bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of the COVID-19 Pandemic on Youth with Chronic Pain and Their Parents: A Longitudinal Examination of Who Are Most at Risk
Authors: Birnie Kathryn A. , Kopala-Sibley Daniel C. , Pavlova Maria , Nania Cara G. , Bernier Emily , Stinson Jennifer N. , Noel Melanie
Published: May 2022

Objectives: Chronic pain and mental illness in youth and parents are poised to reach new heights amidst the societal and healthcare impacts of the COVID-19 pandemic. Evidence from natural disasters (i.e., hurricanes) suggests that a degree of personal impact and individual personality may moderate the effects of high stress events, such as the COVID-19 pandemic, on mental health. Methods: In a pre-existing cohort of 84 youth with chronic pain (Mage = 14.39; 12–18 years; 67.8% female) and 90 parents (86.7% female), we examined changes in youth pain interference and youth and parent mental health (depression, anxiety) from before to during the first wave of the COVID-19 pandemic, and the influence of personal impact of the pandemic (i.e., financial, familial, health, social, occupational, and educational domains) and individual personality (neuroticism, conscientiousness, extroversion). Results: Overall, youth reported significantly lower pain interference and anxiety as compared to pre-pandemic; however, those more personally impacted by the pandemic reported worsening pain interference and anxiety symptoms. Overall, parents reported greater depressive symptoms as compared to pre-pandemic; however, those more personally impacted by the pandemic reported increased anxiety symptoms. Personality traits (high neuroticism, and low conscientiousness and extroversion) predicted worsened pain and mental health, and exacerbated effects of COVID-19-related personal impact on youth and parent anxiety symptoms. Discussion: Identifying risk and resilience profiles in youth and parents at high risk for worsening pain and mental health may better inform matching interventions to individual need.
Neurological Manifestations in Pediatric Patients Hospitalized for COVID-19: Experiences of the National Medical Center “20 de Noviembre” in Mexico City
Authors: López-Pérez Brian Javier , Cruz-Chávez Diana Alejandra , Solórzano-Gómez Elsa , Venta-Sobero José Antonio , Tapia-García Iván Alejandro , Toledo-Lozano Christian Gabriel , Torres-Vallejo Andrea , Castro-Loza Gabriela Vianney , Flores-Jurado Yazmín Evelyn , Hernández-Soriano Cristal Lucero , Alcaraz-Estrada Sofía Lizeth , Mondragón-Terán Paul , Suárez-Cuenca Juan Antonio , Garcia Silvia
Published: May 2022

COVID-19 has affected millions of children and, while it was previously considered as a respiratory disease, neurologic involvement has also been documented. The objective of this study was to identify the neurological manifestations (NMs) and the outcomes of children with COVID-19 who attended the National Medical Center “20 de Noviembre”. Methods: A retrospective cohort study of children hospitalized for COVID-19 from April 2020 to March 2021 was conducted. Clinical-demographic data were registered. Neurologic manifestations were defined as any clinical neurological expression of the central and/or peripheral nervous system that occurred during admission or hospitalization. Results: In total, 46 children with a confirmed COVID-19 result, 26 (56.5%) boys and 20 (43.5%) girls with a median age of 8.9 ± 4.6 years, constituted the study population. Half of the children showed some NMs, and this group of patients concomitantly showed acute lymphoblastic leukemia (ALL, 56%), obesity (17.3%), or acute myeloblastic leukemia (AML, 4.3%). The most frequently described NMs were headache (13, 56%), encephalopathy (10, 43.47%), and epilepsy (4, 17.39%). The mortality rate in children with NMs was 21.7% and they had a higher mortality rate when compared to those without NM p ≤ 0.025. Conclusions: NMs occurred predominantly in male children aged 6 to 12 years; ALL was the most frequent comorbidity. Headache prevailed and hypoxemia, hypocalcemia, elevated ferritin, and C-reactive protein were associated with NM. Finally, NMs were a risk factor for mortality.
Does a Graf Type-I Hip Justify the Discontinuation of Pavlik Harness Treatment in Patients with Developmental Dislocation of the Hip?
Authors: Li Yiqiang , Canavese Federico , Liu Yanhan , Wu Jianping , Li Jingchun , Yuan Zhe , Zhou Qinghe , Liu Yuanzhong , Chen Weidong , Xu Hongwen
Published: May 2022

