bluuebunny/crossref_metadata_2025 huggingface dataset:
Towards Sustainable Construction Materials: A Comparative Study of Prediction Models for Green Concrete with Metakaolin
Authors: Huang Jiandong , Zhou Mengmeng , Yuan Hongwei , Sabri Mohanad Muayad Sabri , Li Xiang
Published: September 2022

Cement-based materials are widely used in transportation, construction, national defense, and other fields, due to their excellent properties. High performance, low energy consumption, and environmental protection are essential directions for the sustainable development of cement-based materials. To alleviate the environmental pressure caused by carbon emissions in cement production, this paper studies cement-based materials containing metakaolin by a comparison of prediction models for the compressive strength. To more accurately evaluate the compressive strength of metakaolin cement-based materials, this paper compares the prediction effects of four models, namely, support vector machine (SVM), decision tree (DT), k-nearest neighbor (KNN), and random forest (RF), with hyperparameters optimized by the Firefly Algorithm (FA) to study the compressive strength of cement-based materials containing metakaolin. The results demonstrated that the RF model showed the optimized prediction effect considering the lowest RSME value and the highest R value among the hybrid models for predicting metakaolin cement-based materials’ compressive strength. The importance test showed that the cement grade and the water-to-binder ratio greatly influence the compressive strength of cement-based materials with metakaolin compared to the other design parameters.
Comparative Urban Performance Evaluation of Sustainable Urbanization in Four Typical Megalopolises in China
Authors: Fang Xue , Shi Xinyu , Phillips Tyson Keen , Gao Weijun
Published: September 2022

The essence of sustainable urbanization is to take a holistic approach to the harmonious development of economic, social, cultural and environmental protection. This paper applies the urban sustainability assessment system to analyze the characteristics of indicators related to the quality of the built environment and environmental pressure of 91 cities in four major megalopolises in China from 2010 to 2018. It also combines statistical methods to summarize the general features of urban development through a comprehensive urban performance evaluation by comparative and classification analysis for the purpose of scientific guidance on sustainable urbanization. The comparative results showed that in terms of urban sustainability, the Yangtze River Delta performed best, followed by JingJinJi, Pearl River Delta and Shandong Peninsula. Of which, the quality of built environment in JingJinJi and the environment pressure in the Shandong Peninsula require particular attention to improve and decrease, respectively. Moreover, cities can be grouped into six development types through performance clustering including three positive and three negative types. The characteristics of all types are summarized, and the performance of the specific indicators are detailed compared to serve as a guiding basis for making generic recommendations of sustainable urbanization.
Degradation of Antibiotics via UV-Activated Peroxodisulfate or Peroxymonosulfate: A Review
Authors: Song Tiehong , Li Guanqiao , Hu Ruihua , Liu Ying , Liu Hongxu , Gao Yanjiao
Published: September 2022

The ultraviolet (UV)/H2O2, UV/O3, UV/peroxodisulfate (PDS) and UV/peroxymonosulfate (PMS) methods are called UV-based advanced oxidation processes. In the UV/H2O2 and UV/O3 processes, the free radicals generated are hydroxyl radicals (•OH), while in the UV/PDS and UV/PMS processes, sulfate radicals (SO4•−) predominate, accompanied by •OH. SO4•− are considered to be more advantageous than •OH in degrading organic substances, so the researches on activation of PDS and PMS have become a hot spot in recent years. Especially the utilization of UV-activated PDS and PMS in removing antibiotics in water has received much attention. Some influencing factors and mechanisms are constantly investigated and discussed in the UV/PDS and UV/PMS systems toward antibiotics degradation. However, a systematic review about UV/PDS and UV/PMS in eliminating antibiotics is lacking up to now. Therefore, this review is intended to present the properties of UV sources, antibiotics, and PDS (PMS), to discuss the application of UV/PDS (PMS) in degrading antibiotics from the aspects of effect, influencing factors and mechanism, and to analyze and propose future research directions.
Studies on the Selectivity Mechanism of Wild-Type E. coli Thioesterase ‘TesA and Its Mutants for Medium- and Long-Chain Acyl Substrates
Authors: Zhang Xinyue , Zhang Hao , Guan Shanshan , Luo Zhijian , E Jingwen , Yang Zhijie , Du Juan , Wang Song
Published: September 2022

