bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation Method of Mixed Teaching Efficiency of College Teachers Based on Kirkpatrick Model
Authors: Liang Fenglan , Shen Weiwei , Shi Hongwei , Zheng Buqin
Published: August 2022

Online teaching has become more prevalent in recent years as a result of the process of digitization and adaptation to the times. Classroom instruction is no longer just conducted in person offline. Online education has received a lot of promotion, especially in the wake of the epidemic’s effects, and has evolved into a blended teaching model that combines the two modes. The old system of measuring the effectiveness of teaching is no longer reliable or scientific in assessing the new blended teaching model, and it has many flaws. A perfect system for evaluating the effects of blended learning must therefore be built. In order to more accurately assess the teaching impact of the blended teaching model, this study aims to build a more comprehensive system for evaluating blended teaching effects. This paper introduces the Kirkpatrick four-level evaluation model, which plays a significant role in the evaluation field, in order to achieve this goal. The experiments in this study compared the Kirkpatrick model with the AHP, which is frequently used in the evaluation. Online, offline, and blended teaching models were the subject of an experimental investigation. The experimental results demonstrated that each index combination’s weights in the Kirkpatrick model and the AHP model of the blended teaching effect evaluation system were fairly close to one another. The evaluation indicators all center on the assessment of practical ability after class, which is consistent with their focus. The innovation evaluation of course papers has the highest weight, and the weight of evaluation indicators is greater than 0.15; the Kirkpatrick model has the lowest weight of the number of platform logins, with a weight value of 0.011, and the evaluation index of the teaching effect evaluation system based on AHP.
Research on Resource Allocation Method of Integrated Avionics System considering Fault Propagation Risk
Authors: Zhao Changxiao , Zhang Wei , Dong Fangzheng , Dai Jun , Dong Lei
Published: August 2022

The integrated modular avionics (IMA) system has coupled cross-linked support characteristics between physical resource entities and logical functions, and the existing resource allocation methods, which mainly consider system performance and resource utilization, do not consider the associated impact of fault propagation among resource entities. Aiming at the fault propagation risk in the resource allocation process of the IMA system, a hierarchical model of the IMA system is established. The fault propagation behavior caused by coupling association during the physical realization of the function layer logical architecture is analyzed, and the impact of different resource allocation methods on the fault propagation behavior is determined. Secondly, resource capacity constraints are established according to the resource requirement for hosted function, and the fault propagation risk model of the IMA system is constructed by considering the fault propagation impact factor, the relative importance of nodes, and the function safety criticality. The resource allocation method is evaluated according to the fault propagation risk model, and a heuristic algorithm is applied to optimize the resource allocation method of the IMA system. The simulation results show that the average propagation probability of the optimized resource allocation scheme decreases by 17.4%, and the overall fault propagation risk of the resource network decreases by 50.3%, indicating that the proposed resource allocation method can effectively improve the safety of the IMA system.
Mixed Ownership Reform of State-Owned Enterprises and R&D Investment
Authors: Luo Haohan , Wu Xiao , Wu Ying
Published: August 2022

State-owned enterprise (SOE) reforms may play a vital role in R&D investment. This paper investigates the impact of mixed ownership reform of SOEs in China on R&D investment. Using a large sample of Chinese SOEs for the 2009–2018 period, we find that the reform has a positive effect on R&D investment. The result is robust to a battery of robustness tests and more prominent for firms with non-state-owned large shareholders holding more shares relative to state-owned large shareholders, and for firms with less stress from local officials pursuing political promotion. Furthermore, we find that to compensate for the adverse impact of R&D on the political promotion of the CEO, non-state-owned large shareholders allow the CEO to increase perk consumption. Our study suggests that the ongoing mixed ownership reform in China improves the SOEs’ efficiency.
Conventional Neural Network-Based Radio Frequency Fingerprint Identification Using Raw I/Q Data
Authors: Yang Tian , Hu Su , Wu Weiwei , Niu Lixin , Lin Di , Song Jiabei
Published: August 2022

Radio frequency (RF) fingerprint identification is a nonpassword authentication method based on the physical layer of communication devices. Deep learning methods have thrown new light on RF fingerprint identification. In this paper, a conventional neural network- (CNN-) based RF identification model is proposed. The CNN models are designed to be lightweight. Raw data that reflects the characteristics of theIchannel, theQchannel, and the 2-dimensionalI+Qdata is successively fed into a CNN model. Therefore, three submodels are generated. The final predictive labels are determined by the results of the three submodels through a voting scheme. Experimental results have demonstrated that in the SNR setting at 5 dB, the final recognition accuracy of four transmit devices could achieve as high as 97.25%, while the identification accuracies based on theIchannel data,Qchannel data, andI+Qchannel data are 94.5%, 95%, and 94.5%, respectively. The training time for the 4 devices is around 30 seconds.
Numerical Analysis of Nasal Flow Characteristics with Microparticles
Authors: Liu Yi , Sun Wan Lin
Published: August 2022