Background: To analyze the clinical data of patients aged < 6 months with developmental dislocation of the hip (DDH) treated with Pavlik Harness (PH) in order to identify the best time to terminate PH treatment. Method: Fifty-four patients (47 females, 7 males; 63 hips) met the inclusion criteria and were included in the study; there were 33 (61.1%) left, 12 (22.2%) right and 9 (16.7%) bilateral DDH. The mean age at diagnosis was 11.8 ± 5.9 weeks (range, 1.4–25.5). All patients underwent fulltime PH treatment for about three months. At completion of PH treatment, patients were then divided into Group A, including patients with clinically stable hip joint and Graf type-I hip on ultrasound (US), and Group B, including patients with clinically stable hip joint and well-reduced hip on anterior-posterior (AP) radiographs without acetabular dysplasia. Six months after completion of PH treatment, the presence/absence of residual acetabular dysplasia (RAD) was evaluated on AP pelvis radiographs. The t-test and chi-square test were used to compare the differences in age, gender, side, Graf classification and RAD rate between the two groups of patients. Results: At completion of PH treatment, 45 hips were in Group A and 18 in Group B. There were no significant differences in age, gender, side, preoperative alpha angle and Graf classification between the two groups. Six months after discontinuation of PH, the AI in Group A (27.1° ± 6.8°) was significantly higher than that in Group B (21.9° ± 3.5°; p = 0.001); moreover 23 hips (51.1%) in Group A developed RAD compared to one hip in Group B (5.6%; p = 0.001). Among Group A patients, those with RAD were significantly older (13.7 ± 4.9 weeks) than those with normal hips (7.6 ± 3.8 weeks; p < 0.001); the incidence of RAD was significantly lower in patients with Graf type-II D hips (22.2%) than in patients with Graf type-III (70%) and type-IV hips (71.4%; p = 0.006). However, logistic regression analysis identified age as the only risk factor for RAD. All 24 hips with RAD (24/63, 38.1%) were treated with abduction braces. At final follow-up, AI in Group A (20.5° ± 3.3°) was not significantly different from that in Group B (21.9° ± 3.3°; p = 0.132). At the last follow-up visit, five hips (11.1%) in Group A still had RAD, compared to none in Group B (p = 0.31). Conclusions: In patients with DDH treated by PH, Graf type-I on US is not an absolute timing to terminate PH treatment. In addition, patients ≥ 13 weeks had a high risk of RAD despite PH treatment as 51.1% of infants developed RAD during follow up. Follow-up radiographs should be requested in all patients achieving Graf type-I hips at completion of PH treatment.
Pilot Study and Preliminary Results of Biodegradable Intramedullary Nailing of Forearm Fractures in Children
Authors: Roeder Christoph , Alves Cristina , Balslev-Clausen Andreas , Canavese Federico , Gercek Erol , Kassai Tamás , Klestil Thomas , Klingenberg Louise , Lutz Nicolas , Varga Marcell , Jozsa Gergo , Weinberg Annelie , Tüshaus Ludger
Published: May 2022

(1) Background: Diaphyseal forearm fractures are a common injury in children and adolescents. When operative treatment is needed, elastic stable intramedullary nailing (ESIN) is the most common surgical procedure. Although there is no clear evidence, hardware removal after fracture healing is performed in many patients. Often, the primary minimal invasive incision needs to be widened during implant removal. In order to decrease the burden of care of pediatric fractures, significant efforts were made to develop biodegradable implants, which make hardware removal unnecessary. Our study will conduct an observational trial on the clinical use of the Activa IM-Nail™ in forearm fractures in children between 3 and 13 years of age. The objective of this trial is to evaluate the risks and benefits of the Activa IM-Nail™. Among other objectives, the rate of refracture will be determined. (2) Methods: An international Europe-based, multicenter, prospective, single-arm, open-label study will be performed to ascertain the rate of refracture and to determine the subjective benefits of Activa IM-Nail™ for patients, parents and other caregivers. The study will include clinical follow-up including early post-operative complication, radiographs until bony healing and an additional follow-up after 1 year. At this stage, preliminary results and early complications on 76 patients are analyzed in this study and presented. (3) Results: As of April 2022, 76 patients were enrolled as per study protocol. There were 31 girls (40.8%) and 45 boys (59.2%). The mean age at the time of inclusion was 8.9 years (±2.4 years). The mean operation time was 58.9 ± 22.9 min (range, 15–119 min). The mean follow-up time was 8.9 ± 5.1 months (range, 0.2–18.6). Up to now, one refracture has occurred in one child falling from a height of about one meter 7 months after index surgery (1/76; 1.3%). (4) Conclusion: The research project assesses the safety and effectiveness of Activa IM-Nails™ as part of the surgical treatment of dislocated forearm fractures in children in the context of a PMCF study. The use of Activa IM-Nails™ with regard to various objectives, including postoperative complications and refracture rate, seems to be equal to the standard titan ESIN procedure compared to the literature. Preliminary results are encouraging and are made available.
Tipping Points and Changes in Australian Climate and Extremes
Authors: Frederiksen Jorgen S. , Osbrough Stacey L.
Published: May 2022

Systematic changes, since the beginning of the 20th century, in average and extreme Australian rainfall and temperatures indicate that Southern Australian climate has undergone regime transitions into a drier and warmer state. South-west Western Australia (SWWA) experienced the most dramatic drying trend with average streamflow into Perth dams, in the last decade, just 20% of that before the 1960s and extreme, decile 10, rainfall reduced to near zero. In south-eastern Australia (SEA) systematic decreases in average and extreme cool season rainfall became evident in the late 1990s with a halving of the area experiencing average decile 10 rainfall in the early 21st century compared with that for the 20th century. The shift in annual surface temperatures over SWWA and SEA, and indeed for Australia as a whole, has occurred primarily over the last 20 years with the percentage area experiencing extreme maximum temperatures in decile 10 increasing to an average of more than 45% since the start of the 21st century compared with less than 3% for the 20th century mean. Average maximum temperatures have also increased by circa 1 °C for SWWA and SEA over the last 20 years. The climate changes in rainfall an d temperatures are associated with atmospheric circulation shifts.
Spatio-Temporal Trends of Precipitation and Temperature Extremes across the North-East Region of Côte d’Ivoire over the Period 1981–2020
Authors: Kouman Kouamé Donald , Kabo-bah Amos T. , Kouadio Boyossoro Hélène , Akpoti Komlavi
Published: May 2022

