bluuebunny/crossref_metadata_2025 huggingface dataset:
Epidemiology of Mucopolysaccharidoses Update
Authors: Celik Betul , Tomatsu Saori C. , Tomatsu Shunji , Khan Shaukat A.
Published: February 2021

Mucopolysaccharidoses (MPS) are a group of lysosomal storage disorders caused by a lysosomal enzyme deficiency or malfunction, which leads to the accumulation of glycosaminoglycans in tissues and organs. If not treated at an early stage, patients have various health problems, affecting their quality of life and life-span. Two therapeutic options for MPS are widely used in practice: enzyme replacement therapy and hematopoietic stem cell transplantation. However, early diagnosis of MPS is crucial, as treatment may be too late to reverse or ameliorate the disease progress. It has been noted that the prevalence of MPS and each subtype varies based on geographic regions and/or ethnic background. Each type of MPS is caused by a wide range of the mutational spectrum, mainly missense mutations. Some mutations were derived from the common founder effect. In the previous study, Khan et al. 2018 have reported the epidemiology of MPS from 22 countries and 16 regions. In this study, we aimed to update the prevalence of MPS across the world. We have collected and investigated 189 publications related to the prevalence of MPS via PubMed as of December 2020. In total, data from 33 countries and 23 regions were compiled and analyzed. Saudi Arabia provided the highest frequency of overall MPS because of regional or consanguineous marriages (or founder effect), followed by Portugal, Brazil, the Netherlands, and Australia. The newborn screening is an efficient and early diagnosis for MPS. MPS I has been approved for newborn screening in the United States. After the newborn screening of MPS I, the frequency of MPS I increased, compared with the past incidence rates. Overall, we conclude that the current identification methods are not enough to recognize all MPS patients, leading to an inaccurate incidence and status. Differences in ethnic background and/or founder effects impact on the frequency of MPS, which affects the prevalence of MPS. Two-tier newborn screening has accelerated early recognition of MPS I, providing an accurate incidence of patients.
Clinico-Pathological Importance of miR-146a in Lung Cancer
Authors: Wani Javaid Ahmad , Majid Sabhiya , Khan Andleeb , Arafah Azher , Ahmad Ajaz , Jan Basit Latief , Shah Naveed Nazir , Kazi Mohsin , Rehman Muneeb U.
Published: February 2021

Lung cancer is a well-known malignant tumor of the respiratory tract, which has caused a significant level of damage to human health in the 21st century. Micro-RNAs (miRNAs) are tiny, non-coding RNA stem-loop structures with a length of roughly 20–25 nucleotides that function as powerful modulators of mRNA and protein products of a gene. miRNAs may modulate many biological processes involving growth, differentiation, proliferation, and cell death and play a key role in the pathogenesis of various types of malignancies. Several accumulating pieces of evidence have proven that miRNA, especially miR-146a, are crucial modulators of innate immune response sequences. A novel and exciting cancer research field has involved miRNA for the detection and suppression of cancer. However, the actual mechanism which is adopted by these miRNA is still unclear. miRNAs have been used as a cancer-associated biomarker in several studies, suggesting their altered expression in various cancers compared to the normal cells. The amount of expression of miRNA can also be used to determine the stage of the disease, aiding in early detection. In breast, pancreatic, and hepatocellular carcinoma, and gastric cancer, cancer cell proliferation and metastasis has been suppressed by miR-146a. Changes in miR-146a expression levels have biomarker importance and possess a high potential as a therapeutic target in lung cancer. It retards epithelial-mesenchymal transition and promotes the therapeutic action of anticancer agents in lung cancer. Studies have also suggested that miR-146a affects gene expression through different signaling pathways viz. TNF-α, NF-κB and MEK-1/2, and JNK-1/2. Further research is required for understanding the molecular mechanisms of miR-146a in lung cancer. The potential role of miR-146a as a diagnostic marker of lung cancer must also be analyzed. This review summarizes the tumor-suppressing, anti-inflammatory, and antichemoresistive nature of miR-146a in lung cancer.
Preoperative Cognitive Impairment and the Prevalence of Postoperative Delirium in Elderly Cancer Patients—A Prospective Observational Study
Authors: Ristescu Anca Irina , Pintilie Georgiana , Moscalu Mihaela , Rusu Daniel , Grigoras Ioana
Published: February 2021

