bluuebunny/crossref_metadata_2025 huggingface dataset:
Newly-Discovered Neural Features Expand the Pathobiological Knowledge of Blastic Plasmacytoid Dendritic Cell Neoplasm
Authors: Sapienza Maria Rosaria , Benvenuto Giuseppe , Ferracin Manuela , Mazzara Saveria , Fuligni Fabio , Tripodo Claudio , Belmonte Beatrice , Fanoni Daniele , Melle Federica , Motta Giovanna , Tabanelli Valentina , Consiglio Jessica , Mazzara Vincenzo , Del Corvo Marcello , Fiori Stefano , Pileri Alessandro , Dellino Gaetano Ivan , Cerroni Lorenzo , Facchetti Fabio , Berti Emilio , Sabattini Elena , Paulli Marco , Croce Carlo Maria , Pileri Stefano A.
Published: September 2021

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare and highly aggressive hematologic malignancy originating from plasmacytoid dendritic cells (pDCs). The microRNA expression profile of BPDCN was compared to that of normal pDCs and the impact of miRNA dysregulation on the BPDCN transcriptional program was assessed. MiRNA and gene expression profiling data were integrated to obtain the BPDCN miRNA-regulatory network. The biological process mainly dysregulated by this network was predicted to be neurogenesis, a phenomenon raising growing interest in solid tumors. Neurogenesis was explored in BPDCN by querying different molecular sources (RNA sequencing, Chromatin immunoprecipitation-sequencing, and immunohistochemistry). It was shown that BPDCN cells upregulated neural mitogen genes possibly critical for tumor dissemination, expressed neuronal progenitor markers involved in cell migration, exchanged acetylcholine neurotransmitter, and overexpressed multiple neural receptors that may stimulate tumor proliferation, migration and cross-talk with the nervous system. Most neural genes upregulated in BPDCN are currently investigated as therapeutic targets.
Circulating Tumour Cell Numbers Correlate with Platelet Count and Circulating Lymphocyte Subsets in Men with Advanced Prostate Cancer: Data from the ExPeCT Clinical Trial (CTRIAL-IE 15-21)
Authors: Hayes Brian , Brady Lauren , Sheill Gráinne , Baird Anne-Marie , Guinan Emer , Stanfill Bryan , Dunne Jean , Holden Dean , Vlajnic Tatjana , Casey Orla , Murphy Verena , Greene John , Allott Emma H. , Hussey Juliette , Cahill Fidelma , Van Hemelrijck Mieke , Peat Nicola , Mucci Lorelei A. , Cunningham Moya , Grogan Liam , Lynch Thomas , Manecksha Rustom P. , McCaffrey John , O’Donnell Dearbhaile M. , Sheils Orla , O’Leary John J. , Rudman Sarah , McDermott Ray , Finn Stephen
Published: September 2021

Interactions between circulating tumour cells (CTCs) and platelets are thought to inhibit natural killer(NK)-cell-induced lysis. We attempted to correlate CTC numbers in men with advanced prostate cancer with platelet counts and circulating lymphocyte numbers. Sixty-one ExPeCT trial participants, divided into overweight/obese and normal weight groups on the basis of a BMI ≥ 25 or <25, were randomized to participate or not in a six-month exercise programme. Blood samples at randomization, and at three and six months, were subjected to ScreenCell filtration, circulating platelet counts were obtained, and flow cytometry was performed on a subset of samples (n = 29). CTC count positively correlated with absolute total lymphocyte count (r2 = 0.1709, p = 0.0258) and NK-cell count (r2 = 0.49, p < 0.0001). There was also a positive correlation between platelet count and CTC count (r2 = 0.094, p = 0.0001). Correlation was also demonstrated within the overweight/obese group (n = 123, p < 0.0001), the non-exercise group (n = 79, p = 0.001) and blood draw samples lacking platelet cloaking (n = 128, p < 0.0001). By flow cytometry, blood samples from the exercise group (n = 15) had a higher proportion of CD3+ T-lymphocytes (p = 0.0003) and lower proportions of B-lymphocytes (p = 0.0264) and NK-cells (p = 0.015) than the non-exercise group (n = 14). These findings suggest that CTCs engage in complex interactions with the coagulation cascade and innate immune system during intravascular transit, and they present an attractive target for directed therapy at a vulnerable stage in metastasis.
Enhanced Catalytic Soot Oxidation by Ce-Based MOF-Derived Ceria Nano-Bar with Promoted Oxygen Vacancy
Authors: Tsai Yu-Chih , Lee Jechan , Kwon Eilhann , Huang Chao-Wei , Huy Nguyen Nhat , You Siming , Hsu Pei-Syuan , Oh Wen Da , Lin Kun-Yi Andrew
Published: September 2021