E. coli thioesterase ‘TesA is an important enzyme in fatty acid production. Medium-chain fatty acids (MCFAs, C6-C10) are of great interest due to their similar physicochemical properties to petroleum-based oleo-chemicals. It has been shown that wild-type ‘TesA had better selectivity for long-chain acyl substrates (≥C16), while the two mutants ‘TesAE142D/Y145G and ‘TesAM141L/E142D/Y145G had better selectivity for medium-chain acyl substrates. However, it is difficult to obtain the selectivity mechanism of substrates for proteins by traditional experimental methods. In this study, in order to obtain more MCFAs, we analyzed the binding mode of proteins (‘TesA, ‘TesAE142D/Y145G and ‘TesAM141L/E142D/Y145G) and substrates (C16/C8-N-acetylcysteamine analogs, C16/C8-SNAC), the key residues and catalytic mechanisms through molecular docking, molecular dynamics simulations and the molecular mechanics Poisson–Boltzmann surface area (MM/PBSA). The results showed that several main residues related to catalysis, including Ser10, Asn73 and His157, had a strong hydrogen bond interaction with the substrates. The mutant region (Met141-Tyr146) and loop107–113 were mainly dominated by Van der Waals contributions to the substrates. For C16-SNAC, except for ‘TesAM141L/E142D/Y145G with large conformational changes, there were strong interactions at both head and tail ends that distorted the substrate into a more favorable high-energy conformation for the catalytic reaction. For C8-SNAC, the head and tail found it difficult to bind to the enzyme at the same time due to insufficient chain length, which made the substrate binding sites more variable, so ‘TesAM141L/E142D/Y145G with better binding sites had the strongest activity, and ‘TesA had the weakest activity, conversely. In short, the matching substrate chain and binding pocket length are the key factors affecting selectivity. This will be helpful for the further improvement of thioesterases.
Effect of Morphology-Dependent Oxygen Vacancies of CeO2 on the Catalytic Oxidation of Toluene
Authors: Ismail Ahmed , Zahid Muhammad , Hu Boren , Khan Adnan , Ali Nauman , Zhu Yujun
Published: September 2022

Catalytic oxidation is regarded as an effective, economical, and practical approach to remove volatile organic compounds such as important air pollutants. CeO2 catalysts with different morphologies exhibit different oxygen vacancies content, which plays a vital role in oxidation reaction. Herein, three distinct morphologies of CeO2 i.e., shuttle (CeO2 (S)), nanorod (CeO2 (R)), and nanoparticle (CeO2 (P)), were successfully fabricated by the SEM and TEM results, and investigated for toluene catalytic oxidation. The various characterizations showed that the CeO2 (S) catalyst exhibited a larger surface area along with higher surface oxygen vacancies in contrast to CeO2 (R) and CeO2 (P), which is responsible for its excellent toluene catalytic oxidation. The 90% toluene conversion temperature at 225 °C over CeO2 (S) was less than that over CeO2 (R) (283 °C) and CeO2 (P) (360 °C). In addition, CeO2 (S) showed a greater reaction rate (14.37 × 10−2 μmol∙g−1∙s−1), TOFov (4.8 × 10−4∙s−1) at 190 °C and lower activation energy value (67.4 kJ/mol). Furthermore, the CeO2 (S) also displayed good recyclability, long-term activity stability, and good tolerance to water. As a result, CeO2 (S) is considered a good candidate to remove toluene.
Production of Taxifolin from Astilbin by Fungal Biotransformation
Authors: Mei Jianfeng , Chen Xiang , Wang Pingya , Wu Yichun , Yi Yu , Ying Guoqing
Published: September 2022

Taxifolin is known to have multiple biological functions. It has been widely used as a multifunctional food additive, and consequently, the global demand for taxifolin is increasing. The main method for taxifolin production is an extraction from larch wood, but the global resources of larch are limited. Astilbin, taxifolin-3-o-rhamnoside, is abundant in many plants and much more readily available, meaning taxifolin can be obtained by deglycosylation of astilbin. In this study, a fungal strain, Aspergillus fumigatus SQH4, was isolated from an enrichment culture of Smilax glabra rhizome to achieve the deglycosylation reaction. A culture of SQH4, adjusted to pH 6.5, with 5 g/L astilbin achieved a yield of taxifolin of 91.3% after biotransformation for 14 h at 35 °C. These findings offer an alternative method for the production of taxifolin.
Spinel Magnesium Ferrite (MgFe2O4): A Glycine-Assisted Colloidal Combustion and Its Potentiality in Gas-Sensing Application
Authors: Nadargi Digambar , Umar Ahmad , Nadargi Jyoti , Patil Jayvant , Mulla Imtiaz , Akbar Sheikh , Suryavanshi Sharad
Published: September 2022

Herein, we describe the facile synthesis of spinel MgFe2O4 ferrite and its potential use as a gas sensor using a straightforward and reliable sol–gel approach, i.e., the glycine-assisted auto-combustion route. The novelty in obtaining the sensing material via the auto-combustion route is its inherent simplicity and capability to produce the material at an industry scale. The said cost-effective process makes use of simple metal salts (Mg and Fe-nitrates) and glycine in an aqueous solution, which leads to the formation of spinel MgFe2O4 ferrite. A single-phase crystallinity with crystallite sizes ranging between 36 and 41 nm was observed for the synthesized materials using the X-ray diffraction (XRD) technique. The porous morphologies of the synthesized materials caused by auto-ignition during the combustion process were validated by the microscopic investigations. The EDS analysis confirmed the constituted elements such as Mg, Fe, and O, without any impurity peaks. The gas-sensing ability of the synthesized ferrites was examined to detect various reducing gases such as LPG, ethanol, acetone, and ammonia. The ferrite showed the highest response (>80%) toward LPG with the response and recovery times of 15 s and 23 s, respectively. Though the sensor responded low toward ammonia (~30%), its response and recovery times were very quick, i.e., 7 s and 9 s, respectively. The present investigation revealed that the synthesized ferrite materials are good candidates for fabricating high-performance sensors for reducing gases in real-world applications.
Highly Specific Silver Ion Detection by Fluorescent Carbon Quantum Dots
Authors: Gontrani Lorenzo , Bauer Elvira Maria , Nucara Alessandro , Tagliatesta Pietro , Carbone Marilena
Published: September 2022

