bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Computer-Aided Diagnostic System for Early Detection of Diabetic Retinopathy Using 3D-OCT Higher-Order Spatial Appearance Model
Authors: Elsharkawy Mohamed , Sharafeldeen Ahmed , Soliman Ahmed , Khalifa Fahmi , Ghazal Mohammed , El-Daydamony Eman , Atwan Ahmed , Sandhu Harpal Singh , El-Baz Ayman
Published: February 2022

Early diagnosis of diabetic retinopathy (DR) is of critical importance to suppress severe damage to the retina and/or vision loss. In this study, an optical coherence tomography (OCT)-based computer-aided diagnosis (CAD) method is proposed to detect DR early using structural 3D retinal scans. This system uses prior shape knowledge to automatically segment all retinal layers of the 3D-OCT scans using an adaptive, appearance-based method. After the segmentation step, novel texture features are extracted from the segmented layers of the OCT B-scans volume for DR diagnosis. For every layer, Markov–Gibbs random field (MGRF) model is used to extract the 2nd-order reflectivity. In order to represent the extracted image-derived features, we employ cumulative distribution function (CDF) descriptors. For layer-wise classification in 3D volume, using the extracted Gibbs energy feature, an artificial neural network (ANN) is fed the extracted feature for every layer. Finally, the classification outputs for all twelve layers are fused using a majority voting schema for global subject diagnosis. A cohort of 188 3D-OCT subjects are used for system evaluation using different k-fold validation techniques and different validation metrics. Accuracy of 90.56%, 93.11%, and 96.88% are achieved using 4-, 5-, and 10-fold cross-validation, respectively. Additional comparison with deep learning networks, which represent the state-of-the-art, documented the promise of our system’s ability to diagnose the DR early.
Effect of Subclinical Hypothyroidism on the Association between Hemoglobin A1c and Reduced Renal Function: A Prospective Study
Authors: Shimizu Yuji , Kawashiri Shin-Ya , Noguchi Yuko , Nakamichi Seiko , Nagata Yasuhiro , Maeda Takahiro , Hayashida Naomi
Published: February 2022

Subclinical hypothyroidism (SCH) was reported to be associated with accelerating endothelial dysfunction, which is recognized as one of the upstream mechanisms that leads to glomerular injury (lower glomerular filtration rate (GFR)). SCH was also reported to be associated with hyperglycemia, which is associated with higher hemoglobin A1c (HbA1c) levels and induces endothelial dysfunction. Therefore, SCH status could influence the association between HbA1c and reduced eGFR. To clarify those associations, we conducted a prospective study of 1580 Japanese individuals who participated in an annual health check-up in 2014 with 2.8 years of follow-up. All participants had free triiodothyronine (T3) and free thyroxine (T4) levels in the normal range. Among study participants, 88 were diagnosed as having SCH. Even though no significant correlation was observed between HbA1c and annual change in estimated GFR among participants without SCH (multi-adjusted standardized parameter estimate (β) = 0.03, p = 0.250), a significant inverse association was observed among participants with SCH (β = −0.26, p = 0.014). When those analyses were performed among participants who were not taking glucose lowering medication, the observed associations were essentially the same: β = 0.03, p = 0.266 for participants without SCH and β = −0.32, p = 0.006 for participants with SCH, respectively. Therefore, SCH status could influence the association between HbA1c and renal function.
Interpretable Clinical Decision Support System for Audiology Based on Predicted Common Audiological Functional Parameters (CAFPAs)
Authors: Buhl Mareike
Published: February 2022

Common Audiological Functional Parameters (CAFPAs) were previously introduced as abstract, measurement-independent representation of audiological knowledge, and expert-estimated CAFPAs were shown to be applicable as an interpretable intermediate layer in a clinical decision support system (CDSS). Prediction models for CAFPAs were built based on expert knowledge and one audiological database to allow for data-driven estimation of CAFPAs for new, individual patients for whom no expert-estimated CAFPAs are available. Based on the combination of these components, the current study explores the feasibility of constructing a CDSS which is as interpretable as expert knowledge-based classification and as data-driven as machine learning-based classification. To test this hypothesis, the current study investigated the equivalence in performance of predicted CAFPAs compared to expert-estimated CAFPAs in an audiological classification task, analyzed the importance of different CAFPAs for high and comparable performance, and derived explanations for differences in classified categories. Results show that the combination of predicted CAFPAs and statistical classification enables to build an interpretable but data-driven CDSS. The classification provides good accuracy, with most categories being correctly classified, while some confusions can be explained by the properties of the employed database. This could be improved by including additional databases in the CDSS, which is possible within the presented framework.
Lanthanum Carbonate Opacities—A Systematic Review
Authors: Kampmann Jan , Hansen Nina Pirschel , Ørsted Schultz Anders Nikolai , Brandt Andreas Hjelm , Brandt Frans
Published: February 2022

