bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Conformation and Thermal Stability of Human Serum Albumin Corona of Ferrihydrite Nanoparticles
Authors: Chilom Claudia G. , Bălan Adriana , Sandu Nicoleta , Bălăşoiu Maria , Stolyar Sergey , Orelovich Oleg
Published: December 2020

In the last few years, a great amount of attention has been given to nanoparticles research due to their physicochemical properties that allow their use in analytical instruments or in promising imaging applications on biological systems. The use of ferrihydrite nanoparticles (Fh-NPs) in practical applications implies a particular control of their magnetic properties, stability, biocompatibility, interaction with the surface of the target, and low toxicity. In this study, the formation and organization of human serum albumin (HSA) molecules around the simple Fh-NPs and Fh-NPs doped with Co and Cu were examined by Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM) in terms of morphology and particle size. The topology of all Fh-NPs shows an organized area of HSA around each type of Fh-NP. Molecular docking studies were used in order to determine the probable location of the ferrihydrite in the HSA structure. The thermal stability of these nanohybrids was further investigated by fluorimetry, using 214-Trp residue from HSA as a spectral sensor. The denaturation temperature (Tm) was determined, and stabilization of the HSA structure in the presence of Fh-NPs was discussed. This study could be a starting point for the development of different applications targeting the structure and stability of Fh-NPs complexes with proteins.
Probiotics, Prebiotics and Synbiotics—A Promising Strategy in Prevention and Treatment of Cardiovascular Diseases?
Authors: Olas Beata
Published: December 2020

Recent evidence suggests that probiotics, prebiotics and synbiotics may serve as important dietary components in the prevention (especially) and treatment of cardiovascular diseases (CVD), but the recommendations for their use are often based on brief reports and small clinical studies. This review evaluates the current literature on the correlation between CVD and probiotics, prebiotics and synbiotics. Although research on probiotics, prebiotics and synbiotics has grown exponentially in recent years, particularly regarding the effect of probiotics on CVD, their mechanisms have not been clearly defined. It has been proposed that probiotics lower cholesterol levels, and may protect against CVD, by increasing bile salt synthesis and bile acid deconjugation. Similar effects have also been observed for prebiotics and synbiotics; however, probiotics also appear to have anti-oxidative, anti-platelet and anti-inflammatory properties. Importantly, probiotics not only have demonstrated effects in vitro and in animal models, but also in humans, where supplementation with probiotics decreases the risk factors of CVD. In addition, the properties of commercial probiotics, prebiotics and synbiotics remain undetermined, and further experimental research is needed before these substances can be used in the prevention and treatment of CVD. In particular, well-designed clinical trials are required to determine the influence of probiotics on trimethylamine-N-oxide (TMAO), which is believed to be a marker of CVDs, and to clarify the long-term effects, and action, of probiotic, prebiotic and synbiotic supplementation in combination with drug therapy (for example, aspirin). However, while it cannot be unequivocally stated whether such supplementation yields benefits in the prevention and treatment of CVDs, it is important to note that clinical studies performed to date have not identified any side-effects to use.
The Extraction Solvent Influences the Anti-Inflammatory Effects of Jakyakgamcho-Tang in Lipopolysaccharide-Stimulated Macrophages and Mice with Gouty Arthritis
Authors: Lee Yun Mi , Kim Dong-Seon
Published: December 2020

Jakyakgamcho-Tang (JGT) is a traditional medicine used to treat muscular tension, spasm, and pain. Several studies have reported its clinical use as an anti-inflammatory and in gynaecological treatment. This study aimed to compare the anti-inflammatory effects of JGT according to extraction solvent, water (JGTW) and 30% EtOH (JGTE) on lipopolysaccharide (LPS)—stimulated macrophages and in mice with monosodium urate (MSU)—induced gouty arthritis. We evaluated the production of inflammatory mediators and cytokines and the expression of inducible nitric oxide (iNOS) and cyclooxygenase-2 (COX-2) in RAW 264.7 cells. We also examined oedema, pain, and inflammation in MSU-induced mice by measuring affected hind paw swelling, weight-bearing, pro-inflammatory cytokines levels, and myeloperoxidase (MPO) activity. In LPS-stimulated RAW264.7 cells, JGTW and JGTE significantly decreased prostaglandin (PG) E2(PGE2) production via suppressing COX-2 expression and cytokines interleukin-1β and interleukin-6. Only JGTE reduced the production of NO and cytokines and the mRNA levels of iNOS and cytokines. In MSU-induced mice, JGTE and JGTW efficiently decreased paw swelling and attenuated joint pain. JGTE (200 and 300 mg/kg) effectively suppressed inflammation by downregulating pro-inflammatory cytokines (tumour necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6) and MPO activity, which were only slightly reduced by JGTW. Our data demonstrate the anti-inflammatory activity of JGT in macrophage and gouty arthritis animal models and show that JGTE is more effective than JGTW at lower concentrations.
Associations between the Complement System and Choroidal Neovascularization in Wet Age-Related Macular Degeneration
Authors: Jensen Emilie Grarup , Jakobsen Thomas Stax , Thiel Steffen , Askou Anne Louise , Corydon Thomas J.
Published: December 2020

