bluuebunny/crossref_metadata_2025 huggingface dataset:
Combined Raman Spectroscopy and Magneto-Transport Measurements in Disordered Graphene: Correlating Raman D Band and Weak Localization Features
Authors: Childres Isaac , Qi Yaping , Sadi Mohammad , Ribeiro John , Cao Helin , Chen Yong
Published: August 2022

Although previous studies have reported the Raman and weak localization properties of graphene separately, very few studies have examined the correlation between the Raman and weak localization characterizations of graphene. Here, we report a Raman spectroscopy and low-magnetic-field electronic transport study of graphene devices with a controlled amount of defects introduced into the graphene by exposure to electron-beam irradiation and oxygen plasma etching. The relationship between the defect correlation length (LD), calculated from the Raman “D” peak, and the characteristic scattering lengths, Lϕ, Li and L*, computed from the weak localization effects measured in magneto-transport was investigated. Furthermore, the effect on the mean free path length due to the increasing amounts of irradiation incident on the graphene device was examined. Both parameters—including LD and Lϕ—decreased with the increase of irradiation, which was shown to be related to the increase of disorder through the concomitant decrease in the mean free path length, l. Although these are similar trends that have been observed separately in previous reports, this work revealed a novel nonlinear relationship between LD and Lϕ, particularly at lower levels of disorder. These findings are valuable for understanding the correlation between disorder in graphene and the phase coherence and scattering lengths of its charge carriers.
Evolution of Cos–Gaussian Beams in the Periodic Potential Optical Lattice
Authors: Wen Bing , Deng Yangbao , Wei Jiamou , Chen Depeng , Leng Xiaoling
Published: August 2022

The evolution of Cos−Gaussian beams in periodic potential optical lattices is theoretically and numerically investigated. By theoretical analysis, a breathing soliton solution of the Gross–Pitaevskii equation with periodic potential is obtained, and the period of the breathing soliton is solved. In addition, the evolution of Cos−Gaussian beams in periodic potential optical lattices is numerically simulated. It is found that breathing solitons generate by appropriately choosing initial medium and beam parameters. Firstly, the effects of the initial parameters of Cos−Gaussian beams (initial phase and width) on its initial waveform and the propagation characteristics of breathing soliton are discussed in detail. Then, the influence of the initial parameters (modulation intensity and modulation frequency) of a photonic lattice on the propagation characteristics of breathing solitons is investigated. Finally, the effects of modulation intensity and modulation frequency on the width and period of the breathing soliton are analyzed. The results show that the number of breathing solitons is manipulated by controlling the initial parameters of Cos−Gaussian beams. The period and width of a breathing soliton are controlled by manipulating the initial parameters of a periodic photonic lattice. The results provide some theoretical basis for the generation and manipulation of breathing solitons.
Phase Diagram Determination and Process Development for Continuous Antisolvent Crystallizations
Authors: Mack Corin , Hoffmann Johannes , Sefcik Jan , ter Horst Joop H.
Published: August 2022

The development of an antisolvent crystallization process requires the construction of an accurate phase diagram for this ternary system of compound, solvent and antisolvent, preferably as a function of temperature. This study gives an efficient methodology to systematically determine such antisolvent phase diagrams, exemplified with four model compounds: Sodium bromate, DL-Asparagine Monohydrate, Mefenamic acid and Lovastatin. Using clear point temperature measurements, single solvent and mixed solvent-antisolvent solubilities are obtained, showing strongly non-linear solubility dependencies as well as more complex solubility behaviour as a function of antisolvent fraction. A semi-empirical model equation is used to describe the phase diagram of the antisolvent crystallization system as a function of both temperature and antisolvent fraction. The phase diagram model then allows for the identification of condition ranges for optimal productivity, yield, and suspension density in continuous antisolvent crystallization processes.
Immune Biomarkers in Blood from Sarcoma Patients: A Pilot Study
Authors: Munisamy Sarmini , Radhakrishnan Ammu Kutty , Ramdas Premdass , Samuel Priscilla Josephine , Singh Vivek Ajit
Published: August 2022

The main role of the host immune system is to identify and eliminate cancer cells, which is a complex process, but it is not a fail-safe mechanism. Many sarcoma patients succumb to this disease despite treatments rendered. The aim of this pilot study was to compare the levels of CD4+ T-cells, T-regulatory (Treg) cells, and cytokines such as tumor necrosis factor-alpha (TNF-α), interferon-gamma (IFN-γ), interleukin-17A (IL-17A), and transforming growth factor-beta-1 (TGF-β1) in peripheral blood leukocytes of sarcoma patients and healthy controls. For gene expression studies, total ribonucleic acid (RNA) was extracted from peripheral blood leukocytes and genes that were differentially regulated in peripheral blood leukocytes of sarcoma patients compared with healthy controls were determined using a commercial T-helper cell differentiation quantitative polymerase chain reaction (qPCR) array. Flow cytometer analysis was performed on blood samples from 26 sarcoma patients and 10 healthy controls to identify the levels of CD4+ T-cells and T-reg cells. The level of cytokines in plasma and culture supernatant were quantified using commercial enzyme-linked immunosorbent assay (ELISA) kits. A marked reduction in the percentage of CD4+ T-cells (p = 0.037) and levels of TNF-α (p = 0.004) and IFN-γ (0.010) was observed in sarcoma patients. Gene expression analysis showed five genes (homeobox A10 (HOXA10), GATA binding protein 3 (GATA3), prostaglandin D2 receptor 2 (PTGDR2), thymocyte selection associated high mobility group box (TOX), and C-C motif chemokine receptor 3 (CCR3)) were dysregulated (p < 0.05) in sarcoma patients. This study suggests that T-helper-1 immune responses are reduced in sarcoma patients.
Phylogeny of Trachelomonas and Strombomonas (Euglenaceae) Based on Morphological and Molecular Data
Authors: Jiang Xiaodie , Chen Xi , Pang Wanting , Wang Quanxi
Published: August 2022

