bluuebunny/crossref_metadata_2025 huggingface dataset:
Determinants of COVID-19 Vaccine Uptake and Hesitancy among Healthcare Workers in Tanzania: A Mixed-Methods Study
Authors: Amour Maryam A. , Mboya Innocent B. , Ndumwa Harrieth P. , Kengia James T. , Metta Emmy , Njiro Belinda J. , Nyamuryekung’e Kasusu Klint , Mhamilawa Lwidiko E. , Shayo Elizabeth H. , Ngalesoni Frida , Kapologwe Ntuli , Sunguya Bruno , Msuya Sia E. , Kalolo Albino
Published: May 2023

The novel Coronavirus disease 2019 (COVID-19) presents a major threat to public health but can be prevented by safe and effective COVID-19 vaccines. Vaccine acceptance among healthcare workers (HCWs) is essential to promote uptake. This study, aimed to determine the COVID-19 vaccination uptake and hesitancy and its associated factors among HCWs in Tanzania. We employed a convergent-parallel mixed-methods design among 1368 HCWs across health facilities in seven geographical zones in Tanzania in 2021. We collected quantitative data by using an interviewer-administered questionnaire and qualitative data, using in-depth interviews and focus group discussions. Participants in the quantitative aspect were conveniently selected whereas those in the qualitative aspect were purposively selected based on their role in patient care, management, and vaccine provision. Stata software version 16.1 was used in the analysis of quantitative data and thematic analysis for the qualitative data. Multiple logistic regression was used to assess the determinants of COVID-19 vaccine uptake. The median age of 1368 HCWs was 33, and the interquartile range was 28–43 years; 65.6% were aged 30+ years, and 60.1% were females. Over half (53.4%) of all HCWs received the COVID-19 vaccine, 33.6% completely refused, and 13% chose to wait. HCWs aged 40+ years, from lower-level facilities (district hospitals and health centers), who worked 6+ years, and with perceived high/very high risk of COVID-19 infection had significantly higher odds of vaccine uptake. The qualitative data revealed misinformation and inadequate knowledge about COVID-19 vaccine safety and efficacy as the key barriers to uptake. Nearly half of all HCWs in Tanzania are still unvaccinated against COVID-19. The predominance of contextual influence on COVID-19 vaccine uptake calls for interventions to focus on addressing contextual determinants, focusing on younger HCWs’ population, short working duration, those working at different facility levels, and providing adequate vaccine knowledge.
Structure Guiding Supramolecular Assemblies in Metal-Organic Multi-Component Compounds of Mn(II): Experimental and Theoretical Studies
Authors: Bhattacharyya Manjit K. , Dutta Kamal K. , Sharma Pranay , Gomila Rosa M. , Barceló-Oliver Miquel , Frontera Antonio
Published: May 2023

Two multi-component coordination compounds of Mn(II), viz. [Mn(H2O)6](2-Mepy)2(4-NO2bz)2·2H2O (1) and [Mn(H2O)6][Mn(2,3-PDCH)3]2 (2) (where, 2-Mepy = 2-methylpyridine, 4-NO2bz = 4-nitrobenzoate, 2,3-PDC = 2,3-pyridinedicarboxylate), have been synthesized and characterized using elemental, spectroscopic (FT-IR and electronic), TGA and single-crystal X-ray diffraction analyses. Complex 1 is a co-crystal hydrate of Mn(II) involving uncoordinated 2-Mepy, 4-NO2bz and water molecules; while compound 2 is a multi-component molecular complex salt of Mn(II) comprising cationic [Mn(H2O)6]2+ and anionic [Mn(2,3-PDCH)3]−complex moieties. The uncoordinated 2-Mepy and 4-NO2bz moieties of 1 are involved in lone-pair (l.p)-π and C–H⋯π interactions which stabilize the layered assembly of the compound. The crystal structure of compound 2 has been previously reported. However, we have explored the unusual enclathration of complex cationic moieties within the supramolecular host cavities formed by the molecular assembly of complex anionic moieties. The supramolecular assemblies obtained in the crystal structure have been further studied theoretically using DFT calculations, quantum theory of atoms-in-molecules (QTAIM) and non-covalent interaction plot (NCI plot) computational tools. Theoretical studies reveal that the combination of π-staking interactions (l.p-π, π-π and C–H···π) have more structure-guiding roles compared to the H-bonds. The large binding energy of π-stacking interactions in 2 is due to the antiparallel orientation of aromatic rings and their coordination to the metal centers, thereby increasing the contribution of the dipole–dipole interactions.
Magnetic Force Microscopy of Multiferroic Bulk Ceramic Oxides
Authors: Uršič Hana , Šadl Matej , Prah Uroš , Fišinger Val
Published: May 2023

