bluuebunny/crossref_metadata_2025 huggingface dataset:
Targeted Metabolic and Transcriptomic Analysis of Pinus yunnanensis var. pygmaea with Loss of Apical Dominance
Authors: Xiao Feng , Zhao Yang , Wang Xiurong , Yang Yao
Published: November 2022

Pinus yunnanensis var. pygmaea demonstrates obvious loss of apical dominance, inconspicuous main trunk, which can be used as an ideal material for dwarfing rootstocks. In order to find out the reasons for the lack of apical dominance of P. pygmaea, endogenous phytohormone content determination by liquid chromatography–tandem mass spectrometry (LC–MS/MS) and comparative transcriptomes were performed on the shoot apical meristem and root apical meristem of three pine species (P. massoniana, P. pygmaea, and P. elliottii). The results showed that the lack of CK and the massive accumulation of ABA and GA-related hormones may be the reasons for the loss of shoot apical dominance and the formation of multi-branching, the abnormal synthesis of diterpenoid biosynthesis may lead to the influence of GA-related synthesis, and the high expression of GA 2-oxidase (GA2ox) gene may be the cause of dwarfing. Weighted correlation network analysis (WGCNA) screened some modules that were highly expressed in the shoot apical meristem of P. pygmaea. These findings provided valuable information for identifying the network regulation of shoot apical dominance loss in P. pygmaea and enhanced the understanding of the molecular mechanism of shoot apical dominance growth differences among Pinus species.
A Comparative Study on the Performances of Spectral Nudging and Scale-Selective Data Assimilation Techniques for Hurricane Track and Intensity Simulations
Authors: Sun Xia , Xie Lian
Published: November 2022

It is a common practice to use a buffer zone to damp out spurious wave growth due to computational error along the lateral boundary of limited-area weather and climate models. Although it is an effective technique to maintain model stability, an unintended side effect of using such buffer zones is the distortion of the data passing through the buffer zone. Various techniques are introduced to enhance the communication between the limited-area model’s inner domain and the outer domain, which provides lateral boundary values for the inner domain. Among them, scale-selective data assimilation (SSDA) and the spectral nudging (SPNU) techniques share similar philosophy, i.e., directly injecting the large-scale components of the atmospheric circulation from the outer model domain into the interior grids of the inner model domain by-passing the lateral boundary and the buffer zone, but the two methods are taking different implementation approaches. SSDA utilizes a 3-dimensional variational data assimilation procedure to accomplish the data injection objective, whereas SPNU uses a nudging process. In the present study, the two approaches are evaluated comparatively for simulating hurricane track and intensity in a pair of cases: Jeanne (2004) and Irma (2017) using the Weather Research and Forecasting (WRF) model. The results indicate that both techniques are effective in improving tropical cyclone intensity and track simulations by reducing the errors of the large-scale circulation in the inner model domain. The SSDA runs produced better simulations of temperature and humidity fields which are not directly nudged. The SSDA runs also produced more accurate storm intensities in both cases and more realistic structure in Hurricane Jeanne’s case than those produced by the SPNU runs. It should be noted, however, that extending these case study results to more general situations requires additional studies covering a large number of additional cases.
Using Hybrid Algorithms of Human Detection Technique for Detecting Indoor Disaster Victims
Authors: Lee Ho-Won , Lee Kyong-Oh , Bae Ji-Hye , Kim Se-Yeob , Park Yoon-Young
Published: November 2022

When an indoor disaster occurs, the disaster site can become very difficult to escape from due to the scenario or building. Most people evacuate when a disaster situation occurs, but there are also disaster victims who cannot evacuate and are isolated. Isolated disaster victims often cannot move quickly because they do not have all the necessary information about the disaster, and secondary damage can occur. Rescue workers must rescue disaster victims quickly, before secondary damage occurs, but it is not always easy to locate isolated victims within a disaster site. In addition, rescue operators can also suffer from secondary damage because they are exposed to disaster situations. We present a HHD technique that can detect isolated victims in indoor disasters relatively quickly, especially when covered by fire smoke, by merging one-stage detectors YOLO and RetinaNet. HHD is a technique with a high human detection rate compared to other techniques while using a 1-stage detector method that combines YOLO and RetinaNet. Therefore, the HHD of this paper can be beneficial in future indoor disaster situations.
The Effects of Surfactants and Essential Oils on Microwave−Assisted Hydrothermal Synthesis of Iron Oxides
Authors: Mitar Ivana , Guć Lucija , Vrankić Martina , Paut Andrea , Marciuš Marijan , Prkić Ante , Krehula Stjepko , Mastelić Anđela , Ramljak Josipa , Ćurlin Paula
Published: November 2022

