bluuebunny/crossref_metadata_2025 huggingface dataset:
Lessons Learned from a Human-Centered Design of an Immersive Exergame for People with Dementia
Authors: Karaosmanoglu Sukran , Rings Sebastian , Kruse Lucie , Stein Christian , Steinicke Frank
Published: October 2021

Cognitive-physical exercises can reduce the progression of dementia. However, traditional methods often induce problems (e.g., lack of motivation), whereas the success of recent virtual reality (VR) exergames such as Beat Saber may provide a playful, motivational, and immersive alternative. Yet, until now, it remains unclear which game mechanics, concepts, and designs work best for people with dementia, and how to implement exergames for and with this user group. In this paper, we adapted a human-centered design approach to address the specifics of developing VR exergames for people with dementia. This includes semi-structured interviews with stakeholders and contextual inquiries to better analyze the user requirements. Based on our analysis, we present Memory Journalist VR - a novel VR exergame specifically designed for people with dementia in a participatory design process. We report the qualitative evaluation based on the feedback gathered in five focus group sessions. Finally, we discuss the lessons learned, which provide important insights for the design of future VR exergames for people with dementia: (i) creating social gaming activities with a focus on shared aspects, (ii) support of an inverse game flow channel addressing decline and variance in cognitive-physical abilities, and (iii) ensuring a safe VR exergame experience.
Eyesthetics
Authors: Ramirez Gomez Argenis , Lankes Michael
Published: October 2021

Gaze interaction has been growing fast as a compelling tool for control and immersion for gameplay. Here, we present a conceptual framework focusing on the aesthetic player experience and the potential interpretation (meaning) players could give to playing with gaze interaction capabilities. The framework is illustrated by a survey of state of the art research-based and commercial games. We complement existing frameworks by reflecting on gaze interaction in games as the attention relationship between the player (the subject) and the game (the object) with four dimensions: Identity; Mapping; Attention; and Direction. The framework serves as a design and inquiry toolbox to analyse and communicate gaze mechanics in games, reflect on the complexity of gaze interaction, and formulate new research questions. We visualise the resulting design space, highlighting future opportunities for gaze interaction design and HCI gaze research through the framework's lens. We deem, this novel approach advocates for the design of gaze-based interactions revealing the richness of gaze input in future meaningful game experiences.
More Than a Gimmick - Digital Tools for Boardgame Play
Authors: Rogerson Melissa J. , Sparrow Lucy A. , Gibbs Martin R.
Published: October 2021

Despite increasing interest in the use of digital tools in boardgames for both commercial and research purposes, little research has to date explored how and why these tools are used. We interviewed 18 professionals working in the boardgame industry to explore the combination of digital tools and tabletop play, which affords new experiences and opportunities for both players and designers. We generated five key themes from the interview data. Participants engaged with ontological questions about the fundamental nature of games; they showed strong opinions about the use of digital tools; they discussed the impacts of digital tools for game design as well as in their design practice; they raised concerns about the costs to develop and maintain such tools; and they considered how they affect the in-game player experience. From these themes, we generate five design principles for digital tools for boardgame play: traceability, completeness, integration, privacy, and materiality. Grounded in empirical data, these design principles guide game designers and researchers seeking to explore this novel design space. Our research focuses attention on the role of digital components in play and on the need for thoughtful implementation that considers the entire lifecycle of the game, from development through publication and, ultimately, archival access.
Respawn, Reload, Relate
Authors: Spors Velvet , Kaufman Imo
Published: October 2021

Games have the potential to not only entertain and immerse people, but can be used as vehicles for meaning-making. Given these qualities, games are approached as inspiration for caring technologies, especially for mental health. This transformative process often prioritises learning from games as systems, but not necessarily from the experiences of people with mental distress who play games for self-care. In this paper, we report on a participatory workshop series that sets out to further illuminate the connection between games, self-care and mental health from a humanistic, person-centred perspective. Over four workshops, we engaged 16 people with experiences of mental distress in speculative making activities and discussions of how self-care technology inspired by games could be re-envisioned. By thematically analysing our discussions and collective sense-making, we showcase how participants actively "re-frame" games for self-care. Finally, we sketch out how game developers and makers of gameful self-care technologies could build on our findings.
Biofeedback Methods in Entertainment Video Games
Authors: Navarro Diego , Sundstedt Veronica , Garro Valeria
Published: October 2021

The area of biofeedback interaction has grown over recent years, thanks to the release of more affordable and reliable sensor technology, and the accessibility offered by modern game development tools. This article presents a systematic literature review focusing on how different biofeedback interaction methods have been used for entertainment purposes in video games, between 2008 and 2020. It divides previous contributions in terms of a proposed interaction classification criteria and five different biofeedback methods (with a sixth category combining them): electroencephalography, electrocardiography, eye tracking, electrodermal activity, electromyography, and multi-modal interaction. The review describes the properties, sensor technologies, and the type of data gathered for every included biofeedback method, and presents their respective interaction techniques. It summarizes a set of opportunities and challenges for each included method, based on the results from previous work, and discusses these findings. It also analyzes how these interaction techniques are distributed between different common game genres. The review is beneficial for people interested in biofeedback methods and their potential use for novel interaction techniques in future video games.
I'll Play on My Other Account
Authors: Morstatter Fred , Kim Do Own (Donna) , Jonckheere Natalie , Liu Calvin , Seth Malika , Williams Dmitri
Published: October 2021