Background: Lanthanum carbonate is a phosphate binder used in advanced kidney disease. Its radiopaque appearance has been described in many case studies and case series. Misinterpretation of this phenomenon leads to unnecessary diagnostic tests and procedures. The objectives of this study were to summarize the literature on lanthanum carbonate opacities and present a visual overview. Methods: A systematic search was conducted using MEDLINE, Embase, and Web of Science. We included all types of studies, including case reports/studies, describing radiological findings of lanthanum carbonate opacities in patients with chronic kidney disease. No filter for time was set. Results: A total of 36 articles were eligible for data extraction, and 33 articles were included in the narrative synthesis. Lanthanum carbonate opacities were most commonly reported in the intestines (26 studies, 73%), stomach (8 studies, 21%), and the aerodigestive tract (2 studies, 6%). The opacities in the intestine were most frequently described as multiple, scattered radiopaque densities, compared with the aerodigestive tract, where the opacities were described as a single, round foreign body. Suspicion of contrast medium or foreign bodies was the most common differential diagnosis. LC opacities in patients with CKD are commonly misinterpreted as foreign bodies or suspect contrast media. Conclusions: CKD patients treated with LC may have opacities throughout the digestive tract that can vary in appearance. Stopping LC treatment or changing to an alternative phosphate binder prior to planned image studies can avoid diagnostic confusion. If this is not an option, knowledge of the presentation of LC opacities is important.
Tracking the Initial Diffusion of SARS-CoV-2 Omicron Variant in Italy by RT-PCR and Comparison with Alpha and Delta Variants Spreading
Authors: Caputo Valerio , Calvino Giulia , Strafella Claudia , Termine Andrea , Fabrizio Carlo , Trastulli Giulia , Ingrascì Arcangela , Peconi Cristina , Bardini Silvia , Rossini Angelo , Salvia Antonino , Borsellino Giovanna , Battistini Luca , Caltagirone Carlo , Cascella Raffaella , Giardina Emiliano
Published: February 2022

The emergence of the Omicron SARS-CoV-2 variant caused public health concerns worldwide, raising the need for the improvement of rapid monitoring strategies. The present manuscript aimed at providing evidence of the utility of a diagnostic kit for the routine testing of SARS-CoV-2 infection as a cost-effective method for tracking the Omicron variant in Italy. The study was conducted on patients’ naso-oropharyngeal-swab-derived RNA samples. These samples were subjected to RT-PCR using the TaqPath COVID-19 RT PCR CE IVD kit. Nonparametric testing and polynomial models fitting were used to compare the spreading of Alpha, Delta and Omicron variants. The samples of interest were correctly amplified and displayed the presence of S gene-target failure, suggesting that these patients carry the Omicron variant. The trend of diffusion was found to be significantly different and more rapid compared with that of the Alpha and Delta variants in our cohorts. Overall, these results highlight that the S gene target failure was a very useful tool for the immediate and inexpensive tracking of Omicron variant in the three weeks from the first detection. Thus, our approach could be used as a first-line screening to reduce the time and costs of monitoring strategies, facilitating the management of preventive and counteracting measures against COVID-19.
Radiomics Analysis of [18F]FDG PET/CT Thyroid Incidentalomas: How Can It Improve Patients’ Clinical Management? A Systematic Review from the Literature
Authors: Gherghe Mirela , Lazar Alexandra Maria , Mutuleanu Mario-Demian , Stanciu Adina Elena , Martin Sorina
Published: February 2022

Background: We performed a systematic review of the literature to provide an overview of the application of PET-based radiomics of [18F]FDG-avid thyroid incidentalomas and to discuss the additional value of PET volumetric parameters and radiomic features over clinical data. Methods: The most relevant databases were explored using an algorithm constructed based on a combination of terms related to our subject and English-language articles published until October 2021 were considered. Among the 247 identified articles, 19 studies were screened for eligibility and 11 met the criteria, with 4 studies including radiomics analyses. Results: We summarized the available literature based on a study of PET volumetric parameters and radiomics. Ten articles provided accurate details about volumetric parameters and their prospective value in tumour assessment. We included the data provided by these articles in a sub-analysis, but could not obtain statistically relevant results. Four publications analyzed the diagnostic potential of radiomics and the possibility of creating precise predictive models, their corresponding quality score being assessed. Conclusions: The use of PET volumetric parameters and radiomics analysis in patients with [18F]FDG-avid thyroid incidentalomas outlines a great prospect in diagnosis and stratification of patients with malignant nodules and may represent a way of limiting the need for unnecessary invasive procedures; however, further studies need to be performed for a standardization of the method.
Multimodal Characterization of a PSMA-Positive Thyroid Nodule Using 68Ga-PSMA and 124Iodine PET/US Fusion Imaging
Authors: Freesmeyer Martin , Gühne Falk , Drescher Robert , Winkens Thomas , Gassler Nikolaus , Seifert Philipp
Published: February 2022

A 54-year-old male diagnosed with prostate cancer was referred for 68Gallium-PSMA-11 PET/CT. The scan revealed a solitary PSMA-positive thyroid lesion. On PET/ultrasound fusion imaging, a nodule with moderate risk of malignancy (TIRADS 4B) could be unambiguously correlated. Additional 124Iodine PET/ultrasound fusion imaging revealed normal iodine uptake within the PSMA-positive thyroid nodule. Fine-needle aspiration cytology was performed using an ultrasound needle-guidance system. The cytopathological investigation confirmed a benign thyroid nodule and excluded a thyroid carcinoma as well as a prostate cancer metastasis. Immunohistochemistry was positive for thyroglobulin staining.
Implementation of a Rapid RT-LAMP Saliva-Based SARS-CoV-2 Testing Program in the Workplace
Authors: Cook Bradley W. M. , Kobasa Kaitlyn , Tamayo Marielou , Theriault Natasha , Gordon Pappas Diane , Theriault Steven S.
Published: February 2022