As CeO2 is a useful catalyst for soot elimination, it is important to develop CeO2 with higher contact areas, and reactivities for efficient soot oxidation and catalytic soot oxidation are basically controlled by structures and surface properties of catalysts. Herein, a Ce-Metal organic framework (MOFs) consisting of Ce and benzene-1,3,5-tricarboxylic acid (H3BTC) is employed as the precursor as CeBTC exhibits a unique bar-like high-aspect-ratio morphology, which is then transformed into CeO2 with a nanoscale bar-like configuration. More importantly, this CeO2 nanobar (CeONB) possesses porou, and even hollow structures, as well as more oxygen vacancies, enabling CeONB to become a promising catalyst for soot oxidation. Thus, CeONB shows a much higher catalytic activity than commercial CeO2 nanoparticle (comCeO) for soot oxidation with a significantly lower ignition temperature (Tig). Moreover, while soot oxidation by comCeO leads to production of CO together with CO2, CeONB can completely convert soot to CO2. The tight contact mode also enables CeONB to exhibit a very low Tig of 310 °C, whereas the existence of NO also enhances the soot oxidation by CeONB to reduce the Tig. The mechanism of NO-assisted soot oxidation is also examined, and validated by DRIFTS to identify the formation and transformation of nitrogen-containing intermediates. CeONB is also recyclable over many consecutive cycles and maintained its high catalytic activity for soot oxidation. These results demonstrate that CeONB is a promising and easily prepared high-aspect-ratio Ce-based catalyst for soot oxidation.
Molecular Dynamics and Machine Learning in Catalysts
Authors: Liu Wenxiang , Zhu Yang , Wu Yongqiang , Chen Cen , Hong Yang , Yue Yanan , Zhang Jingchao , Hou Bo
Published: September 2021

Given the importance of catalysts in the chemical industry, they have been extensively investigated by experimental and numerical methods. With the development of computational algorithms and computer hardware, large-scale simulations have enabled influential studies with more atomic details reflecting microscopic mechanisms. This review provides a comprehensive summary of recent developments in molecular dynamics, including ab initio molecular dynamics and reaction force-field molecular dynamics. Recent research on both approaches to catalyst calculations is reviewed, including growth, dehydrogenation, hydrogenation, oxidation reactions, bias, and recombination of carbon materials that can guide catalyst calculations. Machine learning has attracted increasing interest in recent years, and its combination with the field of catalysts has inspired promising development approaches. Its applications in machine learning potential, catalyst design, performance prediction, structure optimization, and classification have been summarized in detail. This review hopes to shed light and perspective on ML approaches in catalysts.
Autophagy Promotes the Survival of Adipose Mesenchymal Stem/Stromal Cells and Enhances Their Therapeutic Effects in Cisplatin-Induced Liver Injury via Modulating TGF-β1/Smad and PI3K/AKT Signaling Pathways
Authors: El Nashar Eman Mohamad , Alghamdi Mansour Abdullah , Alasmari Wardah Abdullah , Hussein Mohamed M. A. , Hamza Eman , Taha Reham Ismail , Ahmed Mona M. , Al-Khater Khulood Mohammed , Abdelfattah-Hassan Ahmed
Published: September 2021

Autophagy is a key metabolic process where cells can recycle its proteins and organelles to regenerate its own cellular building blocks. Chemotherapy is indispensable for cancer treatment but associated with various side-effects, including organ damage. Stem cell-based therapy is a promising approach for reducing chemotherapeutic side effects, however, one of its main culprits is the poor survival of transplanted stem cells in damaged tissues. Here, we aimed to test the effects of activating autophagy in adipose-derived mesenchymal stem/stromal cells (ADSCs) on the survival of ADSCs, and their therapeutic value in cisplatin-induced liver injury model. Autophagy was activated in ADSCs by rapamycin (50 nM/L) for two hours before transplantation and were compared to non-preconditioned ADSCs. Rapamycin preconditioning resulted in activated autophagy and improved survival of ADSCs achieved by increased autophagosomes, upregulated autophagy-specific LC3-II gene, decreased protein degradation/ubiquitination by downregulated p62 gene, downregulated mTOR gene, and finally, upregulated antiapoptotic BCL-2 gene. In addition, autophagic ADSCs transplantation in the cisplatin liver injury model, liver biochemical parameters (AST, ALT and albumin), lipid peroxidation (MDA), antioxidant profile (SOD and GPX) and histopathological picture were improved, approaching near-normal conditions. These promising autophagic ADSCs effects were achieved by modulation of components in TGF-β1/Smad and PI3K-AKT signaling pathways, besides reducing NF-κB gene expression (marker for inflammation), reducing TGF-β1 levels (marker for fibrosis) and increasing SDF-1 levels (liver regeneration marker) in liver. Therefore, current results highlight the importance of autophagy in augmenting the therapeutic potential of stem cell therapy in alleviating cisplatin-associated liver damage and opens the path for improved cell-based therapies, in general, and with chemotherapeutics, in particular.
A Preliminary Study for Tunable Optical Assessment of Exhaled Breath Ammonia Based on Ultrathin Tetrakis(4-sulfophenyl)porphine Nanoassembled Films
Authors: Korposh Sergiy , Lee Seung-Woo
Published: September 2021

