bluuebunny/crossref_metadata_2025 huggingface dataset:
Fungi Associated with Messor Ants on the Balkan Peninsula: First Biogeographical Data
Authors: Lapeva-Gjonova Albena , Csősz Sándor , Báthori Ferenc
Published: December 2022

Ant nests’ relatively stable and long-lasting microhabitats present ideal living conditions for many uni- and multicellular organisms, whose relationships range from mutualistic to parasitic. Messor harvester ants inhabit arid and semi-arid open areas where their colonies consist of large numbers of individuals. Due to the high number of other organisms associated with harvester ants, their nests can be defined as islands for unique biota. Despite significant progress in research on ant-associated fungi in Europe, little is still known about the recently described ectoparasitic fungus Rickia lenoirii Santamaria, 2015 (Laboulbeniales), found on two species of ants of the genus Messor. Here we report for the first time the occurrence of the ectoparasitic ant-associated fungus R. lenoirii from three countries (Albania, Bulgaria, and continental Greece) and multiple localities in the Balkans. The fungus was detected on four ant host species—Messor structor (Latreille, 1798), M. wasmanni Krausse, 1910, M. hellenius Agosti & Collingwood, 1987, and M. mcarthuri Steiner et al., 2018 with the latter two representing new host records. Furthermore, spores of the widespread endoparasitic fungus of ants, Myrmicinosporidium durum Hölldobler, 1933 (Blastocladiomycota), were reported for the first time in Messor structor (Bulgaria). Images of the ant-associated Rickia lenoirii taken with a scanning electron microscope, a comparison with R. wasmannii, and a distribution map are also presented.
Analysis of Prey Composition in Eurasian Reed Warblers’ Acrocephalus scirpaceus Droppings at Four Breeding Sites in Italy
Authors: Ientile Renzo , Tuliozi Beniamino , Campobello Daniela , Borghi Stefano , Sala Luigi , Dal Zotto Matteo , Massa Bruno
Published: December 2022

Our aim was to investigate the among-populations diversity of prey composition in Eurasian Reed Warblers’ diets via their droppings, both to assess the ecological validity of this sampling method and to test whether the prey species most abundant in fecal samples were also the most present in the Italian study site. We collected fecal samples at four sites throughout Italy, for a total of 144 samples. Within reedbeds, the breeding habitat of the Eurasian Reed Warbler, we also collected arthropods by carrying out entomological sweepings at one of the study sites. Within the fecal samples, we identified dozens of prey species, belonging mainly to Araneae, Coleoptera, Diptera, Hymenoptera and Aphidoidea taxa, whose compositions were not statistically different among sites. The commonest prey species were Coleoptera in the droppings (68.5%) and Diptera in the reedbeds (31.3%), although the latter was less numerous in the fecal samples. The diets of different Italian populations of Eurasian Reed Warbler emerging from our study underline a strong Coleopteran presence, without differences across Italy. Fecal samples appear to be an exhaustive method to study variation in Eurasian Reed Warbler diet and its ecological importance; however, although potential caveats do exist, such as the possible under-representation of Diptera.
Bioclimatic Preferences of the Great Bustard in a Steppe Region
Authors: Ottó Beatrix , Végvári Zsolt
Published: December 2022

(1) The intercorrelated effects of climatic processes and anthropogenic land use changes have been shown to govern the population declines in several bird species, which have led to global extinctions. Ground-nesting birds are especially sensitive to modifications in spatial as well as temporal patterns of climatic change. The Great Bustard (Otis tarda) is one of the most endangered species, which has suffered considerable range contractions and population declines in extensive areas of its historical distribution. (2) Here, we aim to (i) identify the key climatic predictors governing the historical distribution of the Great Bustard within the Carpathian Basin during the past three decades, (ii) provide spatial predictions for the historical range of the study species, and (iii) identify areas where species-specific conservation planning initiatives need to focus on by predicting the distribution of the Great Bustard for future time periods. To do so, here we apply bioclimatic niche modeling implemented in the MaxEnt software package, which is fitted on historical occurrence locations as a function of potential bioclimatic predictors. (3) We show that (i) the most important bioclimatic predictors governing the distribution of the Great Bustard are the annual mean temperature, mean temperatures of the wettest and driest quarters, as well as the annual precipitation; (ii) all lowland areas of the Carpathian Basin were suitable for the Great Bustard during historical time periods; (iii) the SDM predictions show the historical suitability of the Muntenia and Dobrodgea regions and the Upper Thracian Plain; and (iv) the future projections show a substantial decrease in the core distribution area, whereas the boundary areas are expected to remain stable. In summary, our study emphasizes that the distribution modeling of endangered taxa using historical records can strongly support species-specific conservation planning initiatives.
Genetic Detection and a Method to Study the Ecology of Deadly Cubozoan Jellyfish
Authors: Morrissey Scott J. , Jerry Dean R. , Kingsford Michael J.
Published: December 2022

