bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental Investigation on the Low-Velocity Impact Response of Tandem Nomex Honeycomb Sandwich Panels
Authors: Fan Jinbo , Li Penghui , Guo Weiqi , Zhao Xiuguo , Su Chen , Xu Xinxi
Published: January 2023

Sandwich panels are often subjected to unpredictable impacts and crashes in applications. The core type and impactor shape affect their impact response. This paper investigates the responses of five tandem Nomex honeycomb sandwich panels with different core-types under low-velocity-impact conditions with flat and hemispherical impactors. From the force response and impact displacement, gradient-tandem and foam-filled structures can improve the impact resistance of sandwich panels. Compared with the single-layer sandwich panel, the first peak of contact force of the foam-gradient-filled tandem honeycomb sandwich panels increased by 34.84%, and maximum impact displacement reduced by 50.98%. The resistance of gradient-tandem Nomex honeycomb sandwich panels under low-velocity impact outperformed uniform-tandem structures. Foam-filled structures change the impact responses of the tandem sandwich panels. Impact damage with a flat impactor was more severe than the hemispherical impactor. The experimental results are helpful in the design of tandem Nomex honeycomb sandwich panels.
Acknowledgment to the Reviewers of Publications in 2022
Authors:   Publications Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Acknowledgment to the Reviewers of Quaternary in 2022
Authors:   Quaternary Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Patriotism as a Political Religion: Its History, Its Ambiguities, and the Case of Hungary
Authors: Nyirkos Tamás
Published: January 2023

The article discusses patriotism as a “political religion”, an ambiguous phenomenon that is both a substitute for former religious traditions and something that remains profoundly analogous with them. Special emphasis is laid on the origins of such political religions in the modern era and the role of the state in their emergence, which somewhat relativizes Böckenförde’s famous thesis on the rise of the state as a “process of secularization”. The article also follows the spread of religious patriotism in nineteenth-century Europe and how it contributed to the project of nation-building in different environments. This larger context helps to better explain such cases as that of Hungary, which has produced a variety of patriotic narratives, symbols, and rituals from its beginnings to the present day, raising doubts about the overarching validity of the secularization thesis. Methodologically, this approach involves the analysis of historical and contemporary texts, visual representations, and liturgical practices, while the conclusion suggests that, although the concept of “political religion” remains controversial, the enduring force of patriotism is better explained by the interaction of politics and religion than by a purely secular outlook.
A Study in Evil: The Slave Trade in Africa
Authors: Iddrisu Abdulai
Published: January 2023

In this special issue on justice, ethics, and philosophy of religion, let us consider a historical case study. The trade of slaves across the Atlantic lasted 400 years and led to the forcible removal of about 12.5 million people from Africa, south of the Sahara. This paper examines the African slave trade in light of the notion that evil of whatever form is a menace to our very existence and a rupture of the very essence of hope. It will focus on the nature, development, and growth of the African/European Slave Trade, as it interrogates issues such as: if evil is coterminous with human cruelty, then the slave trade was the apogee of human evil and avarice; the notion of slavers saving the enslaved from themselves; and providing an avenue for conversion into Abrahamic religions. The essay will also be interested in how slavers—European and Africans alike—rationalized slavery and how the enslaved and onlookers responded to the spectacle of enslavement.
God, Religion, and War: Language, Concept, and the Problem of Definition from Genesis to Jihad to Levinas
Authors: Soltes Ori Z.
Published: January 2023

Using a discussion of the etymology of re-lig-io as a starting point, this essay begins by considering the problem of religion—of understanding God, and of language as an instrument for achieving the ends of religion and that understanding—and the problem for religion of revelation and interpretation. It follows to the consequences of this double complication for understanding “war” in the biblical and early Christian traditions. The essay leads, then, to a tri-valent discussion of “jihad”, and from this jihad centerpiece toward further versions of these complications as they apply to mysticism, medieval Jewish thought and thence toward and into modernity, from Spinoza to Levinas.
Coseismic Gravity Changes and Crustal Deformation Induced by the 2018 Fiji Deep-Focus Earthquake Observed by GRACE and GRACE-FO Satellites
Authors: Tanaka Yusaku
Published: January 2023

Earthquakes at depths of ≥300 km are generally called deep-focus earthquakes. Only two deep-focus earthquakes with Mw 8.0 or more have occurred in this century—the 2013 Okhotsk earthquake (Mw 8.3) and the 2018 Fiji earthquake (Mw 8.2) on 19 August 2018. However, the 2018 Fiji earthquake was only reported on seismographs, and the related crustal deformations were not observed by the Global Navigation Satellite System because the observation network did not exist around the epicenter. This study analyzed the time series of gravity data observed by the Gravity Recovery And Climate Experiment (GRACE) and its successor, GRACE Follow-On, and detected the spatial distribution of coseismic gravity changes mainly due to crustal deformation by the 2018 Fiji earthquake. The results in this study were not consistent with the numerical calculation of gravity changes when using the fault parameters estimated by the data of seismic waves. Thus, numerical calculations were used to construct a uniform slip rectangle fault model to explain coseismic gravity changes and provide a spatial distribution map of crustal deformation. However, this fault model is only based on gravity changes; thus, new research combining satellite gravimetry and seismic wave data will be necessary in the future.
Time Series of Land Cover Mappings Can Allow the Evaluation of Grassland Protection Actions Estimated by Sustainable Development Goal 15.1.2 Indicator: The Case of Murgia Alta Protected Area
Authors: Tarantino Cristina , Aquilino Mariella , Labadessa Rocco , Adamo Maria
Published: January 2023