The classification of Trachelomonas and Strombomonas is based on the morphology of loricae, which may not reflect phylogenetic relationships. There are different views on the relationship between the two genera. It is thus important for researchers to classify the two genera based on more characteristics besides loricae, such as protoplast and molecular data, and to establish a natural classification system. In this study, 29 strains (13 species) of Trachelomonas and 12 strains (eight species) of Strombomonas were collected from various locations in China. The morphological characteristics of Trachelomonas and Strombomonas were observed in the field and culture conditions, and the sequences of nuclear SSU rDNA, nuclear LSU rDNA, plastid-encoded LSU rDNA and plastid-encoded LSU rDNA of strains were obtained. We constructed a phylogenetic tree by combining four gene sequences with maximum likelihood and Bayesian methods. Based on the development of the loricae, it was found that the shape of the loricae and the presence or absence of the collar were relatively stable in culture, while the length of the collar presence or absence of spines and the color of the loricae changed. The phylogenetic tree showed that Trachelomonas and Strombomonas were sister branches, which supported Trachelomonas and Strombomonas as independent genera. Taxa in the genus Strombomonas sorted into two clades and Trachelomonas sorted into five strongly supported clades. Key morphological features could be attributed to each of the clades.
Diversity, Ecological and Traditional Knowledge of Pteridophytes in the Western Himalayas
Authors: Khoja Aadil Abdullah , Haq Shiekh Marifatul , Majeed Muhammad , Hassan Musheerul , Waheed Muhammad , Yaqoob Umer , Bussmann Rainer W. , Alataway Abed , Dewidar Ahmed Z. , Al-Yafrsi Mohamed , Elansary Hosam O. , Yessoufou Kowiyou , Zaman Wajid
Published: August 2022

Pteridophytes have been used by humans for millennia, but in comparison to flowering plants, the documentation of their traditional uses is still neglected; as a result, they must be highlighted and popularized. The present study was carried out from January 2019 to November 2021 to gather ecological and traditional use information on pteridophytes from local inhabitants of the Kashmir valley via semi-structured personal interviews and group discussions. We recorded 58 pteridophyte species belonging to 13 families. The distributions of the species among the families were unequal, with four families constituting more than half of the total species (Dryopteridaceae 26%, Woodsiaceae 17%, Aspleniaceae 14%, and Pteridaceae (14%). The highest numbers of species (45%) were found growing on the forest floor, followed by those growing in rock crevices (26%). This was supported further by a cluster analysis, which identified two primary clusters based on the species presence in different habitats. Half of the species (56%) were reported from altitudes below 2000m, followed by 19% from 2001–2500m, and 8% (e.g., Deparia allantodioides, Dryopteris xanthomelas, Asplenium viride) from 3001–3500m. Among the documented species (N = 58), only 28 species had a traditional usage (as medicine, vegetables, for oral hygiene, and for veterinary use). The aerial parts were most commonly used (64%) followed by the rachis (18%). The highest use value was observed for Diplazium maximum and the lowest for Asplenium fontanum. The findings of our study contribute baseline data to fill the existing knowledge gaps on ecological and traditional knowledge of pteridophytes in the Himalayas.
Preanalytical Variables in the Analysis of Mitochondrial DNA in Whole Blood and Plasma from Pancreatic Cancer Patients
Authors: Randeu Hannah , Bronkhorst Abel J. , Mayer Zsuzsanna , Oberhofer Angela , Polatoglou Eleni , Heinemann Volker , Haas Michael , Boeck Stefan , Holdenrieder Stefan
Published: August 2022

Given the crucial role of mitochondria as the main cellular energy provider and its contribution towards tumor growth, chemoresistance, and cancer cell plasticity, mitochondrial DNA (mtDNA) could serve as a relevant biomarker. Thus, the profiling of mtDNA mutations and copy number variations is receiving increasing attention for its possible role in the early diagnosis and monitoring therapies of human cancers. This applies particularly to highly aggressive pancreatic cancer, which is often diagnosed late and is associated with poor prognosis. As current diagnostic procedures are based on imaging, tissue histology, and protein biomarkers with rather low specificity, tumor-derived mtDNA mutations detected from whole blood represents a potential significant leap forward towards early cancer diagnosis. However, for future routine use in clinical settings it is essential that preanalytics related to the characterization of mtDNA in whole blood are thoroughly standardized, controlled, and subject to proper quality assurance, yet this is largely lacking. Therefore, in this study we carried out a comprehensive preanalytical workup comparing different mtDNA extraction methods and testing important preanalytical steps, such as the use of different blood collection tubes, different storage temperatures, length of storage time, and yields in plasma vs. whole blood. To identify analytical and preanalytical differences, all variables were tested in both healthy subjects and pancreatic carcinoma patients. Our results demonstrated a significant difference between cancer patients and healthy subjects for some preanalytical workflows, while other workflows failed to yield statistically significant differences. This underscores the importance of controlling and standardizing preanalytical procedures in the development of clinical assays based on the measurement of mtDNA.
Reproducibility and Reliability of Spectralis II OCT Angiography Vascular Measurements
Authors: Pastore Marco , Grotto Alberto , Vezzoni Francesca , Gaggino Andrea , Milan Serena , Gouigoux Stefano , Guerin Pier , Vinciguerra Alex , Cirigliano Gabriella , Tognetto Daniele
Published: August 2022

