bluuebunny/crossref_metadata_2025 huggingface dataset:
The PSA-NCAM-Positive “Immature” Neurons: An Old Discovery Providing New Vistas on Brain Structural Plasticity
Authors: Bonfanti Luca , Seki Tatsunori
Published: September 2021

Studies on brain plasticity have undertaken different roads, tackling a wide range of biological processes: from small synaptic changes affecting the contacts among neurons at the very tip of their processes, to birth, differentiation, and integration of new neurons (adult neurogenesis). Stem cell-driven adult neurogenesis is an exception in the substantially static mammalian brain, yet, it has dominated the research in neurodevelopmental biology during the last thirty years. Studies of comparative neuroplasticity have revealed that neurogenic processes are reduced in large-brained mammals, including humans. On the other hand, large-brained mammals, with respect to rodents, host large populations of special “immature” neurons that are generated prenatally but express immature markers in adulthood. The history of these “immature” neurons started from studies on adhesion molecules carried out at the beginning of the nineties. The identity of these neurons as “stand by” cells “frozen” in a state of immaturity remained un-detected for long time, because of their ill-defined features and because clouded by research ef-forts focused on adult neurogenesis. In this review article, the history of these cells will be reconstructed, and a series of nuances and confounding factors that have hindered the distinction between newly generated and “immature” neurons will be addressed.
Charting a Course towards Resilience Following Adverse Childhood Experiences: Addressing Intergenerational Trauma via Strengths-Based Intervention
Authors: Howell Kathryn H. , Miller-Graff Laura E. , Martinez-Torteya Cecilia , Napier Taylor R. , Carney Jessica R.
Published: September 2021

Early research on adverse childhood experiences (ACEs) provided staggering evidence of the significant ramifications of ACEs on physical health and functioning. It brought to the forefront the importance of addressing trauma and family dysfunction to enhance public health. Over the past several decades, the study of childhood adversity has blossomed, with expanded conceptualizations and assessments of ACEs. This review brings together various biological, psychological, and sociological principles that inform our understanding of ACEs and our approach to treatment. Specifically, we document the evolution of ACEs research, focusing on the intergenerational impact of ACEs, the importance of incorporating a resilience framework when examining ACEs, and implementing interventions that address adversity across generations and at multiple levels of the social ecology. Evidence is provided to support the evolving perspective that ACEs have long-lasting effects beyond the ACE(s)-exposed individual, with significant attention to the impact of parental ACEs on child development. An intergenerational and multilevel approach to understanding and addressing ACEs offers specific areas to target in interventions and in public policy.
Narrative Abilities and Episodic Memory in School-Aged Children Followed by Child Protective Services
Authors: Salomão Sanmya , Canário Catarina , Cruz Orlanda
Published: September 2021

The ability to narrate routine familiar events develops gradually during middle childhood, in increasingly higher levels of coherence and temporal cohesion. Improvements in episodic memory are also observed, reflecting children’s increasing ability to recall specific circumstances of past events and personal experiences. Even though several studies have evaluated children’s narrative abilities and episodic memory, little information is available regarding the children exposed to risks that justify their referral to Child Protective Services (CPS). The current study analysed children’s narrative abilities and episodic memory performance, according to the circumstances related to the referral to CPS. Event schema representation, narrative coherence, narrative temporal cohesion, and episodic memory concerning routine and specific personal events in family context were analysed in a sample of 56 school-aged children followed by the CPS in Portugal. Children referred to CPS due to disruptive behaviour presented higher episodic memory performance, compared to those exposed to domestic violence, neglect, and abuse. No significant differences were found between groups regarding narrative abilities related to familiar routine events. Results highlight the relevance of evaluating the adverse circumstances that lead to CPS referral, considering the levels of risk and danger involved, given its differential effects on children’s episodic memory development.
Forced Oscillation Technique for Monitoring the Respiratory Status of Children with Cystic Fibrosis: A Systematic Review
Authors: Loukou Ioanna , Moustaki Maria , Deligianni Agni , Sardeli Olympia , Douros Konstantinos
Published: September 2021

Spirometry is considered the gold standard method for monitoring lung function of patients with cystic fibrosis (CF) but it requires patients’ cooperation and therefore it is not useful for the majority of preschool-aged children. Oscillometry is an alternative modality for lung function monitoring that requires minimal cooperation and can be applied in children as young as 3 years of age. Furthermore, it generates lesser aerosol compared to spirometry, an issue that is of considerable importance in the COVID-19 era. The aim of this review was to present the existing clinical data regarding the application of oscillometry in children and adolescents with CF. The method seems to have acceptable feasibility and repeatability. However, there is conflicting data regarding the correlation of oscillometry values with the clinical symptoms of CF patients either in clinically stable or in exacerbation periods. Furthermore, it is not clear to what extent oscillometry measurements correlate with the spirometry indices. Based on current evidence, spirometry cannot be substituted by oscillometry in the monitoring of the respiratory status of children and adolescents with CF.
Terrestrial Biota as Bioindicators for Microplastics and Potentially Toxic Elements
Authors: Al Malki Jamila S. , Hussien Nahed Ahmed , Tantawy Ehab M. , Khattab Yassir , Mohammadein Amaal
Published: September 2021

