bluuebunny/crossref_metadata_2025 huggingface dataset:
In Vitro Antithrombotic, Antitumor and Antiangiogenic Activities of Green Tea Polyphenols and Its Main Constituent Epigallocatechin-3-gallate
Authors: Luz Jefferson Romáryo Duarte da , López Jorge A. , Ferreira Macelia Pinheiro , de Sousa Rubiamara Mauricio , Silva Saulo Victor e , Almeida Maria das Graças , Araujo-Silva Gabriel
Published: December 2022

The balance between embolic risk and bleeding represents a clinical challenge in cancer patient treatment, encouraging studies on adjuvant oncologic treatments. Thereby, this study evaluated the in vitro effect of green tea extract (GTE) and epigallocatechin-3-gallate (EGCG) on hemostasis modulation and the antineoplastic effect on melanoma cells (B16-F10) by applying platelet aggregation, angiogenesis and viability cell assays. The results displayed a significant platelet antiaggregant effect, corresponding to 50 and 80% for the extract and EGCG, respectively, compared to the negative control. Furthermore, both GTE and EGCG exhibited antitumor effects by reducing melanoma cell growth by 25 and 50%, respectively, verified by cellular apoptosis. Regarding angiogenesis, these substances inhibited blood vessel formation, reaching about 25% and 99% for GTE and EGCG at 100 μg/mL, respectively. Moreover, TNF-α cell stimulation evidenced VEGF and IL-8 secretion inhibition at 55 and 20% with GTE, while EGCG promoted an inhibition around 78% for both VEGF and IL-8. The results indicate the promising performance of GTE and EGCG as an option for treating cancer and its side effects. Nonetheless, further studies are required to elucidate their action mechanism on clotting, cell death and angiogenesis.
Review of Latest Advances in Nature-Inspired Algorithms for Optimization of Activated Sludge Processes
Authors: Deepak Malini , Rustum Rabee
Published: December 2022

The activated sludge process (ASP) is the most widely used biological wastewater treatment system. Advances in research have led to the adoption of Artificial Intelligence (AI), in particular, Nature-Inspired Algorithm (NIA) techniques such as Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) to optimize treatment systems. This has aided in reducing the complexity and computational time of ASP modelling. This paper covers the latest NIAs used in ASP and discusses the advantages and limitations of each algorithm compared to more traditional algorithms that have been utilized over the last few decades. Algorithms were assessed based on whether they looked at real/ideal treatment plant (WWTP) data (and efficiency) and whether they outperformed the traditional algorithms in optimizing the ASP. While conventional algorithms such as Genetic Algorithms (GAs), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO) were found to be successfully employed in optimization techniques, newer algorithms such as Whale Optimization Algorithm (WOA), Bat Algorithm (BA), and Intensive Weed Optimization Algorithm (IWO) achieved similar results in the optimization of the ASP, while also having certain unique advantages.
Experimental Study on Fractal Characteristics of Adsorption Pore Structure of Coal
Authors: Wang Wendi , Liu Zhen , Zhang Mingrui , Yang He
Published: December 2022

The adsorption pore structure is the key affecting the technology of enhanced coal bed methane recovery (ECBM). In this paper, nitrogen adsorption measurement (NAM) and low-field nuclear magnetic resonance (NMR) methods are used to test the structural parameters of adsorption pores of four coal samples with different metamorphic degrees. Combining with the fractal theory, the applicability and the physical significance of fractal dimensions obtained from different models are analyzed. Finally, the main factors affecting the complexity of the pore size structure and the influence of fractal characteristics on the adsorption properties of coal are discussed. The results show that with the increase in the degree of metamorphism, the ranking order of the volume and the specific surface area of adsorption pores of four coal samples are long flame coal > anthracite > gas coal > coking coal. The fractal dimension D2 calculated by the Frenkel–Halsey–Hill (FHH) fractal model ranges from 2.5 to 2.9, representing the degree of the pore surface irregularity, and D3 calculated by the FHH fractal model ranges from 2.004 to 2.037, representing the complexity of pore size distribution. There is no clear quantitative relationship between the fractal dimension and the single structure parameters of adsorption pores. The more the pore diameter distribution is concentrated in the range of 2–5 nm, the larger the fractal dimension is, the higher the complexity of adsorption pore structure is; D2, which represents the irregularity of the surface of coal, has a good linear positive correlation with the maximum adsorption capacity of N2.
Prediction of the Consumption of Raw Materials and Fuels for the Blast Furnace
Authors: Pustějovská Pavlína , Bilík Jiří , Jursová Simona , Kardas Edyta , Konstanciak Anna
Published: December 2022

