bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Rapid and Automated Antigen Detection Tests for the Diagnosis of SARS-CoV-2 Infection
Authors: Petonnet Dorian , Marot Stéphane , Leroy Isabelle , Cohier Julien , Ramahefasolo Charline , Mansaly Safietou , Calvez Vincent , Marcelin Anne-Geneviève , Burrel Sonia
Published: January 2022

SARS-CoV-2 viral antigen detection may be an interesting alternative to RT-PCR for the diagnosis of SARS-CoV-2 infection as a less laborious or expensive method but requires validation. This study aimed to compare the performance of the DiaSorin™ LiaisonXL automated quantitative antigen test (QAT) and the AAZ™ rapid antigen test (RAT) to the DiaSorin™ MDX RT-PCR assay. A total of 242 nasopharyngeal samples were tested at La Pitié-Salpêtrière University Hospital (Paris, France). Performances for the detection of variants of SARS-CoV-2 were further investigated. RATs were visually read for qualitative results and band intensity was determined. Overall sensitivity was 63.2% for QAT and 58.6% for RAT. For RT-PCR Ct value 25, sensitivity was 89.8% for both tests. Both tests showed comparable sensitivity for detection of variants. There was a strong relationship between antigen concentration and band positivity. On the same set of samples these tests share similar performances.
Biasing Influence of ‘Mental Shortcuts’ on Diagnostic Decision-Making: Radiologists Can Overlook Breast Cancer in Mammograms When Prior Diagnostic Information Is Available
Authors: Branch Fallon , Santana Isabella , Hegdé Jay
Published: January 2022

When making decisions under uncertainty, people in all walks of life, including highly trained medical professionals, tend to resort to using ‘mental shortcuts’, or heuristics. Anchoring-and-adjustment (AAA) is a well-known heuristic in which subjects reach a judgment by starting from an initial internal judgment (‘anchored position’) based on available external information (‘anchoring information’) and adjusting it until they are satisfied. We studied the effects of the AAA heuristic during diagnostic decision-making in mammography. We provided practicing radiologists (N = 27 across two studies) a random number that we told them was the estimate of a previous radiologist of the probability that a mammogram they were about to see was positive for breast cancer. We then showed them the actual mammogram. We found that the radiologists’ own estimates of cancer in the mammogram reflected the random information they were provided and ignored the actual evidence in the mammogram. However, when the heuristic information was not provided, the same radiologists detected breast cancer in the same set of mammograms highly accurately, indicating that the effect was solely attributable to the availability of heuristic information. Thus, the effects of the AAA heuristic can sometimes be so strong as to override the actual clinical evidence in diagnostic tasks.
Practical Guidelines for Diagnosing and Treating Thyroid Disease Based on the WOMED Metabolic Model of Disease Focusing on Glycolysis and Coenzyme Q10 Deficiency—A Clinical Alternative to the 2021 Retired Clinical Practice Guidelines of the Endocrine Society
Authors: Moncayo Roy , Moncayo Helga
Published: January 2022

This review aims to provide a functional, metabolic view of the pathogenesis of benign thyroid disease. Here, we summarize the features of our previous publications on the “WOMED model of benign thyroid disease”. As of 2021, the current state of art indicates that the basic alteration in benign thyroid disease is a metabolic switch to glycolysis, which can be recognized using 3D-power Doppler ultrasound. A specific perfusion pattern showing enlarged vessels can be found using this technology. This switch originates from an altered function of Complex I due to acquired coenzyme Q10 deficiency, which leads to a glycolytic state of metabolism together with increased angiogenesis. Implementing a combined supplementation strategy that includes magnesium, selenium, and CoQ10, the morphological and perfusion changes of the thyroid can be reverted, i.e., the metabolic state returns to oxidative phosphorylation. Normalization of iron levels when ferritin is lower than 50 ng/mL is also imperative. We propose that a modern investigation of probable thyroid disease requires the use of 3D-power Doppler sonography to recognize the true metabolic situation of the gland. Blood levels of magnesium, selenium, CoQ10, and ferritin should be monitored. Thyroid function tests are complementary so that hypo- or hyperthyroidism can be recognized. Single TSH determinations do not reflect the glycolytic state.
Renal and Inflammation Markers—Renalase, Cystatin C, and NGAL Levels in Asymptomatic and Symptomatic SARS-CoV-2 Infection in a One-Month Follow-Up Study
Authors: Serwin Natalia , Cecerska-Heryć Elżbieta , Pius-Sadowska Ewa , Serwin Karol , Niedźwiedź Anna , Wiśniewska Magda , Roszak Marta , Grygorcewicz Bartłomiej , Skwirczyńska Edyta , Machaliński Bogusław , Dołęgowska Barbara
Published: January 2022