Cubozoan jellyfish pose a risk of envenomation to humans and a threat to many businesses, yet crucial gaps exist in determining threats to stakeholders and understanding their ecology. Environmental DNA (eDNA) provides a cost-effective method for detection that is less labour intensive and provides a higher probability of detection. The objective of this study was to develop, optimise and trial the use of eDNA to detect the Australian box jellyfish, Chironex fleckeri. This species was the focus of this study as it is known to have the strongest venom of any cubozoan; it is responsible for more than 200 recorded deaths in the Indo-Pacific region. Further, its ecology is poorly known. Herein, a specific and sensitive probe-based assay, multiplexed with an endogenous control assay, was developed, and successfully utilised to detect the deadly jellyfish species and differentiate them from closely related taxa. A rapid eDNA decay rate of greater than 99% within 27 h was found with no detectable influence from temperature. The robustness of the technique indicates that it will be of high utility for detection and to address knowledge gaps in the ecology of C. fleckeri; further, it has broad applicability to other types of zooplankton.
The Evolution of Business Center Buildings and Prospects for Their Adaptation in the Post-Pandemic Period in Kazakhstan
Authors: Uzakbayev Turar , Samoilov Konstantin , Kuspangaliyev Bolat , Sadvokasova Gaukhar , Nurkusheva Lyazzat
Published: December 2022

The buildings of business centers make up a significant part of the development of modern cities. Having different sizes, functional content and architectural and artistic solutions, these complexes are often spatial dominants. The compositional accent formed by them indicates the place of concentration for social activity associated not only with business activity but also often with an entertainment pastime program. The formation of a business center as a specific type of building has a long history from open or semiclosed spaces in ancient times, in which trade operations were carried out, to modern multifunctional, multistory buildings. These buildings are located singly or form complexes occupying one or more blocks. Business centers in Kazakhstan developed in a peculiar way, having a break in their development. The analysis carried out made it possible to identify a number of characteristic features of this development. The post-COVID-19 period has formed a new stage in the evolution of business centers. Demand for this type of building has partially declined. Existing buildings began to partially or completely reorient themselves to other activities. At this stage, the most promising option for multistory complexes is their transformation into hotels or residential buildings.
A Multimodal Deep Learning Approach to Predicting Systemic Diseases from Oral Conditions
Authors: Zhao Dan , Homayounfar Morteza , Zhen Zhe , Wu Mei-Zhen , Yu Shuk Yin , Yiu Kai-Hang , Vardhanabhuti Varut , Pelekos George , Jin Lijian , Koohi-Moghadam Mohamad
Published: December 2022

Background: It is known that oral diseases such as periodontal (gum) disease are closely linked to various systemic diseases and disorders. Deep learning advances have the potential to make major contributions to healthcare, particularly in the domains that rely on medical imaging. Incorporating non-imaging information based on clinical and laboratory data may allow clinicians to make more comprehensive and accurate decisions. Methods: Here, we developed a multimodal deep learning method to predict systemic diseases and disorders from oral health conditions. A dual-loss autoencoder was used in the first phase to extract periodontal disease-related features from 1188 panoramic radiographs. Then, in the second phase, we fused the image features with the demographic data and clinical information taken from electronic health records (EHR) to predict systemic diseases. We used receiver operation characteristics (ROC) and accuracy to evaluate our model. The model was further validated by an unseen test dataset. Findings: According to our findings, the top three most accurately predicted chapters, in order, are the Chapters III, VI and IX. The results indicated that the proposed model could predict systemic diseases belonging to Chapters III, VI and IX, with AUC values of 0.92 (95% CI, 0.90–94), 0.87 (95% CI, 0.84–89) and 0.78 (95% CI, 0.75–81), respectively. To assess the robustness of the models, we performed the evaluation on the unseen test dataset for these chapters and the results showed an accuracy of 0.88, 0.82 and 0.72 for Chapters III, VI and IX, respectively. Interpretation: The present study shows that the combination of panoramic radiograph and clinical oral features could be considered to train a fusion deep learning model for predicting systemic diseases and disorders.
Preoperative Transient Elastography in Patients with Esophageal Cancer
Authors: Yang Tzu-Yi , Shih Chia-Pang , Huang Pei-Ching , Tsai Chun-Yi , Chao Yin-Kai
Published: December 2022

Since excessive alcohol consumption is a shared risk factor for esophageal cancer and liver fibrosis, it is possible that patients with esophageal cancer may develop unknown liver fibrosis or cirrhosis. We applied preoperative transient elastography (TE) to patients without recorded cirrhosis undergoing esophagectomy to clarify the validity in predicting postesophagectomy hepatic failure. The cohort consisted of 107 patients who received TE before esophagectomy between June 2018 and December 2021. Patients were categorized into two groups based on the fibrosis score yielded by preoperative TE (mild group: 0~2, n = 92; severe group: 3~4, n = 15). There was no significant difference in demographic data nor surgical variables between the two groups. None of the cohort encountered hepatic failure, yet the severe fibrosis group had a significantly higher rate of pleural effusion (40.0% versus 15.2%, p = 0.03). The areas under the curve (AUCs) of TE in predicting postoperative complications and 180-day mortality were 0.60 (95% CI: 0.46–0.74) and 0.67 (95% CI: 0.51–0.83), respectively. In conclusion, stratification of patients with esophageal cancer who had liver fibrosis by preoperative TE demonstrates significant validity in predicting postoperative pleural effusions. Recruitment of noncirrhotic patients with higher TE scores is warranted to examine its power in other parameters.
The Impact of Clostridioides Difficile Infection in Hospitalized Patients: What Changed during the Pandemic?
Authors: Boeriu Alina , Roman Adina , Dobru Daniela , Stoian Mircea , Voidăzan Septimiu , Fofiu Crina
Published: December 2022