The detection of chemical substances excreted from the human body offers an attractive approach for non-invasive, early diagnostics of certain diseases. In this preliminary study, we proposed a susceptible optical sensor capable of quantitatively detecting ammonia from exhaled breath. The proposed sensor consists of nanoassembled ultrathin films composed of tetrakis(4-sulfophenyl)porphine (TSPP) and poly(diallyldimethylammonium chloride) (PDDA) deposited on quartz substrates using a layer-by-layer method. Measurement principles are based on the ammonia-induced absorbance changes at 489 (Soret band) and 702 nm (Q band), associated with the deprotonation of the J-aggregated TSPPs inside the film. Before exposure to breath, the PDDA/TSPP thin film was calibrated using known concentrations of ammonia gases with a projected detection limit of 102 ± 12 parts per billion (ppb). Calibrated sensor films were then exposed to human breath and urine samples to determine the ammonia concentration. Concentrations of exhaled ammonia are influenced significantly by the consumption of food or the amount of urea. Sensor response and maximum sensitivity, obtained from the absorbance changes induced by ammonia, were achieved by initial sensor exposure to HCl vapor. Previously reported procedures for the Helicobacter pylori (HELIC Ammonia Breath) test based on urea reaction with urease were reproduced using the proposed sensor. The observed behavior corresponded very well with the kinetics of the interactions between urea and urease, i.e., ammonia reached a maximum concentration approximately 5 min after the start of the reaction. A large-scale study involving 41 healthy volunteers in their 20s to 60s was successfully conducted to test the capabilities of the sensor to determine the concentration of exhaled ammonia. The concentration of ammonia for the healthy volunteers ranged between 0.3 and 1.5 ppm, with a mean value of ca. 520 ppb in the morning (before eating) and ca. 420 ppb in the afternoon (immediately after eating). These real-test mean values are meaningful when considered against the projected LOD.
Label Free, Lateral Flow Prostaglandin E2 Electrochemical Immunosensor for Urinary Tract Infection Diagnosis
Authors: Ganguly Antra , Ebrahimzadeh Tahmineh , Zimmern Philippe E. , De Nisco Nicole J. , Prasad Shalini
Published: September 2021

A label-free, rapid, and easy-to-use lateral flow electrochemical biosensor was developed for urinary tract infection (UTI) diagnosis in resource challenged areas. The sensor operates in non-faradaic mode and utilizes Electrochemical Impedance Spectroscopy for quantification of Prostaglandin E2, a diagnostic and prognostic urinary biomarker for UTI and recurrent UTI. To achieve high sensitivity in low microliter volumes of neat, unprocessed urine, nanoconfinement of assay biomolecules was achieved by developing a three-electrode planar gold microelectrode system on top of a lateral flow nanoporous membrane. The sensor is capable of giving readouts within 5 min and has a wide dynamic range of 100–4000 pg/mL for urinary PGE2. The sensor is capable of discriminating between low and high levels of PGE2 and hence is capable of threshold classification of urine samples as UTI positive and UTI negative. The sensor through its immunological response (directly related to host immune response) is superior to the commercially available point-of-care UTI dipsticks which are qualitative, have poor specificity for UTI, and have high false-positive rates. The developed sensor shows promise for rapid, easy and cost-effective UTI diagnosis for both clinical and home-based settings. More accurate point-of-care UTI diagnosis will improve patient outcomes and allow for timely and appropriate prescription of antibiotics which can subsequently increase treatment success rates and reduce costs.
The Link between Pediatric Obstructive Sleep Apnea (OSA) and Attention Deficit Hyperactivity Disorder (ADHD)
Authors: Urbano Gino Luis , Tablizo Bea Janine , Moufarrej Youmna , Tablizo Mary Anne , Chen Maida Lynn , Witmans Manisha
Published: September 2021

Obstructive sleep apnea (OSA) is a form of sleep-disordered breathing that affects up to 9.5% of the pediatric population. Untreated OSA is associated with several complications, including neurobehavioral sequelae, growth and developmental delay, cardiovascular dysfunction, and insulin resistance. Attention-deficit/hyperactivity disorder (ADHD) is among the neurobehavioral sequelae associated with OSA. This review aims to summarize the research on the relationship between OSA and ADHD and investigate the impacts of OSA treatment on ADHD symptoms. A literature search was conducted on electronic databases with the key terms: “attention deficit hyperactivity disorder” or “ADHD”, “obstructive sleep apnea” or “OSA”, “sleep disordered breathing”, and “pediatric” or “children”. Review of relevant studies showed adenotonsillectomy to be effective in the short-term treatment of ADHD symptoms. The success of other treatment options, including continuous positive airway pressure (CPAP), in treating ADHD symptoms in pediatric OSA patients has not been adequately evaluated. Further studies are needed to evaluate the long-term benefits of surgical intervention, patient factors that may influence treatment success, and the potential benefits of other OSA treatment methods for pediatric ADHD patients.
Effect of Graphene on Ice Polymorph
Authors: Zheng Chuanbao , Lu Hao , Xu Quanming , Liu Tianyi , Patil Aniruddha , Wu Jianyang , de Vries Renko , Zuilhof Han , Zhang Zhisen
Published: September 2021

Recently, ice with stacking disorder structure, consisting of random sequences of cubic ice (Ic) and hexagonal ice (Ih) layers, was reported to be more stable than pure Ih/Ic. Due to a much lower free energy barrier of heterogeneous nucleation, in practice, the freezing process of water is controlled by heterogeneous nucleation triggered by an external medium. Therefore, we carry out molecular dynamic simulations to explore how ice polymorphism depends on the lattice structure of the crystalline substrates on which the ice is grown, focusing on the primary source of atmospheric aerosols, carbon materials. It turns out that, during the nucleation stage, the polymorph of ice nuclei is strongly affected by graphene substrates. For ice nucleation on graphene, we find Ih is the dominant polymorph. This can be attributed to structural similarities between graphene and basal face of Ih. Our results also suggest that the substrate only affects the polymorph of ice close to the graphene surface, with the preference for Ih diminishing as the ice layer grows.
Patterns of Myometrial Invasion in Endometrial Adenocarcinoma with Emphasizing on Microcystic, Elongated and Fragmented (MELF) Glands Pattern: A Narrative Review of the Literature
Authors: Mateva Svetlana , Nikolova Margarita , Yordanov Angel
Published: September 2021

