bluuebunny/crossref_metadata_2025 huggingface dataset:
COVID-19 Diagnosis from Chest X-ray Images Using a Robust Multi-Resolution Analysis Siamese Neural Network with Super-Resolution Convolutional Neural Network
Authors: Monday Happy Nkanta , Li Jianping , Nneji Grace Ugochi , Nahar Saifun , Hossin Md Altab , Jackson Jehoiada , Ejiyi Chukwuebuka Joseph
Published: March 2022

Chest X-ray (CXR) is becoming a useful method in the evaluation of coronavirus disease 19 (COVID-19). Despite the global spread of COVID-19, utilizing a computer-aided diagnosis approach for COVID-19 classification based on CXR images could significantly reduce the clinician burden. There is no doubt that low resolution, noise and irrelevant annotations in chest X-ray images are a major constraint to the performance of AI-based COVID-19 diagnosis. While a few studies have made huge progress, they underestimate these bottlenecks. In this study, we propose a super-resolution-based Siamese wavelet multi-resolution convolutional neural network called COVID-SRWCNN for COVID-19 classification using chest X-ray images. Concretely, we first reconstruct high-resolution (HR) counterparts from low-resolution (LR) CXR images in order to enhance the quality of the dataset for improved performance of our model by proposing a novel enhanced fast super-resolution convolutional neural network (EFSRCNN) to capture texture details in each given chest X-ray image. Exploiting a mutual learning approach, the HR images are passed to the proposed Siamese wavelet multi-resolution convolutional neural network to learn the high-level features for COVID-19 classification. We validate the proposed COVID-SRWCNN model on public-source datasets, achieving accuracy of 98.98%. Our screening technique achieves 98.96% AUC, 99.78% sensitivity, 98.53% precision, and 98.86% specificity. Owing to the fact that COVID-19 chest X-ray datasets are low in quality, experimental results show that our proposed algorithm obtains up-to-date performance that is useful for COVID-19 screening.
Deep Learning Model Based on 3D Optical Coherence Tomography Images for the Automated Detection of Pathologic Myopia
Authors: Park So-Jin , Ko Taehoon , Park Chan-Kee , Kim Yong-Chan , Choi In-Young
Published: March 2022

Pathologic myopia causes vision impairment and blindness, and therefore, necessitates a prompt diagnosis. However, there is no standardized definition of pathologic myopia, and its interpretation by 3D optical coherence tomography images is subjective, requiring considerable time and money. Therefore, there is a need for a diagnostic tool that can automatically and quickly diagnose pathologic myopia in patients. This study aimed to develop an algorithm that uses 3D optical coherence tomography volumetric images (C-scan) to automatically diagnose patients with pathologic myopia. The study was conducted using 367 eyes of patients who underwent optical coherence tomography tests at the Ophthalmology Department of Incheon St. Mary’s Hospital and Seoul St. Mary’s Hospital from January 2012 to May 2020. To automatically diagnose pathologic myopia, a deep learning model was developed using 3D optical coherence tomography images. The model was developed using transfer learning based on four pre-trained convolutional neural networks (ResNet18, ResNext50, EfficientNetB0, EfficientNetB4). Grad-CAM was used to visualize features affecting the detection of pathologic myopia. The performance of each model was evaluated and compared based on accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). The model based on EfficientNetB4 showed the best performance (95% accuracy, 93% sensitivity, 96% specificity, and 98% AUROC) in identifying pathologic myopia.
Field Experiences with Handheld Diagnostic Devices to Triage Children under Five Presenting with Severe Febrile Illness in a District Hospital in DR Congo
Authors: Tack Bieke , Vita Daniel , Mansosa Irène , Mbaki Thomas Nsema , Wasolua Naomie , Luyindula Aimée , Toelen Jaan , Lunguya Octavie , Jacobs Jan
Published: March 2022

As part of a field study (NCT04473768) in children presenting with severe febrile illness to Kisantu hospital (DR Congo), we retrospectively compiled user experiences (not performance) with handheld diagnostic devices assisting triage: tympanic thermometer, pulse oximeter (measuring heart rate, respiratory rate and oxygen saturation), hemoglobinometer and glucometer. Guidance documents for product selection were generic and scattered. Stock rupture, market withdrawal and unaffordable prices interfered with procurement. Challenges at implementation included environmental temperature, capillary blood sampling (antisepsis, order of multiple tests, filling microcuvettes and glucose strips), calibration (environmental temperature, cold chain) and liability-oriented communication with a manufacturer. Instructions for use were readable and contained symbol keys; two devices had printed French-language instructions. Shortcomings were poor integration of figures with text and distinct procedures for the oximeter and its sensor. Usability interview revealed appreciations for quick results, visibility of the display and memory function (three devices) but also problems of capillary blood sample transfer, cleaning, too long of a time-to-results (respiratory rate) and size, fitting and disposal of thermometer probes. Pictorial error messages were preferred over alphanumeric error codes but interpretation of symbols was poor. Alarm sounds of the oximeter caused unrest in children and caretakers perceived the device as associated with poor prognosis.
Comparison of Two Rapid Assays for the Detection of BRAF V600 Mutations in Metastatic Melanoma including Positive Sentinel Lymph Nodes
Authors: Long-Mira Elodie , Picard-Gauci Alexandra , Lassalle Sandra , Hofman Véronique , Lalvée Salomé , Tanga Virginie , Zahaf Katia , Bonnetaud Christelle , Lespinet Virginie , Camuzard Olivier , Montaudié Henri , Poissonnet Gilles , Passeron Thierry , Ilié Marius , Hofman Paul
Published: March 2022