Age-related macular degeneration (AMD) is the leading cause of blindness affecting the elderly in the Western world. The most severe form of AMD, wet AMD (wAMD), is characterized by choroidal neovascularization (CNV) and acute vision loss. The current treatment for these patients comprises monthly intravitreal injections of anti-vascular endothelial growth factor (VEGF) antibodies, but this treatment is expensive, uncomfortable for the patient, and only effective in some individuals. AMD is a complex disease that has strong associations with the complement system. All three initiating complement pathways may be relevant in CNV formation, but most evidence indicates a major role for the alternative pathway (AP) and for the terminal complement complex, as well as certain complement peptides generated upon complement activation. Since the complement system is associated with AMD and CNV, a complement inhibitor may be a therapeutic option for patients with wAMD. The aim of this review is to (i) reflect on the possible complement targets in the context of wAMD pathology, (ii) investigate the results of prior clinical trials with complement inhibitors for wAMD patients, and (iii) outline important considerations when developing a future strategy for the treatment of wAMD.
The Histamine 3 Receptor Is Expressed in the Heart and Its Activation Opposes Adverse Cardiac Remodeling in the Angiotensin II Mouse Model
Authors: McCaffrey Samuel L. , Lim Grace , Bullock Martyn , Kasparian Ainsley O. , Clifton-Bligh Roderick , Campbell William B. , Widiapradja Alexander , Levick Scott P.
Published: December 2020

Histamine is a basic amine stored in mast cells, with its release capable of activating one of four histamine receptors. The histamine 3 receptor (H3R) is known to be cardioprotective during acute ischemia by acting to limit norepinephrine release. However, a recent study reported that myofibroblasts isolated from the infarct zone of rat hearts responded to H3R activation by up-regulating collagen production. Thus, it is necessary to clarify the potential role of the H3R in relation to fibrosis in the heart. We identified that the mouse left ventricle (LV) expresses the H3R. Isolation of mouse cardiac fibroblasts determined that while angiotensin II (Ang II) increased levels of the H3R, these cells did not produce excess collagen in response to H3R activation. Using the Ang II mouse model of adverse cardiac remodeling, we found that while H3R blockade had little effect on cardiac fibrosis, activation of the H3R reduced cardiac fibrosis and macrophage infiltration. These findings suggest that when activated, the H3R is anti-inflammatory and anti-fibrotic in the mouse heart and may be a promising target for protecting against cardiac fibrosis.
ᶫ-Leucine Loading and Release in MIL-100 Nanoparticles
Authors: Gorban Ivan E. , Soldatov Mikhail A. , Butova Vera V. , Medvedev Pavel V. , Burachevskaya Olga A. , Belanova Anna , Zolotukhin Peter , Soldatov Alexander V.
Published: December 2020

Synthesis of the MIL-100 metal-organic framework particles was carried out by hydrothermal (HT) and microwave (MW)-assisted methods. Transmission electron microscopy showed formation of microparticles in the course of hydrothermal synthesis and nanoparticles for microwave-assisted synthesis. Powder X-ray diffraction confirmed formation of larger crystallites for hydrothermal synthesis. Particle aggregation in aqueous solution was observed by dynamic light scattering. However, the stability of both samples could be improved in acetic acid solution. Nitrogen sorption isotherms showed high porosity of the particles. ᶫ-leucine molecule was used as a model molecule for loading in the porous micro- and nanoparticles. Loading was estimated by FTIR spectroscopy and thermogravimetric analysis. UV-VIS spectroscopy quantified ᶫ-leucine release from the particles in aqueous solution. Cytotoxicity studies using the HeLa cell model showed that the original particles were somewhat toxic, but ᶫ-leucine loading ameliorated the toxic effects, likely due to signaling properties of the amino acid.
Clinical Application of Bone Marrow Mesenchymal Stem/Stromal Cells to Repair Skeletal Tissue
Authors: Arthur Agnieszka , Gronthos Stan
Published: December 2020

There has been an escalation in reports over the last decade examining the efficacy of bone marrow derived mesenchymal stem/stromal cells (BMSC) in bone tissue engineering and regenerative medicine-based applications. The multipotent differentiation potential, myelosupportive capacity, anti-inflammatory and immune-modulatory properties of BMSC underpins their versatile nature as therapeutic agents. This review addresses the current limitations and challenges of exogenous autologous and allogeneic BMSC based regenerative skeletal therapies in combination with bioactive molecules, cellular derivatives, genetic manipulation, biocompatible hydrogels, solid and composite scaffolds. The review highlights the current approaches and recent developments in utilizing endogenous BMSC activation or exogenous BMSC for the repair of long bone and vertebrae fractures due to osteoporosis or trauma. Current advances employing BMSC based therapies for bone regeneration of craniofacial defects is also discussed. Moreover, this review discusses the latest developments utilizing BMSC therapies in the preclinical and clinical settings, including the treatment of bone related diseases such as Osteogenesis Imperfecta.
An Examination of the Interaction of Democratic Ideals with Journalism Training Programmes in the Global South: The Case of Cambodia
Authors: Quinn Fergal
Published: December 2020