Nitrogen-doped carbon quantum dots are easily obtainable nanomaterials endowed with remarkable fluorescence properties for the detection of contaminations by heavy metals. In this report, we show that nanometric particles with high specificity for silver cations can be prepared by hydrothermal synthesis starting from citric and folic acid solutions. Solutions of these N-CQDs give a strong fluorescence emission in the violet region (385 nm) when excited at 330 nm, which can be quenched selectively by silver (I) cations at sub-nanomolar concentrations, while other cations do not give any effect. This remarkable feature was tentatively correlated with the stronger interactions between silver ion and small portions of the nanomaterial surface by comparing Ag+ and the isoelectronic Cd2+.
Influence of Positive Ion (Al3+, Sn4+, and Sb5+) Doping on the Basic Resistance and Sensing Performances of ZnO Nanoparticles Based Gas Sensors
Authors: Zhang Peng , Cao Shuang , Sui Ning , Xu Yifeng , Zhou Tingting , He Yuan , Zhang Tong
Published: September 2022

Despite potential advantages of metal oxide semiconductors (MOSs)-based gas sensors, the limitation of very high baseline resistance is still unsatisfactory for practical application. By means of element doping, the performance of metal oxide materials used as gas sensors can be optimized. Herein, different cations (Al3+, Sn4+, and Sb5+) doped ZnO nanoparticles were synthesized and used as the acetone sensing materials. Results show that the resistance of sensors based on Sn4+ doped ZnO was significantly reduced (from 5.18 to 0.28 MΩ) at 270 °C without sacrificing the acetone sensing responses. In addition, the gas sensor also exhibited the fast response/recovery time (1/10 s) and great long-term stability. The electron compensation and improved adsorbing oxygen ability for the Sn4+ doped ZnO nanoparticles contributed to the relatively low resistance and enhanced acetone sensing performances.
Relationship between Body Schema and Scholar Maturity: A Study from the National College of Banat in Timisoara, Romania
Authors: Șunei Mariana Cristina , Petracovschi Simona , Bota Eugen , Almajan-Guță Bogdan , Nagel Adrian
Published: September 2022

The purpose of this study is to analyze the role and importance of specific physical exercises in the development of the body schema in preparatory class pupils and its effect on the development of maturity. Methods: The experiment took place over a period of 10 weeks in which two physical education lessons per week were scheduled; the lessons include specific themes for the development of the body schema and contain exercises to arouse pupils’ interest in sports and physical activities from this age. A number of 150 pupils aged between 5 years and 6 months and 7 years and 6 months participated in the experiment. The pupils were divided into two groups: the experimental group (76 pupils, 32 boys and 34 girls) and the control group (74 pupils, 31 boys and 33 girls). Next, the “Draw-a-Person” Test was applied at the beginning and end of the experiment. Results: The analysis of the results highlights the fact that after completing the intervention plan there is a significant improvement in the results of the experimental group on the Maturity Scale and implicitly on the three development scales: Head Scale, Body Schema Scale, and Clothing Scale. Among the three scales, the Body Schema Scale has the greatest influence on the Maturity Scale (r = 0.841). Conclusions: The preparatory class produces a connection between the kindergarten and the school; furthermore, the physical education lessons with an emphasis on the development of the body scheme contribute to the development of maturity and school preparation of the pupils.
The Effects of an Intervention Based on the Flipped Classroom on the Learning of Basic Life Support in Schoolchildren Aged 10–13 Years: A Quasi-Experimental Study
Authors: Cons-Ferreiro Miguel , Mecías-Calvo Marcos , Romo-Pérez Vicente , Navarro-Patón Rubén
Published: September 2022

Most out-of-hospital cardiac arrests are attended first by bystanders who are usually friends and/or relatives of the victim. Therefore, the objective of this research was to analyse the impact of a training process based on the flipped classroom on basic life support skills in primary education students. The sample consisted of 308 children (148 experimental group (EG) and 160 control group (CG)) between 10 and 13 years old (M = 10.68 ± 0.64) from 2 schools in Galicia, Spain. The data reveal that the quality parameters are obtained in the number of total compressions in 2 min (CG = 213 and EG = 217; p = 0.024) and in the percentage of correct compressions (CG = 87.23% and EG = 91.6%; p = 0.013) except for the mean depth and the percentage of correct compressions, which were not reached in any case. Regarding the application of an effective discharge with the Automated external defibrillator (AED), there were no significant differences in the time used by schoolchildren between both methods (p = 0.795), but 97.5% (n = 156) of the CG and 100% (n = 148) of the EG are able to do it in just over 1 min. Based on the results obtained, we can conclude that a training program based on the flipped classroom is as effective and viable as traditional training in psychomotricity on CPR techniques and the application of an effective discharge using an AED.
Prevalence of Avascular Necrosis Following Surgical Treatments in Unstable Slipped Capital Femoral Epiphysis (SCFE): A Systematic Review and Meta-Analysis
Authors: Veramuthu Vijayanagan , Munajat Ismail , Islam Md Asiful , Mohd Emil Fazliq , Sulaiman Abdul Razak
Published: September 2022

