bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Adsorption Properties of Zeolite in a New Skin Care Formulation
Authors: Pesando Massimo , Bolzon Veronica , Bulfoni Michela , Nencioni Alessandro , Nencioni Emanuele
Published: February 2022

Introduction: Zeolites are natural or synthetic aluminosilicates, characterized by a regular and microporous crystalline structure that plays a particularly active role in neutralizing free radicals, screening UV rays and in the adsorption of toxins and heavy metals. Skin is one of the main areas for the accumulation of toxic substances released by environmental pollutants. The biological scavenger activity of zeolite opens a wide spectrum of applications in cosmetics and dermatology. Up to now, there is little evidence related to the use of natural zeolite in cosmetics. Aim: The purpose of this work was to evaluate the ability of zeolite to retain heavy metals in a new skin care formulation, in order to provide a proof of principle of its employment in the field of cosmetics. Materials and Methods: Taking the advantages of spiked samples, we studied the in vitro adsorption properties of zeolite in a new skin care formulation. The removal capacities of Cadmium, Lead, Chromium, Nickel and Cobalt were studied, using the inductively coupled plasma optical emission spectrometry (ICP-OES). First of all, the better concentration of zeolite was defined, testing two different proportions of zeolite, from 1% to 3%, keeping all other components constant. Then, on the 3% formulation, the adsorption properties of each single metal were measured. Results and Conclusions: Our preliminary study demonstrated the selectivity of zeolite in retaining Cadmium (p < 0.0001), Nickel (p = 0.026), in a 3% zeolite-based formulation. This work provides a proof of principle of zeolite employment in the field of cosmetics. Based on the data collected, our work provides a scientific proof of principle of zeolite employment in the field of cosmetics. New and extensive research will be needed to explore all the potential benefits of zeolite.
Comparative Analysis of Bubbles Behavior in Different Liquids by Laser-Induced Plasma Micromachining Single-Crystal Silicon
Authors: Liu Ying , Guo Hongjing , Wang Han , Zhang Yi , Zhang Zhen
Published: February 2022

Laser-induced plasma micromachining (LIPMM) can be used to fabricate high-quality microstructures of hard and brittle materials. The liquid medium of the LIPMM process plays a key role in inducing the plasma and cooling the materials, but the liquid medium is overheated which induces lots of bubbles to defocus the laser beam and reduce machining stability. In this paper, a comparative investigation on bubble behavior and its effect on the surface integrity of microchannels in three types of liquids and at different depths during LIPMM has been presented. Firstly, the formation mechanism of microbubbles was described. Secondly, a series of experiments were conducted to study the number and maximum diameter of the attached bubbles and the buoyancy movement of floating bubbles in the LIPMM of single-crystal silicon under deionized water, absolute ethyl alcohol, and 5.6 mol/L phosphoric acid solution with a liquid layer depth of 1–5 mm. It was revealed that the number and maximum diameter of attached bubbles in deionized water were the highest due to its high tension. Different from the continuous rising of bubbles at the tail of the microchannels in the other two liquids, microbubbles in 5.6 mol/L phosphoric acid solution with high viscosity rose intermittently, which formed a large area of bubble barrier to seriously affect the laser focus, resulting in a discontinuous microchannel with an unablated segment of 26.31 μm. When the depth of the liquid layer was 4 mm, absolute ethyl alcohol showed the advantages in narrow width (27.15 μm), large depth (16.5 μm), and uniform depth profile of the microchannel by LIPMM. This was because microbubbles in the anhydrous ethanol quickly and explosively spread towards the edge of the laser processing zone to reduce the bubble interference. This research contributes to a better understanding of the behavior and influence of bubbles in different liquid media and depths in LIPMM of single-crystal silicon.
The BC Generations Project as a Tumor Tissue Resource for Cancer Research
Authors: Zanif Umaimah , Chu Jessica , Simkin Jonathan , Dummer Trevor , Woods Ryan , Belanger Eric , Bhatti Parveen
Published: February 2022

Population-based cohort studies can be a resource for tumor specimens, annotated with demographic, lifestyle, and health history data, that support innovative studies of cancer. Our aim was to establish and test a process for accessing tumor samples, held at pathology laboratories around British Columbia (BC), for participants of the BC Generations Project (BCGP). Through the BC Cancer Registry, we identified pathology reports for 1100 (93%) of the 1180 incident solid cancer cases diagnosed in BCGP as of 2019. Using manually abstracted data from the reports, we successfully retrieved 183 (92%) of the 200 formalin-fixed, paraffin-embedded (FFPE) blocks (breast, lung, bladder, and pancreas cancer cases) that we requested from pathology laboratories. No important differences in retrieval rates by cancer site, sample location (Greater Vancouver vs. Outside Greater Vancouver), sample type (biopsy vs. excision) or year of diagnosis were identified. A text mining solution recently implemented by the Registry will allow us to automate the process for data abstraction and should capture pathology reports for 100% of all newly diagnosed BCGP cancer cases moving forward. This will further enhance the utility of BCGP as a high-quality tumor tissue research resource.
A PCR-Based Retrospective Study for Beak and Feather Disease Virus (BFDV) in Five Wild Populations of Parrots from Australia, Argentina and New Zealand
Authors: Ortiz-Catedral Luis , Wallace Connor J. , Heinsohn Robert , Krebs Elizabeth A. , Langmore Naomi E. , Vukelic Dusan , Bucher Enrique H. , Varsani Arvind , Masello Juan F.
Published: February 2022