The aim of our study was to evaluate the influence of asymptomatic infection and the occurrence of symptomatic COVID-19 on specific biochemical, renal, and immune parameters—renalase, neutrophil gelatinase-associated lipocalin (NGAL) cystatin C (CysC), and creatinine—and their weekly fluctuations during a one-month observation period in COVID-19 patients admitted to hospital. The study involved 86 individuals: 30 patients with diagnosed COVID-19, 28 people with asymptomatic infection confirmed with IgG antibodies—the IG(+) group—and 28 individuals without any (IgG, IgE) anti-SARS-CoV-2 antibodies—the IG(−) group. In the COVID-19 group, blood was drawn four times: (1) on day 0/1 after admission to hospital (C1 group), (2) 7 days later (C7 group), (3) 14 days later (C14 group), and (4) 28 days later (C28 group). In the IG(−) and IG(+) groups, blood was drawn once. There were no significant differences in creatinine, Cys C, and uric acid between any of the analyzed groups. NGAL levels were significantly higher in IG(+) and at all time-points in the COVID-19 groups than in controls. A similar observation was made for renalase at the C7, C14, and C28 time-points. Plasma renalase, NGAL, and CysC are unrelated to kidney function in non-critically ill COVID-19 patients and those with asymptomatic infection. Renalase and NGAL are most likely related to the activation of the immune system rather than kidney function. Asymptomatic SARS-CoV-2 infection causes a rise in plasma NGAL levels similar to those observed in symptomatic COVID-19 patients. Therefore, more attention should be paid to tracking and monitoring the health of these people.
Information Processing Speed Assessed with Letter Digit Substitution Test in Croatian Sample of Multiple Sclerosis Patients
Authors: Jerković Ana , Matijaca Meri , Proroković Ana , Šikić Anđela , Košta Vana , Ćurković Katić Ana , Dolić Krešimir , Duka Glavor Klaudia , Šoda Joško , Đogaš Zoran , Rogić Vidaković Maja
Published: January 2022

Cognitive impairment is a common complaint in people with multiple sclerosis (pwMS). The study objective was to determine the psychometric properties of the letter digit substitution test (LDST) that measures information processing speed and to investigate the impact of relevant predictors of LDST achievement in pwMS. The design was cross-sectional. The study included 87 pwMS and 154 control subjects. The validity of LDST was examined, and a hierarchical regression model was used to explore relevant predictors of LDST success. The LDST had excellent construct validity, as expressed by differences between pwMS and control subjects. Convergent validity of the LDST was supported by a significant moderate correlation with the expanded disability status scale (EDSS) (ρ = −0.36; p < 0.05) and a significantly strong correlation with the multiple sclerosis impact scale (MSIS-29) physical subscale (r = −0.64; p < 0.01). The LDTS score well differentiated the pwMS considering age, education, EDSS, disease duration, comorbidity, and medication therapy. Using the LDST as a criterion variable in pwMS results showed consistent evidence for the age, education, and EDSS impact on LDST performance. The best cut-off score of ≤35 discriminated the control and MS group. LDST proved to be a valid test for assessing information processing speed in pwMS.
Parkinson’s Disease Subtyping Using Clinical Features and Biomarkers: Literature Review and Preliminary Study of Subtype Clustering
Authors: Lee Seung Hyun , Park Sang-Min , Yeo Sang Seok , Kwon Ojin , Lee Mi-Kyung , Yoo Horyong , Ahn Eun Kyoung , Jang Jae Young , Jang Jung-Hee
Published: January 2022

The second most common progressive neurodegenerative disorder, Parkinson’s disease (PD), is characterized by a broad spectrum of symptoms that are associated with its progression. Several studies have attempted to classify PD according to its clinical manifestations and establish objective biomarkers for early diagnosis and for predicting the prognosis of the disease. Recent comprehensive research on the classification of PD using clinical phenotypes has included factors such as dominance, severity, and prognosis of motor and non-motor symptoms and biomarkers. Additionally, neuroimaging studies have attempted to reveal the pathological substrate for motor symptoms. Genetic and transcriptomic studies have contributed to our understanding of the underlying molecular pathogenic mechanisms and provided a basis for classifying PD. Moreover, an understanding of the heterogeneity of clinical manifestations in PD is required for a personalized medicine approach. Herein, we discuss the possible subtypes of PD based on clinical features, neuroimaging, and biomarkers for developing personalized medicine for PD. In addition, we conduct a preliminary clustering using gait features for subtyping PD. We believe that subtyping may facilitate the development of therapeutic strategies for PD.
Accuracy and Clinical Relevance of Intra-Tumoral Fusobacterium nucleatum Detection in Formalin-Fixed Paraffin-Embedded (FFPE) Tissue by Droplet Digital PCR (ddPCR) in Colorectal Cancer
Authors: Datorre José Guilherme , de Carvalho Ana Carolina , dos Reis Mariana Bisarro , dos Reis Monise , Matsushita Marcus , Santos Florinda , Guimarães Denise Peixoto , Reis Rui Manuel
Published: January 2022

