bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on Strength, Water Stability, Shrinkage, and Microstructure of CFB Slag Modified Cement Stabilized Clay
Authors: Zhou Mingkai , Liu Xinyue , Chen Xiao , Gao Peng
Published: December 2021

Circulating fluidized bed slag (CFBS) is an industrial waste produced by coal combustion in power plants. To explore the application of CFB slag in cement-stabilized bases, this paper studies the influence of different dosage of CFBS on the mechanics, water stability, and shrinkage of cement-stabilized soil using laboratory experiments. The hydration activity and interface morphology of CFBS in cement-stabilized clay were observed using XRD and SEM. The improvement mechanism of CFBS on the performance of cement-stabilized clay was revealed. The results indicated that, compared with cement-stabilized clay, cement–CFBS-stabilized clay exhibited better mechanical and water stability, and significantly inhibited the shrinkage deformation of cement-stabilized clay. When the addition of CFBS was 70%, cement–CFBS-stabilized clay had the best mechanics and durability. Microscopic tests show that CFBS contains more active silicon aluminum oxide, which is easily dissolved and the hydration of which produces more gel products, so the mixture structure is denser, the strength is improved, and water does not easily evaporate; it has the characteristics of micro expansion which compensates for dry shrinkage deformation.
Early Prediction of DNN Activation Using Hierarchical Computations
Authors: Suresh Bharathwaj , Pillai Kamlesh , Kalsi Gurpreet Singh , Abuhatzera Avishaii , Subramoney Sreenivas
Published: December 2021

Deep Neural Networks (DNNs) have set state-of-the-art performance numbers in diverse fields of electronics (computer vision, voice recognition), biology, bioinformatics, etc. However, the process of learning (training) from the data and application of the learnt information (inference) process requires huge computational resources. Approximate computing is a common method to reduce computation cost, but it introduces loss in task accuracy, which limits their application. Using an inherent property of Rectified Linear Unit (ReLU), a popular activation function, we propose a mathematical model to perform MAC operation using reduced precision for predicting negative values early. We also propose a method to perform hierarchical computation to achieve the same results as IEEE754 full precision compute. Applying this method on ResNet50 and VGG16 shows that up to 80% of ReLU zeros (which is 50% of all ReLU outputs) can be predicted and detected early by using just 3 out of 23 mantissa bits. This method is equally applicable to other floating-point representations.
Influence of Polyunsaturated Fatty Acid Intake on Kidney Functions of Rats with Chronic Renal Failure
Authors: Muramatsu Hiroki , Akimoto Naoe , Hashimoto Michio , Sugibayashi Kenji , Katakura Masanori
Published: December 2021

Arachidonic acid (ARA), an omega-6 (ω-6) polyunsaturated fatty acid (PUFA), is involved in the development and maintenance of renal functions, whereas docosahexaenoic acid (DHA) is an omega-3 (ω-3) PUFA that has anti-inflammatory effects and attenuates nephropathy. However, their effects on the progression of chronic kidney disease (CKD) remain unknown. The aim of this study was to assess the effects of feeding ARA, DHA, and ARA and DHA-containing diets on rats with 5/6 nephrectomized kidneys. Urine and feces were collected every 4 weeks, and the kidneys were collected at 16 weeks after surgery. Urinary albumin (U-ALB) excretion increased gradually with nephrectomy, but the U-ALB excretion was attenuated by feeding the rats with an ARA + DHA-containing diet. Reactive oxygen species (ROS) levels in the kidneys were lower in the ARA + DHA group than in the other groups. At 4 weeks after surgery, the lipid peroxide (LPO) levels in the plasma of the ARA + DHA groups decreased significantly after surgery compared to the control CKD group, but this did not happen at 16 weeks post-surgery. There was a significant negative correlation between LPO levels in the plasma at 4 weeks and creatinine clearance, and a positive correlation with urinary albumin levels. These results suggest that the combination of ARA and DHA inhibit the progress of early stage CKD.
Eisenia bicyclis Extract Repairs UVB-Induced Skin Photoaging In Vitro and In Vivo: Photoprotective Effects
Authors: Choi Se-In , Han Hee-Soo , Kim Jae-Min , Park Geonha , Jang Young-Pyo , Shin Yu-Kyong , Ahn Hye-Shin , Lee Sun-Hee , Lee Kyung-Tae
Published: December 2021