Microwave-assisted hydrothermal synthesis is a simple, reproducible, rapid, and effective method, and therefore, has attracted considerable interest among scientists in the field of synthesis not only of iron oxide but also of other metal oxides. This method has been used for the synthesis of iron oxide nanoparticles, hematite (α-Fe2O3), and goethite (α-FeOOH) in strongly alkaline media with iron(III) chloride (FeCl3) as precursor under microwave emission of 850 W. In this work, the effect on the size, shape, and composition of the final product was investigated by changing the conditions, such as shortening the synthesis time, increasing the synthesis temperature, and adding various substances to the synthesis pathway. Samples synthesized at 200 °C for 20 min by increasing the added percentage of polyethylene glycol (PEG), sodium dodecyl sulfate (SDS), rosemary essential oil and lavender essential oil promote goethite-to-hematite transformation, while N-guanylurea sulfate (NGS) and sage essential oil behave differently. The aforementioned substances added at 260 °C resulted in a decrease in particle size, but pure hematite was obtained, regardless of the type of the substances added or the decrease in synthesis time from 20 min to 5 min. Furthermore, the use of essential oils rather than surfactants in this study was presented as a novel, environmentally friendly method of iron oxide synthesis.
Determination of Crystal Growth Rates in Multi-Component Solutions
Authors: Helfenritter Christoph , Kind Matthias
Published: November 2022

Many solid forming processes involve crystallization from multi-component solutions. In order to predict final phase assemblages, multi-component phase transfer kinetics must be known. It is not sufficient to have the kinetics of only one crystallizing component in the presence of other entities; the kinetics of concurrent crystallizing components are of interest as well. However, methods for their determination are currently lacking. We propose a new method comprising desupersaturation measurements of a 150 µm film of supersaturated solution in contact with a planar crystalline substrate. We show that concentration measurement at a single point in the film is sufficient to retrieve the phase transfer kinetics. For this, we use a confocal micro-Raman spectroscope, which is able to distinguish between different components and has a high spatial resolution. We chose crystallization of Na2SO4 and Na2CO3 decahydrate from aqueous solution as our model system because of its well-known phase equilibrium. In binary experiments, we demonstrate the mode of operation and its ability to reproduce known kinetics from the literature. In ternary experiments, we successfully distinguish two courses of crystallization, the first of which is a preferential crystallization of one component and the second a simultaneous crystallization of both crystallizing components. In both cases, the parameters for simple power law kinetics are determined. If sodium carbonate decahydrate crystallizes while sodium sulfate remains in solution, the mean mass transfer coefficient is revealed to be kg,CO3=6×10−7ms−1, which is about an order of magnitude lower compared to binary crystallization. If sodium carbonate decahydrate crystallizes concurrently with sodium sulfate decahydrate, the crystallization kinetics are similar to binary cases. The other component tends to be significantly slower compared to its binary crystallization.
Study of Co-Doped K2Ti6O13 Lead-Free Ceramic for Positive Temperature Coefficient Thermistor Applications
Authors: Shariq Mohammad , Asim Siddiqui Mohd , Qamar Muhammad Azam , Altowairqi Y. , Ali Syed Kashif , Madkhali Osama , Fadhali Mohammed M. , Alharbi T. , Khan Mohd. Shakir , Saheb Syed Imam , Ahmed Zeyad M. , Awaji Majed Yousef
Published: November 2022

Cobalt-doped potassium hexa-titanate (Cox:K2Ti6O13 (x = 0.05, 0.10, 0.15 mole%)) ceramics were synthesized by the solid-state reaction method. The XRD patterns confirmed single-phase development in a monoclinic symmetry of various samples, and they were used for different structural calculations of Cox:K2Ti6O13 ceramics. The dielectric constant, tanδ, electrical modulus, and ac conductivity of Co-doped K2Ti6O13 were studied in the temperature range of 100–500 °C. Anomalies were observed in graphs of the dielectric constant versus temperature, showing the transition phase in the studied samples. Dielectric peaks at transition temperature decreased with an increasing frequency, and the peaks shifted toward higher temperatures, illustrating the relaxation of the dielectric materials. The composition with x = 0.10 showed low dielectric loss and a higher dielectric constant and can be utilized for high-temperature dielectric material. Small doping of cobalt improved the ac conductivity of K2Ti6O13 ceramics due to the increase in the spin–phonon interaction and dominant electron hopping conduction; however, the conductivity diminished with substantial doping because of the contraction of the tunnel space and ambushing of conduction electrons. The uniqueness of this study is in the high dielectric optimization of lead-free ceramic Cox:K2Ti6O13 and the discovery of positive temperature coefficients of the resistivity of these ceramic samples.
Musculoskeletal Chronic Graft versus Host Disease—A Rare Complication to Allogeneic Hematopoietic Stem Cell Transplant: A Case-Based Report and Review of the Literature
Authors: Kvinge Alexander Dåtland , Kvammen Tobias , Miletic Hrvoje , Bindoff Laurence Albert , Reikvam Håkon
Published: November 2022

