bluuebunny/crossref_metadata_2025 huggingface dataset:
The Ornamented Shell of a New Bothremydid Turtle from the Uppermost Cretaceous of Niger
Authors: Pérez-García Adán
Published: March 2023

A new pleurodiran turtle is described here. It is identified as attributable to Bothremydidae. The new taxon comes from an upper Maastrichtian (Upper Cretaceous) outcrop located in Southwestern Niger (in the Indamane Mount area, belonging to the Abalak Department of the Tahoua Region). Abalakemys chapmanae gen. et sp. nov. is identified by an almost complete large shell of about 65 cm in length. The new bothremydid turtle is recognized as a member of Bothremydodda, showing several autapomorphies (an exclusive ornamental pattern on the plate’s outer surface, covered by small depressions; small fourth pleural scutes, only anteromedially reaching the sixth pair of costal plates; and noticeably wedged posterior plastral lobe toward the posterior region), as well as a unique combination of characters for this clade. This turtle could belong to Nigeremydini, a poorly understood Maastrichtian to Paleocene lineage of Bothremydodda, which integrates large coastal taxa that inhabited the African Trans-Saharan seaway, and for which shell information is currently extremely limited.
Home Comfort Dataset: Acquired from SGH
Authors: Santos Mariana , Antunes Mário , Gomes Diogo , Aguiar Rui L.
Published: March 2023

In this work, we share the dataset collected during the Smart Green Homes (SGH) project. The project’s goal was to develop integrated products and technology solutions for households, as well as to improve the standards of comfort and user satisfaction. This was to be achieved while improving household energy efficiency and reducing the usage of gaseous pollutants, in response to the planet’s sustainability issues. One of the tasks executed within the project was the collection of data from volunteers’ homes, including environmental information and the level of comfort as perceived by the volunteers themselves. While used in the original project, the resulting dataset contains valuable information that could not be explored at the time. We now share this dataset with the community, which can be used for various scenarios. These may include heating appliance optimisation, presence detection and environmental prediction.
Testing System for PV Grid-Connected Power Condition Systems with Support for Ancillary Services
Authors: Pires Vitor , Cordeiro Armando , Foito Daniel , Martins João , Pires Armando , Chen Hao
Published: March 2023

Due to the high spread of photovoltaic (PV) systems in the low voltage distribution grids there is a substantial number of requirements for the connection of these systems. Therefore, several tests should be performed before the integration of the PV systems into the grid. Moreover, new requirements have been established that are most likely to be implemented in the near future. To provide these tests and verify if PV systems are in accordance with requirements and recommendations, a testing setup for the PV systems was developed. This testing system consists of a controllable power source prepared to receive energy and to inject it into the grid. In fact, that system imposes a controllable voltage, in amplitude and frequency, to the PV system to simulate the perturbations of the grid. Since the system under test must inject energy in accordance with the standards’ specifications, then the controllable power source that emulates the grid must receive that energy. Moreover, it should also be prepared for PV systems that are able to provide ancillary services, including new ones that support imbalanced networks. A fast and robust control system will be used for this controllable power source. Several experimental tests from the developed prototype are presented.
Self-Regulating Adaptive Controller for Oxygen Support to Severe Respiratory Distress Patients and Human Respiratory System Modeling
Authors: Naskar Indrajit , Pal Arabinda Kumar , Jana Nandan Kumar
Published: March 2023

Uncontrolled breathing is the most critical and challenging situation for a healthcare person to patients. It may be due to simple cough/cold/critical disease to severe respiratory infection of the patients and resulting directly impacts the lungs and damages the alveoli which leads to shortness of breath and also impairs the oxygen exchange. The prolonged respiratory failure in such patients may cause death. In this condition, supportive care of the patients by medicine and a controlled oxygen supply is only the emergency treatment. In this paper, as a part of emergency support, the intelligent set-point modulated fuzzy PI-based model reference adaptive controller (SFPIMRAC) is delineated to control the oxygen supply to uncomforted breathing or respiratory infected patients. The effectiveness of the model reference adaptive controller (MRAC) is enhanced by assimilating the worthiness of fuzzy-based tuning and set-point modulation strategies. Since then, different conventional and intelligent controllers have attempted to regulate the supply of oxygen to respiratory distress patients. To overcome the limitations of previous techniques, researchers created the set-point modulated fuzzy PI-based model reference adaptive controller, which can react instantly to changes in oxygen demand in patients. Nonlinear mathematical formulations of the respiratory system and the exchange of oxygen with time delay are modeled and simulated for study. The efficacy of the proposed SFPIMRAC is tested, with transport delay and set-point variations in the devised respiratory model.
Enhancing the Reliability of Intraoperative Ultrasound in Pediatric Space-Occupying Brain Lesions
Authors: Frassanito Paolo , Stifano Vito , Bianchi Federico , Tamburrini Gianpiero , Massimi Luca
Published: March 2023