(1) Background: Clostridioides difficile (C. difficile) and SARS-CoV-2 coronavirus represent significant health threats. Our study focused on the impact of concurrent infections on patient outcomes against the backdrop of changes imposed by the pandemic. (2) Materials and methods. We performed a retrospective analysis and included patients diagnosed with CDI who were admitted in our hospital before and during the pandemic. We compared patient exposure to risk factors for CDI in both groups and patient negative outcomes: need for ICU care, prolonged hospitalization, organ failure, toxic megacolon, and death. (3) Results. Overall, 188 patients were included, of which 100 had CDI (the pre-pandemic group), and 88 patients presented both CDI and COVID-19 (the pandemic group). Patients in the pandemic group were significantly older, with a higher Charlson Comorbidity Index (CCI) and a greater exposure to antibiotics and corticosteroids, and were more likely to develop organ dysfunction, to require ICU care and have prolonged hospitalization. The severity of COVID-19, leukocytosis and increased D-dimer levels were indicators of poor prognosis in the pandemic group. Higher CCI scores and leukocytosis increased the risk for negative outcomes in CDI alone patients. (4) Conclusions. The study highlights the negative impact of associated infections on patient outcome. The severity of COVID-19 directly influences the prognosis of patients with concurrent infections
Somatosensory and Gustatory Profiling in the Orofacial Region
Authors: Hartmann Amely , Welte-Jzyk Claudia , Schmidtmann Irene , Geber Christian , Al-Nawas Bilal , Daubländer Monika
Published: December 2022

Quantitative sensory testing (QST) is a standard procedure in medicine to describe sensory patterns in various pathologies. The aim of this prospective clinical study was to define reference values of the trigeminal nerve (V3), including taste qualities, to create a compatibility for sensory loss or gain in pathologies. Fifty-one patients were included, and a standardized testing battery with 11 QST parameters according to the German Research Network on Neuropathic Pain (DFNS) was applied complemented by quantitative gustatory assessments. Significant somatosensory differences were found between the test sites (MDT at the chin, WDT at the lower lip) but no effect was detected for gender, age, and between body types. Taste sensitivity was dependent on concentration, gender (females being more sensitive) and increasing age (for bitter and sour taste). We provide reference values for somatosensory and gustatory testing of the facial area. Our data facilitate the detection of neurosensory abnormalities in the orofacial region. This might also serve as a control setting for COVID-19.
Endoscopic Diagnosis of Eosinophilic Esophagitis: Basics and Recent Advances
Authors: Abe Yasuhiko , Sasaki Yu , Yagi Makoto , Mizumoto Naoko , Onozato Yusuke , Umehara Matsuki , Ueno Yoshiyuki
Published: December 2022

Eosinophilic esophagitis (EoE) is a chronic, immune-mediated inflammatory disease, characterized by esophageal dysfunction and intense eosinophil infiltration localized in the esophagus. In recent decades, EoE has become a growing concern as a major cause of dysphagia and food impaction in adolescents and adults. EoE is a clinicopathological disease for which the histological demonstration of esophageal eosinophilia is essential for diagnosis. Therefore, the recognition of the characteristic endoscopic features with subsequent biopsy are critical for early definitive diagnosis and treatment, in order to prevent complications. Accumulating reports have revealed that EoE has several non-specific characteristic endoscopic findings, such as rings, furrows, white exudates, stricture/narrowing, edema, and crepe-paper esophagus. These findings were recently unified under the EoE endoscopic reference score (EREFS), which has been widely used as an objective, standard measurement for endoscopic EoE assessment. However, the diagnostic consistency of those findings among endoscopists is still inadequate, leading to underdiagnosis or misdiagnosis. Some endoscopic findings suggestive of EoE, such as multiple polypoid lesions, caterpillar sign, ankylosaurus back sign, and tug sign/pull sign, will aid the diagnosis. In addition, image-enhanced endoscopy represented by narrow band imaging, endocytoscopy, and artificial intelligence are expected to render endoscopic diagnosis more efficient and less invasive. This review focuses on suggestions for endoscopic assessment and biopsy, including recent advances in optical technology which may improve the diagnosis of EoE.
The Effect of Primary Aldosteronism on Carotid Artery Texture in Ultrasound Images
Authors: Kaushik Sumit , Majtan Bohumil , Holaj Robert , Baručić Denis , Kološová Barbora , Widimský Jiří , Kybic Jan
Published: December 2022

