bluuebunny/crossref_metadata_2025 huggingface dataset:
Traditional Medicinal Uses, Phytochemistry, Biological Properties, and Health Applications of Vitex sp.
Authors: Kamal Nurkhalida , Mio Asni Nurul Syahidah , Rozlan Ivana Nur Allisya , Mohd Azmi Muhammad Aniq Hamzah , Mazlan Noor Wini , Mediani Ahmed , Baharum Syarul Nataqain , Latip Jalifah , Assaw Suvik , Edrada-Ebel Ru Angelie
Published: July 2022

The genus Vitex is also known as a chaste tree, in which it is a large shrub native to the tropical and subtropical regions of the world. A diverse range of species is distributed throughout Southern Europe, the Mediterranean, and Central Asia. The Vitex tree, including its leaves and fruits, has been used for herbal remedies in the form of pastes, decoctions, and dried fruits since ancient times. This article aimed to prepare a comprehensive review of traditional uses and secondary metabolites derived from Vitex sp., including the chemical compounds, biological activities, application of Vitex in human clinical trials, toxicology and safety, marketed products, and patents. The scientific findings were obtained using a number of search engines and databases, including Google Scholar, PMC, and ScienceDirect. Vitex species are well known in pharmacology to have medicinal values, such as anti-inflammatory, antibacterial, antifungal, antimicrobial, antioxidant, and anticancer properties. Previous studies reported that some species are proven to be effective in treating diseases, such as diabetes, and improving female health. A total of 161 compounds from different Vitex species are reported, covering the literature from 1982 to 2022. A chemical analysis report of various studies identified that Vitex exhibited a wide range of phytoconstituents, such as iridoid, diterpenoid, ecdysteroid, and flavonoid and phenolic compounds. Apart from that, the review will also discuss the application of Vitex in human clinical trials, toxicology and safety, marketed products, and patents of the genus. While the extracts of the genus have been made into many commercial products, including supplements and essential oils, most of them are made to be used by women to improve menstrual conditions and relieve premenstrual syndrome. Among the species, Vitex agnus-castus L. is the only one that has been reported to undergo clinical trials, mainly related to the use of the genus for the treatment of mastalgia, menstrual bleeding problems, amenorrhea, menorrhagia, luteal insufficiency, and premenstrual syndrome. Overall, the review addresses recent therapeutic breakthroughs and identifies research gaps that should be explored for prospective research work.
The Local Topological Free Energy of the SARS-CoV-2 Spike Protein
Authors: Baldwin Quenisha , Sumpter Bobby , Panagiotou Eleni
Published: July 2022

The novel coronavirus SARS-CoV-2 infects human cells using a mechanism that involves binding and structural rearrangement of its Spike protein. Understanding protein rearrangement and identifying specific amino acids where mutations affect protein rearrangement has attracted much attention for drug development. In this manuscript, we use a mathematical method to characterize the local topology/geometry of the SARS-CoV-2 Spike protein backbone. Our results show that local conformational changes in the FP, HR1, and CH domains are associated with global conformational changes in the RBD domain. The SARS-CoV-2 variants analyzed in this manuscript (alpha, beta, gamma, delta Mink, G614, N501) show differences in the local conformations of the FP, HR1, and CH domains as well. Finally, most mutations of concern are either in or in the vicinity of high local topological free energy conformations, suggesting that high local topological free energy conformations could be targets for mutations with significant impact of protein function. Namely, the residues 484, 570, 614, 796, and 969, which are present in variants of concern and are targeted as important in protein function, are predicted as such from our model.
Effects of MWCNTs on Char Layer Structure and Physicochemical Reaction in Ethylene Propylene Diene Monomer Insulators
Authors: Chen Zhiheng , Han Shida , Ji Yuan , Wu Hong , Guo Shaoyun , Yan Ning , Li Hongyan
Published: July 2022

As one of the most promising ablative fillers, multi-walled carbon nanotubes (MWCNTs) have been used to improve the ablative resistance of Ethylene–Propylene–Diene Monomer (EPDM) insulators by facilitating the carbothermal reduction reaction of silica. However, the contribution of MWCNTs to char layer structure of the insulators was unclear. In this work, the effects of MWCNTs on char layer structure and ablative resistance were investigated in different EPDM-based insulators with and without silica. The results showed that adding only 3 phr MWCNTs can reduce the linear ablation rate of EPDM-based insulators without silica by 31.7%, while 6 phr MWCNTs are required to obtain similar results in EPDM-based insulators with silica. The char layer morphology of the two insulators gradually evolved into a dense porous structure as MWCNTs content increased, but their formation mechanisms were different. The XRD and Raman spectrum showed that different physicochemical reactions occurred around MWCNTs under different charring components. The proposed ablation mechanism was further verified by designing alternating multilayer distribution of MWCNTs and silica. This work can guide the construction of desirable char layer structure for increasing the ablative resistance of EPDM-based insulators.
Characterization of Epoxy-Based Rapid Mold with Profiled Conformal Cooling Channel
Authors: Kuo Chil-Chyuan , Zhu Yi-Jun
Published: July 2022