Rising SARS-CoV-2 cases, testing delays, and the risk of pre-symptomatic and asymptomatic transmission provided the impetus for an in-house rapid testing program. Employees and their household contacts were encouraged to self-collect saliva samples that were pooled for routine testing using an established colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay. In brief, individual or a maximum of four saliva samples were pooled and heat-inactivated to render microorganisms, especially SARS-CoV-2, non-infectious prior to being added to RT-LAMP assay tubes containing either the human sample control gene, RNase P, or a region of the SARS-CoV-2 gene, ORF1ab. During the second wave of SARS-CoV-2 infections in November 2020, two samples from an employee and a member of their household tested positive via RT-LAMP within two days of each other. A delayed clinical qRT-PCR test confirmation of both individuals 5 days later underscored the power of routine rapid testing with within-the-hour turnaround times. Workplace rapid testing programs using RT-LAMP are flexible in their design, have a reduced cost compared to qRT-PCR, may involve non-invasive self-saliva collection for increased safety for the testing personnel, and can be performed with minimal training.
The Prognostic Performance of Ferritin in Patients with Acute Myocardial Infarction: A Systematic Review
Authors: Brinza Crischentian , Floria Mariana , Popa Iolanda Valentina , Burlacu Alexandru
Published: February 2022

The potential benefit of ferritin evaluation resides in its association with adverse outcomes in patients with various pathological conditions. We aimed to conduct the first systematic review evaluating the association between ferritin levels and adverse cardiovascular outcomes in patients with acute myocardial infarction (AMI) during short- or long-term follow-up. Seven studies investigating various endpoints (mortality, major adverse cardiovascular events-MACE, the decline of the left ventricular ejection fraction-LVEF, left ventricular aneurysm development-LVA) were included. AMI patients with low or increased ferritin values tended to have higher in-hospital and 30-day mortality rates. Low and high ferritin levels and chronic kidney disease were independently associated with increased risk of LVA formation. High ferritin concentrations were linked to an accentuated LVEF decline in ST-elevation myocardial infarction patients treated by percutaneous coronary intervention. Both low and high ferritin values were also associated with the duration of hospitalization in patients with AMI during hospital stay and at more extended follow-up. Ferritin evaluation represents a simple investigation that could identify high-risk patients with AMI who might benefit from closer monitoring and specific therapeutic interventions. These data should be confirmed in large trials in the context of currently available therapies for heart failure and AMI.
Concordance between Three PD-L1 Immunohistochemical Assays in Head and Neck Squamous Cell Carcinoma (HNSCC) in a Multicenter Study
Authors: Guerini Rocco Elena , Eccher Albino , Girolami Ilaria , Graziano Paolo , Fontanini Gabriella , Vigliar Elena , Troncone Giancarlo , Barberis Massimo , Morbini Patrizia , Martini Maurizio
Published: February 2022

The introduction of immunotherapy targeting the programmed death-1 (PD-1)/programmed death-ligand-1 (PD-L1) axis has represented a turning point in the treatment of HNSCC. Harmonization studies comparing the different antibodies and immunohistochemistry platforms available for the evaluation of PD-L1 expression with Combined Positive Score (CPS) in HNSCC are strongly required. Tissue microarrays (TMA) constructed from formalin-fixed, paraffin-embedded (FFPE) tissue blocks of HNSCC tumor were stained with two commercial in-vitro diagnostic (IVD) PD-L1 immunohistochemical assays (22C3 pharmDx on Autostainer Link48 and Omnis platforms, and SP263) and were reviewed by seven trained pathologists to assess CPS. We found a very similar distribution for PD-L1 expression between 22C3 pharmDx assay with both platforms and SP263 assay and a strong significant correlation between the two assays in different platforms (p < 0.0001). The interobserver reliability among pathologists for the continuous scores of CPS with intraclass correlation coefficient (ICC) and the correlation between the two assays were both good. Moreover, the agreement rate between assays was high at all cut-offs, while the kappa values were from substantial to almost perfect. These data suggest the interchangeability of the two antibodies and of the different immunohistochemical platforms in the selection of patients with HNSCC for immunotherapy.
Improving the EHMRG Prognostic Evaluation of Acute Heart Failure with TAPSE/PASp: A Sequential Approach
Authors: Falsetti Lorenzo , Zaccone Vincenzo , Viticchi Giovanna , Fioranelli Agnese , Diblasi Ilaria , Guerrieri Emanuele , Ferrini Consuelo , Scarponi Mattia , Giuliani Luca , Scalpelli Caterina , Martino Marianna , Pansoni Adolfo , Luccarini Marinella , Burattini Maurizio , Moroncini Gianluca , Tarquinio Nicola
Published: February 2022