Primary aldosteronism (PA) is the most frequent cause of secondary hypertension. Early diagnoses of PA are essential to avoid the long-term negative effects of elevated aldosterone concentration on the cardiovascular and renal system. In this work, we study the texture of the carotid artery vessel wall from longitudinal ultrasound images in order to automatically distinguish between PA and essential hypertension (EH). The texture is characterized using 140 Haralick and 10 wavelet features evaluated in a region of interest in the vessel wall, followed by the XGBoost classifier. Carotid ultrasound studies were carried out on 33 patients aged 42–72 years with PA, 52 patients with EH, and 33 normotensive controls. For the most clinically relevant task of distinguishing PA and EH classes, we achieved a classification accuracy of 73% as assessed by a leave-one-out procedure. This result is promising even compared to the 57% prediction accuracy using clinical characteristics alone or 63% accuracy using a combination of clinical characteristics and intima-media thickness (IMT) parameters. If the accuracy is improved and the method incorporated into standard clinical procedures, this could eventually lead to an improvement in the early diagnosis of PA and consequently improve the clinical outcome for these patients in future.
Smart Visualization of Medical Images as a Tool in the Function of Education in Neuroradiology
Authors: Simović Aleksandar , Lutovac-Banduka Maja , Lekić Snežana , Kuleto Valentin
Published: December 2022

The smart visualization of medical images (SVMI) model is based on multi-detector computed tomography (MDCT) data sets and can provide a clearer view of changes in the brain, such as tumors (expansive changes), bleeding, and ischemia on native imaging (i.e., a non-contrast MDCT scan). The new SVMI method provides a more precise representation of the brain image by hiding pixels that are not carrying information and rescaling and coloring the range of pixels essential for detecting and visualizing the disease. In addition, SVMI can be used to avoid the additional exposure of patients to ionizing radiation, which can lead to the occurrence of allergic reactions due to the contrast media administration. Results of the SVMI model were compared with the final diagnosis of the disease after additional diagnostics and confirmation by neuroradiologists, who are highly trained physicians with many years of experience. The application of the realized and presented SVMI model can optimize the engagement of material, medical, and human resources and has the potential for general application in medical training, education, and clinical research.
Expression Analysis of Five Different Long Non-Coding Ribonucleic Acids in Nonsmall-Cell Lung Carcinoma Tumor and Tumor-Derived Exosomes
Authors: Talebi Samaneh , Abadi Asal Jalal , Kazemioula Golnesa , Hosseini Nayyerehalsadat , Taheri Forough , Pourali Saba , Mahdloo Touba , Rezaei Marzieh , Mirinezhad Mohammadreza , Ajami Naser , Salmaninejad Arash
Published: December 2022

Long non-coding ribonucleic acids (LncRNAs) are recently known for their role in regulating gene expression and the development of cancer. Controversial results indicate a correlation between the tissue expression of LncRNA and LncRNA content of extracellular vesicles. The present study aimed to evaluate the expression of different LncRNAs in non-small cell lung cancer (NSCLC) patients in tumor tissue, adjacent non-cancerous tissue (ANCT), and exosome-mediated lncRNA. Tumor and ANCT, as well as serum samples of 168 patient with NSCLC, were collected. The GHSROS, HNF1A-AS1, HOTAIR, HMlincRNA717, and LINCRNA-p21 relative expressions in tumor tissue, ANCT, and serum exosomes were evaluated in NSCLC patients. Among 168 NSCLC samples, the expressions of GHSROS (REx = 3.64, p = 0.028), HNF1A-AS1 (REx = 2.97, p = 0.041), and HOTAIR (REx = 2.9, p = 0.0389) were upregulated, and the expressions of HMlincRNA717 (REx = −4.56, p = 0.0012) and LINCRNA-p21 (REx = −5.14, p = 0.00334) were downregulated in tumor tissue in contrast to ANCT. Moreover, similar statistical differences were seen in the exosome-derived RNA of tumor tissues in contrast to ANCT samples. A panel of the five lncRNAs demonstrated that the area under the curve (AUC) for exosome and tumor was 0.937 (standard error: 0.012, p value < 0.0001). LncRNAs GHSROS, HNF1A-AS1, and HOTAIR showed high expression in tumor tissue and exosome content in NSCLC, and a panel that consisted of all five lncRNAs improved diagnosis of NSCLC.
Orthopedic Device-Related Infections Due to Emerging Pathogens Diagnosed by a Combination of Microbiological Approaches: Case Series and Literature Review
Authors: Quirino Angela , Marascio Nadia , Scarlata Giuseppe Guido Maria , Cicino Claudia , Pavia Grazia , Pantanella Marta , Carlisi Giovanni , Mercurio Michele , Familiari Filippo , Rotundo Salvatore , Olivadese Vincenzo , La Gamba Valentina , Serapide Francesca , Gasparini Giorgio , Matera Giovanni
Published: December 2022

Orthopedic and trauma device-related infections (ODRI) due to high virulence microorganisms are a devastating complication after orthopedic surgery. Coagulase-negative Staphylococci (CoNS) are mainly involved but commensal bacteria, located in human mucous membranes, are emerging pathogens in ODRI. Currently, bacterial culture is the gold standard for ODRI but the diagnostic process remains time consuming and laborious. We evaluated a combination of microbiological approaches in the diagnosis of emerging pathogens involved in ODRI. We analyzed two synovial fluids, five tissue samples and five surgical wound swabs from two different patients with ODRI, attending the Department of Orthopedic and Trauma Surgery of Mater Domini Teaching Hospital, Catanzaro, Italy. Identification was carried out with a combination of microbiological approaches (culture, mass spectrometry and 16s rRNA gene sequencing). We demonstrated the importance of a combination of microbiological approaches for the diagnosis of emerging pathogens in ODRI, because the low number of cases in the literature makes it very difficult to formulate guidelines for the management of patients.
A Group Handover Scheme for Supporting Drone Services in IoT-Based 5G Network Architectures
Authors: Skondras Emmanouil , Kosmopoulos Ioannis , Michailidis Emmanouel , Michalas Angelos , Vergados Dimitrios
Published: December 2022

