bluuebunny/crossref_metadata_2025 huggingface dataset:
Tetramethylammonium Fluoride: Fundamental Properties and Applications in C-F Bond-Forming Reactions and as a Base
Authors: Iashin Vladimir , Wirtanen Tom , Perea-Buceta Jesus E.
Published: February 2022

Nucleophilic ionic sources of fluoride are essential reagents in the synthetic toolbox to access high added-value fluorinated building blocks unattainable by other means. In this review, we provide a concise description and rationale of the outstanding features of one of these reagents, tetramethylammonium fluoride (TMAF), as well as disclosing the different methods for its preparation, and how its physicochemical properties and solvation effects in different solvents are intimately associated with its reactivity. Furthermore, herein we also comprehensively describe its historic and recent utilization, up to December 2021, in C-F bond-forming reactions with special emphasis on nucleophilic aromatic substitution fluorinations with a potential sustainable application in industrial settings, as well as its use as a base capable of rendering unprecedented transformations.
State of the Art on the Microbial Production of Industrially Relevant Organic Acids
Authors: Di Lorenzo Raffaella Desirè , Serra Immacolata , Porro Danilo , Branduardi Paola
Published: February 2022

The industrial relevance of organic acids is high; because of their chemical properties, they can be used as building blocks as well as single-molecule agents with a huge annual market. Organic acid chemical platforms can derive from fossil sources by petrochemical refining processes, but most of them also represent natural metabolites produced by many cells. They are the products, by-products or co-products of many primary metabolic processes of microbial cells. Thanks to the potential of microbial cell factories and to the development of industrial biotechnology, from the last decades of the previous century, the microbial-based production of these molecules has started to approach the market. This was possible because of a joint effort of microbial biotechnologists and biochemical and process engineers that boosted natural production up to the titer, yield and productivity needed to be industrially competitive. More recently, the possibility to utilize renewable residual biomasses as feedstock not only for biofuels, but also for organic acids production is further augmenting the sustainability of their production, in a logic of circular bioeconomy. In this review, we briefly present the latest updates regarding the production of some industrially relevant organic acids (citric fumaric, itaconic, lactic and succinic acid), discussing the challenges and possible future developments of successful production.
A Review of Parent-Implemented Early Start Denver Model for Children with Autism Spectrum Disorder
Authors: Jhuo Rong-An , Chu Szu-Yin
Published: February 2022

The purpose of this review is to provide an overview of findings from selected research published between 2012 and 2022 in English-language peer-reviewed journals to evaluate the effectiveness of the parent-implemented Early Start Denver Model (P-ESDM). Thirteen studies used quantitative methods to examine the relationship between variables. We considered four categories of variables in the analysis: child characteristics, intervention intensity and duration, child outcome measures, and parent-related outcome measures and parental fidelity. The findings revealed positive child–parent-related outcomes. In addition, the quality of implementation, relating to parent fidelity, should be considered when evaluating the efficacy of the intervention. However, only half the studies revealed that the standard benchmark for acceptable fidelity was being achieved. Implications for future research and practice are discussed.
Tracheal Tube Misplacement after Emergency Intubation in Pediatric Trauma Patients: A Retrospective, Exploratory Study
Authors: Rost Franziska , Donaubauer Bernd , Kirsten Holger , Schwarz Thomas , Zimmermann Peter , Siekmeyer Manuela , Gräfe Daniel , Ebel Sebastian , Kleber Christian , Lacher Martin , Struck Manuel Florian
Published: February 2022

Inadvertent tracheal tube misplacement and particularly endobronchial intubation are well-known complications of emergency endotracheal intubation (ETI) in pediatric trauma patients, which require repositioning of the tube to avoid impairment of gas exchange. The main aim of study was to identify the frequency of tube misplacement and associated factors of pediatric trauma patients who received ETI either by prehospital physician-staffed emergency medical service (EMS), or at emergency department (ED) admission to a single level-1 trauma center. Sixty-five patients (median age 14 years and median injury severity score 29) were included. Of these, 30 underwent helicopter EMS ETI, 29 ground EMS ETI, and 6 ED ETI. Seventeen cases (26%) of tracheal tube misplacement were recognized. After multivariable analysis, tracheal tube misplacement was independently negatively associated with body weight (OR 0.86; 95% CI, 0.76–0.99; p = 0.032) and helicopter EMS ETI (OR 0.20; 95% CI, 0.04–0.97; p = 0.036). Two of nineteen patients received tube thoracostomy due to endobronchial intubation. Mortality and length of stay were comparable in patients with misplaced tubes and correctly placed tubes. The results suggest that particularly small children require attention to avoid tracheal tube misplacement, which emphasizes the need for special training. Helicopter EMS physicians’ expertise might be beneficial in prehospital pediatric trauma patients requiring advanced airway management.
Differential Diagnosis of Histiocytic Necrotizing Lymphadenitis and Malignant Lymphoma with Simple Clinical Findings
Authors: Omachi Taichi , Atsumi Naho , Yamazoe Takashi , Yamanouchi Sohsaku , Matsuno Ryosuke , Kitawaki Tomoki , Kaneko Kazunari
Published: February 2022