This study was to investigate the airflow characteristics in nasal cavity under different conditions and analyze the effects of different respiratory intensity, particle diameter, and particle density on the deposition of particles carried by airflow in the nasal cavity, respectively. The three-dimensional geometric model of the nasal cavity was established based on typical medical images. The SST k-ω turbulence model in the computational fluid dynamics (CFD) was used to simulate the airflow in the nasal cavity, and the deposition of particles in the airflow was analyzed with the Lagrange discrete phase model. The results showed that the air in the nasal cavity flows in the left and right nasal passages through the perforation in front of the nasal septum and forms a vortex structure at the perforation site, and the particle deposition efficiencies (DE) under perforation nasal cavity are higher than that under normal nasal cavity. Different parameters had different effects on the particle DE. The results showed that the DE of particles with smaller size (≤2.5 μm) is lower; the higher the respiration intensity, the greater the influence on the DE of the larger particle size; and the larger particle density (>1550 kg·m−3) has little effect on the DE of larger particle size (DP = 10 μm). The results agree well with the corresponding research data.
Determining the Optimal Cut-Off Values of Serum E2 and FSH for Evaluating the Menopausal Status of Breast Cancer Patients in a Southern Chinese Population
Authors: Yang Lu , Li Rucai , Yu Mengsi , Huang Fen , Zeng Jiangzheng , Lu Yanda , Yang Changcheng
Published: August 2022

Background. Chemotherapy-induced amenorrhea (CIA) is one of universal phenomena in breast cancer (BC) patients, and it causes difficulties in evaluating the actual menopausal status which is important for the oncologists to choose appropriate treatment. Currently, serum estradiol (E2) and follicle-stimulating hormone (FSH) levels are the most commonly used clinical parameters for the assessment of menopausal status in BC patients. However, the optimal cut-off points of serum E2 and FSH have little been explored in southern Chinese population. Objective. This study is aimed to determine the optimal cut-off values of the serum E2 and FSH levels for evaluating the menopausal status of BC patients in a southern Chinese population. Methods. A retrospective analysis was done among a total of 206 patients with BC from a southern Chinese area. The data of serum E2, FSH, and luteinizing hormone (LH) levels were collected and analyzed for the comparison purpose. The receiver-operating curve (ROC) was generated to assess the specificity and sensitivity of the three biomarkers in discriminating the menopausal status of BC patients. The optimal cut-off values were determined according to the Youden index and then compared with the recommended reference values by the Chinese Anti-cancer Association (CACA) and those recommended by the manufacturers. Results. The areas under the ROC curves (AUCs) of E2, FSH, and LH were 0.846 (95% CI: 0.790-0.903), 0.781 (95% CI: 0.714-0.847) and 0.608 (95% CI: 0.526-0.690), respectively. The optimal cut-off values were 130.0 pg/mL for E2, 23.325 IU/L for FSH, and 11.625 IU/L for LH with a maximum of the Youden index. When E2, FSH, and LH were used in combination for ROC analysis, the AUC increased to 0.847 (95% CI: 0.790-0.904), which was higher than that of any other biomarker alone. In this study, the sensitivity and specificity of E2 and FSH were 91.6% and 73.70% and 94.4% and 58.6%, respectively, in comparison with 85.0% and 75.80% and 76.6% and 65.7% according to the CACA-recommended cut-off points, or 92.5% and 68.7% and 96.3% and 53.5% according to the manufacturer recommended cut-off points. Conclusion. Considering the sensitivity and specificity of serum E2 and FSH for assessing the menopausal status, the optimal cut-off values determined in the present study were similar to the manufacturer’s recommendations, but obviously superior to the cut-off points suggested by CACA. These cut-off points calculated in this study seem to be valuable in southern Chinese population and might be used by clinicians to make a correct medical decision for BC patients who would benefit from endocrine therapy of aromatase inhibitor (AI).
An Initial Study on Automated Acupoint Positioning for Laser Acupuncture
Authors: Lan Kun-Chan , Lee Chang-Yin , Lee Guan-Sheng , Tsai Tzu-Hao , Lee Yu-Chen , Wang Chih-Yu
Published: August 2022

Acupuncture plays an important role in traditional Chinese medicine (TCM) and is one kind of an inexpensive and effective treatment. However, some people might be reluctant to receive acupuncture treatment due to fear of pain. Laser acupuncture, thanks to its painless and infection-free advantages, has recently become an alternative choice to traditional acupuncture. The accuracy of acupuncture point positioning has a decisive influence on the quality of laser acupuncture. In this study, built on top of our prior work, we proposed a low-cost automated acupoint positioning system for laser acupuncture. By integrating several machine learning algorithms and computer vision techniques, we design and implement a robot-assisted laser acupuncture system on top of a smartphone. Our contributions include the following: (a) development of an effective acupoint estimation algorithm with a localization error less than 5 mm; (b) implementation of a smartphone-controlled automated laser acupuncture system with lift-thrust function, as a point-of-care device, that can be used by patients to relieve their symptoms at home.
Hybrid Model for Method for Short-Term Traffic Flow Prediction Based on Secondary Decomposition Technique and ELM
Authors: Zhao LeiNa , Wen XinYu , Shao YiMing , Tang ZhenYu
Published: August 2022

