strategy, promoted reflection, and encouraged students to consider a future career working with older adults. Students also recommended ways to improve the podcasts.

Conclusion:

Delivering living case studies using podcasts is a feasible, inexpensive and effective teaching method for improving physiotherapy students’ attitudes towards caring for older adults. Students enjoyed learning via the podcasts and found them a valuable way to better understand the issues facing older adults. The living case podcasts could have broad applicability to other aging and health courses.
Opus Dei, Opus Hominum: The Trinity, the Four-Point Hypothesis, and the Eucharist
Authors: Schlesinger Eugene
Published: December 2022

This article draws upon the theology of Bernard Lonergan, particularly as expanded upon by Robert Doran in order to provide a theological basis for the claim that ‘the Eucharist makes the church.’ Doran’s use of the so-called ‘four-point hypothesis’ from Lonergan’s trinitarian theology provides the basis of a revised articulation of the psychological analogy for the Trinity, this one drawn from the supernatural order. A consideration of Lonergan’s theologies of eucharistic sacrifice and of the mystical body of Christ in concert with the revised psychological analogy affords a framework for understanding the Eucharist’s role in recruiting humanity into the mission of God and constituting the church as Christ’s body.
Introducing ‘resonance’: Revisioning the relationship between youth and later life in women born 1939–52
Authors: Tinkler Penny , Fenton Laura , Cruz Resto
Published: December 2022

This article proposes ‘resonance’ as a fruitful way of conceptualising the relationship between youth and later life and reflecting on its significance: resonance is how a person’s ‘youth’ is lived with in the present of their later life. Resonance revisions youth, engaging with the complexity of its presence in the lifecourse. Relinquishing a preoccupation with continuity and linearity, youth seen from the vantage point of later life contributes fresh insights into what matters for people and how. This conceptualisation emerged from a qualitative study of women born 1939–52 which revealed that experiences attributed to the teens and early twenties have a presence in a person’s later life in ways unrecognised in established approaches, namely longitudinal life-course studies and socio-cultural approaches. These resonances are often historically inflected such that some cohorts may live with their youth in later life in ways that distinguish them from their predecessors and successors.
Tourism and Troubles: Effects of Security Threats on the Global Travel and Tourism Industry Performance
Authors: Akamavi Raphaël K. , Ibrahim Fahad , Swaray Raymond
Published: December 2022

Literature on the effects of security threats such as terrorism, political instability, and geopolitical power-plays on travel and tourism has produced mixed results with scant attention paid to the spillover effects on the tourism economy (e.g., employment, leisure expenditure, travel, and tourism services’ contribution to gross domestic product). This study provides a conceptual framework for the transmission of direct, indirect, and induced spillover effects of security threats on travel and tourism service industries. It uses rigorous methodological design and non-spatial and spatial panel-data analyses to examine the effects of security threats on tourism demand and economy. The conceptual framework and results of spatial panel data provide novel insights into security threats’ spillover effects on spatial inter-connectivity in the tourism service industry. The results show that security threat indices have significant negative impacts on tourist receipts, but they also contribute positively to employment, leisure expenditure, and tourist arrivals. Our conceptual model and substantial findings will inform both policymakers and future research.
Black Women’s Sexual Assertiveness and Satisfaction: The Role of the Superwoman Schema
Authors: Perkins Tiani R. , Aleibar Desiree , Leath Seanna , Pittman Jami C.
Published: December 2022

Although extant research highlights the detrimental effects of the Superwoman Schema (SWS) on Black women’s physical and psychological well-being, researchers have yet to examine the implications of SWS endorsement on Black women’s sexual attitudes and behaviors. As a culturally salient racialized gender schema that reifies Black women’s supposed superhuman emotional and physical strength, to what extent does endorsement of the SWS contribute to Black women’s reported sexual assertiveness and satisfaction? In the present work, 406 Black women completed an online survey measuring their endorsement of the SWS, as well as their sexual assertiveness and sexual satisfaction. SWS dimensions moderated the association between sexual assertiveness and sexual satisfaction. Findings from the present study highlight the importance of considering culturally salient racialized gender schemas when examining Black women’s sexual attitudes and behaviors.
StateIO - Open Source Economic Input-Output Models for the 50 States of the United States of America
Authors: Li Mo , Ferreira João Pedro , Court Christa D. , Meyer David , Li Mengming , Ingwersen Wesley W.
Published: December 2022