This article studies the effects and implications of sybils (secondary accounts created by a person in an online platform) through the game World of Tanks from interdisciplinary, mixed-methods perspectives. Considering sybils allows us to access a "person based'' network, instead of an "account based" network, revealing formerly undetected patterns. We move on to behavioral differences between the "parent" (the initial account) and "child" (those created afterwards) accounts in a sybil relationship. We explore the behavioral patterns of sybils using network, chat, and gameplay data. We find that sybils represent players experimenting with new roles or features without damaging their play record. We find that there are significant behavioral differences between different sybil accounts, and we leverage them to build a machine learning classifier to differentiate sybils. This classifier is able to identify sybil accounts with over 95% accuracy for sybil/non-sybil, 61% for parent/child. This study demonstrates the underexplored but rich potential for sybils to improve research and industry practitioners' understandings of user practices and experiences.
What is a Visual Novel?
Authors: Camingue Janelynn , Carstensdottir Elin , Melcer Edward F.
Published: October 2021

Visual Novel (VN) is a widely recognizable genre of narrative-focused games that has grown in popularity over the past decade. Surprisingly, despite being so widely recognizable, there is not a singular definition to help guide the design and analysis of such games---with academic definitions and implementations ranging from "interactive textbooks" to "adventure games with multi-ending stories". In this paper, we present a unified definition of VNs drawn from an analysis of 30 prior academic definitions. We also examined 54 existing VNs to further refine our definition and employ a deeper analysis of the interactivity within VNs. We highlight key features of VNs that arise in our definition, and discuss resulting implications for the design of VNs. This work is relevant for narrative game designers and researchers, affording a more unified structure and clearer guidelines to identify, analyze, and design future VN games.
Personalization Improves Gamification
Authors: Rodrigues Luiz , Palomino Paula T. , Toda Armando M. , Klock Ana C. T. , Oliveira Wilk , Avila-Santos Anderson P. , Gasparini Isabela , Isotani Seiji
Published: October 2021

Personalization of gamification is an alternative to overcome the shortcomings of the one-size-fits-all approach, but the few empirical studies analyzing its effects do not provide conclusive results. While many user and contextual information affect gamified experiences, prior personalized gamification research focused on a single user characteristic/dimension. Therefore, we hypothesize if a multidimensional approach for personalized gamification, considering multiple (user and contextual) information, can improve user motivation when compared to the traditional implementation of gamification. In this paper, we test that hypothesis through a mixed-methods sequential explanatory study. First, 26 participants completed two assessments using one of the two gamification designs and self-reported their motivations through the Situational Motivation Scale. Then, we conducted semi-structured interviews to understand learners' subjective experiences during these assessments. As result, the students using the personalized design were more motivated than those using the one-size-fits-all approach regarding intrinsic motivation and identified regulation. Furthermore, we found the personalized design featured game elements suitable to users' preferences, being perceived as motivating and need-supporting. Thus, informing i) practitioners on the use of a strategy for personalizing gamified educational systems that is likely to improve students' motivations, compared to OSFA gamification, and ii) researchers on the potential of multidimensional personalization to improve single-dimension strategies. For transparency, dataset and analysis procedures are available at https://osf.io/grzhp.
Russell Donnelly and His Leaks
Authors: Niemela J.J. , Sreenivasan K.R.
Published: October 2021

Russell James Donnelly (b. 1930) was an exceptionally creative physicist with many other interests: art, music, history, and scientific societies and their scholarly journals. He reinvigorated the maturing field of low temperature physics by linking it strongly to fluid turbulence through bold and optimistic leadership at the intersection of the two fields. Immediately after achieving his Ph.D. at Yale University with C.T. Lane and L. Onsager, Russ joined the University of Chicago in 1956, where he became a professor at the first possible opportunity. After some ten years at University of Chicago, where he worked for a time with S. Chandrasekhar, he moved to the University of Oregon and led a vigorous life until his death in 2015. Russ was an excellent organizer of scientific meetings and an enthusiastic expositor of his science. He had a profound sense of service to the community, both civic and scientific, and showed exceptional scientific openness and generosity to his colleagues. He was greatly admired by his community.
Interstitial cells of Cajal and human colon motility in health and disease
Authors: Huizinga Jan D. , Hussain Amer , Chen Ji-Hong
Published: October 2021