Based on the experience of the foundry industry, reducing the demolding time is the key for mass production of wax patterns with sophisticated geometries. Integration of numerical simulation and rapid tooling technology for decreasing the time to market is essential in advanced manufacturing technology. However, characterization of epoxy-based rapid molds with a profiled conformal cooling channel (PCCC) using computer-aided engineering simulation of the epoxy-based rapid mold with PCCC was not found in the literature. In this study, epoxy-based rapid molds with PCCC were characterized numerically and experimentally. The cooling performance of wax injection molds with two different kinds of cross-sections of the cooling channel was investigated. Four pairs of injection molds with PCCC were implemented using four different kinds of material formulations. It was found that the cooling performance of the PCCC was better than a circular conformal cooling channel (CCCC) since the PCCC maintained a more uniform and steady cooling performance of injection-molded product than CCCC. Epoxy resin added with 41 vol.% Cu powder seems to be a cost-effective empirical material formulation in terms of cooling time and material costs. This empirical material formulation provided an injection mold with low material cost and good cooling performance simultaneously compared to an injection mold fabricated with commercial material. The cooling performance could reach 88% of that of the injection mold fabricated with commercial material. The material cost of making the injection mold was only about 60% of that of the injection mold fabricated with commercial material. The coolant flow rate had no significant effect on the cooling time, whereas the cooling time of the wax pattern was affected by coolant temperature significantly.
Drug Release Property of Poly 3-Hydroxybutyrate 4-Hydroxybutyrate (P34HB) as Drug-Eluting Coatings on Metal Coronary Stents
Authors: Jian Yihui , Zhu Yufang
Published: July 2022

Drug-eluting stents (DES) have become the main method of interventional therapy for coronary heart disease, because their drug coating can effectively reduce the incidence of restenosis after stent implantation. Biodegradable polymers for coatings are the latest development direction for coating polymers, because they can be degraded into small molecules in the human body. In this study, the polymer P34HB(P34HB-1:4HB% = 1 mol%, Mw: 225,000; P34HB-10:4HB% = 10 mol%, Mw: 182,000), the fourth generation of biodegradable Polyhydroxy alkanoates (PHAs), was coated on stents to evaluate the drug release properties of the DES. Both P34HB-1 and P34HB-10 coatings showed increased drug release rates, as the polymer concentrations were gradually increased from 8 mg/mL to 28 mg/mL. Both P34HB-1 and P34HB-10 coatings showed increased drug release rates as the drug polymer ratios were gradually changed from 1:10 to 1:2. The drug release rates of the P34HB-1 coatings became slower than P34HB-10, thus showing sustained drug release effects. The drug release rates of the P34HB-1 coatings decreased when Rates of solution flow increased, decreased when Focusing pressures decreased, and decreased when Mandrel moving speeds increased. P34HB-1 coatings prepared with CHCl3/NPA (10:1) mixed solvents had better controlled drug release rates compared to Firebird2®. The drug release rates of P34HB-1 coatings prepared with CHCl3 solutions decreased as the outer layer weights were increased from 0 to 800 μg. When the outer layer weights reached 800 μg, the drug release rates of P34HB-1 coatings were slower than Firebird2®. P34HB-1 coatings prepared with both CHCl3/NPA (10:1) mixed solvents and double layers had more effectively controlled drug release rates than P34HB-1 coatings prepared with only mixed solvents or double layers and these effects were far greater than Firebird2@; thus, P34HB-1 represents a latent polymer for DES.
Development and Optimization of Nigella sativa Nanoemulsion Loaded with Pioglitazone for Hypoglycemic Effect
Authors: Shehata Tamer M. , Almostafa Mervt M. , Elsewedy Heba S.
Published: July 2022

Diabetes mellitus (DM) is a metabolic disorder associated with an increased blood glucose level. The world health burden of DM has increased as a result of numerous causes that necessitates suitable treatment. Pioglitazone (PGZ) is a generally prescribed medication for managing type II diabetes. However, its low solubility creates complications for its formulation. Therefore, the aim of the current study was to incorporate PGZ into a nanoemulsion (NE) formulation prepared with Nigella sativa oil (NSO) to boost the action of PGZ. To our knowledge, no previous study has addressed the combination and synergistic effect of PGZ and NSO as a hypoglycemic NE formulation intended for oral administration. An experiment was designed to test several PGZ-loaded NE formulations, varying factors such as NSO, surfactant and co-surfactant concentrations. These factors were investigated for their influence on responses including particle size and in vitro release. An optimized PGZ-loaded NE was selected and examined for its morphology, kinetic activity and stability. Further, the anti-diabetic effect of the optimized formulation was evaluated using diabetically induced rats. The optimized formula exhibited a good particle size of 167.1 nm and in vitro release of 89.5%. A kinetic study revealed that the drug release followed the Korsmeyer–Peppas mechanism. Additionally, the PGZ-loaded NE formulation was found to be stable, showing non-significant variation in the evaluated parameters when stored at 4 and 25 °C for a period of 3 months. In vivo investigation of the PGZ-loaded NE formulation showed a significant reduction in blood glucose level, which appeared to be enhanced by the presence of NSO. In conclusion, NS-NE could be a promising nanocarrier for enhancing the hypoglycemic effect of PGZ.
Micromechanical Modeling of the Biaxial Deformation-Induced Phase Transformation in Polyethylene Terephthalate
Authors: Mamache Fateh Enouar , Mesbah Amar , Bian Hanbing , Zaïri Fahmi
Published: July 2022