The use of droplet digital PCR (ddPCR) to identify and quantify low-abundance targets is a significant advantage for accurately detecting potentially oncogenic bacteria. Fusobacterium nucleatum (Fn) is implicated in colorectal cancer (CRC) tumorigenesis and is becoming an important prognostic biomarker. We evaluated the detection accuracy and clinical relevance of Fn DNA by ddPCR in a molecularly characterized, formalin-fixed, paraffin-embedded (FFPE) CRC cohort previously analyzed by qPCR for Fn levels. Following a ddPCR assay optimization and an analytical evaluation, Fn DNA were measured in 139 CRC FFPE cases. The measures of accuracy for Fn status compared to the prior results generated by qPCR and the association with clinicopathological and molecular patients’ features were also evaluated. The ddPCR-based Fn assay was sensitive and specific to positive controls. Fn DNA were detected in 20.1% of cases and further classified as Fn-high and Fn-low/negative, according to the median amount of Fn DNA that were detected in all cases and associated with the patient’s worst prognosis. There was a low agreement between the Fn status determined by ddPCR and qPCR (Cohen’s Kappa = 0.210). Our findings show that ddPCR can detect and quantify Fn in FFPE tumor tissues and highlights its clinical relevance in Fn detection in a routine CRC setting.
C-Arm Cone-Beam CT Virtual Navigation versus Conventional CT Guidance in the Transthoracic Lung Biopsy: A Case-Control Study
Authors: Yang Lian , Wang Yue , Li Lin , Liu Dehan , Wu Xin , Zhang Wei , Pan Feng , Liang Huimin , Zheng Chuansheng
Published: January 2022

C-arm cone-beam computed tomography (CBCT) virtual navigation-guided lung biopsy has been developed in the last decade as an alternative to conventional CT-guided lung biopsy. This study aims to compare the biopsy accuracy and safety between these two techniques and explores the risk factors of biopsy-related complications. A total of 217 consecutive patients undergoing conventional CT- or C-arm CBCT virtual navigation-guided lung biopsy from 1 June 2018 to 31 December 2019 in this single-center were retrospectively reviewed. Multiple factors (e.g., prior emphysema, lesion size, etc.) were compared between two biopsy techniques. The risk factors of complications were explored by using logistic regression. The patients’ median age and male-to-female ratio were 63 years and 2.1:1, respectively. Eighty-two (82) patients (37.8%) underwent conventional CT-guided biopsies, and the other 135 patients (62.2%) C-arm CBCT virtual navigation-guided biopsies. Compared with patients undergoing C-arm CBCT virtual navigation-guided lung biopsies, patients undergoing conventional CT-guided lung biopsies showed higher needle repositioning rate, longer operation time, and higher effective dose of X-ray (52.4% vs. 6.7%, 25 min vs. 15 min, and 13.4 mSv vs. 7.6 mSv, respectively; p < 0.001, each). In total, the accurate biopsy was achieved in 215 of 217 patients (99.1%), without a significant difference between the two biopsy techniques (p = 1.000). The overall complication rates, including pneumothorax and pulmonary hemorrhage/hemoptysis, are 26.3% (57/217), with most minor complications (56/57, 98.2%). The needle repositioning was the only independent risk factor of complications with an odds ratio of 6.169 (p < 0.001). In conclusion, the C-arm CBCT virtual navigation is better in percutaneous lung biopsy than conventional CT guidance, facilitating needle positioning and reducing radiation exposure. Needle repositioning should be avoided because it brings about more biopsy-related complications.
Prevention of Caries and Dental Erosion by Fluorides—A Critical Discussion Based on Physico-Chemical Data and Principles
Authors: Epple Matthias , Enax Joachim , Meyer Frederic
Published: January 2022

Dental erosion is a common problem in dentistry. It is defined as the loss of tooth mineral by the attack of acids that do not result from caries. From a physico-chemical point of view, the nature of the corroding acids only plays a minor role. A protective effect of fluorides, to prevent caries and dental erosion, is frequently claimed in the literature. The proposed modes of action of fluorides include, for example, the formation of an acid-resistant fluoride-rich surface layer and a fluoride-induced surface hardening of the tooth surface. We performed a comprehensive literature study on the available data on the interaction between fluoride and tooth surfaces (e.g., by toothpastes or mouthwashes). These data are discussed in the light of general chemical considerations on fluoride incorporation and the acid solubility of teeth. The analytical techniques available to address this question are presented and discussed with respect to their capabilities. In summary, the amount of fluoride that is incorporated into teeth is very low (a few µg mm−2), and is unlikely to protect a tooth against an attack by acids, be it from acidic agents (erosion) or from acid-producing cariogenic bacteria.
A New Step in the Optimization of the Chambadal Model of the Carnot Engine
Authors: Feidt Michel , Costea Monica
Published: January 2022

This paper presents a new step in the optimization of the Chambadal model of the Carnot engine. It allows a sequential optimization of a model with internal irreversibilities. The optimization is performed successively with respect to various objectives (e.g., energy, efficiency, or power when introducing the duration of the cycle). New complementary results are reported, generalizing those recently published in the literature. In addition, the new concept of entropy production action is proposed. This concept induces new optimums concerning energy and power in the presence of internal irreversibilities inversely proportional to the cycle or transformation durations. This promising approach is related to applications but also to fundamental aspects.
Analysis of Energy Dissipation of Interval-Pooled Stepped Spillways
Authors: Ma Xin , Zhang Jianmin , Hu Yaan
Published: January 2022