Musculoskeletal graft versus host disease (GVHD) is a rare manifestation of chronic GVHD (cGVHD) following allogeneic hematopoietic stem cell transplantation (allo-HSCT). Left untreated, the disease can cause extensive damage to muscle tissue and joints. We describe a 62-year-old male with musculoskeletal GVHD and generalized muscle pain and stiffness. In addition, we performed a systemic literature review based on published cases of musculoskeletal GVHD between 1983 and 2019. We identified 85 cases, 62% male and 38% female with an age of 4–69 years and median age of 39 years at diagnosis. The majority of patients (72%) also had manifestations of cGVHD in at least one other organ system, most frequently the skin (52%), followed by oropharyngeal mucosa (37%), and pulmonary and gastrointestinal tract (GI tract) (21%). We conclude that, while musculoskeletal cGVHD is a rare complication of allo-HSCT, it remains a serious and debilitating risk that must be considered in patients with muscle pain, muscle weakness, joint stiffness, and tissue inflammation. Early intervention is critical for the patient’s prognosis.
Diversity of Avian Species in Peri-Urban Landscapes Surrounding Fez in Morocco: Species Richness, Breeding Populations, and Evaluation of Menacing Factors
Authors: Squalli Wafae , Mansouri Ismail , Douini Ikram , Achiban Hamid , Fadil Fatima , Dakki Mohamed , Wink Michael
Published: November 2022

In this study, we investigated the avian diversity and threatening factors in five peri-urban sites around Fez city (Morocco) for 2 years (2018–2019). The study hosted 131 avian species, including 64.88% breeding species, 19.84% migrant winterers, and 11.45% migrant breeders. Five species of conservation concern such as the vulnerable European turtle dove and the European goldfinch, the near-threatened ferruginous duck and bar-tailed godwit, and the endangered white-headed duck were recorded. Most bird species were recorded at the Oued Fez River (26.89%) and the El Mehraz dam (25%), followed by the El Gaada dam (17.4%), the Ain Bida garbage dump (15.5%), and the Ain Chkef Forest (15.18%). About 44.44% of the breeding species were found at Oued Fez, along with 33.33% at the El Mehraz dam, while El Gâada, Ain Chkef, and Ain Bida hosted only 7.40% of species. An important breeding population of the endangered white-headed duck was recorded at El Mehraz and Oued Fez. The extension of farmlands, urbanization, touristic activities, and drought constitute the most menacing factors for the avian diversity and their habitats in Fez.
First Predation Record of a Tarantula (Euathlus sp., Theraphosidae) on a Juvenile Austral Thrush (Turdus falcklandii, Turdidae) in Central Chile
Authors: Montenegro Rubén , Cotoras Darko D.
Published: November 2022

We describe the first predation record of an undescribed adult male tarantula from the genus Euathlus in a juvenile austral thrush (Turdus falcklandii Quoy and Gaimard, 1824) (Aves: Turdidae) in central Chile. The precise moment of predation was not observed; it could have been an opportunistic event or active hunting. In support of the later alternative, this undescribed species of Euathlus has been relatively frequently seen walking on tree trunks. These incidental observations raise the question of how important Euathlus is as a predator of juvenile birds.
Arabic Twitter Conversation Dataset about the COVID-19 Vaccine
Authors: Alhazmi Huda
Published: November 2022

The development and rollout of COVID-19 vaccination around the world offers hope for controlling the pandemic. People turned to social media such as Twitter seeking information or to voice their opinion. Therefore, mining such conversation can provide a rich source of data for different applications related to the COVID-19 vaccine. In this data article, we developed an Arabic Twitter dataset of 1.1 M Arabic posts regarding the COVID-19 vaccine. The dataset was streamed over one year, covering the period from January to December 2021. We considered a set of crawling keywords in the Arabic language related to the conversation about the vaccine. The dataset consists of seven databases that can be analyzed separately or merged for further analysis. The initial analysis depicts the embedded features within the posts, including hashtags, media, and the dynamic of replies and retweets. Further, the textual analysis reveals the most frequent words that can capture the trends of the discussions. The dataset was designed to facilitate research across different fields, such as social network analysis, information retrieval, health informatics, and social science.
Does a Caesarean Section Scar Affect Placental Volume, Vascularity and Localization?
Authors: Bokučava Diana , Ķīvīte-Urtāne Anda , Domaševs Pavels , Lūse Laura , Vedmedovska Natālija , Donders Gilbert G. G.
Published: November 2022

Caesarean section is associated with an increased risk of abnormal placental implantation and adverse pregnancy outcomes in subsequent pregnancies. Besides the placenta accrete spectrum, only a few of the previous studies focused on other placental development alterations in the scarred uterus. We assessed placental development deviations in the uterus with a Caesarean section scar by evaluating placental volume (PV) and vascular flow indexes. From 1 January 2021 until 31 March 2022, placental volumes and vascularization indexes (VI, FI, VFI) were prospectively measured by 3D power Doppler and VOCAL techniques in 221 patients attending the first trimester screening program. We also calculated the placental quotient to standardize PV to the gestational age. No statistically significant differences in the values of placental volume, placental quotient and placental vascularization indexes were detected between women with previous Caesarean section delivery or women with vaginal delivery. FI was significantly lower in nulliparous in the first trimester. The results of our study suggest that 3D placental evaluation was not able to detect placental development alteration in the uterus with a Caesarean section scar. Future research needs to verify whether 3D power Doppler and Vocal techniques can provide more information if used in an earlier gestational age.
Predicting Progression of Kidney Injury Based on Elastography Ultrasound and Radiomics Signatures
Authors: Zhu Minyan , Tang Lumin , Yang Wenqi , Xu Yao , Che Xiajing , Zhou Yin , Shao Xinghua , Zhou Wenyan , Zhang Minfang , Li Guanghan , Zheng Min , Wang Qin , Li Hongli , Mou Shan
Published: November 2022