Plastic products used in our daily life remain in the environment for a long time. Plastics decompose gradually into smaller fragments (<5 mm) known as microplastics. There are different sources of microplastics contamination, including plastic bags, masks, synthetic textiles, and various coatings. Microplastics’ smaller size enhances toxic pollutants’ adsorption, through which they are easily digested by small biota and finally accumulated along the food chain. Many studies are found concerning marine microplastic distribution and pollution; however, rarely do they address terrestrial contamination. The terrestrial species Eobania vermiculata, Rumina decollata, Porcellio, Armadillo, Lumbricus terrestris, and Scolopendra were evaluated as bioindicators for soil pollution by microplastics and some potentially toxic metallic elements. Microplastics were isolated with the help of caustic potash. The particles were characterized by infrared spectroscopy (FTIR); some associated potentially toxic metals were assessed in the filtrate by inductively coupled plasma spectrometry (ICP). The following polymers were present in all studied samples: copolyamide, nylon, high- and low-density polyethylene, polyamide, and polyester. In addition, the metallic elements antimony, iron, aluminum, selenium, and zinc were determined with different concentrations. Thus, terrestrial biota can serve as bioindicators for microplastic pollution of soil, which could act as a vector for potentially toxic elements.
Imparting Strong Antifouling Properties to the Transparent PVB Coating through the Zwitterionic Compound Condensation
Authors: Zhang Jianbin , Bo Shangshang , Feng Haiyan , Yu Bo , Yu Qiangliang , Yang Wufang , Pei Xiaowei , Zhou Feng
Published: September 2021

Fouling is a ubiquitous and longstanding challenge that causes both economic and environmental problems, especially for underwater detection equipment, as fouling directly limits the normal services and functions of such equipment. Therefore, it is necessary to develop coatings with high transparency and good antifouling performance. Herein, a novel zwitterion compound was synthesized, and an antifouling coating with excellent comprehensive properties was prepared by integrating 3-[[3-(triethoxysilyl)-propyl] amino] propane-1-sulfonic acid (TPAPS) into polyvinyl butyral (PVB) polymer, which possesses excellent mechanical properties and transparency. The physical and chemical, mechanical, and antifouling properties, and the light transmittance of the coating were characterized by the SEM, FT-IR, XPS, UV-VIS. The results show that the coating had good mechanical properties and adhesion to the substrate, and the strong hydration ability of TPAPS endowed the coating with excellent resistance to oil stains and biofouling. More importantly, the structure of the coating was homogenous and its surface roughness was very little, which imparted the coating with high transmittance. This research provides a facile approach for synthesizing high-transparency materials with excellent antifouling and mechanical properties.
Proso-Millet-Starch-Based Edible Films: An Innovative Approach for Food Industries
Authors: Punia Bangar Sneh , Sandhu Kawaljit Singh , Rusu Alexandru Vasile , Kaur Pinderpal , Purewal Sukhvinder Singh , Kaur Maninder , Kaur Navneet , Trif Monica
Published: September 2021

The present investigation searches for functional and antioxidant properties in proso millet starch and films. Proso millet starch was studied for its physical, chemical, morphological, and antioxidant properties. Furthermore, films were prepared from proso millet starch (native) and a starch–ĸ-carrageenan blend. Both films were characterized for moisture content, thickness, water-solubility, opacity, water vapor permeability, and textural and antioxidant properties. The amylose content, water absorption capacity, swelling, and solubility power of the proso millet starch were 19.19%, 87.5%, 15.32%, and 19%, respectively. Compared to aqueous extracts (0.68 mg GAE/g and 0.36 mg AAE/g), the total phenolics and total antioxidant capacity were observed to be higher in methanolic starch extracts (0.75 mg GAE/g and 0.41 mg AAE/g). Methanol extracts of native starch-based films showed higher antioxidant activity than the film prepared using a ĸ-carrageenan blend. The water vapor permeability and solubility of films prepared from native starch (2.38 g/Pa·s·m2 and 28%) were lower than those prepared using the ĸ-carrageenan blend (3.19 g/Pa·s·m2 and 42.05%). The findings may be of commercial interest to pharmaceutical and food industries in producing new antioxidant-rich drugs and food products.
Polarization Splitter-Rotator Based on Multimode Waveguide Grating
Authors: Luo Yannong , Ge Renyou , Luo Haozhi , Wu Meiyan , Zhou Lidan , Aryal Makunda , Li Wenwei , Yuan Jianhui , Xu Jian , Lan Quanxue , Li Yongqing , Cai Xinlun
Published: September 2021

We demonstrate a polarization splitter rotator (PSR) based on multimode waveguide grating (MWG) on a silicon-on-insulator (SOI) platform. Bloch mode hybridization in mini-stopband is exploited to achieve high polarization conversion efficiency. The fabricated device yields a high extinction ratio of > 53 dB and > 31 dB, low crosstalk of < −26.4 dB and < −40 dB for the injected TE0 and TM0 mode, with average insertion loss of 1.2 dB and 1.5 dB in the wavelength regime 1552 nm–1562 nm. Such a device shows great design flexibility and an easy fabrication process, serving as a good candidate in integrated polarization diversity circuits, especially for applications requiring spectra manipulation. Additionally, the polarization conversion approach provides opportunities to develop novel polarization management devices.
Designing Inclusive HPV Cancer Vaccines and Increasing Uptake among Native Americans—A Cultural Perspective Review
Authors: Bordeaux Skyler J. , Baca Anthony W. , Begay Rene L. , Gachupin Francine C. , Caporaso J. Gregory , Herbst-Kralovetz Melissa M. , Lee Naomi R.
Published: September 2021