The presumption that a liberal media landscape and associated press culture strengthens good governance and human development has approached orthodoxy in the western world. Consistent with this, journalism training has been a central component of media aid strategies in the Global South. This research examines how normative assumptions about journalism roles can interact with ideas about democracy in a training environment and the possible implications of this. It explores parallels between programme elements relating to democracy facilitation and particular role conceptualisations of journalists trained by these programmes, with a specific interest in how this process is borne out in countries where democratisation processes are ongoing. A qualitative-based methodology, using journalism training in Cambodia as a case study, finds some correlations between democracy-related emphases at training level and specific normative orientations among working journalists who participated in these programmes. However, we find that these democratic norm-related orientations of practitioners contain subtle, but key differentiations from those advocated by programme facilitators. A vocational, advocacy-oriented approach to journalism programmes may have contributed to this outcome in a Cambodian context.
Machine Learning Methods for Quality Prediction in Production
Authors: Sankhye Sidharth , Hu Guiping
Published: December 2020

The rising popularity of smart factories and Industry 4.0 has made it possible to collect large amounts of data from production stages. Thus, supervised machine learning methods such as classification can viably predict product compliance quality using manufacturing data collected during production. Elimination of uncertainty via accurate prediction provides significant benefits at any stage in a supply chain. Thus, early knowledge of product batch quality can save costs associated with recalls, packaging, and transportation. While there has been thorough research on predicting the quality of specific manufacturing processes, the adoption of classification methods to predict the overall compliance of production batches has not been extensively investigated. This paper aims to design machine learning based classification methods for quality compliance and validate the models via case study of a multi-model appliance production line. The proposed classification model could achieve an accuracy of 0.99 and Cohen’s Kappa of 0.91 for the compliance quality of unit batches. Thus, the proposed method would enable implementation of a predictive model for compliance quality. The case study also highlights the importance of feature construction and dataset knowledge in training classification models.
Identification of Phenolic Compounds and Determination of Antioxidant Activity in Extracts and Infusions of Salvia Leaves
Authors: Francik Sławomir , Francik Renata , Sadowska Urszula , Bystrowska Beata , Zawiślak Agnieszka , Knapczyk Adrian , Nzeyimana Abdul
Published: December 2020

The influence of harvest period and drying method of Salvia officinalis L. leaves on the content of essential oils, polyphenols and antioxidant properties was investigated. Sage leaves were collected twice during plant blossoming (in June and July) and dried traditionally in natural conditions and at 35 °C. Antioxidant activity was assayed in methanol-acetone extracts and infusions of dried leaves with the use of free radical scavenging activity (DPPH) and ferric reducing antioxidant power (FRAP) technique. Total phenolic content in extracts as well as in infusions was determined by the means of Folin–Ciocalteu method. Based on the LC/MS analysis, the polyphenol compounds present in both extracts and in infusions were identified. The extracts contained more polyphenols and were characterized by higher antioxidant activity than infusions. In the extracts significant amount of ferulic acid was found, which was influenced both by the harvest period and drying method. The amount of ferulic acid found in extracts obtained from the June leaves dried traditionally was three times lower (6.185 μg/g DW) than in extracts from July leaves dried in the same conditions. Harvest period had a significant effect on the essential oils’ content, leaves collected in July contained 15% more oils than those collected in June.
Operational Modal Analysis, Testing and Modelling of Prefabricated Steel Modules with Different LSF Composite Walls
Authors: Rashidi Maria , Sharafi Pejman , Alembagheri Mohammad , Bigdeli Ali , Samali Bijan
Published: December 2020

The modal properties of modular structures, such as their natural frequencies, damping ratios and mode shapes, are different than those of conventional structures, mainly due to different structural systems being used for assembling prefabricated modular units onsite. To study the dynamic characteristics of modular systems and define a dynamic model, both the modal properties of the individual units and their connections need to be considered. This study is focused on the former aspect. A full-scale prefabricated volumetric steel module was experimentally tested using operational modal analysis technique under pure ambient vibrations and randomly generated artificial hammer impacts. It was tested in different situations: [a] bare (frame only) condition, and [b] infilled condition with different configurations of gypsum and cement-boards light-steel framed composite walls. The coupled module-wall system was instrumented with sensitive accelerometers, and its pure and free vibration responses were synchronously recorded through a data acquisition system. The main dynamic characteristics of the module were extracted using output-only algorithms, and the effects of the presence of infill wall panels and their material are discussed. Then, the module’s numerical micromodel for bare and infilled states is generated and calibrated against experimental results. Finally, an equivalent linear strut macro-model is proposed based on the calibrated data. The contribution of this study is assessing the effects of different infill wall materials on the dynamic characteristics of modular steel units, and proposing simple models for macro-analysis of infilled module assemblies.
The Pareto Tracer for General Inequality Constrained Multi-Objective Optimization Problems
Authors: Beltrán Fernanda , Cuate Oliver , Schütze Oliver
Published: December 2020