Strong nonstationary and nonlinearity are the main characteristics in the short-term traffic flow data, which frustrates traditional methods (e.g., autoregressive integrated moving average and deep belief network) to provide a satisfactory prediction. To address the above problem, a novel forecasting method, which is composed of a secondary decomposition technique and extreme learning machine, is proposed in this study. This developed technique is a hybrid of time-varying filtering-empirical mode decomposition (TVF-EMD) and local mean decomposition (LMD), which not only can effectively handle the above complex data features by decomposing them into several regular subsets but also produce the smoother subseries that is beneficial to prediction. To verify the effectiveness of the proposed method, a case study based on two groups of actual traffic flow data with different characteristics is performed. Meanwhile, several single models and hybrid models based on the other decomposition methods (e.g., EMD and variational mode decomposition) are considered benchmark models. The experimental results reveal that the proposed model presents the best performance. For example, compared with the TVF-EMD-based method, the improvement by the proposed approach reaches 33.3% in terms of the evaluation criterion of mean absolute percentage error.
GaitRec-Net: A Deep Neural Network for Gait Disorder Detection Using Ground Reaction Force
Authors: Pandey Chandrasen , Roy Diptendu Sinha , Poonia Ramesh Chandra , Altameem Ayman , Nayak Soumya Ranjan , Verma Amit , Saudagar Abdul Khader Jilani
Published: August 2022

Walking (gait) irregularities and abnormalities are predictors and symptoms of disorder and disability. In the past, elaborate video (camera-based) systems, pressure mats, or a mix of the two has been used in clinical settings to monitor and evaluate gait. This article presents an artificial intelligence-based comprehensive investigation of ground reaction force (GRF) pattern to classify the healthy control and gait disorders using the large-scale ground reaction force. The used dataset comprised GRF measurements from different patients. The article includes machine learning- and deep learning-based models to classify healthy and gait disorder patients using ground reaction force. A deep learning-based architecture GaitRec-Net is proposed for this classification. The classification results were evaluated using various metrics, and each experiment was analysed using a fivefold cross-validation approach. Compared to machine learning classifiers, the proposed deep learning model is found better for feature extraction resulting in high accuracy of classification. As a result, the proposed framework presents a promising step in the direction of automatic categorization of abnormal gait pattern.
Experimental Study on Mechanical Properties of Rebar in Steel Half‐Grouted Sleeve Connections with Construction Defects
Authors: Chen Dong , Zhang Zhiyong , Liu Xiaozhen , Wang Qiong , Zhao Baojun , Ren Gang , Wang Changjun
Published: August 2022

A prefabricated concrete structure is a building structure designed for sustainability and low comprehensive carbon emission. The grouted sleeve splice is a major connection method for prefabricated concrete structures. However, construction defects occur easily in the grouted sleeve splice connection at construction sites because of complex construction environments and the high connection accuracy. To determine the influence of rebar in steel half‐grouted sleeve connections with construction defects, investigations were conducted using four different test groups (rebar offset, rebar bended, insufficient fluidity of grout, and control group). The load—displacement curve and load—stress curve were analyzed on 24 different specimens through uniaxial tension experiments. The experimental results showed that rebar fracture was the failure of specimens. The load—displacement curves consisted of elastic, yield, strength, and tight stages. The curves were similar to rebar under uniaxial tension, except for the rebar bended group. The axial stress and circumferential stress on the sleeve surface consistently followed a linear response before the specimen yield, whereas the axial stress and circumferential stress showed a rebound response after the specimen yielded. Different finite element models were established based on the different defects. Compared with the experimental results, the finite element analysis results coincided with those of the experimental results, and the errors were within 8% to evaluate the performance of steel half‐grouted sleeve connections in construction.
River Extraction from Remote Sensing Images in Cold and Arid Regions Based on Attention Mechanism
Authors: Wang Hailong , Shen Yu , Liang Li , Yuan Yubin , Yan Yuan , Liu Guanghui
Published: August 2022

The extraction of rivers in cold and arid regions is of great significance for applications such as ecological environment monitoring, agricultural planning, and disaster warning. However, there are few related studies on river extraction in cold and arid regions, and it is still in its infancy. The accuracy of river extraction is low, and the details are blurred. The rapid development of deep learning has provided us with new ideas, but with lack of corresponding professional datasets, the accuracy of the current semantic segmentation network is not high. This study mainly presents the following. (1) According to the characteristics of cold and arid regions, a professional dataset was made to support the extraction of rivers from remote sensing images in these regions. (2) Combine transfer learning and deep learning, migrate the ResNet-101 network to the LinkNet network, and introduce the attention mechanism to obtain the AR-LinkNet network, which is used to improve the recognition accuracy of the network. (3) A channel attention module and a spatial attention module with residual structure are proposed to strengthen the effective features and improve the segmentation accuracy. (4) Combining dense atrous spatial pyramid pooling (DenseASPP) with AR-LinkNet network expands the network receptive field, which can extract more detailed information and increase the coherence of extracted rivers. (5) For the first time, the binary cross-entropy loss function combined with the Dice loss function is applied to river extraction as a new loss function, which accelerates the network convergence and improves the image quality. Validation on the dataset shows that, compared with typical semantic segmentation networks, the method performs better on evaluation metrics such as recall, intersection ratio, precision, and