Background: Shear wave elastography ultrasound (SWE) is an emerging non-invasive candidate for assessing kidney stiffness. However, its prognostic value regarding kidney injury is unclear. Methods: A prospective cohort was created from kidney biopsy patients in our hospital from May 2019 to June 2020. The primary outcome was the initiation of renal replacement therapy or death, while the secondary outcome was eGFR < 60 mL/min/1.73 m2. Ultrasound, biochemical, and biopsy examinations were performed on the same day. Radiomics signatures were extracted from the SWE images. Results: In total, 187 patients were included and followed up for 24.57 ± 5.52 months. The median SWE value of the left kidney cortex (L_C_median) is an independent risk factor for kidney prognosis for stage 3 or over (HR 0.890 (0.796–0.994), p < 0.05). The inclusion of 9 out of 2511 extracted radiomics signatures improved the prognostic performance of the Cox regression models containing the SWE and the traditional index (chi-square test, p < 0.001). The traditional Cox regression model had a c-index of 0.9051 (0.8460–0.9196), which was no worse than the machine learning models, Support Vector Machine (SVM), SurvivalTree, Random survival forest (RSF), Coxboost, and Deepsurv. Conclusions: SWE can predict kidney injury progression with an improved performance by radiomics and Cox regression modeling.
Automated Artificial Intelligence-Based Assessment of Lower Limb Alignment Validated on Weight-Bearing Pre- and Postoperative Full-Leg Radiographs
Authors: Erne Felix , Grover Priyanka , Dreischarf Marcel , Reumann Marie K. , Saul Dominik , Histing Tina , Nüssler Andreas K. , Springer Fabian , Scholl Carolin
Published: November 2022

The assessment of the knee alignment using standing weight-bearing full-leg radiographs (FLR) is a standardized method. Determining the load-bearing axis of the leg requires time-consuming manual measurements. The aim of this study is to develop and validate a novel algorithm based on artificial intelligence (AI) for the automated assessment of lower limb alignment. In the first stage, a customized mask-RCNN model was trained to automatically detect and segment anatomical structures and implants in FLR. In the second stage, four region-specific neural network models (adaptations of UNet) were trained to automatically place anatomical landmarks. In the final stage, this information was used to automatically determine five key lower limb alignment angles. For the validation dataset, weight-bearing, antero-posterior FLR were captured preoperatively and 3 months postoperatively. Preoperative images were measured by the operating orthopedic surgeon and an independent physician. Postoperative images were measured by the second rater only. The final validation dataset consisted of 95 preoperative and 105 postoperative FLR. The detection rate for the different angles ranged between 92.4% and 98.9%. Human vs. human inter-(ICCs: 0.85–0.99) and intra-rater (ICCs: 0.95–1.0) reliability analysis achieved significant agreement. The ICC-values of human vs. AI inter-rater reliability analysis ranged between 0.8 and 1.0 preoperatively and between 0.83 and 0.99 postoperatively (all p < 0.001). An independent and external validation of the proposed algorithm on pre- and postoperative FLR, with excellent reliability for human measurements, could be demonstrated. Hence, the algorithm might allow for the objective and time saving analysis of large datasets and support physicians in daily routine.
Airway Obstruction in Primary Care Patients: Need for Implementing Spirometry Use
Authors: Bucchieri Salvatore , Alfano Pietro , Audino Palma , Fazio Giovanni , Marcantonio Salvatore ,   Snamid Palermo Cooperative Group, Cuttitta Giuseppina
Published: November 2022

(1) Background: To detect early airway obstruction in an adult primary care setting. (2) Methods: Seventeen general practitioners (GP) were involved. A total of 912 patients consulting their GPs over 40 years were recruited: 583 of them (323M) agreed to perform/undergo all the procedures: respiratory questionnaire, mMRC questionnaire, and spirometry. We identified four subgroups: physician COPD patients; physician asthma patients; asthma-COPD overlap syndrome patients; and no respiratory diagnosis subjects, on the basis of physician diagnosis. For screening purposes, an FEV1/FVC < 70% was considered a marker of airway obstruction (AO). (3) Results: Prevalence rates of COPD, A, and ACOS were 12.5%, 7.8%, and 3.6%, respectively. In the overall sample 16.3% showed airway obstruction: 26% mild, 56% moderate, 17% severe, and 1% very severe. In obstructed subjects, those reporting neither respiratory symptoms nor a physician’s respiratory diagnosis were 60% level I; 43% level II; 44% level III; and none level IV. Wheezing (p < 0.001), sputum (p = 0.01), older age (p < 0.0001), and male gender (p = 0.002) were the best predictors of airway obstruction. (4) Conclusions: A high prevalence of AO was found. In AO we found a high prevalence of subjects without respiratory symptoms or respiratory chronic diagnosis. Airway obstruction was predicted by the presence of wheezing, sputum, older age, and male gender.
Scoping Review on the Multimodal Classification of Depression and Experimental Study on Existing Multimodal Models
Authors: Arioz Umut , Smrke Urška , Plohl Nejc , Mlakar Izidor
Published: November 2022