Chronic exposure to ultraviolet B (UVB) is a major cause of skin aging. The aim of the present study was to determine the photoprotective effect of a 30% ethanol extract of Eisenia bicyclis (Kjellman) Setchell (EEB) against UVB-induced skin aging. By treating human dermal fibroblasts (Hs68) with EEB after UVB irradiation, we found that EEB had a cytoprotective effect. EEB treatment significantly decreased UVB-induced matrix metalloproteinase-1 (MMP-1) production by suppressing the activation of mitogen-activated protein kinase (MAPK)/activator protein 1 (AP-1) signaling and enhancing the protein expression of tissue inhibitors of metalloproteinases (TIMPs). EEB was also found to recover the UVB-induced degradation of pro-collagen by upregulating Smad signaling. Moreover, EEB increased the mRNA expression of filaggrin, involucrin, and loricrin in UVB-irradiated human epidermal keratinocytes (HaCaT). EEB decreased UVB-induced reactive oxygen species (ROS) generation by upregulating glutathione peroxidase 1 (GPx1) and heme oxygenase-1 (HO-1) expression via nuclear factor erythroid-2-related factor 2 (Nrf2) activation in Hs68 cells. In a UVB-induced HR-1 hairless mouse model, the oral administration of EEB mitigated photoaging lesions including wrinkle formation, skin thickness, and skin dryness by downregulating MMP-1 production and upregulating the expression of pro-collagen type I alpha 1 chain (pro-COL1A1). Collectively, our findings revealed that EEB prevents UVB-induced skin damage by regulating MMP-1 and pro-collagen type I production through MAPK/AP-1 and Smad pathways.
Association of ABO Blood Type with Bleeding Severity in Patients with Acute Gastroesophageal Variceal Bleeding
Authors: Lin Wei-Yu , Hong Ming-Yuan , Lin Chih-Hao , Chang Peng-Peng , Chu Shao-Chung , Kao Chia-Lung
Published: December 2021

Background and Objectives: ABO blood types have been implicated as potential risk factors for various hemorrhagic diseases. No study has investigated the association between gastroesophageal variceal bleeding and ABO blood types. We aimed to evaluate the impact of ABO blood types on mortality and bleeding risk in acute gastroesophageal variceal bleeding. Materials and Methods: This is a retrospective observational study. Patients presenting with acute gastroesophageal varices bleeding diagnosed by endoscopy were enrolled, and were divided by blood type into a type O group and non-type O group. The outcomes were death within 30 days and the proportion of further bleeding. We used generalized linear mixed-effects models to analyze the outcomes. Results: A total of 327 patients and 648 records of emergency room visits were included. The 30-day mortality was 14.8% (21 of 142 patients) in the type O group, and 16.2% (30 of 185 patients) in the non-type O group (p = 0.532). Further bleeding within 30 days occurred in 34 cases (12.6%) in the type O group, and in 26 cases (6.9%) in the non-type O group (p = 0.539). Conclusions: There was no significant difference in blood transfusion volume in 24 h, recurrent bleeding rates, or mortality between patients with blood type O and those with non-type O.
Monocyte-to-Lymphocyte Ratio as a Predictor of Worse Long-Term Survival after Off-Pump Surgical Revascularization-Initial Report
Authors: Urbanowicz Tomasz , Michalak Michał , Olasińska-Wiśniewska Anna , Witkowska Anna , Rodzki Michał , Błażejowska Ewelina , Gąsecka Aleksandra , Perek Bartłomiej , Jemielity Marek
Published: December 2021

Background and objective: Coronary artery disease is one of the leading causes of deaths nowadays and the trends in diagnosis and revascularization are still in plateau despite well-known factors. Simple whole blood count parameters may be used to measure inflammatory reactions that are involved in processes of atherosclerosis progression. The aim of our study was to analyse the association between simply available hematologic indices and long-term mortality following off-pump coronary artery bypass grafting (OPCAB). Material and Methods: The study group comprised 129 consecutive patients (16 females and 113 males, mean age 66 ± 6 years) who underwent surgical revascularization with off-pump technique between January 2014 and September 2019. The mean follow-up was 4.7 +/−1.9 years. A receiver operating characteristics curve was applied to estimate demographical and perioperative parameters including MLR for mortality. Results: Cox regression analysis revealed chronic pulmonary obstructive disease (HR = 2.86, 95%CI 1.05–7.78), MLR (HR = 3.81, 95%CI 1.45–10.06) and right coronary artery blood flow (HR = 1.06, 95%CI 1.00–1.10) as significant factors predicting increased mortality risk. In the presented model, the MLR > 1.44 on 1st postoperative day was a significant predictor of late mortality after the OPCAB procedure (HR = 3.82, 95%CI 1.45–10.06). Conclusions: Pronounced inflammatory reaction after off-pump surgery measured by MLR > 1.44 can be regarded as a worse long-term prognostic factor.
Influence of the Amount of Change in Quadriceps Tendon Young’s Modulus on Amount of Change in Walking Speed before and after Total Knee Arthroplasty
Authors: Ebihara Bungo , Mutsuzaki Hirotaka , Fukaya Takashi , Iwai Koichi
Published: December 2021