Despite a global and nationwide decrease, Native Americans continue to experience high rates of cancer morbidity and mortality. Vaccination is one approach to decrease cancer incidence such as the case of cervical cancer. However, the availability of vaccines does not guarantee uptake, as evident in the Coronavirus 2019 pandemic. Therefore, as we consider current and future cancer vaccines, there are certain considerations to be mindful of to increase uptake among Native Americans such as the incidence of disease, social determinants of health, vaccine hesitancy, and historical exclusion in clinical trials. This paper primarily focuses on human papillomavirus (HPV) and potential vaccines for Native Americans. However, we also aim to inform researchers on factors that influence Native American choices surrounding vaccination and interventions including cancer therapies. We begin by providing an overview of the historical distrust and trauma Native Americans experience, both past and present. In addition, we offer guidance and considerations when engaging with sovereign Tribal Nations in vaccine development and clinical trials in order to increase trust and encourage vaccine uptake.
Clinical Outcomes from Dose-Reduced Radiotherapy to the Prostate in Elderly Patients with Localized Prostate Cancer
Authors: Samson Nina , Khanolkar Rutvij A. , Quirk Sarah , Quon Harvey , Roumeliotis Michael , Balogh Alex , Sia Michael , Thind Kundan , Husain Siraj , Martell Kevin
Published: September 2021

Radical treatment of localized prostate cancer in elderly patients may lead to unacceptable treatment-associated toxicities that adversely impact quality of life without improving survival outcomes. This study reports on a cohort of 54 elderly (>70 years) patients that received 4000–5000 cGy of palliative external beam radiotherapy (EBRT) as an alternative to androgen deprivation therapy (ADT). The primary outcome of interest was the period of ADT-free survival, and secondary outcomes included overall survival (OS) and metastases-free survival (MFS). Kaplan–Meier regression was used to estimate survival outcomes. Thirty-six (67%) patients achieved a break in ADT post-radiotherapy, with a median time to ADT reinitiation of 20 months. Common Terminology Criteria for Adverse Events (CTCAE) were limited to low-grade gastrointestinal (GI) or genitourinary (GU) toxicities, with no skin toxicities observed. Grade 1 GI toxicity was observed in 9 (17%) patients, and grades 1 and 2 GU toxicities were observed in 13 (24%) and 3 (6%) patients, respectively, with no higher-grade toxicities reported. Five-year MFS and OS were 56% and 78%, respectively. In summary, the treatment regimen was well-tolerated and achieved durable ADT-free survival in most patients. Dose-reduced EBRT appears to be a viable alternative to ADT in elderly patients with localized prostate cancer.
Shattercane (Sorghum bicolor (L.) Moench Subsp. Drummondii) and Weedy Sunflower (Helianthus annuus L.)—Crop Wild Relatives (CWRs) as Weeds in Agriculture
Authors: Kanatas Panagiotis , Gazoulis Ioannis , Zannopoulos Stavros , Tataridas Alexandros , Tsekoura Anastasia , Antonopoulos Nikolaos , Travlos Ilias
Published: September 2021

Shattercane (Sorghum bicolor (L.) Moench subsp. drummondii) and weedy sunflower (Helianthus annuus L.) are two examples of crop wild relatives (CWRs) that have become troublesome weeds in agriculture. Shattercane is a race belonging to a different subspecies than domesticated sorghum (Sorghum bicolor (L.) Moench subsp. bicolor). Weedy sunflower populations are natural hybrids between wild and domesticated sunflower (Helianthus annuus L.). Both species have key weedy characteristics, such as early seed shattering and seed dormancy, which play an important role in their success as agricultural weeds. They are widely reported as important agricultural weeds in the United States and have invaded various agricultural areas in Europe. Shattercane is very competitive to sorghum, maize (Zea mays L.), and soybean (Glycine max (L.) Merr.). Weedy sunflower causes severe yield losses in sunflower, maize, soybean, pulse crops, and industrial crops. Herbicide resistance was confirmed in populations of both species. The simultaneous presence of crops and their wild relatives in the field leads to crop–wild gene flow. Hybrids are fertile and competitive. Hybridization between herbicide-tolerant crops and wild populations creates herbicide-resistant hybrid populations. Crop rotation, false seedbed, cover crops, and competitive crop genotypes can suppress shattercane and weedy sunflower. Preventative measures are essential to avoid their spread on new agricultural lands. The development of effective weed management strategies is also essential to prevent hybridization between sorghum, sunflower, and their wild relatives and to mitigate its consequences.
Habitat Suitability Modeling to Inform Seascape Connectivity Conservation and Management
Authors: Stuart Courtney E. , Wedding Lisa M. , Pittman Simon J. , Green Stephanie J.
Published: September 2021