Problems where several incommensurable objectives have to be optimized concurrently arise in many engineering and financial applications. Continuation methods for the treatment of such multi-objective optimization methods (MOPs) are very efficient if all objectives are continuous since in that case one can expect that the solution set forms at least locally a manifold. Recently, the Pareto Tracer (PT) has been proposed, which is such a multi-objective continuation method. While the method works reliably for MOPs with box and equality constraints, no strategy has been proposed yet to adequately treat general inequalities, which we address in this work. We formulate the extension of the PT and present numerical results on some selected benchmark problems. The results indicate that the new method can indeed handle general MOPs, which greatly enhances its applicability.
Factors Affecting Quality of Work Life in a Sample of Cancer Survivor Female Nurses
Authors: Jin Ju Hyun , Lee Eun Ju
Published: December 2020

Background and objectives: Identifying the factors affecting the Quality of Work Life (QWL) of cancer survivor female nurses is important and necessary to overcome the various challenges experienced by these professionals upon returning to work following recovery from the disease. Therefore, this study aimed to identify the factors affecting the level of nurses’ QWL. Materials and Methods: A cross-sectional survey was conducted among 115 registered female nurses who had survived cancer, in general hospitals and clinics in South Korea. SPSS statistics version 21 was used for ordinary least squares, and Stata version 12.0 was used for quantile regression analysis. Results: Workplace spirituality affected all quantiles of QWL except the 90% quantile; fatigue was an affecting factor in the 20%, 30%, and 70% quantiles; and job stress in the 20%, 30%, 40%, and 60%, 70%, 80% quantiles. For workplace spirituality, the effect size was 0.33 (p < 0.001) in the 10% quantile, increasing to 0.45 (p < 0.001) in the 80% quantile. Conclusions: Based on the results of this study, suggestions for clinical practice include providing the mediating strategies and programs to manage fatigue and job stress as well as workplace spirituality. Job-related factors such as shift work should also be considered.
Tadalafil Treatment Ameliorates Hypoxia and Alters Placental Expression of Proteins Downstream of mTOR Signaling in Fetal Growth Restriction
Authors: Tsuchiya Kyoka , Tanaka Kayo , Tanaka Hiroaki , Maki Shintaro , Enomoto Naosuke , Takakura Sho , Nii Masafumi , Toriyabe Kuniaki , Katsuragi Shinji , Ikeda Tomoaki
Published: December 2020

Background and Objectives: Fetal growth restriction (FGR) is associated with fetal mortality and is a risk factor for cerebral palsy and future lifestyle-related diseases. Despite extensive research, no effective treatment strategy is available for FGR. Mammalian target of rapamycin (mTOR) signaling is important for the growth of fetal organs and its dysregulation is associated with miscarriage. Here, we focused on mTOR signaling and investigated how the activities of phospho-ribosomal protein S6 (rps6) and phospho-eukaryotic translation initiation factor 4E (eIF-4E), which act downstream of mTOR signaling in the human placenta, change following treatment of FGR with tadalafil and aimed to elucidate the underlying mechanism of action. Placental hypoxia was investigated by immunostaining for hypoxia-inducible factor (HIF)-2α. Materials and Methods: Phosphor-rps6 and phosphor-eIF4E expression were examined by Western blotting and enzyme-linked immunosorbent assay, respectively. Results: HIF-2α expression significantly increased in FGR placenta compared with that in the control placenta but decreased to control levels after tadalafil treatment. Levels of phospho-rps6 and phospho-eIF-4E were significantly higher in FGR placenta than in control placenta but decreased to control levels after tadalafil treatment. Conclusions: Tadalafil restored the levels of HIF-2α, phospho-rps6, and eIF-4E in FGR placenta to those observed in control placenta, suggesting that it could be a promising treatment strategy for FGR.
It May Be Possible to Prevent both Early and Late Relapses in Breast Cancer; Perhaps This Is an Opportunity for Sensors or Biosensors to Help
Authors: Retsky Michael
Published: December 2020

Data presented in 1993 showed an unexpected bimodal relapse pattern in surgically treated breast cancer [...]
Distance and Angle Correction System (DACS) for a kHz A-Scan Rate Pump-Probe Laser-Ultrasound Inspection
Authors: Canfield Ryan A. , Ahrens Jan , Bingham Jill , Fetzer Barry , Müller-Wirts Thomas , O’Donnell Matthew , Georgeson Gary , Pelivanov Ivan
Published: December 2020

Non-contact optical detection of ultrasound critically depends on the amount of light collected from the detection surface. Although it can be optimized in multiple ways for an ideal flat polished surface, industrial non-destructive testing and evaluation (NDT&E) usually requires optical detectors to be robust for unpolished material surfaces that are usually rough and curved. Confocal detectors provide the best light collection but must trade off sensitivity with depth of field. Specifically, detection efficiency increases with the numerical aperture (NA) of the detector, but the depth of field drops. Therefore, fast realignment of the detector focal point is critical for in-field applications. Here, we propose an optical distance and angle correction system (DACS) and demonstrate it in a kHz-rate laser-ultrasound inspection system. It incorporates a Sagnac interferometer on receive for the fast scanning of aircraft composites, which minimizes the required initial alignment. We show that DACS performs stably for different composite surfaces while providing ±2° angular and ±2 mm axial automatic correction with a maximum 100 ms realignment time.
Terahertz Spectroscopy of Gas Absorption Using the Superconducting Flux-Flow Oscillator as an Active Source and the Superconducting Integrated Receiver
Authors: Kinev Nickolay V. , Rudakov Kirill I. , Filippenko Lyudmila V. , Baryshev Andrey M. , Koshelets Valery P.
Published: December 2020