Subnational input–output (IO) tables capture industry- and region-specific production, consumption, and trade of commodities and serve as a common basis for regional and multi-regional economic impact analysis. However, subnational IO tables are not made available by national statistical offices, especially in the United States (US), nor have they been estimated with transparent methods for reproducibility or updated regularly for public availability. In this article, we describe a robust StateIO modeling framework to develop state and two-region IO models for all 50 states in the US using national IO tables and state industry and trade data from reliable public sources such as the US Bureau of Economic Analysis. We develop 2012-2017 state IO models and two-region IO models at the BEA summary level. The two regions are state of interest and rest of the US. All models are validated by a series of rigorous checks to ensure the results are balanced at state and national levels. We then use these models to calculate a 2012–2017 time series of macro economic indicators and highlight results for 11 states that have distinct economies with respect to size, geography, and industry structure. We also compare selected indicators to state IO models created by popular licensed and open-source software. Our StateIO modeling framework is consolidated in an open-source R package, stateior, to ensure transparency and reproducibility. Our StateIO models are US-focused, which may not be transferrable to international accounts, and form the economic base of state versions of the US environmentally-extended IO models.
Primary non-functional pancreatic paraganglioma: A case report and review of the literature
Authors: Zhao Zhanxue , Guo Yan , Liu Linxun , Zhang Linming , Li Shuai , Yang Jinyu
Published: December 2022

Primary pancreatic paragangliomas are rare. They are mainly non-functional tumours that lack typical clinical manifestations. Definite diagnosis relies on histopathology and immunohistochemistry, and the main treatment is surgery. We report here a case of primary, non-functional, pancreatic paraganglioma in a 49-year-old woman. The tumour was approximately 5.0 × 3.2 ×4.7 cm in size and located in the pancreatic neck and body. We undertook 3D laparoscopic complete resection of the tumour. The patient developed a pancreatic fistula (biochemical leak) post-surgery, but she recovered and was discharged from hospital 11 days after surgery. We describe this case study and briefly summarize previous related reports.
Long Sleep Duration Increases the Risk of All-Cause Mortality Among Community-Dwelling Older Adults With Frailty: Evidence From NHANES 2009–2014
Authors: Chen Mingzhuang , Lu Chao , Zha Jingru
Published: December 2022

Objectives: The aim of this study was to determine the effect of sleep duration on all-cause mortality among older adults with frailty. Methods: The prospective cohort study included 5705 community participants aged 60 or above in the National Health and Nutrition Examination Survey (NHANES). Health indicators were selected in the NHANES to obtain the frailty index and sleep duration. The risk of all-cause mortality was estimated by a Cox proportional hazard model. Results: During the follow-up, long sleep duration was associated with higher all-cause mortality (adjusted HR = 1.28, 95% CI 1.03–1.59). The hazard of all-cause mortality was the lowest from the beginning of sleep until sleep duration reached 5.8 hours among older adults with frailty. Discussion: Long sleep duration was associated with higher all-cause mortality among older adults with frailty. There was a U-shaped relationship between sleep duration and all-cause mortality.
Health technology, quality and safety in a learning health system
Authors: Borycki Elizabeth M. , Kushniruk Andre W.
Published: December 2022

Health technology quality and safety is an important issue for health informatics (i.e. digital health) professionals. Health technologies have been used to (1) collect data that can be analyzed to improve the quality and safety of healthcare activities and (2) re-engineer and/or automate error-prone processes. Health technologies are also able to introduce new types of errors (i.e. technology-induced errors) and have been implicated in propagating errors across digital health ecosystems. To develop a learning health system, health technologies need to be considered in terms of how they can improve the quality and safety of health activities traditionally carried out by humans (patients and health professionals) and also how the technology’s quality and safety can be improved. This article outlines how this can be done by integrating evidence from health informatics research into practice using a learning health systems approach.
Henry Breault: Construction of a naval hero
Authors: Walker Ryan C.
Published: December 2022

United States Navy sailors are excellent subjects for personal microhistories due to the volume of surviving official documentation in the form of their Official Military Personnel Files. This article deconstructs a grand narrative surrounding Henry Breault, the only enlisted sailor to receive his Medal of Honor while serving aboard a submarine. Breault experienced contemporary enshrinement, a long period of sporadic interest, and a later iconographic construction into a submarine folk hero in the present day. Breault has come to represent unnamed submariners, who are expected to perform in the same fashion with no expectation of similar commendation. It is found that Breault is still representative of sailors, but as an ordinary man who acted in an extraordinary manner when circumstance required. The methodology provides insight into Breault's relationship and connection to greater society as a submariner and as a highly decorated sailor in the interwar period.
Reinventing democracy in Paris and Madrid: Sylvain George’s Benjaminian urban montage
Authors: O'Shaughnessy Martin
Published: December 2022

