bluuebunny/crossref_metadata_2025 huggingface dataset:
Lysimachiae Herba Inhibits Inflammatory Reactions and Improves Lipopolysaccharide/D-Galactosamine-Induced Hepatic Injury
Authors: Jeong Yun Hee , Kim Tae In , Oh You-Chang , Ma Jin Yeul
Published: August 2021

This study aimed to determine the anti-inflammatory and hepatoprotective effects of Lysimachiae Herba ethanolic extract (LHE) in lipopolysaccharide (LPS)-stimulated macrophages and in a LPS/D-galactosamine (GalN)-induced acute hepatitis mouse model. Then, the production of inflammatory mediators and the activation of related pathways in macrophages were explored. Finally, we assessed the serum aminotransferase levels and the expression of inflammatory/antioxidant molecules in liver tissues in mice. Results revealed that LHE treatment significantly inhibited the production of inflammatory mediators in LPS-stimulated RAW 264.7 macrophages. Molecular data showed that LHE remarkably increased the activities of the antioxidant pathway and inhibited the phosphorylation of mitogen-activated protein kinase as well as the transcriptional activity of nuclear factor-κB induced by LPS. Furthermore, it prevented acute liver damage caused by LPS/D-GalN-induced hepatitis by inhibiting aminotransferase levels and histopathological changes in mice. Moreover, treatment with LHE significantly inhibited the activation of inflammatory pathways and increased the expression of antioxidant molecules including heme oxygenase-1/Nuclear factor erythroid 2-related factor 2. In conclusion, LHE has potent anti-inflammatory and hepatoprotective effects in LPS-stimulated macrophages and the LPS/D-GalN-induced acute hepatitis mouse model. Thus, it can be a treatment option for inflammation, hepatitis, and liver injury.
PtrMYB3, a R2R3-MYB Transcription Factor from Poncirus trifoliata, Negatively Regulates Salt Tolerance and Hydrogen Peroxide Scavenging
Authors: Wei Tonglu , Guo Dalong , Liu Jihong
Published: August 2021

MYB transcription factors are widely present in plants and play significant roles in abiotic stresses. However, most MYB genes have not been identified in plants and their functions in abiotic stresses are still unknown. In this study, one MYB gene, designated as PtrMYB3, was cloned from trifoliate orange (Poncirus trifoliata (L.) Raf.), and its function in salt tolerance was investigated. PtrMYB3 contains a conserved R2R3-MYB domain, which is the typical property of R2R3-MYB subfamily proteins. Expression profiling under abiotic stresses indicated that PtrMYB3 could be induced by salt, dehydration and cold stresses. PtrMYB3 was found to be localized to the nucleus and possessed transactivation activity. Overexpression of PtrMYB3 by genetic transformation in tobacco impaired its salt tolerance, whereas silencing of PtrMYB3 by VIGS (virus-induced gene silencing) in trifoliate orange conferred significantly enhanced salt tolerance, indicating that PtrMYB3 negatively regulates salt tolerance. Furthermore, a peroxidase gene (PtrPOD) was found to be greatly upregulated in PtrMYB3-silenced trifoliate orange, and a dual LUC (luciferase) assay confirmed that PtrMYB3 could suppress the expression of PtrPOD. The hydrogen peroxide (H2O2) accumulation in PtrMYB3 transgenic tobacco plants after salt stress was higher than the wild type (WT), further confirming that overexpression of PtrMYB3 inhibited PtrPOD-mediated H2O2 scavenging. Taken together, these results demonstrate that PtrMYB3 negatively regulates salt tolerance, at least in part, due to the excess accumulation of H2O2.
Shedding Light into the Connection between Chemical Components and Biological Effects of Extracts from Epilobium hirsutum: Is It a Potent Source of Bioactive Agents from Natural Treasure?
Authors: Ak Gunes , Zengin Gokhan , Mahomoodally Mohamad Fawzi , Llorent-Martínez Eulogio , Orlando Giustino , Chiavaroli Annalisa , Brunetti Luigi , Recinella Lucia , Leone Sheila , Di Simone Simonetta Cristina , Menghini Luigi , Ferrante Claudio
Published: August 2021

Epilobium hirsutum is extensively used as a traditional remedy in folk medicine, especially against prostate inflammation. Therefore, we evaluated the chemical profiles and biopharmaceutical potentials of different extracts of E. hirsutum aerial parts and roots. Metabolomic, antioxidant, and enzyme inhibitory profiles were investigated. Human prostate cancer PC3 cells were exposed to the extracts to evaluate antiproliferative effects. Gene expression and bioinformatics analyses were performed to investigate anti-inflammatory mechanisms. Oenothein B and myricetin were prominent compounds in the extracts. In scavenging/reducing assays, the methanol, infusion, and methanol/water extracts exhibited similar activities. We also observed the reduction of PC3 viability occurring following exposure to methanol and methanol/water extracts. According to bioinformatics analysis, myricetin was predicted to interact with COX-2 and TNFα. The interaction between TNFα and oxo-dihydroxy-octadecenoic acid was predicted as well. Intriguingly, the gene expression of COX-2 and TNFα was reduced in PC3 cells after exposure to methanol and methanol/water extracts. These effects were paralleled by the decreased gene expression of IL-8 and NFkB and the inhibition of PGE2 release. Therefore, the present findings suggest the potential use of E. hirsutum for the management of the burden of inflammation and oxidative stress occurring in lower urinary tract diseases, including prostatitis.
Pharmacology of Catechins in Ischemia-Reperfusion Injury of the Heart
Authors: Ferenczyová Kristína , Kindernay Lucia , Vlkovičová Jana , Kaločayová Barbora , Rajtík Tomáš , Barteková Monika
Published: August 2021