We report on the first implementation of a terahertz (THz) source based on a Josephson flux-flow oscillator (FFO) that radiates to open space. The excellent performance of this source and its maturity for practical applications has been demonstrated by the spectroscopy of gas absorption. To study the radiated power, we used a bolometric detection method and additionally calibrated the power by means of pumping the superconductor–insulator–superconductor (SIS) junction, integrated on a single chip with the FFO. For calibration, we developed a program using the SIS-detected power calculations in accordance with the Tien and Gordon model. The power emitted to open space is estimated to be from fractions of µW to several µW in the wide region from 0.25 THz up to 0.75 THz for different designs, with a maximum power of 3.3 µW at 0.34 THz. Next, we used a gas cell and a heterodyne superconducting integrated receiver to trace the absorption lines of water and ammonia with a spectral resolution better than 100 kHz. Our experiment for gas absorption is the first demonstration of the applicability of the FFO as an external active source for different tasks, such as THz spectroscopy, near-field THz imaging and microscopy.
Direct and Label-Free Determination of Human Glycated Hemoglobin Levels Using Bacteriorhodopsin as the Biosensor Transducer
Authors: Lin Ying-Chin , Lin Ching-Yu , Chen Hsiu-Mei , Kuo Li-Pin , Hsieh Cheng-En , Wang Xiang-He , Cheng Chih-Wen , Wu Chih-Yin , Chen Yi-Su
Published: December 2020

Glycated hemoglobin (HbA1c) levels are an important index for the diagnosis and long-term control of diabetes. This study is the first to use a direct and label-free photoelectric biosensor to determine HbA1c using bacteriorhodopsin-embedded purple membranes (PM) as a transducer. A biotinylated PM (b-PM) coated electrode that is layered with protein A-oriented antibodies against hemoglobin (Hb) readily captures non-glycated Hb (HbA0) and generates less photocurrent. The spectra of bacteriorhodopsin and Hb overlap so the photocurrent is reduced because of the partial absorption of the incident light by the captured Hb molecules. Two HbA0 and HbA1c aptasensors that are prepared by conjugating specific aptamers on b-PM coated electrodes single-step detect HbA0 and HbA1c in 15 min, without cross reactivity, with detection limits of ≤0.1 μg/mL and a dynamic range of 0.1–100 μg/mL. Both aptasensors exhibit high selectivity and long-term stability. For the clinical samples, HbA0 concentrations and HbA1c levels that are measured with aptasensors correlate well with total Hb concentrations and the HbA1c levels that are determined using standard methods (correlation gradient = 0.915 ± 0.004 and 0.981 ± 0.001, respectively). The use of these aptasensors for diabetes care is demonstrated.
Classification Algorithm for Person Identification and Gesture Recognition Based on Hand Gestures with Small Training Sets
Authors: Rzecki Krzysztof
Published: December 2020

Classification algorithms require training data initially labelled by classes to build a model and then to be able to classify the new data. The amount and diversity of training data affect the classification quality and usually the larger the training set, the better the accuracy of classification. In many applications only small amounts of training data are available. This article presents a new time series classification algorithm for problems with small training sets. The algorithm was tested on hand gesture recordings in tasks of person identification and gesture recognition. The algorithm provides significantly better classification accuracy than other machine learning algorithms. For 22 different hand gestures performed by 10 people and the training set size equal to 5 gesture execution records per class, the error rate for the newly proposed algorithm is from 37% to 75% lower than for the other compared algorithms. When the training set consists of only one sample per class the new algorithm reaches from 45% to 95% lower error rate. Conducted experiments indicate that the algorithm outperforms state-of-the-art methods in terms of classification accuracy in the problem of person identification and gesture recognition.
Research on High-Resolution Miniaturized MEMS Accelerometer Interface ASIC
Authors: Li Xiangyu , Zheng Yangong , Kong Xiangyan , Liu Yupeng , Tang Danling
Published: December 2020

High-precision microelectromechanical system (MEMS) accelerometers have wide application in the military and civil fields. The closed-loop microaccelerometer interface circuit with switched capacitor topology has a high signal-to-noise ratio, wide bandwidth, good linearity, and easy implementation in complementary metal oxide semiconductor (CMOS) process. Aiming at the urgent need for high-precision MEMS accelerometers in geophones, we carried out relevant research on high-performance closed-loop application specific integrated circuit (ASIC) chips. According to the characteristics of the performance parameters and output signal of MEMS accelerometers used in geophones, a high-precision closed-loop interface ASIC chip based on electrostatic time-multiplexing feedback technology and proportion integration differentiation (PID) feedback control technology was designed and implemented. The interface circuit consisted of a low-noise charge-sensitive amplifier (CSA), a sampling and holding circuit, and a PID feedback circuit. We analyzed and optimized the noise characteristics of the interface circuit and used a capacitance compensation array method to eliminate misalignment of the sensitive element. The correlated double sampling (CDS) technology was used to eliminate low-frequency noise and offset of the interface circuit. The layout design and engineering batch chip were fabricated by a standard 0.35 μm CMOS process. The active area of the chip was 3.2 mm × 3 mm. We tested the performance of the accelerometer system with the following conditions: power dissipation of 7.7 mW with a 5 V power supply and noise density less than 0.5 μg/Hz1/2. The accelerometers had a sensitivity of 1.2 V/g and an input range of ±1.2 g. The nonlinearity was 0.15%, and the bias instability was about 50 μg.
A General Grid-Less Design Method for Location and Pressure Sensors with High Precision
Authors: Zhu Xiaobo , Cheng Xiong , Zhang Weidong , Gao Jiale , Dai Yijie , Gu Wenhua
Published: December 2020