The beak and feather disease virus (family Circovirdae) is a virus of concern in the conservation of wild Psittaciformes globally. We conducted a PCR screening for the beak and feather disease virus (BFDV) using samples collected during previous field studies (1993–2014) in five populations of parrots of the Southern Hemisphere: Eclectus parrots (Eclectus roratus) and Crimson rosellas (Platycercus elegans) from Australia, Burrowing parrots (Cyanoliseus patagonus) and Monk parakeets from Argentina (Myiopsitta monachus), and Forbes’ parakeet from New Zealand (Cyanoramphus forbesi). A total of 612 samples were screened. BFDV was not detected in any of the sampled birds. Our results provide a retrospective screening, covering three different tribes of Old and New World parrots, including two of the most numerous species, and contributing a large set of negative results. Furthermore, our results suggest that geographical and temporal differences in BFDV distribution may exist and merit further research, as a critical component in the efforts to manage the disease and its epidemiological aspects. The results presented here hold the potential to provide a baseline for future studies investigating the temporal evolution and the spread of BFDV.
Diagnostic Performance of Point Shear Wave Elastography (pSWE) Using Acoustic Radiation Force Impulse (ARFI) Technology in Mesenteric Masses: A Feasibility Study
Authors: Alhyari Amjad , Görg Christian , Dietrich Christoph Frank , Kawohl Svenja , Safai Zadeh Ehsan
Published: February 2022

Purpose: To evaluate the diagnostic performance of ultrasound point shear wave elastography (pSWE) using acoustic radiation force impulse (ARFI) technology in different benign and malignant mesenteric masses (MMs). Methods: A total of 69 patients with MMs diagnosed from September 2018 to November 2021 were included retrospectively in the study. The inclusion criteria were (1) an MM over 1 cm; (2) valid ARFI measurements; and (3) confirmation of the diagnosis of an MM by histological examination and/or clinical and radiological follow-up. To examine the mean ARFI velocities (MAVs) for potential cut-off values between benign and malignant MMs, a receiver operating characteristics analysis was implemented. Results: In total, 37/69 of the MMs were benign (53.6%) and 32/69 malignant (46.4%). Benign MMs demonstrated significantly lower MAVs than mMMs (1.59 ± 0.93 vs. 2.76 ± 1.01 m/s; p < 0.001). Selecting 2.05 m/s as a cut-off value yielded a sensitivity and specificity of 75.0% and 70.3%, respectively, in diagnosing malignant MMs (area under the curve = 0.802, 95% confidence interval 0.699–0.904). Conclusion: ARFI elastography may represent an additional non-invasive tool for differentiating benign from malignant MMs. However, to validate the results of this study, further prospective randomized studies are required.
Relationship between Apparent Diffusion Coefficient Distribution and Cancer Grade in Prostate Cancer and Benign Prostatic Hyperplasia
Authors: Saito Shigeyoshi , Koyama Yoshihiro , Ueda Junpei , Hashido Takashi
Published: February 2022

The aim of this paper was to assess the associations between prostate cancer aggressiveness and histogram-derived apparent diffusion coefficient (ADC) parameters and determine which ADC parameters may help distinguish among stromal hyperplasia (SH), glandular hyperplasia (GH), and low-grade, intermediate-grade, and high-grade prostate cancers. The mean, median, minimum, maximum, and 10th and 25th percentile ADC values were determined from the ADC histogram and compared among two benign prostate hyperplasia (BPH) groups and three Gleason score (GS) groups. Seventy lesions were identified in 58 patients who had undergone proctectomy. Thirty-nine lesions were prostate cancers (GS 6 = 7 lesions, GS 7 = 19 lesions, GS 8 = 11 lesions, GS 9 = 2 lesions), and thirty-one lesions were BPH (SH = 15 lesions, GH = 16 lesions). There were statistically significant differences in 10th percentile and 25th percentile ADC values when comparing GS 6 to GS 7 (p < 0.05). The 10th percentile ADC values yielded the highest area under the curve (AUC). Tenth and 25th percentile ADCs can be used to more accurately differentiate lesions with GS 6 from those with GS 7 than other ADC parameters. Our data indicate that the major challenge with ADC mapping is to differentiate between SH and GS 6, and SH and GS 7.
Innovations in Diagnostic Imaging in Oral and Maxillofacial Diseases
Authors: D’Angelo Maurilio , Zanza Alessio , Di Nardo Dario , Testarelli Luca
Published: February 2022

In recent years, improvements in imaging techniques have profoundly facilitated the diagnosis of pathologies of the maxillofacial district [...]
Evaluation of Diagnostic Performance of Automatic Breast Volume Scanner Compared to Handheld Ultrasound on Different Breast Lesions: A Systematic Review
Authors: Ibraheem Shahad A. , Mahmud Rozi , Mohamad Saini Suraini , Abu Hassan Hasyma , Keiteb Aysar Sabah , Dirie Ahmed M.
Published: February 2022