Introduction: Intraoperative ultrasound (IOUS) may aid the resection of space-occupying brain lesions, though technical limits may hinder its reliability. Methods: IOUS (MyLabTwice®, Esaote, Italy) with a microconvex probe was utilized in 45 consecutive cases of children with supratentorial space-occupying lesions aiming to localize the lesion (pre-IOUS) and evaluate the extent of resection (EOR, post-IOUS). Technical limits were carefully assessed, and strategies to enhance the reliability of real-time imaging were accordingly proposed. Results: Pre-IOUS allowed us to localize the lesion accurately in all of the cases (16 low-grade gliomas, 12 high-grade gliomas, eight gangliogliomas, seven dysembryoplastic neuroepithelial tumors, five cavernomas, and five other lesions, namely two focal cortical dysplasias, one meningioma, one subependymal giant cell astrocytoma, and one histiocytosis). In 10 deeply located lesions, IOUS with hyperechoic marker, eventually coupled with neuronavigation, was useful to plan the surgical route. In seven cases, the administration of contrast ensured a better definition of the vascular pattern of the tumor. Post-IOUS allowed the evaluation of EOR reliably in small lesions (<2 cm). In large lesions (>2 cm) assessing EOR is hindered by the collapsed surgical cavity, especially when the ventricular system is opened, and by artifacts that may simulate or hide residual tumors. The main strategies to overcome the former limit are inflation of the surgical cavity through pressure irrigation while insonating, and closure of the ventricular opening with Gelfoam before insonating. The strategies to overcome the latter are avoiding the use of hemostatic agents before IOUS and insonating through normal adjacent brain instead of corticotomy. These technical nuances enhanced the reliability of post-IOUS, with a total concordance to postoperative MRI. Indeed, the surgical plan was changed in about 30% of cases, as IOUS showed a residual tumor that was left behind. Conclusion: IOUS ensures reliable real-time imaging in the surgery of space-occupying brain lesions. Limits may be overcome with technical nuances and proper training.
A Bimodal Emotion Recognition Approach through the Fusion of Electroencephalography and Facial Sequences
Authors: Muhammad Farah , Hussain Muhammad , Aboalsamh Hatim
Published: March 2023

In recent years, human–computer interaction (HCI) systems have become increasingly popular. Some of these systems demand particular approaches for discriminating actual emotions through the use of better multimodal methods. In this work, a deep canonical correlation analysis (DCCA) based multimodal emotion recognition method is presented through the fusion of electroencephalography (EEG) and facial video clips. A two-stage framework is implemented, where the first stage extracts relevant features for emotion recognition using a single modality, while the second stage merges the highly correlated features from the two modalities and performs classification. Convolutional neural network (CNN) based Resnet50 and 1D-CNN (1-Dimensional CNN) have been utilized to extract features from facial video clips and EEG modalities, respectively. A DCCA-based approach was used to fuse highly correlated features, and three basic human emotion categories (happy, neutral, and sad) were classified using the SoftMax classifier. The proposed approach was investigated based on the publicly available datasets called MAHNOB-HCI and DEAP. Experimental results revealed an average accuracy of 93.86% and 91.54% on the MAHNOB-HCI and DEAP datasets, respectively. The competitiveness of the proposed framework and the justification for exclusivity in achieving this accuracy were evaluated by comparison with existing work.
[18F]FDG PET/CT in the Evaluation of Melanoma Patients Treated with Immunotherapy
Authors: Mangas Losada María , Romero Robles Leonardo , Mendoza Melero Alejandro , García Megías Irene , Villanueva Torres Amós , Garrastachu Zumarán Puy , Boulvard Chollet Xavier , Lopci Egesta , Ramírez Lasanta Rafael , Delgado Bolton Roberto C.
Published: March 2023

Immunotherapy is based on manipulation of the immune system in order to act against tumour cells, with growing evidence especially in melanoma patients. The challenges faced by this new therapeutic tool are (i) finding valid evaluation criteria for response assessment; (ii) knowing and distinguishing between “atypical” response patterns; (iii) using PET biomarkers as predictive and response evaluation parameters and (iv) diagnosis and management of immunorelated adverse effects. This review is focused on melanoma patients analysing (a) the role of [18F]FDG PET/CT in the mentioned challenges; (b) the evidence of its efficacy. For this purpose, we performed a review of the literature, including original and review articles. In summary, although there are no clearly established or globally accepted criteria, modified response criteria are potentially appropriate for evaluation of immunotherapy benefit. In this context, [18F]FDG PET/CT biomarkers appear to be promising parameters in prediction and assessment of response to immunotherapy. Moreover, immunorelated adverse effects are recognized as predictors of early response to immunotherapy and may be associated with better prognosis and clinical benefit.
Fatty Acid Profile and Genetic Variants of Proteins Involved in Fatty Acid Metabolism Could Be Considered as Disease Predictor
Authors: Chaaba Raja , Bouaziz Aicha , Ben Amor Asma , Mnif Wissem , Hammami Mohamed , Mehri Sounira
Published: March 2023