The choice of treatment for unstable and severely displaced slipped capital femoral epiphysis (SCFE) is controversial. This meta-analysis was conducted to determine the prevalence of femoral head avascular necrosis (AVN) following various treatments for unstable SCFE. Various databases were searched to identify articles published until 4 February 2022. A random-effects model was used to examine prevalence as well as risk ratios with confidence intervals (CIs) of 95%. Thirty-three articles were analyzed in this study. The pooled prevalences of AVN in pinning in situ, pinning following intentional closed reduction, pinning following unintentional closed reduction, and open reduction via the Parsch method, subcapital osteotomy and the modified Dunn procedure were 18.5%, 23.0%, 27.6%, 9.9%, 18.6% and 19.9%, respectively. The risk of developing AVN in pinning following intentional closed reduction was found to be 1.62 times higher than pinning in situ; however, this result was not significant. The prevalence of AVN in open reduction was lowest when performed via the Parsch method; however, this finding should be interpreted with caution, since the majority of slips so-treated are of mild and moderate types as compared with the subcapital osteotomy and modified Dunn procedures, which are predominantly used to treat severely displaced slips. As the risk ratio between intentional closed reduction and the modified Dunn method showed no significant difference, we believe that the modified Dunn method has the advantage of meticulously preserving periosteal blood flow to the epiphysis, thus minimizing AVN risk. In comparison with intentional closed reduction, the modified Dunn method is used predominantly in cases of severe slips.
Oxidative Stress Biomarkers and Early Brain Activity in Extremely Preterm Infants: A Prospective Cohort Study
Authors: Coviello Caterina , Perrone Serafina , Buonocore Giuseppe , Negro Simona , Longini Mariangela , Groenendaal Floris , Vijlbrief Daniel C. , Dani Carlo , Benders Manon J. N. L. , Tataranno Maria Luisa
Published: September 2022

Early brain activity, measured using amplitude-integrated EEG (aEEG), is correlated with neurodevelopmental outcome in preterm newborns. F2-isoprostanes (IPs) are early biomarkers predictive for brain damage. We aimed to investigate the relationship between perinatal IPs concentrations and quantitative aEEG measures in preterm newborns. Thirty-nine infants (gestational age (GA) 24–27 ± 6 weeks) who underwent neuromonitoring using aEEG during the first two days after birth were enrolled. The rate of spontaneous activity transients per minute (SAT rate) and inter-SAT interval (ISI) in seconds were computed. Two postnatal time-points were examined: within 12 h (day 1) and between 24 and 48 h (day 2). IPs were measured in plasma from cord blood (cb-IPs) and between 24 and 48 h (pl-IPs). Multivariable regression analyses were performed to assess the correlation between IPs and brain activity. Cb-IPs were not associated with SAT rate and ISI at day 1. Higher pl-IPs were followed by longer ISI (R = 0.68; p = 0.034) and decreased SAT rate (R = 0.58; p = 0.007) at day 2 after adjusting for GA, FiO2 and IVH. Higher pl-IPs levels are associated with decreased functional brain activity. Thus, pl-IPs may represent a useful biomarker of brain vulnerability in high-risk infants.
Review of Pediatric Tuberculosis in the Aftermath of COVID-19
Authors: Rangchaikul Patrida , Ahn Phillip , Nguyen Michelle , Zhong Vivian , Venketaraman Vishwanath
Published: September 2022

In 2014, the World Health Organization developed the End Tuberculosis Strategy with the goal of a 95% reduction in deaths from tuberculosis (TB) by 2035. The start of the COVID-19 pandemic and global lockdown has had a major impact on TB awareness, screening, diagnosis, and prompt initiation of treatment, inevitably leading to a significant setback. We explore pediatric tuberculosis through the lens of the COVID-19 era, investigating how COVID-19 has impacted pediatric TB cases in different regions of the world and what the implications are for management moving forward to mitigate these effects. Furthermore, in light of recent findings showing how exposed infants and children are at higher risk than we thought of contracting the disease, greater attention and resources are needed to prevent further downward trends.
A Green Tea Containing Skincare System Improves Skin Health and Beauty in Adults: An Exploratory Controlled Clinical Study
Authors: Liao Ruofen , Parker Tory , Bellerose Kelly , Vollmer David , Han Xuesheng
Published: September 2022