Background and Objectives: Walking speed after total knee arthroplasty (TKA) is an important outcome. However, the effect of quadriceps tendon stiffness on walking speed remains unclear. This study aimed to clarify the influence of the amount of change in quadriceps tendon stiffness on the degree of change in walking speed before and after TKA. Materials and Methods: Sixteen patients who underwent TKA for knee osteoarthritis participated in this study (median age: 74.0 years (interquartile range: 64.5–75.8)). Shear-wave elastography was deployed to measure quadriceps tendon stiffness using Young’s modulus. A motion analysis system was used to assess kinematic parameters and walking speed. Participants’ knee circumference, range of motion, extension strength, one-leg standing time, walking pain level, and activity level were measured preoperatively and one year after TKA, and changes in values were calculated. We used path analysis to clarify the influence of the amount of change in the quadriceps tendon Young’s modulus on the change in walking speed. Results: The quadriceps tendon Young’s modulus negatively affected the knee flexion angle during swing (standardized partial regression coefficients (β) = −0.513, p = 0.042). The knee flexion angle during swing positively affected step length (β = 0.586, p = 0.017). Step length positively affected cadence (β = 0.733, p = 0.001). Step length and cadence positively affected walking speed (β = 0.563, p < 0.001, β = 0.502, p < 0.001, respectively). Conclusions: The amount of change in the quadriceps tendon Young’s modulus may affect the degree of change in walking speed after TKA through the amount of change in the knee flexion angle during swing, step length, and cadence. Clinically, reducing quadriceps tendon stiffness can be addressed in rehabilitation programs to increase walking speed after TKA.
Microstructure and Mechanical Properties of Cast and Hot-Rolled Medium-Carbon Steels under Isothermal Heat-Treatment Conditions
Authors: Shin Byungsue , Kim Kwangyuk , Yi Sung , Choi Sanggyu , Hyun Soongkeun
Published: December 2021

In this study, the changes in the microstructure and mechanical properties during isothermal heat treatment of cast steel before and after hot deformation were investigated using medium-carbon steel with low alloy content. The microstructural characteristics of the cast and hot-rolled medium-carbon steel under isothermal heat-treatment conditions were examined using optical microscopy and scanning electron microscopy in conjunction with electron backscatter diffraction. The variation in the mechanical properties was evaluated using Rockwell hardness and tensile tests. After maintaining an austenitizing condition at 1200 °C for 30 min, an isothermal heat treatment was performed in the range 350–500 °C, followed by rapid cooling with water. Both the cast steel and hot-rolled steel did not completely transform into bainitic ferrite during isothermal heat treatment. The partially untransformed microstructure was a mixture of martensite and acicular ferrite. At 500 °C, the prior austenite phase changed to Widmanstätten ferrite and pearlite. At 450 °C, bainitic ferrite and cementite were coarsened by the coalescence of ferrite and subsequent diffusive growth. The mechanical properties increased as the isothermal heat-treatment temperature decreased, and the hardness of the cast steel was generally higher than that of the hot-rolled steel. Hardness and strength showed similar trends, and overall mechanical properties tend to decrease as the isothermal heat-treatment temperature increases, but there are slight differences depending on complex factors such as various phase fractions and grain size.
Ginsenoside Compound K Assisted G-Quadruplex Folding and Regulated G-Quadruplex-Containing Transcription
Authors: Zhang Yan , Qiu Zhidong , Zhu Ming , Teng Ye
Published: December 2021

Ginsenoside compound K (CK) is one of the major metabolites of the bioactive ingredients in Panax ginseng, which presents excellent bioactivity and regulates the expression of important proteins. In this work, the effects of CK on G-quadruplexes (G4s) were quantitatively analyzed in the presence and absence of their complementary sequences. CK was demonstrated to facilitate the formation of G4s, and increase the quantity of G4s in the competition with duplex. Thermodynamic experiments suggested that the electrostatic interactions were important for G4 stabilization by CK. CK was further found to regulate the transcription of G4-containing templates, reduce full-length transcripts, and decrease the transcription efficiency. Our results provide new evidence for the pharmacological study of ginsenosides at the gene level.
Effects of Sargassum thunbergii Extract on Skin Whitening and Anti-Wrinkling through Inhibition of TRP-1 and MMPs
Authors: Gam Da-Hye , Park Jae-Hyun , Hong Ji-Woo , Jeon Seong-Jin , Kim Jun-Hee , Kim Jin-Woo
Published: December 2021

Sargassum thunbergii has been traditionally used as an edible and medicinal material in oriental countries. However, the skin-whitening and anti-wrinkling effects of S. thunbergii have not yet been investigated. This study was conducted to establish optimal extraction conditions for the production of bioactive compounds with antioxidant activity as well as skin-whitening and anti-wrinkle effects using ultrasound-assisted extraction (UAE) in S. thunbergii. The extraction time (5.30~18.7 min), extraction temperature (22.4~79.6 °C), and ethanol concentration (0.0~99.5%), which are the main variables of the UAE, were optimized using a central composite design. Quadratic regression equations were derived based on experimental data and showed a high coefficient of determination (R2 > 0.85), demonstrating suitability for prediction. The optimal UAE condition for maximizing all dependent variables, including radical scavenging activity (RSA), tyrosinase inhibitory activity (TIA), and collagenase inhibitory activity (CIA), was identified as an extraction time of 12.0 min, an extraction temperature of 65.2 °C, and ethanol of 53.5%. Under these conditions, the RSA, TIA, and CIA of S. thunbergii extract were 86.5%, 88.3%, and 91.4%, respectively. We also confirmed S. thunbergii extract had inhibitory effects on the mRNA expression of tyrosinase-related protein-1, matrix metalloproteinase-1, and matrix metalloproteinase-9, which are the main genes of melanin synthesis and collagen hydrolysis. Liquid chromatography-tandem mass spectrometry was used to identify the main phenolic compounds in S. thunbergii extract, and caffeic acid was identified as a major peak, demonstrating that high value-added ingredients with skin-whitening and anti-wrinkling effects can be produced from S. thunbergii and used for developing cosmetic materials.
Antimicrobial Activity of a Vaginal Gel Formulation: Considerations Related to Vaginal Infection and Dysbiosis
Authors: De Seta Francesco , Larsen Bryan
Published: December 2021