Protected areas, or national parks, are established to preserve natural ecosystems; their effectiveness on the territory needs to be evaluated. We propose considering a time series of the SDG 15.1.2 indicator, “Proportion of important sites for terrestrial and freshwater biodiversity that are covered by protected areas, by ecosystem type”, to quantify the presence over time of grassland ecosystem in Murgia Alta (southern Italy), within the Natura 2000 and national park boundaries. Time series of remote sensing imagery, freely available, were considered for extracting, by Support Vector Machine classifiers, a time series of grassland cover mappings from 1990 to 2021. This latter was, then, used for computing a time series of the SDG 15.1.2 indicator. A high reduction (about 15,000 ha) of grassland presence from 1990 to 2004, the foundation years of the national park, followed by the increasing stability up to nowadays, was evaluated. Furthermore, grassland presence was evaluated in a 5-km buffer area, surrounding Natura 2000 boundary, revealing a continuous loss from 1990 up to now (about 500 ha) in the absence of protection actions. This study represents the first long-term analysis for the grassland ecosystem in Murgia Alta and the first effort to analyze a time series of the SDG 15.1.2 indicator. The findings can provide inputs to governments in monitoring the effectiveness of protection actions.
DirecTES: A Direct Method for Land and Sea Surface Temperature and Emissivity Separation for Thermal Infrared Sensors—Application to TRISHNA and ECOSTRESS
Authors: Marcq Sébastien , Delogu Emilie , Chapelier Morgane , Vidal Thomas H. G.
Published: January 2023

The coming years will see the launch of several missions (TRISHNA, LSTM, SBG), which will acquire images in four or more spectral bands in thermal infrared (TIR) at high spatial resolution (~50–60 m) and with high temporal revisit (~2–3 days). The derivation of surface temperature and emissivity values from top-of-atmosphere radiances is not straightforward, as it is a non-deterministic process requiring additional information. In this paper, we propose the algorithm DirecTES to efficiently separate surface temperature and emissivity. This algorithm is based on the use of a comprehensive spectral database of emissivity, resulting in a well-posed deterministic problem while not assuming strong hypotheses. The algorithm can also benefit from non-TIR information, such as the acquisitions from the same satellite but in the visible and near-infrared domains, or exogenous data—land/sea mask or soil-occupation map. These would help identify the nature of the surface and therefore improve the temperature and emissivity retrievals. After the complete description of the method, we evaluate the performances of DirecTES on theoretical landscapes in TRISHNA’s context under a large range of atmospheric conditions. The retrievals of surface temperature reach RMSEs of 0.8 K over vegetation and 0.5 K over water, including both sensor and atmospheric uncertainties. We then evaluate DirecTES on ECOSTRESS images on sites where the ECOSTRESS Land Surface Temperature (LST) performance has been documented; DirecTES surface temperature retrievals are consistent with the ECOSTRESS LST product and the in-situ data.
Assessment of Restoration Degree and Restoration Potential of Key Ecosystem-Regulating Services in the Three-River Headwaters Region Based on Vegetation Coverage
Authors: Liu Guobo , Shao Quanqin , Fan Jiangwen , Huang Haibo , Liu Jiyuan , He Jianfeng
Published: January 2023

The Three-River Headwaters Region (TRHR) is an important part of the ecological security barrier of the Qinghai–Tibet Plateau in China. Twenty years after the implementation of the TRHR ecological protection and construction project, the restoration degree and restoration potential of its major ecosystem services still lack clear quantification. In this paper, taking the core area of the nature reserve as the climax background of the TRHR zonal ecosystem, based on the multiple regression analysis (MLR) and model parameter control method based on the eco-geographical area, ecosystem types, and climate factors; the climax background, restoration degree, and restoration potential of TRHR’s water retention (WR), soil retention (SR), and windbreak and sand fixation (WD) services were quantitatively researched. The main conclusions were as follows: (1) The evaluation method of climax background, restoration degree, and restoration potential based on fractional vegetation cover (FVC) can accurately quantify the regional differences of the restoration degree and restoration potential of TRHR’s key ecosystem-regulating services. The restoration degree and restoration potential of WR and SR services showed a spatial pattern of high in the southeast and low in the northwest, and the restoration degree and restoration potential of WD services showed a spatial pattern of high in the west and low in the east, which was closely related to natural conditions such as precipitation and wind speed. (2) The proportion of restoration potential to climax background for WR, SR, and WD services were 48.38%, 62.15%, and 56.37%, respectively. (3) The implementation of the TRHR ecological project in the future should focus on the vicinity of the 400 mm dry and wet zone dividing line, as well as in the southeastern mountains, hills, and river valleys, to carry out degraded vegetation restoration and soil and water conservation measures to improve ecosystem services. Near-natural restoration measures should be considered in Zhiduo and Geermu in the western part of the TRHR, where wind erosion is high, and the restoration goals of ecological projects should be formulated in combination with local climatic conditions and restoration potential.
Velocity Vector Estimation of Two-Dimensional Flow Field Based on STIV
Authors: Lu Jianghuai , Yang Xiaohong , Wang Jianping
Published: January 2023