Bionic electronic skin can accurately sense and locate surface pressure, which is widely demanded in many fields. Traditional electronic skin design usually relies on grid-architecture sensor arrays, requiring complex grid and interconnection arrangements as well as high cost. Grid-less planar sensors can solve the problem by using electrodes only at the edges, but they usually require the use of mapping software such as electrical impedance tomography to achieve high precision. In this work, a design method of high-precision grid-less planar pressure sensors based on the back-propagation (BP) neural network is proposed. The measurement precision of this method is demonstrated to be over two orders of magnitude higher than that of a grid-structure sensor array with the same electrode distribution density. Moreover, this method can be used for irregularly-shaped and non-uniform sensors, which further reduces the manufacturing difficulty and increases the application flexibility.
Comparison of Low-Cost Particulate Matter Sensors for Indoor Air Monitoring during COVID-19 Lockdown
Authors: Kaliszewski Miron , Włodarski Maksymilian , Młyńczak Jarosław , Kopczyński Krzysztof
Published: December 2020

This study shows the results of air monitoring in high- and low-occupancy rooms using two combinations of sensors, AeroTrak8220(TSI)/OPC-N3 (AlphaSense, Great Notley, UK) and OPC-N3/PMS5003 (Plantower, Beijing, China), respectively. The tests were conducted in a flat in Warsaw during the restrictions imposed due to the COVID-19 lockdown. The results showed that OPC-N3 underestimates the PN (particle number concentration) by about 2–3 times compared to the AeroTrak8220. Subsequently, the OPC-N3 was compared with another low-cost sensor, the PMS5003. Both devices showed similar efficiency in PN estimation, whereas PM (particulate matter) concentration estimation differed significantly. Moreover, the relationship among the PM1–PM2.5–PM10 readings obtained with the PMS5003 appeared improbably linear regarding the natural indoor conditions. The correlation of PM concentrations obtained with the PMS5003 suggests an oversimplified calculation method of PM. The studies also demonstrated that PM1, PM2.5, and PM10 concentrations in the high- to low-occupancy rooms were about 3, 2, and 1.5 times, respectively. On the other hand, the use of an air purifier considerably reduced the PM concentrations to similar levels in both rooms. All the sensors showed that frying and toast-making were the major sources of particulate matter, about 10 times higher compared to average levels. Considerably lower particle levels were measured in the low-occupancy room.
Flow-Data Gathering Using NetFlow Sensors for Fitting Malicious-Traffic Detection Models
Authors: Campazas-Vega Adrián , Crespo-Martínez Ignacio Samuel , Guerrero-Higueras Ángel Manuel , Fernández-Llamas Camino
Published: December 2020

Advanced persistent threats (APTs) are a growing concern in cybersecurity. Many companies and governments have reported incidents related to these threats. Throughout the life cycle of an APT, one of the most commonly used techniques for gaining access is network attacks. Tools based on machine learning are effective in detecting these attacks. However, researchers usually have problems with finding suitable datasets for fitting their models. The problem is even harder when flow data are required. In this paper, we describe a framework to gather flow datasets using a NetFlow sensor. We also present the Docker-based framework for gathering netflow data (DOROTHEA), a Docker-based solution implementing the above framework. This tool aims to easily generate taggable network traffic to build suitable datasets for fitting classification models. In order to demonstrate that datasets gathered with DOROTHEA can be used for fitting classification models for malicious-traffic detection, several models were built using the model evaluator (MoEv), a general-purpose tool for training machine-learning algorithms. After carrying out the experiments, four models obtained detection rates higher than 93%, thus demonstrating the validity of the datasets gathered with the tool.
An Integrated Positioning and Attitude Determination System for Immersed Tunnel Elements: A Simulation Study
Authors: Li Guanqing , Klingbeil Lasse , Zimmermann Florian , Huang Shengxiang , Kuhlmann Heiner
Published: December 2020

Immersed tunnel elements need to be exactly controlled during their immersion process. Position and attitude of the element should be determined quickly and accurately to navigate the element from the holding area to the final location in the tunnel trench. In this paper, a newly-developed positioning and attitude determination system, integrating a 3-antenna Global Navigation Satellite System (GNSS) system, an inclinometer and a range-measurement system, is presented. The system is designed to provide the absolute position of both ends of the element with sufficient accuracy in real time. Special attention in the accuracy analysis is paid to the influence of GNSS multipath error and sound speed profile. Simulations are conducted to illustrate the performance of the system in different scenarios. If both elements are very close, the accuracies of the system are higher than 0.02 m in the directions perpendicular to and along the tunnel axis.
Histogram of Oriented Gradient-Based Fusion of Features for Human Action Recognition in Action Video Sequences
Authors: Patel Chirag I. , Labana Dileep , Pandya Sharnil , Modi Kirit , Ghayvat Hemant , Awais Muhammad
Published: December 2020