Our understanding of human colonic motility, and autonomic reflexes that generate motor patterns, has increased markedly through high-resolution manometry. Details of the motor patterns are emerging related to frequency and propagation characteristics that allow linkage to interstitial cells of Cajal (ICC) networks. In studies on colonic motor dysfunction requiring surgery, ICC are almost always abnormal or significantly reduced. However, there are still gaps in our knowledge about the role of ICC in the control of colonic motility and there is little understanding of a mechanistic link between ICC abnormalities and colonic motor dysfunction. This review will outline the various ICC networks in the human colon and their proven and likely associations with the enteric and extrinsic autonomic nervous systems. Based on our extensive knowledge of the role of ICC in the control of gastrointestinal motility of animal models and the human stomach and small intestine, we propose how ICC networks are underlying the motor patterns of the human colon. The role of ICC will be reviewed in the autonomic neural reflexes that evoke essential motor patterns for transit and defecation. Mechanisms underlying ICC injury, maintenance, and repair will be discussed. Hypotheses are formulated as to how ICC dysfunction can lead to motor abnormalities in slow transit constipation, chronic idiopathic pseudo-obstruction, Hirschsprung’s disease, fecal incontinence, diverticular disease, and inflammatory conditions. Recent studies on ICC repair after injury hold promise for future therapies.
A rapidly changing understanding of COPD: World COPD Day from the COPD Foundation
Authors: Thomashow Byron M. , Mannino David M. , Tal-Singer Ruth , Crapo James D.
Published: October 2021

World COPD Day raises awareness about chronic obstructive pulmonary disease (COPD). COPD accounts for over 150,000 US deaths per year. A major challenge is that COPD receives only a fraction of the research funding provided to other major diseases. Control of COPD is dependent on developing new approaches to diagnose the disease earlier with a recognition of either pre-COPD or established COPD based on symptoms, lung structural change and/or loss of lung function that occurs before meeting long established criteria for a population-based definition of obstruction. Optimization of current therapies improves lung function, exercise capacity, quality of life, and survival. New pathways of disease progression are being identified creating new opportunities for development of therapies that could stop or cure this disease.
Composition and decomposition of visuomotor maps during manual tracking
Authors: Bernier Pierre-Michel , Mathew James , Danion Frederic R.
Published: October 2021

The ability to compose/decompose task representations is critical for both cognitive and behavioral flexibility. Here, we show that this ability extends to two forms of visuomotor adaptation in which humans have to perform visually guided hand movements. Despite the presence of interference effects when switching between visuomotor maps, we show that participants are able to flexibly compose or decompose knowledge acquired in previous sessions. These results further demonstrate the flexibility of sensorimotor adaptation in humans.
Faces emotional expressions: from perceptive to motor areas in aged and young subjects
Authors: Loi Nicola , Ginatempo Francesca , Manca Andrea , Melis Francesco , Deriu Franca
Published: October 2021

This study shows that aged subjects have less visual attention and impaired perception for sad, but not for happy, face expressions. Conversely, the view of happy, but not sad, faces increases excitability in face M1 bilaterally, regardless of age. The impaired attention for sad expressions, the preserved perception of faces expressing happiness, along with the enhancing effects of the latter on face M1 excitability, likely makes the aged subjects more motivated in approaching positive emotions.
Drivers of transcriptional variance in human intestinal epithelial organoids
Authors: Criss Zachary K. , Bhasin Nobel , Di Rienzi Sara C. , Rajan Anubama , Deans-Fielder Kali , Swaminathan Ganesh , Kamyabi Nabiollah , Zeng Xi-Lei , Doddapaneni Harsha , Menon Vipin K. , Chakravarti Deepavali , Estrella Clarissa , Yu Xiaomin , Patil Ketki , Petrosino Joseph F. , Fleet James C. , Verzi Michael P. , Christakos Sylvia , Helmrath Michael A. , Arimura Sumimasa , DePinho Ronald A. , Britton Robert A. , Maresso Anthony W. , Grande-Allen K. Jane , Blutt Sarah E. , Crawford Sue E. , Estes Mary K. , Ramani Sasirekha , Shroyer Noah F.
Published: October 2021

Human intestinal epithelial organoids (enteroids and colonoids) are tissue cultures used for understanding the physiology of the human intestinal epithelium. Here, we explored the effect on the transcriptome of common variations in culture methods, including extracellular matrix substrate, format, tissue segment, differentiation status, and patient heterogeneity. RNA-sequencing datasets from 276 experiments performed on 37 human enteroid and colonoid lines from 29 patients were aggregated from several groups in the Texas Medical Center. DESeq2 and gene set enrichment analysis (GSEA) were used to identify differentially expressed genes and enriched pathways. PERMANOVA, Pearson’s correlation, and dendrogram analysis of the data originally indicated three tiers of influence of culture methods on transcriptomic variation: substrate (collagen vs. Matrigel) and format (3-D, transwell, and monolayer) had the largest effect; segment of origin (duodenum, jejunum, ileum, colon) and differentiation status had a moderate effect; and patient heterogeneity and specific experimental manipulations (e.g., pathogen infection) had the smallest effect. GSEA identified hundreds of pathways that varied between culture methods, such as IL1 cytokine signaling enriched in transwell versus monolayer cultures and E2F target genes enriched in collagen versus Matrigel cultures. The transcriptional influence of the format was furthermore validated in a synchronized experiment performed with various format-substrate combinations. Surprisingly, large differences in organoid transcriptome were driven by variations in culture methods such as format, whereas experimental manipulations such as infection had modest effects. These results show that common variations in culture conditions can have large effects on intestinal organoids and should be accounted for when designing experiments and comparing results between laboratories. Our data constitute the largest RNA-seq dataset interrogating human intestinal epithelial organoids.
Nitrogen Content Estimation of Apple Leaves Using Hyperspectral Analysis
Authors: Sun Weihao , Wang Dongwei , Jin Ning , Xu Shusheng , Bai Haoran
Published: October 2021