In this paper, a micromechanics-based constitutive representation of the deformation-induced phase transformation in polyethylene terephthalate is proposed and verified under biaxial loading paths. The model, formulated within the Eshelby inclusion theory and the micromechanics framework, considers the material system as a two-phase medium, in which the active interactions between the continuous amorphous phase and the discrete newly formed crystalline domains are explicitly considered. The Duvaut–Lions viscoplastic approach is employed in order to introduce the rate-dependency of the yielding behavior. The model parameters are identified from uniaxial data in terms of stress–strain curves and crystallization kinetics at two different strain rates and two different temperatures above glass transition temperature. Then, it is shown that the model predictions are in good agreement with available experimental results under equal biaxial and constant width conditions. The role of the crystallization on the intrinsic properties is emphasized thanks to the model considering the different loading parameters in terms of mechanical path, strain rate and temperature.
Prediction of Long-Term Tensile Properties of Glass Fiber Reinforced Composites under Acid-Base and Salt Environments
Authors: Zhu Jihua , Deng Yangjian , Chen Piyu , Wang Gang , Min Hongguang , Fang Wujun
Published: July 2022

This study investigates the effects of deionized water, seawater, and solutions with various concentrations (5% and 10% by mass) of HCl and NaOH on the physical and mechanical properties of glass fiber reinforced polymers (GFRPs) through aging tests at 20 °C, 50 °C, and 80 °C. The tensile properties of GFRP were assessed by tensile testing at room temperature, and the strain during the tensile process was observed using digital image correlation. Additionally, the degradation mechanism was analyzed using scanning electron microscopy, and long-term tensile properties were predicted based on the Arrhenius model. The results indicated that the tensile strength of the GFRP decreased by 22%, 71%, and 87% after 56 d of exposure to 5% NaOH solutions at 20 °C, 50 °C, and 80 °C, respectively. The alkaline solutions had a more severe effect on the GFRP than deionized water, seawater, and acidic solutions. The experimental values and Arrhenius model predictions were found to be in good agreement with each other.
Design and Preparation of Localized Heat-Resistant Coating
Authors: Lin Zaiming , Chen Yihan , Ma Zhuang , Gao Lihong , Chen Wenhua , Chen Guohua , Ma Chen
Published: July 2022

Localized heat sources, such as flame guns and high-energy lasers, can cause severe damage to conventional materials. In this study, a novel localized heat-resistant coating with a high in-plane thermal conductivity was designed and prepared. Reduced graphene oxide (rGO) effectively improved the in-plane thermal conductivity of the polyvinyl alcohol (PVA) film, while maintaining the thermal insulation of the resin matrix in the through-plane direction. This characteristic of the rGO/PVA film was combined with the thermal insulation of boron-modified phenolic resin (BPF), and the prepared composite coating with two layers of rGO/PVA films effectively lowered the back-surface temperature in the flame ablation test from 151 to 107 °C. In addition, the area of the ablation-affected region of coating was increased to 103.6 cm2 from 31.9 cm2, indicating an excellent heat transfer performance. The layer-by-layer structure could realize the compatibility of high in-plane thermal conductivity and good through-plane thermal insulation. The synergy of these two different characteristics is demonstrated to be the key to improving the localized heat-resistant performance of the composite coating. This study effectively expands the application range of high-conductive film, and the obtained coating could act as a shield against butane flame, high energy lasers, and other localized heat.
Cadmium-Tolerant Bacteria in Cacao Farms from Antioquia, Colombia: Isolation, Characterization and Potential Use to Mitigate Cadmium Contamination
Authors: Quiroga-Mateus Ruth , López-Zuleta Santiago , Chávez Eduardo , Bravo Daniel
Published: July 2022

Bioremediation of farm soil is a technique that merits in-depth research. There are few studies related to the use of bioremediation to reduce cadmium (Cd) availability in soils used for cacao production. This study investigates (1) field bioprospection and strain characterization using techniques including isothermal microcalorimetry to select a group of cadmium-tolerant bacteria (CdtB) for potential use as bioremediators of cacao soils and (2) the application of bacterial inoculum to compare the immobilization of Cd under field conditions. Bioprospection was carried out in four cacao farms from the Antioquia district in Colombia. Culturable CdtB strains were isolated using CdCl2 as a Cd source and identified using molecular techniques. The metabolic characterization of Cd immobilization was carried out using isothermal microcalorimetry with CdCl2 amendments. Five cadmium-tolerant bacteria were isolated and characterized as Bacillus spp. The strain CdtB14 showed better growth and Cd immobilization ability (estimated through heat ratios) than any strain isolated thus far, suggesting potential for future use in bioproduct development. Furthermore, the application of two previously characterized CdtB strains with zeolite powder was performed in the same farms where the bioprospection process was carried out. The application of the preformulated inoculum resulted in a decrease of 0.30 + 0.1 mg kg−1 of soil Cd in two out of the four assessed farms. The field results are preliminary and require data on the change in Cd in cacao beans to understand what this result means for Cd mitigation. This study is the first to combine bioprospecting and the performance of CdtB in laboratory and field experiments in cacao farms and shows the potential of bioremediation to mitigate Cd contamination in cacao.
A Novel Step-by-Step Automated Heat Exchanger Network Retrofit Methodology Considering Different Heat Transfer Equipment
Authors: Xu Kexin , Qin Kang , Wu Hao , Smith Robin
Published: July 2022