It is desirable that noninvasive differential diagnosis takes place without lymph node biopsy for histiocytic necrotizing lymphadenitis (HNL) or malignant lymphoma (ML). In this study, we propose a novel scoring model for the differential diagnosis of these diseases using clinical information and clinical findings. We retrospectively analyzed the data from 15 HNL and 13 ML pediatric patients. First, a univariate analysis identified 14 clinical factors with significant differences. Second, a subsequent analysis using receiver operating characteristic (ROC) curve analysis identified three factors among them with area under the ROC curve values of >0.95: body temperature (°C), maximum lymph node size (cm), and serum β2-microglobulin level (mg/L). Finally, the cut-off values of each of these three factors were determined and examined for the 28 cases. All 15 HNL cases were within 2–3 of the cut-off values among the three factors, no ML case was within two or more cut-off values. Thus, the diagnostic sensitivity and specificity of this novel scoring system were both 100%, indicating that clinical scoring with body temperature, maximum lymph node size, and β2-microglobulin are useful for distinguishing between HNL and ML.
Sub-Hourly Precipitation Extremes in Mainland Portugal and Their Driving Mechanisms
Authors: Santos João A. , Belo-Pereira Margarida
Published: February 2022

Sub-hourly heavy precipitation events (SHHPs) frequently underlie major meteorological hazards, but their comprehensive analysis is still lacking in Portugal. A 71-weather-station dataset for 2000–2020 is used in this article to (1) diagnose SHHPs corresponding to a 10-min precipitation event of at least 5.0 mm, (2) characterize their spatial-temporal distribution, and (3) identify their associated synoptic-scale conditions. Two synoptic types are associated with SHHPs: remote (RemL) and regional (RegL) low-pressure systems. RegL SHHPs display two marked maxima in spring and autumn, while RemL SHHPs show a single maximum in autumn. Most RegL events occur in the afternoon/evening, while RemL events show a slight bias toward midday occurrences. In the case of RemL, the wind is stronger for 2 to 3 h before and during SHHPs, veers from 180° to 210° near the event, the pressure decreases until 20 min before the event, and the wet-bulb temperature decreases around the time of the event and remains low, thus reflecting cold-front passages. For RegL, maximum winds coincide with precipitation peaks, and the wet-bulb temperature briefly decreases in association with downdrafts. A preliminary relationship between the SHHPs and mesoscale convective systems is established by detecting sudden surface-pressure surges, which are indicative of mesohighs caused by evaporatively cooled downdrafts. A calendar of mesohigh episodes linked to SHHPs is provided herein and their signatures are illustrated for the “Pedrógão-Grande” fires. Indicators of several downbursts, cold pools, and mesohighs were identified by the AROME forecast. This first, systematized analysis paves the way to identifying dynamic precursors, enabling their integration into early warning systems and climate projections.
On the Conic Convex Approximation to Locate and Size Fixed-Step Capacitor Banks in Distribution Networks
Authors: Montoya Oscar Danilo , Gil-González Walter , Garcés Alejandro
Published: February 2022

The problem of the optimal siting and sizing of fixed-step capacitor banks is studied in this research from the standpoint of convex optimization. This problem is formulated through a mixed-integer nonlinear programming (MINLP) model, in which its binary/integer variables are related to the nodes where the capacitors will be installed. Simultaneously, the continuous variables are mainly associated with the power flow solution. The main contribution of this research is the reformulation of the exact MINLP model through a mixed-integer second-order cone programming model (MI-SOCP). This mixed-integer conic model maintains the nonlinearities of the original MINLP model; however, it can be solved efficiently with the branch & bound method combined with the interior point method adapted for conic programming models. The main advantage of the proposed MI-SOCP model is the possibility of finding the global optimum based on the convex nature of the power flow problem for each binary/integer variable combination in the branch & bound search tree. The numerical results in the IEEE 33- and IEEE 69-bus systems demonstrate the effectiveness and robustness of the proposed MI-SOCP model compared to different metaheuristic approaches. The MI-SOCP model finds the final power losses of the IEEE 33- and IEEE 69-bus systems of 138.416kW and 145.397kW, which improves the best literature results reached with the flower pollination algorithm, i.e., 139.075 kW, and 145.860kW, respectively. The simulations are carried out in MATLAB software using its convex optimizer tool known as CVX with the Gurobi solver.
Modifying HKUST-1 Crystals for Selective Ethane Adsorption Using Ionic Liquids as Synthesis Media
Authors: Deyko Gregory S. , Glukhov Lev M. , Isaeva Vera I. , Chernyshev Vladimir V. , Vergun Vadim V. , Archipov Danil A. , Kapustin Gennady I. , Tkachenko Olga P. , Nissenbaum Vera D. , Kustov Leonid M.
Published: February 2022