Bulk multiferroic ceramics have been extensively studied due to their great potential for magneto-electric coupling applications such as low-power and multifunctional nano-electronic devices. In most of these studies the macroscopic magnetic performance was investigated, while the magnetic response on the micro- and nano-scale was not examined in detail. Local magnetic phenomena can be studied using magnetic force microscopy (MFM), a technique derived from atomic force microscopy. MFM measures the magnetic force between the magnetised tip and the magnetic sample. It is one of the most used methods to characterise the structure of ferromagnetic domains, because the sample preparation is simple, non-destructive and provides a relatively high-resolution image. In this review paper we focus on the MFM analyses of bulk multiferroic ceramics. The core of the article is divided into four sections: the introduction, the preparation of samples prior to MFM examination, the reviews of MFM analyses performed on bulk multiferroic ceramics with and without external magnetic fields, and finally the conclusions and an outlook for the future.
Experimental Evaluation on the Microstructural and Mechanical Response of Ce Microalloying AZ31 Fabricated by Multi-Pass Unidirectional and Cross Rolling after TRC
Authors: Ning Fangkun , Kong Shuping , Jia Weitao , Chen Xingrui
Published: May 2023

Conventional billet rolling is being widely used in magnesium (Mg) alloys products, but this method gives rise to biological and environmental problems. The advantages of the short process on sheet fabrication have been widely proved in Mg alloy twin-roll casting (TRC). In this study, an attempt is made to create high-performance Mg alloy sheets via multi-pass unidirectional and cross hot rolling (UR, CR) after TRC for purposes of lowering edge defects and energy consumption. Then, the microstructural and mechanical response of Ce when microalloying AZ31 was observed using UR and CR, respectively. The mechanism of the performance improvement after the AZ31 microalloying is disclosed. In addition, the effect of the rolling parameters on the microstructural and mechanical properties are discussed. Experimental results revealed that the homogenization effect of the AZ31-0.2Ce alloy was the best after being kept at 440 °C for 24 h. The CR-rolled sheet had a more uniform and finer microstructure in the horizontal and center, while for the UR-rolled sheet, it was the opposing edge microstructure. This research is expected to prepare and optimize the microstructural and mechanical properties of microalloying AZ31 in a sheet-rolling process, a material that has important theoretical significance and engineering application value.
Modeling Microsegregation during Metal Additive Manufacturing: Impact of Dendrite Tip Kinetics and Finite Solute Diffusion
Authors: Hariharan V. S. , Nithin Baler , Ruban Raj L. , Makineni Surendra Kumar , Murty B. S. , Phanikumar Gandham
Published: May 2023

Rapid solidification during metal additive manufacturing (AM) leads to non-equilibrium microsegregation, which can result in the formation of detrimental phases and cracking. Most of the microsegregation models assume a Scheil-type solidification, where the solidification interface is planar and there exists a local equilibrium at the interface along with either zero or infinite solute diffusion in the respective participating phases—solid and liquid. This assumption leads to errors in prediction. One has to account for finite solute diffusion and the curvature at the dendritic tip for more accurate predictions. In this work, we compare different microsegregation models, that do and do not consider finite diffusion and dendrite tip kinetics, against experiments. We also propose a method to couple dendrite tip kinetics with the diffusion module (DICTRA®) implemented in Thermo-Calc®. The models which accounted for both finite diffusion and dendrite tip kinetics matched well with the experimental data.
The Role of Telemedicine for Psychological Support for Oncological Patients Who Have Received Radiotherapy
Authors: Caliandro Morena , Carbonara Roberta , Surgo Alessia , Ciliberti Maria Paola , Di Guglielmo Fiorella Cristina , Bonaparte Ilaria , Paulicelli Eleonora , Gregucci Fabiana , Turchiano Angela , Fiorentino Alba
Published: May 2023

AIM: In our radiation departments, all patients received psycho-oncological support during RT and during follow-up. Based on the latter, the aim of this retrospective analysis was to evaluate the role of tele-visits and in-person psychological support for cancer patients after RT, and to report a descriptive analysis pointing out the needs of psychosocial intervention in a radiation department during radiation treatment. METHODS: According to our institutional care management, all patients receiving RT were prospectively enrolled to receive charge-free assessment of their cognitive, emotional and physical states and psycho-oncological support during treatment. For the whole population who accepted the psychological support during RT, a descriptive analysis was reported. For all patients who agreed to be followed up by a psycho-oncologist, at the end of RT, a retrospective analysis was conducted to evaluate the differences between tele-consultations (video-call or telephone) and on-site psychological visits. Patients were followed up by on-site psychological visit (Group-OS) or tele-consult (Group-TC) visit. For each group, to evaluate anxiety, depression and distress, the Hospital Anxiety Depression Scale (HADS), Distress Thermometer and Brief COPE (BC) were used. RESULTS: From July 2019 to June 2022, 1145 cases were evaluated during RT with structured psycho-oncological interviews for a median of 3 sessions (range 2–5). During their first psycho-oncological interview, all the 1145 patients experienced the assessment of anxiety, depression and distress levels with the following results: concerning the HADS-A scale, 50% of cases (574 patients) reported a pathological score ≥8; concerning the HADS-D scale, 30% of cases (340 patients) reported a pathological score ≥8, concerning the DT scale, 60% (687 patients) reported a pathological score ≥4. Eighty-two patients were evaluated after RT: 30 in the Group-OS and 52 in the Group-TC. During follow-up, a median of 8 meetings (range 4–28) were performed. Comparing psychological data at baseline (beginning of RT) and at the last follow-up, in the entire population, a significant improvement in terms of HADS-A, global HADS and BC was shown (p 0.04; p 0.05; and p 0.0008, respectively). Compared to baseline, statistically significant differences were observed between the two groups in terms of anxiety in favor of on-site visit: Group-OS reported a better anxiety score compared with Group-TC. In each group, a statistical improvement was observed in BC (p 0.01). CONCLUSION: The study revealed optimal compliance to tele-visit psychological support, even if the anxiety could be better controlled when patients were followed up on-site. However, rigorous research on this topic is needed.
A Theoretical Thermal Tolerance Function for Ectothermic Animals and Its Implications for Identifying Thermal Vulnerability across Large Geographic Scales
Authors: Camacho Agustín , Angilletta Michael , Levy Ofir
Published: May 2023