The Emergency Heart Failure Mortality Risk Grade (EHMRG) can predict short-term mortality in patients admitted for acute heart failure (AHF) in the emergency department (ED). This paper aimed to evaluate if TAPSE/PASp, an echocardiographic marker of ventricular desynchronization, can improve in-hospital death prediction in patients at moderate-to-high risk, according to EHMRG score classification. From 1 January 2018 to 30 December 2019, we retrospectively enrolled all the consecutive subjects admitted to our Internal Medicine Department for AHF from the ED. We performed bedside echocardiography within the first 24 h of admission. We evaluated EHMRG and NYHA in the ED, days of admission in Internal Medicine, and in-hospital mortality. We assessed cutoffs with ROC curve analysis and survival with Kaplan–Meier and Cox regression. We obtained a cohort of 439 subjects; 10.3% underwent in-hospital death. Patients with normal TAPSE/PASp in EHMRG Classes 4, 5a, and 5b had higher survival rates (100%, 100%, and 94.3%, respectively), while subjects with pathologic TAPSE/PASp had lower survival rates (81.8%, 78.3%, and 43.4%, respectively) (p < 0.0001, log-rank test). TAPSE/PASp, an echocardiographic marker of ventricular desynchronization, can further stratify the risk of in-hospital death evaluated by EHMRG.
Alcohol Consumption and the Risk of Incident Atrial Fibrillation: A Meta-Analysis
Authors: Giannopoulos Georgios , Anagnostopoulos Ioannis , Kousta Maria , Vergopoulos Stavros , Deftereos Spyridon , Vassilikos Vassilios
Published: February 2022

Alcohol consumption is a known, modifiable risk factor for incident atrial fibrillation (AF). However, it remains unclear whether the protective effect of moderate alcohol consumption-that has been reported for various cardiovascular diseases also applies to the risk for new-onset AF. The purpose of this meta-analysis was to evaluate the role of different drinking patterns (low: <14 grams/week; moderate: <168 grams/week; and heavy: >168 grams/week) on the risk for incident AF. Major electronic databases were searched for observational cohorts examining the role of different drinking behaviors on the risk for incident AF. We analyzed 16 studies (13,044,007 patients). Incident AF rate was 2.3%. Moderate alcohol consumption significantly reduced the risk for new-onset AF when compared to both abstainers (logOR: −0.20; 95%CI: −0.28–−0.12; I2: 96.71%) and heavy drinkers (logOR: −0.28; 95%CI: −0.37–−0.18; I2: 95.18%). Heavy-drinking pattern compared to low also increased the risk for incident AF (logOR: 0.14; 95%CI: 0.01–0.2; I2: 98.13%). Substantial heterogeneity was noted, with more homogeneous results documented in cohorts with follow-up shorter than five years. Our findings suggest a J-shaped relationship between alcohol consumption and incident AF. Up to 14 drinks per week seem to decrease the risk for developing AF. Because of the substantial heterogeneity observed, no robust conclusion can be drawn. In any case, our results suggest that the association between alcohol consumption and incident AF is far from being a straightforward dose-response effect.
Vedolizumab Attenuates Immune-Checkpoint-Therapy-Induced Infliximab-Refractory Colitis
Authors: Kaneoka Ayaka , Okada Etsuko , Sugino Hitomi , Saito-Sasaki Natsuko , Omoto Daisuke , Nakamura Motonobu
Published: February 2022

Immune checkpoint inhibitors (ICIs), such as nivolumab and ipilimumab, have drastically changed treatments of advanced melanoma. However, ICI-related enterocolitis is often the most common adverse event, and represents the main reason for ICI discontinuation and mortalities. Here, we report the case of a metastatic melanoma treated with vedolizumab for ICI-induced colitis. A 67-year-old man treated with ipilimumab and nivolumab developed ICI-induced colitis and grade 3 diarrhea refractory to methylprednisolone and infliximab. After his third dose of vedolizumab, oral prednisolone ceased, and the colitis had completely resolved with no recurrence. This case report supports vedolizumab use in treating severe colitis which failed to resolve with first- and second-line immunosuppressive therapy.
Early Diagnosis of Acute Myocarditis in the ED: Proposal of a New ECG-Based Protocol
Authors: Piazza Isabelle , Ferrero Paolo , Marra Alessio , Cosentini Roberto
Published: February 2022

The diagnosis of acute myocarditis (AM) is based on a multi-parametric assessment including clinical presentation, ECG, imaging and biomarkers. Fragmented QRS (fQRS) might be an additional diagnostic sign in patients with proven AM. The main objective of this study was to assess the diagnostic yield of fQRS in patients with suspected AM presenting to the emergency department (ED). Patients admitted between January 2016 and March 2021 with a proven diagnosis of AM, according to clinical, cardiac magnetic resonance (CMR) and/or histologic criteria, were included in the analysis. In total, 51 patients were analyzed (41 men, 78%), with a median age of 36 (29–45) years. Thirty-three (65%) patients had prodromal flu-like symptoms. Patients presented to the ED mostly complaining of chest pain (68%) and palpitations (21%). Seven (14%) patients experienced cardiac arrest, one of whom died. At presentation, 40 patients (78%) displayed fQRS, and 10 (20%) presented ventricular arrhythmias. All the surviving patients underwent CMR and displayed late gadolinium enhancement (LGE). ECG leads showed that fQRS matched the LGE distribution in 38 patients (95%). The presence of fQRS is a simple clinical bedside tool to support the initial suspect of AM in the emergency department and to guide the most appropriate clinical workup.
Editorial of Special Issue “Multiple Sclerosis: From Diagnostic Biomarkers to Imaging and Clinical Predictors”
Authors: Jakimovski Dejan , Zivadinov Robert
Published: February 2022