Novel adsorbents for methane and ethane based on HKUST-1 metal-organic framework were synthesized by microwave (MW) assisted technique using ionic liquids (ILs) as synthesis media. It was found that the MW synthesis time remarkably impacts both the product yield and the physico-chemical characteristics of the produced HKUST-1 material. The crystalline phase purity, crystallite size/dispersion and textural properties of the synthesized HKUST-1 matrices determine their performance in methane and ethane adsorption. Therefore, the HKUST-1 material produced in MW fields for 3 min only shows the highest phase purity and the largest surface area (BET) and porosity, along with a rather small crystallite size (below ~300 nm), demonstrating high methane and ethane adsorption capacity in the pressure range 1–30 atm.
Grain Knowledge Graph Representation Learning: A New Paradigm for Microstructure-Property Prediction
Authors: Shu Chao , He Junjie , Xue Guangjie , Xie Cheng
Published: February 2022

The mesoscopic structure significantly affects the properties of polycrystalline materials. Current artificial-based microstructure-performance analyses are expensive and require rich expert knowledge. Recently, some machine learning models have been used to predict the properties of polycrystalline materials. However, they cannot capture the complex interactive relationship between the grains in the microstructure, which is a crucial factor affecting the material’s macroscopic properties. Here, we propose a grain knowledge graph representation learning method. First, based on the polycrystalline structure, an advanced digital representation of the knowledge graph is constructed, embedding ingenious knowledge while completely restoring the polycrystalline structure. Then, a heterogeneous grain graph attention model (HGGAT) is proposed to realize the effective high-order feature embedding of the microstructure and to mine the relationship between the structure and the material properties. Through benchmarking with other machine learning methods on magnesium alloy datasets, HGGAT consistently demonstrates superior accuracy on different performance labels. The experiment shows the rationality and validity of the grain knowledge graph representation and the feasibility of this work to predict the material’s structural characteristics.
Influence of Non-Metallic Inclusions on Local Deformation and Damage Behavior of Modified 16MnCrS5 Steel
Authors: Qayyum Faisal , Umar Muhammad , Elagin Vladislav , Kirschner Markus , Hoffmann Frank , Guk Sergey , Prahl Ulrich
Published: February 2022

This work investigates a ferrite matrix with multiple non-metallic inclusions to evaluate their influence on the global and local deformation and damage behavior of modified 16MnCrS5 steel. For this purpose, appropriate specimens are prepared and polished. The EBSD technique is used to record local phase and orientation data, then analyze and identify the size and type of inclusions present in the material. The EBSD data are then used to run full phase crystal plasticity simulations using DAMASK-calibrated material model parameters. The qualitative and quantitative analysis of these full phase simulations provides a detailed insight into how the distribution of non-metallic inclusions within the ferrite matrix affects the local stress, strain, and damage behavior. In situ tensile tests are carried out on specially prepared miniature dog-bone-shaped notched specimens in ZEISS Gemini 450 scanning electron microscope with a Kammrath and Weiss tensile test stage. By adopting an optimized scheme, tensile tests are carried out, and local images around one large and several small MnS inclusions are taken at incremental strain values. These images are then processed using VEDDAC, a digital image correlation-based microstrain measurement tool. The damage initiation around several inclusions is recorded during the in situ tensile tests, and damage initiation, propagation, and strain localization are analyzed. The experimental results validate the simulation outcomes, providing deeper insight into the experimentally observed trends.
Performance of Silica Fume-Based Geopolymer Grouts for Heritage Masonry Consolidation
Authors: Baltazar Luis G.
Published: February 2022

Despite the increasing number of studies on geopolymer-based materials, a lack of information still prevails concerning the use of geopolymer materials for the consolidation and conservation of the built heritage. Since the introduction of the term “geopolymer” by Davidovits, several studies have pointed out geopolymers as a potential replacement for traditional binders, mainly due to their advantages associated with mechanical properties and low carbon dioxide emissions. The geopolymers (also known as alkali-activated materials or inorganic polymers) are obtained by a chemical process through which precursors rich in silica and alumina interact with an alkaline medium to result in a material with binding properties. The aim of this study is to exploit the potential of geopolymer-based grouts in the consolidation of stone masonry buildings. Grouting or grout injection is a technique used for the consolidation of heritage masonry buildings; it consists of the introduction of a binding agent to fill the internal voids and cracks. An experimental program was carried out to improve knowledge of geopolymer grouts suitable for consolidation purposes. The experimental findings revealed that the silica-fume-based geopolymer grout has a worse performance from a rheological point of view, whereas it showed promising results in terms of mechanical strength when compared to traditional hydraulic-lime-based grout.
Compositions of Gamma and Gamma Prime Phases in an As-Cast Nickel-Based Single Crystal Superalloy Turbine Blade
Authors: Park KeeHyun , Withey Paul
Published: February 2022