This article was conducted within the framework of project reg. no. CZ.11.4.120/0.0/0.0/16_013/0002594, programme, Interreg V-A Czech Republic-Poland, Microprojects Fund 2014–2020 in the Euroregion Silesia. It is focused in the area of modelling technological processes and the presentation of the main principles of these models. The modelling of technological processes is important in terms of its applicability to process prediction in industry. A complex of analytical and predictive metallurgical models was developed within VSB-TUO. The original mathematical model of coke degradation in a blast furnace makes it possible to calculate the minimum consumption of coke from the dynamic balance for different values of the ratio of direct and indirect reduction. As part of the graphic output, it determines the practically and theoretically achievable minimum coke consumption points. The use of the model enables the determination of a real reserve in reducing the amount of coke.
Screening of Azotobacter, Bacillus and Pseudomonas Species as Plant Growth-Promoting Bacteria
Authors: Minuț Mariana , Diaconu Mariana , Roșca Mihaela , Cozma Petronela , Bulgariu Laura , Gavrilescu Maria
Published: December 2022

In this study, bacteria from the genus of Azotobacter, Bacillus and Pseudomonas were isolated from the roots of Phaseolus vulgaris and used as plant growth-promoting bacteria for Sinapis alba L., Brassica napus L., Amaranthus retroflexus L., Linum usitatissimum L., Panicum miliaceum L. and Rumex patientia L. plants. The results showed that all three bacteria had different effects on plants growth considering both sterile and non-sterile soil. Bacillus sp. induced the greatest influence in terms of the root length of Sinapis alba L. grown in sterile soil (with 28%), while considering non-sterile soil, Pseudomonas sp. increased the root and shoot length by 11.43% and 25.15%, respectively, compared to the blank sample. Azotobacter sp. exerted the highest beneficial influence on Brassica napus L. growth in non-sterile soil, since the root and shoot lengths were stimulated with 27.64% and 52.60%, respectively, compared to uninoculated plants. Bacillus sp. had a positive effect on the growth of the shoot length of Amaranthus retroflexus L. (with 30.30% in sterile soil and 3.69% in non-sterile soil compared to the control). Azotobacter sp. stimulated the growth of the root length of Rumex patientia L. with 35.29% in sterile soil and also the shoot length of Panicum miliaceum L. in non-sterile soil by 20.51% compared to the control. Further, the roots and shoots of Linum usitatissimum L. grown in non-sterile soil and in the presence of Pseudomonas sp. increased by 178.38% and 15.08%, respectively, compared to the flax grown in sterile soil. Statistically, according to Tukey’s Honestly Significant Difference (HSD) test results, not all observed differences in plants grown with the selected bacteria are significantly different compared to the control.
Molecular Diagnosis of Osteoarticular Implant-Associated Infection: Available Techniques and How We Can Use Them
Authors: Salar-Vidal Llanos , Auñón Álvaro , Esteban Jaime
Published: December 2022

Despite recent advances during the last few years, microbiological diagnosis of prosthetic joint infections remains a challenge. Molecular biology techniques have been developed to try to overcome this problem, and recently, many of them have become available for many laboratories. Some of them, especially commercial multiplex PCR-based assays and universal 16S rDNA homemade PCR assays, are now available in many laboratories. Moreover, new technologies have appeared, especially metagenomics and next-generation sequencing. These techniques have demonstrated their potential in many studies but appear to be experimental at present. A few studies have evaluated the possible use of these methods in the clinical routine, and a review of the critical aspects for the selection of a molecular method (accuracy, complexity, cost) was performed. Finally, a proposal for a protocol that includes molecular biology techniques was made according to the literature published in this field. In conclusion, molecular biology techniques are ready to be used in the clinical routine of a microbiology laboratory, but their use must be carried out in accordance with the many special characteristics of each laboratory. In all cases, the interpretation of the results must be conducted by a multidisciplinary team with experience in the management of these patients.
Automated Pulsed Magnet System for Neutron Diffraction Experiments at the Materials and Life Science Experimental Facility in J-PARC
Authors: Watanabe Masao , Kihara Takumi , Nojiri Hiroyuki
Published: December 2022

A pulsed magnet system has been developed as a new user-friendly sample environment equipment at the Materials and Life Science Experimental Facility in Japan Proton Accelerator Research Complex. It comprises a vacuum chamber, a 4 K closed-cycle refrigerator for samples, and a nitrogen bath made of a stainless-steel tube with a miniature solenoidal coil. The coil is cooled by liquid nitrogen supplied by an automatic liquid nitrogen supply system, and the sample is cooled by a refrigerator. This combination facilitates the automatic high magnetic field diffraction measurement for the user’s operation. A relatively large scattering angle 2θ is up to 42°, which is significantly wider than the previous setup. Neutron diffraction experiments were performed on a multiferroic TbMnO3 and the field dependence of the diffraction peaks was clearly observed. The new pulsed magnet system was established for a practical high magnetic field diffraction for the user program.
Beyond Compassion Fatigue: Motive-Based Approaches to Sustaining Compassion in Palliative Care
Authors: Pierdziwol Annette
Published: December 2022