Multiple sclerosis (MS) is a chronic, neuroinflammatory and neurodegenerative disease of the central nervous system (CNS) that can present with a plethora of physical and cognitive impairments [...]
Harmonization of Determination of SARS-CoV-2 Antibodies: Is It Always Possible?
Authors: Dittadi Ruggero
Published: February 2022

A WHO standard was prepared with the aim of harmonizing assays detecting antibodies against SARS-CoV-2, but the issue is currently being debated. We re-evaluated a previously studied set of cases (108 specimens of 48 patients and 60 specimens of 20 vaccinated subjects, collected after 14 days from the first dose and 14 days and 3 months after a second dose of the Comirnaty BNT162b2 vaccine), calculating the ratios between the results of two methods (SARS-CoV-2 IgG anti-RBD, SNIBE, and anti-SARS-CoV-2 QuantiVac ELISA IgG, Euroimmun). In the vaccinated subjects, the ratios of the results between methods according to the WHO standard were relatively dispersed, but the harmonization results were good. On the other hand, in patient samples, the variability between tests was very high, and the harmonization was unsatisfactory (median ratios between methods 2.23, 10th–90th percentile: 1.1–5.6). Interestingly, in patient samples, the harmonization depends on the time from the onset of symptoms and greatly improves after 6 months since the diagnosis. Forty patient specimens and thirty-one of the vaccinated subjects after the second dose were also evaluated with a third method (Access SARS-CoV-2 IgG (1st IS), Beckman Coulter), obtaining a similar trend. We can conclude that the actual effectiveness of harmonization between methods may vary depending on the scenario in which they will be used.
Survey on Fatigue Life Prediction of BGA Solder Joints
Authors: Qiu Baojun , Xiong Jingang , Wang Han , Zhou Shuai , Yang Xiuding , Lin Zhengpei , Liu Maolin , Cai Nian
Published: February 2022

With the development of science and technology, consumers’ requirements for various electronic devices present a trend of more diverse functions and thinner bodies. This makes integrated circuits mounted in electronic products and their packaging more vital to satisfying the above requirements. Ball grid array (BGA) packaging is widely used in the field of microelectronic manufacturing industries due to its multiple I/O volumes and excellent electric characteristics. However, due to environmental loads such as vibration and impact during its production and application, defects inevitably emerge in BGA solder joint defects, which will lead to the failure of electronic products. This article summarizes the state-of-the-art research on the factors, analysis methods, and models for the fatigue failure of BGA chips. After rigorous discussions concerning this research, some theoretical suggestions are provided for BGA packaging in reliability analysis and the establishment of evaluation standards.
Enhancing Knowledge of Propagation-Perception-Based Attention Recommender Systems
Authors: Zhang Hanzhong , Wang Yinglong , Chen Chao , Liu Ruixia , Zhou Shuwang , Gao Tianlei
Published: February 2022

Researchers have introduced side information such as social networks or knowledge graphs to alleviate the problems of data sparsity and cold starts in recommendation systems. However, most of the methods ignore the exploration of feature differentiation aspects in the knowledge propagation process. To solve the above problem, we propose a new attention recommendation method based on an enhanced knowledge propagation perception. Specifically, to capture user preferences in a fine-grained manner in a knowledge graph, an asymmetric semantic attention mechanism is adopted. It identifies the influence of propagation neighbors on user preferences through a more precise representation of the preference semantics for head and tail entities. Furthermore, in consideration of the memory and generalization of different propagation depth features and adaptively adjusting the propagation weights, a new propagation feature exploration framework is designed. The performance of the proposed model is validated by two real-world datasets. The baseline model averagely increases by 9.65% and 9.15% for the Area Under Curve (AUC) and Accuracy (ACC) indicators, which proves the effectiveness of the model.
Compressed Complex-Valued Least Squares Support Vector Machine Regression for Modeling of the Frequency-Domain Responses of Electromagnetic Structures
Authors: Soleimani Nastaran , Trinchero Riccardo
Published: February 2022

This paper deals with the development of a Machine Learning (ML)-based regression for the construction of complex-valued surrogate models for the analysis of the frequency-domain responses of electromagnetic (EM) structures. The proposed approach relies on the combination of two-techniques: (i) the principal component analysis (PCA) and (ii) an unusual complex-valued formulation of the Least Squares Support Vector Machine (LS-SVM) regression. First, the training and test dataset is obtained from a set of parametric electromagnetic simulations. The spectra collected in the training set are compressed via the PCA by exploring the correlation among the available data. In the next step, the compressed dataset is used for the training of compact set of complex-valued surrogate models and their accuracy is evaluated on the test samples. The effectiveness and the performance of the complex-valued LS-SVM regression with three kernel functions are investigated on two application examples consisting of a serpentine delay structure with three parameters and a high-speed link with four parameters. Moreover, for the last example, the performance of the proposed approach is also compared with those provided by a real-valued multi-output feedforward Neural Network model.
Application Strategies of Model Predictive Control for the Design and Operations of Renewable Energy-Based Microgrid: A Survey
Authors: Konneh Keifa Vamba , Adewuyi Oludamilare Bode , Lotfy Mohammed Elsayed , Sun Yanxia , Senjyu Tomonobu
Published: February 2022