As an important part of hydrometry, river discharge monitoring plays an irreplaceable role in the planning and management of water resources and is an essential element and necessary means of river management. Due to its benefits of simplicity, efficiency and safety, Space-Time Image Velocimetry (STIV) has attracted attention from all around the world. The most crucial component of the STIV is the detection of the Main Orientation of Texture (MOT), and the precision of detection directly affects the results of calculations. However, due to the complicated river flow characteristics and the harsh testing environment in the field, a large amount of noise and interfering textures show up in the space-time images, which affects the detection results of the MOT. In response to the shortage of noise and interference texture, a new non-contact image analysis method is developed. Firstly, Multi-scale Retinex (MSR) is proposed to pre-process the images for contrast enhancement; secondly, a fourth-order Gaussian derivative steerable filter is employed to enhance the structure of the texture; next, based on the probability density distribution function and the orientations of the enhanced images, the noise suppression function and the orientation-filtering function are designed to filter out the noise to highlight the texture. Finally, the Fourier Maximum Angle Analysis (FMAA) is used to filter out the noise further and obtain the clear orientations to achieve the measurement of velocity and discharge. The experimental results show that, compared with the widely used image velocimetry measurements, the accuracy of our method in the average velocity and flow discharge is significantly improved, and the real-time performance is excellent.
Reduction in the Motion Artifacts in Noncontact ECG Measurements Using a Novel Designed Electrode Structure
Authors: Ding Jianwen , Tang Yue , Chang Ronghui , Li Yu , Zhang Limin , Yan Feng
Published: January 2023

A noncontact ECG is applicable to wearable bioelectricity acquisition because it can provide more comfort to the patient for long-term monitoring. However, the motion artifact is a significant source of noise in an ECG recording. Adaptive noise reduction is highly effective in suppressing motion artifact, usually through the use of external sensors, thus increasing the design complexity and cost. In this paper, a novel ECG electrode structure is designed to collect ECG data and reference data simultaneously. Combined with the adaptive filter, it effectively suppresses the motion artifact in the ECG acquisition. This method adds one more signal acquisition channel based on the single-channel ECG acquisition system to acquire the reference signal without introducing other sensors. Firstly, the design of the novel ECG electrode structure is introduced based on the principle of noise reduction. Secondly, a multichannel signal acquisition circuit system and ECG electrodes are implemented. Finally, experiments under normal walking conditions are carried out, and the performance is verified by the experiment results, which shows that the proposed design effectively suppresses motion artifacts and maintains the stability of the signal quality during the noncontact ECG acquisition. The signal-to-noise ratio of the ECG signal after noise reduction is 14 dB higher than that of the original ECG signal with the motion artifact.
IoT in Water Quality Monitoring—Are We Really Here?
Authors: Miller Małgorzata , Kisiel Anna , Cembrowska-Lech Danuta , Durlik Irmina , Miller Tymoteusz
Published: January 2023

The Internet of Things (IoT) has become widespread. Mainly used in industry, it already penetrates into every sphere of private life. It is often associated with complex sensors and very complicated technology. IoT in life sciences has gained a lot of importance because it allows one to minimize the costs associated with field research, expeditions, and the transport of the many sensors necessary for physical and chemical measurements. In the literature, we can find many sensational ideas regarding the use of remote collection of environmental research. However, can we fully say that IoT is well established in the natural sciences?
Stress Detection Using Frequency Spectrum Analysis of Wrist-Measured Electrodermal Activity
Authors: Stržinar Žiga , Sanchis Araceli , Ledezma Agapito , Sipele Oscar , Pregelj Boštjan , Škrjanc Igor
Published: January 2023

The article deals with the detection of stress using the electrodermal activity (EDA) signal measured at the wrist. We present an approach for feature extraction from EDA. The approach uses frequency spectrum analysis in multiple frequency bands. We evaluate the proposed approach using the 4 Hz EDA signal measured at the wrist in the publicly available Wearable Stress and Affect Detection (WESAD) dataset. Seven existing approaches to stress detection using EDA signals measured by wrist-worn sensors are analysed and the reported results are compared with ours. The proposed approach represents an improvement in accuracy over the other techniques studied. Moreover, we focus on time to detection (TTD) and show that our approach is able to outperform competing techniques, with fewer data points. The proposed feature extraction is computationally inexpensive, thus the presented approach is suitable for use in real-world wearable applications where both short response times and high detection performance are important. We report both binary (stress vs. no stress) as well as three-class (baseline/stress/amusement) results.
Temporally and Spatially Resolved Reflected Overpressure Measurements in the Extreme Near Field
Authors: Barr Andrew D. , Rigby Sam E. , Clarke Sam D. , Farrimond Dain , Tyas Andy
Published: January 2023