The water flow characteristics over an interval-pooled stepped spillway are investigated by combining the renormalization group (RNG) k-ε turbulence model with the volume of fluid (VOF) interface capture technique in the present study. The results show that the energy dissipation performance of the interval-pooled stepped spillway was generally better than that of the pooled, stepped spillways and the traditional flat-panel stepped spillway. The omega vortex intensity identification method is introduced to evaluate the energy dissipation. Due to the formation of “pseudo-weir”, the energy dissipation did not increase with the growth of the pool’s height. In addition, the average vortex intensity can characterize the dissipation rate to some extent.
Probabilistic Deterministic Finite Automata and Recurrent Networks, Revisited
Authors: Marzen Sarah E. , Crutchfield James P.
Published: January 2022

Reservoir computers (RCs) and recurrent neural networks (RNNs) can mimic any finite-state automaton in theory, and some workers demonstrated that this can hold in practice. We test the capability of generalized linear models, RCs, and Long Short-Term Memory (LSTM) RNN architectures to predict the stochastic processes generated by a large suite of probabilistic deterministic finite-state automata (PDFA) in the small-data limit according to two metrics: predictive accuracy and distance to a predictive rate-distortion curve. The latter provides a sense of whether or not the RNN is a lossy predictive feature extractor in the information-theoretic sense. PDFAs provide an excellent performance benchmark in that they can be systematically enumerated, the randomness and correlation structure of their generated processes are exactly known, and their optimal memory-limited predictors are easily computed. With less data than is needed to make a good prediction, LSTMs surprisingly lose at predictive accuracy, but win at lossy predictive feature extraction. These results highlight the utility of causal states in understanding the capabilities of RNNs to predict.
Ensemble Averaging of Transfer Learning Models for Identification of Nutritional Deficiency in Rice Plant
Authors: Sharma Mayuri , Nath Keshab , Sharma Rupam Kumar , Kumar Chandan Jyoti , Chaudhary Ankit
Published: January 2022

Computer vision-based automation has become popular in detecting and monitoring plants’ nutrient deficiencies in recent times. The predictive model developed by various researchers were so designed that it can be used in an embedded system, keeping in mind the availability of computational resources. Nevertheless, the enormous popularity of smart phone technology has opened the door of opportunity to common farmers to have access to high computing resources. To facilitate smart phone users, this study proposes a framework of hosting high end systems in the cloud where processing can be done, and farmers can interact with the cloud-based system. With the availability of high computational power, many studies have been focused on applying convolutional Neural Networks-based Deep Learning (CNN-based DL) architectures, including Transfer learning (TL) models on agricultural research. Ensembling of various TL architectures has the potential to improve the performance of predictive models by a great extent. In this work, six TL architectures viz. InceptionV3, ResNet152V2, Xception, DenseNet201, InceptionResNetV2, and VGG19 are considered, and their various ensemble models are used to carry out the task of deficiency diagnosis in rice plants. Two publicly available datasets from Mendeley and Kaggle are used in this study. The ensemble-based architecture enhanced the highest classification accuracy to 100% from 99.17% in the Mendeley dataset, while for the Kaggle dataset; it was enhanced to 92% from 90%.
Evaluating Remote Task Assignment of an Online Engineering Module through Data Mining in a Virtual Communication Platform Environment
Authors: Kanetaki Zoe , Stergiou Constantinos , Bekas Georgios , Troussas Christos , Sgouropoulou Cleo
Published: January 2022

E-learning has traditionally emphasised educational resources, web access, student participation, and social interaction. Novel virtual spaces, e-lectures, and digital laboratories have been developed with synchronous or asynchronous practices throughout the migration from face-to-face teaching modes to remote teaching during the pandemic restrictions. This research paper presents a case study concerning the evaluation of the online task assignment of students, using MS Teams as an electronic platform. MS Teams was evaluated to determine whether this communication platform for online lecture delivery and tasks’ assessments could be used to avoid potential problems caused during the teaching process. Students’ data were collected, and after filtering out significant information from the online questionnaires, a statistical analysis, containing a correlation and a reliability analysis, was conducted. The substantial impact of 37 variables was revealed. Cronbach’s alpha coefficient calculation revealed that 89% of the survey questions represented internally consistent and reliable variables, and for the sampling adequacy measure, Bartlett’s test was calculated at 0.816. On the basis of students’ diligence, interaction abilities, and knowledge embedding, two groups of learners were differentiated. The findings of this study shed light on the special features of fully online teaching specifically in terms of improving assessment through digital tools and merit further investigation in virtual and blended teaching spaces, with the goal of extracting outputs that will benefit the educational community.
Multiparameter Identification of Permanent Magnet Synchronous Motor Based on Model Reference Adaptive System—Simulated Annealing Particle Swarm Optimization Algorithm
Authors: Su Guoyong , Wang Pengyu , Guo Yongcun , Cheng Gang , Wang Shuang , Zhao Dongyang
Published: January 2022