Catechins represent a group of polyphenols that possesses various beneficial effects in the cardiovascular system, including protective effects in cardiac ischemia-reperfusion (I/R) injury, a major pathophysiology associated with ischemic heart disease, myocardial infarction, as well as with cardioplegic arrest during heart surgery. In particular, catechin, (−)-epicatechin, and epigallocatechin gallate (EGCG) have been reported to prevent cardiac myocytes from I/R-induced cell damage and I/R-associated molecular changes, finally, resulting in improved cell viability, reduced infarct size, and improved recovery of cardiac function after ischemic insult, which has been widely documented in experimental animal studies and cardiac-derived cell lines. Cardioprotective effects of catechins in I/R injury were mediated via multiple molecular mechanisms, including inhibition of apoptosis; activation of cardioprotective pathways, such as PI3K/Akt (RISK) pathway; and inhibition of stress-associated pathways, including JNK/p38-MAPK; preserving mitochondrial function; and/or modulating autophagy. Moreover, regulatory roles of several microRNAs, including miR-145, miR-384-5p, miR-30a, miR-92a, as well as lncRNA MIAT, were documented in effects of catechins in cardiac I/R. On the other hand, the majority of results come from cell-based experiments and healthy small animals, while studies in large animals and studies including comorbidities or co-medications are rare. Human studies are lacking completely. The dosages of compounds also vary in a broad scale, thus, pharmacological aspects of catechins usage in cardiac I/R are inconclusive so far. Therefore, the aim of this focused review is to summarize the most recent knowledge on the effects of catechins in cardiac I/R injury and bring deep insight into the molecular mechanisms involved and dosage-dependency of these effects, as well as to outline potential gaps for translation of catechin-based treatments into clinical practice.
Perinatal Resveratrol Therapy to Dioxin-Exposed Dams Prevents the Programming of Hypertension in Adult Rat Offspring
Authors: Hsu Chien-Ning , Hung Chih-Hsing , Hou Chih-Yao , Chang Chi-I. , Tain You-Lin
Published: August 2021

Exposure to environmental chemicals during pregnancy and lactation is a contributing factor in gut microbiota dysbiosis and linked to programming of hypertension. 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), the most toxic dioxin, induces toxic effects by mediating aryl hydrocarbon receptor (AHR). Resveratrol, a potent antioxidant with prebiotic properties, can possess high affinity for AHR and protect against TCDD-activated AHR attack. We examined whether perinatal resveratrol therapy prevents offspring hypertension programmed by maternal TCDD exposure and whether its beneficial effects are related to reshaping gut microbiota and antagonizing AHR-mediated T helper 17 (TH17) cells responses using a maternal TCDD exposure rat model. Pregnant Sprague-Dawley rats were given a weekly oral dose of TCDD 200 ng/kg for four doses (T), 50 mg/L of resveratrol in drinking water (CR), TCDD + resveratrol (TR), or vehicle (C) in pregnancy and lactation periods. Male offspring (n = 7–8/group) were sacrificed at the age of 12 weeks. Perinatal TCDD exposure caused elevated blood pressure in adult male offspring, which resveratrol supplementation prevented. Additionally, the TCDD-induced programming of hypertension is coincided with the activation of AHR signaling, TH17-induced renal inflammation, and alterations of gut microbiota compositions. Conversely, TCDD-mediated induction of AHR signaling and TH17 responses were restored by maternal resveratrol supplementation. Furthermore, maternal resveratrol supplementation prevented the programming of hypertension and was related to increased genera Bacteroides, ASF356, and Lachnoclostridium. Taken together, these results suggest that the interplay between gut microbiota, AHR-mediated TH17 responses, and renal inflammation in the gut and kidneys may play an important role in the action of resveratrol against TCDD-induced programming of hypertension.
SecureVision: An Open-Source User-Customizable Image Encryption Program
Authors: Shahmohammadi Beni Mehrdad , Watabe Hiroshi , Yu Kwan Ngok
Published: August 2021

Data security has become indispensable, with a view to keep sensitive information confidential. One important method is through image encryption, upon which features in an image would no longer be visible. The original image with its features could only be restored upon decryption using a set of keys. There are prestigious works in the literature regarding image encryption. However, there is a lack of easy-to-use, GUI-based, user-customizable computer programs for image encryption. In the present work, we developed a GUI-based image encryption and decryption program with server file transfer support, namely, SecureVision. A custom-made random number generator using the equation of an ellipse was developed to randomly shuffle the pixel positions. SecureVision was found to be robust, user-friendly and fast in both encryption and decryption. The program was highly sensitive to the supplied keys, which prevented brute-force attacks. SecureVision provided full user control, where users could modify the program modules to match their desired applications, which was particularly desirable for pedagogical purposes in that interested parties had the freedom to explore the concept of image encryption and decryption. SecureVision is distributed under a GPLv3 license, which would allow everyone to use, modify and distribute the program without any restriction.
A Novel Hybrid Deep Learning Model for Detecting COVID-19-Related Rumors on Social Media Based on LSTM and Concatenated Parallel CNNs
Authors: Al-Sarem Mohammed , Alsaeedi Abdullah , Saeed Faisal , Boulila Wadii , AmeerBakhsh Omair
Published: August 2021