Human Action Recognition (HAR) is the classification of an action performed by a human. The goal of this study was to recognize human actions in action video sequences. We present a novel feature descriptor for HAR that involves multiple features and combining them using fusion technique. The major focus of the feature descriptor is to exploits the action dissimilarities. The key contribution of the proposed approach is to built robust features descriptor that can work for underlying video sequences and various classification models. To achieve the objective of the proposed work, HAR has been performed in the following manner. First, moving object detection and segmentation are performed from the background. The features are calculated using the histogram of oriented gradient (HOG) from a segmented moving object. To reduce the feature descriptor size, we take an averaging of the HOG features across non-overlapping video frames. For the frequency domain information we have calculated regional features from the Fourier hog. Moreover, we have also included the velocity and displacement of moving object. Finally, we use fusion technique to combine these features in the proposed work. After a feature descriptor is prepared, it is provided to the classifier. Here, we have used well-known classifiers such as artificial neural networks (ANNs), support vector machine (SVM), multiple kernel learning (MKL), Meta-cognitive Neural Network (McNN), and the late fusion methods. The main objective of the proposed approach is to prepare a robust feature descriptor and to show the diversity of our feature descriptor. Though we are using five different classifiers, our feature descriptor performs relatively well across the various classifiers. The proposed approach is performed and compared with the state-of-the-art methods for action recognition on two publicly available benchmark datasets (KTH and Weizmann) and for cross-validation on the UCF11 dataset, HMDB51 dataset, and UCF101 dataset. Results of the control experiments, such as a change in the SVM classifier and the effects of the second hidden layer in ANN, are also reported. The results demonstrate that the proposed method performs reasonably compared with the majority of existing state-of-the-art methods, including the convolutional neural network-based feature extractors.
SACT: A New Model of Covert Communication Based on SDN
Authors: Shi Leyi , Song Yuxiao , Xue Zhiyu , Liu Yihao , Chen Honglong
Published: December 2020

Anonymous tracking technology of network watermarking is limited by the deployment of tracking devices in traditional network structure, resulting in poor scalability and reusability. Software Defined Network (SDN) boasts more freedom thanks to its separation of the control plane from the data plane. In this paper, a new anonymous communication tracking model SDN-based Anonymous Communication Tracking (SACT) is proposed, which introduces network watermarking into SDN and combines IP time hidden channel and symbol expansion technology. In addition, we introduce a hopping protection mechanism to improve the anti detection ability of the watermark as well. The experimental results show that in a variety of simulated network environments, SACT achieves excellent detection rate and bit error rate, thus it is sufficient to determine the communication relationship between the two parties. Meanwhile, SACT solves the deployment problem of anonymous tracking and improves the availability and scalability of covert communication.
A Critical Review of Nonlinear Damping Identification in Structural Dynamics: Methods, Applications, and Challenges
Authors: Al-hababi Tareq , Cao Maosen , Saleh Bassiouny , Alkayem Nizar Faisal , Xu Hao
Published: December 2020

In recent decades, nonlinear damping identification (NDI) in structural dynamics has attracted wide research interests and intensive studies. Different NDI strategies, from conventional to more advanced, have been developed for a variety of structural types. With apparent advantages over classical linear methods, these strategies are able to quantify the nonlinear damping characteristics, providing powerful tools for the analysis and design of complex engineering structures. Since the current trend in many applications tends to more advanced and sophisticated applications, it is of great necessity to work on developing these methods to keep pace with this progress. Moreover, NDI can provide an effective and promising tool for structural damage detection purposes, where the changes in the dynamic features of structures can be correlated with damage levels. This review paper provides an overview of NDI methods by explaining the fundamental challenges and potentials of these methods based on the available literature. Furthermore, this research offers a comprehensive survey of different applications and future research trends of NDI. For potential development and application work for nonlinear damping methods, the anticipated results and recommendations of the current paper can assist researchers and developers worldwide to find out the gaps and unsolved issues in the field of NDI.
Sub-Canopy Topography Estimation from TanDEM-X DEM by Fusing ALOS-2 PARSAR-2 InSAR Coherence and GEDI Data
Authors: Tan Pengyuan , Zhu Jianjun , Fu Haiqiang , Wang Changcheng , Liu Zhiwei , Zhang Chen
Published: December 2020