The core and the interdendritic regions of an as-cast nickel based single crystal turbine blade were observed by electron microscopy to understand the microstructural development during an investment casting process. The dendrite core region shows an irregular morphology of gamma prime in gamma due to a relatively short casting time, which prevented the development of gamma prime expected in a solution heat-treated microstructure. By comparison, the interdendritic region comprises three different regions composed of: several elongated gamma prime particles, relatively tiny and irregular gamma prime, and gamma prime with relatively regular morphology. The chemical analysis of these phases showed that, regardless of the analysis point in the core or the interdendritic region, almost the same compositions were acquired in the regular type of gamma and gamma prime phases. This result suggests that if the gamma prime forms in the gamma matrix, the composition of gamma prime is almost uniform regardless of the region and prevailing general chemical composition. In contrast, the composition of the elongated gamma prime in the interdendritic region was slightly different depending on the analysis point even within the same elongated particle.
EVAR Follow-Up with Ultrasound Superb Microvascular Imaging (SMI) Compared to CEUS and CT Angiography for Detection of Type II Endoleak
Authors: Curti Marco , Piacentino Filippo , Fontana Federico , Ossola Christian , Coppola Andrea , Marra Paolo , Basile Antonio , Ierardi Anna Maria , Carrafiello Gianpaolo , Carcano Giulio , Tozzi Matteo , Piffaretti Gabriele , Venturini Massimo
Published: February 2022

The aim of this study was to evaluate the usefulness of superb microvascular imaging (SMI) versus contrast-enhanced ultrasound (CEUS) and compared to computed tomography angiography (CTA) as a reference standard, for detection of type II endoleak during follow-up of endovascular abdominal aortic aneurysm repair (EVAR). Between April 2017 and September 2020, 122 patients underwent post-EVAR follow-up with CTA at 3 months and with ultrasound SMI and CEUS at 4 months from the EVAR procedure. Aneurysmal sac diameter and graft patency were evaluated; endoleaks were assessed and classified. Sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy were calculated both for SMI and CEUS and compared to CTA. Furthermore, the percentage of agreement and Cohen’s Kappa coefficient were calculated. CTA revealed 54 type II endoleaks. Ultrasound SMI and CEUS presented the same sensitivity (91.5%), specificity (100%), positive (100%), and negative (92.8%) predictive and accuracy (95.9%) value for detecting type II endoleak. The same percentage of agreement of 94.9% was found between SMI/CEUS, and CTA with a Cohen’s Kappa coefficient of 0.89. The diagnostic accuracy of SMI is comparable with CEUS in the identification of type II endoleaks after EVAR. Since SMI is less invasive, less expensive, and less time-consuming, this method may be considered to be a potential tool for monitoring patients after EVAR implantation.
Digital Pathology Implementation in Private Practice: Specific Challenges and Opportunities
Authors: Montezuma Diana , Monteiro Ana , Fraga João , Ribeiro Liliana , Gonçalves Sofia , Tavares André , Monteiro João , Macedo-Pinto Isabel
Published: February 2022

Digital pathology (DP) is being deployed in many pathology laboratories, but most reported experiences refer to public health facilities. In this paper, we report our experience in DP transition at a high-volume private laboratory, addressing the main challenges in DP implementation in a private practice setting and how to overcome these issues. We started our implementation in 2020 and we are currently scanning 100% of our histology cases. Pre-existing sample tracking infrastructure facilitated this process. We are currently using two high-capacity scanners (Aperio GT450DX) to digitize all histology slides at 40×. Aperio eSlide Manager WebViewer viewing software is bidirectionally linked with the laboratory information system. Scanning error rate, during the test phase, was 2.1% (errors detected by the scanners) and 3.5% (manual quality control). Pre-scanning phase optimizations and vendor feedback and collaboration were crucial to improve WSI quality and are ongoing processes. Regarding pathologists’ validation, we followed the Royal College of Pathologists recommendations for DP implementation (adapted to our practice). Although private sector implementation of DP is not without its challenges, it will ultimately benefit from DP safety and quality-associated features. Furthermore, DP deployment lays the foundation for artificial intelligence tools integration, which will ultimately contribute to improving patient care.
Automated Structural Analysis and Quantitative Characterization of Scar Tissue Using Machine Learning
Authors: Maknuna Luluil , Kim Hyeonsoo , Lee Yeachan , Choi Yoonjin , Kim Hyunjung , Yi Myunggi , Kang Hyun Wook
Published: February 2022