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score, and the extracted rivers are clearer and more coherent.
Deep Learning-Based Localization with Urban Electromagnetic and Geographic Information
Authors: Wang Wenyu , Li Baozhu , Huang Zhen , Zhu Lei
Published: August 2022

There is a growing demand for localization of illegal signal sources, aiming to guarantee the security of urban electromagnetic environment. The performance of traditional localization methods is limited due to the non-line-of-sight (NLOS) propagation and sparse layouts of sensors. In this paper, a deep learning-based localization method is proposed to overcome these issues in urban scenarios. Firstly, a model of electromagnetic wave propagation considered with geographic information is proposed to prepare reliable datasets for intelligent cognition of urban electromagnetic environment. Then, this paper improves an hourglass neural network which consists of downsampling and upsampling layers to learn the propagation features from sensing data. The core modules of VGG and ResNet are, respectively, utilized as feature extractors in downsampling. Moreover, this paper proposes a weighted loss function to expand the attention on position features, in order to improve the performance of localization with sparse layouts of sensors. Representative numerical results are discussed to assess the proposed method. ResNet-based extractor performs more efficiently than VGG-based extractor, and the proposed weighted loss function increases the localization accuracy by more than 50%. Additionally, the established geographic model supports qualitative and quantitative evaluation of the robustness with varied degree of NLOS propagation. Compared with other deep learning-based algorithms, the proposed method presents the more robust and superior performance under severe NLOS propagation and sparse sensing conditions.
Research on the Innovation of Teaching Mode of Ideological and Political Theory Courses in Colleges and Universities Driven by VR Technology Based on Deep Learning
Authors: Dong Gaowei
Published: August 2022

In order to study the innovative teaching mode of ideological and political courses in colleges and universities, we develop the motivation of students’ active learning and enable students to establish good ideological and moral quality and correct outlook on life, values, and society, and the whole teaching process of the course is analyzed. Through the analysis of students’ learning motivation and the correlation between the students’ learning efficiency and teaching mode, this study finally finds that the VR technology-driven teaching mode can promote students to think and explore the red culture. Finally, it is found that the VR technology-driven teaching mode can promote the interaction between teachers and students, students and students, and jointly think and explore the red culture. Through the innovation of the VR technology-driven teaching mode of ideological and political courses in colleges and universities through in-depth learning, students’ enthusiasm for autonomous learning can be greatly improved and their ideological character can be better cultivated. It also has innovative significance and a research value for the development of China’s education field.
KLHL14: A Novel Prognostic Biomarker and Therapeutic Target for Ovarian Cancer
Authors: Wang Xingwei , Sun Ru , Hong Xia , Chen Chen , Ding Yan
Published: August 2022

Ovarian cancer (OV) is a gynaecological malignancy that poses a serious risk to the health status of women. To date, effective molecular markers are unavailable for the diagnosis and management of ovarian malignancies. In this study, we aimed to investigate the molecular markers associated with the development of this cancer. We used bioinformatic analysis to determine the molecules and genes related to ovarian cancer using the gene expression profiling interactive analysis (GEPIA) and the cancer genome Atlas (TCGA) databases. In addition, we examined the genes and mechanisms underlying ovarian cancer. Our results showed that the KLHL14 gene is overexpressed in some cancers. An increase in the KLHL14 expression indicates a poor prognosis in patients with ovarian cancer. Results of immune cell infiltration analysis and half-maximal inhibitory concentration (IC50) analysis provide novel insights into the treatment of ovarian cancer. KLHL14 is anticipated to emerge as a novel molecular marker specifically for ovarian carcinoma.
Secured Optimized Resource Allocation in Mobile Edge Computing
Authors: Bibi Asma , Majeed Muhammad Faran , Ali Sikandar , Abbasi Irshad Ahmed , Samad Ali , Baseer Samad
Published: August 2022

Mobile edge computing (MEC) uses multiple mobiles to compute several complex tasks that are unable to compute on a single device. Taking advantage of all abundant mobile resources and making a mobile cloud from them will be useful. This study aims to propose and implement a novel framework to cover challenges raised by application execution on resource-constrained devices. The purpose is to overcome the waste of resources in MEC and provide time efficiency to the data packets that are sent and received between offloaded and offloading devices. The main task of MEC is to offload tasks by first selecting resources and then allocating tasks to selected resources. A multiple linear regression algorithm is used for the selection of compatible devices. Particle swarm optimization techniques are used as a benchmark technique to design an algorithm for optimized resource allocation. Multiple mobile devices acted as a major component for making edge clouds. The study finds that response time of processing tasks is reduced, ineffectual resources become beneficial, increase in demand for mobile devices, and usage of mobile resources as a replacement for mobile edge cloud servers. Abundant resource usage of two or more edge clouds, that is, interedge resource usage is the originality of this research, while others are using intraedge resources only.
Glutamine Metabolism Mediates Sensitivity to Respiratory Complex II Inhibition in Acute Myeloid Leukemia
Authors: Roma Alessia , Tcheng Matthew , Ahmed Nawaz , Walker Sarah , Jayanth Preethi , Minden Mark D. , Hope Kristin , Nekkar Rao Praveen P. , Luc Jessica , Doxey Andrew C. , Reisz Julie A. , Culp-Hill Rachel , D'Alessandro Angelo , Spagnuolo Paul A.
Published: August 2022