Many non-prescription preparations intended to treat or alleviate symptoms of vaginal infection are available in American and European markets, but many have scant preclinical or clinical research underpinning. Respecta®Balance Gel (RBG) is marketed as an adjunct to probiotic treatment and its relevant antimicrobial properties were studied. Key findings with the manufacturer-supplied gel showed reduced turbidity in broth-dilution tests by 50% against Candida albicans and Candida glabrata at RBG concentrations 0.2–0.4% of neat product, respectively. A 50% reduction in turbidity of Escherichia coli, Streptococcus agalactiae, Enterococcus faecalis ranged from 1.6–2.2% and Gardnerella vaginalis was shown by flow cytometry counts to undergo a 50% reduction at 0.3% RBG. Propidium iodide staining indicated a rapid reduction of cell integrity of G. vaginalis almost immediately while after 4 h 45% of E. coli cells were stained. The lactic acid in BHI inhibited bacteria and yeast at concentrations ranging from 0.2–1.8% but inhibition was not solely due to pH since a 1:4 dilution of RBG resulted in a pH near neutral (6.75). Other findings showed biofilm accumulation assessed after 10-days exposure of Candida spp. to RBG and was reduced by an average of one-third (community strains) to one-half (drug-resistant strains). One excipient of the RBG, disodium EDTA, inhibited the growth of bacteria and yeast at concentrations below those present in RBG and may accentuate the activity of the host defense factor, lactoferrin. We conclude that RBG is a potent inhibitor of vaginal microorganisms relevant to vaginitis or intrapartum infections and contains excipients that may contribute to its antimicrobial activity.
Religiosity and Cooperation: The COVID-19 Pandemic in Slovenia
Authors: Smrke Marjan , Vovk Tina
Published: December 2021

We researched the COVID-19 pandemic as a give-some social dilemma. The success of solving the dilemma depends on an adequate proportion of cooperative actors. We were interested in the difference between how religious and non-religious Slovenian citizens reported their level of cooperation with government measures aimed at limiting the spread of the virus during the pandemic. Our research shows that during the first wave of the epidemic in Slovenia, religious citizens were slightly more cooperative than non-religious citizens. However, this statistically significant difference was not the consequence of religiosity per se. Regression analysis suggests that the observable difference was due to factors such as age, gender, concern about health, and trust in the ruling government. We explain the effect of these factors in light of the existing corpus of knowledge about social dilemmas.
Cough Sounds Recorded via Smart Devices as Useful Non-Invasive Digital Biomarkers of Aspiration Risk: A Case Report
Authors: Kang Hye-Seon , Lee Eung-Gu , Kim Cheol-Ki , Jung Andy , Song Catherine , Im Sun
Published: December 2021

Spirometer measurements can reflect cough strength but might not be routinely available for patients with severe neurological or medical conditions. A digital device that can record and help track abnormal cough sound changes serially in a noninvasive but reliable manner would be beneficial for monitoring such individuals. This report includes two cases of respiratory distress whose cough changes were monitored via assessments performed using recordings made with a digital device. The cough sounds were recorded using an iPad (Apple, Cupertino, CA, USA) through an embedded microphone. Cough sounds were recorded at the bedside, with no additional special equipment. The two patients were able to complete the recordings with no complications. The maximum root mean square values obtained from the cough sounds were significantly reduced when both cases were diagnosed with aspiration pneumonia. In contrast, higher values became apparent when the patients demonstrated a less severe status. Based on an analysis of our two cases, the patients’ cough sounds recorded with a commercial digital device show promise as potential digital biomarkers that may reflect aspiration risk related to attenuated cough force. Serial monitoring aided the decision making to resume oral feeding. Future studies should further explore the clinical utility of this technique.
Online Frequency Response Analysis of Electric Machinery through an Active Coupling System Based on Power Electronics
Authors: Sant’Ana Wilson Cesar , Lambert-Torres Germano , Bonaldi Erik Leandro , Gama Bruno Reno , Zacarias Tiago Goncalves , Areias Isac Antonio dos Santos , Arantes Daniel de Almeida , Assuncao Frederico de Oliveira , Campos Mateus Mendes , Steiner Fabio Monteiro
Published: December 2021

This paper presents an innovative concept for the online application of Frequency Response Analysis (FRA). FRA is a well known technique that is applied to detect damage in electric machinery. As an offline technique, the machine under testing has to be removed from service—which may cause loss of production. Experimental adaptations of FRA to online operation are usually based on the use of passive high pass coupling—which, ideally, should provide attenuation to the grid voltage, and at the same time, allow the high frequency FRA signals to be injected at the machine. In practice, however, the passive coupling results in a trade-off between the required attenuation and the useful area obtained at the FRA spectra. This paper proposes the use of an active coupling system, based on power electronics, in order to cancel the grid voltage at the terminals of FRA equipment and allow its safe connection to an energized machine. The paper presents the basic concepts of FRA and the issue of online measurements. It also presents basic concepts about power electronics converters and the operating principles of the Modular Multilevel Converter, which enables the generation of an output voltage with low THD, which is important for tracking the grid voltage with minimum error.
Joint Power and Subchannel Allocation for Distributed Storage in Cellular-D2D Underlays
Authors: Han Fengxia , Deng Hao , Shi Jianfeng , Jiang Hao
Published: December 2021