The time-to-thermal-death curve, or thermal death curve, seeks to represent all the combinations of exposure time and temperature that kill individuals of a species. We present a new theoretical function to describe that time in lizards based on traditional measures of thermal tolerance (i.e., preferred body temperatures, voluntary thermal maximum, and the critical thermal maximum). We evaluated the utility of this function in two ways. Firstly, we compared thermal death curves among four species of lizards for which enough data are available. Secondly, we compared the geography of predicted thermal vulnerability based on the thermal death curve. We found that the time to loss of function or death may evolve independently from the critical thermal limits. Moreover, the traditional parameters predicted fewer deleterious sites, systematically situated at lower latitudes and closer to large water bodies (lakes or the coast). Our results highlight the urgency of accurately characterizing thermal tolerance across species to reach a less biased perception of the geography of climatic vulnerability.
How Many Azores Bullfinches (Pyrrhula murina) Are There in the World? Case Study of a Threatened Species
Authors: Costa Tarso de M. M. , Gil Artur , Timóteo Sergio , Ceia Ricardo S. , Coelho Rúben , de la Cruz Martin Azucena
Published: May 2023

The Azores bullfinch (Pyrrhula murina Godman, 1866) is a rare Passeriformes endemic from the eastern part of São Miguel Island, Azores, Portugal. This bird was almost considered extinct in the first half of the 20th century, but due to recent conservation measures, it has experienced a recovery since the beginning of the 2000s. Despite the attention given to this bird, the size of its population is still controversial, and the most recent studies present significant divergences on this behalf. The purpose of the present study is to present data from the long-term monitoring and results of the third single-morning survey of the Azores bullfinch to update information about the population size and range of this species. In addition, we performed a literature review to highlight the limitations and advantages of the different approaches for monitoring this species. The Azores Bullfinch records during the single-morning survey indicated a reduction in the extent of occurrence and area of occupancy of this species in comparison with the previous studies, despite the increase in bird detection. However, we suggest that the distribution range of this species needs further analysis concerning its area to exclude non suitable habitats from this analysis. In this study, we conclude that the most likely size of the Azores bullfinch population is 500 to 800 couples, with a slow population growth tendency and an area of distribution of 136.5 km2.
The Role of Positron Emission Tomography in Advancing the Understanding of the Pathogenesis of Heart and Vascular Diseases
Authors: Blach Anna , Kwiecinski Jacek
Published: May 2023

Cardiovascular disease remains the leading cause of morbidity and mortality worldwide. For developing new therapies, a better understanding of the underlying pathology is required. Historically, such insights have been primarily derived from pathological studies. In the 21st century, thanks to the advent of cardiovascular positron emission tomography (PET), which depicts the presence and activity of pathophysiological processes, it is now feasible to assess disease activity in vivo. By targeting distinct biological pathways, PET elucidates the activity of the processes which drive disease progression, adverse outcomes or, on the contrary, those that can be considered as a healing response. Given the insights provided by PET, this non-invasive imaging technology lends itself to the development of new therapies, providing a hope for the emergence of strategies that could have a profound impact on patient outcomes. In this narrative review, we discuss recent advances in cardiovascular PET imaging which have greatly advanced our understanding of atherosclerosis, ischemia, infection, adverse myocardial remodeling and degenerative valvular heart disease.
Former SARS-CoV-2 Infection Was Related to Decreased VO2 Peak and Exercise Hypertension in Athletes
Authors: Keller Karsten , Friedrich Oliver , Treiber Julia , Quermann Anne , Friedmann-Bette Birgit
Published: May 2023