Circulating fatty acids (FA) have an endogenous or exogenous origin and are metabolized under the effect of many enzymes. They play crucial roles in many mechanisms: cell signaling, modulation of gene expression, etc., which leads to the hypothesis that their perturbation could be the cause of disease development. FA in erythrocytes and plasma rather than dietary FA could be used as a biomarker for many diseases. Cardiovascular disease was associated with elevated trans FA and decreased DHA and EPA. Increased arachidonic acid and decreased Docosahexaenoic Acids (DHA) were associated with Alzheimer’s disease. Low Arachidonic acid and DHA are associated with neonatal morbidities and mortality. Decreased saturated fatty acids (SFA), increased monounsaturated FA (MUFA) and polyunsaturated FA (PUFA) (C18:2 n-6 and C20:3 n-6) are associated with cancer. Additionally, genetic polymorphisms in genes coding for enzymes implicated in FA metabolism are associated with disease development. FA desaturase (FADS1 and FADS2) polymorphisms are associated with Alzheimer’s disease, Acute Coronary Syndrome, Autism spectrum disorder and obesity. Polymorphisms in FA elongase (ELOVL2) are associated with Alzheimer’s disease, Autism spectrum disorder and obesity. FA-binding protein polymorphism is associated with dyslipidemia, type 2 diabetes, metabolic syndrome, obesity, hypertension, non-alcoholic fatty liver disease, peripheral atherosclerosis combined with type 2 diabetes and polycystic ovary syndrome. Acetyl-coenzyme A carboxylase polymorphisms are associated with diabetes, obesity and diabetic nephropathy. FA profile and genetic variants of proteins implicated in FA metabolism could be considered as disease biomarkers and may help with the prevention and management of diseases.
Artificial Intelligence for Evaluation of Retinal Vasculopathy in Facioscapulohumeral Dystrophy Using OCT Angiography: A Case Series
Authors: Maceroni Martina , Monforte Mauro , Cariola Rossella , Falsini Benedetto , Rizzo Stanislao , Savastano Maria Cristina , Martelli Francesco , Ricci Enzo , Bortolani Sara , Tasca Giorgio , Minnella Angelo Maria
Published: March 2023

Facioscapulohumeral muscular dystrophy (FSHD) is a slowly progressive muscular dystrophy with a wide range of manifestations including retinal vasculopathy. This study aimed to analyse retinal vascular involvement in FSHD patients using fundus photographs and optical coherence tomography-angiography (OCT-A) scans, evaluated through artificial intelligence (AI). Thirty-three patients with a diagnosis of FSHD (mean age 50.4 ± 17.4 years) were retrospectively evaluated and neurological and ophthalmological data were collected. Increased tortuosity of the retinal arteries was qualitatively observed in 77% of the included eyes. The tortuosity index (TI), vessel density (VD), and foveal avascular zone (FAZ) area were calculated by processing OCT-A images through AI. The TI of the superficial capillary plexus (SCP) was increased (p < 0.001), while the TI of the deep capillary plexus (DCP) was decreased in FSHD patients in comparison to controls (p = 0.05). VD scores for both the SCP and the DCP results increased in FSHD patients (p = 0.0001 and p = 0.0004, respectively). With increasing age, VD and the total number of vascular branches showed a decrease (p = 0.008 and p < 0.001, respectively) in the SCP. A moderate correlation between VD and EcoRI fragment length was identified as well (r = 0.35, p = 0.048). For the DCP, a decreased FAZ area was found in FSHD patients in comparison to controls (t (53) = −6.89, p = 0.01). A better understanding of retinal vasculopathy through OCT-A can support some hypotheses on the disease pathogenesis and provide quantitative parameters potentially useful as disease biomarkers. In addition, our study validated the application of a complex toolchain of AI using both ImageJ and Matlab to OCT-A angiograms.
Mechanisms of Resistance to CDK4/6 Inhibitors and Predictive Biomarkers of Response in HR+/HER2-Metastatic Breast Cancer—A Review of the Literature
Authors: Stanciu Ioana-Miruna , Parosanu Andreea Ioana , Orlov-Slavu Cristina , Iaciu Ion Cristian , Popa Ana Maria , Olaru Cristina Mihaela , Pirlog Cristina Florina , Vrabie Radu Constantin , Nitipir Cornelia
Published: March 2023

The latest and newest discoveries for advanced and metastatic hormone receptor-positive (HR+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancer are the three cyclin-dependent kinases 4 and 6 inhibitors (CDK4/6i) in association with endocrine therapy (ET). However, even if this treatment revolutionized the world and continued to be the first-line treatment choice for these patients, it also has its limitations, caused by de novo or acquired drug resistance which leads to inevitable progression after some time. Thus, an understanding of the overview of the targeted therapy which represents the gold therapy for this subtype of cancer is essential. The full potential of CDK4/6i is yet to be known, with many trials ongoing to expand their utility to other breast cancer subtypes, such as early breast cancer, and even to other cancers. Our research establishes the important idea that resistance to combined therapy (CDK4/6i + ET) can be due to resistance to endocrine therapy, to treatment with CDK4/6i, or to both. Individuals’ responses to treatment are based mostly on genetic features and molecular markers, as well as the tumor’s hallmarks; therefore, a future perspective is represented by personalized treatment based on the development of new biomarkers, and strategies to overcome drug resistance to combinations of ET and CDK4/6 inhibitors. The aim of our study was to centralize the mechanisms of resistance, and we believe that our work will have utility for everyone in the medical field who wants to deepen their knowledge about ET + CDK4/6 inhibitors resistance.
Impact of Breathing Phase, Liver Segment, and Prandial State on Ultrasound Shear Wave Speed, Shear Wave Dispersion, and Attenuation Imaging of the Liver in Healthy Volunteers
Authors: Paverd Catherine , Kupfer Sivert , Kirchner Iara Nascimento , Nambiar Sherin , Martin Alexander , Korta Martiartu Naiara , Frauenfelder Thomas , Rominger Marga B. , Ruby Lisa
Published: March 2023