Skin dryness, fine lines and wrinkles, red spots, red vasculature, and porphyrin count are common indicators of skin health and beauty. The skincare system in this study contains scientifically validated ingredients such as fermented green tea (Camellia sinensis) water, niacinamide, antioxidants, and a variety of natural plant extracts. The purpose of this study was to evaluate the effectiveness of this skincare system in improving facial-skin health and beauty. Twenty-six healthy adults, both female and male, aged 18–54 and of all skin types and tones, were included in the study and participated as either the active or the control group (competitor product) using designated topical products for 30 days. Skin moisture, fine lines and wrinkles, porphyrin count, red spots, and red vasculature count were measured through high-quality photography, Visia® complexion analysis, FitSkin® skin analysis, and survey questions on day 0, day 8, and day 30. Significant improvements were observed in facial moisture, red-spot count, red vasculature count, and porphyrin count on day 30 in comparison with the control group. Non-significant improvements were observed in pores, skin texture, and wrinkles. With extensive well-documented functional ingredients, the studied skincare system used daily may significantly improve key areas of skin health and beauty.
Towards a Postgraduate Oncology Training Model for Family Medicine: Mixed Methods Evaluation of a Breast Oncology Rotation
Authors: Nadler Michelle B. , Hofbauer Brooke E. , Wu Melinda , Hum Susan , Elser Christine , Nyhof-Young Joyce
Published: September 2022

Background: Family physicians have low knowledge and preparedness to manage patients with cancer. A breast oncology clinical rotation was developed for family medicine residents to address this gap in medical education. Objectives and Methods: A breast oncology rotation for family residents was evaluated using a pre-post knowledge questionnaire and semi-structured interviews comparing rotation (RRs) versus non-rotation (NRRs) residents. Quantitative and qualitative data were collected via a pre-post knowledge questionnaire and semi-structured interviews, respectively. Analysis: Quantitative data were analysed using descriptive statistics and paired t-tests to compare pre-post-rotation knowledge and preparedness. Qualitative data were coded inductively, analysed, and grouped into categories and themes. Data sets were integrated. Results: The study was terminated early due to the COVID-19 pandemic. Six RRs completed the study; 19 and 2 NRRs completed the quantitative and qualitative portions, respectively. RRs’ knowledge scores did not improve, but there was a non-significant increase in preparedness (5.3 to 8.4, p = 0.17) post-rotation. RRs described important rotation outcomes: knowledge of the patient work-up, referral process, and patient treatment trajectory; skills in risk assessment, clinical examination, and empathy, and comfort in counseling. Discussion and Conclusion: Important educational outcomes were obtained despite no change in knowledge scores. This rotation can be adapted to other training programs including an oncology primer to enable trainee integration of new information.
PET/CT for Predicting Occult Lymph Node Metastasis in Gastric Cancer
Authors: Ma Danyu , Zhang Ying , Shao Xiaoliang , Wu Chen , Wu Jun
Published: September 2022

A portion of gastric cancer patients with negative lymph node metastasis at an early stage eventually die from tumor recurrence or advanced metastasis. Occult lymph node metastasis (OLNM] is a potential risk factor for the recurrence and metastasis in these patients, and it is highly important for clinical prognosis. Positron emission tomography (PET)/computed tomography (CT) is used to assess lymph node metastasis in gastric cancer due to its advantages in anatomical and functional imaging and non-invasive nature. Among the major metabolic parameters of PET, the maximum standardized uptake value (SUVmax) is commonly used for examining lymph node status. However, SUVmax is susceptible to interference by a variety of factors. In recent years, the exploration of new PET metabolic parameters, new PET imaging agents and radiomics, has become an active research topic. This paper aims to explore the feasibility and predict the effectiveness of using PET/CT to detect OLNM. The current landscape and future trends of primary metabolic parameters and new imaging agents of PET are reviewed. For gastric cancer patients, the possibility to detect OLNM non-invasively will help guide surgeons to choose the appropriate lymph node dissection area, thereby reducing unnecessary dissections and providing more reasonable, personalized and comprehensive treatments.
Geo-Locations and System Data of Renewable Energy Installations in Germany
Authors: Manske David , Grosch Lukas , Schmiedt Julius , Mittelstädt Nora , Thrän Daniela
Published: September 2022

Information on geo-locations of renewable energy installations is very useful to investigate spatial, social or environmental questions on their impact at local and national level. However, existing data sets do not provide a sufficiently accurate representation of these installations in Germany over space and time. This work provides a valid approach on how a data set of wind power plants, photovoltaic field systems, bioenergy plants and hydropower plants can be created for Germany based on a data extract from the Core Energy Market Data Register (CEMDR) and publicly available data. Established methods were used (e.g., random forest, image recognition), but new techniques were also developed to fill data gaps or locate misplaced renewable energy installations. In this way, a substantial part of the CEMDR data could be corrected and processed in such a way that it can be freely used in a GIS software by any scientific and non-scientific discipline.
Multiple Clay Shoveler’s Fractures of the Thoracic Spine
Authors: Hoong Wilbur Teng Jun , Kaliya-Perumal Arun-Kumar
Published: September 2022

Typically, a clay shoveler’s fracture is a stress-type avulsion fracture involving the spinous processes of the lower cervical or upper thoracic vertebrae. Even though C7 and T1 are the most commonly involved spinal levels, these avulsion fractures can occur at any lower cervical or upper thoracic level, either as solitary or multiple fractures. This fracture used to be common in workers who shovel heavy loads of clay for long periods, hence its name. It does not cause any structural, functional, or neurological impairments and is therefore considered a stable fracture. Management is mostly conservative, involving rest, analgesics, and activity modification for a period of 4–6 weeks. Here, we present a 35-year-old male who sustained a motor vehicle accident. Except for midline tenderness in the back, there were no other positive findings. Plain radiographs showed a T11 vertebral compression fracture and absent or deviated spinous process shadows for most of the upper thoracic vertebrae. Computed tomography (CT) imaging clearly revealed multiple spinous process fractures extending from T2 to T8 levels. Considering the stability of these fractures, the patient was managed conservatively with rest, bracing, and analgesics. The recovery was quick, and he was back to his full functional status by six weeks.
What a Transfusion Physician Should Know about Monkeypox Virus: Barriers to and Risks for Transmission, and Possible Mitigation Strategies
Authors: Focosi Daniele , Franchini Massimo
Published: September 2022