Spreading rumors in social media is considered under cybercrimes that affect people, societies, and governments. For instance, some criminals create rumors and send them on the internet, then other people help them to spread it. Spreading rumors can be an example of cyber abuse, where rumors or lies about the victim are posted on the internet to send threatening messages or to share the victim’s personal information. During pandemics, a large amount of rumors spreads on social media very fast, which have dramatic effects on people’s health. Detecting these rumors manually by the authorities is very difficult in these open platforms. Therefore, several researchers conducted studies on utilizing intelligent methods for detecting such rumors. The detection methods can be classified mainly into machine learning-based and deep learning-based methods. The deep learning methods have comparative advantages against machine learning ones as they do not require preprocessing and feature engineering processes and their performance showed superior enhancements in many fields. Therefore, this paper aims to propose a Novel Hybrid Deep Learning Model for Detecting COVID-19-related Rumors on Social Media (LSTM–PCNN). The proposed model is based on a Long Short-Term Memory (LSTM) and Concatenated Parallel Convolutional Neural Networks (PCNN). The experiments were conducted on an ArCOV-19 dataset that included 3157 tweets; 1480 of them were rumors (46.87%) and 1677 tweets were non-rumors (53.12%). The findings of the proposed model showed a superior performance compared to other methods in terms of accuracy, recall, precision, and F-score.
Characterization of Two Hydrogen Peroxide Resistant Peroxidases from Rhodococcus opacus 1CP
Authors: Ngo Anna Christina R. , Conrad Catleen , Gómez Baraibar Álvaro , Matura Anke , van Pée Karl-Heinz , Tischler Dirk
Published: August 2021

The dye-decolorizing peroxidases (DyP) are a family of heme-dependent enzymes present on a broad spectrum of microorganisms. While the natural function of these enzymes is not fully understood, their capacity to degrade highly contaminant pigments such as azo dyes or anthraquinones make them excellent candidates for applications in bioremediation and organic synthesis. In this work, two novel DyP peroxidases from the organism Rhodococcus opacus 1CP (DypA and DypB) were cloned and expressed in Escherichia coli. The enzymes were purified and biochemically characterized. The activities of the two DyPs via 2,2′-azino-bis [3-ethylbenzthiazoline-6-sulphonic acid] (ABTS) assay and against Reactive Blue 5 were assessed and optimized. Results showed varying trends for DypA and DypB. Remarkably, these enzymes presented a particularly high tolerance towards H2O2, retaining its activities at about 10 mM H2O2 for DypA and about 4.9 mM H2O2 for DypB.
Principal Component Analysis and Machine Learning Approaches for Photovoltaic Power Prediction: A Comparative Study
Authors: Chahboun Souhaila , Maaroufi Mohamed
Published: August 2021

Nowadays, in the context of the industrial revolution 4.0, considerable volumes of data are being generated continuously from intelligent sensors and connected objects. The proper understanding and use of these amounts of data are crucial levers of performance and innovation. Machine learning is the technology that allows the full potential of big datasets to be exploited. As a branch of artificial intelligence, it enables us to discover patterns and make predictions from data based on statistics, data mining, and predictive analysis. The key goal of this study was to use machine learning approaches to forecast the hourly power produced by photovoltaic panels. A comparison analysis of various predictive models including elastic net, support vector regression, random forest, and Bayesian regularized neural networks was carried out to identify the models providing the best predicting results. The principal components analysis used to reduce the dimensionality of the input data revealed six main factor components that could explain up to 91.95% of the variation in all variables. Finally, performance metrics demonstrated that Bayesian regularized neural networks achieved the best results, giving an accuracy of R2 = 99.99% and RMSE = 0.002 kW.
Evaluating the Impact of Indoor Insulation on Historic Buildings: A Multilevel Approach Involving Heat and Moisture Simulations
Authors: Lisitano Ivana Mattea , Laggiard Deborah , Fantucci Stefano , Serra Valentina , Fenoglio Elisa
Published: August 2021

The energy refurbishment of historic buildings is a complex task for building envelope designers who need to carefully consider building conservation guidelines and principles. In most cases, external wall insulation techniques can determine an unacceptable alteration of the historical value of a building. For this reason, internal wall insulation techniques have been used widely in the last few decades. Nevertheless, dealing with internal wall insulation requires a complex design to avoid the risk of condensation and moisture-related pathologies. Moreover, an internal wall insulation may have a relevant impact on indoor comfort conditions. In this paper, the Monastery of Santa Maria de Monfero in Galicia (Spain) has been adopted as a building case study to compare different technological solutions based on: (i) an insulating plaster layer, (ii) dry counter wall systems. In the first step, heat and moisture transfer simulations of the wall components were performed to analyze the hygrothermal behavior of the different alternatives considering two different climate conditions. In a second step, a simulation of the whole building was performed to analyze the impact of the retrofitting strategies on the indoor climate and on the building heating and cooling demand. The obtained results show that the counter wall solution leads to higher energy savings during the heating season in the colder winter climate. However, the use of insulating thermal plaster could also be a viable solution since they lead to several advantages in summer because of their higher thermal inertia. Therefore, the selection of the most appropriate insulation technique has to be evaluated carefully considering the outdoor/indoor climate and using a case-by-case approach.
Effect of Heat Treatment on Microstructure and Creep Behavior of Fe-40Ni-24Cr Alloy
Authors: Mudang Maureen , Hamzah Esah , Bakhsheshi-Rad Hamid Reza , Berto Filippo
Published: August 2021

