bluuebunny/crossref_metadata_2025 huggingface dataset:
Copper Oxide/Functionalized Graphene Hybrid Nanostructures for Room Temperature Gas Sensing Applications
Authors: Gupta Monika , Hawari Huzein , Kumar Pradeep , Burhanudin Zainal
Published: February 2022

Oxide semiconductors are conventionally used as sensing materials in gas sensors, however, there are limitations on the detection of gases at room temperature (RT). In this work, a hybrid of copper oxide (CuO) with functionalized graphene (rGO) is proposed to achieve gas sensing at RT. The combination of a high surface area and the presence of many functional groups in the CuO/rGO hybrid material makes it highly sensitive for gas absorption and desorption. To prepare the hybrid material, a copper oxide suspension synthesized using a copper acetate precursor is added to a graphene oxide solution during its reduction using ascorbic acid. Material properties of the CuO/rGO hybrid and its drop-casted thin-films are investigated using Raman, FTIR, SEM, TEM, and four-point probe measurement systems. We found that the hybrid material was enriched with oxygen functional groups (OFGs) and defective sites, along with good electrical conductivity (Sheet resistance~1.5 kΩ/□). The fabricated QCM (quartz crystal microbalance) sensor with a thin layer of the CuO/rGO hybrid demonstrated a high sensing response which was twice the response of the rGO-based sensor for CO2 gas at RT. We believe that the CuO/rGO hybrid is highly suitable for existing and future gas sensors used for domestic and industrial safety.
Effect of Service-Induced Degradation on Residual Stress Rupture Life of a Directionally Solidified Superalloy
Authors: Guo Xiaotong , Xing Weijie , Zhang Heng , Li Yong , Peng Hemeng , Yang Chuan
Published: February 2022

The influence of service-induced degradation on residual life is very important for the safe service of turbine blades. In this study, a series of simulation experiments were conducted on a directionally solidified superalloy under (880–1020) °C/(70–220) MPa and interrupted after 500 h. Then, the stress rupture life of the interrupted specimens was tested under 980 °C/275 MPa. The results showed that the increase of simulated experiment temperature decreased the residual stress rupture life. In brief, the simulation experiments at 880 °C did not influence the residual stress rupture life of the alloy. The simulated experiments at 980 °C and 1050 °C mainly affected the microstructure of γ’ phase, while not γ/γ’ eutectic and carbides. After the stress rupture tests under 980 °C/275 MPa, cracks were located at the interfaces between carbides and γ matrix in the interdendritic regions. This study provides guidance on the degradation evaluation and safety service of the directionally solidified superalloys.
Gla-Rich Protein, Magnesium and Phosphate Associate with Mitral and Aortic Valves Calcification in Diabetic Patients with Moderate CKD
Authors: Silva Ana P. , Viegas Carla S. B. , Guilherme Patrícia , Tavares Nelson , Dias Carolina , Rato Fátima , Santos Nélio , Faísca Marília , de Almeida Edgar , Neves Pedro L. , Simes Dina C.
Published: February 2022

Accelerated and premature cardiovascular calcification is a hallmark of chronic kidney disease (CKD) patients. Valvular calcification (VC) is a critical indicator of cardiovascular disease and all-cause mortality in this population, lacking validated biomarkers for early diagnosis. Gla-rich protein (GRP) is a cardiovascular calcification inhibitor recently associated with vascular calcification, pulse pressure, mineral metabolism markers and kidney function. Here, we examined the association between GRP serum levels and mitral and aortic valves calcification in a cohort of 80 diabetic patients with CKD stages 2–4. Mitral and aortic valves calcification were detected in 36.2% and 34.4% of the patients and associated with lower GRP levels, even after adjustments for age and gender. In this pilot study, univariate, multivariate and Poisson regression analysis, show that low levels of GRP and magnesium (Mg), and high levels of phosphate (P) are associated with mitral and aortic valves calcification. Receiver operating characteristic (ROC) curves showed that the area under the curve (AUC) values of GRP for mitral (0.762) and aortic (0.802) valves calcification were higher than those of Mg and P. These results suggest that low levels of GRP and Mg, and high levels of P, are independent and cumulative risk factors for VC in this population; the GRP diagnostic value might be potentially useful in cardiovascular risk assessment.
Strategies for Isolating and Propagating Circulating Tumor Cells in Men with Metastatic Prostate Cancer
Authors: Theil Gerit , Bialek Joanna , Weiß Christine , Lindner Felix , Fornara Paolo
Published: February 2022