Preoperative cognitive impairment (PCI) in cancer patients includes a broad spectrum of neurocognitive changes produced by complex interplay of patient, tumoural and treatment-related factors. Reduced preoperative cognitive reserve can favour the emergence of postoperative delirium (POD). The study aims to document PCI prevalence and to assess the relationship with POD in elderly cancer patients. The prospective observational study included consecutive patients scheduled for elective surgery; PCI was assessed with Mini-Cog test and defined at a score ≤ 3, POD was screened using Nursing Delirium Screening Scale (Nu-DESC) and defined at a score ≥ 2. Data on education, American Society of Anesthesiologists (ASA) score, preoperative medications, substance use, comorbidities, sensorial deficits, surgery and anaesthesia type, anaesthetic drugs, Mini-Cog score, postoperative pain, Nu-DESC were collected. In total, 131 patients were enrolled, mean age 72.1 ± 5.9 years. PCI prevalence was 51.9% (n = 68). POD prevalence was 19.8% (n = 26), with significantly higher value in PCI patients (27.9% vs. 11.1%, p = 0.016). In multivariate analysis, Mini-Cog score ≤ 3 (OR = 2.6, p = 0.027), clock draw (OR: 2.9, p = 0.013), preoperative renal dysfunction (OR = 2.6, p = 0.012), morphine (OR = 2.7, p = 0.007), metoclopramide (OR = 6.6, p = 0.006), and high pain score (OR = 1.8, p = 0.018) had a significant association with POD development. In this sample of elderly patients, PCI had a high prevalence and predicted the emergence of POD. Incorporating Mini-Cog test into the preoperative evaluation of onco-geriatric patients seems valuable and feasible.
Salivary Inflammatory Molecules as Biomarkers of Sleep Alterations: A Scoping Review
Authors: Ibáñez-del Valle Vanessa , Navarro-Martínez Rut , Ballestar-Tarín Maria Luisa , Cauli Omar
Published: February 2021

Poor sleep quality and sleep disorders are the most common problems in people, affecting health-related quality of life. Various studies show an association between sleep disorders and altered levels of stress hormones and inflammatory cytokines measured in saliva. The main objective of this article is to provide an analysis of the current evidence related to changes in inflammatory markers in the saliva and their associations with sleep quality measurement (both objective and subjective methods) in healthy subjects and in sleep-related disorders. To that end, a scoping review was carried out, following the PRISMA criteria in the bibliographic search in several databases: PubMed, EBSCO, and SCOPUS. Eleven of the articles are from the adult population and two from the child-youth population. They mainly measure the relationship between sleep and interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor alpha (TNFα) alpha, as well as other inflammatory markers such as myeloperoxidase (MPO) and prostaglandin-endoperoxide synthase 2. An analysis shows the relationship between these salivary biomarkers and sleep quality, especially in the case of IL-6 in both healthy subjects and several pathologies associated with sleep-disorders. The results for TNFα and IL-1β measurements are still inconclusive and the difference with IL-6 was assessed. Two studies reported interventions that result in sleep improvement and are accompanied by the normalization of inflammatory changes detected in the saliva. As it is an easy-to-apply and non-invasive method, the measurement of salivary cytokines can be very useful in chronobiology studies. Further studies are required to determine the sensitivity of salivary inflammatory markers in monitoring biological rhythms and acting as biomarkers in the detection of sleep disorders and sleep interventions.
Rapid Diagnosis of Pseudomonas aeruginosa in Wounds with Point-Of-Care Fluorescence Imaing
Authors: Raizman Rose , Little William , Smith Allie Clinton
Published: February 2021

Pseudomonas aeruginosa (PA) is a common bacterial pathogen in chronic wounds known for its propensity to form biofilms and evade conventional treatment methods. Early detection of PA in wounds is critical to the mitigation of more severe wound outcomes. Point-of-care bacterial fluorescence imaging illuminates wounds with safe, violet light, triggering the production of cyan fluorescence from PA. A prospective single blind clinical study was conducted to determine the positive predictive value (PPV) of cyan fluorescence for the detection of PA in wounds. Bacterial fluorescence using the MolecuLight i:X imaging device revealed cyan fluorescence signal in 28 chronic wounds, including venous leg ulcers, surgical wounds, diabetic foot ulcers and other wound types. To correlate the cyan signal to the presence of PA, wound regions positive for cyan fluorescence were sampled via curettage. A semi-quantitative culture analysis of curettage samples confirmed the presence of PA in 26/28 wounds, resulting in a PPV of 92.9%. The bacterial load of PA from cyan-positive regions ranged from light to heavy. Less than 20% of wounds that were positive for PA exhibited the classic symptoms of PA infection. These findings suggest that cyan detected on fluorescence images can be used to reliably predict bacteria, specifically PA at the point-of-care.
A Growth Differentiation Factor 15-Based Risk Score Model to Predict Mortality in Hemodialysis Patients
Authors: Chang Jia-Feng , Chen Po-Cheng , Hsieh Chih-Yu , Liou Jian-Chiun
Published: February 2021