The northeast region of Côte d’Ivoire, where agriculture is the main economic activity, is potentially vulnerable to extreme climatic conditions. This study aims to make a comprehensive spatio-temporal analysis of trends in extreme indices related to precipitation and temperature for the Zanzan region of Côte d’Ivoire over the period of 1981–2020. The statistical significance of the calculated trends was assessed using the non-parametric Mann–Kendall test, while Sen’s slope estimation was used to define the amount of change. For extreme precipitations, the results showed a decreasing trend in annual total precipitations estimated at 112.37 mm and in daily precipitations intensity indices. Furthermore, the consecutive dry days’ index showed an increasing trend estimated at 18.67 days. Unlike the trends in precipitation extremes, which showed statistically non-significant trends, the trends in temperature extremes were mostly significant over the entire study area. The cold spells indices all show decreasing trends, while the warm spells show increasing trends. Drawing inferences from the results, it becomes clear that the study area may be threatened by food insecurity and water scarcity. The results are aimed to support climate adaptation efforts and policy intervention in the region.
The Climate Change Challenge: A Review of the Barriers and Solutions to Deliver a Paris Solution
Authors: Santos Filipe Duarte , Ferreira Paulo Lopes , Pedersen Jiesper Strandsbjerg Tristan
Published: May 2022

Global greenhouse gas (GHG) emissions have continued to grow persistently since 1750. The United Nations Framework Convention on Climate Change (UNFCCC) entered into force in 1994 to stabilize GHG emissions. Since then, the increasingly harmful impacts of global climate change and repeated scientific warnings about future risks have not been enough to change the emissions trend and enforce policy actions. This paper synthesizes the climate change challenges and the insofar insufficient mitigation responses via an integrated literature review. The fossil industry, mainstream economic thinking, national rather than international interests, and political strive for short-term interests present key barriers to climate mitigation. A continuation of such trends is reflected in the Dice model, leading to a 3.5 °C temperature increase by 2100. Despite receiving the Nobel Prize for integrating climate change into long-run macroeconomic analysis via the Dice model, increases in global mean temperatures overshooting the 1.5 °C to 2 °C Paris targets imply an intensified disruption in the human–climate system. Past and present policy delays and climate disruption pave the way for solar radiation management (SRM) geoengineering solutions with largely unknown and potentially dangerous side effects. This paper argues against SRM geoengineering and evaluates critical mitigation solutions leading to a decrease in global temperatures without overshooting the Paris targets. The essential drivers and barriers are discussed through a unified approach to tipping points in the human–climate system. The scientific literature presents many economically and technologically viable solutions and the policy and measures required to implement them. The present paper identifies the main barriers to integrating them in a globally cooperative way, presenting an efficient, long-term, and ethical policy approach to climate change.
Usefulness of Collaborative Work in the Evaluation of Prostate Cancer from MRI
Authors: Mata Christian , Walker Paul , Oliver Arnau , Martí Joan , Lalande Alain
Published: May 2022

The aim of this study is to show the usefulness of collaborative work in the evaluation of prostate cancer from T2-weighted MRI using a dedicated software tool. The variability of annotations on images of the prostate gland (central and peripheral zones as well as tumour) by two independent experts was firstly evaluated, and secondly compared with a consensus between these two experts. Using a prostate MRI database, experts drew regions of interest (ROIs) corresponding to healthy prostate (peripheral and central zones) and cancer. One of the experts then drew the ROI with knowledge of the other expert’s ROI. The surface area of each ROI was used to measure the Hausdorff distance and the Dice coefficient was measured from the respective contours. They were evaluated between the different experiments, taking the annotations of the second expert as the reference. The results showed that the significant differences between the two experts disappeared with collaborative work. To conclude, this study shows that collaborative work with a dedicated tool allows consensus between expertise in the evaluation of prostate cancer from T2-weighted MRI.
Commodities—Open Access Journal on Commodities
Authors: Baek Jungho
Published: May 2022

We are very pleased to announce the launch of the new open-access journal, Commodities (ISSN: 2813-2432) [...]
Effect of Forced Melt Flow on Al–Si Eutectic-Alloy Microstructures
Authors: Al-Omari Kassab , Roósz András , Rónaföldi Arnold , Veres Zsolt
Published: May 2022