Testing for the BRAF mutation is mandatory for the management of patients with locally advanced or metastatic melanoma. Molecular analysis based on DNA sequencing remains the gold-standard method for the screening of the different BRAF mutations. These methods must be rapid, sensitive, and specific enough to allow optimal therapeutic management in daily practice and also to include patients in clinical trials. Here, we compared the Idylla BRAF Mutation Test and the anti-BRAF V600E (clone VE1) immunohistochemistry (IHC) in 90 melanoma samples, with a focus on a challenging cohort of 32 positive sentinel lymph nodes. The BRAF status was assessed with both methods independently of the percentage of tumor cells. The concordance rate was calculated excluding both non-contributory analyses and BRAFV600K/R/M mutants due to the specific V600E-IHC test design. The incidence of the BRAFV600E mutation was 33% with both BRAF Idylla and BRAF IHC. The agreement rate was 91% (72/79). Although the agreement rate was high, we suggest that the use of IHC is more suitable for rapid BRAF testing on sentinel lymph node biopsies when associated with a low percentage and scattered tumor cells, which gave a high risk of non-contributory analysis and/or false negative results with the IdyllaTMBRAF Mutation Test.
Comparison of Mean Corneal Power of Annular Rings and Zones Using Swept-Source Optical Coherence Tomography
Authors: Dong Jing , Yao Jinhan , Chang Shuimiao , Kanclerz Piotr , Khoramnia Ramin , Wang Xiaogang
Published: March 2022

This study aims to investigate differences in the mean corneal power of annular zones (corneal power measured over the inner annular zone of difference diameters) and rings (corneal power measured over a ring of different diameters) centered on the corneal apex using the swept-source optical coherence tomography technique. The mean anterior axial curvature (AAC), posterior axial curvature (PAC), and total corneal power (TCP) centered on the corneal apex with the annular rings (0–2 mm, 2–4 mm, 4–6 mm, and 6–8 mm) and zones were assessed using the ANTERION device. The paired-sample t-test was used for data comparison. For the 0–2 mm comparison, the AAC, PAC, and TCP values of rings and zones were interchangeable. For the 2–4 mm comparison, the AAC of the rings was lower than that of the zones (p = 0.004), and the TCP values of the rings were higher than that of the zones (p < 0.001). For the 4–6 mm comparison, the AAC of the rings was lower than that of the zones (p < 0.001), and the PAC and TCP values of the rings were higher than that of the zones (both p < 0.001). For the 6–8 mm comparison, the AAC of the rings was lower than that of the zones (p < 0.001), and the PAC and TCP values of the rings were higher than that of the zones (both p < 0.001). Comparisons between AAC and TCP in each sub-region showed significant differences both in the rings (p < 0.001) and the zones (p < 0.008). Differences in the AAC, PAC, and TCP measured at different diameters (2–4 mm, 4–6 mm, and 6–8 mm) of the rings and zones, centered on the corneal apex, should be noticed in clinical practice. As the diameter increases, the difference between the rings and the zones in terms of AAC, PAC, and TCP increase as well. Clinicians should also pay attention to differences between AAC and TCP for the rings and the zones within the same annular region.
Quantification of Abdominal Muscle Mass and Diagnosis of Sarcopenia with Cross-Sectional Imaging in Patients with Polycystic Kidney Disease: Correlation with Total Kidney Volume
Authors: Wu Chih-Horng , Lai Tai-Shuan , Chen Yung-Ming , Chen Chyi-Mong , Yang Shun-Chung , Liang Po-Chin
Published: March 2022

Background: Polycystic kidney disease (PKD) is an inherited disorder characterized by renal cysts that may mask lean body loss. This study quantified and compared muscle mass by using computed tomography (CT) and magnetic resonance imaging (MRI) images between the PKD and control groups and correlated muscle mass with total kidney volume (TKV). Methods: We retrospectively enrolled patients who had a new diagnosis of PKD from May 2015 to May 2016. The CT and MRI images at the third lumbar level were processed to measure the total abdominal muscle (TAM) area for the diagnosis of sarcopenia, and TKV was estimated using the ellipsoid formula. Results: We included 37 women and 25 men (mean age: 50.40 years) in the PKD group. There was no difference in body mass index and albumin levels, but significant differences in creatinine level (p < 0.001), TAM area (p = 0.047), and TKV (p < 0.001), were noted between the two groups. A significantly negative correlation was observed between TKV and TAM area after adjustment for body height (r = −0.217, p = 0.003). Conclusions: CT and MRI images can accurately diagnose sarcopenia, which may be masked by cysts in patients with PKD.
Subepithelial Hyalinisation Predicts Recurrence of Unicystic Ameloblastomas
Authors: Augustine Dominic , Rao Roopa S. , Surendra Lakshminarayana , Gupta Bharti , Yoithapprabhunath Thuckanaickenpalayam Ragunathan , Yadalam Pradeep Kumar , Mushtaq Shazia , Ahmed Zeeshan Hera , Patil Shankargouda
Published: March 2022