Purpose: to investigate the reproducibility and reliability of OCT-A vascular measurements using Heidelberg Spectralis II OCT-A. Methods: a prospective study involving a single eye of patients aged 18 or older with no ocular disease. In order to investigate the reliability of the first and second OCT-A scans, the coefficient of variation of the foveal avascular zone (FAZ) and the vessel density (VD) in the superficial (SCP), intermediate (ICP) and deep capillary plexus (DCP) were calculated. Results: A total of 75 eyes were included in the study. The mean FAZ in the first and second scan was 0.36 × 0.13 mm2 and 0.37 × 0.12 mm2, respectively, in the SCP, 0.23 × 0.10 mm2 and 0.23 × 0.09 mm2 in the ICP, and 0.42 × 0.11 mm2 and 0.43 × 0.12 mm2 in the DCP. The overall VD was 36.05 × 9.01 and 35.33 × 9.92 at the first and second scan, respectively, in the SCP, 21.87 × 5.00 and 21.32 × 5.56 in the ICP, and 23.84 × 6.53 and 23.20 × 6.83 in the DCP. No statistically significant differences in FAZ measurements and VD in all sectors of each capillary plexus were observed between the first and second scan (p > 0.05). Conclusion: our study demonstrated the good reproducibility and reliability of OCT-A vascular measurements in the analysis of the FAZ and the quantification of VD in each capillary plexus of the retina.
Pathogenic and Prognostic Roles of Paraneoplastic Leukocytosis in Cervical Cancer: Can Genomic-Based Targeted Therapies Have a Role? A Literature Review and an Emblematic Case Report
Authors: Madeddu Clelia , Sanna Elisabetta , Nemolato Sonia , Mulas Olga , Oppi Sara , Scartozzi Mario , La Nasa Giorgio , Maccio Antonio
Published: August 2022

Tumor-associated leukocytosis has been associated with poor prognosis in cervical cancer. Leukemoid reaction (i.e., white blood cell count > 40,000/μL) is defined paraneoplastic (PLR) when it occurs in the presence of a cytokine-secreting tumor (CST) without neoplastic bone marrow infiltration. Cervical cancers displaying PLR represent a peculiar entity characterized by a rapidly progressive behavior typically associated with chemo-radioresistance. The present paper aims to review the literature about the pathogenetic mechanisms of PLR and its prognostic role in cervical cancer. Moreover, it reports the emblematic case of a patient with an advanced cervical cancer associated with PLR that was chemotherapy resistant. The patient underwent a palliative cytoreductive surgery of high complexity, obtaining a temporary regression of PLR. The tumor sample stained positive for G-CSF and IL-6, thus indicating a CST. Notably, the tumor genomic analysis revealed a PI3CKA mutation. Therefore, at the instrumental evidence of a rapidly progressive disease relapse, which was accompanied by reappearance of PLR, we started a targeted treatment with a selective PIK3 inhibitor alpesilib combined with the JAK1-2 inhibitor ruxolitinib. We achieved a relief of symptoms and leukocytosis; however, severe side effects necessitated the treatment suspension. In conclusion, as therapeutic strategies for cancer with PLR are scarcely reported in literature, our study could contribute to expand our understanding of the topic and provide a basis for further research.
Histological Findings in Kidney Biopsies of Patients with Monoclonal Gammopathy—Always a Surprise
Authors: Klank David , Hoffmann Martin , Porubsky Stefan , Bergner Raoul
Published: August 2022

Background: The simultaneous occurrence of impaired kidney function and paraproteinemia is common in our constantly aging society. Both can be independent entities; however, renal insufficiency can also be caused by the paraprotein. We assessed all kidney biopsies in patients with monoclonal gammopathy in our clinic over the past 20 years and evaluated the histological results. Methods: Biopsies were systematically performed in nearly all patients with paraproteinemia and impaired kidney function (n = 178). The histological findings were systematically evaluated and correlated with the initial clinical diagnosis. Results: We found cast nephropathy (CN) in n = 66 (37.1%) biopsies, AL amyloidosis in n = 31 (17.4%) biopsies, monoclonal immunoglobulin deposition disease (MIDD) in n = 7 (3.9%) biopsies and other renal diseases (ORDs) in n = 74 (41.6%) biopsies. In the latter group, paraprotein-associated changes were found in 37 of 74 (50%) patients, whereas paraprotein-independent changes were found in the other half. Whereas, in the group of patients with MGUS, the findings were heterogenous, most of the patients with known multiple myeloma (MM) or B-NHL showed malignancy-associated changes in the kidney. The biopsy changed the diagnoses in a significant proportion of the patients: The group of patients with MM grew from 71 to 112 patients, whereas, in the MGUS group, only 31 of 44 patients remained. Conclusion: Kidney biopsies in patients with paraproteinemia and renal impairment show a wide range of findings that can lead to a change in diagnosis.
Rényi Entropy in Statistical Mechanics
Authors: Fuentes Jesús , Gonçalves Jorge
Published: August 2022