Compassionate care is vital to quality palliative care and integral to the provision of spiritual care at the end of life. But is sustaining compassion costly for healthcare providers (HCP), impacting their emotional and spiritual wellbeing, professional purpose, and moral self-image? Concerns about the costs of compassion for carers have gathered pace in a growing healthcare literature on compassion fatigue. Critics, however, argue that compassion fatigue lacks adequate conceptualisation, querying whether it fits with HCP’s own perceptions and suggesting it lacks utility for identifying interventions. This article contributes to this debate about moving beyond compassion fatigue, by bringing new psychological research on compassion as a motivated choice to bear on these questions and demonstrating its potential for illuminating interventions to support compassion in palliative care contexts. It proposes a focus on motive-based interventions which serve to tip the cost–benefit analysis in relation to compassion and thus support HCP motivation to feel and act compassionately. A key implication of this approach is that sustaining compassion is not up to individuals alone, as can often seem to be the case with ‘self-care’ paradigms. Rather, there are multiple ways institutions and society can play a role in motive-based interventions to sustain HCP compassion and wellbeing. The final section explores one example in the form of institutional support for spiritual care education.
Gender Trouble in the Early Lingbao Scriptures
Authors: Lu Jiefeng
Published: December 2022

The early Lingbao scriptures incorporate pluralistic gender discourses. On the one hand, the early Lingbao scriptures accept the social gender system of “differences between men and women” as the decision of all deities, and incorporate the “chastity” virtue of women advocated by Confucianism. The auspiciousness of giving birth to a boy and the masculine perspective of the Daoist discipline are not immune to correlative sexism. On the other hand, the early Lingbao scriptures actively borrow the Buddhist individualized gender, take the term “transforming a female into a male” as one of the “eight difficult situations” and the merit of worshipping the Daoist scriptures and illustrate the cultivated journey of women beyond gender in the stories of past actions, in an attempt to overcome the correlative sexism caused by the dominant gender system. The Dao unifies the concept of correlative gender and the concept of individualized gender, makes men and women equal objects of teachings, gives the perfected transcendent the freedom to choose gender, and integrates family ethics and individual transcendence with the images of a Daoist wife. The early Lingbao scriptures echo the Daoist principle of softness and femininity, use gender as an opportunity for Daoist cultivation, and explore possible ways to resolve gender trouble.
Large-Scale Land Deformation Monitoring over Southern California with Multi-Path SAR Data
Authors: Ao Meng , Wang Xiaotian , Sun Ying , Wang Fang , Zhang Huanan , Wei Lianhuan , Liu Shanjun , Yang Dong
Published: December 2022

Southern California, USA, has been suffering severe surface deformation due to its active crustal movement under the north–south compression of the Pacific Plate and North American Plate. Meanwhile, affected by groundwater extraction and recharge, oil exploitation, surface subsidence, uplift, and seasonal deformation occur commonly in this region. In this paper, multi-path SAR datasets were collected to investigate and monitor surface deformation in Southern California. The unified simultaneous least squares (USLS) approach is applied to remove the deformation discontinuity between adjacent SAR image paths. Multiple deformation patterns of structural faults, groundwater withdrawal, and oil exploitation are observed with the interferometric synthetic aperture radar (InSAR) technique. The InSAR-derived results were validated with GPS monitoring data. The correlations between land deformation and groundwater withdrawal, faults, and precipitation were intensively analyzed, finding out and mastering the magnitude and characteristics of ground deformation in Southern California.
New Structural Complexity Metrics for Forests from Single Terrestrial Lidar Scans
Authors: Batchelor Jonathan L. , Wilson Todd M. , Olsen Michael J. , Ripple William J.
Published: December 2022

We developed new measures of structural complexity using single point terrestrial laser scanning (TLS) point clouds. These metrics are depth, openness, and isovist. Depth is a three-dimensional, radial measure of the visible distance in all directions from plot center. Openness is the percent of scan pulses in the near-omnidirectional view without a return. Isovists are a measurement of the area visible from the scan location, a quantified measurement of the viewshed within the forest canopy. 243 scans were acquired in 27 forested stands in the Pacific Northwest region of the United States, in different ecoregions representing a broad gradient in structural complexity. All stands were designated natural areas with little to no human perturbations. We created “structural signatures” from depth and openness metrics that can be used to qualitatively visualize differences in forest structures and quantitively distinguish the structural composition of a forest at differing height strata. In most cases, the structural signatures of stands were effective at providing statistically significant metrics differentiating forests from various ecoregions and growth patterns. Isovists were less effective at differentiating between forested stands across multiple ecoregions, but they still quantify the ecological important metric of occlusion. These new metrics appear to capture the structural complexity of forests with a high level of precision and low observer bias and have great potential for quantifying structural change to forest ecosystems, quantifying effects of forest management activities, and describing habitat for organisms. Our measures of structure can be used to ground truth data obtained from aerial lidar to develop models estimating forest structure.
Siam-Sort: Multi-Target Tracking in Video SAR Based on Tracking by Detection and Siamese Network
Authors: Fang Hui , Liao Guisheng , Liu Yongjun , Zeng Cao
Published: December 2022