Acute myeloid leukemia (AML) is a hematologic malignancy metabolically dependent on oxidative phosphorylation and mitochondrial electron transport chain (ETC) activity. AML cells are distinct from their normal hematopoietic counterparts by this metabolic reprogramming, which presents targets for new selective therapies. Here, metabolic changes in AML cells after ETC impairment are investigated. Genetic knockdown of the ETC complex II (CII) chaperone protein SDHAF1 (succinate dehydrogenase assembly factor 1) suppressed CII activity and delayed AML cell growth in vitro and in vivo. As a result, a novel small molecule that directly binds to the ubiquinone binding site of CII and inhibits its activity was identified. Pharmacologic inhibition of CII induced selective death of AML cells while sparing normal hematopoietic progenitors. Through stable isotope tracing, results show that genetic or pharmacologic inhibition of CII truncates the tricarboxylic acid cycle (TCA) and leads to anaplerotic glutamine metabolism to reestablish the truncated cycle. The inhibition of CII showed divergent fates, as AML cells lacked the metabolic plasticity to adequately utilize glutamine metabolism, resulting in preferential depletion of key TCA metabolites and death; normal cells were unaffected. These findings provide insight into the metabolic mechanisms that underlie AML's selective inhibition of CII.

Implications:

This work highlights the effects of direct CII inhibition in mediating selective AML cell death and provides insights into glutamine anaplerosis as a metabolic adaptation that can be therapeutically targeted.
Cognitive Screening via Comprehensive Geriatric Assessment of Older Patients for the Risk Factors of Hospital Revisit/Readmission after Emergency Department Visit at 3-Month Follow-Up
Authors: Lin Pei-Ying , Chen Ying-Ju , Fan Ruei-Chen , Wang Tse-Yao , Hsu The-Fu , Peng Li-Ning , Chen Liang-Kung , Huang Hsien-Hao , Hung-Tsang Yen David
Published: August 2022

Introduction: Cognitive impairment (COIM) is a major challenge for healthcare systems and is associated with an increased risk of adverse outcomes in older people visiting emergency departments (EDs). Owing to global aging, both cognitive screening and comprehensive geriatric assessment (CGA) application in ED settings are developing areas of geriatric emergency medicine. Meanwhile, the association between clinical outcomes of COIM; cognitive impairment, no dementia (CIND); and dementia in the ED could be better investigated. Our study aims to identify individuals with COIM from older patients in the ED via CGA and to describe the association of CIND and dementia with prognosis in ED visits. Methods: A prospective cross-sectional study was conducted in the ED of the Taipei Veterans General Hospital, a medical center located in Taipei, Taiwan, from August 2018 to November 2020. Patients aged ≥75 years with and without COIM were compared using data obtained from the CGAs conducted by trained nurses. Results: A total of 823 older patients were enrolled in the study and underwent CGA. Of these, 463 (56.3%) were diagnosed with COIM, of which 292 (35.5%) were diagnosed with dementia; and 171 (20.8%), CIND. Between the no-COIM and COIM groups, the COIM group had a higher rate of hospital admission (p = 0.002) and mortality at 3 months (p < 0.05). Among the no-COIM, CIND, and dementia groups, ED disposition (p = 0.001) and the rate of revisit/readmission (p < 0.05) showed significant differences. In particular, the dementia group had a significantly higher rate of revisit/readmission as compared to the CIND group among the three groups. Discussion/Conclusion: Older patients with COIM had a higher rate of hospital admission and mortality at the 3-month follow-up than older patients without COIM. Among the no-COIM, CIND, and dementia groups, patients with dementia had significantly increased risks of hospital admission and revisit/readmission. The early detection of COIM, and even dementia, could help ED physicians formulate strategies with geriatric specialists to improve mortality outcomes and revisit/readmission.
Beyond the Survival of the Global Humanities
Authors: Guyer Sara
Published: August 2022

Over the past several years, scholars and critics have begun to talk about the survival of the humanities rather than its crisis. This essay traces the emergence of a rhetoric of salvation and survival in academic advocacy literature, evident in the genres, arguments, and metaphors that writers use to describe the academic humanities. Focusing, first, on a set of recent books that advocate for the humanities as a resource for deliberation, community formation, and critique, the essay then turns to the origin of the contemporary humanities in European philology as a background for the dualism of survival and crisis in narratives about the humanities. The essay concludes by arguing that we need a new framework for understanding the survival of the humanities as global humanities, in particular, one that does not emerge from a European and Christological sense of survival. Drawing upon research conducted as part of the “World Humanities Report,” the essay identifies some of these alternative frameworks based upon the humanities in China, South Africa, and Argentina.
The Positive Humanities: A Focus on Human Flourishing
Authors: Pawelski James O.
Published: August 2022