The inductive effect of hyalinisation and its influence on the biologic behaviour of ameloblastoma variants represent a scarcely researched domain of oral pathology. The complexity of the induction effects within the odontogenic apparatus, with the involvement of both ectodermal and mesodermal tissues, is responsible for diverse histopathological characteristics, hyalinisation being the major feature. The present study aims to deduce for the first time the correlation between the severity of hyalinisation (SOH) and recurrence in three unicystic ameloblastoma (UA) variants, namely, intra-luminal (UA-IL), luminal (UA-L) and mural (UA-M). Retrospectively diagnosed archival cases of UA-IL (n = 08), UA-L (n = 22) and UA-M (n = 30) were assessed for SOH and its correlation with recurrence. A subgroup comparison (between UA-IL/UA-L and UA-M) was also performed. The clinical parameters of the patients were also analysed from files for clinicopathological correlation with recurrence. Results: sub-epithelial hyalinisation (SEH) significantly correlated with the recurrence of UA-L and UA-M (p = 0.001). When the histologic types (UA-L and UA-IL vs. UA-M) were grouped and the correlation of SOH with recurrence was checked, it was observed that both groups (p = 0.001) showed strong statistical correlation. UA-M lesions with multilocular radiolucency (p = 0.001) also showed significant correlation with recurrence. SOH can be a reliable histological predictor of recurrence and of aggressive biologic behaviour in UA. The present study shows a significant association of hyalinisation with the biologic behaviour of UA. Further studies with immunohistochemical investigations could validate the presence of hyalinisation and identify the origin of the hyalinised product in UAs.
Diagnostic and Prognostic Roles of CDX2 Immunohistochemical Expression in Colorectal Cancers
Authors: Choi Hong Bae , Pyo Jung-Soo , Son Soomin , Kim Kyungdoc , Kang Guhyun
Published: March 2022

The study is aimed to evaluate the diagnostic and prognostic role of the immunohistochemical expression of the Caudal-type homeobox transcription factor 2 (CDX2) in colorectal cancers (CRCs) through a meta-analysis. By searching relevant databases, 38 articles were eligible to be included in this study. We extracted the information for CDX2 expression rates and the correlation between CDX2 expression and clinicopathological characteristics. The estimated rates of CDX2 expression were 0.882 [95% confidence interval (CI) 0.774–0.861] and 0.893 (95% CI 0.820–0.938) in primary and metastatic CRCs, respectively. Furthermore, based on their histologic subtype, CDX2 expression rates of adenocarcinoma and medullary carcinoma were 0.886 (95% CI 0.837–0.923) and 0.436 (95% CI 0.269–0.618), respectively. There was a significant difference in CDX2 expression rates between adenocarcinoma and medullary carcinoma in the meta-regression test (p < 0.001). In addition, CDX2 expression was significantly lower in CRCs with the BRAFV600E mutation than in CRCs without mutation. Patients with CDX2 expression had better overall and cancer-specific survival rates than those without CDX2 expression. Thus, CDX2 is a useful diagnostic and prognostic marker CRCs.
Overview of Lung Ultrasound in Pediatric Cardiology
Authors: Cantinotti Massimiliano , Marchese Pietro , Giordano Raffaele , Franchi Eliana , Assanta Nadia , Jani Vivek , Kutty Shelby , Gargani Luna
Published: March 2022

Lung ultrasound (LUS) is increasing in its popularity for the diagnosis of pulmonary complications in acute pediatric care settings. Despite the high incidence of pulmonary complications for patients with pediatric cardiovascular and congenital heart disease, especially in children undergoing cardiac surgery, the use of LUS remains quite limited in these patients. The aim of this review is to provide a comprehensive overview and list of current potential applications for LUS in children with congenital heart disease, post-surgery. We herein describe protocols for LUS examinations in children, discuss diagnostic criteria, and introduce methods for the diagnosis and classification of pulmonary disease commonly encountered in pediatric cardiology (e.g., pleural effusion, atelectasis, interstitial edema, pneumothorax, pneumonia, and diaphragmatic motion analysis). Furthermore, applications of chest ultrasounds for the evaluation of the retrosternal area, and in particular, systematic search criteria for retrosternal clots, are illustrated. We also discussed the potential applications of LUS, including the guidance of interventional procedures, namely lung recruitment and drainage insertion. Lastly, we analyzed current gaps in knowledge, including the difficulty of the quantification of pleural effusion and atelectasis, and the need to differentiate different etiologies of B-lines. We concluded with future applications of LUS, including strain analysis and advanced analysis of diaphragmatic mechanics. In summary, US is an easy, accurate, fast, cheap, and radiation-free tool for the diagnosis and follow-up of major pulmonary complications in pediatric cardiac surgery, and we strongly encourage its use in routine practice.
WMR-DepthwiseNet: A Wavelet Multi-Resolution Depthwise Separable Convolutional Neural Network for COVID-19 Diagnosis
Authors: Monday Happy Nkanta , Li Jianping , Nneji Grace Ugochi , Hossin Md Altab , Nahar Saifun , Jackson Jehoiada , Chikwendu Ijeoma Amuche
Published: March 2022