Depression is a prevalent comorbidity in patients with severe physical disorders, such as cancer, stroke, and coronary diseases. Although it can significantly impact the course of the primary disease, the signs of depression are often underestimated and overlooked. The aim of this paper was to review algorithms for the automatic, uniform, and multimodal classification of signs of depression from human conversations and to evaluate their accuracy. For the scoping review, the PRISMA guidelines for scoping reviews were followed. In the scoping review, the search yielded 1095 papers, out of which 20 papers (8.26%) included more than two modalities, and 3 of those papers provided codes. Within the scope of this review, supported vector machine (SVM), random forest (RF), and long short-term memory network (LSTM; with gated and non-gated recurrent units) models, as well as different combinations of features, were identified as the most widely researched techniques. We tested the models using the DAIC-WOZ dataset (original training dataset) and using the SymptomMedia dataset to further assess their reliability and dependency on the nature of the training datasets. The best performance was obtained by the LSTM with gated recurrent units (F1-score of 0.64 for the DAIC-WOZ dataset). However, with a drop to an F1-score of 0.56 for the SymptomMedia dataset, the method also appears to be the most data-dependent.
Solitary Extrapleural Fibrous Tumor in Salivary Glands: Our Experience—Case Series and Literature Review
Authors: Boschetti Ciro Emiliano , Vitagliano Rita , Imola Gianmaria , Cornacchini Nicola , Colella Maria Luisa , Tartaro Gianpaolo , Colella Giuseppe
Published: November 2022

(1) Background: Extrapleural solitary fibrous tumors (ESFTs) are rare oncological entities occurring in the head and neck, and even more so in the salivary glands. The clinical presentation and histologic features are usually unspecific, resulting in frequent misclassification. As an unusual tumor, ESTFs have an unpredictable clinical behavior. (2) Methods: We present two clinical cases referred to our Maxillofacial Surgery Unit for the onset of a symptomless mass involving, in one case, the parotid gland, and in the other case, the sublingual gland. (3) Results: Solitary fibrous tumors could be considered as neoplasms with intermediate biological behavior that are not entirely predictable on the basis of morphological features, as these are mostly still unknown. However, a few histologic, immunohistochemical, and imaging features, such as a hypodense signal at the T1 sequence in an MRI, or positivity for CD34, bcl2, and CD99, and the NAB2-STATS6 fusion gene, could be useful for an early differential diagnosis of ESTFs. (4) Conclusions: All patients were alive at follow-up with no evidence of disease. Surgical management should always be considered as the first choice for oncological radicality, and clinical behavior should always be defined with the help of the study of radiological and anatomopathological features.
The Effectiveness of Manual Therapy in the Cervical Spine and Diaphragm, in Combination with Breathing Reeducation Exercises, in Patients with Non-Specific Chronic Neck Pain: Protocol for Development of Outcome Measures and a Randomized Controlled Trial
Authors: Tatsios Petros I. , Grammatopoulou Eirini , Dimitriadis Zacharias , Koumantakis George A.
Published: November 2022

Until now, non-specific chronic neck pain has mainly been considered as a musculoskeletal system dysfunction, with associated psychological involvement due to its prolonged or recurrent nature. However, patients with non-specific chronic neck pain frequently additionally exhibit respiratory dysfunction. Emerging evidence suggests that addressing the respiratory dysfunction in these patients will provide additional therapeutic benefits in musculoskeletal and respiratory-related outcomes for several reasons (biomechanical, biochemical, and psychological). Motor control dysfunction of the muscles surrounding the spine (diaphragm included) negatively affects the mechanics and biochemistry of breathing (pH-homeostasis). An impaired and ineffective breathing pattern has been recognized as the primary source of many unexplained symptoms (anxiety, depression, confusion, chest pain, hypocapnia, and breathlessness) in patients with non-specific chronic neck pain. The proposed protocol’s purpose is dual: to assess the relative effectiveness of manual therapy in the cervical spine and the diaphragm, in combination with breathing reeducation exercises, along with cervical spine manual therapy or usual physical therapy care on the underlying dysfunctions in patients with non-specific chronic neck pain via a randomized controlled clinical trial, and to validate part of the outcome measures. Several musculoskeletal and respiratory dysfunction outcomes will be employed to delimit the initial extent and level of dysfunction and its resolution with the treatments under study.
Relationship between Children’s and Parents’ Dental Anxiety: A Cross-Sectional Study on the Six European Countries
Authors: Šimunović Luka , Špiljak Bruno , Radulović Milica , Vlahovljak Adna , Ostojić Mihailo , Krlev Jovan , Ibrahimpašić Amina , Vranić Lara , Negovetić Vranić Dubravka
Published: November 2022