An analysis of scar tissue is necessary to understand the pathological tissue conditions during or after the wound healing process. Hematoxylin and eosin (HE) staining has conventionally been applied to understand the morphology of scar tissue. However, the scar lesions cannot be analyzed from a whole slide image. The current study aimed to develop a method for the rapid and automatic characterization of scar lesions in HE-stained scar tissues using a supervised and unsupervised learning algorithm. The supervised learning used a Mask region-based convolutional neural network (RCNN) to train a pattern from a data representation using MMDetection tools. The K-means algorithm characterized the HE-stained tissue and extracted the main features, such as the collagen density and directional variance of the collagen. The Mask RCNN model effectively predicted scar images using various backbone networks (e.g., ResNet50, ResNet101, ResNeSt50, and ResNeSt101) with high accuracy. The K-means clustering method successfully characterized the HE-stained tissue by separating the main features in terms of the collagen fiber and dermal mature components, namely, the glands, hair follicles, and nuclei. A quantitative analysis of the scar tissue in terms of the collagen density and directional variance of the collagen confirmed 50% differences between the normal and scar tissues. The proposed methods were utilized to characterize the pathological features of scar tissue for an objective histological analysis. The trained model is time-efficient when used for detection in place of a manual analysis. Machine learning-assisted analysis is expected to aid in understanding scar conditions, and to help establish an optimal treatment plan.
Augmented Reality (AR) as a Tool for Engaging Museum Experience: A Case Study on Chinese Art Pieces
Authors: Gong Zhe , Wang Ruizhi , Xia Guobin
Published: February 2022

The research explores the efficiency of augmented reality (AR) technology as a tool for the positive triggering museum experience. This article shows the design, development, and evaluation of an AR prototype for information visualization based on a famous Chinese art piece named Along the River During the Qingming Festival. In total, 58 participants were invited to evaluate the prototype. Results suggest that AR technology can trigger users’ engagement, learning, meaningful experience, and emotional connection, and hence arouse their interest and learning process. These findings may interest researchers and designers to develop a broader range of innovative AR applications to prompt a digital learning experience.
Invasion of the Giant Hogweed and the Sosnowsky’s Hogweed as a Multidisciplinary Problem with Unknown Future—A Review
Authors: Grzędzicka Emilia
Published: February 2022

Caucasian hogweeds are plants introduced to Europe from the Caucasus area. This review concerns the two most common ones—the giant hogweed Heracleum mantegazzianum and the Sosnowsky’s hogweed Heracleum sosnowskyi. The first of them was imported as garden decorations from the 19th century, mainly to Western Europe, while the second one was introduced from the mid–20th century to agricultural areas in Eastern Europe. Nowadays, these two species create one of the most problematic invasions in the world. This review aimed to synthesize research on those invaders based on 277 articles selected from the “Scopus” database. Most of the articles concerned their extensive distribution, at least on a continental scale and the rapid dispersal. The reviewed research showed that the complex physicochemical properties of hogweeds tissues and secretions significantly affected insects, aphids, ants, nematodes, fungi, soil microorganisms, plant communities, birds, and many other components of the ecosystems. This knowledge turned out to be disproportionately small to the scale of the problem. The review also showed what ecological traits of hogweeds were responsible for their wide and various role in the environment. Thus far, no effective method to eradicate Caucasian hogweeds has been found. This could be a growing mistake, given that they are probably during the rapid evolutionary changes within the range of their invasion.
How Can the Morphometric Characteristics and Failure Conditions of a Historic Gully Caused by Intense Rainfall Be Reconstructed?
Authors: Rault Claire , Thiery Yannick , Aunay Bertrand , Colas Bastien , Reboul Kahina , Dewez Thomas J. B.
Published: February 2022

In January 1980, during exceptional cyclonic rainfall, an atypical landslide, called déboulé, rapidly generated the permanent 700 m-long gully of the Ravine de l’Eglise on an inhabited plateau in Reunion Island (Indian Ocean). Retrieving the initial conditions that led to this historical process is both challenging and necessary for understanding the mechanism of gully incision and providing pointers for improving risk mitigation in relation to this phenomenon. In this study, we reconstruct the pre- and post-failure topographies using SFM (structure from motion) applied on archive aerial photographs. Based on the comparison of these digital elevation models, we estimate the volume of material eroded to be ca. 0.63 Mm3. Groundwater level increase, part of the triggering mechanism, is hindcast in the catchment of the gully using a lumped hydrological model. This model shows that in only a fortnight the groundwater level probably rose by 36 m, which could have caused a progressive increase in pore pressure and triggered formation of the gully by retrogressive landslides. We test this hypothesis by considering the pre-failure topography and the hindcast groundwater level in a deterministic model based on limit equilibrium equations to explore ground stability. The evolution of ground stability with a rise in the water table shows that the gully may have extended in a headward direction by retrogressive landslides. This is the first quantitative reconstruction of an exceptional historical event affecting the territory of Reunion Island. The methods used to investigate the Ravine de L’Eglise incision thus offer new complementary insights and challenges for understanding the mechanism and the temporality of gully formation.
Teaching Mathematics with Technology: TPACK and Effective Teaching Practices
Authors: Rakes Christopher R. , Stites Michele L. , Ronau Robert N. , Bush Sarah B. , Fisher Molly H. , Safi Farshid , Desai Siddhi , Schmidt Ashley , Andreasen Janet B. , Saderholm Jon , Amick Lisa , Mohr-Schroeder Margaret J. , Viera Julian
Published: February 2022