This paper develops a framework for extracting sub-canopy topography from the TanDEM-X digital elevation model (DEM) by fusing ALOS-2 PARSAR-2 interferometric synthetic aperture radar (InSAR) coherence and Global Ecosystem Dynamics Investigation (GEDI) data. The main idea of this method is to estimate the forest height signals caused by the limited penetration of the X-band into the canopy from the TanDEM-X DEM. To achieve this goal, a spaceborne repeat-pass InSAR coherent scattering model is first used to estimate the forest height by the ALOS-2 PARSAR-2 InSAR coherence (APIC), taking the GEDI canopy height as the reference. Then, a linear regression model of the TanDEM-X DEM Vegetation Bias (TDVB) depending on the forest height and the fraction of vegetation cover (FVC) is established and used to estimate the sub-canopy topography. The proposed method was validated by the data of the Amazon rainforest and a boreal forest in Canada. The results showed that the proposed method extracted the sub-canopy topography at the study sites in the tropical forest and boreal forest with the root mean square error of 4.0 m and 6.33 m, respectively, and improved the TanDEM-X DEM accuracy by 75.7% and 39.7%, respectively.
Achieving 3D Beamforming by Non-Synchronous Microphone Array Measurements
Authors: Yu Liang , Guo Qixin , Chu Ning , Wang Rui
Published: December 2020

Beamforming technology is an essential method in acoustic imaging or reconstruction, which has been widely used in sound source localization and noise reduction. The beamforming algorithm can be described as all microphones in a plane simultaneously recording the source signal. The source position is then localized by maximizing the result of the beamformer. Evidence has shown that the accuracy of the sound source localization in a 2D plane can be improved by the non-synchronous measurements of moving the microphone array. In this paper, non-synchronous measurements are applied to 3D beamforming, in which the measurement array envelops the 3D sound source space to improve the resolution of the 3D space. The entire radiated object is covered better by a virtualized large or high-density microphone array, and the range of beamforming frequency is also expanded. The 3D imaging results are achieved in different ways: the conventional beamforming with a planar array, the non-synchronous measurements with orthogonal moving arrays, and the non-synchronous measurements with non-orthogonal moving arrays. The imaging results of the non-synchronous measurements are compared with the synchronous measurements and analyzed in detail. The number of microphones required for measurement is reduced compared with the synchronous measurement. The non-synchronous measurements with non-orthogonal moving arrays also have a good resolution in 3D source localization. The proposed approach is validated with a simulation and experiment.
Detecting Traces of 17α-Ethinylestradiol in Complex Water Matrices
Authors: Zagalo Paulo M , Ribeiro Paulo A , Raposo Maria
Published: December 2020

Hormones have a harmful impact on the environment and their detection in water bodies is an urgent matter. In this work, we present and analyze a sensor device able to detect traces of the synthetic hormone 17α-ethinylestradiol (EE2) below 10−9 M in media of different complexities, namely, ultrapure, mineral and tap waters. This device consists of solid supports with interdigitated electrodes without and with a polyethylenimine (PEI) and poly (sodium 4-styrenesulfonate) (PSS) layer-by-layer film deposited on it. Device response was evaluated through capacitance, loss tangent and electric modulus spectra and the data were analyzed by principal component analysis method. While the three types of spectra were demonstrated to be able to clearly discriminate the different media, loss tangent spectra allow for the detection of EE2 concentration, with a sensitivity of −0.072 ± 0.009 and −0.44 ± 0.03 per decade of concentration, for mineral and tap water, respectively. Detection limits values were found to be lower than the ones present in the literature and presenting values of 8.6 fM (2.6 pg/L) and of 7.5 fM (22.2 pg/L) for tap and mineral waters, respectively. Moreover, the obtained response values follow the same behavior with EE2 concentration in any medium, meaning that loss tangent spectra allow the quantification of EE2 concentration in aqueous complex matrices.
Developing a Solution for Mobility and Distribution Analysis Based on Bluetooth and Artificial Intelligence
Authors: Minea Marius , Dumitrescu Cătălin , Costea Ilona Mădălina , Chiva Ionuț Cosmin , Semenescu Augustin
Published: December 2020

The purpose of this research was to develop a simple, cost-effective, but enough efficient solution for locating, tracking and distribution analysis of people and/or vehicle flowing, based on non-intrusive Bluetooth sensing and selective filtering algorithms employing artificial intelligence components. The solution provides a tool for analyzing density of targets in a specific area, useful when checking contact proximities of a target along a route. The principle consists of the detection of mobile devices that use active Bluetooth connections, such as personal notebooks, smartphones, smartwatches, Bluetooth headphones, etc. to locate and track their movement in the dedicated area. For this purpose, a specific configuration of three BT sensors is used and RSSI levels compared, based on a combination of differential location estimates. The solution may also be suited for indoor localization where GPS signals are usually weak or missing; for example, in public places such as subway stations or trains, hospitals, airport terminals and so on. The applicability of this solution is estimated to be vast, ranging from travel and transport information services, route guidance, passenger flows tracking, and path recovery for persons suspected to have SARS-COV2 or other contagious viruses, serving epidemiologic enquiries. The specific configuration of Bluetooth detectors may be installed either in a fixed location, or in a public transport vehicle. A set of filters and algorithms for triangulation-based location of detected targets and movement tracking, based on artificial intelligence is employed. When applied in the public transport field, this setup can be also developed to extract additional information on traffic, such as private traffic flowing, or passenger movement patterns along the vehicle route, improved location in absence of GPS signals, etc. Field tests have been carried out for determining different aspects concerning indoor location accuracy, reliability, selection of targets and filtering. Results and possible applications are also presented in the final section of the paper.