Iron-nickel-chromium (Fe-Ni-Cr) alloy Haynes HR120 is an iron-nickel-based superalloy, which is extensively used in gas turbines. Hence, the materials for the fabrication of steam turbine blades should present great mechanical characteristics and creep properties. In this study, Fe-40Ni-24Cr was heat-treated at temperatures from 950 to 1250 °C. High temperature creep behavior and microstructure evolution of the selected heat-treated (1050 °C, 1200 °C, 1225 °C and 1250 °C) Fe-40Ni-24Cr alloy were assessed at temperatures of 800 °C and 900 °C under 100 MPa stress. The alloy consisted of titanium and niobium rich precipitates, namely NbC, (Nb,Ti)C, TiN and Ti(C,N) distributed in the matrix grain boundaries, which enhance the creep properties of the alloy. The hardness of heat-treated Fe-40Ni-24Cr alloy decreased with increasing temperature and grain size. The creep strain of the Fe-40Ni-24Cr alloy increased with escalation in the creep time and the temperature being under constant applied stress. Fe-40Ni-24Cr alloy shows a decrease in steady-state creep rate with an increase in grain size from 62 μm to 183 μm due to the grain boundary sliding mechanism and 183 μm to 312 μm due to the occurrence of dislocation climb. This result exhibited that grain size has a significant influence on the alloys’ high temperature creep properties.
Optimal Coordination of Over-Current Relays in Microgrids Using Principal Component Analysis and K-Means
Authors: Saldarriaga-Zuluaga Sergio D. , López-Lezama Jesús M. , Muñoz-Galeano Nicolás
Published: August 2021

Microgrids (MGs) are decentralized systems that integrate distributed energy resources and may operate in grid-connected or islanded modes. Furthermore, MGs may feature several topologies or operative scenarios. These characteristics bring about major challenges in determining a proper protection coordination scheme. A new optimal coordination approach for directional over-current relays (OCRs) in MGs is proposed. In this case, a clustering of operational models is carried out by means of a K-means algorithm hybridized with the principal component analysis (PCA) technique. The number of clusters is limited by the number of setting groups of commercially available relays. The results carried out on a benchmark IEC microgrid evidence the applicability and effectiveness of the proposed approach.
A Low-Power, Low-Noise, Resistive-Bridge Microsensor Readout Circuit with Chopper-Stabilized Recycling Folded Cascode Instrumentation Amplifier
Authors: Choi Gyuri , Heo Hyunwoo , You Donggeun , Kim Hyungseup , Nam Kyeongsik , Yoo Mookyoung , Lee Sangmin , Ko Hyoungho
Published: August 2021

In this paper, a low-power and low-noise readout circuit for resistive-bridge microsensors is presented. The chopper-stabilized, recycling folded cascode current-feedback instrumentation amplifier (IA) is proposed to achieve the low-power, low-noise, and high-input impedance. The chopper-stabilized, recycling folded cascode topology (with a Monticelli-style, class-AB output stage) can enhance the overall noise characteristic, gain, and slew rate. The readout circuit consists of a chopper-stabilized, recycling folded cascode IA, low-pass filter (LPF), ADC driving buffer, and 12-bit successive-approximation-register (SAR) analog-to-digital converter (ADC). The prototype readout circuit is implemented in a standard 0.18 µm CMOS process, with an active area of 12.5 mm2. The measured input-referred noise at 1 Hz is 86.6 nV/√Hz and the noise efficiency factor (NEF) is 4.94, respectively. The total current consumption is 2.23 μA, with a 1.8 V power supply.
Towards an Ontology-Driven Information System for Archaeological Pottery Studies: The Greyware Experience
Authors: Travé Allepuz Esther , Medina Gordo Sonia , del Fresno Bernal Pablo , Vicens Tarré Joan , Mauri Martí Alfred
Published: August 2021

The archaeological analysis of medieval and modern pottery has benefited from the consolidation of archaeometry in the domain of Medieval Archaeology in the past few decades. As part of an ongoing research project devoted to the characterization of pottery production, distribution processes and technological transfer, we deal with a considerable amount of data that are very diverse in origin and nature and must be exploited within an integrated information system in order to provide information for historical knowledge. The Greyware system has been designed to fulfil this goal and provides the main categories for pottery analysis within a shareable and reusable scenario. Its development and application prove that a little semantics goes a long way and that the creation of domain ontologies for archaeological research is an iterative process under development, as long as several projects sharing data, resources and time can develop a collaborative framework to maximize the assets of individual expertise and collaborative work. In this paper, we discuss the requirements of the system, the challenge of developing strategies for normalized data management and their potential for exploiting historical vestiges from an integrated perspective.
Analysis of Nanoindentation Test Results of Asphalt Mixture with Different Gradations
Authors: Yu Yunhong , Xu Gang , Wang Tianling , Chen Huimin , Wang Houzhi , Yang Jun
Published: August 2021