Selecting a well-suited method for isolating/characterizing circulating tumor cells (CTCs) is challenging. Evaluating sensitive and specific markers for prostate cancer (PCa)-specific CTC identification and analysis is crucial. We used the CellCollector EpCAM-functionalized system (CC-EpCAM) and evaluated and developed a PCa-functionalized version (CC-PCa); we then compared CTC isolation techniques that exploit the physical and biological properties of CTCs. We established two cohorts of metastatic PCa patients (mPCa; 15 in cohort 1 and 10 in cohort 2). CTC cultivation experiments were conducted with two capturing methods (Ficoll and ScreenCell). The most sensitive detection rates and highest CTC counts were reached with the CC-PCa and ScreenCell system. Patients with ≥5 CTCs isolated with CC-EpCAM had an overall survival (OS) of 0.93 years, and patients with ≥5 CTCs isolated with CC-PCa had an OS of 1.5 years in cohort 1. Nevertheless, we observed the highest sensitivity and specificity for 24-month survival by the Ficoll with CD45 depletion and ScreenCell system with May-Grunwald Giemsa (MGG) staining. The EpCAM molecule is an essential factor related to OS for CTC isolation based on biological properties in mPCa patients. The best-suited CTC capture system is not limited to one characteristic of cells but adapted to downstream analysis.
Non-Contrast-Enhanced and Contrast-Enhanced Magnetic Resonance Angiography in Living Donor Liver Vascular Anatomy
Authors: Liao Chien-Chang , Chen Meng-Hsiang , Yu Chun-Yen , Tsang Leung-Chit Leo , Chen Chao-Long , Hsu Hsien-Wen , Lim Wei-Xiong , Chuang Yi-Hsuan , Huang Po-Hsun , Cheng Yu-Fan , Ou Hsin-You
Published: February 2022

Background: Since the advent of a new generation of inflow-sensitive inversion recovery (IFIR) technology, three-dimensional non-contrast-enhanced magnetic resonance angiography is being used to obtain hepatic vessel images without applying gadolinium contrast agent. The purpose of this study was to explore the diagnostic efficacy of non-contrast-enhanced magnetic resonance angiography (non-CE MRA), contrast-enhanced magnetic resonance angiography (CMRA), and computed tomography angiography (CTA) in the preoperative evaluation of living liver donors. Methods: A total of 43 liver donor candidates who were evaluated for living donor liver transplantation completed examinations. Donors’ age, gender, renal function (eGFR), and previous CTA and imaging were recorded before non-CE MRA and CMRA. CTA images were used as the standard. Results: Five different classifications of hepatic artery patterns (types I, III, V, VI, VIII) and three different classifications of portal vein patterns (types I, II, and III) were identified among 43 candidates. The pretransplant vascular anatomy was well identified using combined non-CE MRA and CMRA of hepatic arteries (100%), PVs (98%), and hepatic veins (100%) compared with CTA images. Non-CE MRA images had significantly stronger contrast signal intensity of portal veins (p < 0.01) and hepatic veins (p < 0.01) than CMRA. No differences were found in signal intensity of the hepatic artery between non-CE MRA and CMRA. Conclusion: Combined non-CE MRA and CMRA demonstrate comparable diagnostic ability to CTA and provide enhanced biliary anatomy information that assures optimum donor safety.
A Complex Radiomic Signature in Luminal Breast Cancer from a Weighted Statistical Framework: A Pilot Study
Authors: Castaldo Rossana , Garbino Nunzia , Cavaliere Carlo , Incoronato Mariarosaria , Basso Luca , Cuocolo Renato , Pace Leonardo , Salvatore Marco , Franzese Monica , Nicolai Emanuele
Published: February 2022

Radiomics is rapidly advancing in precision diagnostics and cancer treatment. However, there are several challenges that need to be addressed before translation to clinical use. This study presents an ad-hoc weighted statistical framework to explore radiomic biomarkers for a better characterization of the radiogenomic phenotypes in breast cancer. Thirty-six female patients with breast cancer were enrolled in this study. Radiomic features were extracted from MRI and PET imaging techniques for malignant and healthy lesions in each patient. To reduce within-subject bias, the ratio of radiomic features extracted from both lesions was calculated for each patient. Radiomic features were further normalized, comparing the z-score, quantile, and whitening normalization methods to reduce between-subjects bias. After feature reduction by Spearman’s correlation, a methodological approach based on a principal component analysis (PCA) was applied. The results were compared and validated on twenty-seven patients to investigate the tumor grade, Ki-67 index, and molecular cancer subtypes using classification methods (LogitBoost, random forest, and linear discriminant analysis). The classification techniques achieved high area-under-the-curve values with one PC that was calculated by normalizing the radiomic features via the quantile method. This pilot study helped us to establish a robust framework of analysis to generate a combined radiomic signature, which may lead to more precise breast cancer prognosis.
Sequential Models for Endoluminal Image Classification
Authors: Reuss Joana , Pascual Guillem , Wenzek Hagen , Seguí Santi
Published: February 2022