The impact of former COVID-19 infection on the performance of athletes is not fully understood. We aimed to identify differences in athletes with and without former COVID-19 infections. Competitive athletes who presented for preparticipation screening between April 2020 and October 2021 were included in this study, stratified for former COVID-19 infection, and compared. Overall, 1200 athletes (mean age 21.9 ± 11.6 years; 34.3% females) were included in this study from April 2020 to October 2021. Among these, 158 (13.1%) athletes previously had COVID-19 infection. Athletes with COVID-19 infection were older (23.4 ± 7.1 vs. 21.7 ± 12.1 years, p < 0.001) and more often of male sex (87.7% vs. 64.0%, p < 0.001). While systolic/diastolic blood pressure at rest was comparable between both groups, maximum systolic (190.0 [170.0/210.0] vs. 180.0 [160.0/205.0] mmHg, p = 0.007) and diastolic blood pressure (70.0 [65.0/75.0] vs. 70.0 [60.0/75.0] mmHg, p = 0.012) during the exercise test and frequency of exercise hypertension (54.2% vs. 37.8%, p < 0.001) were higher in athletes with COVID-19 infection. While former COVID-19 infection was not independently associated with higher blood pressure at rest and maximum blood pressure during exercise, former COVID-19 infection was related to exercise hypertension (OR 2.13 [95%CI 1.39–3.28], p < 0.001). VO2 peak was lower in athletes with compared to those without COVID-19 infection (43.4 [38.3/48.0] vs. 45.3 [39.1/50.6] mL/min/kg, p = 0.010). SARS-CoV-2 infection affected VO2 peak negatively (OR 0.94 [95%CI 0.91–0.97], p < 0.0019). In conclusion, former COVID-19 infection in athletes was accompanied by a higher frequency of exercise hypertension and reduced VO2 peak.
Approach to Pancreatic Head Mass in the Background of Chronic Pancreatitis
Authors: Harindranath Sidharth , Sundaram Sridhar
Published: May 2023

Chronic pancreatitis (CP) is a known risk factor for pancreatic cancer. CP may present with an inflammatory mass, and differentiation from pancreatic cancer is often difficult. Clinical suspicion of malignancy dictates a need for further evaluation for underlying pancreatic cancer. Imaging modalities remain the mainstay of evaluation for a mass in background CP; however, they have their shortcomings. Endoscopic ultrasound (EUS) has become the go-to investigation. Adjunct modalities such as contrast-harmonic EUS and EUS elastography, as well as EUS-guided sampling using newer-generation needles are useful in differentiating inflammatory from malignant masses in the pancreas. Paraduodenal pancreatitis and autoimmune pancreatitis often masquerade as pancreatic cancer. In this narrative review, we discuss the various modalities used to differentiate inflammatory from malignant masses of the pancreas.
Low Prevalence of HSV-1 and Helicobacter pylori in HNSCC and Chronic Tonsillitis Patients Compared to Healthy Individuals
Authors: Strzelczyk Joanna Katarzyna , Świętek Agata , Hudy Dorota , Gołąbek Karolina , Gaździcka Jadwiga , Miśkiewicz-Orczyk Katarzyna , Ścierski Wojciech , Strzelczyk Janusz , Misiołek Maciej
Published: May 2023

Recent studies identified viral and bacterial factors, including HSV-1 and H. pylori, as possible factors associated with diseases such as chronic tonsillitis and cancers, including head and neck squamous cell carcinoma (HNSCC). We assessed the prevalence of HSV-1/2 and H. pylori in patients with HNSCC, chronic tonsillitis, and healthy individuals using PCR after DNA isolation. Associations were sought between the presence of HSV-1, H. pylori, and clinicopathological and demographic characteristics and stimulant use. HSV-1 and H. pylori were most frequently identified in controls (HSV-1: 12.5% and H. pylori: 6.3%). There were 7 (7.8%) and 8 (8.6%) patients with positive HSV-1 in HNSCC and chronic tonsillitis patients, respectively, while the prevalence of H. pylori was 0/90 (0%) and 3/93 (3.2%), respectively. More cases of HSV-1 were observed in older individuals in the control group. All positive HSV-1 cases in the HNSCC group were associated with advanced tumor stage (T3/T4). The prevalence of HSV-1 and H. pylori was highest in the controls compared to HNSCC and chronic tonsillitis patients, which indicates that the pathogens were not risk factors. However, since all positive HSV-1 cases in the HNSCC group were observed only in patients with advanced tumor stage, we suggested a possible link between HSV-1 and tumor progression. Further follow-up of the study groups is planned.
Treatment of the Neutropenia Associated with GSD1b and G6PC3 Deficiency with SGLT2 Inhibitors
Authors: Veiga-da-Cunha Maria , Wortmann Saskia B. , Grünert Sarah C. , Van Schaftingen Emile
Published: May 2023

Glycogen storage disease type Ib (GSD1b) is due to a defect in the glucose-6-phosphate transporter (G6PT) of the endoplasmic reticulum, which is encoded by the SLC37A4 gene. This transporter allows the glucose-6-phosphate that is made in the cytosol to cross the endoplasmic reticulum (ER) membrane and be hydrolyzed by glucose-6-phosphatase (G6PC1), a membrane enzyme whose catalytic site faces the lumen of the ER. Logically, G6PT deficiency causes the same metabolic symptoms (hepatorenal glycogenosis, lactic acidosis, hypoglycemia) as deficiency in G6PC1 (GSD1a). Unlike GSD1a, GSD1b is accompanied by low neutrophil counts and impaired neutrophil function, which is also observed, independently of any metabolic problem, in G6PC3 deficiency. Neutrophil dysfunction is, in both diseases, due to the accumulation of 1,5-anhydroglucitol-6-phosphate (1,5-AG6P), a potent inhibitor of hexokinases, which is slowly formed in the cells from 1,5-anhydroglucitol (1,5-AG), a glucose analog that is normally present in blood. Healthy neutrophils prevent the accumulation of 1,5-AG6P due to its hydrolysis by G6PC3 following transport into the ER by G6PT. An understanding of this mechanism has led to a treatment aimed at lowering the concentration of 1,5-AG in blood by treating patients with inhibitors of SGLT2, which inhibits renal glucose reabsorption. The enhanced urinary excretion of glucose inhibits the 1,5-AG transporter, SGLT5, causing a substantial decrease in the concentration of this polyol in blood, an increase in neutrophil counts and function and a remarkable improvement in neutropenia-associated clinical signs and symptoms.
Single-Voxel MR Spectroscopy of Gliomas with s-LASER at 7T
Authors: Prener Martin , Opheim Giske , Shams Zahra , Søndergaard Christian Baastrup , Lindberg Ulrich , Larsson Henrik B. W. , Ziebell Morten , Larsen Vibeke Andrée , Vestergaard Mark Bitsch , Paulson Olaf B.
Published: May 2023