Timely discovery of COVID-19 could aid in formulating a suitable treatment plan for disease mitigation and containment decisions. The widely used COVID-19 test necessitates a regular method and has a low sensitivity value. Computed tomography and chest X-ray are also other methods utilized by numerous studies for detecting COVID-19. In this article, we propose a CNN called depthwise separable convolution network with wavelet multiresolution analysis module (WMR-DepthwiseNet) that is robust to automatically learn details from both spatialwise and channelwise for COVID-19 identification with a limited radiograph dataset, which is critical due to the rapid growth of COVID-19. This model utilizes an effective strategy to prevent loss of spatial details, which is a prevalent issue in traditional convolutional neural network, and second, the depthwise separable connectivity framework ensures reusability of feature maps by directly connecting previous layer to all subsequent layers for extracting feature representations from few datasets. We evaluate the proposed model by utilizing a public domain dataset of COVID-19 confirmed case and other pneumonia illness. The proposed method achieves 98.63% accuracy, 98.46% sensitivity, 97.99% specificity, and 98.69% precision on chest X-ray dataset, whereas using the computed tomography dataset, the model achieves 96.83% accuracy, 97.78% sensitivity, 96.22% specificity, and 97.02% precision. According to the results of our experiments, our model achieves up-to-date accuracy with only a few training cases available, which is useful for COVID-19 screening. This latest paradigm is expected to contribute significantly in the battle against COVID-19 and other life-threatening diseases.
Intracranial Flow Volume Estimation in Patients with Internal Carotid Artery Occlusion
Authors: Kaszczewski Piotr , Elwertowski Michał , Leszczyński Jerzy , Ostrowski Tomasz , Kaszczewska Joanna , Gałązka Zbigniew
Published: March 2022

(1) Background: Carotid artery occlusion (CAO) in population studies has a reported prevalence of about 6 per 100,000 people; however, the data may be underestimated. CAO carries a significant risk of stroke. Up to 15% of large artery infractions may be secondary to the CAO, and in 27–38% of patients, ischaemic stroke is a first presentation of the disease. The presence of sufficient and well-developed collateral circulation has a protective influence, being a good prognostic factor in patients with carotid artery disease, both chronic and acute. Understanding the mechanisms and role of collateral circulation may be very important in the risk stratification of such patients. (2) Materials and Methods: This study included 46 patients (mean age: 70.5 ± 6 years old; 15 female, mean age 68.5 ± 3.8 years old and 31 male, mean age 71.5 ± 6.7 years old) with unilateral or bilateral ICA occlusion. In all patients, a Doppler ultrasound (DUS) examination, measuring blood flow volume in the internal carotid artery (ICA), external carotid artery (ECA), and vertebral artery (VA), was performed. The cerebral blood flow (CBF) was compared to the previously reported CBF values in the healthy population >65 years old. (3) Results: In comparison with CBF values in the healthy population, three subgroups with CBF changes were identified among patients with ICA occlusion: patients with significant volumetric flow compensation (CBF higher than average + standard deviation for healthy population of the same age), patients with flow similar to the healthy population (average ± standard deviation), and patients without compensation (CBF lower than the average-standard deviation for healthy population). The percentage of patients with significant volumetric flow compensation tend to rise with increasing age, while a simultaneous decline was observed in the group without compensation. The percentage of patients with flow similar to the healthy population remained relatively unchanged. ICA played the most important role in volumetric flow compensation in patients with CAO; however, the relative increase in flow in the ICA was smaller than that in the ECA and VA. Compensatory increased flow was observed in about 50% of all patent extracranial arteries and was more frequently observed in ipsilateral vessels than in contralateral ones, in both the ECA and the VA. In patients with CAO, there was no decrease in CBF, ICA, ECA, and VA flow volume with increasing age. (4) Conclusions: Volumetric flow compensation may play an important predictive role in patients with CAO.
Prediction of Adverse Post-Infarction Left Ventricular Remodeling Using a Multivariate Regression Model
Authors: Oleynikov Valentin , Salyamova Lyudmila , Kvasova Olga , Burko Nadezhda
Published: March 2022

Background. In order to provide personalized medicine and improve cardiovascular outcomes, a method for predicting adverse left ventricular remodeling (ALVR) after ST-segment elevation myocardial infarction (STEMI) is needed. Methods. A total of 125 STEMI patients, mean age 51.2 (95% CI 49.6; 52.7) years were prospectively enrolled. The clinical, laboratory, and instrumental examinations were performed between the 7th and 9th day, and after 24 and 48 weeks, including plasma analysis of brain natriuretic peptide (BNP), transthoracic echocardiography, analysis of left ventricular-arterial coupling, applanation tonometry, ultrasound examination of the common carotid arteries with RF signal amplification. Results. Patients were divided into 2 groups according to echocardiography: “ALVR” (n = 63)—end-diastolic volume index (EDVI) >20% and/or end-systolic volume index (ESVI) >15% after 24 weeks compared with initial values; “non-ALVR” (n = 62)—EDVI <20% and ESVI <15%. In the ALVR group, hard endpoints (recurrent myocardial infarction, unstable angina, hospitalization for decompensated heart failure, ventricular arrhythmias, cardiac surgery, cardiovascular death) were detected in 19 people (30%). In the non-ALVR group, hard endpoints were noted in 3 patients (5%). The odds ratio of developing an adverse outcome in ALVR vs. non-ALVR group was 8.5 (95% CI 2.4–30.5) (p = 0.0004). According to the multivariate analysis, the contribution of each of the indicators to the relative risk (RR) of adverse cardiac remodeling: waist circumference, RR = 1.02 (95% CI 1.001–1.05) (p = 0.042), plasma BNP—RR = 1.81 (95% CI 1.05–3.13) (p = 0.033), arterial elastance to left ventricular end-systolic elastance (Ea/Ees)—RR = 1.96 (95% CI 1.11–3.46) (p = 0.020). Conclusion. Determining ALVR status in early stages of the disease can accurately predict and stratify the risk of adverse outcomes in STEMI patients.
Human Rabies by Secondary Transmission in Argentina, 2021
Authors: Firpo Soledad , Piccirilli María Guadalupe , Urizar Rogelio , Vitta Nicolas , Hirmas Riade Stella Maris , Leguizamón Constanza , Vico María Lorena , Martínez Gustavo , Beltrán Fernando J. , Cisterna Daniel M.
Published: March 2022