Background: The risk of cardiovascular (CV) and fatal events remains extremely high in patients with maintenance hemodialysis (MHD), and the growth differentiation factor 15 (GDF15) has emerged as a valid risk stratification biomarker. We aimed to develop a GDF15-based risk score as a death prediction model for MHD patients. Methods: Age, biomarker levels, and clinical parameters were evaluated at study entry. One hundred and seventy patients with complete information were finally included for data analysis. We performed the Cox regression analysis of various prognostic factors for mortality. Then, age, GDF15, and robust clinical predictors were included as a risk score model to assess the predictive accuracy for all-cause and CV death in the receiver operating characteristic (ROC) curve analysis. Results: Age, GDF15, and albumin were significantly associated with higher all-cause and CV mortality risk that were combined as a risk score model. The highest tertile of GDF-15 (>1707.1 pg/mL) was associated with all-cause mortality (adjusted hazard ratios (aHRs): 3.06 (95% confidence interval (CI): 1.20–7.82), p < 0.05) and CV mortality (aHRs: 3.11 (95% CI: 1.02–9.50), p < 0.05). The ROC analysis of GDF-15 tertiles for all-cause and CV mortality showed 0.68 (95% CI = 0.59 to 0.77) and 0.68 (95% CI = 0.58 to 0.79), respectively. By contrast, the GDF15-based prediction model for all-cause and CV mortality showed 0.75 (95% CI: 0.67–0.82) and 0.72 (95% CI: 0.63–0.81), respectively. Conclusion: Age, GDF15, and hypoalbuminemia predict all-cause and CV death in MHD patients, yet a combination scoring system provides more robust predictive powers. An elevated GDF15-based risk score warns clinicians to determine an appropriate intervention in advance. In light of this, the GDF15-based death prediction model could be developed in the artificial intelligence-based precision medicine.
SARS-CoV-2 Subgenomic N (sgN) Transcripts in Oro-Nasopharyngeal Swabs Correlate with the Highest Viral Load, as Evaluated by Five Different Molecular Methods
Authors: Zollo Massimo , Ferrucci Veronica , Izzo Barbara , Quarantelli Fabrizio , Domenico Carmela Di , Comegna Marika , Paolillo Carmela , Amato Felice , Siciliano Roberto , Castaldo Giuseppe , Capoluongo Ettore
Published: February 2021

The COVID-19 pandemic has forced diagnostic laboratories to focus on the early diagnostics of SARS-CoV-2. The positivity of a molecular test cannot respond to the question regarding the viral capability to replicate, spread, and give different clinical effects. Despite the fact that some targets are covered by commercially-available assays, the identification of new biomarkers is desired in order to improve the quality of the information given by these assays. Therefore, since the subgenomic transcripts (sgN and sgE) are considered markers of viral activity, we evaluated these subgenomic transcripts in relation to the genomic amplification obtained using five different commercial CE-IVD tools. Methods: Five CE-IVD kits were compared in terms of their capability to detect both synthetic SARS-CoV-2 viral constructs (spiked in TMB or PBS medium) and targets (N, E, RdRp and Orf1ab genes) in twenty COVID-19–positive patients’ swabs. The sgN and sgE were assayed by real-time RT-qPCR and digital PCR. Results: None of the diagnostic kits missed the viral target genes when they were applied to targets spiked in TMB or PBS (at dilutions ranging from 100 pg to 0.1 pg). Nevertheless, once they were applied to RNA extracted from the patients’ swabs, the superimposability ranged from 50% to 100%, regardless of the extraction procedure. The sgN RNA transcript was detected only in samples with a higher viral load (Ct ≤ 22.5), while sgE was within all of the Ct ranges. Conclusions: The five kits show variable performances depending on the assay layout. It is worthy of note that the detection of the sgN transcript is associated with a higher viral load, thus representing a new marker of early and more severe infection.
AI-Based Radiological Imaging for HCC: Current Status and Future of Ultrasound
Authors: Maruyama Hitoshi , Yamaguchi Tadashi , Nagamatsu Hiroaki , Shiina Shuichiro
Published: February 2021

Hepatocellular carcinoma (HCC) is a common cancer worldwide. Recent international guidelines request an identification of the stage and patient background/condition for an appropriate decision for the management direction. Radiomics is a technology based on the quantitative extraction of image characteristics from radiological imaging modalities. Artificial intelligence (AI) algorithms are the principal axis of the radiomics procedure and may provide various results from large data sets beyond conventional techniques. This review article focused on the application of the radiomics-related diagnosis of HCC using radiological imaging (computed tomography, magnetic resonance imaging, and ultrasound (B-mode, contrast-enhanced ultrasound, and elastography)), and discussed the current role, limitation and future of ultrasound. Although the evidence has shown the positive effect of AI-based ultrasound in the prediction of tumor characteristics and malignant potential, posttreatment response and prognosis, there are still a number of issues in the practical management of patients with HCC. It is highly expected that the wide range of applications of AI for ultrasound will support the further improvement of the diagnostic ability of HCC and provide a great benefit to the patients.
Phylogenetic Curved Optimal Regression for Adaptive Trait Evolution
Authors: Jhwueng Dwueng-Chwuan , Wang Chih-Ping
Published: February 2021

Regression analysis using line equations has been broadly applied in studying the evolutionary relationship between the response trait and its covariates. However, the characteristics among closely related species in nature present abundant diversities where the nonlinear relationship between traits have been frequently observed. By treating the evolution of quantitative traits along a phylogenetic tree as a set of continuous stochastic variables, statistical models for describing the dynamics of the optimum of the response trait and its covariates are built herein. Analytical representations for the response trait variables, as well as their optima among a group of related species, are derived. Due to the models’ lack of tractable likelihood, a procedure that implements the Approximate Bayesian Computation (ABC) technique is applied for statistical inference. Simulation results show that the new models perform well where the posterior means of the parameters are close to the true parameters. Empirical analysis supports the new models when analyzing the trait relationship among kangaroo species.
Fractional Order Graph Filters: Design and Implementation
Authors: Qiu Xinyi , Feng Hui , Hu Bo
Published: February 2021