Shadows are widely used in the tracking of moving targets by video synthetic aperture radar (video SAR). However, they always appear in groups in video SAR images. In such cases, track effects produced by existing single-target tracking methods are no longer satisfactory. To this end, an effective way to obtain the capability of multiple target tracking (MTT) is in urgent demand. Note that tracking by detection (TBD) for MTT in optical images has achieved great success. However, TBD cannot be utilized in video SAR MTT directly. The reasons for this is that shadows of moving target are quite different from in video SAR image than optical images as they are time-varying and their pixel sizes are small. The aforementioned characteristics make shadows in video SAR images hard to detect in the process of TBD and lead to numerous matching errors in the data association process, which greatly affects the final tracking performance. Aiming at the above two problems, in this paper, we propose a multiple target tracking method based on TBD and the Siamese network. Specifically, to improve the detection accuracy, the multi-scale Faster-RCNN is first proposed to detect the shadows of moving targets. Meanwhile, dimension clusters are used to accelerate the convergence speed of the model in the training process as well as to obtain better network weights. Then, SiamNet is proposed for data association to reduce matching errors. Finally, we apply a Kalman filter to update the tracking results. The experimental results on two real video SAR datasets demonstrate that the proposed method outperforms other state-of-art methods, and the ablation experiment verifies the effectiveness of multi-scale Faster-RCNN and SimaNet.
Motion-Constrained GNSS/INS Integrated Navigation Method Based on BP Neural Network
Authors: Xu Ying , Wang Kun , Jiang Changhui , Li Zeyu , Yang Cheng , Liu Dun , Zhang Haiping
Published: December 2022

The global navigation satellite system (GNSS) and inertial navigation system (INS) integrated navigation system have been widely used in Intelligent Transportation Systems (ITSs). However, the positioning error of integrated navigation systems is rapidly divergent when GNSS outages occur. Motion constraint and back propagation (BP) neural networks can provide additional knowledge to solve this issue. However, the predictions of a neural network have outliers and motion constraint is difficult to adapt according to the motion states of vehicles and boats. Therefore, this paper fused a BP neural network with motion constraints, and proposed a motion-constrained GNSS/INS integrated navigation method based on a BP neural network (MC-BP method). The pseudo-measurement of the GNSS was predicted using a fitting model trained by the BP neural network. At the same time, the prediction outliers were detected and corrected using motion constraint. To assess the performance of the proposed method, simulated and real data experiments were conducted with a vehicle on land and a boat offshore. A classical GNSS/INS integration algorithm, a motion-constrained GNSS/INS algorithm, and the proposed method were compared through data processing. Compared with the classical GNSS/INS integration algorithm and the motion-constrained GNSS/INS algorithm, the positioning accuracies of the proposed method were improved by 90% and 64%, respectively, in the vehicle land experiment. Similar performances were found in the offshore boat experiment. Using the proposed MC-BP method, improved meter-level-positioning results can be achieved with the GNSS/INS integration algorithm when GNSS outages occur.
Monitoring the Spatio-Temporal Distribution of Ulva prolifera in the Yellow Sea (2020–2022) Based on Satellite Remote Sensing
Authors: Wang Zhuyi , Fan Bowen , Yu Dingfeng , Fan Yanguo , An Deyu , Pan Shunqi
Published: December 2022

The green tide caused by Ulva prolifera (U. prolifera) is becoming more severe as climate change and human activity accelerate, endangering tourism, aquaculture, and urban landscapes in coastal cities. In order to understand the spatio-temporal distribution of U. prolifera in response to the green tide disaster, this study used the Haiyang-1C (HY-1C) satellite accompanied by the Sentinel-2 and GaoFen-1 (GF-1) satellites to systematically monitor U. prolifera between 2020 and 2022. The consistency of U. prolifera distribution between the HY-1C and Sentinel-2 satellites, as well as the HY-1C and GF-1 satellites, was first investigated and the determination coefficients (R2) were 0.966 and 0.991, respectively, which supports the feasibility of China’s first ocean water color operational satellite, HY-1C, for U. prolifera monitoring. Therefore, the spatio-temporal distribution of U. prolifera is studied herein, along with the influence range, influence area, and drift paths. From 2020 to 2022, U. prolifera appeared in late May and lasted for 61, 88, and 73 days. Additionally, the in influence area continuously decreased in 2020 and 2022, while it generally increased and then decreased in 2021. It is an interesting phenomenon that when the maximum influence area occurred at the early stage of U. prolifera in both 2020 and 2022, the drift paths tended to move southward after traveling northward. The overall trend of the drift path in 2021 was to head northward. Thus, the study of the dynamic evolution, influence range, influence area, and drift paths of U. prolifera is helpful to promote the systematic development of emergency response mechanisms for U. prolifera.
Impact of BeiDou Observations on the Accuracy of Multi-GNSS PPP in a Function of Observing Session Duration within Europe—Analysis Based on Open-Source Software GAMP
Authors: Dawidowicz Karol , Bakuła Mieczysław
Published: December 2022