The design of blast-resistant structures and protective systems requires a firm understanding of the loadings imparted to structures by blast waves. While empirical methods can reliably predict these loadings in the far field, there is currently a lack of understanding on the pressures experienced in the very near field, where physics-based numerical modelling and semi-empirical fast-running engineering model predictions can vary by an order of magnitude. In this paper, we present the design of an experimental facility capable of providing definitive spatially and temporally resolved reflected pressure data in the extreme near field (Z<0.5 m/kg1/3). The Mechanisms and Characterisation of Explosions (MaCE) facility is a specific near-field evolution of the existing Characterisation of Blast Loading (CoBL) facility, which uses an array of Hopkinson pressure bars embedded in a stiff target plate. Maraging steel pressure bars and specially designed strain gauges are used to increase the measurement capacity from 600 MPa to 1800 MPa, and 33 pressure bars in a radial grid are used to improve the spatial resolution from 25 mm to 12.5 mm over the 100 mm radius measurement area. In addition, the pressure bar diameter is reduced from 10 mm to 4 mm, which greatly reduces stress wave dispersion, increasing the effective bandwidth. This enables the observation of high-frequency features in the pressure measurements, which is vital for validating the near-field transient effects predicted by numerical modelling and developing effective blast mitigation methods.
Point Cloud Deep Learning Network Based on Balanced Sampling and Hybrid Pooling
Authors: Deng Chunyuan , Peng Zhenyun , Chen Zhencheng , Chen Ruixing
Published: January 2023

The automatic semantic segmentation of point cloud data is important for applications in the fields of machine vision, virtual reality, and smart cities. The processing capability of the point cloud segmentation method with PointNet++ as the baseline needs to be improved for extremely imbalanced point cloud scenes. To address this problem, in this study, we designed a weighted sampling method based on farthest point sampling (FPS), which adjusts the sampling weight value according to the loss value of the model to equalize the sampling process. We also introduced the relational learning of the neighborhood space of the sampling center point in the feature encoding process, where the feature importance is distinguished by using a self-attention model. Finally, the global–local features were aggregated and transmitted using the hybrid pooling method. The experimental results of the six-fold crossover experiment showed that on the S3DIS semantic segmentation dataset, the proposed network achieved 9.5% and 11.6% improvement in overall point-wise accuracy (OA) and mean of class-wise intersection over union (MIoU), respectively, compared with the baseline. On the Vaihingen dataset, the proposed network achieved 4.2% and 3.9% improvement in OA and MIoU, respectively, compared with the baseline. Compared with the segmentation results of other network models on public datasets, our algorithm achieves a good balance between OA and MIoU.
The IBA-ISMO Method for Rolling Bearing Fault Diagnosis Based on VMD-Sample Entropy
Authors: Zhuang Deyu , Liu Hongrui , Zheng Hao , Xu Liang , Gu Zhengyang , Cheng Gang , Qiu Jinbo
Published: January 2023

Rolling bearings are important supporting components of large-scale electromechanical equipment. Once a fault occurs, it will cause economic losses, and serious accidents will affect personal safety. Therefore, research on rolling bearing fault diagnosis technology has important engineering practical significance. Feature extraction with high price density and fault identification are two keys to overcome in the field of fault diagnosis of rolling bearings. This study proposes a feature extraction method based on variational modal decomposition (VMD) and sample entropy and also designs an improved sequence minimization algorithm with optimal parameters to identify the fault. Firstly, a variational modal decomposition system based on vibration signals is designed, and the sample entropy of the components is extracted as the eigenvalue of the signal. Secondly, in order to improve the accuracy of fault diagnosis, the sequence minimum optimization algorithm optimized by the bat algorithm is used as the classifier. Certainly, the traditional bat algorithm (BA) and the sequence minimum optimization algorithm (SMO) are improved, respectively. Therefore, a fault diagnosis algorithm based on IBA-ISMO is obtained. Finally, the experimental verification is designed to prove that the algorithm model has a good state recognition rate for bearings.
A Novel Point Cloud Registration Method Based on ROPNet
Authors: Li Yuan , Yang Fang , Zheng Wanning
Published: January 2023

Point cloud registration is a crucial preprocessing step for point cloud data analysis and applications. Nowadays, many deep-learning-based methods have been proposed to improve the registration quality. These methods always use the sum of two cross-entropy as a loss function to train the model, which may lead to mismatching in overlapping regions. In this paper, we designed a new loss function based on the cross-entropy and applied it to the ROPNet point cloud registration model. Meanwhile, we improved the ROPNet by adding the channel attention mechanism to make the network focus on both global and local important information, thus improving the registration performance and reducing the point cloud registration error. We tested our method on ModelNet40 dataset, and the experimental results demonstrate the effectiveness of our proposed method.
Single-Cell Classification Based on Population Nucleus Size Combining Microwave Impedance Spectroscopy and Machine Learning
Authors: Ferguson Caroline A. , Hwang James C. M. , Zhang Yu , Cheng Xuanhong
Published: January 2023