Background and Purpose: Magnetic resonance spectroscopy (MRS)—a method of analysing metabolites in vivo—has been utilized in several studies of brain glioma biomarkers at lower field strengths. At ultra-high field strengths, MRS provides an improved signal-to-noise-ratio and spectral resolution, but 7T studies on patients with gliomas are sparse. The purpose of this exploratory study was to evaluate the potential clinical implication of the use of single-voxel MRS at 7T to assess metabolic information on lesions in a pilot cohort of patients with grade II and III gliomas. Methods: We scanned seven patients and seven healthy controls using the semi-localization by adiabatic-selective refocusing sequence on a Philips Achieva 7T system with a standard dual-transmit head coil. The metabolic ratios were calculated relative to water and total creatine. Additionally, 2-hydroxyglutarate (2-HG) MRS was carried out in four of the patients, and the 2-HG concentration was calculated relative to water. Results: When comparing the tumour data to control regions in both patients and healthy controls, we found that the choline/creatine and myo-inositol/creatine ratios were significantly increased and that the N-acetylaspartate/creatine and the neurotransmitter glutamate/creatine ratios were significantly decreased. The N-acetylaspartate/water and glutamate/water ratios were also significantly decreased. The lactate/water and lactate/creatine ratios showed increases, although not significant. The GABA/water ratio was significantly decreased, but the GABA/creatine ratio was not. MRS spectra showed the presence of 2-HG in three of the four patients studied. Three of the patients, including the MRS 2-HG-negative patient, were operated on, and all of them had the IDH mutation. Conclusion: Our findings were consistent with the existing literature on 3T and 7T MRS.
Attribute-Based Verifiable Conditional Proxy Re-Encryption Scheme
Authors: Tang Yongli , Jin Minglu , Meng Hui , Yang Li , Zheng Chengfu
Published: May 2023

There are mostly semi-honest agents in cloud computing, so agents may perform unreliable calculations during the actual execution process. In this paper, an attribute-based verifiable conditional proxy re-encryption (AB-VCPRE) scheme using a homomorphic signature is proposed to solve the problem that the current attribute-based conditional proxy re-encryption (AB-CPRE) algorithm cannot detect the illegal behavior of the agent. The scheme implements robustness, that is the re-encryption ciphertext, can be verified by the verification server, showing that the received ciphertext is correctly converted by the agent from the original ciphertext, thus, meaning that illegal activities of agents can be effectively detected. In addition, the article demonstrates the reliability of the constructed AB-VCPRE scheme validation in the standard model, and proves that the scheme satisfies CPA security in the selective security model based on the learning with errors (LWE) assumption.
The Analysis of Bursary Satisfaction and Learning Performance for Disadvantaged Students: A Case Study from Taiwan
Authors: Chiu Kuei-Chien , Chen Rung-Ching
Published: May 2023

For the majority of people, bursaries are a significant concern during their academic careers. This research focuses on how satisfied subsidized students are with the program and how it affects their ability to learn after receiving disadvantaged students’ bursaries. The study analyzes the 1788 questionnaires returned by students who received the “Dream. Set Sail. Turn Life” Underprivileged Learning Scholarship for three academic years from 2019 to 2021. The data were collected from a university in Taiwan. The primary purpose is to explore the students’ satisfaction with implementing the plan and provide a further analysis of satisfaction and learning effects. The research shows that the rest of the questions are significant, except that applicants can learn more professional skills. The following are the priorities: positive impact on the life and future of subsidized students, expanding personal horizons, improving employability, learning more professional knowledge, reducing the economic pressure of studying, and eliminating the need for work-study. In addition, the overall satisfaction of the recipients with the program will also affect their learning outcomes (academic performance). While using the overall satisfaction of the program to perform regression on the learning effect, it was found that the subsidized recipients significantly impact the overall satisfaction of the program and their learning effects. The higher the subsidized recipients’ overall satisfaction with the program, the more significant the learning effect.
Blended Learning in a Higher Education Context: Exploring University Students’ Learning Behavior
Authors: Nikolopoulou Kleopatra , Zacharis Georgios
Published: May 2023