Objectives: Measurement location and patient state can impact noninvasive liver assessment and change clinical staging in ultrasound examinations. Research into differences exists for Shear Wave Speed (SWS) and Attenuation Imaging (ATI), but not for Shear Wave Dispersion (SWD). The aim of this study is to assess the effect of breathing phase, liver lobe, and prandial state on SWS, SWD, and ATI ultrasound measurements. Methods: Two experienced examiners performed SWS, SWD, and ATI measurements in 20 healthy volunteers using a Canon Aplio i800 system. Measurements were taken in the recommended condition (right lobe, following expiration, fasting state), as well as (a) following inspiration, (b) in the left lobe, and (c) in a nonfasting state. Results: SWS and SWD measurements were strongly correlated (r = 0.805, p < 0.001). Mean SWS was 1.34 ± 0.13 m/s in the recommended measurement position and did not change significantly under any condition. Mean SWD was 10.81 ± 2.05 m/s/kHz in the standard condition and significantly increased to 12.18 ± 1.41 m/s/kHz in the left lobe. Individual SWD measurements in the left lobe also had the highest average coefficient of variation (19.68%). No significant differences were found for ATI. Conclusion: Breathing and prandial state did not significantly affect SWS, SWD, and ATI values. SWS and SWD measurements were strongly correlated. SWD measurements in the left lobe showed a higher individual measurement variability. Interobserver agreement was moderate to good.
Differentiation of Spontaneous Bacterial Peritonitis from Secondary Peritonitis in Patients with Liver Cirrhosis: Retrospective Multicentre Study
Authors: Würstle Silvia , Hapfelmeier Alexander , Karapetyan Siranush , Studen Fabian , Isaakidou Andriana , Schneider Tillman , Schmid Roland M. , von Delius Stefan , Gundling Felix , Burgkart Rainer , Obermeier Andreas , Mayr Ulrich , Ringelhan Marc , Rasch Sebastian , Lahmer Tobias , Geisler Fabian , Turner Paul E. , Chan Benjamin K. , Spinner Christoph D. , Schneider Jochen
Published: March 2023

Ascitic fluid infection is a serious complication of liver cirrhosis. The distinction between the more common spontaneous bacterial peritonitis (SBP) and the less common secondary peritonitis in patients with liver cirrhosis is crucial due to the varying treatment approaches. This retrospective multicentre study was conducted in three German hospitals and analysed 532 SBP episodes and 37 secondary peritonitis episodes. Overall, >30 clinical, microbiological, and laboratory parameters were evaluated to identify key differentiation criteria. Microbiological characteristics in ascites followed by severity of illness and clinicopathological parameters in ascites were the most important predictors identified by a random forest model to distinguish between SBP and secondary peritonitis. To establish a point-score model, a least absolute shrinkage and selection operator (LASSO) regression model selected the ten most promising discriminatory features. By aiming at a sensitivity of 95% either to rule out or rule in SBP episodes, two cut-off scores were defined, dividing patients with infected ascites into a low-risk (score ≥ 45) and high-risk group (score < 25) for secondary peritonitis. Overall, the discrimination of secondary peritonitis from SBP remains challenging. Our univariable analyses, random forest model, and LASSO point score may help clinicians with the crucial differentiation between SBP and secondary peritonitis.
Association of Body Mass Index (BMI) with Lip Morphology Characteristics: A Cross-Sectional Study Based on Chinese Population
Authors: Chen Yiyin , Yang Hongmei , Zheng Zhijin , Zhang Xiaoqi , Yan Xinyu , Long Hu , Lai Wenli
Published: March 2023

Background: Lip morphology is essential in diagnosis and treatment of orthodontics and orthognathic surgery to ensure facial aesthetics. Body mass index (BMI) has proved to have influence on facial soft tissue thickness, but its relationship with lip morphology is unclear. This study aimed to evaluate the association between BMI and lip morphology characteristics (LMCs) and thus provide information for personalized treatment. Methods: A cross-sectional study consisted of 1185 patients from 1 January 2010 to 31 December 2020 was conducted. Confounders of demography, dental features, skeletal parameters and LMCs were adjusted by multivariable linear regression to identify the association between BMI and LMCs. Group differences were evaluated with two-samples t-test and one-way ANOVA test. Mediation analysis was used for indirect effects assessment. Results: After adjusting for confounders, BMI is independently associated with upper lip length (0.039, [0.002–0.075]), soft pogonion thickness (0.120, [0.073–0.168]), inferior sulcus depth (0.040, [0.018–0.063]), lower lip length (0.208, [0.139–0.276]), and curve fitting revealed non-linearity to BMI in obese patients. Mediation analysis found BMI was associated with superior sulcus depth and basic upper lip thickness through upper lip length. Conclusions: BMI is positively associated with LMCs, except for nasolabial angle as negatively, while obese patients reverse or weaken these associations.
Effect of Particle Sizes and Contents of Surface Pre-Reacted Glass Ionomer Filler on Mechanical Properties of Auto-Polymerizing Resin
Authors: Kaga Naoyuki , Morita Sho , Yamaguchi Yuichiro , Matsuura Takashi
Published: March 2023