Objective: To compare the diagnostic performance of the automatic breast volume scanner (ABVS) against the handheld ultrasound (HHUS) in the differential diagnosis of benign and malignant breast lesions. Methods: A systematic search and review of studies involving ABVS and HHUS for breast cancer screening were performed. The search involved the data taken from Scopus, PubMed, and science direct databases and was conducted between the year 2011 to 2020. The prospective method was used in determining the inclusion and exclusion criteria while the evidence level was determined using the BI-RADS categories for diagnostic studies. In addition, the parameters of specificity, mean age, sensitivity, tumor number, and diagnostic accuracy of the ABVS and HHUS were summarized. Results: No systematic review or randomized controlled trial were identified in the systematic search while one cross-sectional study, eight retrospective studies, and 10 prospective studies were found. Sufficient follow-up of the subjects with benign and malignant findings were made only in 10 studies, in which only two had used ABVS and HHUS after performing mammographic screening and MRI. Analysis was made of 21 studies, which included 5448 lesions (4074 benign and 1374 malignant) taken from 6009 patients. The range of sensitivity was (0.72–1.0) for ABVS and (0.62–1.0) for HHUS; the specificity range was (0.52–0.98)% for ABVS and (0.49–0.99)% for HHUS. The accuracy range among the 11 studies was (80–99)% and (59–98)% for the HHUS and ABVS, respectively. The identified tumors had a mean size of 2.1 cm, and the detected cancers had a mean percentage of 94% (81–100)% in comparison to the non-cancer in all studies. Conclusions: The evidence available in the literature points to the fact that the diagnostic performance of both ABVS and HHUS are similar with reference to the differentiation of malignant and benign breast lesions.
Multiscale Geometric Analysis Fusion-Based Unsupervised Change Detection in Remote Sensing Images via FLICM Model
Authors: Li Liangliang , Ma Hongbing , Jia Zhenhong
Published: February 2022

Remote sensing image change detection is widely used in land use and natural disaster detection. In order to improve the accuracy of change detection, a robust change detection method based on nonsubsampled contourlet transform (NSCT) fusion and fuzzy local information C-means clustering (FLICM) model is introduced in this paper. Firstly, the log-ratio and mean-ratio operators are used to generate the difference image (DI), respectively; then, the NSCT fusion model is utilized to fuse the two difference images, and one new DI is obtained. The fused DI can not only reflect the real change trend but also suppress the background. The FLICM is performed on the new DI to obtain the final change detection map. Four groups of homogeneous remote sensing images are selected for simulation experiments, and the experimental results demonstrate that the proposed homogeneous change detection method has a superior performance than other state-of-the-art algorithms.
TLP-CCC: Temporal Link Prediction Based on Collective Community and Centrality Feature Fusion
Authors: Zhu Yuhang , Liu Shuxin , Li Yingle , Li Haitao
Published: February 2022

In the domain of network science, the future link between nodes is a significant problem in social network analysis. Recently, temporal network link prediction has attracted many researchers due to its valuable real-world applications. However, the methods based on network structure similarity are generally limited to static networks, and the methods based on deep neural networks often have high computational costs. This paper fully mines the network structure information and time-domain attenuation information, and proposes a novel temporal link prediction method. Firstly, the network collective influence (CI) method is used to calculate the weights of nodes and edges. Then, the graph is divided into several community subgraphs by removing the weak link. Moreover, the biased random walk method is proposed, and the embedded representation vector is obtained by the modified Skip-gram model. Finally, this paper proposes a novel temporal link prediction method named TLP-CCC, which integrates collective influence, the community walk features, and the centrality features. Experimental results on nine real dynamic network data sets show that the proposed method performs better for area under curve (AUC) evaluation compared with the classical link prediction methods.
Networking Feasibility of Quantum Key Distribution Constellation Networks
Authors: Wang Junyong , Chang Liang , Chen Hongyu , Zhu Zhencai
Published: February 2022

Quantum key distribution constellation is the key to achieve global quantum networking. However, the networking feasibility of quantum constellation that combines satellite-to-ground accesses selection and inter-satellite routing is faced with a lack of research. In this paper, satellite-to-ground accesses selection is modeled as problems to find the longest paths in directed acyclic graphs. The inter-satellite routing is interpreted as problems to find a maximum flow in graph theory. As far as we know, the above problems are initially understood from the perspective of graph theory. Corresponding algorithms to solve the problems are provided. Although the classical discrete variable quantum key distribution protocol, i.e., BB84 protocol, is applied in simulation, the methods proposed in our paper can also be used to solve other secure key distributions. The simulation results of a low-Earth-orbit constellation scenario show that the Sun is the leading factor in restricting the networking. Due to the solar influence, inter-planar links block the network periodically and, thus, the inter-continental delivery of keys is restricted significantly.
Performance of Academic Staff during COVID-19 Pandemic-Induced Work Transformations: An IPO Model for Stress Management
Authors: Shoaib Muhammad , Nawal Ayesha , Korsakienė Renata , Zámečník Roman , Rehman Asad Ur , Raišienė Agota Giedrė
Published: February 2022