Blended learning is a growing phenomenon in higher education after the COVID-19 pandemic (the educational process moved entirely online), and the way is prepared for blended education mode in universities. Although blended learning research is on the rise, fewer studies regard university students’ learning behavior in blended learning environments. This study aims to investigate university students’ blended learning behavior perceptions shortly after the pandemic. A 19-item questionnaire was administered to 176 university students in Greece. Students, in general, expressed positive blended learning behavior perceptions. Higher percentages of agreement were associated with the role of audio-visual online resources in facilitating and supporting independent learning and with student motivation in blended education. Students expressed lower percentages of agreement, and some uncertainty, with regard to involvement in small group work with their peers. Implications for students, educators, as well as university policy and practice are discussed.
Early Years Staff Experiences in a “Culture of Learning” Regarding Inclusion in a Nursery Class in a British School: An Interpretative Phenomenological Analysis
Authors: Corral-Granados Anabel , Martínez-Martínez Ana María , Sánchez-Muñoz Carlos , Navarro-Gómez Noelia
Published: May 2023

Less than 20% of the early childhood education and care (ECEC) staff members working in British early childhood centres agree that the inclusion of all children is an essential part of their working agenda, as they feel unqualified to take care of children with complex SEN or disabilities. This study makes a novel contribution by drawing on data compiled from a one-year ethnographic study which addressed the in-service learning experiences of seven teaching staff members that work inclusively. The participants included 2 classroom teachers, 1 SENCo (Special Educational Needs Coordinator), and 4 teaching assistants from a preschool class that teaches 92 children between the ages of 3 and 4, located in a primary school in England. We explore what professional learning means for the participants’ role, which professional learning opportunities are meaningful to them, and under which circumstances had been offered. This study not only does consider their opportunities for professional development on the job but also outside of work. The data were collected through semi-structured interviews, artifact analysis, and ongoing participant observation over one academic year. Data were analysed using interpretative phenomenological analysis (IPA). The results demonstrate that this case study offers a unique perspective of a microsystem that could be at risk due to a lack of awareness by leaders and administration. The study is divided into four themes that directly impact inclusive professional service-development practices: (1) challenges posed to continuous professional development by differing professional roles, (2) motives for in-service training: combining career, school, and authorities’ interests, (3) promotion of meaningful professional development experiences by school, and (4) self-determined classroom motivated by respect and recognition.
Fighting Discrimination through Sport? Evaluating Sport-Based Workshops in Irish Schools
Authors: Moustakas Louis , Kalina Lisa
Published: May 2023

Discrimination based on ethnicity, gender, or sexual orientation remains a pressing challenge throughout Europe, including within Ireland. Despite this, anti-discrimination education is lacking and uneven within school settings. Responding to this gap and seeking to capitalise on the perceived social potential of sport, one Irish NGO has begun delivering sport-based anti-discrimination workshops to students in primary and secondary schools nationwide. This paper presents an evaluation of these workshops, putting a specific focus on the learning outcomes generated. Data were obtained from standardised, open-ended student feedback forms and qualitatively analysed using a Framework Analysis. The results illustrate fairly consistent learning outcomes, but these outcomes generally focus on individual behaviours and attitudes. This contrasts strongly with literature on anti-discrimination education, which recognises a need to reflect on privilege and social structures while also developing clear strategies to address discrimination. To conclude, we propose recommendations and ways forward to help address both individual and structural realities within such sport-based workshops.
Teachers’ Professional Training through Augmented Reality: A Literature Review
Authors: Mena Juanjo , Estrada-Molina Odiel , Pérez-Calvo Esperanza
Published: May 2023

Practicum is regarded as a fundamental aspect of the training of prospective teachers. In addition, digital tools are increasingly used to enrich a traditional face-to-face experience. However, the technological exploitation of Augmented Reality (AR) by undergraduate students studying early childhood and primary education is low. A Systematic Literature Review (SLR) on the use of Augmented Reality (AR) in teacher training was conducted. Based on the overarching objectives of the ERASMUS+ project, entitled Digital Practicum 3.0 Exploring Augmented Reality, Remote Classrooms, and Virtual Learning to Enrich and Expand Pre-service Teacher Education Preparation (2020-1-ES01-KA226-HE-096120), the ultimate purpose of this study was to assess whether the use of this resource favors learning and expertise. Two main results are prominent. First, it is noteworthy how the use of this digital technology is limited, given the scarcity of studies. Second, the research studies available focus largely on the benefits of the use of AR in teacher education at a theoretical level. Thus, future research needs to further explore the use of AR in teacher training specially focused on student teachers’ learning processes.
Supporting Preservice Teachers in Analyzing Curriculum Materials
Authors: Obczovsky Markus , Schubatzky Thomas , Haagen-Schützenhöfer Claudia
Published: May 2023