Herein, the mechanical properties of an auto-polymerizing resin incorporated with a surface pre-reacted glass ionomer (S-PRG) filler were evaluated. For this, S-PRG fillers with particle sizes of 1 μm (S-PRG-1) and 3 μm (S-PRG-3) were mixed at 10, 20, 30, and 40 wt% to prepare experimental resin powders. The powders and a liquid (powder/liquid ratio = 1.0 g/0.5 mL) were kneaded and filled into a silicone mold to obtain rectangular specimens. The flexural strength and modulus (n = 12) were recorded via a three-point bending test. The flexural strengths of S-PRG-1 at 10 wt% (62.14 MPa) and S-PRG-3 at 10 and 20 wt% (68.68 and 62.70 MPa, respectively) were adequate (>60 MPa). The flexural modulus of the S-PRG-3-containing specimen was significantly higher than that of the S-PRG-1-containing specimen. Scanning electron microscopy observations of the specimen fracture surfaces after bending revealed that the S-PRG fillers were tightly embedded and scattered in the resin matrix. The Vickers hardness increased with an increasing filler content and size. The Vickers hardness of S-PRG-3 (14.86–15.48 HV) was higher than that of S-PRG-1 (13.48–14.97 HV). Thus, the particle size and content of the S-PRG filler affect the mechanical properties of the experimental auto-polymerizing resin.
A Preliminary Study on the Development of a New UAV Concept and the Associated Flight Method
Authors: Frigioescu Tiberius-Florian , Condruz Mihaela Raluca , Badea Teodor Adrian , Paraschiv Alexandru
Published: March 2023

This article presents a preliminary study on the development of a new concept for an unmanned aerial vehicle (UAV) design that incorporates the use of four wings and attached systems to improve overall performance, it being classified as a hybrid quadcopter (a quad tilt wing, tiltrotor UAV). By simulation, it was determined that the developed concept has significant advantages compared with a conventional quadcopter. By implementing this concept, an increase in the maximum speed by 59.21% can be obtained; it reduces time to complete a 10 km route by 36.4%, decreases the energy consumption by 37%, and increases the maximum travel distance by 56.9% at 30% remaining battery capacity. Additionally, the concept improves maneuverability by allowing turning movements to be performed by changing the angle of incidence of the rear wings, resulting in less energy consumption compared to traditional turning methods applied in the case of a conventional quadcopter.
Establishment of a Landscape Information Model (LIM) and AI Convergence Plan through the 3D Digital Transformation of Railway Surroundings
Authors: Kim Min-kyeong , Park Duckshin , Yun Suhwan , Park Won-Hee , Lee Duckhee , Chung Jeong-Duk , Chung Kyung-Jin
Published: March 2023

Digital transformation projects have been undertaken in the land transportation and railway industries, including the introduction of various smart construction technologies. With the expansion of policies to increase the share of railway transportation as an environmentally sustainable means of transportation that meets the needs of the carbon-neutral era, 3D digital information is required throughout the entire chain of railway construction, route selection, status analysis, design, construction, and maintenance. The need for scientific and rational decision making is increasing. In this study, based on point cloud data acquired by an unmanned aerial vehicle (UAV) and a handheld mobile device, the landscape infrastructure around a railway was digitally converted, and a railway Landscape Information Model (LIM) process that modeled various types of landscape information was derived. Additionally, through the voxelization of 3D data, information regarding a railway’s surrounding environment, analyzed as a 3D volume concept and a convergence plan with deep-learning-based artificial intelligence (AI) technology, was presented through object recognition using a clustering algorithm. A railway LIM dataset could be created from a total of seven major categories, and massive data processing through AI convergence will be a future possibility through optimization of the point cloud data clustering algorithm. The future of the railway industry requires the establishment of a railway LIM for the integrated management of a railway’s surrounding environment and building information modeling (BIM) of structures such as tunnels. The railway LIM process has potential for use in various fields, such as environmental management and safety improvement for disaster prevention.
Application of Image Processing Techniques for UAV Detection Using Deep Learning and Distance-Wise Analysis
Authors: Dewangan Vedanshu , Saxena Aditya , Thakur Rahul , Tripathi Shrivishal
Published: March 2023

Drones have many applications in our daily lives and can be employed for agricultural, military, commercial, disaster relief, research and development, and many other purposes. There has been a significant increase in the usage of small drones/unmanned aerial vehicles in recent years. Consequently, there is a rising potential for small drones to be misused for illegal activities, such as terrorism and drug smuggling. Hence, there is a need for accurate and reliable UAV identification that can be used in various environments. In this paper, different versions of the current state-of-the-art object detection model, i.e., YOLO models, are used, by working on the principles of computer vision and deep learning to detect small UAVs. To improve the accuracy of small UAV detection, this paper proposes the application of various image-processing techniques to the current detection model, which has resulted in a significant performance increase. In this study, a mAP score of 96.7% was obtained for an IoU threshold of 50% along with a precision value of 95% and a recall of 95.6%. Distance-wise analysis of drones (i.e., for close, mid, and far ranges) was also performed to measure distance-wise accuracies.
Editorial of Special Issue “Unconventional Drone-Based Surveying”
Authors: Pesci Arianna , Teza Giordano , Fabris Massimo
Published: March 2023