Al–Si eutectic alloys are industrially important; they play a significant role in the casting-manufacturing of most materials. The properties of the materials are governed by their microstructure, which can be tuned by adjusting the solidification process parameters. Herein, the effect of forced melt flow on the microstructure of an Al–Si eutectic alloy during unidirectional solidification was investigated experimentally. Al–12.6-wt%-Si alloy samples were solidified in a vertical Bridgman-type furnace equipped with a rotating magnetic inductor to induce flow in the melt. The samples were subjected to different magnetic induction conditions during the solidification experiments. The diameter of the samples was 8 mm, and their length was 120 mm. The eutectic alloy samples were solidified unidirectionally at a growth rate of v ≈ 0.1 mm/s and a temperature gradient of G ≈ 6 K/mm. The inter-lamellar distances (λ), lengths, and orientation angles of the Si lamellae were investigated using new measurement methods. The experimental results reveal that applying the rotating magnetic field (RMF) during the solidification has a distinct effect on the microstructure of Al–Si eutectic alloys. Indeed, the RMF refines the eutectic structure, reduces the interlamellar distances, and increases the diversity of the Si lamella angle’s orientations. However, the successive stirring process has a negligible effect on the lengths and angles of Si lamellae.
Successes and Challenges of Implementing Tobacco Dependency Treatment in Health Care Institutions in England
Authors: Agrawal Sanjay , Mangera Zaheer , Murray Rachael L. , Howle Freya , Evison Matthew
Published: May 2022

There is a significant body of evidence that delivering tobacco dependency treatment within acute care hospitals can deliver high rates of tobacco abstinence and substantial benefits for both patients and the healthcare system. This evidence has driven a renewed investment in the UK healthcare service to ensure all patients admitted to hospital are provided with evidence-based interventions during admission and after discharge. An early-implementer of this new wave of hospital-based tobacco dependency treatment services is “the CURE project” in Greater Manchester, a region in the North West of England. The CURE project strives to change the culture of a hospital system, to medicalise tobacco dependency and empower front-line hospital staff to deliver an admission bundle of care, including identification of patients that smoke, provision of very brief advice (VBA), protocolised prescription of pharmacotherapy, and opt-out referral to the specialist CURE practitioners. This specialist team provides expert treatment and behaviour change support during the hospital admission and can agree a support package after discharge, with either hospital-led or community-led follow-up. The programme has shown exceptional clinical effectiveness, with 22% of all smokers admitted to hospital abstinent from tobacco at 12 weeks, and exceptional cost-effectiveness with a public value return on investment ratio of GBP 30.49 per GBP 1 invested and a cost per QALY of GBP 487. There have been many challenges in implementing this service, underpinned by the system-wide culture change and ensuring the good communication and engagement of all stakeholders across the complex networks of the tobacco control and healthcare system. The delivery of hospital-based tobacco dependency services across all NHS acute care hospitals represents a substantial step forward in the fight against the tobacco epidemic.
Clinical Validation of a Rapid Variant-Proof RT-RPA Assay for the Detection of SARS-CoV-2
Authors: Cherkaoui Dounia , Heaney Judith , Huang Da , Byott Matthew , Miller Benjamin S. , Nastouli Eleni , McKendry Rachel A.
Published: May 2022

The COVID-19 pandemic has unveiled a pressing need to expand the diagnostic landscape to permit high-volume testing in peak demand. Rapid nucleic acid testing based on isothermal amplification is a viable alternative to real-time reverse transcription polymerase chain reaction (RT-PCR) and can help close this gap. With the emergence of SARS-CoV-2 variants of concern, clinical validation of rapid molecular tests needs to demonstrate their ability to detect known variants, an essential requirement for a robust pan-SARS-CoV-2 assay. To date, there has been no clinical validation of reverse transcription recombinase polymerase amplification (RT-RPA) assays for SARS-CoV-2 variants. We performed a clinical validation of a one-pot multi-gene RT-RPA assay with the E and RdRP genes of SARS-CoV-2 as targets. The assay was validated with 91 nasopharyngeal samples, with a full range of viral loads, collected at University College London Hospitals. Moreover, the assay was tested with previously sequenced clinical samples, including eleven lineages of SARS-CoV-2. The rapid (20 min) RT-RPA assay showed high sensitivity and specificity, equal to 96% and 97%, respectively, compared to gold standard real-time RT-PCR. The assay did not show cross-reactivity with the panel of respiratory pathogens tested. We also report on a semi-quantitative analysis of the RT-RPA results with correlation to viral load equivalents. Furthermore, the assay could detect all eleven SARS-CoV-2 lineages tested, including four variants of concern (Alpha, Beta, Delta, and Omicron). This variant-proof SARS-CoV-2 assay offers a significantly faster and simpler alternative to RT-PCR, delivering sensitive and specific results with clinical samples.
Oral Warty Dyskeratoma—A Systematic Review of the Literature
Authors: Raj A. Thirumal , Awan Kamran Habib , Patil Shankargouda , Morgan Peter , Warnakulasuriya Saman
Published: May 2022