Coastal habitats have experienced significant degradation and fragmentation in recent decades under the strain of interacting ecosystem stressors. To maintain biodiversity and ecosystem functioning, coastal managers and restoration practitioners face the urgent tasks of identifying priority areas for protection and developing innovative, scalable approaches to habitat restoration. Facilitating these efforts are models of seascape connectivity, which represent ecological linkages across heterogeneous marine environments by predicting species-specific dispersal between suitable habitat patches. However, defining the suitable habitat patches and migratory pathways required to construct ecologically realistic connectivity models remains challenging. Focusing on two reef-associated fish species of the Florida Keys, United States of America (USA), we compared two methods for constructing species- and life stage-specific spatial models of habitat suitability—penalized logistic regression and maximum entropy (MaxEnt). The goal of the model comparison was to identify the modeling algorithm that produced the most realistic and detailed products for use in subsequent connectivity assessments. Regardless of species, MaxEnt’s ability to distinguish between suitable and unsuitable locations exceeded that of the penalized regressions. Furthermore, MaxEnt’s habitat suitability predictions more closely aligned with the known ecology of the study species, revealing the environmental conditions and spatial patterns that best support each species across the seascape, with implications for predicting connectivity pathways and the distribution of key ecological processes. Our research demonstrates MaxEnt’s promise as a scalable, species-specific, and spatially explicit tool for informing models of seascape connectivity and guiding coastal conservation efforts.
Exploring Plant Functional Diversity and Redundancy of Mediterranean High-Mountain Habitats in the Apennines
Authors: Bricca Alessandro , Carranza Maria Laura , Varricchione Marco , Cutini Maurizio , Stanisci Angela
Published: September 2021

We analyzed plant functional diversity (FD) and redundancy (FR) in Mediterranean high-mountain communities to explore plant functional patterns and assembly rules. We focused on three above-ground plant traits: plant height (H), a good surrogate of competition for light strategies, and specific leaf area (SLA) and leaf dry matter content (LDMC), useful indicators of resource exploitation functional schemes. We used the georeferenced vegetation plots and field-measured plant functional traits of four widely spread vegetation types growing on screes, steep slopes, snowbeds and ridges, respectively. We calculated Rao’s FD and FR followed by analysis of standardized effect size, and compared FD and FR community values using ANOVA and the Tukey post hoc test. Assemblage rules varied across plant communities and traits. The High FRH registered on snowbeds and ridges is probably linked to climatic filtering processes, while the high FDH and low FDSLA and FDLDMC on steep slopes could be related with underlying competition mechanisms. The absence of FD patterns in scree vegetation pinpoint random assembly processes which are typical of highly unstable or disturbed ecosystems. Improved knowledge about the deterministic/stochastic processes shaping species coexistence on high mountain ecosystems should help researchers to understand and predict vegetation vulnerability to environmental changes.
Weak Geographical Structure of Juniperus sabina (Cupressaceae) Morphology despite Its Discontinuous Range and Genetic Differentiation
Authors: Mazur Małgorzata , Boratyński Adam , Boratyńska Krystyna , Marcysiak Katarzyna
Published: September 2021

In Europe, Juniperus sabina L. is a mountainous, rare species that creates small, scattered populations, suggesting their refugial nature. Recently, a new variety of this juniper, J. sabina var. balkanensis R. P. Adams et A. N. Tashev was described based on genetic studies. We expected morphological differentiation among isolated parts of the species range and between varieties, as was the case with other Mediterranean junipers. Cones, seeds and fragments of shoots from a total of 506 individuals were collected from 24 populations in Europe and for comparisons from three populations from Tian Shan. Almost all of the 16 analysed features significantly differentiated among populations and geographical regions as well as between the varieties, although most groups differed from others only in terms of a single feature. The thickness of cones, the width of shoots and the length of seeds were the most important features for differentiation. The geographical structure of the variation of J. sabina was weak, and comparative populations from Tian Shan were clustered with European populations, similar to the findings of a previous study on essential oils. We found slightly different patterns of variation of the two varieties of the species. The little intra-species differentiation could be the result of the long period of contact between nowadays distinct populations and their relatively late separation in the early Holocene.
Preoperative CT or PET/CT to Assess Pelvic and Para-Aortic Lymph Node Status in Epithelial Ovarian Cancer? A Systematic Review and Meta-Analysis
Authors: Mimoun Camille , Rouzier Roman , Benifla Jean Louis , Fauconnier Arnaud , Huchon Cyrille
Published: September 2021