Background: The purpose of this study is to investigate the relationship between children’s and parents’ dental anxiety. Methods: 731 children of different ages and their parents from six European countries participated in this study. Dental anxiety was investigated through an online questionnaire, which consisted of general questions and the Corah Dental Anxiety Scale (CDAS), which is a questionnaire that measures respondents’ reactions on a 5-point scale for four different situations. Results: CDAS results were calculated for all children and their parents. A total of 12.5% of children from Croatia, 26.67% from Macedonia, 10.94% from Bosnia and Herzegovina, 20.31% from Montenegro, 23.08% from Slovenia and 16.10% from Serbia showed a high level of anxiety. The correlation between dental anxiety of parents and children was 0.4 (p < 0.01). Conclusions: Parents with negative experience from a dental office can have a bad effect on their child’s behaviour, which results in the creation of a non-active patient. Due to the clear and existing cause-and-effect relationship of dental anxiety in children and parents, it is extremely important to educate parents about the proper psychological approach to children in order to promote positive experiences from dental offices, as well as to emphasize the importance of regular visits to the dentist.
Towards Resilient UAV Swarms—A Breakdown of Resiliency Requirements in UAV Swarms
Authors: Phadke Abhishek , Medrano F. Antonio
Published: November 2022

UAVs have rapidly become prevalent in applications related to surveillance, military operations, and disaster relief. Their low cost, operational flexibility, and unmanned capabilities make them ideal for accomplishing tasks in areas deemed dangerous for humans to enter. They can also accomplish previous high-cost and labor-intensive tasks, such as land surveying, in a faster and cheaper manner. Researchers studying UAV applications have realized that a swarm of UAVs working collaboratively on tasks can achieve better results. The dynamic work environment of UAVs makes controlling the vehicles a challenge. This is magnified by using multiple agents in a swarm. Resiliency is a broad concept that effectively defines how well a system handles disruptions in its normal functioning. The task of building resilient swarms has been attempted by researchers for the past decade. However, research on current trends shows gaps in swarm designs that make evaluating the resiliency of such swarms less than ideal. The authors believe that a complete well-defined system built from the ground up is the solution. This survey evaluates existing literature on resilient multi-UAV systems and lays down the groundwork for how best to develop a truly resilient system.
User Identity Linkage across Social Networks with the Enhancement of Knowledge Graph and Time Decay Function
Authors: Gao Hao , Wang Yongqing , Shao Jiangli , Shen Huawei , Cheng Xueqi
Published: November 2022

Users participate in multiple social networks for different services. User identity linkage aims to predict whether users across different social networks refer to the same person, and it has received significant attention for downstream tasks such as recommendation and user profiling. Recently, researchers proposed measuring the relevance of user-generated content to predict identity linkages of users. However, there are two challenging problems with existing content-based methods: first, barely considering the word similarities of texts is insufficient where the semantical correlations of named entities in the texts are ignored; second, most methods use time discretization technology, where the texts are divided into different time slices, resulting in failure of relevance modeling. To address these issues, we propose a user identity linkage model with the enhancement of a knowledge graph and continuous time decay functions that are designed for mitigating the influence of time discretization. Apart from modeling the correlations of the words, we extract the named entities in the texts and link them into the knowledge graph to capture the correlations of named entities. The semantics of texts are enhanced through the external knowledge of the named entities in the knowledge graph, and the similarity discrimination of the texts is also improved. Furthermore, we propose continuous time decay functions to capture the closeness of the posting time of texts instead of time discretization to avoid the matching error of texts. We conduct experiments on two real public datasets, and the experimental results show that the proposed method outperforms state-of-the-art methods.
Administration Methods of Mesenchymal Stem Cells in the Treatment of Burn Wounds
Authors: Jenssen Astrid Bjørke , Mohamed-Ahmed Samih , Kankuri Esko , Brekke Ragnvald Ljones , Guttormsen Anne Berit , Gjertsen Bjørn Tore , Mustafa Kamal , Almeland Stian Kreken
Published: November 2022

Cellular therapies for burn wound healing, including the administration of mesenchymal stem or stromal cells (MSCs), have shown promising results. This review aims to provide an overview of the current administration methods in preclinical and clinical studies of bone-marrow-, adipose-tissue-, and umbilical-cord-derived MSCs for treating burn wounds. Relevant studies were identified through a literature search in PubMed and Embase and subjected to inclusion and exclusion criteria for eligibility. Additional relevant studies were identified through a manual search of reference lists. A total of sixty-nine studies were included in this review. Of the included studies, only five had clinical data from patients, one was a prospective case–control, three were case reports, and one was a case series. Administration methods used were local injection (41% in preclinical and 40% in clinical studies), cell-seeded scaffolds (35% and 20%), topical application (17% and 60%), and systemic injection (1% and 0%). There was great heterogeneity between the studies regarding experimental models, administration methods, and cell dosages. Local injection was the most common administration method in animal studies, while topical application was used in most clinical reports. The best delivery method of MSCs in burn wounds is yet to be identified. Although the potential of MSC treatment for burn wounds is promising, future research should focus on examining the effect and scalability of such therapy in clinical trials.
Net Transmitter of Stock Market Volatility and Safe Haven for Portfolio Investors in the Asian Dragons
Authors: Lee Cheng-Wen , Chen Shu-Hui , Huruta Andrian Dolfriandra , Dewi Christine , Chen Abbott Po Shun
Published: November 2022