Nanoindentation has been applied in the field of asphalt mixtures, but, at the nano-scale, changes in the composition of the mixture and material properties can have a significant impact on the results. Therefore, it is necessary to investigate the feasibility of nanoindentation tests on different types of asphalt mixtures with different gradations and the influence of material properties and test methods on nanoindentation results. In this paper, the nanoindentation test results on three kinds of asphalt mixture (AC-13, SMA-13, and OGFC-13) with different aggregate gradations were investigated. The load-displacement curves and moduli obtained from the nanoindentation tests were analyzed. In addition, nanoindentation tests were carried out before and after polishing with different ratios of filler and asphalt (RFA) (0.8–1.6). On this basis, the morphology of asphalt specimens with different RFAs is observed by scanning electron microscopy (SEM) imaging. The results indicate that using the nanoindentation test to characterize the mechanical behavior of asphalt mixture, the confidence level of the dense-graded mixture is low, and non-dense-graded mixtures are used as much as possible. Moreover, results illustrate that the nanoindentation modulus tends to increase as the RFA increases. and the SEM chart shows that the higher the mineral powder content in the mastic, the more complex the bitumen and mineral powder interaction surface, confirming the influence of mineral powder content on the nanoindentation test results. Furthermore, the effect of polishing is almost insignificant.
Unveiling the Invisible in Uffizi Gallery’s Drawing 8P by Leonardo with Non-Invasive Optical Techniques
Authors: Dal Fovo Alice , Striova Jana , Pampaloni Enrico , Fontana Raffaella
Published: August 2021

Until recently, the study of drawings by old masters has been confined to the art history conservation field. More specifically, scientific investigations of Leonardo’s drawings are still very few, possibly due to the latter’s extreme fragility and artistic value. However, analytical data are crucial to develop a solid knowledge base of the drawing materials and techniques used by artists in the past. In this work, we report on the application of non-invasive optical techniques on a double-sided drawing by Leonardo belonging to the Uffizi Gallery (8P). We used multispectral reflectography in the visible (Vis) and near-infrared (NIR) regions to obtain a spectral mapping of the drawing materials, to be subsequently integrated with technical information provided by art historians and conservators. Morphological analysis by microprofilometry allowed for the identification of the typical wave-like texture impressed in the paper during the sheet’s manufacture, as well as of further paper-impressed traits attributable to the drawing transfer method used by Leonardo. Optical coherence tomography revealed a set of micrometric engraved details in the blank background, which lack any trace of colored material, nor display any apparent relation to the drawn landscape. The disclosure of hidden technical features allowed us to offer new insights into Leonardo’s still under-investigated graphic practices.
Shared Mobility Problems: A Systematic Review on Types, Variants, Characteristics, and Solution Approaches
Authors: Ting Kien Hua , Lee Lai Soon , Pickl Stefan , Seow Hsin-Vonn
Published: August 2021

The Shared Mobility Problems (SMP) with the rideshare concept based on sharing a vehicle are fast becoming a trend in many urban cities around the world. Examples of these problems are like ridesharing, carpooling, taxisharing, buspooling, vanpooling, and multi-modal ridesharing. This is the new way to access transportation services by those who are propelling the sharing economy, where access rather than ownership is the new norm. This paper provides a systematic review of SMP using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) method. A total of 110 papers from the last decade are selected from 12 abstracts and citation databases to be reviewed and classified. This is done based on the problem types, variants, characteristics, and solution approaches. The current trends and analysis of the survey findings are also summarised. From this systematic review, it is observed that both the time window and multi-objective problems are popular among the researchers, while the minimisation of the total cost is the main concern in the literature of the SMP. Both static and dynamic cases of the SMP are the most researched where heuristic and metaheuristic approaches are widely adopted by the researchers in the literature. Finally, challenges and suggestions for future work are discussed and highlighted.
Ellipsoidal Path Planning for Unmanned Aerial Vehicles
Authors: Villaseñor Carlos , Gallegos Alberto A. , Lopez-Gonzalez Gehova , Gomez-Avila Javier , Hernandez-Barragan Jesus , Arana-Daniel Nancy
Published: August 2021

The research in path planning for unmanned aerial vehicles (UAV) is an active topic nowadays. The path planning strategy highly depends on the map abstraction available. In a previous work, we presented an ellipsoidal mapping algorithm (EMA) that was designed using covariance ellipsoids and clustering algorithms. The EMA computes compact in-memory maps, but still with enough information to accurately represent the environment and to be useful for robot navigation algorithms. In this work, we develop a novel path planning algorithm based on a bio-inspired algorithm for navigation in the ellipsoidal map. Our approach overcomes the problem that there is no closed formula to calculate the distance between two ellipsoidal surfaces, so it was approximated using a trained neural network. The presented path planning algorithm takes advantage of ellipsoid entities to represent obstacles and compute paths for small UAVs regardless of the concavity of these obstacles, in a very geometrically explicit way. Furthermore, our method can also be used to plan routes in dynamical environments without adding any computational cost.
Piezoelectric Silicon Micropump for Drug Delivery Applications
Authors: Bußmann Agnes , Leistner Henry , Zhou Doris , Wackerle Martin , Congar Yücel , Richter Martin , Hubbuch Jürgen
Published: August 2021