Existing graph filters, polynomial or rational, are mainly of integer order forms. However, there are some frequency responses which are not easily achieved by integer order approximation. It will substantially increase the flexibility of the filters if we relax the integer order to fractional ones. Motivated by fractional order models, we introduce the fractional order graph filters (FOGF), and propose to design the filter coefficients by genetic algorithm. In order to implement distributed computation on a graph, an FOGF can be approximated by the continued fraction expansion and transformed to an infinite impulse response graph filter.
The Study of the Single Event Effect in AlGaN/GaN HEMT Based on a Cascode Structure
Authors: Liang Yanan , Chen Rui , Han Jianwei , Wang Xuan , Chen Qian , Yang Han
Published: February 2021

An attractive candidate for space and aeronautic applications is the high-power and miniaturizing electric propulsion technology device, the gallium nitride high electron mobility transistor (GaN HEMT), which is representative of wide bandgap power electronic devices. The cascode AlGaN/GaN HEMT is a common structure typically composed of a high-voltage depletion-mode AlGaN/GaN HEMT and low-voltage enhancement-mode silicon (Si) MOSFET connected by a cascode structure to realize its enhancement mode. It is well known that low-voltage Si MOSFET is insensitive to single event burnout (SEB). Therefore, this paper mainly focuses on the single event effects of the cascode AlGaN/GaN HEMT using technical computer-aided design (TCAD) simulation and heavy-ion experiments. The influences of heavy-ion energy, track length, and track position on the single event effects for the depletion-mode AlGaN/GaN HEMT were studied using TCAD simulation. The results showed that a leakage channel between the gate electrode and drain electrode in depletion-mode AlGaN/GaN HEMT was formed after heavy-ion striking. The enhancement of the ionization mechanism at the edge of the gate might be an important factor for the leakage channel. To further study the SEB effect in AlGaN/GaN HEMT, the heavy-ion test of a cascode AlGaN/GaN HEMT was carried out. SEB was observed in the heavy-ion irradiation experiment and the leakage channel was found between the gate and drain region in the depletion-mode AlGaN/GaN HEMT. The heavy-ion irradiation experimental results proved reasonable for the SEB simulation for AlGaN/GaN HEMT with a cascode structure.
Evaluation of VTH and RON Drifts during Switch-Mode Operation in Packaged SiC MOSFETs
Authors: Cioni Marcello , Bertacchini Alessandro , Mucci Alessandro , Zagni Nicolò , Verzellesi Giovanni , Pavan Paolo , Chini Alessandro
Published: February 2021

In this paper, we investigate the evolution of threshold voltage (VTH) and on-resistance (RON) drifts in the silicon carbide (SiC) power metal-oxide-semiconductor field-effect transistors (MOSFETs) during the switch-mode operation. A novel measurement setup for performing the required on-the-fly characterization is presented and the experimental results, obtained on commercially available TO-247 packaged SiC devices, are reported. Measurements were performed for 1000 s, during which negative VTH shifts (i.e., VTH decrease) and negative RON drifts (i.e., RON decrease) were observed. To better understand the origin of these parameter drifts and their possible correlation, measurements were performed for different (i) gate-driving voltage (VGH) and (ii) off-state drain voltage (VPH). We found that VTH reduction leads to a current increase, thus yielding RON to decrease. This correlation was explained by the RON dependence on the overdrive voltage (VGS–VTH). We also found that gate-related effects dominate the parameter drifts at low VPH with no observable recovery, due to the repeated switching of the gate signal required for the parameter monitoring. Conversely, the drain-induced instabilities caused by high VPH are completely recoverable within 1000 s from the VPH removal. These results show that the measurement setup is able to discern the gate/drain contributions, clarifying the origin of the observed VTH and RON drifts.
CDM Protection Test Structure for I/O Cells in a Submicronic Technology
Authors: Dobre Mihaela-Daniela , Coll Philippe , Brezeanu Gheorghe
Published: February 2021

This paper proposes an investigation of a CDM (charge device model) electrostatic discharge (ESD) protection method used in submicronic input–output (I/O) structures. The modeling of the commonly used ESD protection devices as well as the modeling of the breakdown caused by ESD is not accurate using traditional commercial tools, hence the need for test-chip implementation, whenever a new technology node is used in production. The proposed method involves defining, implementing, testing, and concluding on one test-chip structure named generically “CDM ground resistance”. The structure assesses the maximum ground resistance allowed for the considered technology for which CDM protection is assured. The findings are important because they will be actively used as CDM protection for all I/O structures developed in the considered submicronic technology node. The paper will conclude on the constraints in terms of maximum resistance of ground metal track allowed to be CDM protected.
Improved Intelligent Image Segmentation Algorithm for Mechanical Sensors in Industrial IoT: A Joint Learning Approach
Authors: Xie Xin , Wan Tiancheng , Wang Bin , Cai Tijian , Yu Ao , Cheriet Mohamed , Hu Fengping
Published: February 2021