The ongoing monkeypox pandemic is posing new challenges to the transfusion community. While to date most regulatory agencies recommend deferrals for cases and contacts, we summarize here arguments for introduction of universal PCR testing of MPXV in blood donations and donated tissue/organs.
Conceptual Models of Disability: The Development of the Consideration of Non-Biomedical Aspects
Authors: Forstner Matthias
Published: September 2022

In 1965, Saad Z. Nagi published a very influential conceptual model of disablement in which he distinguished among several aspects of the disability phenomenon. In the following decades, several other conceptual models were proposed, increasingly taking up ideas and demands emerging from the disability movement, especially the social model of disability. In this review, three generations of these conceptual models of disability are presented, contrasted, and evaluated, especially in regard to the thematization of non-biomedical aspects. The elaboration ensues with the help of the criterion of construct clarity and thus focuses on the model’s definitions of components, application context, value assumptions, and content validity. For the latter aspects, the health sociological triad of disease/illness/sickness is employed. These concepts are adapted to the disability phenomenon. While the first generation focuses on a mainly biomedical disablement process, only later supplemented with other context factors, the second generation attempts to combine this assortment with a relational understanding of disability and also increasingly departs from conceptualizing the components negatively. Finally, the third generation of conceptual models is more holistic, and gives more weight to environmental aspects, but still somewhat neglects the individual aspects.
Savings Groups for Social Health Protection: A Social Resilience Study in Rural Tanzania
Authors: Obrist Brigit , Dillip Angel , Kalolo Albino , Mayumana Iddy M. , Rutishauser Melina , Simon Vendelin T.
Published: September 2022

Global health experts use a health system perspective for research on social health protection. This article argues for a complementary actor perspective, informed by the social resilience framework. It presents a Saving4Health initiative with women groups in rural Tanzania. The participatory qualitative research design yielded new insights into the lived experience of social health protection. The study shows how participation in saving groups increased women’s collective and individual capacities to access, combine and transform five capitals. The groups offered a mechanism to save for the annual insurance premium and to obtain health loans for costs not covered by insurance (economic capital). The groups organized around aspirations of mutual support and protection, fostered social responsibility and widened women’s interaction arena to peers, government and NGO representatives (social capital). The groups expanded women’s horizon by exposing them to new ways of managing financial health risk (cultural capital). The groups strengthened women’s social recognition in their family, community and beyond and enabled them to initiate transformative change through advocacy for health insurance (symbolic capital). Savings groups shape the evolving field of social health protection in interaction with governmental and other powerful actors and have further potential for mobilization and transformative change.
Dwarf Mongoose Optimization-Based Secure Clustering with Routing Technique in Internet of Drones
Authors: Alrayes Fatma S. , Alzahrani Jaber S. , Alissa Khalid A. , Alharbi Abdullah , Alshahrani Hussain , Elfaki Mohamed Ahmed , Yafoz Ayman , Mohamed Abdullah , Hilal Anwer Mustafa
Published: September 2022

Over the last few years, unmanned aerial vehicles (UAV), also called drones, have attracted considerable interest in the academic field and exploration in the research field of wireless sensor networks (WSN). Furthermore, the application of drones aided operations related to the agriculture industry, smart Internet of things (IoT), and military support. Now, the usage of drone-based IoT, also called Internet of drones (IoD), and their techniques and design challenges are being investigated by researchers globally. Clustering and routing aid to maximize the throughput, reducing routing, and overhead, and making the network more scalable. Since the cluster network used in a UAV adopts an open transmission method, it exposes a large surface to adversaries that pose considerable network security problems to drone technology. This study develops a new dwarf mongoose optimization-based secure clustering with a multi-hop routing scheme (DMOSC-MHRS) in the IoD environment. The goal of the DMOSC-MHRS technique involves the selection of cluster heads (CH) and optimal routes to a destination. In the presented DMOSC-MHRS technique, a new DMOSC technique is utilized to choose CHs and create clusters. A fitness function involving trust as a major factor is included to accomplish security. Besides, the DMOSC-MHRS technique designs a wild horse optimization-based multi-hop routing (WHOMHR) scheme for the optimal route selection process. To demonstrate the enhanced performance of the DMOSC-MHRS model, a comprehensive experimental assessment is made. An extensive comparison study demonstrates the better performance of the DMOSC-MHRS model over other approaches.
Robust Control Strategy for Quadrotor Drone Using Reference Model-Based Deep Deterministic Policy Gradient
Authors: Liu Hongxun , Suzuki Satoshi , Wang Wei , Liu Hao , Wang Qi
Published: September 2022