Subcutaneous injection is crucial for the treatment of many diseases. Especially for regular or continuous injections, automated dosing is beneficial. However, existing devices are large, uncomfortable, visible under clothing, or interfere with physical activity. Thus, the development of small, energy efficient and reliable patch pumps or implantable systems is necessary and research on microelectromechanical system (MEMS) based drug delivery devices has gained increasing interest. However, the requirements of medical applications are challenging and especially the dosing precision and reliability of MEMS pumps are not yet sufficiently evaluated. To enable further miniaturization, we propose a precise 5 × 5 mm2 silicon micropump. Detailed experimental evaluation of ten pumps proves a backpressure capability with air of 12.5 ± 0.8 kPa, which indicates the ability to transport bubbles. The maximal water flow rate is 74 ± 6 µL/min and the pumps’ average blocking pressure is 51 kPa. The evaluation of the dosing precision for bolus deliveries with water and insulin shows a high repeatability of dosed package volumes. The pumps show a mean standard deviation of only 0.02 mg for 0.5 mg packages, and therefore, stay below the generally accepted 5% deviation, even for this extremely small amount. The high precision enables the combination with higher concentrated medication and is the foundation for the development of an extremely miniaturized patch pump.
Spatio-Temporal Variation of Reference Evapotranspiration and Its Climatic Drivers over the Tibetan Plateau during 1970–2018
Authors: Hu Shanshan , Gao Ruyi , Zhang Tao , Bai Peng , Zhang Rui
Published: August 2021

Reference evapotranspiration (ET0) is a key component of hydrologic cycle and it is important for water resources management. Analysis of ET0 changes is particularly critical for understanding the impacts of climatic change on hydrology in ecologically fragile regions. In this study, using the Penman–Monteith method and the Mann–Kendall test, the variation characteristics of ET0 on the Tibetan Plateau (TP) from 1970 to 2018 was analyzed, and the dominant climatic factors controlling the change of ET0 was also explored. The result shows that in TP region: (1) there was an abrupt change in the trend of ET0 around 1997, and the ET0 declined at a rate of −25.9 mm/decade during 1970–1996 but increased by 31.1 mm/decade during 1997–2018; (2) ET0 is most sensitive to solar radiation, then relative humidity, wind speed and mean temperature; (3) the decrease of ET0 before 1997 was mainly due to the decline of wind speed and the increase of relative humidity, while the increase of ET0 after 1997 was mainly due to the decrease of relative humidity. The results of this study can provide data reference for the research of water balance on the TP.
A Dynamic Model Updating Method with Thermal Effects Based on Improved Support Vector Regression
Authors: Chen Zhe , Zhao Qijun
Published: August 2021

The dynamic modeling of structures in a thermal environment has become a new research topic in structural dynamics. The amount of calculation caused by the complexity of the structure and the size of the FEM, which increase the difficulty in modeling the structural dynamic thermal effects are considered. In this study, model updating in thermal temperature environment is proposed based on the hierarchical method and improved SVR, and an iterative procedure is presented. First, the dynamic problem of structure under a thermal environment is classified into a thermal model and a structural dynamic model, and they are both constructed with the FE method. As a result, the model updating process is conducted for both the thermal model and structural dynamic model. Different from the variables in other model updating methods, the updating variables, which are composed of the mechanical characteristics and thermal parameters, in the proposed method are dominated by the temperature distribution of the structure. A surrogate model based on improved SVR is adopted in the hierarchical model updating approach to make the updating process more efficient. Finally, the improved SVR method is validated on a typical nonlinear function, and the proposed method is validated by updating the model of an elastic thin plate and a wing structure in a thermal environment.
XRF and 3D Modelling on a Composite Etruscan Helmet
Authors: Emmitt Joshua , McAlister Andrew , Bawden Neda , Armstrong Jeremy
Published: August 2021

The presentation of X-ray fluorescence data (XRF) assays is commonly restricted to tables or graphical representations. While the latter may sometimes be in a 3D format, they have yet to incorporate the actual objects they are from. The presentation of multiple XRF assays on a 3D model allows for more accessible presentation of data, particularly for composite objects, and aids in their interpretation. We present a method to display and interpolate assay data on 3D models using the PyVista Python package. This creates a texture of the object that displays the relative differences in elemental composition. A crested helmet from Tomb 1036 from the Casale del Fosso necropolis, Veii, Italy, is used to exemplify this method. The results of the analysis are presented and show variation in composition across the helmet, which also corresponds with macroscopic and decorrelation stretching analyses.
Methods for Noise Event Detection and Assessment of the Sonic Environment by the Harmonica Index
Authors: Alsina-Pagès Rosa Ma , Benocci Roberto , Brambilla Giovanni , Zambon Giovanni
Published: August 2021