The accurate identification of permanent magnet synchronous motor (PMSM) parameters is the basis for high-performance drive control. The traditional PMSM multiparameter identification method experiences problems with the uncertainty of the identification results and low identification accuracy due to the under-ranking of the mathematical model of motor control. A multiparameter identification of PMSM based on a model reference adaptive system and simulated annealing particle swarm optimization (MRAS-SAPSO) is proposed here. The algorithm first identifies the electrical parameters of the PMSM (stator winding resistance R, cross-axis inductance L, and magnetic linkage ψf) by means of the model reference adaptive system method. Second, the result is used as the initial population in particle swarm optimization identification to further optimize and identify the electrical and mechanical parameters (moment of inertia J and damping coefficient B) in the motor control system. Additionally, in order to avoid problems such as premature convergence of the particle swarm in the optimization search process, the results of the adaptive simulated annealing algorithm to optimize multiparameter identification are introduced. The simulation experiment results show that the five identification parameters obtained by the MRAS-SAPSO algorithm are highly accurate and stable, and the errors between them and the real values are below 2%. This also verifies the effectiveness and reliability of this identification method.
Design and Analysis of a 35 GHz Rectenna System for Wireless Power Transfer to an Unmanned Air Vehicle
Authors: Hoque Muttahid Ull , Kumar Deepak , Audet Yves , Savaria Yvon
Published: January 2022

In this article, the concept of a 22-kW microwave-powered unmanned aerial vehicle is presented. Its system architecture is analyzed and modeled for wirelessly transferring microwave power to the flying UAVs. The microwave system transmitting power at a 35 GHz frequency was found to be suitable for low-cost and compact architectures. The size of the transmitting and receiving systems are optimized to 108 m2 and 90 m2, respectively. A linearly polarized 4 × 2 rectangular microstrip patch antenna array has been designed and simulated to obtain a high gain, high directivity, and high efficiency in order to satisfy the power transfer requirements. The numerically simulated gain, directivity, and efficiency of the proposed patch antenna array are 13.4 dBi, 14 dBi, and 85%, respectively. Finally, a rectifying system (rectenna) is optimized using the Agilent advanced design system (ADS) software as a microwave power receiving system. The proposed rectenna at the core of the system has an efficiency profile of more than 80% for an RF input power range of 9 to 18 dBm. Moreover, the RF-to-DC conversion efficiency and DC output voltage of the proposed rectenna are 80% and 3.5 V, respectively, for a 10 dBm input power at 35 GHz with a load of 1500 Ω.
Investigation of Flowback Behaviours in Hydraulically Fractured Shale Gas Well Based on Physical Driven Method
Authors: Guo Wei , Zhang Xiaowei , Kang Lixia , Gao Jinliang , Liu Yuyang
Published: January 2022

Due to the complex microscope pore structure of shale, large-scale hydraulic fracturing is required to achieve effective development, resulting in a very complicated fracturing fluid flowback characteristics. The flowback volume is time-dependent, whereas other relevant parameters, such as the permeability, porosity, and fracture half-length, are static. Thus, it is very difficult to build an end-to-end model to predict the time-dependent flowback curves using static parameters from a machine learning perspective. In order to simplify the time-dependent flowback curve into simple parameters and serve as the target parameter of big data analysis and flowback influencing factor analysis, this paper abstracted the flowback curve into two characteristic parameters, the daily flowback volume coefficient and the flowback decreasing coefficient, based on the analytical solution of the seepage equation of multistage fractured horizontal Wells. Taking the dynamic flowback data of 214 shale gas horizontal wells in Weiyuan shale gas block as a study case, the characteristic parameters of the flowback curves were obtained by exponential curve fittings. The analysis results showed that there is a positive correlation between the characteristic parameters which present the characteristics of right-skewed distribution. The calculation formula of the characteristic flowback coefficient representing the flowback potential was established. The correlations between characteristic flowback coefficient and geological and engineering parameters of 214 horizontal wells were studied by spearman correlation coefficient analysis method. The results showed that the characteristic flowback coefficient has a negative correlation with the thickness × drilling length of the high-quality reservoir, the fracturing stage interval, the number of fracturing stages, and the brittle minerals content. Through the method established in this paper, the shale gas flowback curve containing complex flow mechanism can be abstracted into simple characteristic parameters and characteristic coefficients, and the relationship between static data and dynamic data is established, which can help to establish a machine learning method for predicting the flowback curve of shale gas horizontal wells.
Linking Energy Poverty with Thermal Building Regulations and Energy Efficiency Policies in Portugal
Authors: Mafalda Matos Ana , Delgado João M. P. Q. , Guimarães Ana Sofia
Published: January 2022

Energy-poverty (EP) must be considered an energy-related issue since buildings are a central part of people’s daily lives. Thus, it has an important role in energy-related policy implementation. Even though the European Union (EU) has endorsed general energy efficiency through the Energy Efficiency Directive and Energy Performance of Buildings Directive recast, it was the Clean Energy Package for all Europeans that clearly highlighted EP. The growing concerns with EP have also been emphasised in subsequent directives and initiatives. Despite some regulatory framework and the milder climate situation, the proportion of the population experiencing thermal discomfort in southern and eastern European countries, namely in the winter season, is relatively high, reflecting the poor thermal performance of building stock, low family incomes and high energy prices, among others. The current work analysed the EP evolution in Portugal in the EU context, and the Thermal Building Regulations and Energy Efficiency Policies developed, aiming to add insight into the effectiveness of those policies concerning EP mitigation in Portugal as an EU Member state. Moreover, a critical debate on the potential to lower the EP Portuguese situation was also an objective to pursue. It is plausible to admit that reducing EP by acting on residential building stock, namely through the increase of energy efficiency and comfort, plays a key role in improving the living conditions, namely of vulnerable households and deprived areas. This will also decrease energy consumption and dependence while further promoting a smarter, sustainable and inclusive society, contributing to economic growth.
Self-Balancing Supercapacitor Energy Storage System Based on a Modular Multilevel Converter
Authors: Hernandez Fernando Davalos , Samanbakhsh Rahim , Ibanez Federico Martin , Martin Fernando
Published: January 2022