Rényi entropy was originally introduced in the field of information theory as a parametric relaxation of Shannon (in physics, Boltzmann–Gibbs) entropy. This has also fuelled different attempts to generalise statistical mechanics, although mostly skipping the physical arguments behind this entropy and instead tending to introduce it artificially. However, as we will show, modifications to the theory of statistical mechanics are needless to see how Rényi entropy automatically arises as the average rate of change of free energy over an ensemble at different temperatures. Moreover, this notion is extended by considering distributions for isospectral, non-isothermal processes, resulting in relative versions of free energy, in which the Kullback–Leibler divergence or the relative version of Rényi entropy appear within the structure of the corrections to free energy. These generalisations of free energy recover the ordinary thermodynamic potential whenever isothermal processes are considered.
The Effects of Corporate Social Responsibility (CSR) on Consumer Behaviour in Online Commerce: The Case of Cosmetics during the COVID-19 Pandemics
Authors: Popa Ion , Nicolescu Luminița , Ștefan Simona Cătălina , Popa Ștefan Cătălin
Published: August 2022

Corporate social responsibility (CSR) is a trend that manifests on a global level. The positive effects of CSR initiatives depend on the reaction of stakeholders, among which customers represent an important category. The purpose of this paper was to analyse the impact that CSR initiatives of cosmetics companies have on customer behaviour in both the short-term (buying intention) and the long-term (client loyalty) in the case of electronic commerce. Starting from the existing literature, the conceptual model proposed different dimensions of CSR as influencers (legal and ethical, philanthropic and community services, respect for environment, respect for consumers), and as mediators, which were considered as the brand trust and the competitive advantage of the company. The research method used was quantitative with the empirical data being collected from 1265 actual and potential consumers of cosmetic products. The hypotheses were tested using the partial least squares structural equation modelling (PLS-SEM). The main findings illustrated positive relationships between CSR and both buying intention and client loyalty, as the two facets of consumer behaviour. The interpretation is that CSR activities can increase both the consumer intentions to buy cosmetics products provided by CSR-involved companies, and increase the long-term customer loyalty for these companies. The research also provided evidence for a strong mediation effect of brand trust for both sides of customer behaviour. This illustrates that when brand trust is higher the effect of CSR initiatives on customer behaviour increases. The paper includes theoretical and practical contributions associated to the results of the research.
Methods of Intelligent Control in Mechatronics and Robotic Engineering: A Survey
Authors: Zaitceva Iuliia , Andrievsky Boris
Published: August 2022

Artificial intelligence is becoming an increasingly popular tool in more and more areas of technology. New challenges in control systems design and application are related to increased productivity, control flexibility, and processing of big data. Some kinds of systems require autonomy in real-time decision-making, while the other ones may serve as an essential factor in human-robot interaction and human influences on system performance. Naturally, the complex tasks of controlling technical systems require new modern solutions, but there remains an inextricable link between control theory and artificial intelligence. The first part of the present survey is devoted to the main intelligent control methods in technical systems. Among them, modern methods of adaptive and optimal control, fuzzy logic, and machine learning are considered. In its second part, the crucial achievements in intelligent control applications in robotic and mechatronic systems over the past decade are considered. The references are structured according to the type of such common control problems as stabilization, controller tuning, identification, parametric optimization, iterative learning, and prediction. In the conclusion, the main problems and tendencies toward intelligent control methods improvement are outlined.
Image Denoising Based on GAN with Optimization Algorithm
Authors: Zhu Min-Ling , Zhao Liang-Liang , Xiao Li
Published: August 2022

Image denoising has been a knotty issue in the computer vision field, although the developing deep learning technology has brought remarkable improvements in image denoising. Denoising networks based on deep learning technology still face some problems, such as in their accuracy and robustness. This paper constructs a robust denoising network based on a generative adversarial network (GAN). Since the neural network has the phenomena of gradient dispersion and feature disappearance, the global residual is added to the autoencoder in the generator network, to extract and learn the features of the input image, so as to ensure the stability of the network. On this basis, we proposed an optimization algorithm (OA), to train and optimize the mean and variance of noise on each node of the generator. Then the robustness of the denoising network was improved through back propagation. Experimental results showed that the model’s denoising effect is remarkable. The accuracy of the proposed model was over 99% in the MNIST data set and over 90% in the CIFAR10 data set. The peak signal to noise ratio (PSNR) and structural similarity (SSIM) values of the proposed model were better than the state-of-the-art models in the BDS500 data set. Moreover, an anti-interference test of the model showed that the defense capacities of both the fast gradient sign method (FGSM) and project gradient descent (PGD) attacks were significantly improved, with PSNR and SSIM values decreased by less than 2%.
Position Distribution Matters: A Graph-Based Binary Function Similarity Analysis Method
Authors: Pan Zulie , Wang Taiyan , Yu Lu , Yan Yintong
Published: August 2022