The COVID-19 pandemic has adversely affected all spheres of services-related business, including the higher education sector. As a pre-emptive measure, almost all traditional educational institutions have been transformed into virtual organizations. This pandemic-induced work transition has created stress among academic staff and has hampered their performance. The present study aims to examine the impact of leadership behaviors, e-training, and employment security on the stress management process, consequently improving employee performance during and after the pandemic. Based on the IPO (input–process–output) model, this study examines the effect of leadership behavior, e-training, and employment security on teaching staff’s tasks and adaptive and contextual performance, mediated by stress management. To test the conceptual model, data were collected from the teaching staff of Malaysian universities. The structural equation modeling technique was used for data analysis, while bootstrapping with the maximum likelihood estimator was used to confirm the mediational role of stress management. The study revealed that task- and relation-oriented leadership behavior, e-training, and employment security positively influence stress management and employee performance in virtual organizations. Moreover, stress management acts as a full mediator in the relationship between leadership behavior and employee performance, while partial mediation occurs between e-training, employment security, and employee performance. This study offers valuable insights into the literature by proposing leadership behavior, e-training, and employment security as input in the stress management process to attain the performance output of teaching staff. Higher education institutions should come forward to assist their teaching employees in managing their stress levels for better outcomes.
Investigation of Attributes Influencing the Attractiveness of Mobile Commerce Advertisements on the Facebook Platform
Authors: Cvirka Donatas , Rudienė Elzė , Morkūnas Mangirdas
Published: February 2022

Examining and analyzing the determinants facilitating consumers’ intention to buy via mobile commerce platforms have untapped potential when it comes to advertisement potential and perceived advertising value. Therefore, this paper examines various aspects of the advertisements on mobile commerce platforms and analyzes the importance of intention to buy. The goal of the article is to analyze and determine which aspects of the advertisements have an influence on expediting purchase through mobile commerce. The underlying hypothesis for this investigation is the applicability of the perceived advertising value of mobile commerce, positively associated with attitude towards advertising channels. The Facebook social network has been chosen as an advertisement channel as it is the most popular and biggest investment-generated channel. It is also proven that subjective norms are positively associated with the intention to buy via mobile commerce. This, combined with perceived advertising values and attitudes towards Facebook ads on mobile commerce, influenced the intention to buy.
The Dynamics of the Profitability and Growth of Restaurants; The Case of Norway
Authors: Opstad Leiv , Idsø Johannes , Valenta Robin
Published: February 2022

The restaurant industry is quite similar across borders. It is a labour-intensive industry that is important for tourism and employment. It consists mainly of many small businesses that are regionally dispersed. There are many studies that have analysed this sector. However, rather few articles have focused on the dynamics of growth and profit. The purpose of this paper is to apply the theory of profit persistence and the law of proportionate effect (LPE) to Norwegian restaurants by using publicly available public panel data from 2010 to 2019. The sample includes 866 restaurants. One important finding is that Gibrat’s law (LPE) does not seem to hold, meaning the growth is not independent of the size of the firms. Small businesses grow faster than the others, and they are also more profitable. There is some degree of profit persistence in the restaurant industry. Profitability is negatively linked to debt ratios but positively related to working capital. The study shows there is a trade-off between size and profit. These findings are useful for the industry and for others (public planning, lenders, and more).
A Systematic Review of the Effects of Physical Activity on Specific Academic Skills of School Students
Authors: Loturco Irineu , Montoya Natalia P. , Ferraz Marina B. , Berbat Vanderson , Pereira Lucas A.
Published: February 2022

This systematic review examined the effects of distinct physical activity interventions on the academic achievement of school students based on an analysis of four distinct outcomes: mathematics, language, reading, and composite scores. This study was performed in accordance with the PRISMA guidelines and the QUORUM statement. A literature search was conducted using the PubMed-MEDLINE, Scopus, and Web of Science databases. Peer-reviewed studies published in English, Portuguese, and Spanish were considered. A random-effect meta-analysis was employed to determine the effect of interventions on academic performance. The effects between interventions and control groups were expressed as standardized mean differences. Thirty-one studies were included in the meta-analysis based on the inclusion and exclusion criteria. The exercise programs were not capable of significantly improving language, reading skills, and composite scores. Conversely, performance in math tests increased significantly after the interventions compared with the control groups. Regarding the overall effect, a significant improvement in academic achievement was detected after physical activity programs compared with controls. In conclusion, the positive effects of school-based physical education on academic performance are not uniform and may be higher for math skills. The implementation of evidence-based exercise programs in school settings emerges as a promising strategy to increase overall academic achievement in school-aged students.
Lecturer Competence from the Perspective of Undergraduate Psychology Students: A Qualitative Pilot Study
Authors: Di Battista Silvia , Pivetti Monica , Melotti Giannino , Berti Chiara
Published: February 2022