Nowadays, Unmanned Aerial Vehicles (UAVs), as well as Unmanned Surface Vehicles (USVs) or also Unmanned Underwater Vehicles (UUVs), later on simply called drones, have reached a sufficient degree of maturity to allow their use for various purposes [...]
Dynamic Heat Dissipation Model of Distributed Parameters for Oil-Directed and Air-Forced Traction Transformers and Its Experimental Validation
Authors: You Yonghua , Shao Kun , Yi Zhengming
Published: March 2023

A traction transformer with narrow oil channels is usually cooled with the ODAF or “Oil Directed Air Forced” method, where its temperature greatly depends on the Joule heat of windings, the conjugate heat transfer in the transformer, and the secondary heat release via oil cooler, together with the oil flowrate generated by oil pump. Neither the thermal–electric analogy nor the CFD simulation approach is qualified to predict the temporal and spatial temperature variations in this type of transformer. In the current work, the distributed parameter models are built for traction transformers and oil coolers with the assumption of a one-dimensional temperature field in the oil flow direction, respectively. Then, the two models are combined with the lumped parameter ones of oil pumps and pipes via the flow rate, temperature and pressure continuities at their interfaces, resulting in the derivation of the dynamic heat dissipation model of oil-directed and air-forced traction transformers. Additionally, an efficient algorithm is proposed for its numerical solution, and the temperature rise experiment is performed for model validation. Finally, the fundamental of dynamic heat dissipation in traction transformers is investigated with the current numerical model and the effects of ambient temperature are studied.
Using Pop-GUIDE to Assess the Applicability of MCnest for Relative Risk of Pesticides to Hummingbirds
Authors: Etterson Matthew A. , Paulukonis Elizabeth A. , Purucker S. Thomas
Published: March 2023

Hummingbirds are charismatic fauna that provide important pollination services, including in the continental US, where 15 species regularly breed. Compared to other birds in North America, hummingbirds (family Trochilidae) have a unique exposure route to pesticides because they forage on nectar. Therefore, hummingbirds may be exposed to systemic pesticides borne in nectar. They also may be particularly vulnerable to pesticide exposure due to their small size and extreme metabolic demands. We review relevant factors including hummingbird life history, nectar residue uptake, and avian bioenergetic considerations with the goal of clearly identifying and articulating the specific modeling challenges that must be overcome to develop and/or adapt existing modeling approaches. To help evaluate these factors, we developed a dataset for ruby-throated hummingbirds (Archilochus colubris) and other avian species potentially exposed to pesticides. We used the systemic neonicotinoid pesticide imidacloprid as an illustration and compared results to five other common current use pesticides. We use the structure of Pop-GUIDE to provide a conceptual modeling framework for implementation of MCnest and to compile parameter values and relevant algorithms to predict the effects of pesticide exposure on avian pollinators. Conservative screening assessments suggest the potential for adverse effects from imidacloprid, as do more refined assessments, though many important limitations and uncertainties remain. Our review found many areas in which current USEPA avian models must be improved in order to conduct a full higher-tier risk assessment for avian pollinators exposed to neonicotinoid insecticides, including addition of models suitable for soil and seed treatments within the MCnest environment, ability to include empirical residue data in both nectar and invertebrates rather than relying on existing nomograms, expansion of MCnest to a full annual cycle, and increased representation of spatial heterogeneity. Although this work focuses on hummingbirds, the methods and recommendations may apply more widely to other vertebrate pollinators.
Exploring Influential Factors in Hiring Freelancers in Online Labor Platforms: An Empirical Study
Authors: Ren Jie , Raghupathi Viju , Raghupathi Wullianallur
Published: March 2023

Sharing economy online labor platforms play a critical role in bringing together freelancers and potential employers. This research is one of the few studies to address how freelancers’ characteristics impact the likelihood of being hired by employers using the theory of person–environment fit as a broad framework. Using Freelancer data, this research investigates if country of residence (of a freelancer and the employer), amount earned, and time since registered on the platform, are associated with the employment decision. The results indicate that country of residence does matter. Freelancers who tend to be from the same country as the employers are more likely to be hired. Likewise, high-income freelancers are less likely to be hired. Further, being longer on the platform influences the association between income level and likelihood of being hired. Greater efforts should be made to eliminate the asymmetric information between freelancers and employers and to provide more opportunities for both parties. The operators of online labor platforms should be encouraged to display information about freelancers that relates to country of origin, along with reviews, ratings, and rates earned in the same skill category, which would have strategic implications for freelance entrepreneurs on how to leverage themselves on a shared-economy-based online labor platform.
The Road to Hell Is Paved with Good Intentions: Modeling Grant Competition between Universities
Authors: Daumann Frank , Follert Florian , Wassermann Alfred
Published: March 2023