Binary function similarity analysis evaluates the similarity of functions at the binary level to aid program analysis, which is popular in many fields, such as vulnerability detection, binary clone detection, and malware detection. Graph-based methods have relatively good performance in practice, but currently, they cannot capture similarity in the aspect of the graph position distribution and lose information in graph processing, which leads to low accuracy. This paper presents PDM, a graph-based method to increase the accuracy of binary function similarity detection, by considering position distribution information. First, an enhanced Attributed Control Flow Graph (ACFG+) of a function is constructed based on a control flow graph, assisted by the instruction embedding technique and data flow analysis. Then, ACFG+ is fed to a graph embedding model using the CapsGNN and DiffPool mechanisms, to enrich information in graph processing by considering the position distribution. The model outputs the corresponding embedding vector, and we can calculate the similarity between different function embeddings using the cosine distance. Similarity detection is completed in the Siamese network. Experiments show that compared with VulSeeker and PalmTree+VulSeeker, PDM can stably obtain three-times and two-times higher accuracy, respectively, in binary function similarity detection and can detect up to six-times more results in vulnerability detection. When comparing with some state-of-the-art tools, PDM has comparable Top-5, Top-10, and Top-20 ranking results with respect to BinDiff, Diaphora, and Kam1n0 and significant advantages in the Top-50, Top-100, and Top-200 detection results.
A Compact mmWave MIMO Antenna for Future Wireless Networks
Authors: Khan Muhammad Imran , Khan Sarmadullah , Kiani Saad Hassan , Ojaroudi Parchin Naser , Mahmood Khalid , Rafique Umair , Qadir Muhammad Mansoor
Published: August 2022

This article presents a four-element multiple-input multiple-output (MIMO) antenna design for next-generation millimeter-wave (mmWave) communication systems. The single antenna element of the MIMO systems consists of a T-shaped and plow-shaped patch radiator designed on an ultra-thin Rogers RT/Duroid 5880 substrate. The dimensions of the single antenna are 10 × 12 mm2. The MIMO system is designed by placing four elements in a polarization diversity configuration whose overall dimensions are 24 × 24 mm2. From the measured results, it is observed that the MIMO antenna provides 9.23 GHz impedance bandwidth ranging from 22.43 to 31.66 GHz. In addition, without the utilization of any decoupling network, a minimum isolation of 25 dB is achieved between adjacent MIMO elements. Furthermore, the proposed MIMO antenna system is fabricated, and it is noted that the simulated results are in good agreement with the measured results. Through the achieved results, it can be said that the proposed MIMO antenna system can be used in 5G mmWave radio frequency (RF) front-ends.
Design and Simulation of a Novel Single-Chip Integrated MEMS Accelerometer Gyroscope
Authors: Gao Yang , Meng Lin , Tong Jinwu , Ruan Zhihu , Jia Jia
Published: August 2022

This paper presents the design and simulation of a single-chip integrated MEMS accelerometer gyroscope by integrating a Coriolis vibratory ring gyroscope and a differential resonant accelerometer into one single-chip structure, measuring both the acceleration and the angular velocity (or the angle). At the same time, it has the advantages of small volume, low cost, and high precision based on the characteristics of a ring gyroscope and resonant accelerometer. The proposed structure consists of a microring gyroscope and a MEMS resonant accelerometer. Tthe accelerometer is located inside the gyroscope and the two structures are concentric. The operating mechanisms of the ring gyroscope and the resonant accelerometer are first introduced. Then, the whole structure of the proposed single-chip integrated accelerometer gyroscope is presented, and the structural components are introduced in detail. Modal analysis shows the resonant frequencies of upper and lower DETFs in resonant accelerometer are 28,944.8 Hz and 28,948.0 Hz, and the resonant frequencies of the ring gyroscope (n=2) are 15,768.5 Hz and 15,770.3 Hz, respectively. The scale factor of the resonant accelerometer is calculated as 83.5 Hz/g by the analysis of the input–output characteristic. Finally, the thermal analysis fully demonstrates that the single-chip integrated accelerometer gyroscope has excellent immunity to temperature change.
Dynamic Modeling and Simulation of a Four-Wheel Skid-Steer Mobile Robot Using Linear Graphs
Authors: McCormick Eric , Lang Haoxiang , de Silva Clarence W.
Published: August 2022

This paper presents the application of the concepts and approaches of linear graph (LG) theory in the modeling and simulation of a four-wheel skid-steer mobile robotic system. An LG representation of the system is proposed, and the accompanying state-space model of the dynamics of a mobile robot system is evaluated using the associated LGtheory MATLAB toolbox, which was developed in our lab. A genetic algorithm (GA)-based parameter estimation method is employed to determine the system parameters, which leads to a very accurate simulation of the model. The developed model is then evaluated and validated by comparing the simulated LG model trajectory with the trajectory of an ROS Gazebo-simulated robot and experimental data obtained from the physical robotic system. The obtained results demonstrate that the proposed LG model, combined with the GA parameter estimation process, produces a highly accurate method of modeling and simulating a mobile robotic system.
Dim and Small Target Tracking Using an Improved Particle Filter Based on Adaptive Feature Fusion
Authors: Huo Youhui , Chen Yaohong , Zhang Hongbo , Zhang Haifeng , Wang Hao
Published: August 2022