Developing evidence-based curricula is a common approach in science education research to improve the quality of teaching. Curriculum developers recurrently provide curriculum materials (CMs) to support teachers who design instruction in the classroom. However, these CMs are often designed for students, and the features of CMs that are supportive of student learning are not sufficiently explained. Extant studies indicate that teachers struggle to identify these features in CMs or reject certain features of CMs. Therefore, we developed a teaching and learning sequence (TLS) for teacher education programs to support preservice physics teachers in analyzing CMs. We designed a tool that provides a scheme for systematically analyzing CMs and investigated if this tool is suitable for supporting preservice physics teachers in analyzing CMs. We implemented the TLS in a bachelor seminar (N = 8) of our teacher education program, conducted short, guided interviews as well as problem-centered interviews, and collected several learning products. The tool helps preservice teachers to discover a broader range of features of CMs; however, they struggle to argue the role of these features in facilitating student learning. Further, we discuss the refinement of the tool and provide design conjectures for the development of a similar TLS.
Efficient Multiclass Classification Using Feature Selection in High-Dimensional Datasets
Authors: Kumar Ankur , Kaur Avinash , Singh Parminder , Driss Maha , Boulila Wadii
Published: May 2023

Feature selection has become essential in classification problems with numerous features. This process involves removing redundant, noisy, and negatively impacting features from the dataset to enhance the classifier’s performance. Some features are less useful than others or do not correlate with the system’s evaluation, and their removal does not affect the system’s performance. In most cases, removing features with a monotonically decreasing impact on the system’s performance increases accuracy. Therefore, this research aims to propose a dimensionality reduction method using a feature selection technique to enhance accuracy. This paper proposes a novel feature-selection approach that combines filter and wrapper techniques to select optimal features using Mutual Information with the Sequential Forward Method and 10-fold cross-validation. Results show that the proposed algorithm can reduce features by more than 75% in datasets with large features and achieve a maximum accuracy of 97%. The algorithm outperforms or performs similarly to existing ones. The proposed algorithm could be a better option for classification problems with minimized features.
Deep Reinforcement Learning-Based Adaptive Beam Tracking and Resource Allocation in 6G Vehicular Networks with Switched Beam Antennas
Authors: Ahmed Tahir H. , Tiang Jun Jiat , Mahmud Azwan , Gwo Chin Chung , Do Dinh-Thuan
Published: May 2023

In this paper, we propose a novel switched beam antenna system model integrated with deep reinforcement learning (DRL) for 6G vehicle-to-vehicle (V2V) communications. The proposed system model aims to address the challenges of highly dynamic V2V environments, including rapid changes in channel conditions, interference, and Doppler effects. By leveraging the beam-switching capabilities of switched beam antennas and the intelligent decision making of DRL, the proposed approach enhances the performance of 6G V2V communications in terms of throughput, latency, reliability, and spectral efficiency. The proposed work develops a comprehensive mathematical model that accounts for 6G channel modeling, beam-switching, and beam-alignment errors. The Proposed DRL framework is designed to learn optimal beam-switching decisions in real time, adapting to the complex and varying V2V communication scenarios. The integration of the proposed antenna system and DRL model results in a robust solution that is capable of maintaining reliable communication links in a highly dynamic environment. To validate the proposed approach, extensive simulations were conducted and performance analysis using various performance metrics, such as throughput, latency, reliability, energy efficiency, resource utilization, and network scalability, was analyzed. Results demonstrate that the proposed system model significantly outperforms conventional V2V communication systems and other state-of-the-art techniques. Furthermore, the proposed approach shows that the beam-switching capabilities of the switched beam antenna system and the intelligent decision making of the DRL model are essential in addressing the challenges of 6G V2V communications.
Handling the Complexity of Computing Maximal Consistent Blocks
Authors: Mroczek Teresa
Published: May 2023

The maximal consistent blocks technique, adopted from discrete mathematics, describes the maximal collection of objects, in which all objects are indiscernible in terms of available information. In this paper, we estimate the total possible number of maximal consistent blocks and prove that the number of such blocks may grow exponentially with respect to the number of attributes for incomplete data with “do not care” conditions. Results indicate that the time complexity of some known algorithms for computing maximal consistent blocks has been underestimated so far. Taking into account the complexity, for the practical usage of such blocks, we propose a performance improvement involving the parallelization of the maximal consistent blocks construction method.
Recent Research for HZO-Based Ferroelectric Memory towards In-Memory Computing Applications
Authors: Yoo Jaewook , Song Hyeonjun , Lee Hongseung , Lim Seongbin , Kim Soyeon , Heo Keun , Bae Hagyoul
Published: May 2023

The AI and IoT era requires software and hardware capable of efficiently processing massive amounts data quickly and at a low cost. However, there are bottlenecks in existing Von Neumann structures, including the difference in the operating speed of current-generation DRAM and Flash memory systems, the large voltage required to erase the charge of nonvolatile memory cells, and the limitations of scaled-down systems. Ferroelectric materials are one exciting means of breaking away from this structure, as Hf-based ferroelectric materials have a low operating voltage, excellent data retention qualities, and show fast switching speed, and can be used as non-volatile memory (NVM) if polarization characteristics are utilized. Moreover, adjusting their conductance enables diverse computing architectures, such as neuromorphic computing with analog characteristics or ‘logic-in-memory’ computing with digital characteristics, through high integration. Several types of ferroelectric memories, including two-terminal-based FTJs, three-terminal-based FeFETs using electric field effect, and FeRAMs using ferroelectric materials as capacitors, are currently being studied. In this review paper, we include these devices, as well as a Fe-diode with high on/off ratio properties, which has a similar structure to the FTJs but operate with the Schottky barrier modulation. After reviewing the operating principles and features of each structure, we conclude with a summary of recent applications that have incorporated them.
A Survey on Sparsity Exploration in Transformer-Based Accelerators
Authors: Fuad Kazi Ahmed Asif , Chen Lizhong
Published: May 2023