Competition is a core feature of science and has for some time also been viewed by institutions in the higher education sector, as well as the state, as an incentive to produce scientific output. Due to scarce financial resources third-party funding plays an increasingly important role. However, the race for the coveted grants also has its downsides and can lead to a loss of efficiency. To advance the discussion concerning grant competition we present a rent-seeking model that helps to understand the crucial factors influencing overall welfare. We show that the extent of the increase in productivity of independent research triggered by the grant competition, the extent of administrative expenses and the productivity of the research financed by the grant are decisive. Our main implications for policy-makers and university managers are that competition for third-party funding brings positive and negative effects and therefore, for the individual situation of the university, it has to be carefully considered whether scarce resources are invested in applications and that grant procedures should be designed in such a way that both a Matthew effect and a path-dependency effect are avoided.
Early Award Scholarship Program Results in Improved Attendance and State Math Test Scores for Students from Lower-Income Households
Authors: Elliott William , Sorensen Nick , Zheng Haotian , O’Brien Megan
Published: March 2023

In this study we conduct a quasi-experimental analysis comparing students who enrolled in Early Award Scholarship Program (EASP) (formerly Promise Scholars) at any time during the 2016–17 or 2017–18 school year with their counterparts who did not enroll in the program during this time. We employed an inverse-propensity weighting (IPW) design to adjust for baseline differences in characteristics between students who did enroll in EASP (treatment) and students who did not enroll in the program (comparison) using pretreatment administrative data from 2015–16. This IPW approach successfully removed baseline differences for baseline equivalence between a treatment and comparison group. Our findings show that participation in EASP results in significant educational benefits—higher state math test scores and improved attendance—for students from lower-income households (students receiving free/reduced lunch) but not their economically more advantaged peers. No impacts were found for ELA test scores. In short, these findings suggest that EASP may be an effective gap-closing program that improves math achievement and attendance for students from lower-income households. Effects are stronger for students who earned more award dollars by participating in more incentivized engagement activities across the 2016–17 and 2017–18 school years.
Recent Robots in STEAM Education
Authors: Kalaitzidou Magdalini , Pachidis Theodore P.
Published: March 2023

Robotics is increasingly entering the field of education. The tools, methods, and approaches of robotics contribute to the development of all areas of STEAM education, both individually and interdisciplinary. The present work aims to highlight the robots that are most effective in STEAM education and to classify robots used in education in terms of their frequency of use, features, flexibility, manufacturer, sensors, software, programming language, connection, recommended age, usefulness in education, and their cost. It turned out that there are packages for building robots, pre-assembled robots, and social robots. Their form can be animal, human, car, etc., and they have various properties; for example, they can move and fly. Moreover, most of the robots proposed for education use block-based programming; for example, the Scratch language. Common features of robots are that the robot follows a path, reacts to sounds, and recognizes obstacles, with various sensors; for example, vision. Finally, it turned out to be necessary to design an activity guide for each lesson, which will be accompanied by instructions and specific steps for teachers and students.
Spiritual Care in the Undergraduate Nursing Degree in Portugal
Authors: Afonso Ana , Sitefane Sara , Rabiais Isabel , Nunes Lucília , Caldeira Sílvia
Published: March 2023

Spiritual care is an essential dimension of holistic care. The purpose of this study was to identify the explicit presence of spiritual care in undergraduate nursing curricula in Portugal. Data were collected through a search in the syllabuses of undergraduate nursing degrees as displayed on the websites of higher education institutions (HEI). Of the 36 HEI, none had a course unit entitled (with title or subtitle) spirituality or spiritual care, even though all the HEI describe a common mission related to preparing nursing students for holistic care.
Policy Landscape and Promotion of Life-Long Learning in Croatia in the EU Context (2018–2022)
Authors: Žiljak Tihomir , Alfirević Nikša , Vučić Mario
Published: March 2023

In this paper, we review the EU and national (Croatian) education policy trends related to life-long learning and adult education in the last five years, focusing on the subsequent crises (COVID-19 and the security crisis caused by the war in Ukraine) and their influence on policy processes and documents. We also provide secondary data on trends in Croatian adult education, as well as present the results of empirical research performed on a sample of adult education providers from the Republic of Croatia. Our research aimed to identify how the policy trends have been reflected in the practice of Croatian adult education providers in the last five years (2018–2022), with the focus on (a) the practice of life-long learning and adult education promotion; (b) target groups for adult education providers in Croatia; and (c) how the institutional infrastructure in Croatia has supported adult education providers. The obtained results inform the policymakers and practitioners of adult education of potential discrepancies between policy trends and education practices relevant to small and peripheral EU member countries.
Newborn Feeding Knowledge and Attitudes among Medical Students
Authors: Pereira Henrique , Campos Ricardo , Silva Patricia , Cruz Madalena
Published: March 2023