Next generation mobile networks are expected to integrate multiple drones organized in Flying Ad Hoc Networks (FANETs) to support demanding and diverse services. The highly mobile drones should always be connected to the network in order to satisfy the strict requirements of upcoming applications. As the number of drones increases, they burden the network with the management of signaling and continuous monitoring of the drones during data transmission. Therefore, designing transmission mechanisms for fifth-generation (5G) drone-aided networks and using clustering algorithms for their grouping is of paramount importance. In this paper, a clustering and selection algorithm of the cluster head is proposed together with an efficient Group Handover (GHO) scheme that details how the respective Point of Access (PoA) groups will be clustered. Subsequently, for each cluster, the PoA elects a Cluster Head (CH), which is responsible for manipulating the mobility of the cluster by orchestrating the handover initiation (HO initiation), the network selection, and the handover execution (HO execution) processes. Moreover, the members of the cluster are informed about the impending HO from the CH. As a result, they establish new uplink and downlink communication channels to exchange data packets. In order to evaluate the proposed HO scheme, extensive simulations are carried out for a next-generation drone network architecture that supports Internet of Things (IoT) and multimedia services. This architecture relies on IEEE 802.11p Wireless Access for Vehicular Environment (WAVE) Road Side Units (RSUs) as well as Long-Term Evolution Advanced (LTE-A) and IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMAX). Furthermore, the proposed scheme is also evaluated in a real-world scenario using a testbed deployed in a controlled laboratory environment. Both simulation and real-world experimental results verify that the proposed scheme outperforms existing HO algorithms.
A Finite Element Approximation for Nematic Liquid Crystal Flow with Stretching Effect Based on Nonincremental Pressure-Correction Method
Authors: Meng Zhaoxia , Liu Meng , Jia Hongen
Published: December 2022

In this paper, a new decoupling method is proposed to solve a nematic liquid crystal flow with stretching effect. In the finite element discrete framework, the director vector is calculated by introducing a new auxiliary variable w, and the velocity vector and scalar pressure are decoupled by a nonincremental pressure-correction projection method. Then, the energy dissipation law and unconditional energy stability of the resulting system are given. Finally, some numerical examples are given to verify the effects of various parameters on the singularity annihilation, stability and accuracy in space and time.
Characterization of Nitrogen Use by Neotropical Myrtaceae in Dry and Wet Forests of Southeast Brazil
Authors: Pereira-Silva Erico Fernando Lopes , Joly Carlos , Sodek Ladaslav , Hardt Elisa , Aidar Marcos
Published: December 2022

We hypothesized that neotropical Myrtaceae could be organized into groups that are naturally less or non-responsive to NO3−, and that use other N forms, such as amino acids, for internal N transport. Ecophysiological tests were conducted to measure nitrate reductase activity (NRA), NO3− content, total N, δ15N natural abundance, the C:N ratio in leaves, free amino acid, and NO3− transport via xylem sap. We showed that Myrtaceae tree species have a relatively low NRA, in addition to little NO3− in leaves and free NO3− in the xylem sap during the wet and dry seasons. We suggested a possible compartmentalization of N use, wherein plants derive their internal N from and use their transport mechanism to move N between below-ground and above-ground parts, assimilating and transporting more N and C through amino acids such as glutamine, arginine, and citrulline. Evidence of low NO3− availability in tropical soils is important when trying to understand forest species’ N-use strategies, given their importance to plant nutrition. Differences in the responses of some Myrtaceae species to the seasonality of environmental factors suggest the need for further studies concerning N in natural forests, for example, to help understand the problem of N deposition ecosystems.
Founder and Descendant vs. Professional CEO: Does CEO Overconfidence Affect Tax Avoidance in the Indonesia Case?
Authors: Sutrisno Paulina , Utama Sidharta , Anitawati Hermawan Ancella , Fatima Eliza
Published: December 2022

This study aims to test whether the founder or descendants of CEOs have differences from professional CEOs in influencing the relationship between CEO overconfidence and tax avoidance. Overconfident CEOs have strong incentives to avoid taxes. However, the role of the founder or descendant CEOs is expected to mitigate the relationship between the CEO’s overconfidence and tax avoidance. This study used a sample of non-financial companies listed on the Indonesia Stock Exchange in 2012–2019 and tested random effect panel data. The results of this study show that CEO-led companies that are overconfident are more driven to tax avoidance. Meanwhile, the relationship between CEO overconfidence and tax avoidance is not influenced by the presence of a descendant, founder, or professional CEO. Indonesia as one of the countries that adheres to a two tier governance system, the founder or descendant CEO is not the only significant actor in the company but based on the upper echelon theory that role of the entire company management team that influences the company’s policy strategy. This study provides implications for developing the literature regarding the relationship between CEO overconfidence and tax avoidance. However, the relationship between CEO overconfidence and tax avoidance is not influenced by the presence of the founder, descendant, or professional CEO. Likewise, this research is useful for investors, creditors, and regulators in paying attention to the characteristics of the CEO in making decisions.
Examination of the Effect of Career Barriers and Presenteeism Behaviors on Teacher Professionalism through Structural Equation Model
Authors: Güngör Nuri Berk , Kurtipek Serkan , Soyer Fikret , İlhan Ekrem Levent , Talaghir Laurentiu-Gabriel
Published: December 2022