In recent times, Microgrids (MG) have emerged as solution approach to establishing resilient power systems. However, the integration of Renewable Energy Resources (RERs) comes with a high degree of uncertainties due to heavy dependency on weather conditions. Hence, improper modeling of these uncertainties can have adverse effects on the performance of the microgrid operations. Due to this effect, more advanced algorithms need to be explored to create stability in MGs’. The Model Predictive Control (MPC) technique has gained sound recognition due to its flexibility in executing controls and speed of processors. Thus, in this review paper, the superiority of MPC to several techniques used to model uncertainties is presented for both grid-connected and islanded system. It highlights the features, strengths and incompetencies of several modeling methods for MPCs and some of its variants regarding handling of uncertainties in MGs. This survey article will help researchers and model developers to come up with more robust model predictive control algorithms and techniques to cope with the changing nature of modern energy systems, especially with the increasing level of RERs penetration.
Dynamically-Tunable Dataflow Architectures Based on Markov Queuing Models
Authors: Tibaldi Mattia , Palermo Gianluca , Pilato Christian
Published: February 2022

Dataflow architectures are fundamental to achieve high performance in data-intensive applications. They must be optimized to elaborate input data arriving at an expected rate, which is not always constant. While worst-case designs can significantly increase hardware resources, more optimistic solutions fail to sustain execution phases with high throughput, leading to system congestion or even computational errors. We present an architecture to monitor and control dataflow architectures that leverage approximate variants to trade off accuracy and latency of the computational processes. Our microarchitecture features online prediction based on queuing models to estimate the response time of the system and select the proper variant to meet the target throughput, enabling the creation of dynamically-tunable systems.
Machine-Learning-Based Darknet Traffic Detection System for IoT Applications
Authors: Abu Al-Haija Qasem , Krichen Moez , Abu Elhaija Wejdan
Published: February 2022

The massive modern technical revolution in electronics, cognitive computing, and sensing has provided critical infrastructure for the development of today’s Internet of Things (IoT) for a wide range of applications. However, because endpoint devices’ computing, storage, and communication capabilities are limited, IoT infrastructures are exposed to a wide range of cyber-attacks. As such, Darknet or blackholes (sinkholes) attacks are significant, and recent attack vectors that are launched against several IoT communication services. Since Darknet address space evolved as a reserved internet address space that is not contemplated to be used by legitimate hosts globally, any communication traffic is speculated to be unsolicited and distinctively deemed a probe, backscatter, or misconfiguration. Thus, in this paper, we develop, investigate, and evaluate the performance of machine-learning-based Darknet traffic detection systems (DTDS) in IoT networks. Mainly, we make use of six supervised machine-learning techniques, including bagging decision tree ensembles (BAG-DT), AdaBoost decision tree ensembles (ADA-DT), RUSBoosted decision tree ensembles (RUS-DT), optimizable decision tree (O-DT), optimizable k-nearest neighbor (O-KNN), and optimizable discriminant (O-DSC). We evaluate the implemented DTDS models on a recent and comprehensive dataset, known as the CIC-Darknet-2020 dataset, composed of contemporary actual IoT communication traffic involving four different classes that combine VPN and Tor traffic in a single dataset covering a wide range of captured cyber-attacks and hidden services provided by the Darknet. Our empirical performance analysis demonstrates that bagging ensemble techniques (BAG-DT) offer better accuracy and lower error rates than other implemented supervised learning techniques, scoring a 99.50% of classification accuracy with a low inferencing overhead of 9.09 µ second. Finally, we also contrast our BAG-DT-DTDS with other existing DTDS models and demonstrate that our best results are improved by (1.9~27%) over the former state-of-the-art models.
Full-Reference Image Quality Assessment Based on Grünwald–Letnikov Derivative, Image Gradients, and Visual Saliency
Authors: Varga Domonkos
Published: February 2022

The purpose of image quality assessment is to estimate digital images’ perceptual quality coherent with human judgement. Over the years, many structural features have been utilized or proposed to quantify the degradation of an image in the presence of various noise types. Image gradient is an obvious and very popular tool in the literature to quantify these changes in the images. However, gradient is able to characterize images locally. On the other hand, results from previous studies indicate that global contents of a scene are analyzed before the local features by the human visual system. Relying on these features of the human visual system, we propose a full-reference image quality assessment metric that characterizes the global changes of an image by the Grünwald–Letnikov derivatives and the local changes by image gradients. Moreover, visual saliency is also utilized for weighting the changes in the images and emphasizing those areas of the image which are salient to the human visual system. To prove the efficiency of the proposed method, massive experiments were carried out on publicly available benchmark image quality assessment databases.
Near-Nyquist-Limit Optical Communication and Ranging Method Based on Waveform Matched PPM
Authors: Hu Chunyuan , Lin Yujie , Li Jianguo , Bu Xiangyuan , An Jianping
Published: February 2022