Many recent efforts in the diagnostic field address the accessibility of cancer diagnosis. Typical histological staining methods identify cancer cells visually by a larger nucleus with more condensed chromatin. Machine learning (ML) has been incorporated into image analysis for improving this process. Recently, impedance spectrometers have been shown to generate all-inclusive lab-on-a-chip platforms to detect nucleus abnormities. In this paper, a wideband electrical sensor and data analysis paradigm that can identify nuclear changes shows the realization of a single-cell microfluidic device to detect nuclei of altered sizes. To model cells of altered nucleus, Jurkat cells were treated to enlarge or shrink their nucleus followed by broadband sensing to obtain the S-parameters of single cells. The ability to deduce important frequencies associated with nucleus size is demonstrated and used to improve classification models in both binary and multiclass scenarios, despite a heterogeneous and overlapping cell population. The important frequency features match those predicted in a double-shell circuit model published in prior work, demonstrating a coherent new analytical technique for electrical data analysis. The electrical sensing platform assisted by ML with impressive accuracy of cell classification looks forward to a label-free and flexible approach to cancer diagnosis.
Comparison of X-ray Radiant Power Absolute Measurement between a Free-Air Ionization Chamber and a Cryogenic Electrical Substitution Radiometer
Authors: Li Fan , Zhao Yidong , Wang Peiwei , Tang Kun , Zheng Lei
Published: January 2023

Absolute measurement of radiant power in the X-ray region is essential for many applications in astrophysics, spectroscopy, and X-ray diagnostics. Comparison between different measuring methods is an effective way to check their reliability. In the present work, a comparison of X-ray radiant power absolute measurement between a free-air ionization chamber and a cryogenic electrical substitution radiometer was performed at Beijing Synchrotron Radiation Facility. The absolute radiant power obtained by these two methods were mutually compared via a transfer standard detector’s spectral responsivity at a photon energy of 10 keV. The result of the comparison showed that the difference was 0.47%. A conclusion was reached that the free-air ionization chamber and the cryogenic electrical substitution radiometer agreed within the combined relative uncertainty of 3.35%.
Assessment of the Effectiveness of Treatment of Vascular Lesions within the Facial Skin with a Laser with a Wavelength of 532 nm Based on Photographic Diagnostics with the Use of Polarized Light
Authors: Zawodny Piotr , Malec Wiola , Gill Kamil , Skonieczna-Żydecka Karolina , Sieńko Jerzy
Published: January 2023

Aesthetic medicine is a dynamically developing field of medicine. It has an impact not only on the improvement of the external appearance, but also on health and quality of life. Currently, vascular changes affect many patients and significantly diminish the condition of the skin. The development of modern laser therapy has contributed to the successful management of multiple skin conditions, among them vascular lesions. The aim of our study was to show the efficacy of repetitive 532 nm laser therapy in reducing vascular skin lesions located on the facial area. Observations were possible due to the implementation of System of Skin Analysis. We retrospectively analyzed the records of 120 patients (100 women and 20 men) using “VISIA” Skin Analysis System after 532 nm laser therapy. Treatment with the use of the 532 nm vascular laser turned out to be effective in reducing vascular changes in both women and men. The skin phototypes did not significantly affect the therapy efficacy. Neither the age of patients nor number of laser sessions affect therapy efficacy. 532 nm laser therapy is effective in reducing vascular skin lesions located in the face area.
Differences in Tridimensional Shoulder Kinematics between Asymptomatic Subjects and Subjects Suffering from Rotator Cuff Tears by Means of Inertial Sensors: A Cross-Sectional Study
Authors: Roldán-Jiménez Cristina , Cuadros-Romero Miguel , Bennett Paul , Cuesta-Vargas Antonio I.
Published: January 2023

Background: The aim of this study was to analyze differences in three-dimensional shoulder kinematics between asymptomatic subjects and patients who were diagnosed with rotator cuff tears. Methods: This cross-sectional study recruited 13 symptomatic subjects and 14 asymptomatic subjects. Data were obtained from three inertial sensors placed on the humerus, scapula and sternum. Kinematic data from the glenohumeral, scapulothoracic and thoracohumeral joints were also calculated. The participants performed shoulder abductions and flexions. The principal angles of movements and resultant vectors in each axis were studied. Results: The glenohumeral joint showed differences in abduction (p = 0.001) and flexion (p = 0.000), while differences in the scapulothoracic joint were only significant during flexion (p = 0.001). The asymptomatic group showed higher velocity values in all sensors for both movements, with the differences being significant (p < 0.007). Acceleration differences were found in the scapula during abduction (p = 0.001) and flexion (p = 0.014), as well as in the sternum only during shoulder abduction (p = 0.022). Conclusion: The results showed kinematic differences between the patients and asymptomatic subjects in terms of the mobility, velocity and acceleration variables, with lower values for the patients.
A Novel Piecewise Tri-Stable Stochastic Resonance System Driven by Dichotomous Noise
Authors: Zhao Shuai , Shi Peiming
Published: January 2023