Particle filters have been widely used in dim and small target tracking, which plays a significant role in navigation applications. However, their characteristics, such as difficulty of expressing features for dim and small targets and lack of particle diversity caused by resampling, lead to a considerable negative impact on tracking performance. In the present paper, we propose an improved resampling particle filter algorithm based on adaptive multi-feature fusion to address the drawbacks of particle filters for dim and small target tracking and improve the tracking performance. We first establish an observation model based on the adaptive fusion of the features of the weighted grayscale intensity, edge information, and wavelet transform. We then generate new particles based on residual resampling by combining the target position in the previous frame and the particles in the current frame with higher weights, with the tracking accuracy and particle diversity improving simultaneously. The experimental results demonstrate that our proposed method achieves a high tracking performance with a distance accuracy of 77.2% and a running speed of 106 fps, respectively, meaning that it will have a promising prospect in dim and small target tracking applications.
A Fortunate Refining Trip Recommendation Model
Authors: Abbas Rizwan , Amran Gehad Abdullah , Abdulraheem Ahmed A. , Hussain Irshad , Ghoniem Rania M. , Ewees Ahmed A.
Published: August 2022

Personalized travel recommendations propose locations of interest (LOIs) for users. The LOI sequence suggestion is more complicated than a single LOI recommendation. Only a few studies have considered LOI sequence recommendations. Creating a reliable succession of LOIs is difficult. The two LOIs that follow each other should not be identical or from the same category. It is vital to examine the types of subsequent LOIs when designing a sequence of LOIs. Another issue is that providing precise and accurate location recommendations bores users. It can be tedious and monotonous to look at the same types of LOIs repeatedly. Users may want to change their plans in the middle of a trip. The trip must be dynamic rather than static. To address these concerns in the recommendations, organize a customized journey by looking for continuity, implications, innovation, and surprising (i.e., high levels of amusement) LOIs. We use LOI-likeness and category differences between subsequent LOIs to build sequential LOIs. In our travel recommendations, we leveraged luck and dynamicity. We suggest a fortunate refining trip recommendation (FRTR) to address the issues of identifying and rating user pleasure. An algorithm oof compelling recommendation should offer what we are likely to enjoy and provide spontaneous yet objective components to maintain an open doorway to new worlds and discoveries. In addition, two advanced novel estimations are presented to examine the recommended precision of a sequence of LOIs: regulated precision (RP) and pattern precision (PP). They consider the consistency and order of the LOIs. We tested our strategy using data from a real-world dataset and user journey records from Foursquare dataset. We show that our system outperforms other recommendation algorithms to meet the travel interests of users.
Modeling and Design of Split-Pi Converter
Authors: Subramaniyan Geethanjali , Krishnasamy Vijayakumar , Mohammed Jagabar Sathik
Published: August 2022

High-power bidirectional dc–dc converters are being widely employed in renewable energy interfacing, energy storage, electric vehicle charging, military, aerospace, and marine applications. Among various bidirectional topologies documented in the literature for dc–dc power conversion, the split-pi converter invites special attention with regard to applications involving multi-phase systems requiring high-power density. This paper endeavors to present the small-signal modeling of the split-pi converter in its various operating modes. Subsequently, the dynamic characteristics of the converter are studied, and appropriate control design is presented for stable operation of the converter. Frequency response plots are illustrated, and a hardware prototype model of the converter is designed and implemented.
New Perspectives for Logistics Processes in the Energy Sector
Authors: Kulińska Ewa , Dendera-Gruszka Małgorzata
Published: August 2022

The publication analyzes the logistic processes taking place in the energy sector. The impact of the analyzed logistic processes is crucial for the alternative energy sources industry. This article focuses on home photovoltaic installations. The bases for further research are the previously identified stages of logistic processes related to photovoltaic installations. Individual, selected logistics processes and their impact on the implementation of photovoltaic installations have been described in detail together with the results of the research. The basis of the research was to conduct a survey among randomly selected people who have been in possession of a photovoltaic installation since 2018 in Poland. This article is an introduction to further research on the analysis of logistic processes in other branches of energy.
Artificial Neural Network Controller in Two-Area and Five-Area System with Security Attack and Game-Theory Based Defender Action
Authors: Khadarvali S. , Madhusudhan V. , Kiranmayi R.
Published: August 2022

Smart grids are the latest technology to generate and dispatch an optimal amount of power. Thus, there is a need for stability analysis in smart grid systems. If the smart grid is incorporated into the power system, then the phasor measurement unit (PMU) is used to measure the voltage, current, and frequency. Additionally, the central control unit monitors and controls the power. However, there is a possibility of inserting wrong data into the smart grid as the PMUs are transmitting the data through the Internet and other wireless protocols. There is a need to find solutions to this threat to make the power flow safe and secure in the future. In this paper, two-area load frequency control (LFC) is used for testing the game-theory based security treatment and improving the system’s stability by using an artificial neural network. The two-area system and five-area system are used to test the stability of the power system.
Convolutional Neural Network Identification of Stall Flow Patterns in Pump–Turbine Runners
Authors: Wu Junjie , Zhang Xiaoxi
Published: August 2022