The return and volatility spillover effects on Asian Dragons were investigated in this study. Yahoo Finance provided the monthly statistics (from August 1997 to December 2020). This study used a generalized autoregressive conditional heteroskedasticity–autoregressive moving average (GARCH–ARMA) model. The results showed that return spillover effects were observed in unidirectional relationships, but volatility spillover effects were shown in both unidirectional and bidirectional connections. The TSEC Weighted Index (TWII) and the Hang Seng Index (HSI) were net stock market return transmitters to other markets, whereas the Straits Times Index (STI) and the Korean Composite Stock Price Indices (KOSPI) were net receivers. Simultaneously, the STI was a significant net transmitter of stock market volatility to other markets, according to research. As a result, the KOSPI has become a safe haven for portfolio investors. Portfolio managers and overseas investors who are reviewing investment and asset allocation decisions should be aware of these facts.
A Review of the Gate-All-Around Nanosheet FET Process Opportunities
Authors: Mukesh Sagarika , Zhang Jingyun
Published: November 2022

In this paper, the innovations in device design of the gate-all-around (GAA) nanosheet FET are reviewed. These innovations span enablement of multiple threshold voltages and bottom dielectric isolation in addition to impact of channel geometry on the overall device performance. Current scaling challenges for GAA nanosheet FETs are reviewed and discussed. Finally, an analysis of future innovations required to continue scaling nanosheet FETs and future technologies is discussed.
A 3.2 GHz Injection-Locked Ring Oscillator-Based Phase-Locked-Loop for Clock Recovery
Authors: Vert Dorian , Pignol Michel , Lebre Vincent , Moutaye Emmanuel , Malou Florence , Begueret Jean-Baptiste
Published: November 2022

An injection-locked ring oscillator-based phase-locked-loop targeting clock recovery for space application at 3.2 GHz is presented here. Most clock recovery circuits need a very low phase noise and jitter performance and are thus based on LC-type oscillators. These excellent performances come at the expense of a very poor integration density. To alleviate this issue, this work introduces an injection-locked ring oscillator-based PLL circuit. The combination of the injection-locking process with the use of ring oscillators allows for the benefit of excellent jitter performance while presenting an extremely low surface area due to an architecture without any inductor. The injection locking principle is addressed, and evidence of its phase noise and jitter improvements are confirmed through measurement results. Indeed, phase noise and jitter enhancements up to 43 dB and 23.3 mUI, respectively, were measured. As intended, this work shows the best integration density compared to recent similar state-of-the-art studies. The whole architecture measures 0.1 mm2 while consuming 34.6 mW in a low-cost 180 nm CMOS technology.
Genetic Algorithm for the Optimization of a Building Power Consumption Prediction Model
Authors: Oh Seungmin , Yoon Junchul , Choi Yoona , Jung Young-Ae , Kim Jinsul
Published: November 2022

Accurately predicting power consumption is essential to ensure a safe power supply. Various technologies have been studied to predict power consumption, but the prediction of power consumption using deep learning models has been quite successful. However, in order to predict power consumption by utilizing deep learning models, it is necessary to find an appropriate set of hyper-parameters. This introduces the problem of complexity and wide search areas. The power consumption field should be accurately predicted in various distributed areas. To this end, a customized consumption prediction deep learning model is needed, which is essential for optimizing the hyper-parameters that are suitable for the environment. However, typical deep learning model users lack the knowledge needed to find the optimal values of parameters. To solve this problem, we propose a method for finding the optimal values of parameters for learning. In addition, the layer parameters of deep learning models are optimized by applying genetic algorithms. In this paper, we propose a hyper-parameter optimization method that solves the time and cost problems that depend on existing methods or experiences. We derive a hyper-parameter optimization plan that solves the existing method or experience-dependent time and cost problems. As a result, the RNN model achieved a 30% and 21% better mean squared error and mean absolute error, respectively, than did the arbitrary deep learning model, and the LSTM model was able to achieve 9% and 5% higher performance.
Kernel Density Estimation and Convolutional Neural Networks for the Recognition of Multi-Font Numbered Musical Notation
Authors: Wang Qi , Zhou Li , Chen Xin
Published: November 2022

Optical music recognition (OMR) refers to converting musical scores into digitized information using electronics. In recent years, few types of OMR research have involved numbered musical notation (NMN). The existing NMN recognition algorithm is difficult to deal with because the numbered notation font is changing. In this paper, we made a multi-font NMN dataset. Using the presented dataset, we use kernel density estimation with proposed bar line criteria to measure the relative height of symbols, and an accurate separation of melody lines and lyrics lines in musical notation is achieved. Furthermore, we develop a structurally improved convolutional neural network (CNN) to classify the symbols in melody lines. The proposed neural network performs hierarchical processing of melody lines according to the symbol arrangement rules of NMN and contains three parallel small CNNs called Arcnet, Notenet and Linenet. Each of them adds a spatial pyramid pooling layer to adapt to the diversity of symbol sizes and styles. The experimental results show that our algorithm can accurately detect melody lines. Taking the average accuracy rate of identifying various symbols as the recognition rate, the improved neural networks reach a recognition rate of 95.5%, which is 8.5% higher than the traditional convolutional neural networks. Through audio comparison and evaluation experiments, we find that the generated audio maintains a high similarity to the original audio of the NMN.
Academic Use of Rapid Prototyping in Digitally Controlled Power Factor Correctors
Authors: Lamo Paula , Azcondo Francisco J. , Pigazo Alberto
Published: November 2022