Endometrioid endometrial adenocarcinoma (EEC) is the most common malignancy of the female genital tract. According to the 2009 FIGO staging system, the depth of myometrial invasion (MI), and tumor spread to adjacent organs or tissues are the staging criteria for endometrial carcinoma (EC). Therefore, assessment of the depth of MI is of great importance. There is a spectrum of morphological patterns of MI. Still, their number and features vary according to the scientific literature, with a certain overlap that creates difficulties and controversies in the precise assessment of MI depth. The purpose of this review is to present and discuss the most important and recent information about patterns of MI, focusing on the more aggressive and the elongated and fragmented glands (MELF) pattern in particular. Assessment of MI depth and correct staging of EC is possible only after the precise recognition of each MI pattern.
CSGBBNet: An Explainable Deep Learning Framework for COVID-19 Detection
Authors: Yao Xu-Jing , Zhu Zi-Quan , Wang Shui-Hua , Zhang Yu-Dong
Published: September 2021

The COVID-19 virus has swept the world and brought great impact to various fields, gaining wide attention from all walks of life since the end of 2019. At present, although the global epidemic situation is leveling off and vaccine doses have been administered in a large amount, confirmed cases are still emerging around the world. To make up for the missed diagnosis caused by the uncertainty of nucleic acid polymerase chain reaction (PCR) test, utilizing lung CT examination as a combined detection method to improve the diagnostic rate becomes a necessity. Our research considered the time-consuming and labor-intensive characteristics of the traditional CT analyzing process, and developed an efficient deep learning framework named CSGBBNet to solve the binary classification task of COVID-19 images based on a COVID-Seg model for image preprocessing and a GBBNet for classification. The five runs with random seed on the test set showed our novel framework can rapidly analyze CT scan images and give out effective results for assisting COVID-19 detection, with the mean accuracy of 98.49 ± 1.23%, the sensitivity of 99.00 ± 2.00%, the specificity of 97.95 ± 2.51%, the precision of 98.10 ± 2.61%, and the F1 score of 98.51 ± 1.22%. Moreover, our model CSGBBNet performs better when compared with seven previous state-of-the-art methods. In this research, the aim is to link together biomedical research and artificial intelligence and provide some insights into the field of COVID-19 detection.
Study of Concentrated Short Fiber Suspensions in Flows, Using Topological Data Analysis
Authors: Mezher Rabih , Arayro Jack , Hascoet Nicolas , Chinesta Francisco
Published: September 2021

The present study addresses the discrete simulation of the flow of concentrated suspensions encountered in the forming processes involving reinforced polymers, and more particularly the statistical characterization and description of the effects of the intense fiber interaction, occurring during the development of the flow induced orientation, on the fibers’ geometrical center trajectory. The number of interactions as well as the interaction intensity will depend on the fiber volume fraction and the applied shear, which should affect the stochastic trajectory. Topological data analysis (TDA) will be applied on the geometrical center trajectories of the simulated fiber to prove that a characteristic pattern can be extracted depending on the flow conditions (concentration and shear rate). This work proves that TDA allows capturing and extracting from the so-called persistence image, a pattern that characterizes the dependence of the fiber trajectory on the flow kinematics and the suspension concentration. Such a pattern could be used for classification and modeling purposes, in rheology or during processing monitoring.
Model for Risk Calculation and Reliability Comparison of Level Crossings
Authors: Ercegovac Pamela , Stojić Gordan , Kopić Miloš , Stević Željko , Sinani Feta , Tanackov Ilija
Published: September 2021

There is not a single country in the world that is so rich that it can remove all level crossings or provide their denivelation in order to absolutely avoid the possibility of accidents at the intersections of railways and road traffic. In the Republic of Serbia alone, the largest number of accidents occur at passive crossings, which make up three-quarters of the total number of crossings. Therefore, it is necessary to constantly find solutions to the problem of priorities when choosing level crossings where it is necessary to raise the level of security, primarily by analyzing the risk and reliability at all level crossings. This paper presents a model that enables this. The calculation of the maximal risk of a level crossing is achieved under the conditions of generating the maximum entropy in the virtual operating mode. The basis of the model is a heterogeneous queuing system. Maximum entropy is based on the mandatory application of an exponential distribution. The system is Markovian and is solved by a standard analytical concept. The basic input parameters for the calculation of the maximal risk are the geometric characteristics of the level crossing and the intensities and structure of the flows of road and railway vehicles. The real risk is based on statistical records of accidents and flow intensities. The exact reliability of the level crossing is calculated from the ratio of real and maximal risk, which enables their further comparison in order to raise the level of safety, and that is the basic idea of this paper.
OATCR: Outdoor Autonomous Trash-Collecting Robot Design Using YOLOv4-Tiny
Authors: Kulshreshtha Medhasvi , Chandra Sushma S. , Randhawa Princy , Tsaramirsis Georgios , Khadidos Adil , Khadidos Alaa O.
Published: September 2021