Deep-space optical communication and ranging technologies have attracted much attention for satellite-to-earth and moon-to-earth exploration. In integrated communication and ranging scenarios, non-integer oversampling factors are employed to improve the ranging performance, which can cause accumulated timing errors. We propose a novel pulse position modulation (PPM) symbol decision method based on waveform matching to reduce the impact of accumulated timing errors near the Nyquist sampling limit. Simulation results demonstrate that the ranging accuracy can reach 2.6 and 0.52 mm at sampling rates of 625 Msps and 2.5 Gsps, respectively. The proposed symbol decision method has a gain of over 1.1 dB compared with the traditional method at the bit error rate (BER) of less than 10−6. The experimental results verify that this method can achieve high-precision measurements of distance and reliable transmission of information.
Intelligent Load-Balancing Framework for Fog-Enabled Communication in Healthcare
Authors: Malik Swati , Gupta Kamali , Gupta Deepali , Singh Aman , Ibrahim Muhammad , Ortega-Mansilla Arturo , Goyal Nitin , Hamam Habib
Published: February 2022

The present technological era significantly makes use of Internet-of-Things (IoT) devices for offering and implementing healthcare services. Post COVID-19, the future of the healthcare system is highly reliant upon the inculcation of Artificial-Intelligence (AI) mechanisms in its day-to-day procedures, and this is realized in its implementation using sensor-enabled smart and intelligent IoT devices for providing extensive care to patients relative to the symmetric concept. The offerings of such AI-enabled services include handling the huge amount of data processed and sensed by smart medical sensors without compromising the performance parameters, such as the response time, latency, availability, cost and processing time. This has resulted in a need to balance the load of the smart operational devices to avoid any failure of responsiveness. Thus, in this paper, a fog-based framework is proposed that can balance the load among fog nodes for handling the challenging communication and processing requirements of intelligent real-time applications.
Stability Analysis of Chaotic Grey-Wolf Optimized Grid-Tied PV-Hybrid Storage System during Dynamic Conditions
Authors: Chankaya Mukul , Hussain Ikhlaq , Ahmad Aijaz , Malik Hasmat , Alotaibi Majed A.
Published: February 2022

This paper presents the stability improvement of the three-phase four-wire (3P-4W) grid-tied PV-hybrid energy storage system (HESS) using chaotic grew wolf optimization (CGWO) for DC bus voltage (Vdc) and AC bus voltage (Vpcc) control. The CGWO tuned fractional order proportional–integral (FOPI) controllers reduce the Vdc and Vpcc variations during diverse, dynamic conditions, i.e., sudden irradiation variations, deep voltage sag/swell, etc. The DC bus is responsible for the current injection/extraction control, maximum PV power extraction, bi-directional power flow, dc second-harmonics component elimination, and active power balance. At the point of common coupling (PCC), the AC bus is accountable for bi-directional power flow and active and reactive power control. The two-level voltage source converter (VSC) is controlled by a novel variable step-size incremental least mean square (VSS-ILMS) in zero voltage regulation (ZVR) mode. Due to its varying step size, VSC control is less prone to noise signals offers better stability, improved convergence rate, dc offset rejection, and tracking speed during dynamics, i.e., large oscillations. A battery and ultracapacitor are coupled to the DC link by buck-boost converters in the HESS. To regulate power transit between the DC bus and the grid, the HESS current control technique is designed to shift frequently from charging to discharging stage and vice versa. The novelty of the PV-HESS system lies in CGWO tuned VSS-ILMS control of VSC, which effectively and efficiently filter out the active fundamental constituents of load current and eliminate dc offset from VSC output. The HESS control maintains the DC bus voltage profile by absorbing and delivering energy (during dynamic conditions) rather than curtailing it. The presented system is simulated in a MATLAB/SIMULINK environment. The simulation results in graphical and numerical forms verify the stable and satisfactory operation of the proposed system as per IEEE519 standard.
Research on Capacity Allocation Optimization of Commercial Virtual Power Plant (CVPP)
Authors: Wang Songkai , Jia Rong , Shi Xiaoyu , Luo Chang , An Yuan , Huang Qiang , Guo Pengcheng , Wang Xueyan , Lei Xuewen
Published: February 2022

Commercial virtual power plants (CVPP) connect the form of renewable energy resource portfolio to the power market and reduce the risk of the unstable operation of a single renewable energy. Combining different kinds of large-scale renewable energy in CVPP to provide capacity services like base load, peak shaving, and valley-filling, etc., for the system loads is an urgent problem to be solved. Therefore, it is valuable to analyze the capacity allocation ratio of the CVPP to maximize the utilization of all kinds of energy, especially for the large-scale multi-energy base. This paper proposed a multi-energy coordinated operation framework by considering various load demands, including base load and peak shaving for the capacity allocation of CVPP based on the world’s largest renewable energy resource base on the upstream area of the Yellow River. The main procedures of this framework are as follows: (1) A paratactic model satisfying base load and peak shaving is proposed to determine the ability of the CVPP operation model’s capacity services to meet the different demands of the power system load. (2) A hybrid dimension reduction algorithm with a better convergence rate and optimization effect solves the proposed paratactic model based on the ReliefF and the Adaptive Particle Swarm Optimization (APSO). The results show that the large-scale CVPP with different compositions can achieve both of the goals of a stable base load output and stable residual load under different weather conditions. Compared with the operation on sunny days, the base load fluctuation and residual load fluctuation of CVPP on rainy days are reduced by 14.5% and 21.9%, respectively, proving that CVPP can alleviate renewable energy’s dependence on weather and improve energy utilization.
A Methodological Proposal for Implementing Demand-Shifting Strategies in the Wholesale Electricity Market
Authors: Domínguez-Garabitos Máximo A. , Ocaña-Guevara Víctor S. , Santos-García Félix , Arango-Manrique Adriana , Aybar-Mejía Miguel
Published: February 2022