Wireless distributed storage is beneficial in the provision of reliable content storage and offloading of cellular traffic. In this paper, we consider a cellular device-to-device (D2D) underlay-based wireless distributed storage system, in which the minimum storage regenerating (MSR) coding combined with the partial downloading scheme is employed. To alleviate burdens on insufficient cellular resources and improve spectral efficiency in densely deployed networks, multiple storage devices can simultaneously use the same uplink cellular subchannel under the non-orthogonal multiple access (NOMA) protocol. Our objective is to minimize the total transmission power for content reconstruction, while guaranteeing the signal-to-interference-plus-noise ratio (SINR) constraints for cellular users by jointly optimizing power and subchannel allocation. To tackle the non-convex combinational program, we decouple the original problem into two subproblems and propose two low-complexity algorithms to efficiently solve them, followed by a joint optimization, implemented by alternately updating the solutions to each subproblem. The numerical results illustrate that our proposed algorithms are capable of performing an exhaustive search with lower computation complexity, and the NOMA-enhanced scheme provides more transmission opportunities for neighbor storage devices, thus significantly reducing the total power consumption.
A Holistic and Interoperable Approach towards the Implementation of Services for the Digital Transformation of Smart Cities: The Case of Vitoria-Gasteiz (Spain)
Authors: Larrinaga Félix , Pérez Alain , Aldalur Iñigo , Hernández José L. , Izkara José Luis , Sáez de Viteri Patxi
Published: December 2021

Cities in the 21st century play a major role in the sustainability and climate impact reduction challenges set by the European agenda. As the population of cities grows and their environmental impact becomes more evident, the European strategy aims to reduce greenhouse gas emissions—the main cause of climate change. Measures to reduce the impact of climate change include reducing energy consumption, improving mobility, harnessing resources and renewable energies, integrating nature-based solutions and efficiently managing infrastructure. The monitoring and control of all this activity is essential for its proper functioning. In this context, Information and Communication Technology (ICT) plays a key role in the digitisation, monitoring, and managing of these different verticals. Urban data platforms support cities on extracting Key Performance Indicators (KPI) in their efforts to make better decisions. Cities must be transformed by applying efficient urban planning measures and taking into account not only technological aspects, but also by applying a holistic vision in building solutions where citizens are at the centre. In addition, standardisation of platforms where applications are integrated as one is necessary. This requires interoperability between different verticals. This article presents the information platform developed for the city of Vitoria-Gasteiz in Spain. The platform is based on the UNE 178104 standard to provide a holistic architecture that integrates information from the different urban planning measures implemented in the city. The platform was constructed in the context of the SmartEnCity project following the urban transformation strategy established by the city. The article presents the value-added solutions implemented in the platform. These solutions have been developed by applying co-creation techniques in which stakeholders have been involved throughout the process. The platform proposes a step forward towards standardization, harmonises the integration of data from multiple vertical, provides interoperability between services, and simplifies scalability and replicability due to its microservice architecture.
Dance Tempo Estimation Using a Single Leg-Attached 3D Accelerometer
Authors: Stančin Sara , Tomažič Sašo
Published: December 2021

We present a methodology that enables dance tempo estimation through the acquisition of 3D accelerometer signals using a single wearable inertial device positioned on the dancer’s leg. Our tempo estimation method is based on enhanced multiple resonators, implemented with comb feedback filters. To validate the methodology, we focus on the versatile solo jazz dance style. Including a variety of dance moves, with different leg activation patterns and rhythmical variations, solo jazz provides for a highly critical validation environment. We consider 15 different solo jazz dance moves, with different leg activation patterns, assembled in a sequence of 5 repetitions of each, giving 65 moves altogether. A professional and a recreational dancer performed this assembly in a controlled environment, following eight dancing tempos, dictated by a metronome, and ranging from 80 bpm to 220 bpm with 20 bpm increment steps. We show that with appropriate enhancements and using single leg signals, the comb filter bank provides for accurate dance tempo estimates for all moves and rhythmical variations considered. Dance tempo estimates for the overall assembles match strongly the dictated tempo—the difference being at most 1 bpm for all measurement instances is within the limits of the established beat onset stability of the used metronome. Results further show that this accuracy is achievable for shorter dancing excerpts, comprising four dance moves, corresponding to one music phrase, and as such enables real-time feedback. By providing for a dancer’s tempo quality and consistency assessment, the presented methodology has the potential of supporting the learning process, classifying individual level of experience, and assessing overall performance. It is extendable to other dance styles and sport motion in general where cyclical patterns occur.
Sea Surface Temperature Analysis for Fengyun-3C Data Using Oriented Elliptic Correlation Scales
Authors: Liao Zhihong , Xu Bin , Gu Junxia , Shi Chunxiang
Published: December 2021