Objective: To systematically review the clinicopathological features of oral warty keratoma based on published literature. Materials and Methods: PubMed and Scopus databases were searched for reports of oral warty dyskeratoma. Of the 52 identified articles, only 25 articles (43 cases) satisfied the selection criteria (case report/series in the English language reporting clinicopathologically diagnosed oral warty dyskeratoma/oral focal acantholytic keratosis/oral isolated dyskeratosis follicularis in humans). Risk of bias was assessed using the Joanna Briggs institute critical appraisal checklist for case reports and case series. Results: Most cases had well-circumscribed, white, nodular verruco-papillary lesions with a central depressed/crater-like area. Alveolar ridges were the most frequent sites of occurrence and tobacco was the most commonly associated risk factor. Histopathologically, the most pathognomonic feature was the supra-basal clefting. The cleft had dyskeratotic acantholytic cells (corps ronds, and grains). Below the cleft were projections of the connective tissue villi lined by basal cells. The basal cells in a few cases exhibited hyperplasia in the form of budding into the stroma, but epithelial dysplasia was not reported. The surface epithelium had crypts filled with keratin debris. Conclusion: Oral warty dyskeratoma is a rare solitary self-limiting benign entity, which due to its clinical and histopathological resemblance and associated habit history could be misdiagnosed as leukoplakia or carcinoma. None of the assessed articles provided molecular data, which in turn could be the reason for the lack of insight into the etiopathogenesis of this enigmatic lesion.
Feasibility of 18F-Fluorocholine PET for Evaluating Skeletal Muscle Atrophy in a Starved Rat Model
Authors: Park Sun Mi , Kim Jisu , Baek Suji , Jeon Joo-Yeong , Lee Sang Ju , Kang Seo Young , Yoo Min Young , Yoon Hai-Jeon , Kwon Seung Hae , Lim Kiwon , Oh Seung Jun , Kim Bom Sahn , Lee Kang Pa , Moon Byung Seok
Published: May 2022

Imaging techniques for diagnosing muscle atrophy and sarcopenia remain insufficient, although various advanced diagnostic methods have been established. We explored the feasibility of 18F-fluorocholine (18F-FCH) positron emission tomography/computed tomography (PET/CT) for evaluating skeletal muscle atrophy, as an imaging technique that tracks choline level changes in muscles. Cell uptake in L6 cells by 18F-FCH was performed in a complete medium containing serum (untreated group, UN) and a serum-free medium (starved group, ST). Small-animal-dedicated PET/CT imaging with 18F-FCH was examined in in-vivo models with rats that were starved for 2 days to cause muscle atrophy. After the hind limbs were dissected, starvation-induced in-vivo models were anatomically confirmed by reverse-transcription polymerase chain reaction to evaluate the expression levels of the atrophy markers muscle RING-finger protein-1 (MuRF-1) and atrogin-1. 18F-FCH uptake was lower in the starvation-induced cells than in the untreated group, and in-vivo PET uptake also revealed a similar tendency (the average standardized uptake value (SUVmean) = 0.26 ± 0.06 versus 0.37 ± 0.07, respectively). Furthermore, the expression levels of MuRF-1 and atrogin-1 mRNA were significantly increased in the starvation-induced muscle atrophy of rats compared to the untreated group. 18F-FCH PET/CT may be a promising tool for diagnosing skeletal muscle atrophy.
Open Collaborative Platform for Multi-Drones to Support Search and Rescue Operations
Authors: Ho Yao-Hua , Tsai Yu-Jung
Published: May 2022

Climate-related natural disasters have affected the lives of thousands of people. Global warming creates warmer and drier conditions which increase the risk of wildfires. In large-scale disasters such as wildfires, search and rescue (SAR) operations become extremely challenging due to low visibility, difficulty to breath, and high temperature from fire and smoke. Unmanned aerial vehicles (UAVs), such as drones, have been used to support such operations. In our previous work, a Krypto module is proposed to “sniff” out wireless signals from mobile phones to locate any possible survivors. With the increased popularity of drones, it is possible to allow people to volunteer in SAR operations with their drones. In this paper, we propose an Open Collaborative Platform for multiple drones to assist SAR operations. The open platform manages different searching drones that carry the Krypto module to collaborate by sharing information and planning search paths/areas. With our Open Collaborative Platform, anyone can participate in SAR operations and contribute to finding possible survivors. The novelty of this work is the openness and collaboration of the platform that “crowdsourcing” the searching operation to a large group of people who share information and contribute to finding possible survivors in a large disaster such as wildfires. Our experimental study shows that the Open Collaborative Platform is effective in reducing both the number of drones required and the search time for finding survivors.
Information Dynamics of Electric Field Intensity before and during the COVID-19 Pandemic
Authors: Mijatovic Gorana , Kljajic Dragan , Kasas-Lazetic Karolina , Milutinov Miodrag , Stivala Salvatore , Busacca Alessandro , Cino Alfonso Carmelo , Stramaglia Sebastiano , Faes Luca
Published: May 2022