Wireless Capsule Endoscopy (WCE) is a procedure to examine the human digestive system for potential mucosal polyps, tumours, or bleedings using an encapsulated camera. This work focuses on polyp detection within WCE videos through Machine Learning. When using Machine Learning in the medical field, scarce and unbalanced datasets often make it hard to receive a satisfying performance. We claim that using Sequential Models in order to take the temporal nature of the data into account improves the performance of previous approaches. Thus, we present a bidirectional Long Short-Term Memory Network (BLSTM), a sequential network that is particularly designed for temporal data. We find the BLSTM Network outperforms non-sequential architectures and other previous models, receiving a final Area under the Curve of 93.83%. Experiments show that our method of extracting spatial and temporal features yields better performance and could be a possible method to decrease the time needed by physicians to analyse the video material.
Factors Associated with Withdrawal Time in European Colonoscopy Practice: Findings of the European Colonoscopy Quality Investigation (ECQI) Group
Authors: Spada Cristiano , Koulaouzidis Anastasios , Hassan Cesare , Amaro Pedro , Agrawal Anurag , Brink Lene , Fischbach Wolfgang , Hünger Matthias , Jover Rodrigo , Kinnunen Urpo , Ono Akiko , Patai Árpád , Pecere Silvia , Petruzziello Lucio , Riemann Jürgen F. , Staines Harry , Stringer Ann L. , Toth Ervin , Antonelli Giulio , Fuccio Lorenzo
Published: February 2022

The European Colonoscopy Quality Investigation (ECQI) Group aims to raise awareness for improvement in colonoscopy standards across Europe. We analyzed data collected on a sample of procedures conducted across Europe to evaluate the achievement of the European Society of Gastrointestinal Endoscopy (ESGE) mean withdrawal time (WT) target. We also investigated factors associated with WT, in the hope of establishing areas that could lead to a quality improvement. Methods: 6445 form completions from 12 countries between 2 June 2016 and 30 April 2018 were considered for this analysis. We performed an exploratory analysis looking at WT according to the ESGE definition. Stepwise multivariable logistic regression analysis was conducted to determine the most influential associated factors after adjusting for the other pre-specified variables. Results: In 1150 qualifying colonoscopies, the mean WT was 7.8 min. Stepwise analysis, including 587 procedures where all inputs were known, found that the variables most associated with mean WT were a previous total colonoscopy in the last five years (p = 0.0011) and the time of day the colonoscopy was performed (p = 0.0192). The main factor associated with a WT < 6 min was the time of day that a colonoscopy was performed. Use of sedation was the main factor associated with a higher proportion of WT > 10 min, along with a previous colonoscopy. Conclusions: On average, the sample of European practice captured by the ECQI survey met the minimum standard set by the ESGE. However, there was variation and potential for improvement.
Approximate Entropy in Canonical and Non-Canonical Fiction
Authors: Mohseni Mahdi , Redies Christoph , Gast Volker
Published: February 2022

Computational textual aesthetics aims at studying observable differences between aesthetic categories of text. We use Approximate Entropy to measure the (un)predictability in two aesthetic text categories, i.e., canonical fiction (‘classics’) and non-canonical fiction (with lower prestige). Approximate Entropy is determined for series derived from sentence-length values and the distribution of part-of-speech-tags in windows of texts. For comparison, we also include a sample of non-fictional texts. Moreover, we use Shannon Entropy to estimate degrees of (un)predictability due to frequency distributions in the entire text. Our results show that the Approximate Entropy values can better differentiate canonical from non-canonical texts compared with Shannon Entropy, which is not true for the classification of fictional vs. expository prose. Canonical and non-canonical texts thus differ in sequential structure, while inter-genre differences are a matter of the overall distribution of local frequencies. We conclude that canonical fictional texts exhibit a higher degree of (sequential) unpredictability compared with non-canonical texts, corresponding to the popular assumption that they are more ‘demanding’ and ‘richer’. In using Approximate Entropy, we propose a new method for text classification in the context of computational textual aesthetics.
Case Study: Teaching with Industry (TWI) Using New Videoconferencing Technology and Innovative Classroom Setups
Authors: Jacobs Francois , Cain William , Lu Renxiang , Daugherty Amy
Published: February 2022

This paper describes a case study of a novel teaching method where the “Teaching with Industry” (TWI) model–industry practitioners incorporated as co-instructors in a semester-long classroom setting–is enhanced by using new videoconferencing technologies such as Zoom and Meeting Owl Pro, and innovative classroom setups. This enhanced model was developed with the intent to bridge the gap between information acquired in the classroom and the skills and competencies required in the industry. The different teaching platforms not only facilitated the teaching when industry practitioners were/are not able to be physically present in the classroom, but also led to efficient organization of the different activities carried out in class. Results obtained from end-course surveys showed that students had a positive experience using Zoom and Meeting Owl Pro welcoming the opportunity to engage with industry practitioners and gain better understanding of the practical usefulness of the course.
Evolutionary Optimization Based Set Joint Integrated Probabilistic Data Association Filter
Authors: Liang Shuang , Zhu Yun , Li Hao
Published: February 2022