Background: In advanced epithelial ovarian cancer (EOC), the LION trial restricted lymphadenectomy indication to patients with suspect lymph nodes before and during surgery. Preoperative imaging is used to assess lymph node status, and particularly CT and PET/CT. The aim of this systematic review and meta-analysis was to evaluate the diagnostic accuracy of preoperative CT and PET/CT to detect lymph node metastasis (LNM) in patients with EOC; Methods: Databases were searched from January 1990 to May 2019 for studies that evaluated the diagnostic accuracy of preoperative CT and PET/CT to detect LNM in patients with EOC with histology as the gold standard. Pooled diagnostic accuracy was calculated using bivariate random-effects models and hierarchical summary receiver operating curve (HSROC). This study is registered with PROSPERO number CRD42020179214; Results: A total of five studies were included in the meta-analysis: four articles concerned preoperative CT and four articles concerned preoperative PET/CT, involving 106 and 138 patients, respectively. For preoperative CT, pooled sensitivity was 0.47 95% CI [0.20–0.76], pooled specificity was 0.99 95% CI [0.75–1.00] and area under the curve (AUC) of the HSROC was 0.91 95% CI [0.88–0.93]. For preoperative PET/CT, pooled sensitivity was 0.81 95% CI [0.61–0.92], pooled specificity was 0.96 95% CI [0.91–0.99] and AUC of the HSROC was 0.97 95% CI [0.95–0.98]; Conclusions: PET/CT has a very high diagnostic accuracy, especially for specificity, to detect LNM in EOC and should be realized systematically, additionally to CT recommended to evaluate peritoneal spread, in the preoperative staging of patients with an advanced disease.
Evaluation of the Advanta Dx SARS-CoV-2 RT-PCR Assay, a High-Throughput Extraction-Free Diagnostic Test for the Detection of SARS-CoV-2 in Saliva: A Diagnostic Accuracy Study
Authors: Balaska Sofia , Pilalas Dimitrios , Takardaki Anna , Koutra Paraskevoula , Parasidou Eleftheria , Gkeka Ioanna , Tychala Areti , Meletis Georgios , Fyntanidou Barbara , Metallidis Simeon , Protonotariou Efthymia , Skoura Lemonia
Published: September 2021

Nasopharyngeal swab specimen (NPS) molecular testing is considered the gold standard for SARS-CoV-2 detection. However, saliva is an attractive, noninvasive specimen alternative. The aim of the study was to evaluate the diagnostic accuracy of Advanta Dx SARS-CoV-2 RT-PCR saliva-based assay against paired NPS tested with either NeumoDxTM SARS-CoV-2 assay or Abbott Real Time SARS-CoV-2 assay as the reference method. We prospectively evaluated the method in two settings: a diagnostic outpatient and a healthcare worker screening convenience sample, collected in November–December 2020. SARS-CoV-2 was detected in 27.7% (61/220) of diagnostic samples and in 5% (10/200) of screening samples. Overall, saliva test in diagnostic samples had a sensitivity of 88.5% (77.8–95.3%) and specificity of 98.1% (94.6–99.6%); in screening samples, the sensitivity was 90% (55.5–99.7%) and specificity 100% (98.1–100%). Our data suggests that the Fluidigm Advanta Dx RT-PCR saliva-based assay may be a reliable diagnostic tool for COVID-19 diagnosis in symptomatic individuals and screening asymptomatic healthcare workers.
The Study of Usefulness of a Set of Fractal Parameters to Build Classes of Disease Units Based on Images of Pigmented Skin Lesions
Authors: Styła Monika , Giżewski Tomasz
Published: September 2021

Dermatoscopic images are also increasingly used to train artificial neural networks for the future to provide fully automatic diagnostic systems capable of determining the type of pigmented skin lesion. Therefore, fractal analysis was used in this study to measure the irregularity of pigmented skin lesion surfaces. This paper presents selected results from individual stages of preliminary processing of the dermatoscopic image on pigmented skin lesion, in which fractal analysis was used and referred to the effectiveness of classification by fuzzy or statistical methods. Classification of the first unsupervised stage was performed using the method of analysis of scatter graphs and the fuzzy method using the Kohonen network. The results of the Kohonen network learning process with an input vector consisting of eight elements prove that neuronal activation requires a larger learning set with greater differentiation. For the same training conditions, the final results are at a higher level and can be classified as weaker. Statistics of factor analysis were proposed, allowing for the reduction in variables, and the directions of further studies were indicated.
Energy and Entropy Production of Nanofluid within an Annulus Partly Saturated by a Porous Region
Authors: Raizah Zehba A. S. , Alsabery Ammar I. , Aly Abdelraheem M. , Hashim Ishak
Published: September 2021

The flow and heat transfer fields from a nanofluid within a horizontal annulus partly saturated with a porous region are examined by the Galerkin weighted residual finite element technique scheme. The inner and the outer circular boundaries have hot and cold temperatures, respectively. Impacts of the wide ranges of the Darcy number, porosity, dimensionless length of the porous layer, and nanoparticle volume fractions on the streamlines, isotherms, and isentropic distributions are investigated. The primary outcomes revealed that the stream function value is powered by increasing the Darcy parameter and porosity and reduced by growing the porous region’s area. The Bejan number and the average temperature are reduced by the increase in Da, porosity ε, and nanoparticles volume fractions ϕ. The heat transfer through the nanofluid-porous layer was determined to be the best toward high rates of Darcy number, porosity, and volume fraction of nanofluid. Further, the local velocity and local temperature in the interface surface between nanofluid-porous layers obtain high values at the smallest area from the porous region (D=0.4), and in contrast, the local heat transfer takes the lower value.
Analysis on International Competitiveness of Service Trade in the Guangdong–Hong Kong–Macao Greater Bay Area Based on Using the Entropy and Gray Correlation Methods
Authors: Xu Xianhang , Arshad Mohd Anuar , Mahmood Arshad
Published: September 2021