The industrial Internet of Things (IoT) can monitor production in real-time by collecting the status of parts on the production line with cameras. It is easy to have bright and dark areas in the same image because of the smooth surfaces of mechanical parts and the unstable light source, which affects semantic segmentation’s performance. This paper proposes a joint learning method to eliminate the influence of illumination on semantic segmentation. Semantic image segmentation and image decomposition are jointly trained in the same model, and the reflectance image is used to guide the semantic segmentation task without the illumination component. Moreover, this paper adopts an enhanced convolution kernel to improve the pixel accuracy and BN fusion to enhance the inference speed, optimizing the model to meet real-time detection needs. In the experiments, a dataset of real gear parts was collected from industrial IoT cameras. The experimental results show that the proposed joint learning approach outperforms the state-of-the-art methods in the task of edge mechanical part detection, with about 4% pixel accuracy improvement.
Model-Free Control Using Improved Smoothing Extended State Observer and Super-Twisting Nonlinear Sliding Mode Control for PMSM Drives
Authors: Gao Peng , Zhang Guangming , Lv Xiaodong
Published: February 2021

This paper proposes a novel model-free super-twisting nonlinear sliding mode control (MFSTNLSMC) strategy with an improved smoothing extended state observer (SESO) for permanent magnet synchronous motor (PMSM) drives. First of all, the improved SESO is introduced to estimate the unknown term of the PMSM ultra-local model. Secondly, a novel nonlinear sliding mode surface (NLSMS) is designed, which can effectively overcome the disadvantages of simple and rough signal processing of the conventional linear sliding mode surface. At the same time, a super-twisting (ST) structure is chosen to suppress the chattering phenomenon and improve system robustness. Then, the Lyapunov stability theorem is used to prove the stability of the proposed control algorithm. Finally, both comparative simulations and experimental demonstrations verify the excellent speed tracking performance and robustness of the proposed control strategy.
Comparison of Conventional and Variable Borehole Heat Exchangers for Use in a Desiccant Assisted Air Conditioning System
Authors: Richter Finn , Niemann Peter , Schuck Matthias , Grabe Jürgen , Schmitz Gerhard
Published: February 2021

The objective of this work is to analyze a gas injection borehole heat exchanger coupled with a desiccant assisted air conditioning system during cooling and heating operation. A common problem that occurs in air conditioning systems is peak loads, during which the cooling or heating power of the soil can be exceeded. To counteract this drawback, a gas injection borehole heat exchanger, which is capable of creating artificial groundwater flow along the heat exchanger by inducing a pressure difference inside the well, is used. Experimental results of the performance differences between a conventional and a gas injection borehole heat exchanger are presented. Under the same inlet conditions, a reduction in the outlet temperature of up to 2 °C is achieved compared with an equivalent conventional borehole heat exchanger in cooling mode. The maximum cooling power is increased by 26%. As a result, a fast and dynamic responding control of the heat transfer between the heat exchanger and the soil is possible. During winter operation, despite the lower drilling depth of the gas injection borehole heat exchanger system, the performance is within the range of a conventional system. The power increase is limited to around 0.2 kWth at a steady state. In conclusion, gas injection borehole heat exchangers can be promising in terms of reliable peak load handling within large geothermal fields.
Mathematical Formulation and Analytic Solutions for Uncertainty Analysis in Probabilistic Safety Assessment of Nuclear Power Plants
Authors: Song Gyun Seob , Kim Man Cheol
Published: February 2021

Monte Carlo simulations are widely used for uncertainty analysis in the probabilistic safety assessment of nuclear power plants. Despite many advantages, such as its general applicability, a Monte Carlo simulation has inherent limitations as a simulation-based approach. This study provides a mathematical formulation and analytic solutions for the uncertainty analysis in a probabilistic safety assessment (PSA). Starting from the definitions of variables, mathematical equations are derived for synthesizing probability density functions for logical AND, logical OR, and logical OR with rare event approximation of two independent events. The equations can be applied consecutively when there exist more than two events. For fail-to-run failures, the probability density function for the unavailability has the same probability distribution as the probability density function (PDF) for the failure rate under specified conditions. The effectiveness of the analytic solutions is demonstrated by applying them to an example system. The resultant probability density functions are in good agreement with the Monte Carlo simulation results, which are in fact approximations for those from the analytic solutions, with errors less than 12.6%. Important theoretical aspects are examined with the analytic solutions such as the validity of the use of a right-unbounded distribution to describe the uncertainty in the unavailability/probability. The analytic solutions for uncertainty analysis can serve as a basis for all other methods, providing deeper insights into uncertainty analyses in probabilistic safety assessment.
Adaptive Fuzzy Approximation Control of PV Grid-Connected Inverters
Authors: Shadoul Myada , Yousef Hassan , Al Abri Rashid , Al-Hinai Amer
Published: February 2021

Three-phase inverters are widely used in grid-connected renewable energy systems. This paper presents a new control methodology for grid-connected inverters using an adaptive fuzzy control (AFC) technique. The implementation of the proposed controller does not need prior knowledge of the system mathematical model. The capabilities of the fuzzy system in approximating the nonlinear functions of the grid-connected inverter system are exploited to design the controller. The proposed controller is capable to achieve the control objectives in the presence of both parametric and modelling uncertainties. The control objectives are to regulate the grid power factor and the dc output voltage of the photovoltaic systems. The closed-loop system stability and the updating laws of the controller parameters are determined via Lyapunov analysis. The proposed controller is simulated under different system disturbances, parameters, and modelling uncertainties to validate the effectiveness of the designed controller. For evaluation, the proposed controller is compared with conventional proportional-integral (PI) controller and Takagi–Sugeno–Kang-type probabilistic fuzzy neural network controller (TSKPFNN). The results demonstrated that the proposed AFC showed better performance in terms of response and reduced fluctuations compared to conventional PI controllers and TSKPFNN controllers.
Functional Safety Concept to Support Hazard Assessment and Risk Management in Water-Supply Systems
Authors: Tchórzewska-Cieślak Barbara , Pietrucha-Urbanik Katarzyna , Eid Mohamed
Published: February 2021