Stall flow patterns occur frequently in pump turbines under off-design operating conditions. These flow patterns may cause intensive pressure pulsations, sudden increases in the hydraulic forces of the runner, or other adverse consequences, and are some of the most notable subjects in the study of pump turbines. Existing methods for identifying stall flow patterns are not, however, sufficiently objective and accurate. In this study, a convolutional neural network (CNN) is built to identify and analyze stall flow patterns. The CNN consists of input, convolutional, downsampling, fully connected, and output layers. The runner flow field data from a model pump–turbine are simulated with three-dimensional computational fluid dynamics and part of the classifiable data are used to train and test the CNN. The testing results show that the CNN can predict whether or not a blade channel is stalled with an accuracy of 100%. Finally, the CNN is used to predict the flow status of the unclassifiable part of the simulated data, and the correlation between the flow status and the relative flow rate in the runner blade channel is analyzed and discussed. The results show that the CNN is more reliable in identifying stall flow patterns than using the existing methods.
An Electromagnetic Wind Energy Harvester Based on Rotational Magnet Pole-Pairs for Autonomous IoT Applications
Authors: Roy Sajib , Kabir Md Humayun , Salauddin Md , Halim Miah A.
Published: August 2022

In this paper, we report a wind energy harvesting system for Internet of Things (IoT)-based environment monitoring (e.g., temperature and humidity, etc.) for potential agricultural applications. A wind-driven electromagnetic energy harvester using rotational magnet pole-pairs (rotor) with a back-iron shield was designed, analyzed, fabricated, and characterized. Our analysis (via finite element method magnetic simulations) shows that a back-iron shield enhances the magnetic flux density on the front side of a rotor where the series connected coils interact and convert the captured mechanical energy (wind energy) into electrical energy by means of electromagnetic induction. A prototype energy harvester was fabricated and tested under various wind speeds. A custom power management circuit was also designed, manufactured, and successfully implemented in real-time environmental monitoring. The experimental results show that the harvester can generate a maximum average power of 1.02 mW and maximum power efficiency of 73% (with power management circuit) while operated at 4.5 m/s wind speed. The system-level demonstration shows that this wind-driven energy harvesting system is capable of powering a commercial wireless sensor that transmits temperature and humidity data to a smartphone for more than 200 min after charging its battery for only 10 min. The experimental results indicate that the proposed wind-driven energy harvesting system can potentially be implemented in energetically autonomous IoT for smart agriculture applications.
Torrefaction Upgrading of Heterogenous Wastes Containing Cork and Chlorinated Polymers
Authors: Longo Andrei , Nobre Catarina , Sen Ali , Panizio Roberta , Brito Paulo , Gonçalves Margarida
Published: August 2022

Torrefaction of two mixed wastes composed of cork and chlorinated polymers was studied at temperatures from 200 to 350 °C, for residence times of 30 and 60 min. These wastes were recovered from sandwich panels with cork core, have different contents of cork biomass and chlorinated polymers and present poor fuel properties for energy recovery applications. The raw wastes and the produced biochars were characterized for proximate and ultimate analysis, chlorine content, mineral composition, calorific value, mass yield, energy density, particle size distribution, and adsorption capacity towards cationic and anionic dyes. Torrefaction enabled the production of biochars with mass yields from 97.2 to 54.5%, with an increase in 12.1 to 37.9% in apparent density relative to the raw wastes, and HHV from 18.2 to 20.7 MJ/kg. Nevertheless, the chlorine content of the biochars was increased to values higher than 5%, inadequate for solid fuels. Dechlorination of the biochars by washing with hot water enabled 84 to 91% removal of the chlorine species achieving final concentrations lower than 1%, without significant reduction in the biochars calorific values. For the waste with higher polymer and ash content, the torrefaction process reduced the heating value; therefore, energy valorization was not adequate. Both the raw wastes and the biochars were tested as adsorbents for cationic and anionic dyes. After activation with KOH, both the raw materials and the biochars had removal efficiencies higher than 90% for methylene blue, a cationic dye often found in industrial effluents. The results showed that torrefaction combined with hot water washing converted these wastes to biochars with the potential for energy or material valorization contributing to a circular economy in the cork industrial sector.
Effect of Forest Edge Cutting on Transpiration Rate in Picea abies (L.) H. Karst.
Authors: Özçelik Mehmet S. , Tomášková Ivana , Surový Peter , Modlinger Roman
Published: August 2022

A field study was conducted to investigate the effect of forest-edge cutting on the transpiration rates of individual Picea abies (L.) H. Karst. trees regarding their susceptibility to bark-beetle Ips typographus (L.) infestation. The study period, spanning from 2019 to 2020, involved two treatment plots (Tp) and two control plots (Cp). Sap-flow sensors working according to the trunk-heat-balance method were set up on selected sample trees from Tp and Cp. Calibration equations were established after a one-year monitoring period between Cp and Tp, followed by 50-meter-long forest edges created at Tp. The changes in the daily sap flow rates were determined as the differences between the measured and predicted values derived from the calibration equations. The results showed that the created forest-edge clearance caused an increase of up to 16% in the sap flow of trees positioned near the new edge. There was a positive correlation between the increase in the sap flow of the trees and the decreased canopy density of the surroundings. The results of this study indicated that forest-edge clearance and forest fragmentation significantly affect the responses of forest-edge trees to new microclimatic conditions.
A Bioactive Compounds Profile Present in the Selected Wood Rot
Authors: Szwajkowska-Michałek Lidia , Stuper-Szablewska Kinga , Krzyżaniak Michał , Łakomy Piotr
Published: August 2022