Stochastic resonance (SR) has been widely studied as a means of signal processing since its conception. Since SR is different from other denoising methods in nature, it can be used for not only feature extraction but also signal enhancement. Additive white Gaussian noise (AWGN) is often used as a driving source in SR research due to its convenience in numerical simulation and uniform distribution, but as a special noise, it is of great significance to study the SR principle of dichotomous noise as a driving source for nonlinear dynamics. In this paper, the method of piecewise tri-stable SR (PTSR) driven by dichotomous noise is studied, and it is verified that signal enhancement can still be achieved in the PTSR system. At the same time, the influence of the parameters of the PTSR system, periodic signal, and dichotomous noise on the mean of signal-to-noise ratio gain (SNR-GM) is analyzed. Finally, dichotomous noise and AWGN are used as the driving sources of the PTSR system, and the signal enhancement ability and noise resistance ability of the two drivers are compared.
A Dilated Residual Network for Turbine Blade ICT Image Artifact Removal
Authors: Han Rui , Zeng Fengying , Li Jing , Yao Zhenwen , Guo Wenhua , Zhao Jiyuan
Published: January 2023

Artifacts are divergent strip artifacts or dark stripe artifacts in Industrial Computed Tomography (ICT) images due to large differences in density among the components of scanned objects, which can significantly distort the actual structure of scanned objects in ICT images. The presence of artifacts can seriously affect the practical application effectiveness of ICT in defect detection and dimensional measurement. In this paper, a series of convolution neural network models are designed and implemented based on preparing the ICT image artifact removal datasets. Our findings indicate that the RF (receptive field) and the spatial resolution of network can significantly impact the effectiveness of artifact removal. Therefore, we propose a dilated residual network for turbine blade ICT image artifact removal (DRAR), which enhances the RF of the network while maintaining spatial resolution with only a slight increase in computational load. Extensive experiments demonstrate that the DRAR achieves exceptional performance in artifact removal.
Peukert’s Law-Based State-of-Charge Estimation for Primary Battery Powered Sensor Nodes
Authors: Dai Hongli , Xia Yu , Mao Jing , Xu Cheng , Liu Wei , Hu Shunren
Published: January 2023

Accurate state-of-charge (SOC) estimation is essential for maximizing the lifetime of battery-powered wireless sensor networks (WSNs). Lightweight estimation methods are widely used in WSNs due to their low measurement and computation requirements. However, accuracy of existing lightweight methods is not high, and their adaptability to different batteries and working conditions is relatively poor. This paper proposes a lightweight SOC estimation method, which applies Peukert’s Law to estimate the effective capacity of the battery and then calculates the SOC by subtracting the cumulative current consumption from the estimated capacity. In order to evaluate the proposed method comprehensively, different primary batteries and working conditions (constant current, constant resistance, and emulated duty-cycle loads) are employed. Experimental results show that the proposed method is superior to existing methods for different batteries and working conditions, which mainly benefits from the ability of Peukert’s Law to better model the rate-capacity effect of the batteries.
Detailing the Ten Main Professional Roles of a Pharmacist to Provide the Scope of Professional Functions
Authors: Kremin Yuliia , Lesyk Lilia , Lesyk Roman , Levytska Oksana , Hromovyk Bohdan
Published: January 2023

As members of a public trust profession, pharmacists are the most accessible medical team members. Therefore, every pharmacist must know the scope of their professional roles (PR) and professional functions (PF). The study aimed to detail the major PR into a pooled set of PF. The research materials were the provisions of the World Health Organization, the International Pharmaceutical Federation, and scientific works on the PR of pharmacists. Methods of critical analysis, concretization, functional decomposition, and scientific generalization were used. As a result of detailing the 10 main PR according to the “ten-star pharmacist” concept for each, a combined set of partial PFs of the pharmacist was obtained. The decomposition takes into account the principle of complexity limitation, which allowed three to six partial PF for the respective PR to be obtained, namely: three PFs for a life-long-learner, five PFs for a caregiver, a decision-maker, a teacher, a leader, a researcher, an entrepreneur, and an agent of positive change, six PFs for a communicator and a manager. Thus, due to the decomposition of each of the 10 main PR of the pharmacist into three or six corresponding partial PFs, we received a multifunctional verbal model of difficult to organize, professional activities, which is identified by a total of 50 PFs. The importance of using this model in formulating professional competencies and learning outcomes of educational programs for pharmacists is emphasized.
Bioactive Chemical Constituents of Matthiola longipetala Extract Showed Antioxidant, Antibacterial, and Cytotoxic Potency
Authors: El-Amier Yasser A. , Zaghloul Nouf S. , Abd-ElGawad Ahmed M.
Published: January 2023