Understanding what students mean by lecturer competence can be crucial in order to recognise indicators with which to assess these competences, improve the quality of university teaching and support lecturers in undertaking their role appropriately. This qualitative pilot study aimed to explore the meaning of competence in a convenience sample of Italian undergraduate psychology students (N = 122). We collected free-associations about what “lecturer competence” actually means for the students. The data corpus underwent a lexical Correspondence Analysis (CA) using the ASPAR procedure of SPAD-T. Two factors were extracted: “socio-emotional dimension” and “task specialist.” Students associated the competent lecturer with those who was involved with the achievement of the task goals, on the one hand or those who was engaged in the group’s maintenance, on the other. Furthermore, Cluster Analysis identified four clusters: (1) the captivating lecturer; (2) the lecturer oriented to both task and socio-emotional aspects; (3) the rigorous lecturer; and (4) the benevolent lecturer. The preliminary results of this pilot study showed an articulated and multi-dimensional representation of the meanings of lecturer competence from the students’ point of view and lay the foundations for a broader quantitative study on the conceptions concerning lecturer competence.
Image Deblurring Aided by Low-Resolution Events
Authors: Wang Zhouxia , Ren Jimmy , Zhang Jiawei , Luo Ping
Published: February 2022

Due to the limitation of event sensors, the spatial resolution of event data is relatively low compared to the spatial resolution of the conventional frame-based camera. However, low-spatial-resolution events recorded by event cameras are rich in temporal information which is helpful for image deblurring, while intensity images captured by frame cameras are in high resolution and have potential to promote the quality of events. Considering the complementarity between events and intensity images, an alternately performed model is proposed in this paper to deblur high-resolution images with the help of low-resolution events. This model is composed of two components: a DeblurNet and an EventSRNet. It first uses the DeblurNet to attain a preliminary sharp image aided by low-resolution events. Then, it enhances the quality of events with EventSRNet by extracting the structure information in the generated sharp image. Finally, the enhanced events are sent back into DeblurNet to attain a higher quality intensity image. Extensive evaluations on the synthetic GoPro dataset and real RGB-DAVIS dataset have shown the effectiveness of the proposed method.
Analysis and Design of a Wideband Low-Noise Amplifier with Bias and Parasitic Parameters Derived Wide Bandpass Matching Networks
Authors: Zhao Jinxiang , Wang Feng , Yu Hanchao , Zhang Shengli , Wang Kuisong , Liu Chang , Wan Jing , Liang Xiaoxin , Yan Yuepeng
Published: February 2022

This paper proposes a 110% relative bandwidth (RBW) low-noise amplifier (LNA) for broadband receivers with flat gain, low noise and high linearity. Bias and parasitic parameters derived wide bandpass (BPDWB) matching networks and a cascode with dual feedbacks are introduced for broadband performance. Matching network design procedures are demonstrated, and results show that the frequency response of the network fits the target impedance well from 1 GHz to 3.5 GHz. The proposed BPDWB network improves the design efficiency and enhances the prediction accuracy of impedance matching. The proposed LNA in 0.25 μm GaAs pseudomorphic high electron mobility transistor (GaAs pHEMT) technology realizes a minimum NF of 0.45 dB at 1.6 GHz where the NF is less than 0.55 dB within the operating frequency band. A flat gain of 22.5–25.2 dB is achieved with the input voltage standing wave ratio (VSWR) below 1.22 and output VSWR less than 2.5. In addition, the proposed LNA has good linearity where the output third-order intercept point (OIP3) is better than +31.5 dBm, and the output 1 dB compression point (OP1dB) is better than +19 dBm over the wide frequency range.
Study on an Ultrasonic Combined Electro-Machining Control System with Composite Material Experiments
Authors: Chen Wanwan , Li Jing , Zhu Yongwei , Zhao Jianshe
Published: February 2022

Materials such as stainless steel, cemented carbide, metal matrix composites, etc., usually require combinations of multiple machining, due to their high hardness, high wear resistance, and other mechanical properties. Ultrasonic combined electro-machining (UCEM) is the preferred solution for the efficient machining of high hardness and high toughness products. However, the machining can deviate from the expected values for factors such as physical and chemical complexity and variability, as well as tool head wear, which can make it difficult to keep the process stable, thus leading to a decrease in machining efficiency. To address the above problems, this study constructed and optimized a UCEM detection and control system based on an analysis of the mutual coordination mechanism of each effects of combined machining, and proposed a machining short-circuit avoidance method based on inter-pulse voltage detection that can avoid the irreversible harm caused by the high current generated during electrode short-circuiting in electrolytic machining. This method could be of great value and significance in preventing workpiece burns and improving machining quality.
Wi-Fi-Based Location-Independent Human Activity Recognition with Attention Mechanism Enhanced Method
Authors: Ding Xue , Jiang Ting , Zhong Yi , Wu Sheng , Yang Jianfei , Zeng Jie
Published: February 2022