Sylvain George is one of the most interesting French filmmakers working today. He has made a series of poetic, experimental documentaries about migrants and refugees around Calais and has brought together migrant figures and Occupy movements in his two ‘city symphonies’, Vers Madrid (The Burning Bright) (2012) and Paris est une fête (2018). The principal theoretical influence on George's cinema is the work of Walter Benjamin. This article shows how certain essential Benjaminian concepts can help us understand George's films as they seek productive alignments and collisions between contemporary mobilisations and the history embedded in urban spaces. But it also argues that, even as they point towards a renewal of fundamental European political traditions, they show that a politics no longer limited by national belonging remains to be found.
An integrated data-driven surrogate model and thermofluid network-based model of a 620 MWe utility-scale boiler
Authors: Rawlins Brad Travis , Laubscher Ryno , Rousseau Pieter
Published: December 2022

An integrated data-driven surrogate model and one-dimensional (1-D) process model of a 620 [ MWe] utility scale boiler is presented. A robust and computationally inexpensive computational fluid dynamic (CFD) model of the utility boiler was utilized to generate the solution dataset for surrogate model training and testing. Both a standard multi-layer perceptron (MLP) and mixture density network (MDN) machine learning architectures are compared for use as a surrogate model to predict the furnace heat loads and the flue gas inlet conditions to the convective pass. A hyperparameter search was performed to find the best MLP and MDN architecture. The MDN was selected for surrogate model integration since it showed comparable accuracy and provides the ability to predict the associated uncertainties. Validation of the integrated model against plant data was performed for a wide range of loads, and critical results were predicted within 5–8% of the measured results. The validated model was subsequently used to investigate the effects of using a poor-quality fuel for the 100% maximum continuous rating load case. The uncertainties predicted by the surrogate model were propagated through the integrated model using the Monte Carlo technique, adding valuable insight into the operational limits of the power plant and the uncertainties associated with it.
Techno-economic feasibility analysis of grid-connected residential PV systems in Algeria
Authors: Mohand Kaci Ghania , Mahrane Achour , Ghedamsi Kaci , Chikh Madjid
Published: December 2022

Small-scale photovoltaic (PV) power systems have been proven to be successful in generating electricity, conserving fossil fuels, and reducing greenhouse gas emissions in the residential sector, which is one of the largest consumers of energy. In Algeria, to reduce energy consumption in this sector, the authorities are considering implementing a policy that would encourage grid-connected residential PV systems. This paper presents a techno-economic assessment of grid-connected residential PV systems in four climate zones in Algeria. This work was performed using HOMER software for two different PV system configurations, grid/PV and grid/PV/battery. The technical performances of the considered systems were evaluated through the assessment of the self-consumption and self-sufficiency, while the net present value (NPV), internal rate of return (IRR), profitability index (PI), and discounted payback period (DPBP) were used to determine their feasibility. A sensitivity analysis was carried out to evaluate the effects of feed-in tariff (FiT), battery costs, and PV array capacity on the profitability of the systems. The results revealed that the grid/PV systems are technically and economically feasible in all of the four climate zones. For the grid/PV/battery systems, the grant of battery costs and the development of a regional FiT system are recommended. This article provides a tool for policymakers to assess the technical and financial performance of residential solar PV systems to develop adequate policy supports and tariff structures for Algeria.
Always liminal, always learning: Why community learning is needed, and how to start
Authors: Beech Nic
Published: December 2022

This article sets out the case that there is a conflation of personal and situational liminality in the music industry. The response to this needs to include greater dynamism and development both of musical identities and innovations in the production and business of music. However, the confluence of liminalities produces vulnerabilities and precarities which militate against learning and innovation and lean toward stasis. I offer an alternative way forward, which adopts a different conceptualization of vulnerability and discusses how a situated learning approach can be used to develop socially enabled resilience.
Correction of Anticoagulant Therapy in Patients with Severe COVID-19 Virus Infection Using a Thrombodynamics Coagulation Assay
Authors: Vuimo Tatiana S. , Tsarenko Sergey V. , Filimonova Elena V. , Seregina Elena A. , Karamzin Sergey S.
Published: December 2022

Background

The average frequency of thrombosis in patients with COVID-19 is still high despite low molecular weight heparin (LMWH) prophylactic. Global hemostasis assays, particularly thrombodynamics (TD), known to be sensitive to both hypercoagulation and heparin effects, could potentially be useful for individual management of anticoagulant therapy.