Sea surface temperature (SST) is critical for global climate change analysis and research. In this study, we used visible and infrared scanning radiometer (VIRR) sea surface temperature (SST) data from the Fengyun-3C (FY-3C) satellite for SST analysis, and applied the Kalman filtering methods with oriented elliptic correlation scales to construct SST fields. Firstly, the model for the oriented elliptic correlation scale was established for SST analysis. Secondly, observation errors from each type of SST data source were estimated using the optimal matched datasets, and background field errors were calculated using the model of oriented elliptic correlation scale. Finally, the blended SST analysis product was obtained using the Kalman filtering method, then the SST fields using the optimum interpolation (OI) method were chosen for comparison to validate results. The quality analysis for 2016 revealed that the Kalman analysis with a root-mean-square error (RMSE) of 0.3243 °C had better performance than did the OI analysis with a RMSE of 0.3911 °C, which was closer to the OISST product RMSE of 0.2897 °C. The results demonstrated that the Kalman filtering method with dynamic observation error and background error estimation was significantly superior to the OI method in SST analysis for FY-3C SST data.
Development of Wrist Interface Based on Fully Actuated Coaxial Spherical Parallel Mechanism for Force Interaction
Authors: Lee Jaeyong , Kim Hyungjoo , Yang Woosung
Published: December 2021

To develop a wrist robotic exoskeleton-type interface (REI) for force interaction, it should have a suitable range of motion similar to human wrist activities of daily living, large torque output performance, and low moving parts inertia for dynamic motion response to cover the human behavior frequency. In this paper, a wrist REI based on a fully actuated coaxial spherical parallel mechanism (CSPM) is proposed to satisfy the aforementioned features. The fully actuated CSPM-based wrist REI (FC-WREI) has the characteristics of pure rotation similar to the human wrist, high torque output by parallel torque synthesis, and low moving parts inertia due to the base arrangement of the actuators. Due to the mechanical advantages and design optimization, the FC-WREI maximally provides torque as much as 56.49–130.43% of the maximum isometric torque of the human wrist, while providing a consistent range of motion to the human wrist without interference problem. Moreover, it is confirmed that the inertia of the FC-WREI is up to 5.35 times lower than similar devices. These advantages of the FC-WREI mean that the device is applicable to various fields of REIs for force interaction.
A Survey of Recent Indoor Localization Scenarios and Methodologies
Authors: Yang Tian , Cabani Adnane , Chafouk Houcine
Published: December 2021

Recently, various novel scenarios have been studied for indoor localization. The trilateration is known as a classic theoretical model of geometric-based indoor localization, with uniform RSSI data that can be transferred directly into distance ranges. Then, a trilateration solution can be algebraically acquired from theses ranges, in order to fix user’s actual location. However, the collected RSSI or other measurement data should be further processed and classified to lower the localization error rate, instead of using the raw data influenced by multi-path effect, multiple nonlinear interference and noises. In this survey, a large number of existing techniques are presented for different indoor network structures and channel conditions, divided as LOS (light-of-sight) and NLOS (non light-of-sight). Besides, the input measurement data such as RSSI (received signal strength indication), TDOA (time difference of arrival), DOA (distance of arrival), and RTT (round trip time) are studied towards different application scenarios. The key localization techniques like RSSI-based fingerprinting technique are presented using supervised machine learning methods, namely SVM (support vector machine), KNN (K nearest neighbors) and NN (neural network) methods, especially in an offline training phase. Other unsupervised methods as isolation forest, k-means, and expectation maximization methods are utilized to further improve the localization accuracy in online testing phase. For Bayesian filtering methods, apart from the basic linear Kalman filter (LKF) methods, nonlinear stochastic filters such as extended KF, cubature KF, unscented KF and particle filters are introduced. These nonlinear methods are more suitable for dynamic localization models. In addition to the localization accuracy, the other important performance features and evaluation aspects are presented in our paper: scalability, stability, reliability, and the complexity of proposed algorithms is compared in this survey. Our paper provides a comprehensive perspective to compare the existing techniques and related practical localization models, with the aim of improving localization accuracy and reducing the complexity of the system.
On the Rollout of Network Slicing in Carrier Networks: A Technology Radar
Authors: Ordonez-Lucena Jose , Ameigeiras Pablo , Contreras Luis M. , Folgueira Jesús , López Diego R.
Published: December 2021

Network slicing is a powerful paradigm for network operators to support use cases with widely diverse requirements atop a common infrastructure. As 5G standards are completed, and commercial solutions mature, operators need to start thinking about how to integrate network slicing capabilities in their assets, so that customer-facing solutions can be made available in their portfolio. This integration is, however, not an easy task, due to the heterogeneity of assets that typically exist in carrier networks. In this regard, 5G commercial networks may consist of a number of domains, each with a different technological pace, and built out of products from multiple vendors, including legacy network devices and functions. These multi-technology, multi-vendor and brownfield features constitute a challenge for the operator, which is required to deploy and operate slices across all these domains in order to satisfy the end-to-end nature of the services hosted by these slices. In this context, the only realistic option for operators is to introduce slicing capabilities progressively, following a phased approach in their roll-out. The purpose of this paper is to precisely help designing this kind of plan, by means of a technology radar. The radar identifies a set of solutions enabling network slicing on the individual domains, and classifies these solutions into four rings, each corresponding to a different timeline: (i) as-is ring, covering today’s slicing solutions; (ii) deploy ring, corresponding to solutions available in the short term; (iii) test ring, considering medium-term solutions; and (iv) explore ring, with solutions expected in the long run. This classification is done based on the technical availability of the solutions, together with the foreseen market demands. The value of this radar lies in its ability to provide a complete view of the slicing landscape with one single snapshot, by linking solutions to information that operators may use for decision making in their individual go-to-market strategies.
Federated Reinforcement Learning Based AANs with LEO Satellites and UAVs
Authors: Yoo Seungho , Lee Woonghee
Published: December 2021