Energy Storage Systems (ESS) are an attractive solution in environments with a high amount of renewable energy sources, as they can improve the power quality in such places and if required, can extend the integration of more renewable sources of energy. If a large amount of power is needed, then supercapacitors are viable energy storage devices due to their specific power, allowing response times that are in the range of milliseconds to seconds. This paper details the design of an ESS that is based on a modular multilevel converter (MMC) with bidirectional power flow, which reduces the number of cascaded stages and allows the supercapacitors SCs to be connected to the grid to perform high-power transfers. A traditional ESS has four main stages or subsystems: the energy storage device, the balancing system, and the DC/DC and DC/AC converters. The proposed ESS can perform all of those functions in a single circuit by adopting an MMC topology, as each submodule (SM) can self-balance during energy injection or grid absorption. This article analyses the structure in both power flow directions and in the control loops and presents a prototype that is used to validate the design.
Fault Detection and Efficiency Assessment for HVAC Systems Using Non-Intrusive Load Monitoring: A Review
Authors: Rafati Amir , Shaker Hamid Reza , Ghahghahzadeh Saman
Published: January 2022

Heat, ventilation, and air conditioning (HVAC) systems are some of the most energy-intensive equipment in buildings and their faulty or inefficient operation can significantly increase energy waste. Non-Intrusive Load Monitoring (NILM), which is a software-based tool, has been a popular research area over the last few decades. NILM can play an important role in providing future energy efficiency feedback and developing fault detection and diagnosis (FDD) tools in smart buildings. Therefore, the review of NILM-based methods for FDD and the energy efficiency (EE) assessment of HVACs can be beneficial for users as well as buildings and facilities operators. To the best of the authors’ knowledge, this paper is the first review paper on the application of NILM techniques in these areas and highlights their effectiveness and limitations. This review shows that even though NILM could be successfully implemented for FDD and the EE evaluation of HVACs, and enhance the performance of these techniques, there are many research opportunities to improve or develop NILM-based FDD methods to deal with real-world challenges. These challenges and future research works are also discussed in-depth.
Numerical Analysis of Thermal Stress for a Stack of Planar Solid Oxide Fuel Cells
Authors: Zheng Jianmin , Xiao Liusheng , Wu Mingtao , Lang Shaocheng , Zhang Zhonggang , Chen Ming , Yuan Jinliang
Published: January 2022

In this work, a 3D multi-physics coupled model was developed to analyze the temperature and thermal stress distribution in a planar solid oxide fuel cell (SOFC) stack, and then the effects of different flow channels (co-flow, counter-flow and cross-flow) and electrolyte thickness were investigated. The simulation results indicate that the generated power is higher while the thermal stress is lower in the co-flow mode than those in the cross-flow mode. In the cross-flow mode, a gas inlet and outlet arrangement is proposed to increase current density by about 10%. The generated power of the stack increases with a thin electrolyte layer, but the temperature and its gradient of the stack also increase with increase of heat generation. The thermal stress for two typical sealing materials is also studied. The predicted results can be used for design and optimization of the stack structure to achieve lower stress and longer life.
Quantifying Environmental and Economic Impacts of Highly Porous Activated Carbon from Lignocellulosic Biomass for High-Performance Supercapacitors
Authors: Wang Yuxi , Wang Jingxin , Zhang Xufeng , Bhattacharyya Debangsu , Sabolsky Edward M.
Published: January 2022

Activated carbons (AC) from lignocellulosic biomass feedstocks are used in a broad range of applications, especially for electrochemical devices such as supercapacitor electrodes. Limited studies of environmental and economic impacts for AC supercapacitor production have been conducted. Thus, this paper evaluated the environmental and economic impacts of AC produced from lignocellulosic biomass for energy-storage purposes. The life cycle assessment (LCA) was employed to quantify the potential environmental impacts associated with AC production via the proposed processes including feedstock establishment, harvest, transport, storage, and in-plant production. A techno-economic model was constructed to analyze the economic feasibility of AC production, which included the processes in the proposed technology, as well as the required facility installation and management. A base case, together with two alternative scenarios of KOH-reuse and steam processes for carbon activation, were evaluated for both environmental and economic impacts, while the uncertainty of the net present value (NPV) of the AC production was examined with seven economic indicators. Our results indicated that overall “in-plant production” process presented the highest environmental impacts. Normalized results of the life-cycle impact assessment showed that the AC production had environmental impacts mainly on the carcinogenics, ecotoxicity, and non-carcinogenics categories. We then further focused on life cycle analysis from raw biomass delivery to plant gate, the results showed that “feedstock establishment” had the most significant environmental impact, ranging from 50.3% to 85.2%. For an activated carbon plant producing 3000 kg AC per day in the base case, the capital cost would be USD 6.66 million, and annual operation cost was found to be USD 15.46 million. The required selling price (RSP) of AC was USD 16.79 per kg, with the discounted payback period (DPB) of 9.98 years. Alternative cases of KOH-reuse and steam processes had GHG emissions of 15.4 kg CO2 eq and 10.2 kg CO2 eq for every 1 kg of activated carbon, respectively. Monte Carlo simulation showed 49.96% of the probability for an investment to be profitable in activated carbon production from lignocellulosic biomass for supercapacitor electrodes.
Open-Circuit Fault-Tolerant Strategy for Interleaved Boost Converters via Filippov Method
Authors: Morel Cristina , Akrad Ahmad , Sehab Rabia , Azib Toufik , Larouci Cherif
Published: January 2022