Methods

A total of 74 patients with lung involvement >50% were randomized into two groups: Group A (44 patients) received weight-based dosing of LMWH, and Group B (30 patients) received the first LMWH dose by a weight-based dosing protocol and then received an adjusted dose based on TD daily results. The endpoints of the study were thrombosis and bleeding as well as discharge or death of the patient.

Results

The incidence of thrombosis was 3 times lower in Group B under TD control compared to Group A without TD control: 7% versus 23 respectively ( p = .05). The relative risk of thrombosis if the average clot growth rate V in TD exceeded the threshold value of 25 μm/min was 14.3 ( p = .0005, 95% confidence interval 3.2-63.7). There were no clinically significant bleeding episodes in Group B while there were 7% in unregulated Group A. Mortality in Group B under TD control was lower than that in Group A without control: 27% versus 36%, respectively ( p = .13).

Conclusions

The dosing LMWH under thrombodynamics control in severe patients with COVID-19 allows for a significant reduction in thrombotic complications. Long-term hypercoagulation revealed by thrombodynamics (3 and more days) is a strong predictor of thrombosis (AUC = 0.83).
Suppressing thermal stress in the vicinity of a circular nano-inhomogeneity via the mechanism of size effects
Authors: Huang Haojie , Xing Shichao , Song Kun
Published: December 2022

Thermal stress is one of the main factors threatening the reliability of nanocomposites. In this paper, we propose a set of interfacial conditions to simulate the interfacial phonon scattering and interfacial elasticity in the nanocomposite, and then obtain closed-form solutions for the thermal-elastic fields around the circular nano-inhomogeneity. The results show that the interfacial thermal stress within matrix is more sensitive to interfacial phonon scattering than that in nano-inhomogeneity, while the size change of inhomogeneity has greater impact on the stress of nano-inhomogeneity than that of the matrix. In view of the significant effects of thermal conductivities and thermal expansion coefficients on the thermal stress around inhomogeneity, the maximum von Mises stress is reduced up to three orders of magnitude by adjusting these parameters. More importantly, the thermal stresses within matrix and inhomogeneity can be, respectively, designed as “zero” even though the nanocomposite is subjected to a large thermal loading, which is viewed as an update mechanism of “neutral inhomogeneity.” Our work provides guidance for the design of nanocomposites and has important potential applications.
Knowledge of automated journalism moderates evaluations of algorithmically generated news
Authors: Jang Wonseok (Eric) , Kwak Dae Hee , Bucy Erik
Published: December 2022

Drawing on propositions from the HAII-TIME (Human–artificial intelligence [AI] Interaction and the Theory of Interactive Media Effects) and Persuasion Knowledge Model, this study examines how knowledge of automated journalism (AJ) moderates the evaluation of algorithmically generated news. Experiment 1 demonstrates the utility of process-related knowledge in user evaluations of agency: individuals with little knowledge of AJ prefer attributions of human authorship over news stories attributed to algorithms, whereas individuals with high AJ knowledge have an equal or stronger preference for news that is described as algorithmically generated. Experiment 2 conditions these effects to show how prior characterizations of AJ—whether more machine- or human-like—shape evaluations of algorithmically generated news contingent on user age and knowledge level. Effects are found for differing age groups at lower levels of AJ knowledge, where machine-like characterizations enhance evaluations of algorithmically generated news for younger users but ascribing human-like traits enhances evaluations of automated news for older users.
Managing newly arrived children's double transition: Towards inclusionary practices in rural Swedish preschools
Authors: Löthman Charlotte
Published: December 2022

This study examines preschool practitioners’ accounts of managing newly arrived children's double transition into rural preschools with little previous experience of migration. The narratives are analysed through Bakhtin's theory of dialogism. The analysis reveals that the practitioners at first found the migrant children's double transition troublesome and challenging. Eventually, they started to reflect critically on their own culturally endorsed beliefs and practices, and took a dialogical approach that helped them to adjust their practices to the needs of the newly arrived children. The results show that in order to support the inclusion of the migrant children, the practitioners themselves had to go through a process that included a change of mindset and a change of practice. Hence, to manage the children's double transition, the practitioners needed to make a dual adjustment.