Based on the analysis and measurement of the overall situation, import and export structure and international competitiveness of the various sectors of service trade in the Guangdong–Hong Kong–Macao Greater Bay Area, with the help of MATLAB and Gray System Modeling software, the synergy degree model was established to quantitatively analyze the synergy level of service trade in the Greater Bay Area with the help of grey correlation analysis method and entropy weight method. The results show that the overall development trend of service trade in the Guangdong–Hong Kong–Macao Greater Bay Area is good. The service trade industries in different regions are highly complementary and have a high degree of correlation. The potential for the coordinated development of internal service trade is excellent, and the overall situation of service trade in the Greater Bay Area is in a stage of transition from a moderate level of synergy to a high level of synergy. The Greater Bay Area can achieve industrial synergy by accelerating industrial integration and green transformation, establishing a coordinated development mechanism, sharing market platform, strengthening personnel security, and further enhancing the international competitiveness of service trade. The established model better reflects the current coordination of service trade in the Guangdong–Hong Kong–Macao Greater Bay Area and has good applicability. In the future, more economic, technological, geographic, and policy data and information can be comprehensively used to study the spatial pattern, evolution rules, and mechanisms of coordinated development in the broader area.
Bridging the Research Gap—A Framework for Assessing Entrepreneurial Competencies Based on Self-Esteem and Self-Efficacy
Authors: Seikkula-Leino Jaana , Salomaa Maria
Published: September 2021

This research contributes to the growing discussion on entrepreneurial competencies from a multidisciplinary point of view, integrating elements of entrepreneurship research, education sciences, and psychology. Despite many efforts to develop and utilize different entrepreneurial constructs in entrepreneurship education, there is still a lack of theoretical framework for systematic development and measurement validation related to entrepreneurial competencies. This paper aims to widen the theoretical and conceptual discussion on entrepreneurial competencies by stressing the roles of self-esteem and self-efficacy. The study aims to contribute to the academic discussion (1) by addressing this research gap through a literature-based analysis on how entrepreneurial competencies, self-efficacy and self-esteem relate to each other; and (2) by presenting a conceptual framework (ENTself) for further development of entrepreneurship education. The results of the study reflect how self-esteem and self-efficacy are connected, and how they can be aligned with entrepreneurial competencies. We argue that a systematic, theory-based approach to further research on entrepreneurial competencies, based on the proposed framework, is needed for a broader understanding and facilitation of entrepreneurship education. Also, the development of assessment tools adapted from ENTself is suggested for conducting future research of the framework and its validation.
An Insight into Teachers’ Classroom Practices: The Case of Secondary Education Science Teachers
Authors: Sofianidis Angelos , Kallery Maria
Published: September 2021

Teachers’ knowledge rooted in classroom practices guides their actions when dealing with a specific subject matter. To assess the quality of these practices, a close examination of the “classroom reality” is needed. The present study, which was carried out in Greece, investigates secondary science teachers’ practices. To record these practices, we used special classroom observation tools as well as questionnaires to record students’ views of their teachers’ practices. The observation tools and the student questionnaire focus on specifically formed criteria deriving from aspects of Pedagogical Content Knowledge (PCK). In total, 32 secondary science teachers and 1154 students participated in our study. The results indicated that the strong points of teachers’ teaching practices concern their subject matter knowledge, the use of representations, their questioning, their communication of the instructional objectives to the students, and knowledge of students’ difficulties. The weak points are related to the use of a variety of teaching approaches, the investigation of the students’ alternative conceptions, the experimental and ICT-based teaching, and the implementation of inquiry-based activities. The methodology employed in our study was fruitful in providing a holistic view of science teachers’ practices and can be used for investigating classroom practices of teachers of other subjects as well.
A New Analytical Design Methodology for a Three-Section Wideband Wilkinson Power Divider
Authors: Omi Asif I. , Zafar Zeba N. , Al-Shakhori Hussain , Savage Aubrey N. , Islam Rakibul , Maktoomi Mohammad A. , Zakzewski Christine , Sekhar Praveen
Published: September 2021

In this paper, a new analytical design technique for a three-section wideband Wilkinson power divider is presented. The proposed design technique utilizes the dual-frequency behavior of commensurate transmission lines for the even-mode analysis and contributes a set of completely new and rigorous design equations for the odd-mode analysis. Measurement of a fabricated prototype utilizing the proposed technique shows an excellent return-loss (>16 dB), insertion loss (<3.35 dB), and excellent isolation (>22.7 dB) over 104% fractional bandwidth extending beyond the minimum requirements.
Design of an Einzel Lens with Square Cross-Section
Authors: Krysztof Michał
Published: September 2021