Rabies is a zoonotic disease caused by the rabies virus (RABV) that causes fatal encephalitis in mammals. Bats can transmit the disease to urban canines and felines, which rarely infect humans, establishing a secondary link. The last case of human rabies in Argentina was transmitted by a dog in 2008. We present the first case of human rabies originating from an insectivorous bat, Tadarida brasiliensis, transmitted by a feral cat in Buenos Aires province, Argentina.
Chronic Stress and Depression in Periodontitis and Peri-Implantitis: A Narrative Review on Neurobiological, Neurobehavioral and Immune–Microbiome Interplays and Clinical Management Implications
Authors: D’Ambrosio Francesco , Caggiano Mario , Schiavo Luigi , Savarese Giulia , Carpinelli Luna , Amato Alessandra , Iandolo Alfredo
Published: March 2022

Besides the well-known systemic factors for periodontal and peri-implant diseases, additional co-factors, such as chronic stress and depression, may also affect disease onset and progression as well as treatment responsiveness. Neurobiological and neurobehavioral pathogenic links between chronic stress and depression, on the one side, and periodontitis and peri-implantitis, on the other side, which have been little investigated and principally related to necrotizing periodontal disease, have been reviewed, along with their putative interconnections with periodontal immune–microbiome balance. Rising evidence suggest that dysregulated neurobiological and neurobehavioral factors, as well as periodontal immune–microbiome unbalance, all related to chronic stress and depression, may crucially interact and thus represent contributing factors in the genesis and worsening not only of necrotizing periodontal lesions, but also of chronic periodontitis and peri-implantitis. Such potential interconnections may be even more relevant in recurrent and aggressive cases of periodontal and peri-implant disease, which are frequently refractory to therapy, and may, if corroborated, coherently pave the way for personalized prevention and treatment strategies, possibly targeting immune–microbiome unbalance and neurobehavioral factors and focusing on neurobiological ones, especially in chronically stressed and depressed subjects with periodontitis and peri-implantitis.
H∞ Observer Based on Descriptor Systems Applied to Estimate the State of Charge
Authors: Meng Shengya , Li Shihong , Chi Heng , Meng Fanwei , Pang Aiping
Published: March 2022

This paper proposes an H∞ observer based on descriptor systems to estimate the state of charge (SOC). The battery’s open-current voltage is chosen as a generalized state variable, thereby avoiding the artificial derivative calculation of the algebraic equation for the SOC. Furthermore, the observer’s dynamic performance is saved. To decrease the impacts of the uncertain noise and parameter perturbations, nonlinear H∞ theory is implemented to design the observer. The sufficient conditions for the H∞ observer to guarantee the disturbance suppression performance index are given and proved by the Lyapunov stability theory. This paper systematically gives the design steps of battery SOC H∞ observers. The simulation results highlight the accuracy, transient performance, and robustness of the presented method.
Entropy Analysis of Neonatal Electrodermal Activity during the First Three Days after Birth
Authors: Visnovcova Zuzana , Kozar Marek , Kuderava Zuzana , Zibolen Mirko , Ferencova Nikola , Tonhajzerova Ingrid
Published: March 2022

The entropy-based parameters determined from the electrodermal activity (EDA) biosignal evaluate the complexity within the activity of the sympathetic cholinergic system. We focused on the evaluation of the complex sympathetic cholinergic regulation by assessing EDA using conventional indices (skin conductance level (SCL), non-specific skin conductance responses, spectral EDA indices), and entropy-based parameters (approximate, sample, fuzzy, permutation, Shannon, and symbolic information entropies) in newborns during the first three days of postnatal life. The studied group consisted of 50 healthy newborns (21 boys, average gestational age: 39.0 ± 0.2 weeks). EDA was recorded continuously from the feet at rest for three periods (the first day—2 h after birth, the second day—24 h after birth, and the third day—72 h after birth). Our results revealed higher SCL, spectral EDA index in a very-low frequency band, approximate, sample, fuzzy, and permutation entropy during the first compared to second and third days, while Shannon and symbolic information entropies were lower during the first day compared to other periods. In conclusion, EDA parameters seem to be sensitive in the detection of the sympathetic regulation changes in early postnatal life and which can represent an important step towards a non-invasive early diagnosis of the pathological states linked to autonomic dysmaturation in newborns.
DrawnNet: Offline Hand-Drawn Diagram Recognition Based on Keypoint Prediction of Aggregating Geometric Characteristics
Authors: Fang Jiaqi , Feng Zhen , Cai Bo
Published: March 2022