The joint integrated probabilistic data association (JIPDA) algorithm is widely used for the automatic tracking of multiple targets, but it has the well-known problem of track coalescence. By optimizing the posterior density, the accuracy of the target state estimation can be improved. Motivated by this idea, we developed a novel evolutionary optimization based joint integrated probabilistic data association (EOJIPDA) filter to overcome the coalescence problem of the JIPDA filter. The trace for the covariance matrix of the posterior density is used as the objective function for the above optimization problem. It is shown that the accuracy of the target state estimation can be improved by reducing the trace. Evolutionary optimization was employed to minimize the trace and optimize the posterior density. More specifically, we enumerated all the possible permutations of the targets and assign a unique index to each permutation. The resulting indices were randomly assigned to all possible association hypothesis events. Each assignment indicated one possible gene in the evolutionary algorithm. This process was repeated several times to arrive at the initial population. An illustrative example shows that the EOJIPDA filter can effectively improve the accuracy of state estimation. Numerical studies are presented for two challenging multi-target tracking scenarios with clutter and missed detections. The experimental results demonstrate that the EOJIPDA filter provides better tracking accuracy than traditional coalescence-avoiding methods.
Sustainable Management and Policies: The Roles of Stakeholders in the Practice of Inclusive Education in Digital Transformation
Authors: Ari Refia , Altinay Zehra , Altinay Fahriye , Dagli Gokmen , Ari Engin
Published: February 2022

Children are a country’s most valuable asset. Educating them and bringing them into society is one of the most fundamental tasks of a nation. The disadvantageous position that individuals with a disability are exposed to shows the importance of the need for inclusive education for the quality of life. It is important to use the merits of digital transformation to provide services and education for all to support sustainability. This research aims to shine a light on the problems related to inclusive education faced in the special education schools and rehabilitation centers and put forward suggestions for digital transformation. As inclusive means inclusion, social interaction, access, and equality for education, the role of digital transformation is examined for the quality of inclusive education. Self-reflection is a qualitative form which was employed in the research involving school managers and teachers who were selected randomly from the Special Education Schools and Rehabilitation Centers that participated in the research. It is revealed that most of the studies focus on inclusive education, the digital divide, social inclusion, online learning, and the implication of inclusive education in digital transformation. Although studies expose inclusive education in digital transformation, most of these have 0.20 quality criteria, showing an intensified need to extend the existing body of knowledge. It is shown that the vast majority of inclusive education aligns with the institution’s inclusive education vision and purpose. Concerning financing, it is difficult to find sponsors among non-governmental organizations to support the institution’s inclusive education-related material, equipment, and security needs, and Ministry of National Education funding is essential. There is a need to improve the inclusive education competencies of administrators and teachers, and in-service training should be provided. Self-improvement opportunities of administrators and teachers of the institution are significantly inadequate and should be improved.
A Review of Deep Learning Methods for Compressed Sensing Image Reconstruction and Its Medical Applications
Authors: Xie Yutong , Li Quanzheng
Published: February 2022

Compressed sensing (CS) and its medical applications are active areas of research. In this paper, we review recent works using deep learning method to solve CS problem for images or medical imaging reconstruction including computed tomography (CT), magnetic resonance imaging (MRI) and positron-emission tomography (PET). We propose a novel framework to unify traditional iterative algorithms and deep learning approaches. In short, we define two projection operators toward image prior and data consistency, respectively, and any reconstruction algorithm can be decomposed to the two parts. Though deep learning methods can be divided into several categories, they all satisfies the framework. We built the relationship between different reconstruction methods of deep learning, and connect them to traditional methods through the proposed framework. It also indicates that the key to solve CS problem and its medical applications is how to depict the image prior. Based on the framework, we analyze the current deep learning methods and point out some important directions of research in the future.
Recent Developments and Challenges on Beam Steering Characteristics of Reconfigurable Transmitarray Antennas
Authors: Ali Qasim , Shahzad Waseem , Ahmad Iftikhar , Safiq Shozab , Bin Xi , Abbas Syed Muzahir , Sun Houjun
Published: February 2022

This paper highlights recent developments and challenges on beam steering characteristics of reconfigurable transmitarray antennas. It introduces the operating principle of beam forming/beam steering high gain transmitarray antennas to enable the user to opt for economical and high performance solutions. A transmitarray antenna typically consists of a source antenna and a phase transformation structure. The incident waves generated from the source antenna is tilted using the phase transformation structure in a desired direction to steer the beam. Moreover, the phase transformation structure alters the incident wavefront to a plane wavefront using phase change characteristics. In order to steer a beam to a specific desired angle, it can be divided into two methods. There is a method of applying a transmitarray with a variable transmission phase change or a method of changing the shape of the wavefront of the source antenna. This type of beam forming/beam steering high gain antenna has been mainly studied from the point of view of high efficiency, low profile, and low cost. Several solutions of transmitarray unit cells have been presented in the literature, using PIN diodes, varactors, MEMS switches, and microfluids enable electronics to realize reconfigurable characteristics of transmitarray antennas. This paper analyzes the characteristics of various beam steering high gain reconfigurable transmitarrays (RTA) and highlights the future opportunities and challenges of the structure design for transmitarray antennas. This paper also highlights the challenges and gaps in terahertz and optical frequencies related to future work due to the structure complexity and lack of components’ availability. Moreover, the challenges and limitations related to multi-bit structures and dual-band requirements are presented.
Angles-Only Initial Orbit Determination via Multivariate Gaussian Process Regression
Authors: Schwab David , Singla Puneet , O’Rourke Sean
Published: February 2022