Improving the energy efficiency in heat exchanger networks (HENs) remains a significant industrial problem, specifically in energy-intensive operations. A particular method for such an objective is the modification of HENs at the equipment-use level, where structural changes take place and units within the network are moved, replaced and/or removed. This practice is usually known as retrofit. The objective of a retrofit is to maximize the heat recovery using the minimum modifications possible and minimum retrofit cost. Traditional retrofit techniques would normally consider one type of heat exchanger (based on the original network) with no additional design features (i.e., heat transfer enhancement technologies). The expansion of such alternatives is limited by practical use and availability of theoretical methods. In this context, the inclusion of high-performance heat exchangers such as plate heat exchangers (PHEs) has not been widely explored, even when their design and operational advantages are known. In this work, a new step-by-step automated HENs retrofit approach based on Pinch Analysis is proposed. The approach is possible to identify the best modification, its location within the network, and its cost simultaneously. Moreover, to increase energy savings, this work presents a strategy that seeks to utilize high efficiency heat exchangers such as plate heat exchangers for retrofit. A distinctive feature of this new method is the ability to handle different minimum approach temperatures, given the different types of exchangers, within the optimization of HENs. Three cases are studied using this methodology to quantify the potential benefits of including PHEs in HEN retrofits, via the analysis of the retrofit cost. Results are compared with a baseline consisting in the same network, where only Shell-and-Tube-Heat-Exchangers (STHXs) are used. In addition, the results demonstrate that this methodology is flexible enough to be applied in a wide range of retrofit problems.
Influence of the Extraction Solvent and of the Altitude on the Anticancer Activity of Lebanese Eucalyptus camaldulensis Extract Alone or in Combination with Low Dose of Cisplatin in A549 Human Lung Adenocarcinoma Cells
Authors: Nasser Mohamad , Alyamani Amal A. , Daou Anis , Nasser Malak , Saad Zahraa , Hijazi Akram , Maresca Marc , Nasser Marc
Published: July 2022

Background: Lung cancer is the second most common cancer worldwide. Eucalyptus plant extract has been shown to have anti-neoplastic effects. We investigated the antitumor effect of ethanolic and aqueous extracts of Eucalyptus camaldulensis collected at different altitudes on A549. In addition, we evaluated the additive effect of its combination with low-dose cisplatin (CDDP). Methods: Qualitative and quantitative analyses of secondary metabolites present in the plants were carried out. The antioxidant and cytotoxic activities of the different extracts on A549 were evaluated using the 2.2-diphenyl-1-picrylhydrazyl radical scavenging activity and neutral red assay, respectively. The cytotoxic effect of the combination of certain extract concentrations with low-dose CDDP on A549 cells was studied. Results: In the Ethanoic extract, a higher number of active substances and antioxidant activities were observed. The four E. camaldulensis extracts showed cytotoxic activity on A549 cells, with a higher cytotoxicity for the Ethanoic extract and the sea-level altitude species. Moreover, the dual exposure of cells to both E. camaldulensis extracts and a low dose of Cisplatin showed an additional cytotoxic effect on A549 cells in certain concentrations. Conclusions: This study opens novel therapeutic options in combinational therapies of Eucalyptus camaldulensis with low-dose CDDP for the treatment of adenocarcinoma cells of human lungs.
A Step for the Valorization of Spent Yeast through Production of Iron–Peptide Complexes—A Process Optimization Study
Authors: Ferreira Carlos , Pereira Carla F. , Oliveira Ana Sofia , Faustino Margarida , Pereira Ana M. , Durão Joana , Pereira Joana Odila , Pintado Manuela E. , Carvalho Ana P.
Published: July 2022

Given the importance of iron in human nutrition and the significance of waste and by-product valorisation in a circular economy environment, we investigated the effects of protein and iron concentration on the production yield of iron–peptide complexes from spent Saccharomyces cerevisiae. For this purpose, different amounts of protein and iron were used in the complexation process. The results have shown that higher concentrations, although permitting a faster and larger scale process, provide a significantly lower complexation yield, which deems the process less feasible. This is corroborated by fluorescence analysis, which shows a lower degree of complexation with higher protein concentration. In addition, varying the concentration of iron does not change the quality of formed complexes, as evidenced by Fourier transform infrared spectroscopy (FT-IR) analysis. The morphology of all samples was also evaluated using scanning electron microscopy (SEM). Therefore, further studies are needed to optimize the process and to evaluate the best conditions for an economically sound valorization process for iron–peptide complexes. Nonetheless, current results in the development of a new process for the valorisation of spent yeast, in the form of iron-peptide complexes, look promising.
Time, Memoria, Creation: Receptions of Augustinism in the Philosophical Theology
Authors: Litvin Tatiana
Published: July 2022