Leaf nitrogen content (LNC) is an important factor reflecting the growth quality of plants. We estimated the nitrogen content of apple leaves using hyperspectral wavelength analysis using the differential spectrum, differential spectrum transformation, and vegetation spectrum index with different derivative gaps. We then used the characteristic wavelengths extracted via the correlation coefficient method as the input vectors to the gradient boosting decision tree (GBDT) model for analysis and performed cross-validation to optimize the inversion model parameters. We analyzed the results with different input variables and loss functions and compared the GBDT model with other mainstream algorithm models. The results show that the R2 value of the optimized GBDT inversion model is higher than that obtained using the random forest (RF) and support vector regression (SVR) models. Thus, the GBDT model is accurate, and the characteristic wavelength analysis is helpful for the tasks of real-time monitoring and detection of apple tree health.
The Regulatory Effect of MicroRNA‐101‐3p on Disc Degeneration by the STC1/VEGF/MAPK Pathway
Authors: Wang Juehan , Huang Leizhen , Yang Xi , Zhu Ce , Huang Yong , He Xin , Shi Kun , Wang Jingcheng , Feng Ganjun , Liu Limin , Song Yueming
Published: October 2021

Aims. Accumulating evidence reported that the microRNA (miRNA) took an important role in intervertebral disc degeneration (IDD). In this study, we revealed a novel miRNA regulatory mechanism in IDD. Main Methods. The miRNA microarray analyses of human degenerated and normal disc samples were employed to screen out the target miRNA. In vitro and in vivo experiments were conducted to verify the regulatory effect of miR‐101‐3p. Key Findings. The expression level of miR‐101‐3p was significantly decreased in the degenerated disc samples which were confirmed by qRT‐PCR. Moreover, the miR‐101‐3p expression level was changed dynamically according to the disc degeneration grade. Upregulation of miR‐101‐3p expression level inhibited cell apoptosis. Furthermore, stanniocalcin‐1 (STC1) was selected to be the target gene of miR‐101‐3p according to the bioinformatic algorithms. Mechanically, upregulation of miR‐101‐3p significantly decreased the expression of STC1, vascular endothelial growth factor (VEGF), and MAPK pathway expression levels. Therapeutically, in vivo experiment on IDD rat model illustrated that agomir‐101‐3p could effectively suspend IDD. Significance. Our findings demonstrated that miR‐101‐3p alleviated IDD process through the STC1/VEGF/MAPK pathway.
Analytical Solutions of Seismic-Generated Internal Tsunamis
Authors: Liu Chi-Min
Published: October 2021

Internal tsunamis induced by an instantaneous seabed deformation are theoretically analyzed in this paper. Based on Hammack’s mathematical methods and findings, an in-depth and extensive study is performed to examine tsunami waveforms, especially at the initial stage. Waveforms of surface and internal tsunamis induced by three fundamental seabed uplifts, the rectangle-, cosine-, and sine-shape deformations, are solved to constitute an important base for analyzing waves generated by arbitrary seabed movements. A closed-form solution for the rectangle-shape deformation and analytic solutions for cosine and sine cases are obtained. The effects of spatial parameters on waveforms and the contributions of two frequency modes are investigated for the Boussinesq limit. The derived wave solutions not only improve the understanding of the formation of internal tsunamis but also provide an exact initial waveform for simulating wave propagation by various wave models.
Prediction of IoT Traffic Using the Gated Recurrent Unit Neural Network- (GRU-NN-) Based Predictive Model
Authors: Patil Sonali Appasaheb , Raj L. Arun , Singh Bhupesh Kumar
Published: October 2021

Prediction of IoT traffic in the current era has attracted noteworthy attention to utilize the bandwidth and channel capacity optimally. In this paper, the problem of IoT traffic prediction has been studied, and solutions have been proposed by using machine learning method ARIMA and learning time series algorithms such as LSTM and gated recurrent unit (GRU-NN) based on neural networks. The proposed GRU-NN predicts the traffic on the basis of transfer learning. The advantage of the GRU-NN over LSTM is also highlighted by solving the problem of gradient disappearance. The proposed GRU-NN memorizes the traffic characteristics of the IoT environment for a long time which eventually helps the system to forecast the upcoming traffic from the existing traces of the traffic. The proposed GRU-NN makes use of the transfer learning technique to handle the problem of insufficient IoT traffic data along with the gradient boosting training method for achieving better accuracy in predicting the network traffic in the IoT environment. The results reveal that the proposed GRU-NN model outperforms the other traffic predictors in terms of statistical performance evaluation parameters such as MAE, RMSE, MRE, and MSE. The results show that the GRU-NN provides the most accurate predictions followed by the LSTM predictor and then ARIMA and other approaches taken up for the comparative study.
KIF2C Is a Novel Prognostic Biomarker and Correlated with Immune Infiltration in Endometrial Cancer
Authors: An Lanfen , Zhang Jun , Feng Dilu , Zhao Yingchao , Ouyang Weixiang , Shi Rui , Zhou Xing , Yu Zhicheng , Wei Sitian , Min Jie , Wang Hongbo
Published: October 2021