Vital for Space Situational Awareness, Initial Orbit Determination (IOD) may be used to initialize object tracking and associate observations with a tracked satellite. Classical IOD algorithms provide only a point solution and are sensitive to noisy measurements and to certain target-observer geometry. This work examines the ability of a Multivariate GPR (MV-GPR) to accurately perform IOD and quantify the associated uncertainty. Given perfect test inputs, MV-GPR performs comparably to a simpler multitask learning GPR algorithm and the classical Gauss–Gibbs IOD in terms of prediction accuracy. It significantly outperforms the multitask learning GPR algorithm in uncertainty quantification due to the direct handling of output dimension correlations. A moment-matching algorithm provides an analytic solution to the input noise problem under certain assumptions. The algorithm is adapted to the MV-GPR formulation and shown to be an effective tool to accurately quantify the added input uncertainty. This work shows that the MV-GPR can provide a viable solution with quantified uncertainty which is robust to observation noise and traditionally challenging orbit-observer geometries.
IoT-Based Human Fall Detection System
Authors: Ribeiro Osvaldo , Gomes Luis , Vale Zita
Published: February 2022

Human falls are an issue that especially affects elderly people, resulting in permanent disabilities or even in the person’s death. Preventing human falls is a social desire, but it is almost impossible to achieve because it is not possible to ensure full prevention. A possible solution is the detection of human falls in near real-time so that help can quickly be provided. This has the potential to greatly reduce the severity of the fall in long-term health consequences. This work proposes a solution based on the internet of things devices installed in people’s homes. The proposed non-wearable solution is non-intrusive and can be deployed not only in homes but also in hospitals, rehabilitation facilities, and elderly homes. The solution uses a three-layered computation architecture composed of edge, fog, and cloud. A mathematical model using the Morlet wavelet and an artificial intelligence model using artificial neural networks are used for human fall classification; both approaches are compared. The results showed that the combination of both models is possible and brings benefits to the system, achieving an accuracy of 92.5% without false negatives.
Control and Optimization of Lattice Converters
Authors: Mei Zhiting , Fang Jingyang , Goetz Stefan
Published: February 2022

Multilevel converters continue their upward trend in renewable generation, electric vehicles, and power quality conditioning applications. Despite having satisfactory voltage capabilities, mainstream multilevel converters suffer from poor current sharing performances, thereby leading to the development of lattice converters, i.e., a strong and versatile type of future multilevel power converters. This article addresses two problems faced by lattice converters. First, we propose and detail how to optimize the efficiency of a given lattice converter by controlling the on/off states of H-bridge submodules. Second, we introduce the method that determines the voltage at each node of the converter in order to satisfy output voltage and current requirements. Design and analysis of lattice converters need a different mathematical toolbox than routinely exercised in power electronics. By use of graph theory, this article provides control methods of 3 × 3 and 4 × 4 lattice converters, satisfying various control objectives such as input/output terminals and output voltages. We further validate the methods with simulation results. The methodologies, algorithms, and special cases described in the article will aid further design and refinement of more efficient and easy-to-control lattice converters.
Calculation of the Voltage Unbalance Factor for High-Speed Railway Substations with V-Connection Scheme
Authors: Flumian Didier , Ladoux Philippe , Sarraute Emmanuel
Published: February 2022

In France, high-speed railway lines are powered by a 2 × 25 kV/50 Hz electrification system. The substations include two single-phase transformers connected to the high-voltage electrical transmission network on different pairs of phases according to a so-called “V-connection scheme”. In practice, due to the large variations in the power absorbed by the trains, this connection does not make it possible to satisfactorily limit the unbalance in the three-phase voltages. In order to correctly size a balancing system to be associated with the substation, it is necessary to calculate, with precision, the voltage unbalance factor as a function of the power drawn by the trains. In its first part, this paper presents modelling of the substation and proposes an algorithm which allows for the calculation of the upstream line voltage as a function of the power consumption at the secondary of the transformers. The voltage unbalance factor can then be determined over a long period of operation. In the second part of this paper, the same approach is applied with an unbalance-compensator based on Steinmetz circuits controlled by AC choppers. Finally, in both cases, the results of the calculations are validated by simulations performed with PLECS simulation software.
An Overall Analysis of the Static Characteristics of the Single Active Bridge Converter
Authors: Rodriguez Alberto , Sebastian Javier , Lamar Diego G. , Hernando Marta M. , Ayarzaguena Iban , Larrazabal Igor , Ortega David , Bermejo Jose M. , Vazquez Francisco
Published: February 2022