This work investigates the temporal statistical structure of time series of electric field (EF) intensity recorded with the aim of exploring the dynamical patterns associated with periods with different human activity in urban areas. The analyzed time series were obtained from a sensor of the EMF RATEL monitoring system installed in the campus area of the University of Novi Sad, Serbia. The sensor performs wideband cumulative EF intensity monitoring of all active commercial EF sources, thus including those linked to human utilization of wireless communication systems. Monitoring was performed continuously during the years 2019 and 2020, allowing us to investigate the effects on the patterns of EF intensity of varying conditions of human mobility, including regular teaching and exam activity within the campus, as well as limitations to mobility related to the COVID-19 pandemic. Time series analysis was performed using both simple statistics (mean and variance) and combining the information-theoretic measure of information storage (IS) with the method of surrogate data to quantify the regularity of EF dynamic patterns and detect the presence of nonlinear dynamics. Moreover, to assess the possible coexistence of dynamic behaviors across multiple temporal scales, IS analysis was performed over consecutive observation windows lasting one day, week, month, and year, respectively coarse grained at time scales of 6 min, 30 min, 2 h, and 1 day. Our results document that the EF intensity patterns of variability are modulated by the movement of people at daily, weekly, and monthly scales, and are blunted during periods of restricted mobility related to the COVID-19 pandemic. Mobility restrictions also affected significantly the regularity of the EF intensity time series, resulting in lower values of IS observed simultaneously with a loss of nonlinear dynamics. Thus, our analysis can be useful to investigate changes in the global patterns of human mobility both during pandemics or other types of events, and from this perspective may serve to implement strategies for safety assessment and for optimizing the design of networks of EF sensors.
Robust Variable-Step Perturb-and-Observe Sliding Mode Controller for Grid-Connected Wind-Energy-Conversion Systems
Authors: Toumi Ilham , Meghni Billel , Hachana Oussama , Azar Ahmad Taher , Boulmaiz Amira , Humaidi Amjad J. , Ibraheem Ibraheem Kasim , Kamal Nashwa Ahmad , Zhu Quanmin , Fusco Giuseppe , Bahgaat Naglaa K.
Published: May 2022

In order to extract efficient power generation, a wind turbine (WT) system requires an accurate maximum power point tracking (MPPT) technique. Therefore, a novel robust variable-step perturb-and-observe (RVS-P&O) algorithm was developed for the machine-side converter (MSC). The control strategy was applied on a WT based permanent-magnet synchronous generator (PMSG) to overcome the downsides of the currently published P&O MPPT methods. Particularly, two main points were involved. Firstly, a systematic step-size selection on the basis of power and speed measurement normalization was proposed; secondly, to obtain acceptable robustness for high and long wind-speed variations, a new correction to calculate the power variation was carried out. The grid-side converter (GSC) was controlled using a second-order sliding mode controller (SOSMC) with an adaptive-gain super-twisting algorithm (STA) to realize the high-quality seamless setting of power injected into the grid, a satisfactory power factor correction, a high harmonic performance of the AC source, and removal of the chatter effect compared to the traditional first-order sliding mode controller (FOSMC). Simulation results showed the superiority of the suggested RVS-P&O over the competing based P&O techniques. The RVS-P&O offered the WT an efficiency of 99.35%, which was an increase of 3.82% over the variable-step P&O algorithm. Indeed, the settling time was remarkably enhanced; it was 0.00794 s, which was better than for LS-P&O (0.0841 s), SS-P&O (0.1617 s), and VS-P&O (0.2224 s). Therefore, in terms of energy efficiency, as well as transient and steady-state response performances under various operating conditions, the RVS-P&O algorithm could be an accurate candidate for MPP online operation tracking.
Implementing Digital Competencies in University Science Education Seminars Following the DiKoLAN Framework
Authors: Henne Anna , Möhrke Philipp , Thoms Lars-Jochen , Huwer Johannes
Published: May 2022

Prospective teachers must acquire subject-specific digital competencies to design contemporary lessons and to promote digital competencies among students themselves. The DiKoLAN framework (Digital Competencies for Teaching in Science Education) describes basic digital competencies for the teaching profession in the natural sciences precisely for this purpose. In this article, we describe the development, implementation, and evaluation of a university course based on DiKoLAN which promotes the digital competencies of science teachers. As an example, the learning module Data Processing in Science Education is presented, and its effectiveness is investigated. For this purpose, we used a questionnaire developed by the Working Group Digital Core Competencies to measure self-efficacy, which can also be used in the future to promote digital competencies among pre-service teachers. The course evaluation showed a positive increase in the students’ self-efficacy expectations. Overall, the paper thus contributes to teacher education by using the course as a best-practice example—a blueprint for designing new courses and for implementing a test instrument for a valid evaluation.
Attentive Part-Based Alignment Network for Vehicle Re-Identification
Authors: Liu Yichu , Hu Haifeng , Chen Dihu
Published: May 2022

Vehicle Re-identification (Re-ID) has become a research hotspot along with the rapid development of video surveillance. Attention mechanisms are utilized in vehicle Re-ID networks but often miss the attention alignment across views. In this paper, we propose a novel Attentive Part-based Alignment Network (APANet) to learn robust, diverse, and discriminative features for vehicle Re-ID. To be specific, in order to enhance the discrimination of part features, two part-level alignment mechanisms are proposed in APANet, consisting of Part-level Orthogonality Loss (POL) and Part-level Attention Alignment Loss (PAAL). Furthermore, POL aims to maximize the diversity of part features via an orthogonal penalty among parts whilst PAAL learns view-invariant features by means of realizing attention alignment in a part-level fashion. Moreover, we propose a Multi-receptive-field Attention (MA) module to adopt an efficient and cost-effective pyramid structure. The pyramid structure is capable of employing more fine-grained and heterogeneous-scale spatial attention information through multi-receptive-field streams. In addition, the improved TriHard loss and Inter-group Feature Centroid Loss (IFCL) function are utilized to optimize both the inter-group and intra-group distance. Extensive experiments demonstrate the superiority of our model over multiple existing state-of-the-art approaches on two popular vehicle Re-ID benchmarks.
Smart Home: Deep Learning as a Method for Machine Learning in Recognition of Face, Silhouette and Human Activity in the Service of a Safe Home
Authors: Vardakis George , Tsamis George , Koutsaki Eleftheria , Haridimos Kondylakis , Papadakis Nikos
Published: May 2022