The Positive Humanities can be defined as the branch of learning concerned with culture in its relation to human flourishing. This new field advocates for a eudaimonic turn in the humanities, an explicit recognition of and commitment to human flourishing as a central theme of study and practical aim of the humanities. It holds that this eudaimonic turn can reconnect the humanities with their initial values and goals and provide a unifying and inspiring rationale for the humanities today, opening pathways for greater individual and collective flourishing in societies around the world. After exploring the historical roots and conceptual orientations of the Positive Humanities (which are inclusive of the arts), I present five recommendations for strengthening the focus of the humanities on human flourishing: emphasize 1) wisdom as much as knowledge, 2) collaboration as much as specialization, 3) the positive as much as the negative, 4) effective friction as much as increased efficiency, and 5) the flourishing of humans as much as the flourishing of the humanities.
The Unsettled History of Passive Voice in the Sciences: The Royal Society, 1665–2020
Authors: Plotnick Jerry
Published: August 2022

This paper seeks to understand the rise and fall of passive voice in the publications of the Royal Society from 1665 to 2020. Though it came to be seen as the very voice of scientific objectivity, passive voice remained in the clear ascendency for just over a century. The rise of passive voice coincided with the progressively diminished role of an observer who directly apprehends the world through the senses. The recent re-emergence of active voice is more of a puzzle. I argue that the unsettled history of voice reflects the unsettled relationship of science to agency and conscious experience.
The Amplification of Exaggerated and False News on Social Media: The Roles of Platform Use, Motivations, Affect, and Ideology
Authors: Chadwick Andrew , Vaccari Cristian , Kaiser Johannes
Published: August 2022

We use a unique, nationally representative, survey of UK social media users ( n = 2,005) to identify the main factors associated with a specific and particularly troubling form of sharing behavior: the amplification of exaggerated and false news. Our conceptual framework and research design advance research in two ways. First, we pinpoint and measure behavior that is intended to spread, rather than correct or merely draw attention to, misleading information. Second, we test this behavior’s links to a wider array of explanatory factors than previously considered in research on mis-/disinformation. Our main findings are that a substantial minority—a tenth—of UK social media users regularly engages in the amplification of exaggerated or false news on UK social media. This behavior is associated with four distinctive, individual-level factors: (1) increased use of Instagram, but not other public social media platforms, for political news; (2) what we term identity-performative sharing motivations; (3) negative affective orientation toward social media as a space for political news; and (4) right-wing ideology. We discuss the implications of these findings and the need for further research on how platform affordances and norms, emotions, and ideology matter for the diffusion of dis-/misinformation.
The 21st Century Globetrotters’ Fans: The Case of Israeli Transnational Football Supporters’ Communities Before and During the Pandemic
Authors: Levental Orr , Laor Tal , Galily Yair
Published: August 2022

In the modern era of commercialized, mediated, and global football, there is a decline in the importance of the local aspect of sports fandom. Nowadays, through television broadcasts, the Internet, and especially social networks, a fan continuously follows elite football clubs from around the world, which provide an alternative to local clubs. This has created a growing trend of football fan communities known as “transnational fans”—fans of sports clubs from other countries. Contrary to traditional definitions of fandom, the transnational fans are not close to the home stadium and therefore do not take part in the ceremonial ritual of actively supporting the club from the stands. Because of this, they are not seen as part of the club’s traditional fans. This means that transnational fans are forced to redefine the image of the football fan and to place special emphasis on an active community and loyalty to the team as markers of devotion. Contributing to the study of the psychology of fandom, this article discusses the characteristics of those fans’ communities in Israel and seeks to present an analysis of the construction of their members’ social and personal identity. To this end, an anthropological approach was adopted, which involved attending community gatherings throughout an entire gaming season and also included a series of in-depth interviews with community members. The findings of the study illustrate two main premises: the use of personal and community resources for self-determination, and the community and its place in the modern fan typology. Each theme attempts to redefine the individual’s role in the social setting and present a dynamic image of football fandom as it will take shape in coming decades.
The Next Best Thing: How Media Dependency and Uses and Gratifications Inform Esport Fandom During the COVID-19 Pandemic
Authors: Billings Andrew , Mikkilineni Sai Datta
Published: August 2022

COVID-19 ushered new forms of media engagement when traditional sporting events and league play were suspended. Subsequently, certain sections of the audience moved online to fill their needs typically satisfied via traditional sport consumption. Esport is one such form of digital entertainment that significantly altered the ways in which sport fans can immerse themselves in related content. To examine how those audience obtained gratifications, we surveyed traditional sport fans who have either increased or initiated esports media consumption during the pandemic, doing so through the lens of media dependency theory. Results from 155 sports fans demonstrate three key findings. First, gratifications for traditional sports were significantly higher than those of esports. Secondly, ascending esports consumers maintained significantly more intense gratifications than did new users. Finally, media dependency was a significant, positive predictor of all 12 of the traditional sports motivations and 9 of the 12 esport motivations.
The Impact of Intratympanic Steroid Dosage on Hearing Recovery in Sudden Sensorineural Hearing Loss
Authors: Nelson Lacey , Swanson Daniel , Borowiec Elizabeth , Crossley Jason , Geng Xue , Cao Xiao , Kim Hung Jeffrey , Hoa Michael
Published: August 2022

Objective:

To investigate how dexamethasone dosage impacts intratympanic steroid therapy (IST) for treatment of sudden sensorineural hearing loss (SSNHL).