Endometrial cancer (EC) is commonly diagnosed cancer in women, and the prognosis of advanced types of EC is extremely poor. Kinesin family member 2C (KIF2C) has been reported as an oncogene in cancers. However, its pathophysiological roles and the correlation with tumor-infiltrating lymphocytes in EC remain unclear. The mRNA and protein levels of KIF2C in EC tissues were detected by qRT-PCR, Western blot (WB), and IHC. CCK8, Transwell, and colony formation assay were applied to assess the effects of KIF2C on cell proliferation, migration, and invasion. Cell apoptosis and cell cycle were analyzed by flow cytometry. The antitumor effect was further validated in the nude mouse xenograft cancer model and humanized mouse model. KIF2C expression was higher in EC. Knockdown of KIF2C prolonged the G1 phases and inhibited EC cell proliferation, migration, and invasion in vitro. Bioinformatics analysis indicated that KIF2C is negatively correlated with the infiltration level of CD8+ T cells but positively with the poor prognosis of EC patients. The apoptosis of CD8+ T cell was inhibited after the knockdown of KIF2C and was further inhibited when it is combined with anti-PD1. Conversely, compared to the knockdown of KIF2C expression alone, the combination of anti-PD1 further promoted the apoptosis of Ishikawa and RL95-2 cells. Moreover, the knockdown of KIF2C inhibited the expression of Ki-67 and the growth of tumors in the nude mouse xenograft cancer model. Our study found that the antitumor efficacy was further evaluated by the combination of anti-PD1 and KIF2C knockdown in a humanized mouse model. This study indicated that KIF2C is a novel prognostic biomarker that determines cancer progression and also a target for the therapy of EC and correlated with tumor immune cells infiltration in EC.
A Two‐Phase Mitosis Detection Approach Based on U‐Shaped Network
Authors: Lu Wenjing
Published: October 2021

This paper proposes a deep learning‐based method for mitosis detection in breast histopathology images. A main problem in mitosis detection is that most of the datasets only have weak labels, i.e., only the coordinates indicating the center of the mitosis region. This makes most of the existing powerful object detection methods hardly be used in mitosis detection. Aiming at solving this problem, this paper firstly applies a CNN‐based algorithm to pixelwisely segment the mitosis regions, based on which bounding boxes of mitosis are generated as strong labels. Based on the generated bounding boxes, an object detection network is trained to accomplish mitosis detection. Experimental results show that the proposed method is effective in detecting mitosis, and the accuracies outperform state‐of‐the‐art literatures.
Bioinformatics Analysis of ZBTB16 as a Prognostic Marker for Ewing’s Sarcoma
Authors: Ding Ke , Qiu Wenli , Yu Dianbo , Ma Huade , Xie Kangqi , Luo Fuqiang , Li Shanlang , Li Zaiyong , Wei Jihua
Published: October 2021

Objective. The purpose of this study is to identify novel biomarkers for the prognosis of Ewing’s sarcoma based on bioinformatics analysis. Methods. The GSE63157 and GSE17679 datasets contain patient and healthy control microarray data that were downloaded from the Gene Expression Omnibus (GEO) database and analyzed through R language software to obtain differentially expressed genes (DEGs). Firstly, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment, protein‐protein interaction (PPI) networks, and Cytoscape Molecular Complex Detection (MCODE) plug‐in were then used to compute the highest scores of the module. After survival analysis, the hub genes were lastly obtained from the two module genes. Results. A total of 1181 DEGs were identified from the two GSEs. Through MCODE and survival analysis, we obtain 53 DEGs from the module and 29 overall survival‐ (OS‐) related genes. ZBTB16 was the only downregulated gene after Venn diagrams. Survival analysis indicates that there was a significant correlation between the high expression of ZBTB16 and the OS of Ewing’s sarcoma (ES), and the low expression group had an unfavorable OS when compared to the high expression group. Conclusions. High expression of ZBTB16 may serve as a predictor biomarker of poor prognosis in ES patients.
Prevalence and Presentation of Paediatric Coronavirus Disease 2019 in Lagos, Nigeria
Authors: Salako Abideen , Odubela Oluwatosin , Musari-Martins Tomilola , Ezemelue Priscilla , Gbaja-Biamila Titilola , Opaneye Babasola , James Ayorinde , Oforomeh Osaga , Osuolale Kazeem , Musa Adesola , Chukwu Emelda , Rahman Nurudeen , David Agatha , Audu Rosemary , Ezechi Oliver , Salako Babatunde
Published: October 2021