Due to the differences between simulations and the real world, the application of reinforcement learning (RL) in drone control encounters problems such as oscillations and instability. This study proposes a control strategy for quadrotor drones using a reference model (RM) based on deep RL. Unlike the conventional studies associated with optimal and adaptive control, this method uses a deep neural network to design a flight controller for quadrotor drones, which can map the drone’s states and target values to control commands directly. The method was developed based on a deep deterministic policy gradient (DDPG) algorithm combined with the deep neural network. The RM was further employed for the actor–critic structure to enhance the robustness and dynamic stability. The RM–DDPG-based flight-control strategy was confirmed to be practicable through a two-fold experiment. First, a quadrotor drone model was constructed based on an actual drone, and the offline policy was trained on it. The performance of the policy was evaluated via simulations while confirming the transition of system states and the output of the controller. The proposed strategy can eliminate oscillations and steady error and can achieve robust results for the target value and external interference.
GTIP: A Gaming-Based Topic Influence Percolation Model for Semantic Overlapping Community Detection
Authors: Yang Hailu , Zhang Jin , Ding Xiaoyu , Chen Chen , Wang Lili
Published: September 2022

Community detection in semantic social networks is a crucial issue in online social network analysis, and has received extensive attention from researchers in various fields. Different conventional methods discover semantic communities based merely on users’ preferences towards global topics, ignoring the influence of topics themselves and the impact of topic propagation in community detection. To better cope with such situations, we propose a Gaming-based Topic Influence Percolation model (GTIP) for semantic overlapping community detection. In our approach, community formation is modeled as a seed expansion process. The seeds are individuals holding high influence topics and the expansion is modeled as a modified percolation process. We use the concept of payoff in game theory to decide whether to allow neighbors to accept the passed topics, which is more in line with the real social environment. We compare GTIP with four traditional (GN, FN, LFM, COPRA) and seven representative (CUT, TURCM, LCTA, ACQ, DEEP, BTLSC, SCE) semantic community detection methods. The results show that our method is closer to ground truth in synthetic networks and has a higher semantic modularity in real networks.
Cross-Subject Emotion Recognition Using Fused Entropy Features of EEG
Authors: Zuo Xin , Zhang Chi , Hämäläinen Timo , Gao Hanbing , Fu Yu , Cong Fengyu
Published: September 2022

Emotion recognition based on electroencephalography (EEG) has attracted high interest in fields such as health care, user experience evaluation, and human–computer interaction (HCI), as it plays an important role in human daily life. Although various approaches have been proposed to detect emotion states in previous studies, there is still a need to further study the dynamic changes of EEG in different emotions to detect emotion states accurately. Entropy-based features have been proved to be effective in mining the complexity information in EEG in many areas. However, different entropy features vary in revealing the implicit information of EEG. To improve system reliability, in this paper, we propose a framework for EEG-based cross-subject emotion recognition using fused entropy features and a Bidirectional Long Short-term Memory (BiLSTM) network. Features including approximate entropy (AE), fuzzy entropy (FE), Rényi entropy (RE), differential entropy (DE), and multi-scale entropy (MSE) are first calculated to study dynamic emotional information. Then, we train a BiLSTM classifier with the inputs of entropy features to identify different emotions. Our results show that MSE of EEG is more efficient than other single-entropy features in recognizing emotions. The performance of BiLSTM is further improved with an accuracy of 70.05% using fused entropy features compared with that of single-type feature.
Positive Periodic Solution for Second-Order Nonlinear Differential Equations with Variable Coefficients and Mixed Delays
Authors: Dai Zejian , Du Bo
Published: September 2022

In this paper, we study two types of second-order nonlinear differential equations with variable coefficients and mixed delays. Based on Krasnoselskii’s fixed point theorem, the existence results of positive periodic solution are established. It should be pointed out that the equations we studied are more general. Therefore, the results of this paper have better applicability.
Anatomy in Competencies-Based Medical Education
Authors: Brenner Erich
Published: September 2022

Anatomy as a basic science discipline is “vanishing” in recent competencies-based medical curricula. The fundamental requirement of these curricula to apply the knowledge from the basic disciplines in practical and clinical everyday life contributes to this disappearance. Anatomical educational objectives are in many cases not yet adapted to these changes. At the same time, the higher levels of the progress dimension in the cognitive domain and the activities associated with them certainly allow the application; even the analysis or evaluation of anatomical knowledge. However, a change in the teaching objectives to these higher levels of the progress dimension must also be accompanied by a change in the anatomical assessments. Since these forms of examinations themselves represent a practical application of anatomical knowledge, they must be carried out on suitable examination material. However, in order to protect living persons, the donated body again comes into focus.
Student-Guided Math Practice in Elementary School: Relation among Math Anxiety, Emotional Self-Efficacy, and Children’s Choices When Practicing Math
Authors: Tarkar Aditi , Matalka Brandie , Cartwright Macey , Kloos Heidi
Published: September 2022