The dual active bridge (DAB) converter has been extensively analyzed and used in recent years for applications where bidirectional power flow is required. The unidirectional version of the DAB, which replaces the active output bridge with a diode bridge, has been called the single active bridge (SAB). The static behavior of the SAB differs markedly from similar DC/DC converters and can provide interesting advantages in certain applications. This paper presents a thorough study of the static behavior of the single active bridge (SAB) converter in different conduction modes. This study focuses on the description of the conduction modes, marking the main differences compared to similar DC/DC converters. Moreover, the SAB can be designed to operate in conduction mode for a given power level with different performance. A design guide is proposed, and the performance of different designs are compared, quantifying current stresses in the semiconductors. Finally, the main contribution of this paper is the identification of the similarities and differences between the SAB and the buck, forward, and phase-shifted full-bridge converters. It should be noted that the position of the inductor, either before or after the output rectifier bridge, modifies the voltage withstood by the output diodes and depends on the conduction mode, the voltage conversion ratio of the converter, and consequently, its main operation and performance. Moreover, the operation of the SAB is similar to a current source in all conduction modes, and it is not usual in similar converters. This peculiar behavior can be useful in certain applications. The theoretical study, the different designs, and the predicted operation of the SAB in different conduction modes have been validated using simulation and experimental results.
Robust Errorless-Control-Targeted Technique Based on MPC for Microgrid with Uncertain Electric Vehicle Energy Storage Systems
Authors: Liang Yalin , He Yuyao , Niu Yun
Published: February 2022

Regarding the microgrid with large-scale electric vehicle (EV) energy storage systems working at the vehicle-to-grid (V2G) mode, uncertain factors (e.g., the number of EVs feeding the microgrid shifts frequently) make the system unfixed, leading to the fact that it is difficult to precisely determine the real-time droop coefficients of the system, thereby degrading the performance of the traditional inverter control strategies that rely on the droop coefficients. To solve the problem, this paper proposes an errorless-control-targeted double control loop (DCL) technique based on robust MPC to control the microgrid with EV energy storage systems without using droop coefficients. Firstly, the structure of the DCL method is developed, with each component in the structure detailed. Compared to the traditional control strategies, the novel one regards the frequency, voltage, and currents as the control objectives instead of active/inactive power. It deserves to be mentioned that the frequency and voltage are regulated by proportional-integral controllers, while the currents are regulated by the finite control set model predictive control (FCS-MPC) method. Secondly, the impacts of system parameter uncertainties on the prediction accuracy of the FCS-MPC controller are analyzed clearly, illustrating that it is necessary to develop effective techniques to enhance the robustness of the controller. Thirdly, sliding mode observers (SMO) based on a novel hyperbolic function are constructed to detect the real-time disturbances, which can be used to generate voltage compensations by using automatic disturbance regulators. Then, the voltage compensations are adopted to establish a modified predicting plant model (PPM) used for the FCS-MPC controller. By using the proposed SMO-based disturbance detection and compensation techniques, the MPC controller gains a strong robustness against parameter uncertainties. Finally, a simulation is conducted on a microgrid system to verify the effectiveness of the proposed techniques, and the obtained results are compared with the traditional virtual synchronous machine (VSG) strategy relying on droop coefficients.
A Wide-Area Fuzzy Control Design with Latency Compensation to Mitigate Sub-Synchronous Resonance in DFIG-Based Wind Farms
Authors: Bostani Yaser , Jalilzadeh Saeid , Mobayen Saleh , Fekih Afef , Assawinchaichote Wudhichai
Published: February 2022

This paper proposes an auxiliary damping control approach based on the wide-area measurement system (WAMS). Its main objective is to mitigate sub-synchronous resonance (SSR) in doubly fed induction generator (DFIG)-based wind farms connected to a series capacitive compensated transmission network. To mitigate the delay in sending measurement signals, typically associated with wide-area measurement systems, a fuzzy logic wide-area damping controller (FLWADC) is considered to mitigate the time delay caused by the phasor measurement unit (PMU) measurement. The FLWADC is a supplementary signal at the stator voltage of the grid-side converter (GSC) of the DFIG-based wind farms. The FLWADC was executed by using the voltage and capacitor voltage variations of the series capacitive compensated transmission network. The effectiveness and validity of the proposed auxiliary damping control was verified using a modified scheme of the IEEE first benchmark model via time-area simulation analysis using MATLAB/Simulink.
Impact of PWM Voltage Waveforms in High-Speed Drives: A Survey on High-Frequency Motor Models and Partial Discharge Phenomenon
Authors: D’Amato Davide , Loncarski Jelena , Monopoli Vito Giuseppe , Cupertino Francesco , Di Noia Luigi Pio , Del Pizzo Andrea
Published: February 2022