Transformer models have emerged as the state-of-the-art in many natural language processing and computer vision applications due to their capability of attending to longer sequences of tokens and supporting parallel processing more efficiently. Nevertheless, the training and inference of transformer models are computationally expensive and memory intensive. Meanwhile, utilizing the sparsity in deep learning models has proven to be an effective approach to alleviate the computation challenge as well as help to fit large models in edge devices. As high-performance CPUs and GPUs are generally not flexible enough to explore low-level sparsity, a number of specialized hardware accelerators have been proposed for transformer models. This paper provides a comprehensive review of hardware transformer accelerators that have been proposed to explore sparsity for computation and memory optimizations. We classify existing works based on the strategies of utilizing sparsity and identify their pros and cons in those strategies. Based on our analysis, we point out promising directions and recommendations for future works on improving the effective sparse execution of transformer hardware accelerators.
Soft Segmentation and Reconstruction of Tree Crown from Laser Scanning Data
Authors: Dai Mingrui , Li Guohua
Published: May 2023

Point cloud data obtained by laser scanning can be used for object shape modeling and analysis, including forest inventory. One of the inventory tasks is individual tree extraction and measurement. However, individual tree segmentation, especially tree crown segmentation, is challenging. In this paper, we present a novel soft segmentation algorithm to segment tree crowns in point clouds automatically and reconstruct the tree crown surface from the segmented crown point cloud. The soft segmentation algorithm mainly processes the overlapping region of the tree crown. The experimental results showed that the segmented crown was accurate, and the reconstructed crown looked natural. The reconstruction algorithm was highly efficient in calculating the time and memory cost aspects since the number of the extracted boundary points was small. With the reconstructed crown geometry, the crown attributes, including the width, height, superficial area, projecting ground area, and volume, could be estimated. The algorithm presented here is effective for tree crown segmentation.
Research on Railway Dispatcher Fatigue Detection Method Based on Deep Learning with Multi-Feature Fusion
Authors: Chen Liang , Zheng Wei
Published: May 2023

Traffic command and scheduling are the core monitoring aspects of railway transportation. Detecting the fatigued state of dispatchers is, therefore, of great significance to ensure the safety of railway operations. In this paper, we present a multi-feature fatigue detection method based on key points of the human face and body posture. Considering unfavorable factors such as facial occlusion and angle changes that have limited single-feature fatigue state detection methods, we developed our model based on the fusion of body postures and facial features for better accuracy. Using facial key points and eye features, we calculate the percentage of eye closure that accounts for more than 80% of the time duration, as well as blinking and yawning frequency, and we analyze fatigue behaviors, such as yawning, a bowed head (that could indicate sleep state), and lying down on a table, using a behavior recognition algorithm. We fuse five facial features and behavioral postures to comprehensively determine the fatigue state of dispatchers. The results show that on the 300 W dataset, as well as a hand-crafted dataset, the inference time of the improved facial key point detection algorithm based on the retina–face model was 100 ms and that the normalized average error (NME) was 3.58. On our own dataset, the classification accuracy based the an Bi-LSTM-SVM adaptive enhancement algorithm model reached 97%. Video data of volunteers who carried out scheduling operations in the simulation laboratory were used for our experiments, and our multi-feature fusion fatigue detection algorithm showed an accuracy rate of 96.30% and a recall rate of 96.30% in fatigue classification, both of which were higher than those of existing single-feature detection methods. Our multi-feature fatigue detection method offers a potential solution for fatigue level classification in vital areas of the industry, such as in railway transportation.
Elucidation of Response and Electrochemical Mechanisms of Bio-Inspired Rubber Sensors with Supercapacitor Paradigm
Authors: Shimada Kunio
Published: May 2023

The electrochemical paradigm of a supercapacitor (SC) is effective for investigating cutting-edge deformable and haptic materials made of magnetic compound fluid (MCF) rubber in order to advance the production of bio-inspired sensors as artificial haptic sensors mimicking human tissues. In the present study, we measure the cyclic voltammetry (CV) profiles and electric properties with electrochemical impedance spectroscopy (EIS) to morphologically evaluate the intrinsic structure of MCF rubber containing fillers and agents. In addition, the electrochemical mechanisms of molecule and particle behavior are theorized using the SC physical framework. The solid-doped fillers in the MCF rubber characterized the behavior of the electrical double-layer capacitor (EDLC). Meanwhile, the liquid agents showed the characteristics of a pseudocapacitor (PC) due to the redox response among the molecules and particles. The potential responses to extraneous stimuli relevant to the EIS properties, categorized as slow adaption (SA), fast adaption (FA), and other type (OT), were also analyzed in terms of the sensory response of the bio-inspired sensor. The categories were based on how the response was induced from the EIS properties. By controlling the EIS properties with different types of doping agents, sensors with various sensory responses become feasible.