This paper examines how 17 secondary mathematics teacher candidates (TCs) in four university teacher preparation programs implemented technology in their classrooms to teach for conceptual understanding in online, hybrid, and face to face classes during COVID-19. Using the Professional Development: Research, Implementation, and Evaluation (PrimeD) framework, TCs, classroom mentor teachers, field experience supervisors, and university faculty formed a Networked Improvement Community (NIC) to discuss a commonly agreed upon problem of practice and a change idea to implement in the classroom. Through Plan-Do-Study-Act cycles, participants documented their improvement efforts and refinements to the change idea and then reported back to the NIC at the subsequent monthly meeting. The Technology Pedagogical Content Knowledge framework (TPACK) and the TPACK levels rubric were used to examine how teacher candidates implemented technology for Mathematics conceptual understanding. The Mathematics Classroom Observation Protocol for Practices (MCOP2) was used to further examine how effective mathematics teaching practices (e.g., student engagement) were implemented by TCs. MCOP2 results indicated that TCs increased their use of effective mathematics teaching practices. However, growth in TPACK was not significant. A relationship between TPACK and MCOP2 was not evident, indicating a potential need for explicit focus on using technology for mathematics conceptual understanding.
A Study on the Effects of Digital Learning Sheet Design Strategy on the Learning Motivation and Learning Outcomes of Museum Exhibition Visitors
Authors: Chen Tien-Li , Lee Yun-Chi , Hung Chi-Sen
Published: February 2022

This study focuses on “digital learning sheets” by exploring the effects of different design strategies of the digital learning sheet on visitors’ motivation and learning outcomes. This study chose the woodcraft themed exhibition as a case study, adopting the learning sheet design principles proposed by Hooper-Greenhill in order to design three types of digital learning sheets for this exhibition. A control group of students who did not use the sheets and three experimental groups of students who used the sheets were invited to visit the exhibition for the purpose of examining the impact of different strategies of digital learning sheet design on the “learning motivation” and “learning outcomes” of the visitors. The study results show that among the four learning motivations of Attention, Relevance, Confidence, and Satisfaction, the digital learning sheet designed with the “principle of sensory exploration of physical objects” had the highest effectiveness among the various design strategies. In terms of three aspects of learning outcomes: Cognitive, Affective, and Psychomotor, the three types of digital learning design strategies do not produce significant differences in the affective impact on children. As for Cognitive and Psychomotor, students learn best when they use digital learning sheets designed with the “design principle of sensory and exploration of physical objects”. The results of this study will provide future exhibition planners, digital learning designers, and educators with precise and practical references.
From PKU Online Lessons for Dietetics Students to the PKU Sandwiches Album
Authors: Konikowska Klaudia , Mozrzymas Renata
Published: February 2022

The purpose of the manuscript is to present to academic teachers, doctors and nutritionists how practical online classes with dietetics students can be used to develop ready-made tools at work and for the education of phenylketonuria (PKU) patients and their caregivers/parents. During online classes in 2020, as part of the subject—diet therapy of metabolic blocks, 53 students prepared PKU sandwiches at home. Each PKU sandwich has a calculated nutritional value, and phenylalanine exchanger content, but does not include low-protein bread. The selection of a particular type of PKU bread depends solely on the PKU patient, hence it was deliberately not included in the calculations. The sandwiches, made by students and assessed by academic teachers, will be published with the following title “The PKU Sandwiches Album”. The Album with more than 400 colorful pictures of PKU sandwiches, will be expected to inspire patients and help them add appeal to their diet, enriching it with new tastes, at the same time facilitating the memorizing process of ingredients, thanks to visualization and presented calculations, and motivating them to comply with strict dietary recommendation. The same nutritional calculations and ideas for sandwiches, with the use of different bread, e.g., gluten-free, may be useful in other diseases, such as celiac disease.
What’s in Your Culture? Embracing Stability and the New Digital Age in Moving Colleges of Health Professions Virtually during the COVID-19 Pandemic: An Experiential Narrative Review
Authors: Poudevigne Melanie , Armstrong Erika S. , Mickey Marisa , Nelson Michelle A. , Obi Comfort N. , Scott Andrew , Thomas Naquilla , Thompson Tamara N.
Published: February 2022

As traditional education transitioned from face-to-face interactions to virtual learning during the COVID-19 pandemic, faculty and staff in dental hygiene, nursing, and exercise science programs placed students at the center of every educational decision and promoted stability in learning with their commitments to excellence in teaching and the delivery of content using educational and communication technology. This experiential narrative review explains how faculty members and administrators addressed online education with technology specific to health professions and how universities managed to assist students with innovative services for mental health. It also provides an insight into how degree-specific academic personnel embraced technology-based hands-on activities in community health clinics and clinical laboratories, with sustainable and impactful lessons in equity, affordability, and transformative education. Finally, health administrators gather their top-10 leadership recommendations to continue moving forward during the pandemic and present a unique self-reflection on the process of caring considerations required for a successful experience for faculty members, staff, and students.
An Integrative Literature Review of University-Based Early Childhood Education and Care Centres within Early Childhood Teacher Education Settings
Authors: Pihanperä Meri , Lepistö Jaana , Ruokonen Inkeri
Published: February 2022