The insulation system’s dielectric of the electric motor is very often subjected to severe electrical stress generated by the high dv/dt seen at the machine’s terminals. The electrical stress and high reflected wave transient overvoltage are even more evident in case of high-speed machines fed by high-frequency (HF) converters featuring very fast wide-bandgap devices. They are promoting the occurrence of partial discharges and consequently accelerate ageing. As this is serious issue and the main cause of the drive failure, it is important to analyse and characterise the surges at the motor terminals. Several HF models of motors have been proposed in the literature for this purpose. This article presents a survey on HF motor models, which is crucial in understanding and studying the most critical parameter identification and overvoltage mitigation techniques. Moreover, it offers a comparison of the models’ main features as well as a comparison with the experimental voltage waveform at motor terminals. A general overview of the partial discharge (PD) phenomenon is also provided, as it is favoured by HF operation and together with HF motor modelling provides key insights to the insulation ageing issue. In particular, an analysis of the effects of PWM waveform affecting insulation is given, as well as useful methods for developing strategies for the inspection and maintenance of winding insulation.
Performance Analysis of Calcium-Doped Titania (TiO2) as an Effective Electron Transport Layer (ETL) for Perovskite Solar Cells
Authors: Arshad Zafar , Shakir Sehar , Khoja Asif Hussain , Javed Ahad Hussain , Anwar Mustafa , Rehman Abdur , Javaid Rahat , Qazi Umair Yaqub , Farrukh Sarah
Published: February 2022

Ca-doped TiO2 films were synthesized by the modified sol-gel method and employed as the electron transport material of perovskite solar cells (PSCs). Morphological, optoelectronic, thermal, and electrical studies of thin films were investigated through XRD, RAMAN, SEM, AFM, UV-Vis, FTIR, and IV characteristics. Ca doping was detected with the help of structural properties while morphological analysis revealed that thin films based on Ca-doped titania are crack-free, homogenous, and uniformly distributed. Further optoelectronic properties have shown a promising conversion efficiency of 9.79% for 2% Ca-doped titania followed by 1% Ca-doped titania, while 3% have shown the lowest conversion efficiency among these prepared samples. The 2% an optimized doping of Ca has shown an almost two-fold increase in conversion efficiency in comparison to pristine TiO2, along with an increase in current density from 15 mA⋅cm−2 to 19.3 mA⋅cm−2. Improved energy efficiency and higher current density are attributed to faster electron transportation; moreover, the optimized percentage of Ca doping seems to be an effective approach to improve the PSCs’ performance.
Overview of SERMA’s Graphical User Interfaces for Lattice Transport Calculations
Authors: Tomatis Daniele , Bidault François , Bruneton Adrien , Stankovski Zarko
Published: February 2022

This article presents an overview of the graphical user interfaces (GUIs) developed at CEA/SERMA (Service d’Études des Réacteurs et de Mathématiques Appliquées) in Saclay, France, which have been used for over forty years by engineers and scientists to build geometries and meshes for general-purpose lattice transport calculations (neutrons and photons). Several applications make use of these calculations, from fuel assembly to full core design, criticality and safety, needing consistency check of the geometry and input properties before starting any lattice calculation. The software pattern design of the GUIs is briefly discussed, showing also the rationale behind the two interfaces for the construction of the geometries for simple fuel assemblies and complex motifs including the reflector (colorsets). The new GUI, ALAMOS, specifically developed for APOLLO3® with a Python Application Programming Interface (API), is here presented as the successor of Silène, which was the first GUI released in the 1990s to serve APOLLO2 calculations. The considerable experience gained by Silène over the years with plenty of various applications has provided a crucial support for the development of ALAMOS.
Life Cycle and Exergoenvironmental Analyses of Ethanol: Performance of a Flex-Fuel Spark-Ignition Engine at Wide-Open Throttle Conditions
Authors: Cavalcanti Eduardo J. C. , da Silva Daniel R. S. , Carvalho Monica
Published: February 2022

The growth in the number of vehicles circulating has led to a proportional increase in polluting gas emissions. Bioenergy can be used to help meet these increasing energy demands and mitigate environmental impacts. This work verified the effect of the content of ethanol on the exergy and exergoenvironmental analyses of a spark-ignition engine. Different gasoline–ethanol mixtures were tested along with hydrous ethanol (4.6% water by volume). The thermodynamic data refer to wide-open throttle conditions and variable engine speeds. The life cycle assessment methodology quantified the environmental impacts associated with equipment and fuel using the Eco-indicator 99 method. Pollutants emitted during combustion were measured and included in the environmental assessment (nitrogen oxides, carbon monoxide, and dioxide). Hydrous ethanol at 1500 rpm presented the highest energy efficiency. The effects of the environmental impact rate of pollutant formation and exergy efficiency were significantly higher than the environmental impact rate of fuel. The lowest specific environmental impact of the product (brake power) was 24.39 mPt/MJ, obtained with the fuel blend with 50% ethanol at 2500 rpm. The combined evaluation of the exergoenvironmental factor and the relative difference in environmental impact indicated the optimization priorities and where improvements should be directed.
Metabolomic Analysis Reveals Nutritional Diversity among Three Staple Crops and Three Fruits
Authors: Shi Yunxia , Guo Yanxiu , Wang Yuhui , Li Mingyang , Li Kang , Liu Xianqing , Fang Chuanying , Luo Jie
Published: February 2022