This study aims to verify whether the open-source software may provide Precise Point Positioning (PPP) with high accuracy. In this way, we address a question on the potential usability of open-source software for PPP analysis. On 31 July 2020, the full constellation of BeiDou satellites (SV) was announced. Over the European area, however, the number of visible BeiDou SVs is significantly smaller than in Asian-Pacific regions. Additionally, the system is in a modernization process, which may result in difficulties in utilizing its full potential. Ten days of multi-GNSS data were processed using the open-source software GAMP to determine how the accuracy of a derived three-dimensional PPP coordinates depends on observation session length and satellite systems used. The time series of position components of selected EUREF Permanent Network (EPN) stations generated from sub-daily (30 min and longer) solutions were analyzed. The obtained results prove that adding BeiDou observations, even in the case of using an incomplete constellation, leads to visible improvements, which can be observed both in the reduction of differences between estimated and true coordinates, as well as in the reduction of the standard deviation (SD). Improved accuracy caused by adding BeiDou data is especially noticeable for short observation sessions (in the range of 0.5 to 2.0 h) and in the case of a joint solution with GLONASS or Galileo observations. Finally, the open-source software GAMP proved to be a useful tool for multi-GNSS data processing and analysis.
Merging Microwave, Optical, and Reanalysis Data for 1 Km Daily Soil Moisture by Triple Collocation
Authors: Zhu Luyao , Li Wenjie , Wang Hongquan , Deng Xiaodong , Tong Cheng , He Shan , Wang Ke
Published: December 2022

High-spatiotemporal resolution soil moisture (SM) plays an essential role in optimized irrigation, agricultural droughts, and hydrometeorological model simulations. However, producing high-spatiotemporal seamless soil moisture products is challenging due to the inability of optical bands to penetrate clouds and the coarse spatiotemporal resolution of microwave and reanalysis products. To address these issues, this study proposed a framework for multi-source data merging based on the triple collocation (TC) method with an explicit physical mechanism, which was dedicated to generating seamless 1 km daily soil moisture products. Current merging techniques based on the TC method often lack seamless daily optical data input. To remedy this deficiency, our study performed a spatiotemporal reconstruction on MODIS LST and NDVI, and retrieved seamless daily optical soil moisture products. Then, the optical-derived sm1, microwave-retrieved sm2 (ESA CCI combined), and reanalysis sm3 (CLDAS) were matched by the cumulative distribution function (CDF) method to eliminate bias, and their weights were determined by the TC method. Finally, the least squares algorithm and the significance judgment were adopted to complete the merging. Although the CLDAS soil moisture presented anomalies over several stations, our proposed method can detect and reduce this impact by minimizing its weight, which shows the robustness of the method. This framework was implemented in the Naqu region, and the results showed that the merged products captured the temporal variability of the SM and depicted spatial information in detail; the validation with the in situ measurement obtained an average ubRMSE of 0.046 m³/m³. Additionally, this framework is transferrable to any area with measured sites for better agricultural and hydrological applications.
Attention-Based Matching Approach for Heterogeneous Remote Sensing Images
Authors: Hou Huitai , Lan Chaozhen , Xu Qing , Lv Liang , Xiong Xin , Yao Fushan , Wang Longhao
Published: December 2022

Heterogeneous images acquired from various platforms and sensors provide complementary information. However, to use that information in applications such as image fusion and change detection, accurate image matching is essential to further process and analyze these heterogeneous images, especially if they have significant differences in radiation and geometric characteristics. Therefore, matching heterogeneous remote sensing images is challenging. To address this issue, we propose a feature point matching method named Cross and Self Attentional Matcher (CSAM) based on Attention mechanisms (algorithms) that have been extensively used in various computer vision-based applications. Specifically, CSAM alternatively uses self-Attention and cross-Attention on the two matching images to exploit feature point location and context information. Then, the feature descriptor is further aggregated to assist CSAM in creating matching point pairs while removing the false matching points. To further improve the training efficiency of CSAM, this paper establishes a new training dataset of heterogeneous images, including 1,000,000 generated image pairs. Extensive experiments indicate that CSAM outperforms the existing feature extraction and matching methods, including SIFT, RIFT, CFOG, NNDR, FSC, GMS, OA-Net, and Superglue, attaining an average precision and processing time of 81.29% and 0.13 s. In addition to higher matching performance and computational efficiency, CSAM has better generalization ability for multimodal image matching and registration tasks.
Multi-Element UWB Probe Optimization for Medical Microwave Imaging
Authors: Akazzim Youness , El Mrabet Otman , Romeu Jordi , Jofre-Roca Luis
Published: December 2022

The need for non-ionizing techniques for medical imaging applications has led to the use of microwave signals. Several systems have been introduced in recent years based on increasing the number of antennas and frequency bandwidth to obtain high resolution and good accuracy in locating objects. A novel microwave imaging system that reduces the number of required antennas for precise target location appropriate for medical applications is presented. The proposed system consists of four UWB extended gap ridge horn (EGRH) antennas covering the frequency band from 0.5 GHz to 1.5 GHz mounted on a cylindrical phantom that mimics the brain in an orthogonal set of two EGRH probes. This configuration has the ability to control both the longitudinal and transversal dimensions of the reconstructed target’s image, rather than controlling the spatial resolution, by increasing the frequency band that can be easily affected by medium losses. The system is tested numerically and experimentally by the detection of a cylindrical target within a human brain model.
From Optical Tracking to Tactical Performance via Voronoi Diagrams: Team Formation and Players’ Roles Constrain Interpersonal Linkages in High-Level Football
Authors: Caldeira Nelson , Lopes Rui J. , Fernandes Dinis , Araujo Duarte
Published: December 2022