The aim of this study is to reveal the effect of career barriers and presenteeism behaviors of physical education and sports teachers on teacher professionalism through a structural equation model. The hypotheses presented because of the literature review were tested with the fictional model. The sample of the study consists of a total of 411 physical education and sports teachers, who work in Ankara. As data collection tools, the Teachers’ Career Barriers Scale, the Stanford Presenteeism Scale and the Teacher Professionalism Scale were used in the research. In the analysis of the data, the theoretically created model was tested through a structural equation model. Considering the findings obtained from the research, it can be stated that the participants are faced with career barriers, that they exhibit their presenteeism behaviors at a reasonable level, and that the professionalism level is above average. On the other hand, it was concluded that male participants encountered more career barriers and displayed more presenteeism behavior, while female participants had a higher professionalism level than that of male participants. In addition, it was determined that administrative barriers affect teacher professionalism, while presenteeism behaviors do not have an impact on professionalism level.
Identity-Conscious Scholar Formation: Shaping More Inclusive Academic Communities
Authors: Talusan Liza A.
Published: December 2022

As colleges and universities commit to creating and sustaining a more inclusive and equitable community, it is important to understand how the role of identity intersects with the existing processes of socialization and development. An identity-conscious practice is the process of realizing that who we are informs and impacts how we act, interact, and see the world around us. In particular, how identity should be considered as part of bidirectional socialization. Understanding socialization as bidirectional means that organizations can contribute to healthier communities that not only retain scholars but also engage with the identities and experiences of their students. This paper explores the ways in which doctoral students of color, in particular, Asian American and Pacific Islanders, experience the socialization and development processes through the lens of race; identifies the key organizational challenges; and provides recommendations for how colleges and universities can move towards a more inclusive and equitable community. This paper advances a framework for an identity-conscious model of the formation of scholars.
Development and Validation of a Critical Thinking Assessment-Scale Short Form
Authors: Payan-Carreira Rita , Sacau-Fontenla Ana , Rebelo Hugo , Sebastião Luis , Pnevmatikos Dimitris
Published: December 2022

This study presents and validates the psychometric characteristics of a short form of the Critical Thinking Self-assessment Scale (CTSAS). The original CTSAS was composed of six subscales representing the six components of Facione’s conceptualisation of critical thinking. The CTSAS short form kept the same structures and reduced the number of items from 115 in the original version, to 60. The CTSAS short form was tested with a sample of 531 higher education students from five countries (Germany, Greece, Lithuania, Romania, and Portugal) enrolled in different disciplinary fields (Business Informatics, Teacher Education, English as a Foreign Language, Business and Economics, and Veterinary Medicine). The confirmatory analysis was used to test the new instrument reliability, internal consistency, and construct validity. Both the models that hypothesized the six factors to be correlated and to tap into a second-order factor representing the complex concept of critical thinking, had acceptable fit to the data. The instrument showed strong internal consistency (α = 0.969) and strong positive correlations between skills and between the skills and the overall scale (p < 0.05). Despite the unbalanced sex distribution in the population (close to 75% females), the instrument retained its factorial structure invariance across sexes. Therefore, the new instrument shows adequate goodness of fit and retained stability and reliability, and is proposed as a valid and reliable means to evaluate and monitor critical thinking in university students.
Intelligent Fault Diagnosis Method for Industrial Processing Equipment by ICECNN-1D
Authors: Li Zhaofei , Jiang Yutao , Liu Bowen , Ma Le , Qu Jianfeng , Chai Yi
Published: December 2022

Intelligent algorithm has been widely implemented to effectively diagnose faults in industrial instrument, electrical equipment and mechanical equipment. In addition, the rapid development of sensing technology generated enormous time series signal. Accordingly, diagnosing faults by analyzing time series signal has been widely developed. This paper aims to diagnose faults by applying improved Convolution Neural Network with Compression Enhancement (ICECNN-1D) to analyze time series signal, which effectively considers time series property of signal while diagnosing faults by artificial intelligence. Additionally, a large number of trend features and fluctuation features in high-frequency time series are also considered. the recognition rates of almost other machine learning algorithm are less than 90% in the experiments. Other methods may provide high rate of recognition, but their fluctuation of the recognition rate has varied obviously with different loads, and results provide undesirable ability of generalization under different working conditions. Comparatively, ICECNN-1D model provides high recognition rate and terrific ability of generation while processing time series with high frequency, and its accuracy of the recognition rate fluctuates inconspicuously with different loads.
Global Scattering Center Representation of Target Wide-Angle Single Reflection/Diffraction Mechanisms Based on the Multiple Manifold Concept
Authors: Lu Jinwen , Zhang Yanjin , Yan Hua , Zhang Lei , Yin Hongcheng
Published: December 2022