Wood rot fungi are an essential link in the forest ecosystem. The presented study aimed to determine the content of selected antioxidant active compounds of selected saprobionts commonly found in the European forests: Hypholoma fasciculare (Huds.) P. Kumm, Bjerkandera adusta (Willd.) P. Karst., Inonotus obliquus (Fr.) Pilát, Kuehneromyces mutabilis (Schaeff.) Singer & AH Sm., Trametes versicolor (L.) Lloyd, Pleurotusostreatus (Jacq.) P. Kumm., Pholiota squarrosa (Vahl) P. Kumm. Chemical methods (HPLC determination, ABTS+ and FPA methods, and a saponification method by Acquity UPLC) were used to analyze active compounds. In the tested isolates, the presence of 13 phenolic acids has been observed, including p-coumaric, ferulic, chlorogenic, and sinapic acid, in high concentrations. The antioxidant activity was from 2.5 to 3.5 times higher in the isolates of I. obliquus, P. ostreatus, and H. fasciculare in comparison to P. squarrosa and B. adusta. All isolates were tested for β-carotene, lutein, zeaxanthin, and astaxanthin. High concentrations of flavonoids were observed in H. fasciculare and P. squarrosa. In addition, the observed concentration of naringenin, quercetin, and kaempferol above 21 mg/kg DM was found. The ergosterol was quantified in the saprobiont fungi cultures. A diversified content of bioactive compounds characterized the tested fungi, and the Chaga (I. obliquus) reported the highest content of tested compounds.
Enhancing Residents’ Environmentally Responsible Behavioral Intentions: The Role of Awe and Place Attachment in Potatso National Park Communities, Tibet
Authors: Zhao Minyan , Li Zehong , Xia Bing , Chen Wuqiang , Tang Tiantian , Meng Zichao , Ding Yan
Published: August 2022

China announced its first policy framework for the construction of a protected areas system centered on national parks in 2019. It is increasingly recognized that the intentions of local community residents to engage in environmentally responsible behaviors are essential to achieving biodiversity goals in area-based conservation. Using an extended theory of planned behavior that incorporates the emotional factors of “Awe” and “place attachment,” this research tested hypotheses and constructed a theoretical model regarding the environmentally responsible behavioral intentions of community residents within and outside Potatso National Park, a pilot park in the new Chinese protected area system. A quantitative questionnaire survey of residents yielded 503 valid responses, and structural equation modeling was used to test the theoretical hypotheses. The results show that Awe has a significantly positive effect on environmentally responsible behavioral intentions. It also has a significantly positive effect on Place Attachment and subjective norms, which also strengthen environmentally responsible behavioral intentions. In addition, Place Attachment was found to be an important mediating factor for the influence of Awe on environmentally responsible behavioral intentions. According to the general model, both rational and emotional factors drive the behavioral intentions of local residents. Moreover, the findings reveal that the regulating effect of Place Attachment plays a greater role among those whose livelihoods are more dependent on the natural environment, while subjective norms play a greater role among those whose livelihoods are less dependent on the natural environment. The results provide a useful theoretical basis and practical reference for the use of rational and emotional factors to drive environmentally responsible behaviors among residents in and surrounding national parks, and for the promotion of the role of protected areas in nature preservation and community development.
Integrated Bioprocess for Cellulosic Ethanol Production from Wheat Straw: New Ternary Deep-Eutectic-Solvent Pretreatment, Enzymatic Saccharification, and Fermentation
Authors: Xian Xiaoling , Fang Lv , Zhou Yongxing , Li Biying , Zheng Xiaojie , Liu Yao , Lin Xiaoqing
Published: August 2022

Wheat straw (WS) is an excellent raw material for biofuel ethanol production. However, the recalcitrance of WS prevents its efficient utilization. In this study, a novel ternary deep eutectic solvent (DES) was developed for enhancing component separation and enzymatic saccharification of WS. Without any detoxification and sterilization, the DES-treated WS hydrolysate was successfully used to produce ethanol. Overall, this research evaluated the effect of ternary DES pretreatment on WS at various temperatures and adjusted the enzyme load, substrate concentration, and fermentation method of treated WS. The results suggested that the cellulose recovery of treated WS after DES pretreatment (120 °C, 1 h) was 94.73 ± 0.22%, while the removal of xylan and lignin reached 89.53 ± 0.36% and 80.05 ± 0.62%, respectively. Importantly, at enzyme loading of 11.4 filter paper unit (FPU)/g WS with 16% fermentation substrate concentration, 91.15 ± 1.07% of cellulose was hydrolyzed, and the glucose yield was 71.58 ± 1.34%. The maximum ethanol yield of DES-treated WS was 81.40 ± 0.01%.