This paper proposed an innovative mechanical design using the Rocker-bogie mechanism for resilient Trash-Collecting Robots. Mask-RCNN, YOLOV4, and YOLOv4-tiny were experimented on and analyzed for trash detection. The Trash-Collecting Robot was developed to be completely autonomous as it was able to detect trash, move towards it, and pick it up while avoiding any obstacles along the way. Sensors including a camera, ultrasonic sensor, and GPS module played an imperative role in automation. The brain of the Robot, namely, Raspberry Pi and Arduino, processed the data from the sensors and performed path-planning and consequent motion of the robot through actuation of motors. Three models for object detection were tested for potential use in the robot: Mask-RCNN, YOLOv4, and YOLOv4-tiny. Mask-RCNN achieved an average precision (mAP) of over 83% and detection time (DT) of 3973.29 ms, YOLOv4 achieved 97.1% (mAP) and 32.76 DT, and YOLOv4-tiny achieved 95.2% and 5.21 ms DT. The YOLOv4-tiny was selected as it offered a very similar mAP to YOLOv4, but with a much lower DT. The design was simulated on different terrains and behaved as expected.
Minimization of Torque Ripple in the Brushless DC Motor Using Constrained Cuckoo Search Algorithm
Authors: Knypiński Łukasz , Kuroczycki Sebastian , Márquez Fausto Pedro García
Published: September 2021

This paper presents the application of the cuckoo search (CS) algorithm in attempts to the minimization of the commutation torque ripple in the brushless DC motor (BLDC). The optimization algorithm was created based on the cuckoo’s reproductive behavior. The lumped-parameters mathematical model of the BLDC motor was developed. The values of self-inductances, mutual inductances, and back-electromotive force waveforms applied in the mathematical model were calculated by the use of the finite element method. The optimization algorithm was developed in Python 3.8. The CS algorithm was coupled with the static penalty function. During the optimization process, the shape of the voltage supplying the stator windings was determined to minimize the commutation torque ripple. Selected results of computer simulation are presented and discussed.
Space Imaging Sensor Power Supply Filtering: Improving EMC Margin Assessment with Clustering and Sensitivity Analyses
Authors: Patier Laurent , Lalléchère Sébastien
Published: September 2021

This work is dedicated to the assessment of the filtering performances of an optoelectronic sensor for space applications. Particular care is taken concerning the power supply subsystem (here voltage shifter integrated circuit), which is part of the electromagnetic compatibility (EMC) compliance of an imaging equipment embedded on spacecrafts. The proposed methodology aims at two major targets: First, evaluating the Filter Effectiveness (FE) subject concerning varying parameters (including filter topology, parasitic effects and source/load impedance variations); second, quantifying the relative importance of representative equivalent electrical components through sensitivity analyses (nominal and parasitic values). The latter point is of utmost importance considering the expected versatility of such systems, such as manufacturing tolerances, for instance. Nominal values and/or components are often badly defined for confidentiality reasons, lack of knowledge or pure ignorance of inputs. An analytical deterministic formulation (here through the transfer matrix approach) is proposed and completed with an original stochastic strategy (Reduced Order Clustering, ROC). This ensures the reliable assessment of both statistical filter performances and most influential parameters, jointly with computational resources saving relatively to brute force Monte Carlo simulations.
Towards Realization of a Low-Voltage Class-AB VCII with High Current Drive Capability
Authors: Safari Leila , Barile Gianluca , Stornelli Vincenzo , Minaei Shahram , Ferri Giuseppe
Published: September 2021

In this paper, the implementation of a low-voltage class AB second generation voltage conveyor (VCII) with high current drive capability is presented. Simple realization and good overall performance are the main features of the proposed circuit. Proper solutions and techniques were used to achieve high signal swing and high linearity at Y, X and Z ports of VCII as well as low-voltage operation. The operation of the proposed VCII was verified through SPICE simulations based on TSMC 0.18 µm CMOS technology parameters and a supply voltage of ±0.9 V. The small signal impedance values were 973 Ω, 120 kΩ and 217 Ω at Y, X and Z ports, respectively. The maximum current at the X port was ±10 mA with maximum total harmonic distortion (THD) of 2.4% at a frequency of 1 MHz. Considering a bias current (IB) of 29 µA and output current at the X port (IX) of 10 mA, the current drive capability (IX/IB) of about 345 was achieved at the X port. The voltage swing at the Z port was (−0.4, 0.4) V. The THD value at the Z port for an input signal with 0.8 V peak-to-peak value and frequency of 1 MHz was 3.9%. The total power consumption was 0.393 µW.
Parameter Estimation of Modified Double-Diode and Triple-Diode Photovoltaic Models Based on Wild Horse Optimizer
Authors: Ramadan Abdelhady , Kamel Salah , Taha Ibrahim B. M. , Tostado-Véliz Marcos
Published: September 2021