Offline hand-drawn diagram recognition is concerned with digitizing diagrams sketched on paper or whiteboard to enable further editing. Some existing models can identify the individual objects like arrows and symbols, but they become involved in the dilemma of being unable to understand a diagram’s structure. Such a shortage may be inconvenient to digitalization or reconstruction of a diagram from its hand-drawn version. Other methods can accomplish this goal, but they live on stroke temporary information and time-consuming post-processing, which somehow hinders the practicability of these methods. Recently, Convolutional Neural Networks (CNN) have been proved that they perform the state-of-the-art across many visual tasks. In this paper, we propose DrawnNet, a unified CNN-based keypoint-based detector, for recognizing individual symbols and understanding the structure of offline hand-drawn diagrams. DrawnNet is designed upon CornerNet with extensions of two novel keypoint pooling modules which serve to extract and aggregate geometric characteristics existing in polygonal contours such as rectangle, square, and diamond within hand-drawn diagrams, and an arrow orientation prediction branch which aims to predict which direction an arrow points to through predicting arrow keypoints. We conducted wide experiments on public diagram benchmarks to evaluate our proposed method. Results show that DrawnNet achieves 2.4%, 2.3%, and 1.7% recognition rate improvements compared with the state-of-the-art methods across benchmarks of FC-A, FC-B, and FA, respectively, outperforming existing diagram recognition systems on each metric. Ablation study reveals that our proposed method can effectively enable hand-drawn diagram recognition.
Generalized Householder Transformations
Authors: Svozil Karl
Published: March 2022

The Householder transformation, allowing a rewrite of probabilities into expectations of dichotomic observables, is generalized in terms of its spectral decomposition. The dichotomy is modulated by allowing more than one negative eigenvalue or by abandoning binaries altogether, yielding generalized operator-valued arguments for contextuality. We also discuss a form of contextuality by the variation of the functional relations of the operators, in particular by additivity.
Reconstructing Binary Signals from Local Histograms
Authors: Sporring Jon , Darkner Sune
Published: March 2022

In this paper, we considered the representation power of local overlapping histograms for discrete binary signals. We give an algorithm that is linear in signal size and factorial in window size for producing the set of signals, which share a sequence of densely overlapping histograms, and we state the values for the sizes of the number of unique signals for a given set of histograms, as well as give bounds on the number of metameric classes, where a metameric class is a set of signals larger than one, which has the same set of densely overlapping histograms.
Sustainable Growth Rate and ROE Analysis: An Applied Study on Saudi Banks Using the PRAT Model
Authors: Altahtamouni Farouq , Alfayhani Ahoud , Qazaq Amna , Alkhalifah Arwa , Masfer Hajar , Almutawa Ryoof , Alyousef Shikhah
Published: March 2022

This study aims at testing the effect of the components of the PRAT model and the basic model developed by Robert Higgins on the rate of sustainable growth by applying them to a sample of Saudi banks during the period of 2010–2019. Regarding the PRAT model, as Higgins explained, it is that detailed model measuring the sustainable growth rate by profit margin (P), retention rate (R), asset turnover (A), and leverage (T). To test the relation between the study variables, multiple regression analyses were conducted using the Pooled Model (PEM), the Fixed Effect Model (FEM), and the Random Effect Model (REM). The results showed that all the variables of the PRAT model affect sustainable growth (profitability margin, retained earnings, asset turnover, and financial leverage). Moreover, the application of the basic model of Higgins shows that the rate of return on equity and retained earnings affect sustainable growth. When drawing a comparison among statistical measurement models and checking the validity of these models, the validity of the fixed effect model for measuring the relation between the variables of the PRAT model and Higgins basic model is seen.
Promoting Enquiry Skills in Trainee Teachers within the Context of the University Ecological Garden
Authors: Aragón Lourdes , Gómez-Chacón Beatriz
Published: March 2022

One of the objectives of science teaching and learning is to achieve quality science education, which involves improving initial teacher training. The use of methodologies that promote learning in science, such as the enquiry-based learning strategy, are encouraged. It is also necessary to provide appropriate contexts that give meaning to the investigation conducted, and arouse the students’ interest. The purpose of this study is to identify the skills related to the enquiry competency that future pre-school teachers acquire after carrying out investigations using the University Ecological Garden as a context. To undertake this study, a non-experimental quantitative methodology was developed based on the application of two instruments: the New Practical Test Assessment Inventory (NPTAI), based on the Practical Test Assessment Inventory, and the trainee teachers’ Enquiry Competency Level (ECL), adapted for the present work. Thirty-seven group reports were analysed and recoded to establish five levels of enquiry competency. A predominance of students with a high level of enquiry competency as opposed to "pre-scientific" and "unscientific" lower levels was observed. The results allowed us to explore the role of the teacher in the monitoring process during the strategy, the context used, and the main difficulties encountered in the implementation of the strategy.
Primary Pupils’ Multimodal Representations in Worksheets—Text Work in Science Education
Authors: Jeppsson Fredrik , Danielsson Kristina , Bergh Nestlog Ewa , Tang Kok-Sing
Published: March 2022