Background. The objective of this study was to describe the prevalence and clinical features of coronavirus disease 2019 (COVID-19) among children (≤18 years) evaluated for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection at a testing centre in Lagos, Nigeria. Methodology. This was a retrospective study. Data on the sociodemographic, clinical characteristics and SARS-CoV-2 results of participants at a modified drive-through centre for COVID-19 test sample collection over four months were retrieved from the electronic medical records (EMR). Data obtained were analyzed using SPSS version 22.0. Results. A total of 307 children (≤18 years) were evaluated in this review. The prevalence of SARS-CoV-2 infection among the paediatric population was 16.3%. The median age (interquartile range (IQR)) was 9 (4–14) years. Common symptoms reported by the positive cases were fever (40.0%), cough (32.9%), sore throat (17.1%), and runny nose (15.7%). The majority of the positive cases had mild symptoms. Fever and sore throat were associated with the positive cases. Conclusion. Fever and sore throat were associated with SARS-CoV-2 infection among our cohort which buttresses the need for a high level of suspicion and clinical acumen in the management of common febrile diseases in paediatric settings.
Improved Estimation of Bio‐Oil Yield Based on Pyrolysis Conditions and Biomass Compositions Using GA‐ and PSO‐ANFIS Models
Authors: Li Zhimin , Zhao Deyin , Han Linbo , Yu Li , Jafari Mohammad Mahdi Molla
Published: October 2021

This paper incorporates the adaptive neurofuzzy inference system (ANFIS) technique to model the yield of bio‐oil. The estimation of this parameter was performed according to pyrolysis conditions and biomass compositions of feedstock. For this purpose, this paper innovates two optimization methods including a genetic algorithm (GA) and particle swarm optimization (PSO). Primary data were gathered from previous studies and included 244 data of biodiesel oils. The findings showed a coefficient determination (R2) of 0.937 and RMSE of 2.1053 for the GA‐ANFIS model, and a coefficient determination (R2) of 0.968 and RMSE of 1.4443 for PSO‐ANFIS. This study indicates the capability of the PSO‐ANFIS algorithm in the estimation of the bio‐oil yield. According to the performed analysis, this model shows a higher ability than the previously presented models in predicting the target values and can be a suitable alternative to time‐consuming and difficult experimental tests.
Date Palm Seed Oil (Phoenix dactylifera L.) Green Extraction: Physicochemical Properties, Antioxidant Activities, and Phenolic and Fatty Acid Profiles
Authors: Hamza Hammadi , Elfalleh Walid , Nagaz Kameleddine
Published: October 2021

Date palm seed oil is among the precious vegetable oils with low yield, whose extraction is commonly done with organic solvents which cause serious problems. This study aims to assess the effectiveness of orange peel essential oil as biosolvent for date seed oil extraction. Green extraction was conducted by Soxhlet apparatus as well as by soaking and compared with the Soxhlet method using petroleum ether. The GC-MS analysis of orange peel essential oil confirmed its richness with limonene (94.31%), which justifies its usefulness as green solvent. The latter gave higher yields, the extracted bio-oil was light brown with pleasant odor, and the characteristics were consistent with international standards. Based on the GC profiles, obtained oils were similar using both solvents, and the major compounds were oleic and lauric acids. The bio-oil phenolic content and the antioxidant activity were high, and the major compounds were the protocatechuic, chlorogenic, and 4-O-caffeoylquinic acids. Gallic and

p

-coumaric acids were the major compounds for oil extracted by petroleum ether.
Deep Learning-Based Positron Emission Tomography Molecular Imaging in the Assessment of Cognitive Dysfunction in Patients with Epilepsy
Authors: Tuerxun Mayila , Yin Lixin , Chen Huiqun , Lin Jingqian
Published: October 2021

This work aimed to investigate the application of positron emission tomography (PET) molecular imaging based on the deep learning algorithm in the assessment of cognitive dysfunction in patients with epilepsy. In this study, 52 hospitalized patients with epilepsy were selected as the epilepsy group and treated with different kinds of antiepileptic drugs, and 52 volunteers were selected as the control group. A U-net optimized network structure algorithm based on deep learning was proposed in this study and compared with a fully convolutional neural network (FCNN). Besides, it was applied in the PET molecular imaging of patients with epilepsy, and the segmentation effect of the U-net optimized network structure was good. According to event-related potential examinations, the proportion of patients with cognitive dysfunction in the epilepsy group (74.19%) was higher than the proportion of the control group (7.46%) (

P
<
0.05

). The patients with cognitive dysfunction (57.89%) who took one antiepileptic drug were lower than those with two antiepileptic drugs (84.61%) (

P
<
0.05

). The difference was statistically obvious in the overall quality of life of patients with epilepsy (

P
<
0.05

). The occurrence of cognitive dysfunction in patients with epilepsy was related to the type of seizures. In addition, the quality of life of patients who suffered from cognitive dysfunction was low.
Safety Evaluation of Fog Warning Systems in a Connected Vehicle Environment Based on Sample Entropy
Authors: Li Xuewei , Jia Yuchen , Chen Yufei , Xing Guanyang , Zhao Xiaohua , Rong Jian
Published: October 2021