The increase in industrial and commercial applications of photovoltaic systems (PV) has a significant impact on the increase in interest in studying the improvement of the efficiency of these systems. Estimating the efficiency of PV is considered one of the most important problems facing those in charge of manufacturing these systems, which makes it interesting to many researchers. The difficulty in estimating the efficiency of PV is due to the high non-linear current–voltage characteristics and power–voltage characteristics. In addition, the absence of ample efficiency information in the manufacturers’ datasheets has led to the development of an effective electrical mathematical equivalent model necessary to simulate the PV module. In this paper, an application for an optimization algorithm named Wild Horse Optimizer (WHO) is proposed to extract the parameters of a double-diode PV model (DDM), modified double-diode PV model (MDDM), triple-diode PV model (TDM), and modified triple-diode PV model (MTDM). This study focuses on two main objectives. The first concerns comparing the original models (DDM and TDM) and their modification (MDDM and MTDM). The second concerns the algorithm behavior with the optimization problem and comparing this behavior with other recent algorithms. The evaluation process uses different methods, such as Root Mean Square Error (RMSE) for accuracy and statistical analysis for robustness. Based on the results obtained by the WHO, the estimated parameters using the WHO are more accurate than those obtained by the other studied optimization algorithms; furthermore, the MDDM and MTDM modifications enhanced the original DDM and TDM efficiencies.
Improved Air-Conditioning Demand Response of Connected Communities over Individually Optimized Buildings
Authors: Campbell Nicolas A. , Phelan Patrick E. , Peinado-Guerrero Miguel , Villalobos Jesus R.
Published: September 2021

Connected communities potentially offer much greater demand response capabilities over singular building energy management systems (BEMS) through an increase of connectivity. The potential increase in benefits from this next step in connectivity is still under investigation, especially when applied to existing buildings. This work utilizes EnergyPlus simulation results on eight different commercial prototype buildings to estimate the potential savings on peak demand and energy costs using a mixed-integer linear programming model. This model is used in two cases: a fully connected community and eight separate buildings with BEMS. The connected community is optimized using all zones as variables, while the individual buildings are optimized separately and then aggregated. These optimization problems are run for a range of individual zone flexibility values. The results indicate that a connected community offered 60.0% and 24.8% more peak demand savings for low and high flexibility scenarios, relative to individually optimized buildings. Energy cost optimization results show only marginally better savings of 2.9% and 6.1% for low and high flexibility, respectively.
Development and Validation of a Special Protection System for Internal Fault in a High-Power Three-Level NPC VSC
Authors: Dan Mattia , Zanotto Loris , Gaio Elena , Panizza Carlo , Finotti Claudio , Perna Mauro
Published: September 2021

This paper describes the development and validation of an innovative protection system based on medium-voltage fuses for a high-power switching conversion system. This special conversion system, rated to deliver about 56 MW to the load, is based on neutral-point clamped IGCT inverters, connected to the same dc link through a set of distributed busbars, with a dc-link voltage of 6.5 kV and a capacitive stored energy up to 837 kJ. The sudden release of this energy in case of a switch failure in one inverter and the subsequent short circuit of one leg can lead to destructive consequences. From the analysis of different protection strategies, performed by numerical simulations of the fault evolutions, the developed solution based on medium-voltage fuses was found the only provision able to cope with such high stored energy and uncommon circuit topology. Custom fuses were developed for this application, and a specially tailored test was designed for validating the fuse selection. The paper, after summarizing the work carried out to simulate the fault evolution and select the protection, presents the analyses carried out to set up the validation test, and describes and discusses the results of the test and the complementing numerical simulations, which demonstrated the effectiveness of the protection system.
COVID-19 Lessons for Climate Change and Sustainable Health
Authors: Srivastava Siddharth , Khokhar Fahad , Madhav Archana , Pembroke Billy , Shetty Vignesh , Mutreja Ankur
Published: September 2021

The drivers underpinning the emergence of SARS-CoV-2 and climate change attest to the fact that we are now living in the Anthropocene Epoch, with human activities significantly impacting and altering the global ecosystem. Here, we explore the historical context of zoonoses, the effect of anthropogenic climate change and interrelated drivers on the emergence of, and response to emerging infectious diseases. We call attention to an urgent need for inculcating a One Health research agenda that acknowledges the primary interconnection between animals, humans, pathogens, and their collective milieus to foster long term resilience across all systems within our shared planetary environment.
On the Road to a Green Economy: How Do European Union Countries ‘Do Their Homework’?
Authors: Kasztelan Armand
Published: September 2021

Multidimensional crisis phenomena (financial–economic, environmental and social), plaguing the international community, especially in the last 30 years, have intensified resentment towards traditional models of growth and socio-economic development. The European Commission has placed the idea of a green economy (GE) at the heart of the Europe 2020 strategy. This paper presents an assessment of the implementation of the green economy assumptions in EU countries in 2018, taking 2010 as the base year. Using taxonomic methods, a synthetic evaluation index (GEI—Green Economy Index) was constructed based on a multi-criterion set of 27 indicators. This paper attempts to answer the following questions: How green are the European economies? What are the main challenges in this context? The average value of the index for the EU countries decreased in the studied years from 0.3423 to 0.3294, which can be interpreted as a slowdown in the greening processes. The key recommendations for the upcoming years include the improvement of energy efficiency indicators, the further increase in the share of renewable energy sources in the energy balance. Moreover, a significant problem continues to be the high percentage of the population at risk of poverty or social exclusion, as well as low CO2 and resource productivity rates.
On the Suitability of Intrusion Detection System for Wireless Edge Networks
Authors: Shakhov Vladimir , Sokolova Olga , Koo Insoo
Published: September 2021