The aim of the paper is to develop a thesis about the potential of phenomenology as a method for analyzing classical ancient texts. The article outlines the key issues of the doctrine of the time of Augustine and raises the question of the principles of phenomenological interpretation. Proceeding from the presentism approach, parallels are drawn between the philosophy of Augustine and the phenomenology of E. Husserl, the issue of duration and structure of the present is especially considered. The philosophy of Augustine includes both theological and epistemological conclusions.
From Mental Health Crisis to Existential Human Suffering: The Role of Self-Transcendence in Contemporary Mindfulness
Authors: Cueto de Souza Renata , Scott Charles
Published: July 2022

Our paper addresses the so-called college mental health crisis and the adoption of the strategy of mindfulness-based interventions. We offer a critique of their underlying medical–therapeutic paradigm by engaging the notion of self-transcendence in Viktor Frankl’s Existential Analysis and Buddhism in dialogue. We argue that the current mindfulness movement has decontextualized and appropriated mindfulness from its Buddhist foundations in favor of a model that offers objectively verifiable biophysical and mental benefits. Self-transcendence, whether from the perspective of Buddhism or Frankl’s work, offers what we feel is an existentially viable path forward for college students, in lieu of the current paradigm promoted by those advocating use of these mindfulness-based interventions. We conclude by considering Existential and Buddhist notions of self-transcendence in dialogue, suggesting they offer an educational practice worthy of implementation.
Extremism(s) and Their Fight against Modernity: The Case of Islamists and Eco-Radicals
Authors: Orofino Elisa
Published: July 2022

Extremism in both its vocal and violent forms is a core topic of research, as well as a priority issue standing at the top of national and international security agendas. While most of the literature is still focused on violent forms of extremism, an emerging research trend is looking at vocal extremism and radicalisation as crucial steps to understand, as Neumann said “what happens before the bomb goes off”. Within this new trend, scholars are interested in exploring the ideology of extremist groups (rather than just their methods) and the frames (schemata of interpretation) they disseminate in order to win more followers and fidelise their members. Based on the author’s previous research, as well as on relevant data extracted from the manifestos and relevant publications of emblematic groups of both ideologies, this paper compares Islamists and Eco-radicals as two forms of extremism fighting the Western-sponsored modernisation process. By exploring the meaning of “modernity”, as well as the role played by frames, this research sheds light on three common frames present in both ideologies, i.e., the enemy to fight, the victims to protect, and the change to achieve. These three frames are the linchpin of the discourses of both forms of extremism. By innovatively unpacking these frames from a comparative perspective, this research offers new insights into the impact of modernity on the development of alternative and extremist ideologies.
Accounting Beta as an Indicator of Risk Measurement: The Case of the Casablanca Stock Exchange
Authors: Faiteh Anouar , Aasri Mohammed Rachid
Published: July 2022

The problem of determining the cost of equity is crucial to the development of organizations. It is an essential means of calculating value creation. The financial literature has proposed several models for estimating the cost of equity, such as the capital asset pricing model (CAPM). However, this model is only used for listed companies, and cannot be used for unlisted companies. To remedy this situation, alternative measures of the cost of equity have emerged, such as accounting beta. The main objective of this research was to explore the relationship between market beta and accounting beta calculated using ROA, ROE and net income to demonstrate the ability of accounting beta to measure risk for unlisted companies. To carry out this study, we exploited data from a sample of 49 companies listed on the Casablanca Stock Exchange during the period of 2015–2019. We used panel data econometrics to empirically test the research hypotheses. The results show that the accounting beta calculated using ROA and ROE significantly represents the market beta and is a satisfactory solution to calculate the cost of equity of unlisted firms. The results of the study contribute to the existing literature on the cost of capital by reinforcing the role of accounting beta as a solution for determining the cost of equity and therefore the creation of value for the organization.
Investigating Suppression of Cloud Return with a Novel Optical Configuration of a Doppler Lidar
Authors: Jin Liqin , Mann Jakob , Sjöholm Mikael
Published: July 2022

The full-width at half-maximum or probe length of the Lorentzian weighting function of continuous-wave Doppler lidars increases quadratically with the focus distance, which results in a deterioration in the spatial resolution of measurements. What is worse, a Doppler lidar is susceptible to moving objects that are far away from the intended measurement point. Therefore, we suggest a novel configuration to mitigate these problems by deploying two co-planar quarter-wave plates with orthogonal fast axes in the conventional continuous-wave lidar system, without any change to the other optical or electronic components. If the vertically polarized laser beam that we emit goes out and its backscattered beam returns back through the same quarter-wave plate, the returned beam will become horizontally polarized. The horizontally polarized backscattered beam cannot beat with the vertically polarized local oscillator to generate a Doppler signal. However, the polarization of the returned beam will remain unchanged if the emitted beam travels out through one plate and returns through the other. In this way, the influence of a moving backscattering particle far away from the focus point can be reduced. Both theoretical and experimental results show that, in a proper configuration, the probe length of the continuous-wave lidar can be reduced by 10%, compared with that of the conventional lidar. In addition, the fat tails of the Lorentzian weighting function can be suppressed by up to 80% to reduce the return from a cloud, albeit with a large reduction (perhaps 90%) in the signal power. This investigation provides a potential method to increase the spatial resolution of Doppler wind lidars and suppress the low-hanging cloud return.
2D Phase-Based RFID Localization for On-Site Landslide Monitoring
Authors: Charléty Arthur , Le Breton Mathieu , Larose Eric , Baillet Laurent
Published: July 2022