Many radar applications, such as system design and testing and target detection and recognition, need to compress and rapidly reconstruct the target-scattering characteristics data through some suitable sparse representations, while the scattering center (SC) model resulting from different scattering mechanisms is just a prospective candidate. For the target scattering characteristics data with single reflection/diffraction mechanisms, the multimanifold structures of wide-angle SCs were revealed in light of asymptotic high-frequency theory and ray theory of electromagnetic field. Then the multimanifold clustering and curve/surface fitting algorithms are introduced to construct the target global SC (GSC) model. Compared with simulation data of sphere-cone target, the RCS at elevation 90°, azimuth 0–180° can be accurately reconstructed by only 77 parameters, the compress rate and root mean square error are 0.66 and 1.17 dB respectively. Simulation results showed that the GSC model could greatly compress the wide-angle scattering data while ensuring a suitable reconstruction accuracy. The proposed multimanifold GSC representation is convenient to implement and can effectively replace the redundant original scattering characteristics data.
A Direct Single-Phase to Three-Phase AC/AC Power Converter
Authors: Biswas Shuvra Prokash , Uddin Md. Shihab , Islam Md. Rabiul , Mondal Sudipto , Nath Joysree
Published: December 2022

The traditional DC-link indirect AC/AC power converters (AC/DC/AC converters) employ two-stage power conversion, which increases the circuit complexity along with gate driving challenges, placing an excessive burden on the processor while implementing complex switching modulation techniques and leads to power conversion losses due to the use of a large amount of controlled power semiconductor switches. On the contrary, the traditional direct AC/AC voltage controllers, as well as frequency changers, suffer from high total harmonic distortion (THD) problems. In this paper, a new single-phase to three-phase AC/AC step-down power converter is proposed, which utilizes a multi-linking transformer and bilateral triode thyristors (TRIACs) as power semiconductor switches. The proposed direct AC/AC power converter employs single-stage power conversion, which mitigates the complexity of two-stage DC-link indirect AC/AC converters and traditional single-stage AC/AC frequency changers. Instead of using high-frequency pulse width modulated gate driving signals, line frequency gate pulses are used to trigger the TRIACs of the proposed AC/AC converter, which not only aids in reducing the power loss of the converter but also mitigates the cost and complexity of gate driver circuits. The proposed AC/AC converter reduces the THD of the output voltage significantly as compared to traditional direct AC/AC frequency changers. The performance of the proposed AC/AC converter is validated against RL and induction motor load in terms of overall THD and individual harmonic components through MATLAB/Simulink environment. A reduced-scale laboratory prototype is built and tested to evaluate the performance of the proposed AC/AC power converter. The experimental and simulation outcomes reveal the feasibility and excellent features of the proposed single-phase to three-phase AC/AC converter topology.
Broadband Modeling and Simulation Strategy for Conducted Emissions of Power Electronic Systems Up to 400 MHz
Authors: Riener Christian , Hackl Herbert , Hansen Jan , Barchanski Andreas , Bauernfeind Thomas , Pak Amin , Auinger Bernhard
Published: December 2022

Energy efficiency is becoming one of the most important topics in electronics. Among others, wide band-gap semiconductors can raise efficiency and lead to shrinking volumes in power conversion systems. As different markets have regulations that require different designs, it is necessary to cope with a large variety of similar designs. By using effective modeling and simulation strategies, the efforts of building these variants can be diminished, and re-designs can be avoided. In this paper, we present a universally valid way to come to reasonable simulation results for conducted emissions of a power electronic system in the frequency range from 150 kHz up to 400 MHz. After giving an overview of the state-of-the-art, the authors show how to implement and set up a simulation environment for a gallium-nitride (GaN) power converter. It shows how to differentiate between important and not that important components for Electromagnetic Compatibility (EMC), how to model these components, the printed circuit board, the load, and the setup, including the Line Impedance Stabilization Networks (LISNs), etc. Multiport S-parameter strategies as well as vector fitting methods are employed. Computational costs are kept low, and all simulations are verified with measurements; thus, this model is valid up to 400 MHz.
Convolutional Network Research for Defect Identification of Productor Appearance Surface
Authors: Xie Xu , Shen Xizhong
Published: December 2022

The accurate and rapid identification of surface defects is an important element of product appearance quality evaluation, and the application of deep learning for surface defect recognition is an ongoing hot topic. In this paper, a lightweight KD-EG-RepVGG network based on structural reparameterization is designed for the identification of surface defects on strip steel as an example. In order to improve the stability and accuracy in the recognition of strip steel surface defects, an efficient attention network was introduced into the network, and then a Gaussian error linear activation function was applied in order to prevent the neurons from being set to zero during neural network training, leaving neuron parameters without being updated. Finally, knowledge distillation is used to transfer the knowledge of the RepVGG-A0 network to give the lightweight model better accuracy and generalization capability. The outcomes of the experiments indicate that the model has a computational and parametric volume of 22.3 M and 0.14 M, respectively, in the inference phase, a defect recognition accuracy of 99.44% on the test set, and a single image detection speed of 2.4 ms, making it more suitable for deployment in real engineering environments.
Design of a Wheel-Side Rear-Drive Distributed Electric Bus Control Strategy Based on Self-Correcting Fuzzy Control
Authors: Luo Wenhua , Chen Huipeng , Zhu Shaopeng , Chen Sen , Gao Jian , Wang Weiyang , Zhou Rougang
Published: December 2022