Study Design:

Retrospective review.

Methods:

Inclusion criteria identified subjects who received IST between January 1, 2010 and June 1, 2020 for iSSNHL. Subjects with Meniere’s disease, autoimmune inner ear disease, subjects who received injections of non-dexamethasone steroid formulations, and subjects with missing audiogram data were excluded. Subjects were stratified by dexamethasone dosage: low-dose (10 mg/ml) versus high-dose (24 mg/ml), time-to-treatment and oral corticosteroid use. Outcome measures included post-treatment improvement in 4-frequency pure tone average (4F-PTA [500, 1000, 2000,4000 Hz]), low- and high-frequency PTA (250-1000 Hz and 2000-8000 Hz, respectively).

Results:

Of the 55 included subjects (50.9% male, mean age 48.9 ± 16.4 years), 31 received high-dose while 24 received low-dose injections. 90.9% of subjects were treated with oral steroids prior to or during IST. No significant differences in hearing outcomes were observed between low- and high-dose cohorts or when stratifying by oral steroid use. Time-to-treatment analysis comparing ≤1 month (67.3%) versus >1 month (32.7%) groups demonstrated a significant improvement in post-treatment 4F-PTA ( P = .01) in the ≤1 month group.

Conclusions:

Hearing recovery was not significantly different between the 10 mg/ml versus 24 mg/ml doses of intratympanic dexamethasone, suggesting that steroid dose may not impact the efficacy of IST. A shorter time-to-treatment was observed to be favorable for hearing improvement.
Farm-to-School programmes, benefits, health outcomes and barriers: A structured literature review
Authors: Mishra Sachin K , Khanal Aditya R , Collins William J
Published: August 2022

Introduction:

A common refrain in public health and medicine concerns the rapidly rising incidence of obesity and metabolic-like syndromes over the last two decades. A plethora of data suggests there are many roots to the issue and what to do about it. The rise of childhood obesity and the growing incidence of adult endocrine diseases like type 2 diabetes mellitus in paediatric populations are the most concerning. One of the solutions that aims to tackle health and food justice issues is the Farm-to-School programme (FTSP), which helps bring local fruit and vegetables (FVs) to schools and associated nutrition-related programmes. In the USA, a significant expansion of FTSPs has happened since the early 2000s. Numerous economic, social and nutritional benefits of these programmes have been documented, and various methodologies have been used to elucidate the benefits and barriers.

Method:

This paper reviews the multifaceted strengths of FTSPs including health, institutional and farm-related benefits. The paper also discusses federal- and state-level environment and the obstacles to FTSP implementation.

Conclusion:

FTSPs offer a comprehensive way to strengthen childhood nutrition education and stimulate local communities economically and socially. FTSPs increase the purchase of locally produced food items, resulting in higher incomes for small farmers. FTSPs have also increased community engagement and new opportunities for farming businesses. In sum, FTSPs can be considered a boon for local schools, producers, communities and better health outcomes for school-age children. Teaching children about food literacy could prove beneficial for supporting their self-efficacy regarding foods and encouraging lifetime healthy dietary behaviours.
Hydrothermal aging effect on the tensile properties of hybrid aramid/glass/epoxy composites: Comparison of distilled water and seawater
Authors: Oğuz Zeynal A , Erkliğ Ahmet
Published: August 2022

This paper evaluated the effect of water adsorption on the tensile characteristics of hybrid aramid/glass/epoxy composites. The composite samples ([G6]S, [A6]S, [G3A3]S, [A3G3]S immersed in hydrothermal aging conditions (distilled water at 25°C, distilled water at 70°C, seawater at 25°C, seawater at 70°C) for 1000 h. The kinetic diffusion parameters of hybrid and plain specimens were evaluated experimentally and theoretically. Further, the effects of the stacking sequence of fabrics, seawater/distilled water aging, and temperature on the tensile behavior of dry, wet, and re-dried specimens were systematically discussed. At the end of the test, SEM images were obtained from the surfaces of the broken samples. Water gain plots for various conditions displayed that the samples absorbed more water when the aramid fabrics were on the outer surface of the hybrid composites. The hydrothermal aging significantly decreased the tensile strength of hybrid aramid/glass/epoxy and plain glass/epoxy composites. The tensile strength decrease rate of samples immersed in distilled water was higher than in seawater. Besides, the re-drying process induced more tensile strength degradation for both water types. SEM results showed that delaminations increased with aging and increasing temperature.
Land and State Capacity During Civil Wars: How Land-Based Coalitions Undermine Property Taxation in Colombia
Authors: Nieto-Matiz Camilo
Published: August 2022