In the current study, we explored math anxiety in the context of a special kind of math practice, one that allowed for some flexibility on the part of the students. Such student-guided math practice is conducive to exploring how math anxiety relates to children’s day-to-day experiences with math, potentially yielding insights into math anxiety that would not be available otherwise. Students in Grades 3 and 4 (N = 26) could choose math problems that were below, at, or above their proficiency level. They also completed a math-anxiety survey and an emotional self-efficacy survey. Descriptive results revealed that math anxiety was implicated in two negative outcomes of math practice: children’s tendency to avoid challenging math problems and children’s relatively low success rate when working on class-level math. Finding that math anxiety relates to several negative experiences could explain why math anxiety can persist. Importantly, results show that emotional self-efficacy plays a role in both children’s willingness to challenge themselves and their success rate. This adds to the ongoing discussion on whether emotional self-efficacy can compensate for the negative effects of math anxiety.
Performance of WLAN in Downlink MU-MIMO Channel with the Least Cost in Terms of Increased Delay
Authors: Kassa Lemlem , Deng Jianhua , Davis Mark , Cai Jingye
Published: September 2022

To improve the performance of IEEE 802.11 wireless local area (WLAN) networks, different frame-aggregation algorithms are proposed by IEEE 802.11n/ac standards to improve the throughput performance of WLANs. However, this improvement will also have a related cost in terms of increasing delay. The traffic load generated by mixed types of applications in current modern networks demands different network performance requirements in terms of maintaining some form of an optimal trade-off between maximizing throughput and minimizing delay. However, the majority of existing researchers have only attempted to optimize either one (to maximize throughput or minimize the delay). Both the performance of throughput and delay can be affected by several factors such as a heterogeneous traffic pattern, target aggregate frame size, channel condition, competing stations, etc. However, under the effect of uncertain conditions of heterogeneous traffic patterns and channel conditions in a network, determining the optimal target aggregate frame size is a significant approach that can be controlled to manage both throughput and delay. The main contribution of this study was to propose an adaptive aggregation algorithm that allows an adaptive optimal trade-off between maximizing system throughput and minimizing system delay in the WLAN downlink MU-MIMO channel. The proposed approach adopted different aggregation policies to adaptively select the optimal aggregation policy that allowed for achieving maximum system throughput by minimizing delay. Both queue delay and transmission delay, which have a significant impact when frame-aggregation algorithms are adopted, were considered. Different test case scenarios were considered such as channel error, traffic pattern, and number of competing stations. Through system-level simulation, the performance of the proposed approach was validated over the FIFO aggregation algorithm and earlier adaptive aggregation approaches, which only focused on achieving maximum throughput at the expense of delay. The performance of the proposed approach was evaluated under the effects of heterogenous traffic patterns for VoIP and video traffic applications, channel conditions, and number of STAs for WLAN downlink MU-MIMO channels.
SAR Image Reconstruction of Vehicle Targets Based on Tensor Decomposition
Authors: Tang Tao , Kuang Gangyao
Published: September 2022

Due to the imaging mechanism of Synthetic Aperture Radars (SARs), the target shape on an SAR image is sensitive to the radar incidence angle and target azimuth, but there is strong correlation and redundancy between adjacent azimuth images of SAR targets. This paper studies multi-angle SAR image reconstruction based on non-negative Tucker decomposition using adjacent azimuth images reconstructed to form a sparse tensor. Sparse tensors are used to perform non-negative Tucker decomposition, resulting in non-negative core tensors and factor matrices. The reconstruction tensor is obtained by calculating the n-mode product of the core tensor and the factor matrix, and then image reconstruction is realized. The similarity between the original image and the reconstructed image is calculated by using the structural similarity index and the cosine of the angle between the feature vectors. The reconstruction results of three target images of MSTAR show that the reconstructed image has a similarity higher than 95% with the original image in most cases, which can support target recognition under sparse observation to a certain extent.
IoT-Based Motorbike Ambulance: Secure and Efficient Transportation
Authors: Mahmoud Halah Hasan , Alghawli Abed Saif , Al-shammari Marwan Kadhim Mohammed , Amran Gehad Abdullah , Mutmbak Khaled H. , Al-harbi Khaled H. , Al-qaness Mohammed A. A.
Published: September 2022

The predilection for 5G telemedicine networks has piqued the interest of industry researchers and academics. The most significant barrier to global telemedicine adoption is to achieve a secure and efficient transport of patients, which has two critical responsibilities. The first is to get the patient to the nearest hospital as quickly as possible, and the second is to keep the connection secure while traveling to the hospital. As a result, a new network scheme has been suggested to expand the medical delivery system, which is an agile network scheme to securely redirect ambulance motorbikes to the nearest hospital in emergency cases. This research provides a secured and efficient telemedicine transport strategy compatible with the vehicle social network (VSN). The proposed telemedicine method should find the best ambulance motorbike route for getting patients to the hospital as quickly as possible. This approach also enables the secure exchange of information between ambulance motorbikes and hospitals. Ant colony optimization (ACO) is utilized as a SWARM technique to expand the capabilities of 5G-wireless mesh networks to determine the best path. To secure communication, the secure socket layer (SSL), which is boosted once by the advanced encryption standard (AES), has achieved a new suggested scheme as a cybersecurity approach. According to the performance evaluation, this approach will determine the optimal route for motorbike ambulances. Additionally, this technique establishes a secure connection between ambulance motorbikes and the hospital. The study enhances telemedicine transportation.