Passive radio-frequency identification (RFID) was recently used to monitor landslide displacement at a high spatio-temporal resolution but only measured 1D displacement. This study demonstrates the tracking of 2D displacements, using an array of antennas connected to an RFID interrogator. Ten tags were deployed on a landslide for 12 months and 2D relative localization was performed using a phase-of-arrival approach. A period of landslide activity was monitored through RFID and displacements were confirmed by reference measurements. The tags showed displacements of up to 1.2 m over the monitored period. The centimeter-scale accuracy of the technique was confirmed experimentally and theoretically for horizontal localization by developing a measurement model that included antenna and tag positions, as well as multipath interference. This study confirms that 2D landslide displacement tracking with RFID is feasible at relatively low instrumental and maintenance cost.
Site Selection via Learning Graph Convolutional Neural Networks: A Case Study of Singapore
Authors: Lan Tian , Cheng Hao , Wang Yi , Wen Bihan
Published: July 2022

Selection of store sites is a common but challenging task in business practices. Picking the most desirable location for a future store is crucial for attracting customers and becoming profitable. The classic multi-criteria decision-making framework for store site selection oversimplifies the local characteristics that are both high dimensional and unstructured. Recent advances in deep learning enable more powerful data-driven approaches for site selection, many of which, however, overlook the interaction between different locations on the map. To better incorporate the spatial interaction patterns in understanding neighborhood characteristics and their impact on store placement, we propose to learn a graph convolutional network (GCN) for highly effective site selection tasks. Furthermore, we present a novel dataset that encompasses land use information as well as public transport networks in Singapore as a case study to benchmark site selection algorithms. It allows us to construct a geospatial GCN based on the public transport system to predict the attractiveness of different store sites within neighborhoods. We show that the proposed GCN model outperforms the competing methods that are learning from local geographical characteristics only. The proposed case study corroborates the geospatial interactions and offers new insights for solving various geographic and transport problems using graph neural networks.
PIIE-DSA-Net for 3D Semantic Segmentation of Urban Indoor and Outdoor Datasets
Authors: Gao Fengjiao , Yan Yiming , Lin Hemin , Shi Ruiyao
Published: July 2022

In this paper, a 3D semantic segmentation method is proposed, in which a novel feature extraction framework is introduced assembling point initial information embedding (PIIE) and dynamic self-attention (DSA)—named PIIE-DSA-net. Ideal segmentation accuracy is a challenging task, since the sparse, irregular and disordered structure of point cloud. Currently, taking into account both low-level features and deep features of the point cloud is the more reliable and widely used feature extraction method. Since the asymmetry between the length of the low-level features and deep features, most methods cannot reliably extract and fuse the features as expected and obtain ideal segmentation results. Our PIIE-DSA-net first introduced the PIIE module to maintain the low-level initial point-cloud position and RGB information (optional), and we combined them with deep features extracted by the PAConv backbone. Secondly, we proposed a DSA module by using a learnable weight transformation tensor to transform the combined PIIE features and following a self-attention structure. In this way, we obtain optimized fused low-level and deep features, which is more efficient for segmentation. Experiments show that our PIIE-DSA-net is ranked at least in the top seventh among the most recent published state-of-art methods on the indoor dataset and also made a great improvement than original PAConv on outdoor datasets.
An Advanced Echo Separation Scheme for Space-Time Waveform-Encoding SAR Based on Digital Beamforming and Blind Source Separation
Authors: Chang Sheng , Deng Yunkai , Zhang Yanyan , Wang Rongxiang , Qiu Jinsong , Wang Wei , Zhao Qingchao , Liu Dacheng
Published: July 2022

To achieve high-resolution and wide-swath (HRWS) imaging, a space-time waveform-encoding (STWE) spaceborne synthetic aperture radar (SAR) system is adopted. In rugged terrain, the beam-pointing mismatch problem will appear when the traditional digital beamforming (DBF) technique is used to separate the received echoes. This problem leads to decreasing the received echo’s gain, deteriorating the quality of the image product and making the interpretation of SAR image difficult. To address this problem, an advanced echo separation scheme for STWE spaceborne SAR based on the DBF and blind source separation (BSS) is put forward in this paper. In the scheme, the echoes are transmitted within the adjacent pulse repetition intervals to simulate multiple beams, and the scattered echoes are received by the sixteen-channel antennas in elevation simultaneously. In post-processing, a detailed flow is adopted. In the method, the DBF is firstly performed on received echoes. Due to the error caused by terrain undulation, the degree of echo separation is not enough. Then, the BSS is performed on the multiple echoes obtained after the DBF processing. Finally, the highly separated echo signal can be obtained. In this scheme, there is no need to perform the direction of arrival (DOA) estimation before the DBF processing, which saves valuable computing resources. In addition, to verify the proposed scheme, point target and distributed target simulations based on the 16-channel data of an elevation X-band DBF-SAR system are carried out. The results of point targets indicate that the residual echo caused by rough terrain can be reduced by more than 14 dB using the proposed scheme. The proposed scheme can be directly implemented into existing SAR systems; thus, it does not increase the complexity of the system design. The scheme has the potential to be applied to future spaceborne SAR missions.
A Deep Ensemble Neural Network with Attention Mechanisms for Lung Abnormality Classification Using Audio Inputs
Authors: Wall Conor , Zhang Li , Yu Yonghong , Kumar Akshi , Gao Rong
Published: July 2022