Within the frame of upgrading and modernisation of the Water Supply System (WSS), our work is focussing on the safety systems/devices implemented or that should be implemented in the WSS. The implementation of safety systems is supposed to reduce hazard occurrence and hazardous consequences in case of a WSS unsafe disruption. To assess this reduction, we preconise the use of the safety integrity levels standards. The implementation of the safety systems/devices is undertaken on the ground of the multi-barriers safeguard approach. The “Water Contamination Hazard” is considered in the paper. A case study is presented, assessed and conclusions are drawn. The methodology presented in the paper and the results of the case study assessment will contribute to the decision-making regarding the upgrading of the safety and the performance of the WSS.
Visualization of Chemical Heavy Oil EOR Displacement Mechanisms in a 2D System
Authors: Guerrero Francy , Bryan Jonathan , Kantzas Apostolos
Published: February 2021

This study aims to develop a visual understanding of the macro-displacement mechanisms associated with heavy oil recovery by water and chemical flooding in a 2D system. The sweep efficiency improvements by water, surfactant, polymer, and surfactant-polymer (SP) were evaluated in a Hele-Shaw cell with no local pore-level trapping of fluids. The results demonstrated that displacement performance is highly correlated to the mobility ratio between the fluids. Surfactant and water reached similar oil recovery values at similar mobility ratios; however, they exhibited different flow patterns in the 2D system—reductions in IFT can lead to the formation of emulsions and alter flow pathways, but in the absence of porous media these do not lead to significant improvements in oil recovery. Polymer flooding displayed a more stable front and a higher reduction in viscous fingering. Oil recovery by SP was achieved mostly by polymer rather than due to the effect of the surfactant. The surfactant in the SP slug washed out residual oil in the swept zone without increasing the swept area. This shows the impact of the surfactant on reducing the oil saturation in water-swept zones, but the overall oil recovery was still controlled by the injection of polymer. This study provides insight into the fluid flow behavior in diverging flow paths, as opposed to linear core floods that have limited pathways. The visualization of bulk liquid interactions between different types of injection fluids and oil in the Hele-Shaw cell might assist in the screening process for new chemicals and aid in testing the production process.
A Novel Procedure for Coupled Simulation of Thermal and Fluid Flow Models for Rough-Walled Rock Fractures
Authors: Xiong Feng , Zhu Chu , Jiang Qinghui
Published: February 2021

An enhanced geothermal system (EGS) proposed on the basis of hot dry rock mining technology has become a focus of geothermal research. A novel procedure for coupled simulation of thermal and fluid flow models (NPCTF) is derived to model heat flow and thermal energy absorption characteristics in rough-walled rock fractures. The perturbation method is used to calculate the pressure and flow rate in connected wedge-shaped cells at pore-scale, and an approximate analytical solution of temperature distribution in wedge-shaped cells is obtained, which assumes an identical temperature between the fluid and fracture wall. The proposed method is verified in Barton and Choubey (1985) fracture profiles. The maximum deviation of temperature distribution between the proposed method and heat flow simulation is 13.2% and flow transmissivity is 1.2%, which indicates the results from the proposed method are in close agreement with those obtained from simulations. By applying the proposed NPCTF to real rock fractures obtained by a 3D stereotopometric scanning system, its performance was tested against heat flow simulations from a COMSOL code. The mean discrepancy between them is 1.51% for all cases of fracture profiles, meaning that the new model can be applicable for fractures with different fracture roughness. Performance analysis shows small fracture aperture increases the deviation of NPCTF, but this decreases for a large aperture fracture. The accuracy of the NPCTF is not sensitive to the size of the mesh.
Influence of the Preformed Coil Design on the Thermal Behavior of Electric Traction Machines
Authors: Groschup Benedikt , Pauli Florian , Hameyer Kay
Published: February 2021

Preformed coils are used in electrical machines to improve the copper slot fill factor. A higher utilization of the machine can be realized. The improvement is a result of both, low copper losses due to the increased slot fill factor and an improved heat transition out of the slot. In this study, the influence of these two aspects on the operational improvement of the machine is studied. Detailed simulation models allow a separation of the two effects. A preform wound winding in comparison to a round wire winding is studied. Full machine prototypes as well as motorettes of the two designs are built up. Thermal finite element models of the stator slot are developed and parameterized with the help of motorette microsections. The resulting thermal lumped parameter model is enlarged to represent the entire electric machine. Electromagnetic finite element models for loss calculation and the thermal lumped parameter models are parameterized using test bench measurements. The developed models show very good agreement in comparison to the test bench evaluation. The study indicates that both, the improvements in the heat transition path and the advantages of the reduced losses in the slot contribute to the improved operational range in dependency of the studied operational point.
A PWM/PFM Dual-Mode DC-DC Buck Converter with Load-Dependent Efficiency-Controllable Scheme for Multi-Purpose IoT Applications
Authors: Kim Myeong , Kim Jae
Published: February 2021