More than 2 billion people worldwide are under threat of nutritional deficiency. Thus, an in-depth comprehension of the nutritional composition of staple crops and popular fruits is essential for health. Herein, we performed LC-MS-based non-targeted and targeted metabolome analyses with crops (including wheat, rice, and corn) and fruits (including grape, banana, and mango). We detected a total of 2631 compounds by using non-targeted strategy and identified more than 260 nutrients. Our work discovered species-dependent accumulation of common present nutrients in crops and fruits. Although rice and wheat lack vitamins and amino acids, sweet corn was rich in most amino acids and vitamins. Among the three fruits, mango had more vitamins and amino acids than grape and banana. Grape and banana provided sufficient 5-methyltetrahydrofolate and vitamin B6, respectively. Moreover, rice and grape had a high content of flavonoids. In addition, the three crops contained more lipids than fruits. Furthermore, we also identified species-specific metabolites. The crops yielded 11 specific metabolites, including flavonoids, lipids, and others. Meanwhile, most fruit-specific nutrients were flavonoids. Our work discovered the complementary pattern of essential nutrients in crops and fruits, which provides metabolomic evidence for a healthy diet.
The Blazar Sequence and Its Physical Understanding
Authors: Prandini Elisa , Ghisellini Gabriele
Published: February 2022

Introduced in 1998 to attempt a first unified view of the broad-band emission properties of blazars, the blazar sequence has been extensively used in the past 25 years to guide observations as well as the physical interpretation of the overall emission from these galaxies. In this review, we describe the evolution of the sequence along with the tremendous advances in the observational field, in particular in the gamma-ray band. A new version of the sequence built on TeV-detected objects is also presented. Two extreme classes of objects (MeV and hard-TeV blazars) are included in the discussion, given their relevance for future observatories. Finally, the current physical understanding at the base of the sequence is presented along with the major criticisms to the blazar sequence.
Review of the Advanced LIGO Gravitational Wave Observatories Leading to Observing Run Four
Authors: Cahillane Craig , Mansell Georgia
Published: February 2022

Gravitational waves from binary black hole and neutron star mergers are being regularly detected. As of 2021, 90 confident gravitational wave detections have been made by the LIGO and Virgo detectors. Work is ongoing to further increase the sensitivity of the detectors for the fourth observing run, including installing some of the A+ upgrades designed to lower the fundamental noise that limits the sensitivity to gravitational waves. In this review, we will provide an overview of the LIGO detectors optical configuration and lock acquisition procedure, discuss the detectors’ fundamental and technical noise limits, show the current measured sensitivity, and explore the A+ upgrades currently being installed in the detectors.
Analysis of Massaciuccoli Peat after Maturation in Sodium Chloride Water of Undulna Thermae
Authors: Di Pasqua Laura Giuseppina , Berardo Clarissa , Raffo Lorenzo , Ferrigno Andrea , Guffanti Enrico , Vairetti Mariapia
Published: February 2022

In Italy, peat extracted from the peat bogs of Lake Massaciuccoli is the only peat used for therapeutic purposes. Massaciuccoli peat (M-peat) soaked in the salty bromine–iodine water of Undulna Thermae has given positive results in various pathological situations, mainly in dermatological, rheumatological, and traumatological conditions. Morphological and biochemical analysis were performed using base M-peat samples matured in the salty bromine–iodine water of the Undulna Thermae for different times, to evaluate whether maturation time modifies peat chemico-physical properties. The maturation process induced particle aggregation, with an increase in the fractions with larger particle size. The presence of a high number of proteins derived from organic degradation was observed; after 6 months of maturation, a significant increase in proteins was found, suggesting that salty bromine–iodine water plays a role in the clinical action of the peat. The presence of lipids in M-peat was also confirmed, allowing us to draw important considerations on its therapeutic properties possibly deriving from the relevant interactions between lipids and humic acids. Finally, from our observations, it could be reasonably argued that longer periods of maturation do not result in additional advantages regarding clinical activity.
Proposal of a Comprehensive and Multi-Component Approach to Promote Physical Activity among Japanese Office Workers: A Qualitative Focus Group Interview Study
Authors: Kim Jihoon , Mizushima Ryoko , Nishida Kotaro , Morimoto Masahiro , Nakata Yoshio
Published: February 2022

Office workers spend up to two-thirds of their working hours sitting and are less physically active than other occupational groups. It is necessary to develop an effective approach to promote physical activity among office workers. We conducted a focus group interview with seven Japanese office workers to investigate the current status (topic 1) of, and their opinions on (topic 2), physical activity promotion programs in their workplace. Data were analyzed using qualitative data analysis. We classified the data from topic 1 into individual, socio-cultural, physical, and organizational environments. Most participants indicated that they spent a lot of time sitting and needed programs for a wide range of corresponding employee demands. We classified the data from topic 2 into capability, opportunity, and motivation. Most participants indicated that they wanted evidence-based information, a standing desk, and a conducive workplace environment to enhance physical activity. Thus, we proposed a comprehensive and multi-component approach comprising individual (information delivery), socio-cultural environment (team building, supportive atmosphere), physical environment (standing desk, use of poster), and organizational (incentive, encouraging message from an executive, workplace policy) strategies. Future studies should evaluate the effectiveness of this proposal.