Football performance behaviour relies on the individual and collective perceptual attunement to the opportunities for action (affordances) available in a given competitive environment. Such perception–action coupling is constrained by players’ spatial dominance. Aiming to understand the influence of team formation and players’ roles in their dynamic interaction (interpersonal linkages), Voronoi diagrams were used to assess the differences in players’ spatial dominance resulting from their interactions according to ball-possession status in high-performance football. Notational (i.e., team formation, players’ role, and ball-possession status) and positional data (from optical sensors) from ten matches of the men’s French main football league were analysed. Voronoi diagrams were computed from players’ positional data for both teams. Probability density functions of the players’ Voronoi cell areas were then computed and compared, using the Kolmogorov–Smirnov test, for the different variables (i.e., team formation, player role, and ball-possession status) and their classes. For these variables, the players’ Voronoi cell areas presented statistical differences, which were sensitive to team formation classes (i.e., defenders, midfielders, and forwards) and relative pitch location (interior or exterior in the effective play space). Differences were also found between players with similar roles when in different team formations. Our results showed that team formation and players’ roles constrain their interpersonal linkages, resulting in different spatial dominance patterns. Using positional data captured by optical sensors, Voronoi diagrams can be computed into compound variables, which are meaningful for understanding the match and thus offer information to the design representative training tasks.
Inverted Microstrip Gap Waveguide Filtering Antenna Based on Coplanar EBG Resonators
Authors: Inclán-Sánchez Luis
Published: December 2022

A new simple design of an inverted microstrip Gap Waveguide filtering antenna integrated with two stopband filters is proposed in this work. In order to simultaneously provide filtering and radiating functions, we use the direct integration approach to cascade two periodic sets of coplanar coupled EBG resonators with a slot antenna. The analysis shows that the filters can be easily adjusted in the same feeding layer of the antenna, without extra circuitry and without modifying the lines. EBG-filters are compact and offer great flexibility in determining the frequency, width and selectivity of the rejected bands. Experimental results for an X-band filtering antenna prototype are provided showing a 7.3% transmission band centered at 10.2 GHz and a realized gain peak of 2.1 dBi. The measurements demonstrate the filtering capability of the proposed antenna, achieving rejection levels greater than 12 dB and 20 dB for the bands below and above the operation band. The proposed low-complexity design offers good performance as a filter and as an antenna, showing the essential advantages of the Gap Waveguide Technology, including low losses, self-packaging and limited cost. This work demonstrates the possibility of integrating the new coplanar EBG-filters into future Gap Waveguide antenna designs to avoid unwanted radiation, to reduce interfering signals or to provide high isolation in multiband systems.
Design and Development of a Broadband Vibration Energy Harvester Suitable for Tractor Exhaust Cylinder Vibration
Authors: Ma Xinxin , Zhou Tianshuo , Gong Lijiao , Zhang Xin , Yao Fuyuan , Wang Chujian
Published: December 2022

A large amount of vibration energy exists in the working environment of tractors. Therefore, the use of vibration energy harvesting technology to convert the vibration energy into electrical energy is a feasible way to supply power to low-power sensor equipment in agricultural machinery. Aiming at the problem in which the internal sensors of traditional tractors require built-in batteries or overlapping cables, this work proposes a broadband piezoelectric vibration energy harvester that could harvest the vibration energy from the tractor exhaust cylinder when the tractor is working. The vibration energy can be converted into electrical energy to power the air pressure sensor device. This experimental investigation shows that the energy harvester is composed of a folded piezoelectric energy harvester and a multi-source input synchronous electronic charge extraction circuit.The circuit has a high power density of 12,398 μW/(mm3·g2). Hence, it can convert vibration energy into a wide frequency range between 90–140 Hz and cause the air pressure sensor to operate.
Influence of Noise in Computer-Vision-Based Measurements on Parameter Identification in Structural Dynamics
Authors: Ostrowski Mariusz , Blachowski Bartlomiej , Mikułowski Grzegorz , Jankowski Łukasz
Published: December 2022

Nowadays, consumer electronics offer computer-vision-based (CV) measurements of dynamic displacements with some trade-offs between sampling frequency, resolution and low cost of the device. This study considers a consumer-grade smartphone camera based on complementary metal-oxide semiconductor (CMOS) technology and investigates the influence of its hardware limitations on the estimation of dynamic displacements, modal parameters and stiffness parameters of bolted connections in a laboratory structure. An algorithm that maximizes the zero-normalized cross-correlation function is employed to extract the dynamic displacements. The modal parameters are identified with the stochastic subspace identification method. The stiffness parameters are identified using a model-updating technique based on modal sensitivities. The results are compared with the corresponding data obtained with accelerometers and a laser distance sensor. The CV measurement allows lower-order vibration modes to be identified with a systematic (bias) error that is nearly proportional to the vibration frequency: from 2% for the first mode (9.4 Hz) to 10% for the third mode (71.4 Hz). However, the measurement errors introduced by the smartphone camera have a significantly lower influence on the values of the identified stiffness parameters than the numbers of modes and parameters taken into account. This is due to the bias–variance trade-off. The results show that consumer-grade electronics can be used as a low-cost and easy-to-use measurement tool if lower-order modes are required.
An Extended Review Concerning the Relevance of Deep Learning and Privacy Techniques for Data-Driven Soft Sensors
Authors: Bocu Razvan , Bocu Dorin , Iavich Maksim
Published: December 2022