Wi-Fi-based human activity recognition is emerging as a crucial supporting technology for various applications. Although great success has been achieved for location-dependent recognition tasks, it depends on adequate data collection, which is particularly laborious and time-consuming, being impractical for actual application scenarios. Therefore, mitigating the adverse impact on performance due to location variations with the restricted data samples is still a challenging issue. In this paper, we provide a location-independent human activity recognition approach. Specifically, aiming to adapt the model well across locations with quite limited samples, we propose a Channel–Time–Subcarrier Attention Mechanism (CTS-AM) enhanced few-shot learning method that fulfills the feature representation and recognition tasks. Consequently, the generalization capability of the model is significantly improved. Extensive experiments show that more than 90% average accuracy for location-independent human activity recognition can be achieved when very few samples are available.
An Intelligent Data Analysis System Combining ARIMA and LSTM for Persistent Organic Pollutants Concentration Prediction
Authors: Yu Lu , Wu Chunxue , Xiong Neal
Published: February 2022

Persistent Organic Pollutants (POPs) are toxic and difficult to degrade, which will cause huge damages to human life and the ecological environment. Therefore, based on historical measurements, it is important to use intelligent methods and data analysis technologies to build an intelligent prediction system to accurately predict the future POPs concentrations in advance. This work has extremely important significance for policy formulation, human health, environmental protection and the sustainable development of society. Since the POPs concentrations sequence contains both linear and nonlinear components, this paper proposes an intelligent data analysis system combining autoregressive integrated moving average (ARIMA) and long short-term memory network (LSTM) to analyze and predict the POPs concentrations in the Great Lakes region. ARIMA is used to capture linear components while LSTM is used to process nonlinear components, which overcomes the deficiency of single models. Moreover, a one-class SVM algorithm is used to detect outliers during data preprocessing. Bayesian information criterion and grid search methods are also used to obtain the optimal parameter combinations of ARIMA and LSTM, respectively. This paper compares our intelligent data analysis system with other single baseline models by using multiple evaluation indicators and finds that our system has the smallest MAE, RMSE and SMAPE values on all datasets. Meanwhile, our system can predict the trends of concentration changes well and the predicted values are closer to true values, which prove that it can effectively improve the precision of prediction. Finally, our system is used to predict concentration values of sites in the Great Lakes region in the next 5 years. The predicted concentrations present a large fluctuation trend in each year, but the overall trend is downward.
Heat and Mass Transfer by Vapour in Freezing Soils
Authors: Sarsembayeva Assel , Zhussupbekov Askar , Collins Philip E. F.
Published: February 2022

Vapour mass transfer is often underestimated when designing the bases for structures in frost susceptible soils. Intensive and long-term vapour transport may lead to excessive frost heaving and associated issues. A vapour transport model and the algorithm of its calculation is presented in this study based on the results of experimental freeze–thaw cycles of nine soil samples with varied density. The temperature field distribution, air voids volume and the energy comprising latent heat for the phase transition and heat extracted during the temperature drop are the main parameters for determining the vapour velocity and the amount of ice formed. According to the results, the average speed of vapour transport in frozen soils was about 0.4 m/h. The amount of ice built in 1 h during uniaxial freezing due to the saturated vapour pressure difference was 1.64 × 10−5–3.6 × 10−⁵ g/h in loose samples and 1.41 × 10−⁶ g/h to 5.61 × 10−⁷ g/h in dense samples of 10 cm diameter and 10 cm high sections. The results show that vapour mass transfer can increase the risk of ice growth and related problems.
Comparison of Pyrolysis and Combustion Processes of Vinyl Floor Panels Using Thermogravimetric Analysis (TG-FTIR) in Terms of the Circular Economy
Authors: Kajda-Szcześniak Małgorzata , Czop Monika
Published: February 2022

The article analyzes the thermal degradation in the inert and oxidative atmosphere of waste vinyl panels, the main component of which is PVC. Both pyrolysis and incineration of plastic waste are difficult, complex and multifaceted processes due to several physical and chemical phenomena occurring during their performance. The coupled TG-MS (thermogravimetry-mass spectrometry) analysis combined with the Fourier transform infrared spectrometry (TG-FTIR) analysis was used to identify the decomposition mechanisms of waste vinyl panels. Thermogravimetric tests were carried out for two heating rates of 5 and 20 K/min in the temperature range of 40–1000 °C, mass losses were determined, and products resulting from thermal degradation were identified. It was found that the individual components decompose at different temperatures depending on the heating rate and the choice of an inert or oxidative atmosphere. Vinyl floor panels were treated in terms of secondary raw material, which, in the light of the circular economy, may constitute a potential energy or chemical resource.
Anomaly Detection in Cyclic Communication in OT Protocols
Authors: Smolarczyk Milosz , Plamowski Sebastian , Pawluk Jakub , Szczypiorski Krzysztof
Published: February 2022