The exploration of bioactive compounds from natural resources attracts the attention of researchers and scientists worldwide. M. longipetala is an annual aromatic herb that emits a pleasant odor during the night. Regarding the chemical composition and biological characteristics, M. longipetala extracts are poorly studied. The current study aimed to characterize the chemical composition of M. longipetala methanol extract using GC-MS and determine its biological potencies, including its capacity for cytotoxicity and antioxidant and antibacterial activities. In this approach, 37 components were identified, representing 99.98% of the total mass. The major chemical components can be classified as oxygenated hydrocarbons (19.15%), carbohydrates (10.21%), amines (4.85%), terpenoids (12.71%), fatty acids and lipids (50.8%), and steroids (2.26%). The major identified compounds were ascaridole epoxide (monoterpene, 12.71%) and methyl (E)-octadec-11-enoate (ester of fatty acid, 12.21%). The extract of M. longipetala showed substantial antioxidant activity. Based on the DPPH and ABTS scavenging, the antioxidant activity of the extracted components of M. longipetala revealed that leaf extract is the most effective with IC50 values of 31.47 and 28.94 mg/L, respectively. On the other hand, the extracted plant showed low antibacterial activities against diverse bacterial species, viz., Escherichia coli, Klebsiella pneumonia, Staphylococcus epidermidis, S. haemolyticus, and S. aureus. The most potent antibacterial results were documented for leaf and flower extracts against E. coli and S. aureus. Additionally, the extract’s effectiveness against HepG2 cells was evaluated in vitro using the measures of MTT, DNA fragmentation, and cell proliferation cycle, where it showed considerable activity. Therefore, we can conclude that M. longipetala extract displayed improvement in cytocompatibility and cell migration properties. In conclusion, M. longipetala could be considered a potential candidate for various bioactive compounds with promising biological activities. However, further characterization of the identified compounds, particularly the major compounds, is recommended to evaluate their efficacy, modes of action, and safety.
Adsorption Performance of Zeolite for the Removal of Congo Red Dye: Factorial Design Experiments, Kinetic, and Equilibrium Studies
Authors: Imessaoudene Ali , Cheikh Sabrina , Hadadi Amina , Hamri Nadia , Bollinger Jean-Claude , Amrane Abdeltif , Tahraoui Hichem , Manseri Amar , Mouni Lotfi
Published: January 2023

In the present research, zeolite is used for the removal of toxic Congo red dye from water solution. The effects of different operating conditions such as hydrogen potential (pH), contact time (time), zeolite dose (D), initial dye concentration (C0), and ionic strength (I) are investigated for Congo red adsorption under batch mode. It was found that the adsorption process was greatly affected by the initial pH of the dye solution. The removal efficiency decreased from 97.68 to 5.22% when the pH varied from 3 to 5; thus, acidic conditions clearly improve Congo red adsorption on zeolite. At pH 3, an increase in C0 and I and decrease in D resulted in an increase in the adsorption capacity qe. The effects of these three parameters and their interactions were also investigated using the 23 full factorial design experiments approach where qe was chosen as the response. The results obtained from this method followed by the analysis of variance and the Student’s t-test show that, the influence of these parameters on dye adsorption process are in the order I < C0 < D. The kinetic studies revealed that adsorption follows a pseudo-second-order kinetic model. The adsorption isotherms experimental data were analyzed using the Langmuir, Freundlich, and Temkin isotherms models. The Freundlich isotherm was the best-fit model to the experimental data. The fitting of kinetics and isotherm models was evaluated by using non-linear modeling, R2, MSE, and RMSE.
What if a Bioterrorist Attack Occurs?—A Survey on Citizen Preparedness in Aveiro, Portugal
Authors: Santos Helena , Pinto Maria , Cardoso Luís , Rodrigues Isilda , Coelho Ana
Published: January 2023

Introduction: A bioterrorist attack is the intentional release of pathogenic micro-organisms, such as viruses, bacteria, or their toxins, with the aim of causing illness or death in people, animals, or plants. In this study, we investigated the knowledge and practices related to bioterrorism preparedness in Central Portugal. Methods: A descriptive cross-sectional study was performed with a convenience sample in the population of Aveiro, Central Portugal, to assess their knowledge about bioterrorism, self-perceived preparation to act in case of bioterrorism and pet owners’ preparation. An online validated questionnaire was completed by 198 participants from January to February 2020. Results: In this study, 46.0% of the respondents answered that they knew nothing about bioterrorism or had never heard about the possibility of bioterrorist attacks. In the case of an attack, 77.8% participants did not consider themselves prepared to act, and 62.1% did not know how to use personal protective equipment. More than half of the respondents (60.6%) were not familiar with the local emergency response system in response to catastrophes/bioterrorist attacks. Almost all respondents (95.6%) assigned high importance to drinking water and food for pets, but only 22.9% of respondents attributed high importance to pet carrier boxes, an item essential for cat evacuation. Conclusion: This is the first survey of this kind in Portugal concerning bioterrorism preparedness in citizens and animals. Results suggest that Portuguese knowledge is limited, and people have inadequate preparedness for a bioterrorist attack. These results reinforce the importance of further studies to better understand the existing gaps in knowledge of Portuguese citizens, strengthen the need to adopt the One Health concept in preparedness plans and emphasize the crucial role of health education in prevention.
A Review on Hydration Process and Setting Time of Limestone Calcined Clay Cement (LC3)
Authors: Zhao Yuhan , Zhang Yingda
Published: January 2023