Changes in driving behavior caused by reduced visibility in fog can lead to crashes. To improve driving safety in fog weather, a fog warning system based on connected vehicle (CV) technology is proposed. From the perspective of human factors, this study evaluates the driving safety based on drivers’ speed change under different fog levels (i.e., no fog, light fog, and heavy fog) and different technical levels (i.e., normal, with a dynamic message sign (DMS), and with a human-machine interface (HMI)). The driving behavior data were collected by a driving simulation experiment. The experimental road was divided into three zones: clear zone, transition zone, and fog zone. To quantify the change of vehicle speed comprehensively, the speed and acceleration were selected. Meanwhile, the vehicle speed safety entropy and acceleration safety entropy were proposed based on sample entropy theory. Furthermore, the changes of each index in different zones were analyzed. The results show that the use of fog warning system can improve speed stability and driving safety in fog zones and can make the driver decelerate in advance with a smaller deceleration before entering the fog zones. The higher the technical level is, the earlier the driver decelerates. Under the condition of light fog, the fog warning system with HMI has a better effect in terms of improving speed stability, while under the condition of heavy fog, there is little difference between the two technical levels. In general, this study proposed a novel safety evaluation index and a general evaluation method of the fog warning system.
Corneal and Epithelial Thickness Mapping: Comparison of Enhanced Spectral-Domain- and Spectral-Domain-Optical Coherence Tomography
Authors: Georgeon Cristina , Marciano Ilanite , Cuyaubère Roxane , Sandali Otman , Bouheraoua Nacim , Borderie Vincent
Published: October 2021

Objective. To compare the results and repeatability of the corneal thickness (CT) and epithelial thickness (ET) maps provided by Enhanced Spectral-Domain-Optical Coherence Tomography with those of Spectral-Domain-OCT in normal eyes. Methods. 30 normal eyes of 30 patients were assessed by 3 trained operators with ESD-OCT and SD-OCT. Results. The central and minimum ET obtained with both devices were correlated: central ET, r = 0.86,

p
<
0.05

; minimum ET, r = 0.72,

p
<
0.05

. Compared with SD-OCT, ESD-OCT tended to underestimate these figures by 1.4 and 1.9 μm on average. The central and minimum CT obtained with both devices were strongly correlated: central CT, r = 0.994,

p
<
0.05

; minimum CT, r = 0.995,

p
<
0.05

. ESD-OCT tended to overestimate these figures by 11 and 14 μm on average. Repeatability was good for both devices with a mean coefficient of variation of measurements <6% for ET and <2% for CT. Interoperator variability (standard deviation and COV) was significantly higher for ESD-OCT than for SD-OCT for all local epithelial thicknesses and significantly lower for the central CT and several local corneal thicknesses, whereas no significant differences between both technologies were found for the central and minimum ET and the minimum CT. Conclusion. ESD-OCT and SD-OCT provide reproducible measurements of CT and ET in normal corneas with a strong correlation between both technologies. However, both technologies are not interchangeable when the main thickness parameters (i.e., central and minimum CT and minimum ET) are used for diagnosing early keratoconus or calculating the expected residual stromal bed thickness before corneal refractive surgery or anterior lamellar keratoplasty.
Anticipated Reductions in Tax Rates and Earning Management of Listed Companies: Evidence from China
Authors: Bai Mo , Song Dandan , Li Helin
Published: October 2021

The effects of tax rate changes on corporations’ earning management are not fully understood. As a transitional economy, China has listed companies with different ownership and special regulatory rules. We explore under the expectation of tax reduction whether there are differences in the way and degree of earnings management implemented by different types of companies. Our study shows that firms under the anticipation of tax reduction make use of earning management, including delaying sales, taking unusual income-decreasing discretionary accruals, and so on, which leads to lower income in higher tax rate period. We find that private enterprises have more attention to reduce earning in the higher tax rate period than state-owned enterprises (SOEs), indicating that the ownership has effect on the extent of earning management. Moreover, under the specific regulations in Chinese stock market, we find that for those listed companies with negative net profit in the previous year, the priority is how to reverse losses rather than tax saving.
Clinical Study on the Efficacy of Laparoscopic Hepatectomy and Its Influence on the Expression of Serum VEGF, FGF, and Immune Function
Authors: Tang Zhengyong , Tang Yi , Liu Tianqi , Liu Rongjun , Xie Shaowei , Xie Dongyi , Yang Jianrong , Tang Yuntian
Published: October 2021

Liver cancer is one of the most common malignant tumors. Partial hepatectomy is the most basic and effective treatment for hepatocellular carcinoma because of its high operative effect and perioperative safety. Open surgery is the most traditional hepatectomy. Although it can completely remove tumor lesions and prolong patient survival, it has disadvantages such as large trauma and long postoperative recovery time. Meanwhile, long-term bed rest can increase the risk of complications such as venous thrombosis and infection. The advantages of laparoscopic partial hepatectomy, such as clear operative field, simple operation, little trauma, light surgical stress, quick postoperative recovery, and low complications, can avoid damage to vital organs, blood vessels, and nerves, which has been widely accepted and recognized in clinical practice.
Target Threat Assessment in Air Combat Based on Improved Glowworm Swarm Optimization and ELM Neural Network
Authors: Cao Yuan , Kou Ying-Xin , Xu An , Xi Zhi-Fei
Published: October 2021