Revenue, especially that from agricultural crops, has been considered fundamental for the development of state capacity. While existing research has mostly focused on dynamics of violence, we know less about the impact of commodities shocks on a key dimension of state power: property taxation. In this article, I explore how and why land-based coalitions—alliances between landowners and paramilitaries around the appropriation of land—undermine taxation during civil conflict. Focusing on the expansion of oil palm in Colombia and using a difference-in-differences design, I leverage the international price of oil palm and municipal variation in crop suitability. I find that, in municipalities with higher paramilitary violence and land concentration, the palm shock was associated with lower taxation, outdated cadastral information, and lower land values. This article underscores the deleterious consequences of land inequality for the state’s extractive capacity even in moments of agricultural abundance.
Care Experienced Adults in Education: Barriers and Facilitators
Authors: Burns Victoria , Cassidy Tony
Published: August 2022

This study explored the life experiences of care experienced adults in higher education to understand the factors that impeded or enhanced their journeys. Care experienced refers to someone who has been in the care of the state at some point in their life. Six students with a history in the care system took part in semi-structured interviews. Thematic analysis identified global themes of self-reliance, resilience, intrinsic motivation and optimism which derived from underlying experiences of support, attachment, trust, expectations and placement experiences. Findings suggest that more could be done to enable looked after children to proceed into higher education.
Accidental paediatric ingestion of amlodipine after pharmacy dispensing error
Authors: Shukla Anant , Rutman Maia , Moeller John
Published: August 2022

Incorrect dispensing of medications by community pharmacies can lead to accidental poisonings. This may not be considered by emergency medicine physicians in patients describing vague symptoms. We present a case of a paediatric ingestion of amlodipine, resulting from a community pharmacy dispensing error, that was recognized by the child’s mother, and consider the liability implications.
Oversharing on Social Media: Anxiety, Attention-Seeking, and Social Media Addiction Predict the Breadth and Depth of Sharing
Authors: Shabahang Reza , Shim Hyejin , Aruguete Mara S. , Zsila Ágnes
Published: August 2022

Oversharing on social media by adolescents is a considerable problem in the digital age, and has the potential to instigate online shaming, cyberbullying, identity theft, and other security risks. To date, oversharing has not been comprehensively studied and there is scarce understanding of the possible psychological conditions that may underlie this maladaptive online behavior. This study aimed to measure online oversharing and its potential psychological correlates among adolescents. Data were collected from 352 Iranian adolescent social media users (270 girls and 82 boys; Mage = 16.38, SD = 1.71). The Online Oversharing Inventory, developed for this study, demonstrated unidimensionality and excellent internal consistency. Further results showed that boys overshared significantly more on social media than girls did. Anxiety, attention-seeking, and social media addiction were significantly associated with elevated levels of online oversharing. Results show that the Online Oversharing Inventory is a brief and robust tool for the assessment of high frequency self-disclosure on social media. The findings suggest that anxiety, attention-seeking, and problematic use of social media may predispose adolescents to overshare personal information online.
“I Think This News Is Accurate”: Endorsing Accuracy Decreases the Sharing of Fake News and Increases the Sharing of Real News
Authors: Capraro Valerio , Celadin Tatiana
Published: August 2022

Accuracy prompts, nudges that make accuracy salient, typically decrease the sharing of fake news, while having little effect on real news. Here, we introduce a new accuracy prompt that is more effective than previous prompts, because it does not only reduce fake news sharing, but it also increases real news sharing. We report four preregistered studies showing that an “endorsing accuracy” prompt (“I think this news is accurate”), placed into the sharing button, decreases fake news sharing, increases real news sharing, and keeps overall engagement constant. We also explore the mechanism through which the intervention works. The key results are specific to endorsing accuracy, rather than accuracy salience, and endorsing accuracy does not simply make participants apply a “source heuristic.” Finally, we use Pennycook et al.’s limited-attention model to argue that endorsing accuracy may work by making people more carefully consider their sharing decisions.
How do entrepreneurs and their ventures benefit from prior setbacks: The mediating role of attitude towards failure
Authors: Zhang Wenwei , Soh Pek-Hooi , Zhao Wenhong
Published: August 2022

By integrating an experiential learning view into an attitude model, we propose that an entrepreneur’s attitude towards failure resulting from a prior setback experience can positively affect a new venture’s commitment to learning. Moreover, the entrepreneur may be exposed to indirect experiential information by gaining access to managerial ties in the venture industry, moderating the influence of prior setback experience on attitudes towards failure. We developed a conceptual model to account for the conditional and indirect effects of an entrepreneur’s setback experience on organisational commitment to learning through the entrepreneur’s attitude towards failure. Using structural equation modelling, we analysed a sample of 143 entrepreneurs located in Western China’s high-technology industrial development zones and found full support for our model. This study provides theoretical and empirical insights into the intertwined relationships between context-specific experiences, individual attitude development and venture outcomes in entrepreneurship.