Interleaved converters use an increased number of power electronics switches; this may subsequently affect their reliability. However, this is an opportunity to develop fault-tolerant strategies to improve their reliability and to ensure continuity of service. This is why we herein propose, for the first time, a mathematical function to simultaneously model the healthy and faulty conditions of each switch, thus enabling a unique model of the system. This model is then used in an original fault-tolerant strategy based upon the peak current control with slope compensation. This method not only extends the stable range of the load variation but also ensures the stability in faulty conditions. Finally, the simulation results validate its effectiveness and confirm the theoretical analysis.
Does the Net Present Value as a Financial Metric Fit Investment in Green Energy Security?
Authors: Dobrowolski Zbysław , Drozdowski Grzegorz
Published: January 2022

Surprisingly, little is known whether the net present value (NPV) used as a financial metric in budgeting and investment planning to analyse a projects’ profitability is universal. Meanwhile, the epochal green energy revolution ensuring carbon neutrality through green innovations requires enormous investments, and projects realised must ensure energy security. Therefore, there is a need to reanalyse financial metrics used in financial planning, including NPV. We eliminate this research gap and, based on data from Poland, Romania, Hungary, Croatia, the USA, the United Kingdom, Japan, Israel, and Euro Zone, explain why one may not perceive the currently used NPV formula as a universal financial metric. We show that the variable discount rate influences the time value of money. Therefore, there is a need to redefine the NPV formula. This study makes two main contributions. First, it creates new ground by revisiting the NPV formula in the emerging market context compared to stable economies and contributes to developing business and management theory. Second, we propose and empirically verify the modified NPV formula as a financial metric that considers the situation of energy firms in emerging markets. Thus, this research helps the capital budgeting process, and the modified NPV formula can help provide optimal outcomes in firms, helping to reduce financial risks. Our study contributes to a further contextual diagnosis of business projects and can, in turn, be relevant for other energy sector analyses.
Nature-Based Solutions in Poland against Climate Change
Authors: Małecka-Ziembińska Edyta , Janicka Izabela
Published: January 2022

One of the currently promoted methods of counteracting climate change is nature-based climate solutions, which harness the power of nature to reduce greenhouse gas emissions. Sustainable management of ecosystems is a guarantee for sustained human well-being. This underestimated, but extremely efficient and cheap method of integrating nature resources into the urban fabric is an economic “injection” for communal authorities. These “green” benefits should be standard in land-use planning in the era of anthropocentrism. Solutions based on nature were the reason for investigating their perception by Polish municipalities. The survey covered the entire country (all 2477 municipalities) from 20 July to 31 August 2021 through an electronic survey, obtaining 2128 responses (85.9% return rate). In the final result, data were obtained that support the hypotheses posed in the study. The main objective of the research was to check the level of activity of municipalities in Poland in the field of proecological activities using nature-based solutions (NbS). The survey results confirmed little knowledge of nature-based solutions, at the same time giving it an educational dimension. Half of the respondents declared that they learned about NbS only from the survey. Polish decision makers and municipal authorities introduce some solutions based on nature without being aware of their European classification and adequate nomenclature. Environmental awareness in Poland remains largely the domain of urban municipalities, with higher current budget revenues per capita and in the central and western parts of the country. NbS are marginal in rural municipalities, which can be explained by the lack of ecological specialists, less car traffic and more single-family houses and thus modest public areas. The following surveys covering the entire territory of Poland are the first to be carried out on such a large scale.
A Robust Fractional-Order PID Controller Based Load Frequency Control Using Modified Hunger Games Search Optimizer
Authors: Fathy Ahmed , Yousri Dalia , Rezk Hegazy , Thanikanti Sudhakar Babu , Hasanien Hany M.
Published: January 2022