Despite the general improvement of living conditions and the ways of building buildings, the sense of security in or around them is often not satisfactory for their users, resulting in the search and implementation of increasingly effective protection measures. The insecurity that modern people face every day, especially in urban centers regarding their home security, led computer science to the development of intelligent systems, aiming to mitigate the risks and ultimately lead to the consolidation of the feeling of security. In order to establish security, smart applications were created that turned a house into a Smart and Safe Home. We first present and analyze the deep learning method and emphasize its important contribution to the development of the process for machine learning, both in terms of the development of methods for safety at home, but also in terms of its contribution to other sciences and especially medicine where the results are spectacular. We then analyze in detail the back propagation algorithm in neural networks in both linear and non-linear networks as well as the X-OR problem simulation. Machine learning has a direct and effective application with impressive results in the recognition of human activity and especially in face recognition, which is the most basic condition for choosing the most appropriate method in order to design a smart home. Due to the large amount of data and the large computing capabilities that a system must have in order to meet the needs of a safe, smart home, technologies such as fog and cloud computing are used for both face recognition and recognition of human silhouettes and figures. These smart applications compose the systems that are created mainly through “Deep Learning” methods based on machine learning techniques. Based on the study we have done and present in this work, we believe that with the use of DL technology, the creation of a completely safe house has been achieved to a large extent today, covering an urgent need these days due to the increase in crime.
Blockchain-Enabled: Multi-Layered Security Federated Learning Platform for Preserving Data Privacy
Authors: Mahmood Zeba , Jusas Vacius
Published: May 2022

Privacy and data security have become the new hot topic for regulators in recent years. As a result, Federated Learning (FL) (also called collaborative learning) has emerged as a new training paradigm that allows multiple, geographically distributed nodes to learn a Deep Learning (DL) model together without sharing their data. Blockchain is becoming a new trend as data protection and privacy are concerns in many sectors. Technology is leading the world and transforming into a global village where everything is accessible and transparent. We have presented a blockchain enabled security model using FL that can generate an enhanced DL model without sharing data and improve privacy through higher security and access rights to data. However, existing FL approaches also have unique security vulnerabilities that malicious actors can exploit and compromise the trained model. The FL method is compared to the other known approaches. Users are more likely to choose the latter option, i.e., providing local but private data to the server and using ML apps, performing ML operations on the devices without benefiting from other users’ data, and preventing direct access to raw data and local training of ML models. FL protects data privacy and reduces data transfer overhead by storing raw data on devices and combining locally computed model updates. We have investigated the feasibility of data and model poisoning attacks under a blockchain-enabled FL system built alongside the Ethereum network and the traditional FL system (without blockchain). This work fills a knowledge gap by proposing a transparent incentive mechanism that can encourage good behavior among participating decentralized nodes and avoid common problems and provides knowledge for the FL security literature by investigating current FL systems.
Deep-Learning-Assisted Multi-Dish Food Recognition Application for Dietary Intake Reporting
Authors: Liu Ying-Chieh , Onthoni Djeane Debora , Mohapatra Sulagna , Irianti Denisa , Sahoo Prasan Kumar
Published: May 2022

Artificial intelligence (AI) is among the major emerging research areas and industrial application fields. An important area of its application is in the preventive healthcare domain, in which appropriate dietary intake reporting is critical in assessing nutrient content. The traditional dietary assessment is cumbersome in terms of dish accuracy and time-consuming. The recent technology in computer vision with automatic recognition of dishes has the potential to support better dietary assessment. However, due to the wide variety of available foods, especially local dishes, improvements in food recognition are needed. In this research, we proposed an AI-based multiple-dish food recognition model using the EfficientDet deep learning (DL) model. The designed model was developed taking into consideration three types of meals, namely single-dish, mixed-dish, and multiple-dish, from local Taiwanese cuisine. The results demonstrate high mean average precision (mAP) = 0.92 considering 87 types of dishes. With high recognition performance, the proposed model has the potential for a promising solution to enhancing dish reporting. Our future work includes further improving the performance of the algorithms and integrating our system into a real-world mobile and cloud-computing-based system to enhance the accuracy of current dietary intake reporting tasks.
Design and Analysis of an Eight-Port Dual-Polarized High-Efficiency Shared-Radiator MIMO Antenna for 5G Mobile Devices
Authors: Shao Rui , Chen Xiaomin , Wang Junlin , Wang Xin
Published: May 2022