This research is an integrative literature review regarding the variety of university-based early childhood education and care (ECEC) centre models. This research focuses on those models that collaborate closely with early childhood (EC) teacher education programmes. The data were gathered from three different databases: ERIC (Ebscohost), Education Research Complete (Ebscohost) and ProQuest Central by using six different search terms. A total of 2766 publications were found. Based on the inclusion criteria, 40 publications were included in a data analysis. These publications consisted of descriptions of 53 different models regarding the collaboration between ECEC centres and universities. Two out of three models (n = 34) were university-based ECEC centres that collaborated closely with EC teacher education programmes by implementing various collaborations in education and research in their daily work. Outreach efforts were also implemented. This research invites EC teacher education programmes and ECEC centres for international collaboration and further research on this topic.
Analytical Methods of Voltage Stability in Renewable Dominated Power Systems: A Review
Authors: Liang Xinyu , Chai Hua , Ravishankar Jayashri
Published: February 2022

The ongoing development of renewable energy and microgrid technologies has gradually transformed the conventional energy infrastructure and upgraded it into a modernized system with more distributed generation and localized energy storage options. Compared with power grids utilizing synchronous generation, inverter-based networks cannot physically provide large amounts of inertia, which means that more advanced and extensive studies regarding stability considerations are required for such systems. Therefore, appropriate analytical methods are needed for the voltage stability analysis of renewable-dominated power systems, which incorporate a large number of inverters and distributed energy sources. This paper provides a comprehensive literature review of voltage stability analyses of power systems with high levels of renewable energy penetration. A series of generalized evaluation schemes and improvement methods relating to the voltage stability of power systems integrated with various distributed energy resources are discussed. The existing voltage stability analysis methods and corresponding simulation verification models for microgrids are also reviewed in a systematic manner. The traditional and improved voltage stability analysis methods are reviewed according to the microgrid operation mode, the types of distributed generators, and the microgrid configurations. Moreover, the voltage stability indices, which play a crucial role in voltage stability assessments, are critically evaluated in terms of the applicable conditions. The associated modeling and simulation techniques are also presented and discussed. This contribution presents guidelines for voltage stability analysis and instability mitigation methods for modern renewable-rich power systems.
Blockchain for IoT Applications: Taxonomy, Platforms, Recent Advances, Challenges and Future Research Directions
Authors: Abdelmaboud Abdelzahir , Ahmed Abdelmuttlib Ibrahim Abdalla , Abaker Mohammed , Eisa Taiseer Abdalla Elfadil , Albasheer Hashim , Ghorashi Sara Abdelwahab , Karim Faten Khalid
Published: February 2022

The Internet of Things (IoT) has become a popular computing technology paradigm. It is increasingly being utilized to facilitate human life processes through a variety of applications, including smart healthcare, smart grids, smart finance, and smart cities. Scalability, interoperability, security, and privacy, as well as trustworthiness, are all issues that IoT applications face. Blockchain solutions have recently been created to help overcome these difficulties. The purpose of this paper is to provide a survey and tutorial on the use of blockchain in IoT systems. The importance of blockchain technology in terms of features and benefits for constituents of IoT applications is discussed. We propose a blockchain taxonomy for IoT applications based on the most significant factors. In addition, we examine the most widely used blockchain platforms for IoT applications. Furthermore, we discuss how blockchain technology can be used to broaden the spectrum of IoT applications. Besides, we discuss the recent advances and solutions offered for IoT environments. Finally, we discuss the challenges and future research directions of the use of blockchain for the IoT.
A Fast Image Guide Registration Supported by Single Direction Projected CBCT
Authors: Gong Jian , He Kangjian , Xie Lisiqi , Xu Dan , Yang Tao
Published: February 2022

Image registration is an important research topic in medical image-guided therapy, which is dedicated to registering the high-dose imaging sequences with low-dose/faster means. Registering computer tomography (CT) scanning sequences with cone beam computer tomography (CBCT) scanning sequences is a typical application and has been widely used in CBCT-guided radiotherapy. The main problem is the difference in image clarity of these two image sequences. To solve this problem, for the single projection image sequence matching tasks encountered in medical practice, a novel local quality based curved section encoding strategy is proposed in this paper, which is called the high-quality curved section (HQCS). As an optimized cross-section regularly encoded along the sequence of image, this curved section could be used in order to solve the matching problem. Referencing the independent ground truth provided by medical image physicians, with an experiment combined with the four most widely used indicators used on image registration, matching performance of HQCS on CT/CBCT datasets was tested with varying clarity. Experimental results show that the proposed HQCS can register the CT/CBCT effectively and outperforms the commonly used methods. Specifically, the proposed HQCS has low time complexity and higher scalability, which indicates that the application enhanced the task of diagnosis.
A New Realization of Electronically Tunable Multiple-Input Single-Voltage Output Second-Order LP/BP Filter Using VCII
Authors: Safari Leila , Barile Gianluca , Ferri Giuseppe , Ragnoli Mattia , Stornelli Vincenzo
Published: February 2022