The energy transition has shown that fossil generation can be complemented with renewable energy and other resources capable of providing flexibility to the energy system’s operation, in compliance with the wholesale electricity market’s rules. This paper proposes a market-based methodology for introducing flexible demand in the energy dispatch, optimizing the scheduling of electricity system operation in the short-term, and considers the challenge of implementing an incentive scheme for participants in demand-response programs. The scheme includes the criteria of the elasticity of substitution and a renewable energy quota. This methodology is focused on a strategic demand shift to minimize the cost of supply; increase the dispatch of renewable energy; control CO2 emissions; and satisfy the generation, demand, and transmission operating constraints. These conditions encourage the development of a simulation tool that allows a sensitivity analysis to aid decision-making by operators and agents. The proposed methodology optimizes the operational cost of generation supply and specific performance indicators to determine the percentages of demand shift, the amount of CO2 emissions, the ratio of unserved power, the demand benefits obtained from an incentive scheme, and the natural market behavior.
Experimental Study on Temporal and Spatial Evolutions of Temperature Field of Double-Pipe Freezing in Saline Stratum with a High Velocity
Authors: Rong Chuanxin , Sun Shicheng , Cheng Hua , Duan Yin , Yang Fan
Published: February 2022

Freezing construction in saline stratum under the action of groundwater is typical. To study the coupling effect of the groundwater velocity and salinity on the freezing in saline stratum, the freezing temperature of saline sand with different salinities was obtained through experiments. A controllable velocity double-pipe freezing physical model test system for saline sand was established. The temperature distribution in saturated saline sand under different salinities and velocities were studied. The test results showed that the temporal and spatial evolutions of the temperature field were affected by the velocity and salinity. Under the same boundary temperature, the higher the salinity, the lower the temperature at the measuring point on the main surface and interface. The overlapping time varies significantly. The analysis results showed that the larger velocity and the higher the salinity, the longer the overlapping time. The velocity and salinity inhibited the development of the frozen curtain. Under different test conditions, the development rate of the freezing curtain area was in the range of 3987–15,246 mm2/h.
Activities Undertaken in the Member Cities of the Polish National Cittaslow Network in the Area of “Energy and Environmental Policy”
Authors: Wierzbicka Wioletta
Published: February 2022

Cittaslow is a network of small cities which have adopted the assumptions of the “slow city” model and strive towards the improvement of the quality of life for their residents. This is a network of cities which put pro-social and pro-environmental measures in the first place, while ensuring that the unique character of every city is preserved. A city which wishes to join the Cittaslow network must go through the so-called certification process and satisfy a number of criteria classified in seven macro-areas, including the “energy and environmental policy” area. Significantly, after becoming a member of the network, the city is obligated to carry out activities that will enable it to meet the membership criteria to a higher degree, and in particular to satisfy the criteria it has previously failed to meet. Considering the above, the aim of this study has been to evaluate the activities initiated and implemented by the member cities of the Polish Cittaslow network in the sphere of the “energy and environmental policy”. A comparative analysis was made of the results of certification before entering the network and the results of recertification that each city underwent after five years of its membership. The study shows that, even in the first five years following their access to the network, the cities were able to implement many projects dedicated to the protection of environmental, reduced consumption of electricity and use of alternative energy sources as well as improvement in the ecological awareness of city inhabitants. This is reflected by a higher degree to which these cities meet the certification criteria in this field, from 71% to 75%.
Structural Architecture and Permeability Patterns of Crystalline Reservoir Rocks in the Northern Upper Rhine Graben: Insights from Surface Analogues of the Odenwald
Authors: Bossennec Claire , Seib Lukas , Frey Matthis , van der Vaart Jeroen , Sass Ingo
Published: February 2022

Fracture network is a crucial element to address in any model of the thermo-hydro-mechanical behaviour of a reservoir rock. This study aims to provide quantified datasets and a further understanding of the critical parameters of the fracture network pattern in crystalline rocks. In the Northern Upper Rhine Graben, such rock units are targeted for multiple energy applications, from deep geothermal heat extraction to heat storage. Eleven outcrops were investigated with a combined LiDAR and 2D profiles analysis to extract faults and fracture network geometrical parameters, including length distribution, orientation, connectivity, and topology. These properties are used to decipher the structural architecture and estimate the flow properties of crystalline units. Fracture networks show a multi-scale power-law behaviour for length distribution. Fracture topology and orientation are mainly driven by both fault networks and lithology. Fracture apertures and permeability tensors were then calculated for two application case studies, including the stress field effect on aperture. Obtained permeabilities are in the range of those observed in the sub-surface in currently exploited reservoirs. The dataset provided in this study is thus suitable to be implemented in the modelling during the exploration stage of industrial applications involving fractured crystalline reservoirs.