In this paper, the results of modeling and simulation of a microcolumn are presented. The microcolumn is part of a developed miniature MEMS electron microscope equipped with a miniature MEMS high-vacuum micropump. Such an arrangement makes this device the first stand-alone miniature electron-optical device to operate without an external high-vacuum chamber. Before such a device can be fabricated, research on particular elements must be carried out to determine the working principles of the device. The results of the calculations described in this article help us to understand the work of a microcolumn with square holes in the electrodes. The formation of an electron beam spot at the anode is discussed. Further calculations and results show the dependence of the Einzel lens size on the electron beam spot diameter, electron beam current, and microcolumn focusing voltage. The results are used to define the optimal design of the developed MEMS electron microscope.
Improved Heart Disease Prediction Using Particle Swarm Optimization Based Stacked Sparse Autoencoder
Authors: Mienye Ibomoiye Domor , Sun Yanxia
Published: September 2021

Heart disease is the leading cause of death globally. The most common type of heart disease is coronary heart disease, which occurs when there is a build-up of plaque inside the arteries that supply blood to the heart, making blood circulation difficult. The prediction of heart disease is a challenge in clinical machine learning. Early detection of people at risk of the disease is vital in preventing its progression. This paper proposes a deep learning approach to achieve improved prediction of heart disease. An enhanced stacked sparse autoencoder network (SSAE) is developed to achieve efficient feature learning. The network consists of multiple sparse autoencoders and a softmax classifier. Additionally, in deep learning models, the algorithm’s parameters need to be optimized appropriately to obtain efficient performance. Hence, we propose a particle swarm optimization (PSO) based technique to tune the parameters of the stacked sparse autoencoder. The optimization by the PSO improves the feature learning and classification performance of the SSAE. Meanwhile, the multilayer architecture of autoencoders usually leads to internal covariate shift, a problem that affects the generalization ability of the network; hence, batch normalization is introduced to prevent this problem. The experimental results show that the proposed method effectively predicts heart disease by obtaining a classification accuracy of 0.973 and 0.961 on the Framingham and Cleveland heart disease datasets, respectively, thereby outperforming other machine learning methods and similar studies.
Lane Image Detection Based on Convolution Neural Network Multi-Task Learning
Authors: Li Junfeng , Zhang Dehai , Ma Yu , Liu Qing
Published: September 2021

Based on deep neural network multi-task learning technology, lane image detection is studied to improve the application level of driverless technology, improve assisted driving technology and reduce traffic accidents. The lane line database published by Caltech and Tucson company is used to extract the ROI (Region of Interest), scale, and inverse perspective transformation as well as to preprocess the image, so as to enrich the data set and improve the efficiency of the algorithm. In this study, ZFNet is used to replace the basic networks of VPGNet, and their structures are changed to improve the detection efficiency. Multi-label classification, grid box regression and object mask are used as three task modules to build a multi-task learning network named ZF-VPGNet. Considering that neural networks will be combined with embedded systems in the future, the network will be compressed to CZF-VPGNet without excessively affecting the accuracy. Experimental results show that the vision system of driverless technology in this study achieved good test results. In the case of fuzzy lane line and missing lane line mark, the improved algorithm can still detect and obtain the correct results, and achieves high accuracy and robustness. CZF-VPGNet can achieve high real-time performance (26FPS), and a single forward pass takes about 36 ms or less.
An Analysis of 3D Steganography Techniques
Authors: Tanwar Rohit , Pilania Urmila , Zamani Mazdak , Manaf Azizah Abdul
Published: September 2021

Steganography has become a preferred technique these days to successfully hide secret messages. Various research has been done in the past to justify and analyze suitable types of cover file, such as images, audio, videos, etc. Advancement in the image-processing domain has opened various possibilities of using three-dimensional (3D) images as cover files. In this paper, a systematic study of the research work done on 3D steganography in the last fifteen years has been carried out. The study is divided into different sections based on the types of algorithms used, additional security features, evaluation parameters, etc. Moreover, certain steganalysis techniques that are applicable for 3D steganography are also discussed.
FMEA and Risks Assessment for Thermochemical Energy Storage Systems Based on Carbonates
Authors: Carro Andrés , Chacartegui Ricardo , Tejada Carlos , Gravanis Georgios , Eusha Muhammad , Spyridon Voutetakis , Simira Papadopoulou , Ortiz Carlos
Published: September 2021

Thermochemical energy storage systems from carbonates, mainly those based on calcium carbonate, have been gaining momentum in the last few years. However, despite the considerable interest in the process, the Technology Readiness Level (TRL) is still low. Therefore, facing the progressive development of the technology at different scales is essential to carry out a comprehensive risk assessment and a Failure Mode Effect and Analysis (FMEA) process to guarantee the safety and operation of the technology systems. In this study, the methodology was applied to a first-of-its-kind prototype, and it is a valuable tool for assessing safe design and operation and potential scaling up. The present work describes the methodology for carrying out these analyses to construct a kW-scale prototype of an energy storage system based on calcium carbonate. The main potential risks occur during the testing and operation stages (>50% of identified risks), being derived mainly from potential overheating in the reactors, failures in the control of the solar shape at the receiver, and potential failures of the control system. Through the assessment of Risk Priority Numbers (RPNs), it was identified that the issues requiring more attention are related to hot fluid path to avoid loss of heat transfer and potential damages (personal and on the facilities), mainly due to their probability to occur (>8 on a scale of 10). The results derived from the FMEA analysis show the need for specific control measures in reactors, especially in the calciner, with high operation temperatures (1000 °C) and potential effects of overheating and corrosion.
Supply Chain Management for Bioenergy and Bioresources: Bridging the Gap between Theory and Practice
Authors: Achillas Charisios , Bochtis Dionysis
Published: September 2021