Target threat assessment technology is one of the key technologies of intelligent tactical aid decision-making system. Aiming at the problem that traditional beyond-visual-range air combat threat assessment algorithms are susceptible to complex factors, there are correlations between assessment indicators, and accurate and objective assessment results cannot be obtained. A target threat assessment algorithm based on linear discriminant analysis (LDA) and improved glowworm swarm optimization (IGSO) algorithm to optimize extreme learning machine (ELM) is proposed in this paper. Firstly, the linear discriminant analysis method is used to classify the threat assessment indicators, eliminate the correlation between the assessment indicators, and achieve dimensionality reduction of the assessment indicators. Secondly, a prediction model with multiple parallel extreme learning machines as the core is constructed, and the input weights and thresholds of extreme learning machines are optimized by the improved glowworm swarm optimization algorithm, and the weighted integration is carried out according to the training level of the kernel. Then, the threat assessment index functions of angle, speed, distance, altitude, and air combat capability are constructed, respectively, and the sample data of air combat target threat assessment are obtained by combining the structure entropy weight method. Finally, the air combat data is selected from the air combat maneuvering instrument (ACMI), and the accuracy and real-time performance of the LDA-IGSO-ELM algorithm are verified through simulation. The results show that the algorithm can quickly and accurately assess target threats.
Response of Potato (Solanum tuberosum L.) to NPS Fertilizer Rates and Inter-Row Spacing in Kechi District, South Western Ethiopia
Authors: Getaneh Lakew , Laekemariam Fanuel
Published: October 2021

Fertilizer requirement and spacing vary across locations due to differences in soil types, nutrient and moisture availability, economic factors, and other environmental conditions. Therefore, a field experiment was carried out to investigate the effect of different rates of NPS fertilizers and inter-row spacing on growth, yield, yield components, and economic performance of potato in Kechi research farm, Dawro zone of south-western Ethiopia. The experiment was arranged in factorial combination of six NPS (19N–38P2O5–7S) fertilizer rates (0 kg/ha, 50 kg/ha, 100 kg/ha, 150 kg/ha, 200 kg/ha, and 250 kg/ha) and five inter-row spacings (45, 55, 65, 75, and 85 cm) which were laid out in RCBD with three replications using the Gudene variety. Growth, yield component, and yield data were collected and analyzed. In addition, a partial budget analysis was performed. The results showed that the main effect of NPS fertilizer and inter-row spacing had significantly (

P
<
0.05

) affected plant height, tuber number, tuber yield, and tuber size and average tuber weight. Maximum marketable tuber number per plant (11.627), total tuber number per plant (13.020), average tuber weight per plant (83.493 g), the proportion of large-sized tuber number per plant (41.893%), marketable tuber yield (48.056 t/ha), and total tuber yield (51.145 t/ha) were obtained from 200 kg/ha of NPS fertilizer which was statistically at par with 150 kg/ha and 250 kg/ha NPS, while the lowest result for those parameters was recorded from unfertilized plots. Results regarding inter-row spacing revealed that the highest marketable tuber number per plant (11.744), total tuber number per plant (13.144), and average tuber weight per plant (85.559 g) were recorded at 75 cm, while the lowest result for these parameters was recorded at 45 cm. Moreover, the highest marketable tuber yield (45.084 t/ha) and total tuber yield (48.462 t/ha) were obtained from the inter-row spacing of 65 cm which was statistically at par with 55 cm inter-row spacing, while the lowest result for these parameters was recorded at 85 cm. The partial budget analysis further revealed that 200 kg/ha NPS fertilizer gave the maximum net benefit. However, 150 kg/ha NPS resulted in the highest marginal rate of return (4303.91%). Thus, 150 kg/ha NPS fertilizer and inter-row spacing of 55 cm or 65 cm are suggested for attaining higher potato yield.
Phylogenetically Diverse Escherichia coli Strains from Chicken Coharbor Multiple Carbapenemase‐Encoding Genes (blaNDM-blaOXA‐blaIMP)
Authors: Aklilu Erkihun , Harun Azian , Singh Kirnpal Kaur Banga , Ibrahim Shamsaldeen , Kamaruzzaman Nor Fadhilah
Published: October 2021

Carbapenem‐resistant Enterobacteriaceae (CRE) has been a public health risk in several countries, and recent reports indicate the emergence of CRE in food animals. This study was conducted to investigate the occurrence, resistance patterns, and phylogenetic diversity of carbapenem‐resistant E. coli (CREC) from chicken. Routine bacteriology, PCR detection of E. coli species, multiplex PCR to detect carbapenemase‐encoding genes, and phylogeny of CRE E. coli were conducted. The results show that 24.36% (19/78) were identified as CREC based on the phenotypic identifications of which 17 were positive for the tested carbapenemases genes. The majority, 57.99% (11/19), of the isolates harbored multiple carbapenemase genes. Four isolates harbored all blaNDM, blaOXA, and blaIMP, and five and two different isolates harbored blaNDM and blaOXA and blaOXA and blaIMP, respectively. The meropenem, imipenem, and ertapenem MIC values for the isolates ranged from 2 μg/mL to ≥256 μg/mL. Phylogenetic grouping showed that the CREC isolates belonged to five different groups: groups A, B1, C, D, and unknown. The detection of CREC in this study shows that it has become an emerging problem in farm animals, particularly, in poultry farms. This also implies the potential public health risks posed by CRE from chicken to the consumers.