This paper presents a dual-mode DC-DC buck converter including a load-dependent, efficiency-controllable scheme to support multi-purpose IoT applications. For light-load applications, a selectable adaptive on-time pulse frequency modulation (PFM) control is proposed to achieve optimum power efficiency by selecting the optimum switching frequency according to the load current, thereby reducing unnecessary switching losses. When the inductor peak current value or converter output voltage ripple are considered in some applications, its on-time can be adjusted further. In heavy-load applications, a conventional pulse width modulation (PWM) control scheme is adopted, and its gate driver is structured to reduce dynamic current, preventing the current from shooting through the power switch. A proposed dual-mode buck converter prototype is fabricated in a 180 nm CMOS process, achieving its measured maximum efficiency of 95.7% and power density of 0.83 W/mm2.
Research on a Comprehensive Maintenance Optimization Strategy for an Offshore Wind Farm
Authors: Lu Yang , Sun Liping , Xue Yanzhuo
Published: February 2021

Offshore wind is considered a crucial part in the future energy supply. However, influenced by weather conditions, the maintenance of offshore wind turbine system (OWTs) equipment is challenged by poor accessibility and serious failure consequences. It is necessary to study the optimized strategy of comprehensive maintenance for offshore wind farms, with consideration of the influences of incomplete equipment maintenance, weather accessibility and economic relevance. In this paper, a Monte Carlo algorithm-improved factor is presented to simulate the imperfect preventive maintenance activity, and waiting windows were created to study the accessibility of weather conditions. Based on a rolling horizon approach, an opportunity group maintenance model of an offshore wind farm was proposed. The maintenance correlations between systems and between equipment as well as breakdown losses, maintenance uncertainty, and weather conditions were taken into account in the model, thus realizing coordination of maintenance activities of different systems and different equipment. The proposed model was applied to calculate the maintenance cost of the Dafengtian Offshore Wind Farm in China. Results proved that the proposed model could realize long-term dynamic optimization of offshore wind farm maintenance activities, increase the total availability of the wind power system and reduce total maintenance costs.
A Systematic Review on Predicting and Forecasting the Electrical Energy Consumption in the Manufacturing Industry
Authors: Walther Jessica , Weigold Matthias
Published: February 2021

In the context of the European Green Deal, the manufacturing industry faces environmental challenges due to its high demand for electrical energy. Thus, measures for improving the energy efficiency or flexibility are applied to address this problem in the manufacturing industry. In order to quantify energy efficiency or flexibility potentials, it is often necessary to predict or forecast the energy consumption. This paper presents a systematic review of state-of-the-art of existing approaches to predict or forecast the energy consumption in the manufacturing industry. Seventy-two articles are classified according to the defined categories System Boundary, Modelling Technique, Modelling Focus, Modelling Horizon, Modelling Perspective, Modelling Purpose and Model Output. Based on the reviewed articles future research activities are derived.
Measurement of Dielectric Liquid Electrification in the Shuttle System with Two Parallel Electrodes
Authors: Zmarzły Dariusz , Frącz Paweł
Published: February 2021

In this paper, a device with swinging plate electrodes has been proposed to measure contact electrification of a liquid sample. The proposed structure is composed of two parallel metallic plates immersed in a dielectric liquid. One of the plates is swinging with a constant frequency in a range from 0.4 to 4 Hz. The paper investigates the dependence in time and frequency of electrode velocity and streaming electrification. The measured current occurs for a very low intermittent velocity of less than 10 mm/s. In this range, the electrification current is around 50 pA. For higher velocities of up to 150 mm/s, the current is at the level of 1200 pA. The time–frequency characteristic using short-time Fourier transform shows no temporal changes in the frequency spectrum. The dependence of electrification on shuttle speed was calculated and it can be approximated with a second order polynomial model with the determination coefficient higher than 0.9. The advantage of the sensor is the ability to measure electrification phenomena without the necessity of having rotating electrodes or having a large volume of flowing liquids.
What Is the Effect of Outer Jacket Degradation on the Communication Parameters? A Case Study of the Twisted Pair Cable Applied in the Railway Industry
Authors: Grzechca Damian , Zieliński Dariusz , Filipowski Wojciech
Published: February 2021

Among the variety of problems encountered in transmission lines, the outer jacket degradation-derived faults of communication cables in railway applications have a significant impact on the transmission line parameters, especially if the cables are exposed to extremely varying environmental conditions, such as temperature deviation and humidity changes. In this paper, an advanced model of a twisted pair communication cable is proposed, together with approximated degradation functions for distributed parameters of the model, such as the shielding inductance, resistance, and capacitance per meter of cable length. This allows for gathering the distributed parameters for the proposed model under specific environmental conditions. The degradation functions for the parameters have been identified and compared with simulation results, including the communication speed and frequency band, and it has been confirmed that the transmission reliability depends on the cable condition. The authors discuss the influence of outer jacket degradation on signal behavior in terms of time and frequency domains that should be considered while developing new signaling devices for railway transportation.
CFD and Experimental Study of Wind Pressure Distribution on the High-Rise Building in the Shape of an Equilateral Acute Triangle
Authors: Jendzelovsky Norbert , Antal Roland
Published: February 2021