The continuously increasing number of mobile devices actively being used in the world amounted to approximately 6.8 billion by 2022. Consequently, this implies a substantial increase in the amount of personal data collected, transported, processed, and stored. The authors of this paper designed and implemented an integrated personal health data management system, which considers data-driven software and hardware sensors, comprehensive data privacy techniques, and machine-learning-based algorithmic models. It was determined that there are very few relevant and complete surveys concerning this specific problem. Therefore, the current scientific research was considered, and this paper comprehensively analyzes the importance of deep learning techniques that are applied to the overall management of data collected by data-driven soft sensors. This survey considers aspects that are related to demographics, health and body parameters, and human activity and behaviour pattern detection. Additionally, the relatively complex problem of designing and implementing data privacy mechanisms, while ensuring efficient data access, is also discussed, and the relevant metrics are presented. The paper concludes by presenting the most important open research questions and challenges. The paper provides a comprehensive and thorough scientific literature survey, which is useful for any researcher or practitioner in the scope of data-driven soft sensors and privacy techniques, in relation to the relevant machine-learning-based models.
A Novel Method for Calibration of Digital Soil Images Captured under Irregular Lighting Conditions
Authors: Baek Sung-Ha , Park Ka-Hyun , Jeon Jun-Seo , Kwak Tae-Young
Published: December 2022

Soil color is commonly used as an indicator to classify soil and identify its properties. However, color-based soil assessments are susceptible to variations in light conditions and the subjectivity of visual evaluations. This study proposes a novel method of calibrating digital images of soil, regardless of lighting conditions, to ensure accurate identification. Two different color space models, RGB and CIELAB, were assessed in terms of their potential utility in calibrating changes to soil color in digital images. The latter system was determined to be suitable, as a result of its ability to accurately reflect illuminance and color temperature. Linear regression equations relating soil color and light conditions were developed based on digital images of four different types of soil samples, each photographed under 15 different light conditions. The proposed method can be applied to calibrate variations in the soil color obtained by digital images, thus allowing for more standardized, objective, and accurate classification and evaluation of soil based on its color.
Phase Nanoscopy with Correlated Frequency Combs
Authors: Zhu Xiaobing , Lenzner Matthias , Diels Jean-Claude
Published: December 2022

This study addresses any sensor based on measuring a physical quantity through the phase of a probing beam. This includes sensing of rotation, acceleration, index change, displacement, fields… While most phase measurements are made by detecting an amplitude change in interfering beams, we detect instead a phase change through a relative frequency shift of two correlated frequency combs. This paper explores the limit sensitivity that this method can achieve, when the combs are generated in an Optical Parametric Oscillator (OPO), pumped synchronously by a train of femtosecond pulses separated by half the OPO cavity round-trip time. It is shown that a phase difference as small as 0.4 nanoradians can be resolved between the two pulses circulating in the cavity. This phase difference is one order of magnitude better than the previous record. The root-mean-square deviation of the measured phase over measuring time is close to the standard quantum limit (phase-photon number uncertainty product of 0.66). Innovations that made such improved performances possible include a more stable OPO cavity design; a stabilization system with a novel purely electronic locking of the OPO cavity length relative to that of the pump laser; a shorter pump laser cavity; and a square pulse generator for driving a 0.5 mm pathlength lithium niobate phase modulator. Future data acquisition improvements are suggested that will bring the phase sensitivity exactly to the standard quantum limit, and beyond the quantum limit by squeezing.
Low Complexity Radar Gesture Recognition Using Synthetic Training Data
Authors: Zhao Yanhua , Sark Vladica , Krstic Milos , Grass Eckhard
Published: December 2022

Developments in radio detection and ranging (radar) technology have made hand gesture recognition feasible. In heat map-based gesture recognition, feature images have a large size and require complex neural networks to extract information. Machine learning methods typically require large amounts of data and collecting hand gestures with radar is time- and energy-consuming. Therefore, a low computational complexity algorithm for hand gesture recognition based on a frequency-modulated continuous-wave (FMCW) radar and a synthetic hand gesture feature generator are proposed. In the low computational complexity algorithm, two-dimensional Fast Fourier Transform is implemented on the radar raw data to generate a range-Doppler matrix. After that, background modelling is applied to separate the dynamic object and the static background. Then a bin with the highest magnitude in the range-Doppler matrix is selected to locate the target and obtain its range and velocity. The bins at this location along the dimension of the antenna can be utilised to calculate the angle of the target using Fourier beam steering. In the synthetic generator, the Blender software is used to generate different hand gestures and trajectories and then the range, velocity and angle of targets are extracted directly from the trajectory. The experimental results demonstrate that the average recognition accuracy of the model on the test set can reach 89.13% when the synthetic data are used as the training set and the real data are used as the test set. This indicates that the generation of synthetic data can make a meaningful contribution in the pre-training phase.
A Rapid Prototyping Method for Sub-MHz Single-Element Piezoelectric Transducers by Using 3D-Printed Components
Authors: Kim Jinwook , Menichella Bryce , Lee Hanjoo , Dayton Paul A. , Pinton Gianmarco F.
Published: December 2022