The extensive usage of concrete and ordinary Portland cement has generated 5~8% of annual global CO2 emissions, causing serious environmental problems. To reduce such environmental impact, researchers have made significant efforts to develop alternative materials that may partially or entirely replace the ordinary Portland cement, such as limestone calcined clay cement (LC3). LC3 has not been commonly adopted in reality because of uncertain setting times during the transportation and construction processes. Comprehensive investigation and understanding of the setting times of LC3 has great significance to industrial upgrading. As a result, this study is committed to comprehensively reviewing the hydration process and the setting time of LC3 materials.
Unemployment and Enterprise Births in European Countries: A Sectoral Approach
Authors: Wosiek Małgorzata
Published: January 2023

Different types of entrepreneurial activities are more or less conducive to socio-economic development. Among others, opportunity entrepreneurs are found to have a greater impact on economic growth, innovation, and employment compared to necessity entrepreneurs (pushed by the risk of being unemployed). In this context, the main goal of the study is to find the answer to the following research question: Which business sectors in European countries are sensitive to the unemployment push effect and thus more prone to necessity entrepreneurship? The paper provides further insight into the unemployment push hypothesis by investigating this issue in the group of 20 European countries across 11 business sectors (NACE Rev. 2 classification): manufacturing, construction, and services of business economies (nine sectors). The issue is examined by analyzing Eurostat and World Bank data for 2004–2020 using the panel vector autoregression (p-VAR) approach. The results confirm the unemployment push effect only in wholesaling, retailing, and repair services. The effect, however, seems to be triggered by entry behaviors in the Central Eastern European countries, which are more active in creating new businesses and more prone to necessity entrepreneurship. In addition, the interplay between unemployment and new enterprise dynamics in wholesaling, retailing, and repair services seems to be relatively more robust to existing heterogeneity within entrepreneurs, countries, and estimation techniques. The implications of the results could assist policymakers responsible for active labor market instruments promoting entrepreneurial attitudes.
Investigating the Determinants of Financial Inclusion in BRICS Economies: Panel Data Analysis Using Fixed-Effect and Cross-Section Random Effect
Authors: Pandey Amit , Kiran Ravi , Sharma Rakesh Kumar
Published: January 2023

The current research empirically analyses the determinants of financial inclusion (FI) for BRICS (Brazil, Russia, India, China and South Africa) nations using the no. of depositors and Automated Teller Machines/user as dependent variables, a proxy for FI from 2004 to 2019. The study employs fixed-effect, cross-section random-effect and simple panel least square techniques to determine FI for different BRICS countries. The empirical findings of fixed effect and cross-section random highlight that population and internet users affirmatively and significantly influence FI. Simple panel least square analysis indicates that domestic credit to the finance sector, population, internet users and bank branches positively influence the no. of depositors in these economies. Gross domestic product (GDP) and domestic credit to private sector (DCPS) inversely affected FI. Results of the second measure of FI (ATM per user) show the exchange rate of domestic credit to the private sector, and GDP positively influences FI. These findings will induce policymakers to take corrective actions by considering the significant factors to boost FI in respective BRICS economies.
Active and Reactive Power Control of the Voltage Source Inverter in an AC Microgrid
Authors: Khan Hamid Saeed , Memon Attaullah Y.
Published: January 2023

This paper presents the mathematical model and control of a voltage source inverter (VSI) connected to an alternating current (AC) microgrid. The VSI considered in this paper is six switches three-phase Pulse Width Modulated (PWM) inverter, whose output active and reactive power is controlled in the dq reference frame. The control strategy presented here is state feedback control with disturbance cancellation. This disturbance signal is either provided by a voltage sensor or estimated using a presented extended high gain observer (EHGO). The control strategy without EHGO requires a current sensor and a voltage sensor, and the control strategy with EHGO requires only a current sensor. The EHGO is saving the requirement of a voltage sensor. The stability analysis of the presented control strategy is showing that the error is ultimately bounded in the presence of disturbance, formed due to Pulse Width Modulated (PWM) inverters. The microgrid is simulated using the SimPowerSystems Toolbox of MATLAB/Simulink. The simulation results are also showing the effectiveness of the proposed control strategy, that the output active and reactive power control is achieved with ultimately bounded errors. The comparison of the proposed control with the PI-based control scheme is also presented, and it is shown that better reference tracking with the desired settling time of “0.04 s” is achieved with the proposed control.