Nowadays, the MIMO can achieve fifth generation (5G) ultra-high capacity, but it is a great challenge for the smartphone antenna to achieve good isolation, high efficiency, and other performance in limited space. The paper designed and completed an eight-port dual-polarized high-efficiency shared-radiator antenna working in 3.5 GHz (3.4–3.6 GHz) for 5G mobile devices. The two antenna elements are regarded as one building block and share one radiator, and the size of one radiator is 17.1 × 17.1 mm2 (0.02 λ × 0.02 λ, where λ presents the free-space wavelength at 3.5 GHz). The MIMO system consists of four radiators, and the edge-to-edge distance between the radiators on the short side is 31.9 mm (0.038 λ), and the total size of the MIMO antenna system is 150 × 80 × 1.6 mm3 (0.176 λ × 0.094 λ × 0.0019 λ). The antenna uses an orthogonal placement of feed lines to produce dual polarization in the MIMO system, resulting in high isolation without introducing other decoupling structures. In addition, the reason for the high efficiency of the antenna is explained by the common mode (CM) and differential model (DM). Finally, the simulated results are as follows: the isolation is 14 dB; the total efficiency (TE) is 75–85%; the envelope correlation coefficient (ECC) is lower than 0.065; and the gain is 6.5 dB. The prototype is fabricated and tested: the isolation is better than 17 dB, the range of the measured TE is 60–75%, and the ECC is lower than 0.045. In addition, the influence of the human body model on the antenna are also discussed. Overall, the proposed MIMO antenna has a shared radiator with high isolation and high TE, and is more suitable for the current stage of 5G MIMO antenna technology. More importantly, the planar structure block is very simple to build and easy to fabricate on the substrate.
Measurement, Evaluation, and Control of Active Intelligent Gait Training Systems—Analysis of the Current State of the Art
Authors: Han Yi , Liu Chenhao , Zhang Bin , Zhang Ning , Wang Shuoyu , Han Meimei , Ferreira João P. , Liu Tao , Zhang Xiufeng
Published: May 2022

Gait recognition and rehabilitation has been a research hotspot in recent years due to its importance to medical care and elderly care. Active intelligent rehabilitation and assistance systems for lower limbs integrates mechanical design, sensing technology, intelligent control, and robotics technology, and is one of the effective ways to resolve the above problems. In this review, crucial technologies and typical prototypes of active intelligent rehabilitation and assistance systems for gait training are introduced. The limitations, challenges, and future directions in terms of gait measurement and intention recognition, gait rehabilitation evaluation, and gait training control strategies are discussed. To address the core problems of the sensing, evaluation and control technology of the active intelligent gait training systems, the possible future research directions are proposed. Firstly, different sensing methods need to be proposed for the decoding of human movement intention. Secondly, the human walking ability evaluation models will be developed by integrating the clinical knowledge and lower limb movement data. Lastly, the personalized gait training strategy for collaborative control of human–machine systems needs to be implemented in the clinical applications.
YOLOv3_ReSAM: A Small-Target Detection Method
Authors: Liu Bailin , Luo Huan , Wang Haotong , Wang Shaoxu
Published: May 2022

Small targets in long-distance aerial photography have the problems of small size and blurry appearance, and traditional object detection algorithms face great challenges in the field of small-object detection. With the collection of massive data in the information age, traditional object detection algorithms have been gradually replaced by deep learning algorithms and have an advantage. In this paper, the YOLOV3-Tiny backbone network is augmented by using the pyramid structure of image features to achieve multi-level feature fusion prediction. In order to eliminate the loss of spatial feature information and hierarchical information caused by pooling operations in convolution processes and multi-scale operations in multi-layer structures, a spatial attention mechanism based on residual structure is proposed. At the same time, the idea of reinforcement learning is introduced to guide bounding box regression on the basis of the rough positioning of the native boundary regression strategy, and the variable IoU calculation method is used as the evaluation index of the reward function, and the boundary regression model based on the reward mechanism is proposed for fine adjustment. The VisDrone2019 data set was selected as the experimental data support. Experimental results show that the mAP value of the improved small-object detection model is 33.15%, which is 11.07% higher than that of the native network model, and the boundary regression accuracy is improved by 23.74%.
Exploring Gaze Movement Gesture Recognition Method for Eye-Based Interaction Using Eyewear with Infrared Distance Sensor Array
Authors: Futami Kyosuke , Tabuchi Yuki , Murao Kazuya , Terada Tsutomu
Published: May 2022

With the spread of eyewear devices, people are increasingly using information devices in various everyday situations. In these situations, it is important for eyewear devices to have eye-based interaction functions for simple hands-free input at a low cost. This paper proposes a gaze movement recognition method for simple hands-free interaction that uses eyewear equipped with an infrared distance sensor. The proposed method measures eyelid skin movement using an infrared distance sensor inside the eyewear and applies machine learning to the time-series sensor data to recognize gaze movements (e.g., up, down, left, and right). We implemented a prototype system and conducted evaluations with gaze movements including factors such as movement directions at 45-degree intervals and the movement distance difference in the same direction. The results showed the feasibility of the proposed method. The proposed method recognized 5 to 20 types of gaze movements with an F-value of 0.96 to 1.0. In addition, the proposed method was available with a limited number of sensors, such as two or three, and robust against disturbance in some usage conditions (e.g., body vibration, facial expression change). This paper provides helpful findings for the design of gaze movement recognition methods for simple hands-free interaction using eyewear devices at a low cost.