Worksheets are common in science classrooms with an aim to support pupils’ meaning-making, e.g., for guiding them in performing hands-on activities and documenting their experiences of such activities. Yet, there have been few systematic studies of pupils’ disciplinary representations in worksheets. Drawing on systemic functional linguistics, we have analyzed fifth grade pupils’ (age 10–11) multimodal texts in worksheets (n = 25) when they were working with shadow formation as part of their regular classroom activities. In the worksheets they were asked to first explain in writing why or why not a shadow was formed and then explain shadow formation through a drawing. At an overall level, we found that a majority of the pupils managed to express in writing why a shadow is formed, though it appeared to be more challenging for them to explain why a shadow is not formed. In their drawings, quite a few pupils managed to include several key aspects of shadow formation, at least when combining image with writing. For all tasks, the explanatory parts of the pupils’ responses were often implicit. Based on our results, we suggest that pupils may benefit from teaching practices that integrate a parallel focus on form and content as a way to raise their awareness of, for instance, the affordances of different resources and how explanations can be structured. Such practices may support pupils to be able to consider and choose appropriate resources in their disciplinary texts.
An ESP Approach to Teaching Nursing Note Writing to University Nursing Students
Authors: Su Shiou-Mai , Tsai Yuan-Hsiung , Tai Hung-Cheng
Published: March 2022

For nursing students in the vocational education system in Taiwan, English-language writing skills, whether for general or specific purposes, have long been ignored, which may jeopardize their success in medical-oriented courses and their future careers. This study designed a nursing note-writing course (NNWC) for university nursing students and explored the teaching outcomes of its implementation. The three main objectives were to (a) examine the effectiveness of the NNWC in enhancing learners’ competencies; (b) survey learners’ satisfaction with the NNWC, and (c) investigate learners’ perceptions of the NNWC. In this action research, 49 students practiced five writing tasks while guided with five teaching tools, namely an online writing platform, multiple revisions, peer-review activities, and direct and indirect teacher feedback, for a semester. External examiners included a language teacher and a nursing professional, and the data-collection instruments used included a writing competence scale and a course satisfaction questionnaire. The results showed that the learners’ writing competence significantly improved after the NNWC. They also demonstrated a fair level of satisfaction toward the NNWC. A total of 90% of the learners preferred online writing compared to traditional handwriting. The learners also indicated a preference for feedback from the teacher rather than from peers, and they perceived vocabulary capability to be crucial. ESP/ENP teachers are advised to consider the implementation of the NNWC when designing syllabi.
Teaching Innovation in STEM Education Using an Unmanned Aerial Vehicle (UAV)
Authors: Bolick Madeleine M. , Mikhailova Elena A. , Post Christopher J.
Published: March 2022

The use of unmanned aerial vehicles (UAVs) has increased in the science, technology, engineering, and mathematics (STEM) professions. This means there is a growing need to integrate UAV training into STEM education. This study aimed to develop and evaluate a UAV education module and laboratory exercise for natural resource science students. The study used a series of reusable learning objects (RLOs) to assess students’ prior knowledge of remote sensing and UAVs. Students were taught the steps of UAV data acquisition and processing through lectures and UAV simulation videos. Students applied this knowledge by completing a laboratory exercise that used previously collected UAV data. Student knowledge retention and understanding were evaluated using an online quiz to determine the effectiveness of the education module. The average quiz score was 92%, indicating that the UAV laboratory exercise effectively taught students about UAV data acquisition and processing for natural resource research. Overall, students expressed positive opinions about the UAV education module. Student feedback indicated that the laboratory exercise was engaging, but some students would have preferred a hands-on experience for some parts of the exercise. However, in-person UAV instruction may not be accessible for all educators because of UAV cost or lack of instructor training. This study provides educators with crucial recommendations for designing UAV exercises to improve access to UAV-related educational content. This study indicates that online training can effectively introduce students to UAVs. Given the wide range of UAV uses across STEM fields, students in many STEM disciplines would benefit from UAV education.
Embedding Sustainability in Learning and Teaching: Lessons Learned and Moving Forward—Approaches in STEM Higher Education Programmes
Authors: Gamage Kelum A. A. , Ekanayake Sakunthala Yatigammana , Dehideniya Shyama C. P.
Published: March 2022

Embedding sustainability into pedagogical approaches is a key priority in higher education. Equipping students with knowledge, understanding, and skills, and developing the next generation of innovators and leaders, can potentially provide the change needed and create a real impact in the journey to a sustainable future. Advancement in Science, Technology, Engineering, and Mathematics (STEM), and corresponding industries can be seen as vital for the success of meeting a majority of the sustainable development goals, and hence the approaches taken to embed sustainability in learning and teaching in STEM higher education programmes can be considered significant in many ways. This paper is based on published literature over the last two decades and a semi-structured interview with 12 university academics from a developing country. Hence, the paper reviews approaches taken to embed sustainability in learning, teaching and assessments in STEM programmes. It also aims to investigate the actions taken by universities to integrate sustainability in STEM education and the remedies taken to minimise the impact of the pandemic on the effectiveness of the learning pedagogies used to integrate sustainability concepts.
Student Grade Evaluation, Survey Feedback, and Lessons Learned during the COVID-19 Pandemic: A Comparative Study of Virtual vs. In-Person Offering of a Freshman-Level General Chemistry II Course in Summer at Xavier University of Louisiana
Authors: Goyal Navneet , Abdulahad Asem I. , Privett Janet A. , Verma Abha , Foroozesh Maryam , Coston Tiera S.
Published: March 2022