The growing use of power converters connected to the grid motivates their study in power electronics courses and the prototype development in the degree final project (DFP). However, the practical realization of using state-of-the-art components and conversion techniques is complex due to the numerous multidisciplinary aspects that students must consider in its design and development and the workload associated with the DFP. An example of this is that, unlike a conventional power factor correction (PFC) design, the individual dedication of students to complete the design and validation of modern bridgeless PFC stages exceeds the number of credits of the DFP. The reason for this is that it includes system modeling, becoming familiar with the devices used, discrete selection, circuit design, control development, and programming, to build the converter and verify the operation of the complete system. To reinforce the individual skills needed for the DFP and reduce this time, a novel strategy is proposed. It allows the student to focus their efforts on integrating the individual skills achieved in the degree at the appropriate competence level during the modeling and construction of the power converter while carrying out part of the tasks out of the lab, if necessary, as was the case during the pandemic restrictions. For this, the rapid prototyping technique is introduced to speed up the overall design and speed up the tuning of digital controllers. This manuscript presents a teaching experience in which students build digitally controlled power converters using Texas Instruments microcontroller boards and PLECS®. The example of a bridgeless totem-pole power factor corrector is shown. Although it began to develop and was motivated due to the restrictions during the COVID-19 pandemic, the experience has been verified and is maintained over time, successfully consolidating.
The Incoherence of Deep Isotropic Neural Networks Increases Their Performance in Image Classification
Authors: Feng Wenfeng , Zhang Xin , Song Qiushuang , Sun Guoying
Published: November 2022

Although neural-network architectures are critical for their performance, how the structural characteristics of a neural network affect its performance has still not been fully explored. Here, we map architectures of neural networks to directed acyclic graphs (DAGs), and find that incoherence, a structural characteristic to measure the order of DAGs, is a good indicator for the performance of corresponding neural networks. Therefore, we propose a deep isotropic neural-network architecture by folding a chain of the same blocks and then connecting the blocks with skip connections at different distances. Our model, named FoldNet, has two distinguishing features compared with traditional residual neural networks. First, the distances between block pairs connected by skip connections increase from always equal to one to specially selected different values, which lead to more incoherent graphs and let the neural network explore larger receptive fields and, thus, enhance its multi-scale representation ability. Second, the number of direct paths increases from one to multiple, which leads to a larger proportion of shorter paths and, thus, improves the direct propagation of information throughout the entire network. Image-classification results on CIFAR-10 and Tiny ImageNet benchmarks suggested that our new network architecture performs better than traditional residual neural networks. FoldNet with 25.4M parameters can achieve 72.67% top-1 accuracy on the Tiny ImageNet after 100 epochs, which is competitive compared with the-state-of-art results on the Tiny ImageNet.
The Energy Consumption of Electric Scooters Used in the Polish Shared Mobility Market
Authors: Kubik Andrzej
Published: November 2022

The growing popularity of traveling with electric scooters in recent years is, on the one hand, a great opportunity to shift from the current forms of mobility to a new service among the public, but it is also a huge challenge for urban centers and operators. One of the main challenges related to electric scooters is the growing demand for high energy consumption, which is currently a big issue due to the growing interest in electromobility used in mobility as a service (MaaS) systems. However, in order to properly estimate the level of energy consumption of scooters, there is a real need for reliable scientific information on the actual electricity consumption of electric scooters used in shared mobility systems. An extensive literature analysis indicates the lack of research conducted in this area. Noting this research gap, studies were conducted to determine the factors influencing the energy consumption of an electric scooter. The study attempts to determine these values on the basis of the proposed research experiment. The scientific experiment was based on a three-factor plan; an experimental plan. The author conducted the research by driving and measuring electric scooters in order to compare the actual consumption with the data provided by vehicle manufacturers. The result of the research was to determine the influence of factors that influence the significant energy consumption of electric scooters from shared mobility systems. Interestingly, the results generated show that the electricity requirements for six scooters corresponded to one electric car. This proposal raises the question of whether scooters are the best form of electric mobility for the environment. In addition, the work also includes guidelines for scooter users and recommendations for shared mobility operators on the energy consumption of electric scooters.
Approximating Shading Ratio Using the Total-Sky Imaging System: An Application for Photovoltaic Systems
Authors: Dhimish Mahmoud , Lazaridis Pavlos I.
Published: November 2022

In recent years, a determined shading ratio of photovoltaic (PV) systems has been broadly reviewed and explained. Observing the shading ratio of PV systems allows us to navigate for PV faults and helps to recognize possible degradation mechanisms. Therefore, this work introduces a novel approximation shading ratio technique using an all-sky imaging system. The proposed solution has the following structure: (i) we determined four all-sky imagers for a region of 25 km2, (ii) computed the cloud images using our new proposed model, called color-adjusted (CA), (iii) computed the shading ratio, and (iv) estimated the global horizontal irradiance (GHI) and consequently, obtained the predicted output power of the PV system. The estimation of the GHI was empirically compared with captured data from two different weather stations; we found that the average accuracy of the proposed technique was within a maximum ±12.7% error rate. In addition, the PV output power approximation accuracy was as high as 97.5% when the shading was zero and reduced to the lowest value of 83% when overcasting conditions affected the examined PV system.