Supported by the advances in rocket technology, companies like SpaceX and Amazon competitively have entered the satellite Internet business. These companies said that they could provide Internet service sufficiently to users using their communication resources. However, the Internet service might not be provided in densely populated areas, as the satellites coverage is broad but its resource capacity is limited. To offload the traffic of the densely populated area, we present an adaptable aerial access network (AAN), composed of low-Earth orbit (LEO) satellites and federated reinforcement learning (FRL)-enabled unmanned aerial vehicles (UAVs). Using the proposed system, UAVs could operate with relatively low computation resources than centralized coverage management systems. Furthermore, by utilizing FRL, the system could continuously learn from various environments and perform better with the longer operation times. Based on our proposed design, we implemented FRL, constructed the UAV-aided AAN simulator, and evaluated the proposed system. Base on the evaluation result, we validated that the FRL enabled UAV-aided AAN could operate efficiently in densely populated areas where the satellites cannot provide sufficient Internet services, which improves network performances. In the evaluations, our proposed AAN system provided about 3.25 times more communication resources and had 5.1% lower latency than the satellite-only AAN.
CFNet: LiDAR-Camera Registration Using Calibration Flow Network
Authors: Lv Xudong , Wang Shuo , Ye Dong
Published: December 2021

As an essential procedure of data fusion, LiDAR-camera calibration is critical for autonomous vehicles and robot navigation. Most calibration methods require laborious manual work, complicated environmental settings, and specific calibration targets. The targetless methods are based on some complex optimization workflow, which is time-consuming and requires prior information. Convolutional neural networks (CNNs) can regress the six degrees of freedom (6-DOF) extrinsic parameters from raw LiDAR and image data. However, these CNN-based methods just learn the representations of the projected LiDAR and image and ignore the correspondences at different locations. The performances of these CNN-based methods are unsatisfactory and worse than those of non-CNN methods. In this paper, we propose a novel CNN-based LiDAR-camera extrinsic calibration algorithm named CFNet. We first decided that a correlation layer should be used to provide matching capabilities explicitly. Then, we innovatively defined calibration flow to illustrate the deviation of the initial projection from the ground truth. Instead of directly predicting the extrinsic parameters, we utilize CFNet to predict the calibration flow. The efficient Perspective-n-Point (EPnP) algorithm within the RANdom SAmple Consensus (RANSAC) scheme is applied to estimate the extrinsic parameters with 2D–3D correspondences constructed by the calibration flow. Due to its consideration of the geometric information, our proposed method performed better than the state-of-the-art CNN-based methods on the KITTI datasets. Furthermore, we also tested the flexibility of our approach on the KITTI360 datasets.
Swin-HSTPS: Research on Target Detection Algorithms for Multi-Source High-Resolution Remote Sensing Images
Authors: Fang Kun , Ouyang Jianquan , Hu Buwei
Published: December 2021

Traffic port stations are composed of buildings, infrastructure, and transportation vehicles. The target detection of traffic port stations in high-resolution remote sensing images needs to collect feature information of nearby small targets, comprehensively analyze and classify, and finally complete the traffic port station positioning. At present, deep learning methods based on convolutional neural networks have made great progress in single-target detection of high-resolution remote sensing images. How to show good adaptability to the recognition of multi-target complexes of high-resolution remote sensing images is a difficult point in the current remote sensing field. This paper constructs a novel high-resolution remote sensing image traffic port station detection model (Swin-HSTPS) to achieve high-resolution remote sensing image traffic port station detection (such as airports, ports) and improve the multi-target complex in high-resolution remote sensing images The recognition accuracy of high-resolution remote sensing images solves the problem of high-precision positioning by comprehensive analysis of the feature combination information of multiple small targets in high-resolution remote sensing images. The model combines the characteristics of the MixUp hybrid enhancement algorithm, and enhances the image feature information in the preprocessing stage. The PReLU activation function is added to the forward network of the Swin Transformer model network to construct a ResNet-like residual network and perform convolutional feature maps. Non-linear transformation strengthens the information interaction of each pixel block. This experiment evaluates the superiority of the model training by comparing the two indicators of average precision and average recall in the training phase. At the same time, in the prediction stage, the accuracy of the prediction target is measured by confidence. Experimental results show that the optimal average precision of the Swin-HSTPS reaches 85.3%, which is about 8% higher than the average precision of the Swin Transformer detection model. At the same time, the target prediction accuracy is also higher than the Swin Transformer detection model, which can accurately locate traffic port stations such as airports and ports in high-resolution remote sensing images. This model inherits the advantages of the Swin Transformer detection model, and is superior to mainstream models such as R-CNN and YOLOv5 in terms of the target prediction ability of high-resolution remote sensing image traffic port stations.
Integrated Pedal System for Data Driven Rehabilitation
Authors: Schaer Alessandro , Helander Oskar , Buffa Francesco , Müller Alexis , Schneider Kevin , Maurenbrecher Henrik , Becsek Barna , Chatzipirpiridis George , Ergeneman Olgac , Pané Salvador , Nelson Bradley J. , Schaffert Nina
Published: December 2021