This paper demonstrates the effectiveness of using anomaly detection in cyclic communication as a method aimed at protecting industrial installations from steganographic communication and a wide range of cyberattacks. The analysis was performed for a method based on deterministic finite automaton and the authors’ method using cycles. In this paper, we discuss the cycle detection algorithm and graph construction as well as demonstrate an anomaly detection method for cyberattack detection that utilizes stochastic elements, such as time-to-response and time-between-messages. We present a novel algorithm that combines finite automaton determinism modeling consecutive admissible messages with a time-domain model allowing for random deviations of regularity. The study was conducted for several test scenarios, including C&C steganographic channels generated using the Modbus TCP/IP protocol. Experimental results demonstrating the effectiveness of the algorithms are presented for both methods. All algorithms described in this paper are implemented and run as part of a passive warden system embedded in a bigger commercial IDS (intrusion detection system).
A New Climate Change Analysis Parameter: A Global or a National Approach Dilemma
Authors: Portillo Juan Nerea , Negro Valdecantos Vicente , del Campo José María
Published: February 2022

Climate change is an issue nowadays present in almost all of the media daily, but information can be manipulated very easily. It is a fact that, in the last decades, greenhouse gas emissions have multiplied, and to tackle climate change efficiently, it is necessary to analyze their origin and their relationship with regards to countries, population, production, etc. When analyzing a country’s emissions, not only the total emissions, but also the emissions in relation to its population, production, etc., should be considered. In this paper, a new parameter (CE2N) that merges total emissions, and emissions per capita and per GDP is proposed and applied, obtaining, for the first time, a unified and universal parameter that considers the emission efficiency and total emissions at the same time and can be used in all countries. We validated this new parameter with its implementation in previous environmental models, and the results obtained showed that CE2N would help to increase the transparency and objectivity of these models, giving more weight to emission efficiency, rather than other, more subjective criteria previously used. In addition, CE2N could be implemented in future international agreements, being beneficial not only for the scientific community, but also for policymakers.
The Impact of Water Hammer on Hydraulic Power Units
Authors: Lupa Sorin-Ioan , Gagnon Martin , Muntean Sebastian , Abdul-Nour Georges
Published: February 2022

Water hammer influences the life cycle of hydraulic passages and may even cause catastrophic structural failures. Several catastrophic failures of hydraulic power units have been reported in the literature due to the effects of transient regimes. The objective of the study is to highlight the global trend in water hammer assessment and to quantify the effect of factors influencing overpressure in hydraulic passages during load rejection in different hydropower plants. A brief and concise literature review is conducted to document the parameters associated with the water hammer phenomenon and to thereby identify the necessary prerequisites to validate theoretical and numerical results against experimental data. The purpose of the analysis is to identify extreme transient loads on hydraulic passages in order to properly adapt hydropower unit operation, to make recommendations for design and industry, and to guide the progress of adapted models and numerical simulations to capture complex phenomena. Empirical correlations are determined based on the experimental data that are transferable from one unit to another, even if a deep flow analysis is performed. The experimental results confirm that the rapid closure rate of the guide vanes has a significant impact on the phenomenon. A third order polynomial equation is applied to capture the general overpressure trends. Equation parameters change from case to case depending on the type of hydraulic power unit, closing rate and the type of hydraulic passage. The results confirm also that overpressure values depend significantly on other factors, some of which are not usually taken into account (e.g., runner speed). Experimental correlations make it possible to understand the water hammer phenomenon, which could help not just assessing and optimizing loads, but also verifying and validating more complex physical models, to ensure that hydraulic passages are reliable. A well-documented analysis also makes it possible to optimize equipment design, improve and adapt maintenance programs and to recommend appropriate operating parameters to increase equipment lifespan, while preventing incidents.
Optimizing Multi Cross-Docking Systems with a Multi-Objective Green Location Routing Problem Considering Carbon Emission and Energy Consumption
Authors: Meidute-Kavaliauskiene Ieva , Sütütemiz Nihal , Yıldırım Figen , Ghorbani Shahryar , Činčikaitė Renata
Published: February 2022

Cross-docking is an excellent way to reduce the space required to store goods, inventory management costs, and customer order delivery time. This paper focuses on cost optimization, scheduling incoming and outgoing trucks, and green supply chains with multiple cross-docking. The three objectives are minimizing total operating costs, truck transportation sequences, and carbon emissions within the supply chain. Since the linear programming model is an integer of zero and one and belongs to NP-hard problems, its solution time increases sharply with increasing dimensions. Therefore, the non-dominated sorting genetic algorithm-II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) were used to find near-optimal solutions to the problem. Then, these algorithms were compared with criteria such as execution time and distance from the ideal point, and the superior algorithm in each criterion was identified.
Numerical Simulation of the Cleaning Performance of a Venturi Scrubber
Authors: Khadra Haouari , Kouider Rahmani , Toufik Tayeb Naas , Al-Kassir Awf , Carrasco-Amador Juan Pablo
Published: February 2022