Medical audio classification for lung abnormality diagnosis is a challenging problem owing to comparatively unstructured audio signals present in the respiratory sound clips. To tackle such challenges, we propose an ensemble model by incorporating diverse deep neural networks with attention mechanisms for undertaking lung abnormality and COVID-19 diagnosis using respiratory, speech, and coughing audio inputs. Specifically, four base deep networks are proposed, which include attention-based Convolutional Recurrent Neural Network (A-CRNN), attention-based bidirectional Long Short-Term Memory (A-BiLSTM), attention-based bidirectional Gated Recurrent Unit (A-BiGRU), as well as Convolutional Neural Network (CNN). A Particle Swarm Optimization (PSO) algorithm is used to optimize the training parameters of each network. An ensemble mechanism is used to integrate the outputs of these base networks by averaging the probability predictions of each class. Evaluated using respiratory ICBHI, Coswara breathing, speech, and cough datasets, as well as a combination of ICBHI and Coswara breathing databases, our ensemble model and base networks achieve ICBHI scores ranging from 0.920 to 0.9766. Most importantly, the empirical results indicate that a positive COVID-19 diagnosis can be distinguished to a high degree from other more common respiratory diseases using audio recordings, based on the combined ICBHI and Coswara breathing datasets.
Multi-GNSS-Weighted Interpolated Tropospheric Delay to Improve Long-Baseline RTK Positioning
Authors: Mirmohammadian Farinaz , Asgari Jamal , Verhagen Sandra , Amiri-Simkooei Alireza
Published: July 2022

Until now, RTK (real-time kinematic) and NRTK (Network-based RTK) have been the most popular cm-level accurate positioning approaches based on Global Navigation Satellite System (GNSS) signals in real-time. The tropospheric delay is a major source of RTK errors, especially for medium and long baselines. This source of error is difficult to quantify due to its reliance on highly variable atmospheric humidity. In this paper, we use the NRTK approach to estimate double-differenced zenith tropospheric delays alongside ambiguities and positions based on a complete set of multi-GNSS data in a sample 6-station network in Europe. The ZTD files published by IGS were used to validate the estimated ZTDs. The results confirmed a good agreement, with an average Root Mean Squares Error (RMSE) of about 12 mm. Although multiplying the unknowns makes the mathematical model less reliable in correctly fixing integer ambiguities, adding a priori interpolated ZTD as quasi-observations can improve positioning accuracy and Integer Ambiguity Resolution (IAR) performance. In this work, weighted least-squares (WLS) were performed using the interpolation of ZTD values of near reference stations of the IGS network. When using a well-known Kriging interpolation, the weights depend on the semivariogram, and a higher network density is required to obtain the correct covariance function. Hence, we used a simple interpolation strategy, which minimized the impact of altitude variability within the network. Compared to standard RTK where ZTD is assumed to be unknown, this technique improves the positioning accuracy by about 50%. It also increased the success rate for IAR by nearly 1.
An Efficient and Privacy-Preserving Scheme for Disease Prediction in Modern Healthcare Systems
Authors: Padinjappurathu Gopalan Shynu , Chowdhary Chiranji Lal , Iwendi Celestine , Farid Muhammad Awais , Ramasamy Lakshmana Kumar
Published: July 2022

With the Internet of Things (IoT), mobile healthcare applications can now offer a variety of dimensionalities and online services. Disease Prediction Systems (DPS) increase the speed and accuracy of diagnosis, improving the quality of healthcare services. However, privacy is garnering an increasing amount of attention these days, especially concerning personal healthcare data, which are sensitive. There are a variety of prevailing privacy preservation techniques for disease prediction that are rendered. Nonetheless, there is a chance of medical users being affected by numerous disparate diseases. Therefore, it is vital to consider multi-label instances, which might decrease the accuracy. Thus, this paper proposes an efficient privacy-preserving (PP) scheme for patient healthcare data collected from IoT devices aimed at disease prediction in the modern Health Care System (HCS). The proposed system utilizes the Log of Round value-based Elliptic Curve Cryptography (LR-ECC) to enhance the security level during data transfer after the initial authentication phase. The authorized healthcare staff can securely download the patient data on the hospital side. Utilizing the Herding Genetic Algorithm-based Deep Learning Neural Network (EHGA-DLNN) can test these data with the trained system to predict the diseases. The experimental results demonstrate that the proposed approach improves prediction accuracy, privacy, and security compared to the existing methods.
Measuring Relative Wind Speeds in Stratospheric Balloons with Cup Anemometers: The TASEC-Lab Mission
Authors: Alfonso-Corcuera Daniel , Ogueta-Gutiérrez Mikel , Fernández-Soler Alejandro , González-Bárcena David , Pindado Santiago
Published: July 2022