We present a system capable of providing visual feedback for ergometer training, allowing detailed analysis and gamification. The presented solution can easily upgrade any existing ergometer device. The system consists of a set of pedals with embedded sensors, readout electronics and wireless communication modules and a tablet device for interaction with the users, which can be mounted on any ergometer, transforming it into a full analytical assessment tool with interactive training capabilities. The methods to capture the forces and moments applied to the pedal, as well as the pedal’s angular position, were validated using reference sensors and high-speed video capture systems. The mean-absolute error (MAE) for load is found to be 18.82 N, 25.35 N, 0.153 Nm for Fx, Fz and Mx respectively and the MAE for the pedal angle is 13.2°. A fully gamified experience of ergometer training has been demonstrated with the presented system to enhance the rehabilitation experience with audio visual feedback, based on measured cycling parameters.
A Novel Biosensor and Algorithm to Predict Vitamin D Status by Measuring Skin Impedance
Authors: Heo Jin-Chul , Kim Doyoon , An Hyunsoo , Son Chang-Sik , Cho Sangwoo , Lee Jong-Ha
Published: December 2021

The deficiency and excess of vitamin D cause various diseases, necessitating continuous management; but it is not easy to accurately measure the serum vitamin D level in the body using a non-invasive method. The aim of this study is to investigate the correlation between vitamin D levels, body information obtained by an InBody scan, and blood parameters obtained during health checkups, to determine the optimum frequency of vitamin D quantification in the skin and to propose a vitamin D measurement method based on impedance. We assessed body composition, arm impedance, and blood vitamin D concentrations to determine the correlation between each element using multiple machine learning analyses and an algorithm which predicted the concentration of vitamin D in the body using the impedance value developed. Body fat percentage obtained from the InBody device and blood parameters albumin and lactate dehydrogenase correlated with vitamin D level. An impedance measurement frequency of 21.1 Hz was reflected in the blood vitamin D concentration at optimum levels, and a confidence level of about 75% for vitamin D in the body was confirmed. These data demonstrate that the concentration of vitamin D in the body can be predicted using impedance measurement values. This method can be used for predicting and monitoring vitamin D-related diseases and may be incorporated in wearable health measurement devices.
Application Perspective on Cybersecurity Testbed for Industrial Control Systems
Authors: Pospisil Ondrej , Blazek Petr , Kuchar Karel , Fujdiak Radek , Misurec Jiri
Published: December 2021

In recent years, the Industry 4.0 paradigm has accelerated the digitalization process of the industry, and it slowly diminishes the line between information technologies (IT) and operational technologies (OT). Among the advantages, this brings up the convergence issue between IT and OT, especially in the cybersecurity-related topics, including new attack vectors, threats, security imperfections, and much more. This cause raised new topics for methods focused on protecting the industrial infrastructure, including monitoring and detection systems, which should help overcome these new challenges. However, those methods require high quality and a large number of datasets with different conditions to adapt to the specific systems effectively. Unfortunately, revealing field factory setups and infrastructure would be costly and challenging due to the privacy and sensitivity causes. From the lack of data emerges the new topic of industrial testbeds, including sub-real physical laboratory environments, virtual factories, honeynets, honeypots, and other areas, which helps to deliver sufficient datasets for mentioned research and development. This paper summarizes related works in the area of industrial testbeds. Moreover, it describes best practices and lessons learned for assembling physical, simulated, virtual, and hybrid testbeds. Additionally, a comparison of the essential parameters of those testbeds is presented. Finally, the findings and provided information reveal research and development challenges, which must be surpassed.
DCSST Multi-Modular Equalization Scheme Based on Distributed Control
Authors: Teng Fei , Kong Dezheng , Cui Zixuan , Qin Yuan , Hao Zhenghang , Rong Na , Chen Zhuo
Published: December 2021

As an important part of the DC micro-grid, DC solid-state transformers (DCSST) usually use a dual-loop control that combines the input equalization and output voltage loop. This strategy fails to ensure output equalization when the parameters of each dual active bridge (DAB) converter module are inconsistent, thus reducing the operational efficiency of the DCSST. To solve the above problems, a DCSST-balancing control strategy based on loop current suppression is presented. By fixing the phase-shifting angle within the bridge and adjusting the phase-shifting angle between bridges, the circulation current of each DAB converter module is reduced. Based on the double-loop control of the DAB, five controllers are nested outside each DAB submodule to achieve distributed control of the DCSST. The proposed control strategy can reduce the system circulation current with different circuit parameters of the submodules, ensure the balance of input voltage and output current of each submodule, and increase the robustness of the system. The simulation results verify the validity of the proposed method.