A suitable and effective control strategy is a prerequisite for achieving the stable driving of a distributed drive electric bus. In order to effectively utilize the advantage of the independent controllability of each rear wheel, this paper designs and compares two direct transverse moment control strategies of sliding mode control and self-correcting fuzzy control and distributes the drive torque in combination with the vehicle steering torque constraint. Moreover, based on the established seven-degrees-of-freedom vehicle model, the simulation was verified in the MATLAB/Simulink and TruckSim co-simulation platforms. The simulation results show that, compared with the sliding mode control, the self-correcting fuzzy control strategy can reduce the maximum sideslip angle deviation by 19%, 6% and 9.7%, respectively, under the double shift line condition, the high-speed small steering angle step condition and the sinusoidal line shift condition and can more effectively reduce the vehicle lateral acceleration and improve the vehicle yaw rate tracking ability, significantly improving the lateral stability of the vehicle.
Hybrid Beamforming for Multi-User Millimeter-Wave Heterogeneous Networks
Authors: Li Zhannan , Chen Tao
Published: December 2022

Millimeter-wave (mmWave) communications are a critical technique with next-generation network characteristics such as ultra-dense small cells can meet the skyrocketing demand for mobile data. Hybrid precoding, which combines analog and digital processing to provide both spatial diversity gains and beamforming, is commonly studied for mmWave communications to lower the power and cost consumption of radio frequency (RF) networks. However, the combination of ultra-dense small cells and ever-increasing data traffic results in massive interference. In this paper, we propose a minimum mean square error (MMSE)-based hybrid beamforming strategy for downlink mmWave MIMO two-tier heterogeneous networks (HetNets). The analog beamforming is generalized by an orthogonal matching pursuit technique. The analog beamforming problem is formulated as a sparse signal recovery problem. An MMSE-based digital beamforming algorithm is proposed to minimize the sum MSE of the user-intended data streams so that the inter- and intra-tier interferences are mitigated iteratively. The simulation results demonstrate the advantageous performance of the proposed hybrid beamforming schemes under different cellular cooperation and data transmission scenarios when hardware constraints are taken into account.
A Novel Geo-Social-Aware Video Edge Delivery Strategy Based on Modeling of Social-Geographical Dynamic in an Urban Area
Authors: Jia Shijie , Cui Yan , Zhang Ruiling
Published: December 2022

Social networks change the way and approaches of video spread and promote range and speed of video spread, which results in frequent traffic blowout and a heavy load on the networks. The social and geographical communication efficiency determines the efficiency of video sharing, which enables the eruptible traffic to be offloaded in underlaying networks to relieve the load of networks and ensure the user quality of the experience. In this paper, we propose a novel geo-social-aware video edge delivery strategy based on the modeling of the social-geographical dynamic in urban area (GSVD). By investigating the frequency of sharing behaviors, social communication efficiency, and efficiency of social sub-network consisting of one-hop social neighbors of users, GSVD estimates the interactive and basic social relationship to calculate the closeness of the social relationship between mobile users. GSVD makes use of grid partition and coding subarea to express the geographical location of mobile users and designs a calculation method of coding-based geographical distance. GSVD considers the dynamic update of social distance and geographical location and designs a measurement of video delivery quality in terms of delivery delay and playback continuity. A strategy of video delivery with the consideration of adapting to social-geographical dynamic is designed, which effectively promotes the efficiency of video sharing. Extensive tests show how GSVD achieves much better performance results in comparison with other state of the art solutions.
Path Tracking for Car-like Robots Based on Neural Networks with NMPC as Learning Samples
Authors: Bai Guoxing , Meng Yu , Liu Li , Gu Qing , Huang Jianxiu , Liang Guodong , Wang Guodong , Liu Li , Chang Xinrui , Gan Xin
Published: December 2022

In the field of path tracking for car-like robots, although nonlinear model predictive control (NMPC) can handle the system constraints well, its real-time performance is poor. To solve this problem, a neural network control method with NMPC as the learning sample is proposed. The design process of this control method includes establishing the NMPC controller based on the time-varying local model, generating learning samples based on this NMPC controller, and training to obtain the neural network controller. The proposed controller is tested by a joint simulation of MATLAB and Carsim and compared with other controllers. According to the simulation results, the accuracy of the NN controller is close to that of the NMPC controller and far better than that of the Stanley controller. In all simulations, the absolute value of displacement error of the NN controller does not exceed 0.2854 m, and the absolute value of heading error does not exceed 0.2279 rad. In addition, the real-time performance of the NN controller is better than that of the NMPC controller. The maximum time cost and average time cost of the NN controller are, respectively, 40.91% and 22.37% smaller than those of the NMPC controller under the same conditions.