A primary motivation for this study was to compare student perceptions and performance within a virtual learning environment to the traditional in-person learning experience for the General Chemistry II course taught during a 5-week summer session at Xavier University of Louisiana, a minority serving institution. The authors present quantitative and qualitative analyses including the comparison of student performance on exams during the COVID-19 remote learning experience with exam performance over a 3-year period of conventional in-person instruction. In this article, student grades, survey feedback, and learning outcomes are outlined. This study was performed to assist the faculty in improving and enriching the course content and its delivery, as they coped with the transition to a virtual learning environment imposed by the COVID-19 pandemic.
Infrared Image Small-Target Detection Based on Improved FCOS and Spatio-Temporal Features
Authors: Yao Shengbo , Zhu Qiuyu , Zhang Tao , Cui Wennan , Yan Peimin
Published: March 2022

The research of infrared image small-target detection is of great significance to security monitoring, satellite remote sensing, infrared early warning, and precision guidance systems. However, small infrared targets occupy few pixels and lack color and texture features, which make the detection of small infrared targets extremely challenging. This paper proposes an effective single-stage infrared small-target detection method based on improved FCOS (Fully Convolutional One-Stage Object Detection) and spatio-temporal features. In view of the simple features of infrared small targets and the requirement of real-time detection, based on the standard FCOS network, we propose a lightweight network model combined with traditional filtering methods, whose response for small infrared targets is enhanced, and the background response is suppressed. At the same time, in order to eliminate the influence of static noise points in the infrared image on the detection of small infrared targets, time domain features are added to the improved FCOS network in the form of image sequences, so that the network can learn the spatio-temporal correlation features in the image sequence. Finally, compared with current typical infrared small-target detection methods, the comparative experiments show that the improved FCOS method proposed in this paper had better detection accuracy and real-time performance for infrared small targets.
Exploration of the High-Efficiency Hardware Architecture of SM4-CCM for IoT Applications
Authors: Chen Rui , Li Bing
Published: March 2022

The widespread use of the internet of things (IoT) is due to the value of the data collected by IoT devices. These IoT devices generate, process, and exchange large amounts of safety-critical or privacy-sensitive data. Before transmission, the data should be protected against information leakage and data stealing. Deploying authenticated encryption with additional data (AEAD) algorithms on IoT devices ensures data confidentiality and integrity. However, AEAD algorithms are computationally intensive, while IoT devices are resource constrained or even battery powered. Therefore, a low-cost, low-power, and high-efficiency method of implementing an AEAD algorithm into resource-constrained IoT devices is required. The SM4-CCM algorithm, introduced in RFC 8998, is selected as the AEAD algorithm to address this problem. Algorithms similar to SM4-CCM (e.g., SM4 and AES-CCM) provide many architectural design references, but it is challenging to decide which architecture is the most suitable for SM4-CCM. In order to find the most efficient SM4-CCM hardware architecture, a design space exploration method is proposed. Firstly, the SM4-CCM algorithm is divided into five layers, and three candidate architectures are provided for each layer. Secondly, 63 design schemes for SM4-CCM are constructed by combining candidate architectures from each layer. Finally, a batch number of comparisons and analyses of experimental results are used to identify the most efficient one. Under TSMC 90 nm technology, the experimental results of the identified scheme show that the throughput, power consumption, and area achieve 199.99 Mbps, 1.625 mW, and 14.6 K gates, respectively. As a proof of concept, implementing this scheme on an FPGA board is also presented.
Assessment of Dual-Tree Complex Wavelet Transform to Improve SNR in Collaboration with Neuro-Fuzzy System for Heart-Sound Identification
Authors: Al-Naami Bassam , Fraihat Hossam , Al-Nabulsi Jamal , Gharaibeh Nasr Y. , Visconti Paolo , Al-Hinnawi Abdel-Razzak
Published: March 2022

The research paper proposes a novel denoising method to improve the outcome of heart-sound (HS)-based heart-condition identification by applying the dual-tree complex wavelet transform (DTCWT) together with the adaptive neuro-fuzzy inference System (ANFIS) classifier. The method consists of three steps: first, preprocessing to eliminate 50 Hz noise; second, applying four successive levels of DTCWT to denoise and reconstruct the time-domain HS signal; third, to evaluate ANFIS on a total of 2735 HS recordings from an international dataset (PhysioNet Challenge 2016). The results show that the signal-to-noise ratio (SNR) with DTCWT was significantly improved (p < 0.001) as compared to original HS recordings. Quantitatively, there was an 11% to many decibel (dB)-fold increase in SNR after DTCWT, representing a significant improvement in denoising HS. In addition, the ANFIS, using six time-domain features, resulted in 55–86% precision, 51–98% recall, 53–86% f-score, and 54–86% MAcc compared to other attempts on the same dataset. Therefore, DTCWT is a successful technique in removing noise from biosignals such as HS recordings. The adaptive property of ANFIS exhibited capability in classifying HS recordings.
Review of Ka-Band Power Amplifier
Authors: Wang Zhong , Hu Shanwen , Gu Ling , Lin Lujun
Published: March 2022

With the increase in the demand for high-speed transmission communication, satellite communication is developing rapidly. Because of the bandwidth capacity, the K/Ka band is considered the mainstream frequency band of satellite communication. The performance of a power amplifier (PA) directly affects the power of the transmitter, so the application of a power amplifier in Ka-band satellite communication is very important. A review of the state-of-the-art PA in the Ka band is presented in this article. The structure of the PA introduced includes common source, cascode, stacked field-effect transistor (FET), power combining, and Doherty PA, highlighting the advantages and disadvantages. The main solid-state technologies are outlined, including Si, SiGe, GaAs, and GaN, emphasizing Si complementary metal–oxide–semiconductor (CMOS) due to low price and high integration.