Over the past few decades, energy demand around the globe has exponentially increased [...]
DC-Link Capacitor Voltage Balancing Control of a Five-Level Regenerative AC Electronic Load Using One-Cycle Control
Authors: Jeong In Wha
Published: September 2021

High voltage electric power equipment requires rigorous regulation testing to specific standards which ensure proper and safe operation in the grid. Manufacturers conduct these tests in order to prove standard compliance and product liability. Variable linear or nonlinear loads are necessary for testing medium voltage (MV) high power AC power converters. Generally, those AC power converters or power supplies require performance validation, burn-in and/or lifetime testing under different load conditions, defined by the end-user or standards for the given applications. For flexible and efficient MV verification testing, this paper presents a five-level multilevel converter-based MV regenerative AC electronic load with one-cycle control (OCC), which is based on five-level diode-clamped multilevel converters with back-to-back structure and can emulate any impedance load. In this paper, especially the dc-link capacitor voltage balance of the proposed multilevel MV regenerative AC load is deeply analyzed. Simulation and experimental results are presented to verify the dc-link voltage balance performance of the proposed multilevel MV regenerative AC electronic load.
Comparative Study of an EKF-Based Parameter Estimation and a Nonlinear Optimization-Based Estimation on PMSM System Identification
Authors: Sel Artun , Sel Bilgehan , Coskun Umit , Kasnakoglu Cosku
Published: September 2021

In this study, two different parameter estimation algorithms are studied and compared. Iterated EKF and a nonlinear optimization algorithm based on on-line search methods are implemented to estimate parameters of a given permanent magnet synchronous motor whose dynamics are assumed to be known and nonlinear. In addition to parameters, initial conditions of the dynamical system are also considered to be unknown, and that comprises one of the differences of those two algorithms. The implementation of those algorithms for the problem and adaptations of the methods are detailed for some other variations of the problem that are reported in the literature. As for the computational aspect of the study, a convexity study is conducted to obtain the spherical neighborhood of the unknown terms around their correct values in the space. To obtain such a range is important to determine convexity properties of the optimization problem given in the estimation problem. In this study, an EKF-based parameter estimation algorithm and an optimization-based method are designed for a given nonlinear dynamical system. The design steps are detailed, and the efficacies and shortcomings of both algorithms are discussed regarding the numerical simulations.
Are You a Typical Energy Consumer? Socioeconomic Characteristics of Behavioural Segmentation Representatives of 8 European Countries
Authors: Słupik Sylwia , Kos-Łabędowicz Joanna , Trzęsiok Joanna
Published: September 2021

Scarcity of resources and their waste, as well as deteriorating quality of life and the environment, are pressing problems of modern civilisations. Rational and efficient energy consumption is one of the possibilities for preventing harmful practices and the degradation of ecosystems. Understanding the consumer’s way of thinking and acting by identifying his needs and preferences are essential for effective efforts for smart, sustainable, and inclusive economic growth. Therefore, the aim of this article was a comprehensive socioeconomic analysis of particular behavioural types of energy consumers, as a continuation of the authors’ previous research. The paper uses statistical methods (chi-square test and correspondence analysis) dedicated to non-metric variables for an effective analysis of the data obtained from the questionnaires. The identification of socioeconomic factors was carried out on a representative sample of n = 4506 respondents from eight European countries (the Czech Republic, France, Greece, Spain, Germany, Poland, Romania, and the United Kingdom). This allowed for distinguishing a typical representative of five consumer segments (EI; AE; DS; O; I), developed on the basis of motivation to save energy. The authors succeeded in combining behavioural segmentation with the socioeconomic characteristics of the created classes. The results indicated that 10 out of 12 examined factors were significantly correlated with the behavioural type. These are (in order of significance): attitude towards saving energy; age; employment status; home country; the ownership status of the premises; the number of people in a household; average monthly income per person in a household; education; gender and place of residence.
Economic Analysis and Generic Algorithm for Optimizing the Investments Decision-Making Process in Oil Field Development
Authors: Popescu Catalin , Gheorghiu Sorin Alexandru
Published: September 2021

Due to the substantial amounts of money involved and the complex interactions of a number of different factors, managers of oil and gas companies are faced with significant challenges when making investment decisions that will increase business efficiency and achieve competitive advantages, especially through cost control. Due to the various uncertainties of the current period, optimal investment strategies are difficult to determine. Thus, through an economic analysis that includes data analysis, quantitative risk analysis scenarios, modelling and simulations, a work framework, in the form of a generic algorithm, is proposed with the aim of generating a complex procedure for optimizing investment decisions in oil field development. A complex set of elements is considered in the analysis: costs (operational expenditures (OPEX) and capital expenditures (CAPEX), daily drilling rig costs), prices (oil, gas, separation and water injection preparation), production profiles, different types of taxes and discount factors. Above all, oil price volatility plays an essential role and creates uncertainty in relation to profitability and the strategic investment decisions made by oil exploration and production companies.