Noise annoyance depends not only on sound energy, but also on other features, such as those in its spectrum (e.g., low frequency and/or tonal components), and, over time, amplitude fluctuations, such as those observed in road, rail, or aircraft noise passages. The larger these fluctuations, the more annoying a sound is generally perceived. Many algorithms have been implemented to quantify these fluctuations and identify noise events, either by looking at transients in the sound level time history, such as exceedances above a fixed or time adaptive threshold, or focusing on the hearing perception process of such events. In this paper, four criteria to detect sound were applied to the acoustic monitoring data collected in two urban areas, namely Andorra la Vella, Principality of Andorra, and Milan, Italy. At each site, the 1 s A-weighted short LAeq,1s time history, 10 min long, was available for each hour from 8:00 a.m. to 7:00 p.m. The resulting 92-time histories cover a reasonable range of urban environmental noise time patterns. The considered criteria to detect noise events are based on: (i) noise levels exceeding by +3 dB the continuous equivalent level LAeqT referred to the measurement time (T), criteria used in the definition of the Intermittency Ratio (IR) to detect noise events; (ii) noise levels exceeding by +3 dB the running continuous equivalent noise level; (iii) noise levels exceeding by +10 dB the 50th noise level percentile; (iv) progressive positive increments of noise levels greater than 10 dB from the event start time. Algorithms (iii) and (iv) appear suitable for notice-event detection; that is, those that (for their features) are clearly perceived and potentially annoy exposed people. The noise events detected by the above four algorithms were also evaluated by the available anomalous noise event detection (ANED) procedure to classify them as produced by road traffic noise or something else. Moreover, the assessment of the sonic environment by the Harmonica index was correlated with the single event level (SEL) of each event detected by the four algorithms. The threshold value of 8 for the Harmonica index, separating the “noisy” from the “very noisy” environments, corresponds to lower SEL levels for notice-events as identified by (iii) and (iv) algorithms (about 88–89 dB(A)) against those identified by (i) and (ii) criteria (92 dB(A)).
Use of Seismic Spectral Decomposition, Phase, and Relative Geologic Age as Attributes to Improve Quantitative Porosity Prediction in the Daqing Field, China
Authors: Mora Calderon David , Castagna John P. , Meza Ramses , Chen Shumin , Jiang Renqi
Published: August 2021

The high production potential of the Daqing oilfield in China is recognized for seismically thin sand bodies that usually are not resolved with conventional seismic data. The present study assesses the usefulness of applying seismic multi-attribute analysis to bandwidth extended data in resolving and making inferences about these thin layers. In thin layers, tuning can obscure relationships between seismic amplitude and rock properties. In such cases, the seismic phase varies with the layer impedance and may hence aid in reservoir characterization. A seismically derived relative geologic age may also be a useful attribute in predicting rock properties because it helps define the stratigraphic position of a layer. When utilized in multi-attribute analysis in the Daqing field, spectral decomposition amplitude, phase, and a relative geological age attribute to improved prediction of well log effective porosity from seismic data and are preferentially selected by stepwise regression. The study follows standard methodology by implementing seismic multi-attribute analysis and discusses the improvement of applying it to bandwidth extended data. This will include a combination of attributes such as relative geologic age, phase, amplitude, and the magnitude components of spectrally decomposed data.
Analysis Strategies for MHz XPCS at the European XFEL
Authors: Dallari Francesco , Reiser Mario , Lokteva Irina , Jain Avni , Möller Johannes , Scholz Markus , Madsen Anders , Grübel Gerhard , Perakis Fivos , Lehmkühler Felix
Published: August 2021

The nanometer length-scale holds precious information on several dynamical processes that develop from picoseconds to seconds. In the past decades, X-ray scattering techniques have been developed to probe the dynamics at such length-scales on either ultrafast (sub-nanosecond) or slow ((milli-)second) time scales. With the start of operation of the European XFEL, thanks to the MHz repetition rate of its X-ray pulses, even the intermediate μs range have become accessible. Measuring dynamics on such fast timescales requires the development of new technologies such as the Adaptive Gain Integrating Pixel Detector (AGIPD). μs-XPCS is a promising technique to answer many scientific questions regarding microscopic structural dynamics, especially for soft condensed matter systems. However, obtaining reliable results with complex detectors at free-electron laser facilities is challenging and requires more sophisticated analysis methods compared to experiments at storage rings. Here, we discuss challenges and possible solutions to perform XPCS experiments with the AGIPD at European XFEL; in particular, at the Materials Imaging and Dynamics (MID) instrument. We present our data analysis pipeline and benchmark the results obtained at the MID instrument with a well-known sample composed by silica nanoparticles dispersed in water.
COVID-19 Lesion Segmentation Using Lung CT Scan Images: Comparative Study Based on Active Contour Models
Authors: Akbari Younes , Hassen Hanadi , Al-Maadeed Somaya , Zughaier Susu M.
Published: August 2021

Pneumonia is a lung infection that threatens all age groups. In this paper, we use CT scans to investigate the effectiveness of active contour models (ACMs) for segmentation of pneumonia caused by the Coronavirus disease (COVID-19) as one of the successful methods for image segmentation. A comparison has been made between the performances of the state-of-the-art methods performed based on a database of lung CT scan images. This review helps the reader to identify starting points for research in the field of active contour models on COVID-19, which is a high priority for researchers and practitioners. Finally, the experimental results indicate that active contour methods achieve promising results when there are not enough images to use deep learning-based methods as one of the powerful tools for image segmentation.
Aging Affects Multi-Objective Optimal Control Strategies during Obstacle Crossing
Authors: Kuo Chien-Chung , Wang Jr-Yi , Chen Sheng-Chang , Lu Tung-Wu , Hsu Horng-Chaung
Published: August 2021