Multi-access edge computing has become a strategic concept of the Internet of Things. The edge computing market has reached USD several billion and is growing intensively. In the edge-computing paradigm, most of the data is processed close to, or at the edge of, the network. This greatly reduces the computation and communication load of the network core. Moreover, edge computing provides better support for user privacy. On the other hand, an increase in data processing locations will proportionately increase the attack surface. An edge node can be put out of service easily by being flooded with spoofed packets owing to limited capacities and resources. Furthermore, wireless edge nodes are quite vulnerable to energy exhaustion attacks. In this situation, traditional network security mechanisms cannot be used effectively. Therefore, a tradeoff between security and efficiency is needed. This study considered the requirements under which the use of an intrusion detection system (IDS) is justified. To the best of our knowledge, this is a first attempt to combine IDS quality, system performance degradation due to IDS operations, and workload specificity into a unified quantitative criterion. This paper is an extended version of a report published in the proceedings of the ICCSA 2020 and differs from it in many ways. In particular, this paper considers novel mathematical problems regarding the deployment strategies for an IDS and the corresponding inverse problems and provides closed-form solutions for a few previously unsolved problems.
Physicochemical and Electrochemical Characterization of Vanadium Electrolyte Prepared with Different Grades of V2O5 Raw Materials
Authors: Ding Muqing , Liu Tao , Zhang Yimin , Liu Hong , Pan Dong , Chen Liming
Published: September 2021

The physicochemical and electrochemical performance of electrolytes prepared with different grades of V2O5 raw materials were investigated systematically for a vanadium redox flow battery. Physicochemical tests showed that the conductivity of electrolytes prepared with lower grades of V2O5 raw materials obviously decreased, while the viscosity increased. The results of electrochemical experiments showed that the electrochemical activity and reversibility of electrolytes decreased, and the solution resistance increased obviously, as the grade of V2O5 raw materials gradually decreased. In addition, the battery efficiency and charge–discharge capacity were negatively affected by impurities in the lower grade V2O5 raw materials, due to an increase of polarization on the charge–discharge voltage. Moreover, the performance of electrolytes was related to the total concentration of impurities in the electrolyte, and Na, K impurity ions were the main factors that adversely affected the electrochemical activity and reversibility, mass transfer, and capacity of the electrolytes. Based on the economic analysis, the impurities in V2O5 raw materials would not only reduce the performance of electrolytes, but also affect the production costs of electrolytes and the economic profits. Through this fundamental research, people can better understand the influence of V2O5 raw materials on electrolyte properties, and direct more attention to research how to effectively use lower grade V2O5 raw materials to reduce the costs of electrolyte preparation.
Influence of Fuel Type and Water Content Variation on Pollutant Emission Characteristics of a Biomass Circulating Fluidized Bed Boiler
Authors: He Jianjie , Liu Shanjian , Yao Di , Kong Ranran , Liu Yaya
Published: September 2021

In general, the biomass raw materials burned by biomass power plants generally have the characteristics of variable fuel types, high moisture content, and high volatile content. In this paper, a 130 t/h biomass circulating fluidized bed (BCFB) model was established on the MWorks platform with Modelica language. The influence of biomass type changes on operation parameters, the corresponding steady-state characteristics, and the dynamic characteristics of the BCFB were carried out. The temperature corresponding to the combustion of pine was overall higher than that of the other fuels, and the flue gas from the combustion of pine had the highest concentration of SO2, up to 520.49 mg/Nm3. The flue gas from the combustion of pure cotton sticks had the highest concentration of NO, up to 254.34 mg/Nm3. The changes of fuel type and moisture content all have a great influence on the operation of BCFBs. The emission of pollutants was not only related to the element content of fuel, but also closely related to the furnace temperature. The fuel moisture content also indirectly affects the pollutant emission concentration and the steam-water system.
The Hydration and Volume Expansion Mechanisms of Modified Expansive Cements for Sustainable In-Situ Rock Fragmentation: A Review
Authors: Liyanage Janethri Buddhipraba , Gamage Ranjith Pathegama
Published: September 2021

This review provides the hydration and volume expansion mechanism of expansive materials, with the goal of utilizing them in the development of sustainable mining methods. The main focus of the review will be the newly developed non-destructible rock fragmentation method, slow releasing energy material agent (SREMA), which is a modified soundless chemical demolition agent (SCDA). The review aims to address one of the main gaps in studies related to SREMA, by presenting a thorough understanding of the components of SREMA and their mechanisms of action, leading to volume expansion. Thus, this review would act as a guide for researchers working on using expansive materials for rock breaking. As many literatures have not been published regarding the recently discovered SREMA, studies on cements, expansive cements, and soundless chemical demolition agents (SCDA) were mainly considered. The chemical reactions and volume expansive processes of these materials have been studied and incorporated with the additives included in SREMA, to understand its behavior. Literature containing experimental studies analyzing the heat of hydration and microstructural changes have been mostly considered along with some of the heavily discussed hypotheses regarding the hydration of certain components, to predict the volume expansive mechanism of SREMA. Studies related to SREMA and other similar materials have shown drastic changes in the heats of hydration as the composition varies. Thus, SREMA has the capability of giving a wider range of expansive energies in diverse environmental conditions
Infestation of Early- and Late-Flushing Trees by Spring Caterpillars: An Associational Effect of Neighbouring Trees
Authors: Sarvašová Lenka , Zach Peter , Parák Michal , Saniga Miroslav , Kulfan Ján
Published: September 2021