This paper shows wind speed measurements from the TASEC-Lab experiment in a stratospheric balloon mission. The mission was launched in July 2021 from León (Spain) aerodrome. Measurements of horizontal wind speed in relation to the balloon gondola were successfully carried out with a cup anemometer. According to the available literature, this is the first time a cup anemometer has been used in a stratospheric balloon mission. The results indicate the need to consider the horizontal wind speed from the balloon ascent phase for thermal calculations of the mission.
An Effective Camera-to-Lidar Spatiotemporal Calibration Based on a Simple Calibration Target
Authors: Grammatikopoulos Lazaros , Papanagnou Anastasios , Venianakis Antonios , Kalisperakis Ilias , Stentoumis Christos
Published: July 2022

In this contribution, we present a simple and intuitive approach for estimating the exterior (geometrical) calibration of a Lidar instrument with respect to a camera as well as their synchronization shifting (temporal calibration) during data acquisition. For the geometrical calibration, the 3D rigid transformation of the camera system was estimated with respect to the Lidar frame on the basis of the establishment of 2D to 3D point correspondences. The 2D points were automatically extracted on images by exploiting an AprilTag fiducial marker, while the detection of the corresponding Lidar points was carried out by estimating the center of a custom-made retroreflective target. Both AprilTag and Lidar reflective targets were attached to a planar board (calibration object) following an easy-to-implement set-up, which yielded high accuracy in the determination of the center of the calibration target. After the geometrical calibration procedure, the temporal calibration was carried out by matching the position of the AprilTag to the corresponding Lidar target (after being projected onto the image frame), during the recording of a steadily moving calibration target. Our calibration framework was given as an open-source software implemented in the ROS platform. We have applied our method to the calibration of a four-camera mobile mapping system (MMS) with respect to an integrated Velodyne Lidar sensor and evaluated it against a state-of-the-art chessboard-based method. Although our method was a single-camera-to-Lidar calibration approach, the consecutive calibration of all four cameras with respect to the Lidar sensor yielded highly accurate results, which were exploited in a multi-camera texturing scheme of city point clouds.
Reconfigurable Security Architecture (RESA) Based on PUF for FPGA-Based IoT Devices
Authors: Babaei Armin , Schiele Gregor , Zohner Michael
Published: July 2022

Cybersecurity is a challenge in the utilization of IoT devices. One of the main security functions that we need for IoT devices is authentication. In this work, we used physical unclonable function (PUF) technology to propose a lightweight authentication protocol for IoT devices with long lifetimes. Our focus in this project is a solution for FPGA-based IoT devices. We evaluated the resiliency of our solution against state-of-the-art machine learning attacks.
Chlorine Concentration Modelling and Supervision in Water Distribution Systems
Authors: Pérez Ramon , Martínez-Torrents Albert , Martínez Manuel , Grau Sergi , Vinardell Laura , Tomàs Ricard , Martínez-Lladó Xavier , Jubany Irene
Published: July 2022

The quality of the drinking water distributed through the networks has become the main concern of most operators. This work focuses on one of the most important variables of the drinking water distribution networks (WDN) that use disinfection, chlorine. This powerful disinfectant must be dosed carefully in order to reduce disinfection byproducts (DBPs). The literature demonstrates researchers’ interest in modelling chlorine decay and using several different approaches. Nevertheless, the full-scale application of these models is far from being a reality in the supervision of water distribution networks. This paper combines the use of validated chlorine prediction models with an intensive study of a large amount of data and its influence on the model’s parameters. These parameters are estimated and validated using data coming from the Supervisory Control and Data Acquisition (SCADA) software, a full-scale water distribution system, and using off-line analytics. The result is a powerful methodology for calibrating a chlorine decay model on-line which coherently evolves over time along with the significant variables that influence it.
Comparative In Situ Study of Dynamic Load Generated by Gravel Piles Measured by a Fiber-Optic Interferometer
Authors: Stolárik Martin , Kepák Stanislav , Pinka Miroslav , Čubík Jakub , Nedoma Jan
Published: July 2022

Currently, all the technology used for seismic monitoring is based on sensors in the electrical domain. There are, however, other physical principles that may enable and fully replace existing devices in the future. This paper introduces one of these approaches, namely the field of fiber optics, which has great potential to be fully applied in the field of vibration measurement. The proposed solution uses a Michelson fiber-optic interferometer designed without polarization fading and with an operationally passive demodulation technique using three mutually phase-shifted optical outputs. Standard instrumentation commonly used in the field of seismic monitoring in geotechnical engineering was used as a reference. Comparative measurements were carried out during the implementation of gravel piles, which represents a significant source of vibration. For the correlation of the data obtained, the linear dependence previously verified in laboratory measurements was used. The presented results show that the correlation is also highly favorable (correlation coefficient in excess of 0.9) from the values measured in situ, with an average deviation for the oscillation velocity amplitude of the optical sensor not exceeding 0.0052.