In this article, a recent modified meta-heuristic optimizer named the modified hunger games search optimizer (MHGS) is developed to determine the optimal parameters of a fractional-order proportional integral derivative (FOPID) based load frequency controller (LFC). As an interconnected system’s operation requires maintaining the tie-line power and frequency at their described values without permitting deviations in them, an enhanced optimizer is developed to identify the controllers’ parameters efficiently and rapidly. Therefore, the non-uniform mutation operator is proposed to strengthen the diversity of the solutions and discover the search landscape of the basic hunger games search optimizer (HGS), aiming to provide a reliable approach. The considered fitness function is the integral time absolute error (ITAE) comprising the deviations in tie-line power and frequencies. The analysis is implemented in two networks: the 1st network comprises a photovoltaic (PV) plant connected to the thermal plant, and the 2nd network has four connected plants, which are PV, wind turbine (WT), and 2 thermal units with generation rate constraints and governor dead-band. Two different load disturbances are imposed for two studied systems: static and dynamic. The results of the proposed approach of MHGS are compared with the marine predators algorithm (MPA), artificial ecosystem based optimization (AEO), equilibrium optimizer (EO), and Runge–Kutta based optimizer (RUN), as well as movable damped wave algorithm (DMV) results. Moreover, the performance specifications of the time responses of frequencies and tie-line powers’ violations comprising rise time, settling time, minimum/maximum setting values, overshoot, undershoot, and the peak level besides its duration are calculated. The proposed MHGS shows its reliability in providing the most efficient values for the FOPID controllers’ parameters that achieve the lowest fitness of 0.89726 in a rapid decaying. Moreover, the MHGS based system becomes stable the most quickly as it has the shortest settling time and is well constructed as it has the smallest peak, overshoots at early times, and then the system becomes steady. The results confirmed the competence of the proposed MHGS in designing efficient FOPID-LFC controllers that guarantee reliable operation in case of load disturbances.
Development and Test of a Novel Electronic Radiator Thermostat with a Return Temperature Limiting Function
Authors: Tunzi Michele , Skaarup Østergaard Dorte , Svendsen Svend
Published: January 2022

Automated hydronic balancing in space heating systems is crucial for the fourth-generation district heating transition. The current manual balancing requires labor- and time-consuming activities. This article presents the field results of an innovative electronic radiator thermostat tested on two Danish multi-family buildings. The prototypes had an additional return temperature sensor on each radiator and an algorithm was used to accurately control valve opening to ensure automated hydronic balancing. The results highlighted that the new thermostat performed as expected and helped secure the cooling of district heating temperatures —defined as the difference between supply and return temperature—4–12 °C higher during the test compared to results obtained in 2020, when the prototypes were replaced with state-of-the-art thermostats in the first building. The measurements from the other building illustrated how only two uncontrolled radiators out of 175 could contaminate the overall return temperature. The remote connection of the thermostats helped pinpoint the faults in the heating system, although the end-users were not experiencing any discomfort, and secure, after fixing the problems, a return temperature of 35 °C. Future designs may consider integrating a safety functionality to close the valve or limit the flow in case of damage or malfunction to avoid a few radiators compromising the low-temperature operation of an entire building before the cause of the problem has been identified.
The Impact of Alumina Nanofluids on Pool Boiling Performance on Biphilic Surfaces for Cooling Applications
Authors: Santos Ricardo , Moita Ana Sofia , Ribeiro Ana Paula C. , Moreira António Luís N.
Published: January 2022

This work aims to study the impact of nanofluids with alumina particles on pool boiling performance. Unlike most studies, which use a trial-and-error approach to improve boiling performance parameters, this study details the possible effects of nanoparticles on the effective mechanisms of boiling and heat transfer. For this purpose, biphilic surfaces (hydrophilic surfaces with superhydrophobic spots) were used, which allow the individual analysis of bubbles. Surfaces with different configurations of superhydrophobic regions were used. The thermophysical properties of fluids only vary slightly with increasing nanoparticle concentration. The evolution of the dissipated heat flux and temperature profiles for a nucleation time frame is independent of the fluid and imposed heat flux. It can be concluded that the optimal concentration of nanoparticles is 3 wt%. Using this nanoparticle concentration leads to lower surface temperature values than those obtained with water, the reference fluid. This is due to the changes in the balance of forces in the triple line, induced by increased wettability as a consequence of the deposited particles. Wherefore, smaller and more frequent bubbles are formed, resulting in higher heat transfer coefficients. This effect, although relevant, is still of minor importance when compared to that of the use of biphilic surfaces.
Experimental Validation of a Hydrostatic Transmission for Community Wind Turbines
Authors: Mohanty Biswaranjan , Stelson Kim A.
Published: January 2022

Hydrostatic transmissions are commonly used in heavy-duty equipment for their design flexibility and superior power density. Compared to a conventional wind turbine transmission, a hydrostatic transmission (HST) is a lighter, more reliable, cheaper, continuously variable alternative for a wind turbine. In this paper, for the first time, a validated dynamical model and controlled experiment have been used to analyze the performance of a hydrostatic transmission with a fixed-displacement pump and a variable-displacement motor for community wind turbines. From the dynamics of the HST, a pressure control strategy is designed to maximize the power capture. A hardware-in-the-loop simulation is developed to experimentally validate the performance and efficiency of the HST drive train control in a 60 kW virtual wind turbine environment. The HST turbine is extensively evaluated under steady and time-varying wind on a state-of-the-art power regenerative hydrostatic dynamometer. The proposed controller tracks the optimal tip-speed ratio to maximize power capture.