In temperate forests within Europe, early-flushing (EF) deciduous trees are often heavily infested by early spring leaf-eating Lepidoptera, while late-flushing (LF) trees are better protected in a phenological manner against such heavy infestations, as spring moth larvae begin to appear before their bud burst. The associational effects of EF trees on LF ones are only poorly known. We studied whether or not the infestation of LF trees by spring Lepidoptera can be affected by EF ones if they grow in the immediate vicinity. We compared spring assemblages of leaf-eating larvae of Lepidoptera on LF Quercus cerris L. with those on EF Q. pubescens Willd. in several microhabitats in Slovakia, Central Europe. Larvae were collected from mature and young trees. Mature trees sampled were growing: (1) in a closed-canopy forest; (2) in small groups; or (3) as a lone tree. Forest and tree groups are both constituted by oak species. Tree groups and lone trees were 20–50 m distant from forest edges. Young trees were growing (1) under mature Q. pubescens trees in a forest or (2) as a lone tree within forest gaps or near the edges. In the closed-canopy forest where LF trees (Q. cerris) were surrounded by EF ones (Q. pubescens), the caterpillars on mature LF trees were in abundance, almost as on mature EF ones. The species composition of larval assemblages on the two oak species was similar. In contrast, on small groups and on lone trees, the lepidopteran larvae were significantly less abundant on LF trees than EF ones. In the case of young trees, the abundance of larvae and their composition assemblages on both oaks were comparable in the forest. In the open habitat, LF trees were less infested by larvae than EF ones and the assemblages of moth larvae differed between the two. Our results reveal the effect (associational susceptibility) of EF trees on LF ones when growing in a close vicinity. It means that the phenological protection of LF trees may not be sufficient if they grow close to or are surrounded by EF ones.
Surface Characteristics and Acoustical Properties of Bamboo Particle Board Coated with Polyurethane Varnish
Authors: Karlinasari Lina , Adzkia Ulfa , Sudarsono Anugrah Sabdono , Larasatie Pipiet , Amin Yusup , Nugroho Naresworo
Published: September 2021

Using bamboo particle board as a wall divider, a furniture component, or an automotive component with a sound absorber function may be a viable option for architects and engineers seeking to achieve desired acoustical qualities, including noise reduction. However, there is still a dearth of research on the effect of particle board finishing and coatings on acoustical sound absorption and noise reduction qualities. This study, therefore, aims to determine the surface characteristics and acoustical properties of bamboo particle board, coated with polyurethane (PU). The single-layer homogeneous particle boards were constructed using particles classified as fine and coarse with two different board densities, and coated with a high-quality PU lacquer. This study found that the coating treatment of 0.3 mm 0.6 mm succeeded to significantly decrease surface roughness, as well as thickness, swelling, and water absorption, with the thickness coating as a dominant factor compared with board density and board particle size. Adding a PU coating increases sound absorption performance at low frequencies, but significantly reduces acoustical properties at high frequencies. The increase of particle board density leads to the decrease in noise reduction coefficient capability. Results obtained from this study are useful to determine the optimal coating thickness in terms of evaluating acoustical panel products.
An Ecological Development Level Evaluation of the Forestry Industry in China Based on a Hybrid Ensemble Approach
Authors: Xu Dayu , Lu Chunping , Zhang Xuyao
Published: September 2021

The straits of ecological development in the forestry industry and the problems existing in the industrial forestry system are currently the main focus of policy-making research in China, to alleviate the contradiction between forestry economic development and the ecological environment, as well as evaluate the level and trend of the ecological development in China’s forestry industry. This paper analyzed the status of ecological development in China’s forestry industry via public data, constructed a novel evaluation index system for forestry industrial ecological development, and proposed a hybrid ensemble approach combined with principal component analysis, entropy weights, and fuzzy-DEMATEL to synthetically evaluate the ecological development level and system coordination of the forestry industry in each province of China. The experimental results show that technological innovation ability is the most significant restriction for the ecological development of China’s forestry industry. Obvious regional differences in the promotion degree of ecological development and the coordination of various elements throughout the country has also been confirmed. Findings of our research could be used for promoting the green transformation and upgrading of the forestry industry, and providing targeted practical countermeasures according to local conditions for governments at all levels.
High Seedling Mortality of Scots Pine Caused by Heterobasidion annosum s.s.
Authors: Piri Tuula , Vainio Eeva J. , Nuorteva Heikki , Hantula Jarkko
Published: September 2021

This study provides new information on the infection biology and pathogenicity of an important root-rot fungus, Heterobasidion annosum sensu stricto (Fr.) Bref., through a detailed examination of the vegetative spread of clonal individuals and their capacity to produce fruiting bodies on young pine seedlings. The seedlings were planted in a clear-cutting area (c. 1.2 ha in size) after a pine generation that showed slight external symptoms of Heterobasidion root rot. The first dead seedlings were found five years after planting and during a nine-year monitoring period; nearly 600 seedlings were killed by H. annosum s.s. in 48 individual disease centers. Based on pairing tests of 482 isolates, 117 different H. annosum s.s. genotypes were identified. On average, 2.9 genotypes occurred in a single disease center. The extensive secondary spread of genotypes within root systems (up to 48 pine seedlings infected by the same genotype) resulted in annually expanding disease centers. In addition, more than half of the seedlings killed by H. annosum s.s. produced perennial fruiting bodies thus providing air-borne inoculum. The risk of spore infection should be taken into account in any type of cutting operation in young pine stands. Moreover, new control measures directed towards the secondary spread of H. annosum s.s. in pine regeneration are urgently needed in order to maintain the productivity of the pine forest on infested sites.