In this paper, a new realization of electronically tunable voltage output second-order low-pass (LP) and band-pass (BP) filter is presented. The circuit has a multiple-input single-output structure, and LP and BP outputs are provided using the same structure. One electronically variable second-generation voltage conveyor (VCII), whose impedance at the Y port can be electronically varied using a control current (Icon), two capacitors, and one resistor are used. By changing the value of Icon, the impedance value at the Y port can be electronically varied; therefore, the value of ω0 can be tuned. This feature helps to reduce the number of passive components used. Interestingly, the LP and BP outputs are provided at the low-impedance Z port of the VCII, and there is no need for an extra voltage buffer for practical use. The circuit enjoys a simple realization consisting of only 24 MOS transistors. Simulation results using PSpice and 0.18 μm CMOS parameters are provided. The value of ω0 can be varied from 1.2 MHz to 1.7 MHz, while Icon varies from 0 to 50 µA, with a power consumption variation from 244 µW to 515 µW.
An Artificial Fish Swarm Scheme Based on Heterogeneous Pheromone for Emergency Evacuation in Social Networks
Authors: Zong Xinlu , Yi Jingxi , Wang Chunzhi , Ye Zhiwei , Xiong Naixue
Published: February 2022

A two-layer artificial fish swarm evacuation model based on heterogeneous pheromones is presented in this paper. Firstly, the movements of evacuees are simulated by the behaviors of an artificial fish swarm, including preying, swarming, and following. Then, the positive feedback mechanism of heterogeneous pheromones is introduced to improve evacuation performance. Based on the interaction and communication mechanisms of biological groups of social networks in nature, the perceptual and cooperative model among individuals and between individuals and the environment is established. An optimization scheme based on fish swarms and heterogeneous pheromones is proposed. The simulation and experimental results show that the two-layer evacuation model can optimize the spatial-temporal distribution of people and can finally achieve better evacuation plans. The proposed model and algorithm can provide effective guidance for emergency safety responses and robot cooperative control in intelligent robot systems.
Cross-Day EEG-Based Emotion Recognition Using Transfer Component Analysis
Authors: He Zhongyang , Zhuang Ning , Bao Guangcheng , Zeng Ying , Yan Bin
Published: February 2022

EEG-based emotion recognition can help achieve more natural human-computer interaction, but the temporal non-stationarity of EEG signals affects the robustness of EEG-based emotion recognition models. Most existing studies use the emotional EEG data collected in the same trial to train and test models, once this kind of model is applied to the data collected at different times of the same subject, its recognition accuracy will decrease significantly. To address the problem of EEG-based cross-day emotion recognition, this paper has constructed a database of emotional EEG signals collected over six days for each subject using the Chinese Affective Video System and self-built video library stimuli materials, and the database is the largest number of days collected for a single subject so far. To study the neural patterns of emotions based on EEG signals cross-day, the brain topography has been analyzed in this paper, which show there is a stable neural pattern of emotions cross-day. Then, Transfer Component Analysis (TCA) algorithm is used to adaptively determine the optimal dimensionality of the TCA transformation and match domains of the best correlated motion features in multiple time domains by using EEG signals from different time (days). The experimental results show that the TCA-based domain adaptation strategy can effectively improve the accuracy of cross-day emotion recognition by 3.55% and 2.34%, respectively, in the classification of joy-sadness and joy-anger emotions. The emotion recognition model and brain topography in this paper, verify that the database can provide a reliable data basis for emotion recognition across different time domains. This EEG database will be open to more researchers to promote the practical application of emotion recognition.
V-Band Channel Modeling, Throughput Measurements, and Coverage Prediction for Indoor Residential Environments
Authors: De Beelde Brecht , Almarcha Andrés , Plets David , Joseph Wout
Published: February 2022

With the increased resolution and frame rates of video recordings, in combination with the current evolution towards video-on-demand streaming services and the user expecting ubiquitous wireless connectivity, it is necessary to design wireless communication systems that allow high-rate data transfer. The large bandwidths that are available in the mmWave frequency band allow such high data rates. In this paper, we provide an experimental and simulated indoor residential radio channel model at V-band frequencies and perform packet error rate and throughput measurements at 60 GHz using IEEE 802.11ad transceivers. We compare the path loss and throughput measurements to simulations using a network performance prediction tool. The path loss measurement results using an omnidirectional transmit antenna correspond well to generic indoor mmWave channel models. Double-directional path loss measurements show that generic models underestimate path loss of non-Line-of-Sight (NLOS) links. A ray-launching algorithm is designed and validated, and used for IEEE 802.11ad throughput estimation based on link budget calculations. The link budget underestimates the achieved throughput, when comparing to adaptive-rate MCS selection in a commercial transceiver, based on the measured signal-to-noise ratio. Packet error rate measurements confirm that, even for NLOS links, throughputs exceeding 1 Gbps are possible.