There is a lack of detailed information about wind flow and distribution of wind pressure around atypically shaped high-rise buildings. The national standard EN 1991-1-4 Eurocode 1 used to determine the effects of wind on the territory of Slovakia (and indeed other countries of the European Union) does not have a procedure for determining the effects of wind on objects of triangular shape. This presents a problem for designers and engineers, as there exist no generally binding/valid rules to follow when performing the wind effect analysis. This paper shows the procedure of identification and results of the external wind pressure coefficient for the triangularly shaped high-rise building. Two methods of calculation have been chosen for this purpose. First, experimental measurements were performed on a scaled model of the building cross-section in the wind tunnel. Subsequently, software simulations were performed on the same scaled model in the CFD (computational fluid dynamics) program ANSYS CFX. Results of wind pressure were obtained for two directions of wind flow measured in 16 sampling points distributed irregularly around the circumference of the model. Results were mutually compared and verified. At the end, the wind flow effects on a real-size triangular high-rise building in the built-up area performed by software simulation are shown.
Characterization and Control of Hidden Micro-Oxygenation in the Winery: Wine Racking
Authors: Nevares Ignacio , Fernández-Díaz Ainara , del Alamo-Sanza Maria
Published: February 2021

Transferring wine is a common operation in most of the wineries in the world that depends mainly on the equipment and materials used. These contributions are widely unknown, and their knowledge is of vital importance to controlling the winemaking process. This work presents the results of characterizing the oxygen supply due to the use of hoses of different materials (Butyl Rubber, IIR; Nitrile Butadiene Rubber, NBR; Ethylene Propylene Diene Monomer rubber, EPDM; Ultra-high-molecular-weight polyethylene, UHMW; Natural Rubber, NR), dimensions (DN32; DN50), connectors (DIN 11851, Tri-CLAMP) with gaskets of different materials (NBR; EPDM; Fluorocarbon, FKM/FPM; silicone rubber, Q/VMQ; Polytetrafluoroethylene, PTFE). In addition, the use of different inert gases (N2, CO2, Ar, N2 + CO2 and Ar + CO2) for air purging of hoses and tanks, as well as for ullage blanketing during tank-to-tank racking, and their economic impact were studied. The results indicated that the IIR hoses had the least amount of O2 added to the liquid and that the Tri-clamp connectors were generally more airtight, with the FKM seals standing out. The most recommended inert gas was CO2 when the type of wine allows it, N2 being the most recommended in any case. When all these recommendations were used together the addition of O2 during tank-to-tank racking was drastically reduced.
Accumulation Pattern of Amygdalin and Prunasin and Its Correlation with Fruit and Kernel Agronomic Characteristics during Apricot (Prunus armeniaca L.) Kernel Development
Authors: Deng Ping , Cui Bei , Zhu Hailan , Phommakoun Buangurn , Zhang Dan , Li Yiming , Zhao Fei , Zhao Zhong
Published: February 2021

To reveal the accumulation pattern of cyanogenic glycosides (amygdalin and prunasin) in bitter apricot kernels to further understand the metabolic mechanisms underlying differential accumulation during kernel development and ripening and explore the association between cyanogenic glycoside accumulation and the physical, chemical and biochemical indexes of fruits and kernels during fruit and kernel development, dynamic changes in physical characteristics (weight, moisture content, linear dimensions, derived parameters) and chemical and biochemical parameters (oil, amygdalin and prunasin contents, β-glucosidase activity) of fruits and kernels from ten apricot (Prunus armeniaca L.) cultivars were systematically studied at 10 day intervals, from 20 days after flowering (DAF) until maturity. High variability in most of physical, chemical and biochemical parameters was found among the evaluated apricot cultivars and at different ripening stages. Kernel oil accumulation showed similar sigmoid patterns. Amygdalin and prunasin levels were undetectable in the sweet kernel cultivars throughout kernel development. During the early stages of apricot fruit development (before 50 DAF), the prunasin level in bitter kernels first increased, then decreased markedly; while the amygdalin level was present in quite small amounts and significantly lower than the prunasin level. From 50 to 70 DAF, prunasin further declined to zero; while amygdalin increased linearly and was significantly higher than the prunasin level, then decreased or increased slowly until full maturity. The cyanogenic glycoside accumulation pattern indicated a shift from a prunasin-dominated to an amygdalin-dominated state during bitter apricot kernel development and ripening. β-glucosidase catabolic enzyme activity was high during kernel development and ripening in all tested apricot cultivars, indicating that β-glucosidase was not important for amygdalin accumulation. Correlation analysis showed a positive correlation of kernel amygdalin content with fruit dimension parameters, kernel oil content and β-glucosidase activity, but no or a weak positive correlation with kernel dimension parameters. Principal component analysis (PCA) showed that the variance accumulation contribution rate of the first three principal components totaled 84.56%, and not only revealed differences in amygdalin and prunasin contents and β-glucosidase activity among cultivars, but also distinguished different developmental stages. The results can help us understand the metabolic mechanisms underlying differential cyanogenic glycoside accumulation in apricot kernels and provide a useful reference for breeding high- or low-amygdalin-content apricot cultivars and the agronomic management, intensive processing and exploitation of bitter apricot kernels.