Obstacle crossing challenges balance and increases the risk of falls in older people. Knowledge of the control strategies adopted by older people will be helpful for the study of the mechanisms of falls during obstacle crossing and the development of fall-prevention approaches. A mechanical model of the body combined with measured gait data was used to study the control strategies adopted by 17 healthy older and 17 young adults when crossing obstacles of different heights, in terms of the best-compromise weighting sets for the objectives of minimizing energy expenditure and maximizing the toe-obstacle and heel-obstacle clearances. The older group showed increased leading toe-obstacle clearance and trailing toe-obstacle distance, but decreased leading heel-obstacle distance. Compared with the young, the crossing strategy of older people emphasized the foot-obstacle clearance to reduce the risk of tripping, at the expense of energy expenditure. It appears that the multi-objective optimal control strategy relies on the muscular strength of the lower extremities and precise end-point control. Therefore, maintaining or improving the muscle strength and the ability of limb position control is critical for safe and successful obstacle-crossing in the older population.
Glassy Carbon Electrochemical Sensor for Gallic and Vanillic Acid Detection in Aqueous Solutions
Authors: Zagoraios Dimitrios , Ioakeimidis Charis , Kyriakou Georgios , Katsaounis Alexandros
Published: August 2021

In the present study, an inexpensive and practical way to detect phenolic compounds in wastewater was investigated. By using a simple one compartment three-electrode cell and performing cyclic voltammetry measurements, it was possible to quantitatively determine the presence of gallic and vanillic acid in acidic aqueous solutions due to their electrooxidation upon potential scanning. In the case of gallic acid, two oxidation peaks were observed whereas the vanillic acid cyclic voltammograms consisted of two oxidation and one reduction peaks. Correlation of the observed electrooxidation current density value with the concentration of each phenolic compound led to a linear relationship. Following the above methodology for a 1:1 mixture of these phenols, it was found that only a qualitative analysis was possible rather than a quantitative one.
A Novel Approach to Learning Models on EEG Data Using Graph Theory Features—A Comparative Study
Authors: Prakash Bhargav , Baboo Gautam Kumar , Baths Veeky
Published: August 2021

Brain connectivity is studied as a functionally connected network using statistical methods such as measuring correlation or covariance. The non-invasive neuroimaging techniques such as Electroencephalography (EEG) signals are converted to networks by transforming the signals into a Correlation Matrix and analyzing the resulting networks. Here, four learning models, namely, Logistic Regression, Random Forest, Support Vector Machine, and Recurrent Neural Networks (RNN), are implemented on two different types of correlation matrices: Correlation Matrix (static connectivity) and Time-resolved Correlation Matrix (dynamic connectivity), to classify them either on their psychometric assessment or the effect of therapy. These correlation matrices are different from traditional learning techniques in the sense that they incorporate theory-based graph features into the learning models, thus providing novelty to this study. The EEG data used in this study is trail-based/event-related from five different experimental paradigms, of which can be broadly classified as working memory tasks and assessment of emotional states (depression, anxiety, and stress). The classifications based on RNN provided higher accuracy (74–88%) than the other three models (50–78%). Instead of using individual graph features, a Correlation Matrix provides an initial test of the data. When compared with the Time-resolved Correlation Matrix, it offered a 4–5% higher accuracy. The Time-resolved Correlation Matrix is better suited for dynamic studies here; it provides lower accuracy when compared to the Correlation Matrix, a static feature.
Effect of the MPT Pore Inhibitor Alisporivir on the Development of Mitochondrial Dysfunction in the Heart Tissue of Diabetic Mice
Authors: Belosludtseva Natalia V. , Starinets Vlada S. , Mikheeva Irina B. , Serov Dmitriy A. , Astashev Maxim E. , Belosludtsev Maxim N. , Dubinin Mikhail V. , Belosludtsev Konstantin N.
Published: August 2021

Diabetes mellitus is a systemic metabolic disorder associated with mitochondrial dysfunction, with the mitochondrial permeability transition (MPT) pore opening being considered as one of its possible mechanisms. The effect of alisporivir, a non-immunosuppressive cyclosporin derivative and a selective inhibitor of the MPT pore opening, on the ultrastructure and functions of the heart mitochondria of mice with diabetes mellitus induced by a high-fat diet combined with streptozotocin injections was studied. The treatment of diabetic animals with alisporivir (2.5 mg/kg ip for 20 days) increased the rate of glucose clearance during the glucose tolerance test. The blood glucose level and the indicator of heart rate in alisporivir-treated diabetic mice tended to restore. An electron microscopy analysis showed that alisporivir prevented mitochondrial swelling and ultrastructural alterations in cardiomyocytes of diabetic mice. Alisporivir canceled the diabetes-induced increases in the susceptibility of heart mitochondria to the MPT pore opening and the level of lipid peroxidation products, but it did not affect the decline in mitochondrial oxidative phosphorylation capacity. The mRNA expression levels of Pink1 and Parkin in the heart tissue of alisporivir-treated diabetic mice were elevated, suggesting the stimulation of mitophagy. In parallel, alisporivir decreased the level of mtDNA in the heart tissue. These findings suggest that targeting the MPT pore opening by alisporivir alleviates the development of mitochondrial dysfunction in the diabetic heart. The cardioprotective effect of the drug in diabetes can be mediated by the induction of mitophagy and the inhibition of lipid peroxidation in the organelles.