Industrial applications need to use different systems for the problem of gas cleaning. A lot of processes have been developed, such as the use of a venturi for gas cleaning and pollution reduction. Additionally, several studies have been developed especially in terms of pressure drop because it is one of the main parameters to determine its efficiency. While the phenomenon of mass transfer in a venturi scrubber has not found much attention, in the present study, a mass transfer two-dimensional simulation is developed for gasification gas cleaning through a venturi scrubber with boundary conditions represented in air inlet velocities of 10, 15, and 20 m/s and water inlet mass flow of 0.02, 0.04 and 0.06 kg/s. In this work, Navier–Stokes equations are solved numerically and the mass transfer technique is treated by the volume of fluid (VOF) model, using CFD software. The obtained results were analyzed by presenting the mass fraction, velocity and pressure contours, and profiles. The probability density function (PDF) of mass transfer is studied too, showing how the removal efficiency of the venturi scrubber increases with a decrease in the liquid flow rate and an increase in the gas velocity. Therefore, the results show that the proposed venturi has the best mass transfer performance with a PDF that reaches 97.6 for velocity liquid of 20 m/s and the removal efficiency showed higher values at low liquid flow rates.
Comparison of China’s Biomass Combustion Power Generation with Different Installed Capacities
Authors: Zhu Xiaocheng , Zhang Yanru , Wang Zhenzhong , Pan Xunzhang
Published: February 2022

As a major technical route to utilize biomass energy, biomass combustion power generation (BCPG) has been shown to be of environmental and economic significance. According to the operating experience, the installed capacity has a decisive impact on the operation and economic return of BCPG projects. In China, an installed capacity of either 30 MW or 12 MW is often chosen for constructing a BCPG project. To explore which one is more suitable for China, this paper uses actual operating data to compare the operation performance and techno-economics of two representative BCPG projects with an installed capacity of 30 MW and 12 MW. The results show that the operation situation and electricity production of the 30 MW project are better than those of the 12 MW project. The 30 MW project has a lower biomass consumption than the 12 MW project to produce per unit of electricity. The Internal Rate of Return (IRR) of the 30 MW project is greater than the industry benchmark in China and is almost three times the IRR of the 12 MW project. Therefore, it is recommended to construct BCPG projects with installed capacity of 30 MW in China.
National Culture and the Market Development of Battery Electric Vehicles in 21 Countries
Authors: Novotny Adam , Szeberin Inez , Kovács Sándor , Máté Domicián
Published: February 2022

Electric vehicles (EVs) have become a symbol of the fight against climate change. However, in many countries, the market development of EVs is sluggish, and adoption rates greatly vary worldwide. This study examines the impact of Hofstede’s six dimensions of national culture on the development of the electric car market using sales data from 2019 and 2020 in 21 OECD countries. Results of (OLS) linear regression analyses show that uncertainty avoidance, individualism, masculinity, and indulgence have a significantly negative impact on the sales of battery electric cars, while long-term orientation positively influences their market share. The results indicate that national culture is an important cross-country factor that influences the rate and direction of the adoption electric cars. The research also explains how cultural values are translated into the purchase of EVs and provides marketers and policymakers with an insight into how they can increase the spread of alternative-fuel vehicles.
Optimal Design of Automatic Generation Control Based on Simulated Annealing in Interconnected Two-Area Power System Using Hybrid PID—Fuzzy Control
Authors: Magzoub Muntasir A. , Alquthami Thamer
Published: February 2022

Electricity demand continues to rise on a daily basis. The most difficult task is ensuring that customers have access to reliable, high-quality electricity regardless of the weather. Automatic generation control (AGC) accomplishes this by keeping the target output power and frequency constant despite load fluctuations. This paper presents a hybrid PID-fuzzy controller for optimal automatic generation control in a two-area interconnected power system. A comparative analysis of the proposed controller was performed with the PID controller. The parameters of the both controllers were developed by simulated annealing (SA) techniques in order to obtain the best dynamic performance. MATLAB Simulink software was used to simulate the models. The results of the simulation for the two-area power system based on simulated annealing using the hybrid PID–fuzzy controller showed superior performance in comparison to a conventional PID controller.
Multiple Fault Detection in Induction Motors through Homogeneity and Kurtosis Computation
Authors: Martinez-Herrera Ana L. , Ferrucho-Alvarez Edna R. , Ledesma-Carrillo Luis M. , Mata-Chavez Ruth I. , Lopez-Ramirez Misael , Cabal-Yepez Eduardo
Published: February 2022

In the last few years, induction motor fault detection has provoked great interest among researchers because it is a fundamental element of the electric-power industry, manufacturing enterprise, and services. Hence, considerable efforts have been carried out on developing reliable, low-cost procedures for fault diagnosis in induction motors (IM) since the early detection of any failure may prevent the machine from suffering a catastrophic damage. Therefore, many methodologies based on the IM startup transient current analysis have been proposed whose major disadvantages are the high mathematical complexity and demanding computational cost for their development. In this study, a straightforward procedure was introduced for identifying and classifying faults in IM. The proposed approach is based on the analysis of the startup transient current signal through the current signal homogeneity and the fourth central moment (kurtosis) analysis. These features are used for training a feed-forward, backpropagation artificial neural network used as a classifier. From experimentally obtained results, it was demonstrated that the brought-in scheme attained high certainty in recognizing and discriminating among five induction motor conditions, i.e., a motor in good physical condition (HLT), a motor with one broken rotor bar (1BRB), a motor with two broken rotor bars (2BRB), a motor with damage on the bearing outer race (BRN), and a motor with an unbalanced mechanical load (UNB).