This study sought to assess newborn feeding knowledge and attitudes among medical students. A sample of 649 Portuguese medical students completed an online survey containing a sociodemographic questionnaire, the Newborn Feeding Ability Questionnaire (NFA), and the Iowa Infant Feeding Attitudes Scale (IIFAS). The overall sample showed moderate scores for all variables. Gender analysis identified significant differences only for the dimension related to the benefits of skin-to-skin contact between mother and newborn where women scored higher. Analysis by year of training found that students with more years of training scored higher on all variables of newborn feeding knowledge that were positively correlated and were positive predictors of newborn feeding attitudes. Students with fewer years of training scored higher on work practices interfering with newborn feeding ability, which were negatively correlated and were negative predictors of newborn feeding attitudes. These results demonstrate that medical students with more years of training are the most prepared, however, the moderate results of the sample raise concerns. Our results point to the importance of providing medical students with adequate knowledge in order to influence their attitudes toward newborn feeding and contribute to better working practices for future health professionals.
Bibliographical Synthesis on the Corrosion and Protection of Archaeological Iron by Green Inhibitors
Authors: Zouarhi Meryem
Published: March 2023

Iron is a widely used metal due to its low cost and availability, but it is susceptible to corrosion in many circumstances. This corrosion can result in economic and environmental losses, and negatively affect the physical and chemical properties of the metal. This chapter provides a background on iron corrosion in archaeology and introduces various inhibitors used for its protection. It starts with a general overview of corrosion and metallurgy of iron, followed by an in-depth explanation of the mechanisms of iron corrosion in water and air. The chapter concludes with a review of different corrosion inhibitors, focusing on those made from natural plant extracts.
Research on a Lip Reading Algorithm Based on Efficient-GhostNet
Authors: Zhang Gaoyan , Lu Yuanyao
Published: March 2023

Lip reading technology refers to the analysis of the visual information of the speaker’s mouth movements to recognize the content of the speaker’s speech. As one of the important aspects of human–computer interaction, the technology of lip reading has gradually become popular with the development of deep learning in recent years. At present, most the lip reading networks are very complex, with very large numbers of parameters and computation, and the model generated by training needs to occupy large memory, which brings difficulties for devices with limited storage capacity and computation power, such as mobile terminals. Based on the above problems, this paper optimizes and improves GhostNet, a lightweight network, and improves on it by proposing a more efficient Efficient-GhostNet, which achieves performance improvement while reducing the number of parameters through a local cross-channel interaction strategy, without dimensionality reduction. The improved Efficient-GhostNet is used to perform lip spatial feature extraction, and then the extracted features are inputted to the GRU network to obtain the temporal features of the lip sequences, and finally for prediction. We used Asian volunteers for the recording of the dataset in this paper, while also adopting data enhancement for the dataset, using the angle transformation of the dataset to deflect the recording process of the recorder by 15 degrees each to the left and right, in order to be able to enhance the robustness of the network and better reduce the influence of other factors, as well as to improve the generalization ability of the model so that the model can be more consistent with recognition scenarios in real life. Experiments prove that the improved Efficient-GhostNet + GRU model can achieve the purpose of reducing the number of parameters with comparable accuracy.
Blockchain-Based Continuous Knowledge Transfer in Decentralized Edge Computing Architecture
Authors: Jin Wenquan , Xu Yinan , Dai Yilin , Xu Yihu
Published: March 2023

Edge computing brings computational ability to network edges to enable low latency based on deploying devices close to the environment where the data is generated. Nevertheless, the limitation of size and energy consumption constrain the scalability and performance of edge device applications such as deep learning, although, cloud computing can be adopted to support high-performance tasks with centralized data collection. However, frequently communicating with a central cloud server brings potential risks to security and privacy issues by exposing data on the Internet. In this paper, we propose a secure continuous knowledge transfer approach to improve knowledge by collaborating with multiple edge devices in the decentralized edge computing architecture without a central server. Using blockchain, the knowledge integrity is maintained in the transfer process by recording the transaction information of each knowledge improvement and synchronizing the blockchain in each edge device. The knowledge is a trained deep-learning model that is derived by learning the local data. Using the local data of each edge device, the model is continuously trained to improve performance. Therefore, each improvement is recorded as the contribution of each edge device immutably in the decentralized edge computing architecture.
A Novel Bio-Inspired Energy Optimization for Two-Tier Wireless Communication Networks: A Grasshopper Optimization Algorithm (GOA)-Based Approach
Authors: Sherif Ashraf , Haci Huseyin
Published: March 2023

Energy consumption has become one of the most challenging problems in future wireless communication networks. One of the promising methods in fifth generation (5G) cellular networks to meet the ever-increasing demand for high data traffic is wireless heterogeneous networks (HetNets). Adding more base stations may improve network coverage, but leads to the consumption of a significant amount of power. The scheme of two-tier networks contains small cell base stations (SCBs) that cooperate with macro cell base stations (MCBs) to provide wider coverage. Some small cell base station SCBs are experiencing light traffic loads due to the movement of user equipment (UEs), but these SCBs still consume a considerable amount of energy. Therefore, to reduce SCBs’ power consumption and maximize the overall energy efficiency (EE) of a two-tier network, some SCBs need to be switched off. In this paper, we extend the operation modes for BSs and present a novel mechanism to select an appropriate operation mode for each SCB that is based on bio-inspired behavior. We employ a bias function to manage the power consumption of each operation mode. Each SCB has four power mode selections: On, Standby, Sleep, and Off. We formulate the EE maximization problem under a set of constraints and present a Grasshopper Optimization Algorithm-based Variant Power Mode Selection (GOA-VPMS) to solve it. The proposed algorithm scheme outperforms previous work and provides a higher EE, according to the simulation results.