We present a rapid prototyping method for sub-megahertz single-element piezoelectric transducers by using 3D-printed components. In most of the early research phases of applying new sonication ideas, the prototyping quickness is prioritized over the final packaging quality, since the quickness of preliminary demonstration is crucial for promptly determining specific aims and feasible research approaches. We aim to develop a rapid prototyping method for functional ultrasonic transducers to overcome the current long lead time (>a few weeks). Here, we used 3D-printed external housing parts considering a single matching layer and either air backing or epoxy-composite backing (acoustic impedance > 5 MRayl). By molding a single matching layer on the top surface of a piezoceramic in a 3D-printed housing, an entire packaging time was significantly reduced (<26 h) compared to the conventional methods with grinding, stacking, and bonding. We demonstrated this prototyping method for 590-kHz single-element, rectangular-aperture transducers for moderate pressure amplitudes (mechanical index > 1) at focus with temporal pulse controllability (maximum amplitude by <5-cycle burst). We adopted an air-backing design (Type A) for efficient pressure outputs, and bandwidth improvement was tested by a tungsten-composite-backing (Type B) design. The acoustic characterization results showed that the type A prototype provided 3.3 kPa/Vpp far-field transmitting sensitivity with 25.3% fractional bandwidth whereas the type B transducer showed 2.1 kPa/Vpp transmitting sensitivity with 43.3% fractional bandwidth. As this method provided discernable quickness and cost efficiency, this detailed rapid prototyping guideline can be useful for early-phase sonication projects, such as multi-element therapeutic ultrasound array and micro/nanomedicine testing benchtop device prototyping.
How Do Autonomous Vehicles Decide?
Authors: Malik Sumbal , Khan Manzoor Ahmed , El-Sayed Hesham , Khan Jalal , Ullah Obaid
Published: December 2022

The advancement in sensor technologies, mobile network technologies, and artificial intelligence has pushed the boundaries of different verticals, e.g., eHealth and autonomous driving. Statistics show that more than one million people are killed in traffic accidents yearly, where the vast majority of the accidents are caused by human negligence. Higher-level autonomous driving has great potential to enhance road safety and traffic efficiency. One of the most crucial links to building an autonomous system is the task of decision-making. The ability of a vehicle to make robust decisions on its own by anticipating and evaluating future outcomes is what makes it intelligent. Planning and decision-making technology in autonomous driving becomes even more challenging, due to the diversity of the dynamic environments the vehicle operates in, the uncertainty in the sensor information, and the complex interaction with other road participants. A significant amount of research has been carried out toward deploying autonomous vehicles to solve plenty of issues, however, how to deal with the high-level decision-making in a complex, uncertain, and urban environment is a comparatively less explored area. This paper provides an analysis of decision-making solutions approaches for autonomous driving. Various categories of approaches are analyzed with a comparison to classical decision-making approaches. Following, a crucial range of research gaps and open challenges have been highlighted that need to be addressed before higher-level autonomous vehicles hit the roads. We believe this survey will contribute to the research of decision-making methods for autonomous vehicles in the future by equipping the researchers with an overview of decision-making technology, its potential solution approaches, and challenges.
Recent Advances in Forward Brillouin Scattering: Sensor Applications
Authors: Sánchez Luis A. , Díez Antonio , Cruz José Luis , Andrés Miguel V.
Published: December 2022

In-fiber opto-mechanics based on forward Brillouin scattering has received increasing attention because it enables sensing the surrounding of the optical fiber. Optical fiber transverse acoustic resonances are sensitive to both the inner properties of the optical fiber and the external medium. A particularly efficient pump and probe technique—assisted by a fiber grating—can be exploited for the development of point sensors of only a few centimeters in length. When measuring the acoustic resonances, this technique provides the narrowest reported linewidths and a signal-to-noise ratio better than 40 dB. The longitudinal and transverse acoustic velocities—normalized with the fiber radius—can be determined with a relative error lower than 10−4, exploiting the derivation of accurate asymptotic expressions for the resonant frequencies. Using this technique, the Poisson’s ratio of an optical fiber and its temperature dependence have been measured, reducing the relative error by a factor of 100 with respect to previously reported values. Using a single-point sensor, discriminative measurements of strain and temperature can be performed, achieving detection limits of ±25 με and ±0.2 °C. These results show the potential of this approach for the development of point sensors, which can be easily wavelength-multiplexed.