bluuebunny/crossref_metadata_2025 huggingface dataset:
Omega−3 Polyunsaturated Fatty Acids (PUFAs): Emerging Plant and Microbial Sources, Oxidative Stability, Bioavailability, and Health Benefits—A Review
Authors: Saini Ramesh Kumar , Prasad Parchuri , Sreedhar Reddampalli Venkataramareddy , Akhilender Naidu Kamatham , Shang Xiaomin , Keum Young-Soo
Published: October 2021

The omega−3 (n−3) polyunsaturated fatty acids (PUFAs) eicosapentaenoic acid (EPA) and docosahexaenoic (DHA) acid are well known to protect against numerous metabolic disorders. In view of the alarming increase in the incidence of chronic diseases, consumer interest and demand are rapidly increasing for natural dietary sources of n−3 PUFAs. Among the plant sources, seed oils from chia (Salvia hispanica), flax (Linum usitatissimum), and garden cress (Lepidium sativum) are now widely considered to increase α-linolenic acid (ALA) in the diet. Moreover, seed oil of Echium plantagineum, Buglossoides arvensis, and Ribes sp. are widely explored as a source of stearidonic acid (SDA), a more effective source than is ALA for increasing the EPA and DHA status in the body. Further, the oil from microalgae and thraustochytrids can also directly supply EPA and DHA. Thus, these microbial sources are currently used for the commercial production of vegan EPA and DHA. Considering the nutritional and commercial importance of n−3 PUFAs, this review critically discusses the nutritional aspects of commercially exploited sources of n−3 PUFAs from plants, microalgae, macroalgae, and thraustochytrids. Moreover, we discuss issues related to oxidative stability and bioavailability of n−3 PUFAs and future prospects in these areas.
The Recovery of Cognitive and Affective Deficiencies Linked with Chronic Osteoarthritis Pain and Implicated Pathways by Slow-Releasing Hydrogen Sulfide Treatment
Authors: Batallé Gerard , Bai Xue , Pouso-Vázquez Enric , Roch Gerard , Rodríguez Laura , Pol Olga
Published: October 2021

Chronic osteoarthritis pain is accompanied by several comorbidities whose treatment has not been completely resolved. The anti-inflammatory, analgesic, and antidepressant effects of slow-releasing hydrogen sulfide (H2S) donors during osteoarthritic pain have been shown, but their actions in the accompanying memory impairment and anxious-like behaviors have not yet been demonstrated. Using female mice with chronic osteoarthritic pain, the effects of natural, diallyl disulfide (DADS) or synthetic, morpholin-4-ium 4-methoxyphenyl(morpholino) phosphinodithioate dichloromethane complex (GYY4137) slow-releasing H2S donors, on associated cognitive and grip strength deficits and anxiodepressive-like behaviors, were assessed. Their effects on specific brain areas implicated in the modulation of pain and emotional responses were also determined. Results demonstrated an improvement in memory and grip strength deficits, as well as in the anxious-like behaviors associated with chronic pain in GYY4137 and/or DADS treated mice. The painkiller and antidepressant properties of both treatments were also established. Treatment with DADS and/or GYY4137 inhibited: oxidative stress in the amygdala; phosphoinositide 3-kinase overexpression in the amygdala, periaqueductal gray matter, and anterior cingulate cortex; protein kinase B activation in the amygdala and infralimbic cortex; up-regulation of inducible nitric oxide synthase in the amygdala, periaqueductal gray matter and infralimbic cortex and apoptotic responses in the amygdala. These results might explain the recovery of memory and grip strength and the inhibition of allodynia and associated anxiodepressive-like behaviors by these treatments. In conclusion, this study revealed new properties of slow-releasing H2S donors in cognitive impairment and affective disorders linked with chronic osteoarthritis pain and their effects on the central nervous system.
Superoxide Production by the Red Tide-Producing Chattonella marina Complex (Raphidophyceae) Correlates with Toxicity to Aquacultured Fishes
Authors: Shikata Tomoyuki , Yuasa Koki , Kitatsuji Saho , Sakamoto Setsuko , Akita Kazuki , Fujinami Yuichiro , Nishiyama Yoshitaka , Kotake Toshihisa , Tanaka Ryusuke , Yamasaki Yasuhiro
Published: October 2021

The marine raphidophyte Chattonella marina complex forms red tides, causing heavy mortalities of aquacultured fishes in temperate coastal waters worldwide. The mechanism for Chattonella fish mortality remains unresolved. Although several toxic chemicals have been proposed as responsible for fish mortality, the cause is still unclear. In this study, we performed toxicity bioassays with red sea bream and yellowtail. We also measured biological parameters potentially related to ichthyotoxicity, such as cell size, superoxide (O2•−) production, and compositions of fatty acids and sugars, in up to eight Chattonella strains to investigate possible correlations with toxicity. There were significant differences in moribundity rates of fish and in all biological parameters among strains. One strain displayed no ichthyotoxicity even at high cell densities. Strains were categorized into three groups based on cell length, but this classification did not significantly correlate with ichthyotoxicity. O2•− production differed by a factor of more than 13 between strains at the late exponential growth phase. O2•− production was significantly correlated with ichthyotoxicity. Differences in fatty acid and sugar contents were not related to ichthyotoxicity. Our study supports the hypothesis that superoxide can directly or indirectly play an important role in the Chattonella-related mortality of aquacultured fishes.
Peri-Implant Tissue Behaviour Next to Different Titanium Surfaces: 16-Year Post-Trial Follow-Up
Authors: Delucchi Francesca , Pozzetti Enrico , Bagnasco Francesco , Pesce Paolo , Baldi Domenico , Pera Francesco , Di Tullio Nicolò , Pera Paolo , Menini Maria
Published: October 2021

The present post-trial follow-up investigated the influence of titanium implants with different surface treatments on clinical behavior of soft and hard peri-implant tissues. Each of the 18 included patients received at least two adjacent implants: one control implant with a dual acid-etched (DAE) surface in their apical portion and a machined coronal part, and one test implant with a DAE surface up to its coronal portion. Peri-implant bone level change (BLC), probing depth (PD), bleeding on probing (BOP) and plaque index (PI) were recorded. A total of 42 implants was inserted. The mean follow-up period was 9.3 years (range: 5–16 years) and there were six dropouts. No implant failed. Moderate crestal bone remodeling occurred during the first year after implant insertion, with lower bone loss next to test implants compared to control ones (0.80 vs. 1.39 mm; p = 0.002). This difference was also detected at the 5- (p = 0.011), 6- (p = 0.008) and 7-year follow-up appointment (p = 0.027). No statistically significant differences were found in bone resorption between implants rehabilitated with ceramic vs. composite resin veneering material. No statistically significant differences were detected between test and control implants for BOP, PI, and PD at any time point. The results of the present study suggest that DAE surfaces reduce peri-implant bone loss in the initial phase of healing compared to machined surfaces, while they do not significantly affect soft peri-implant tissue and bone maintenance in the long-term. In conclusion, the minimally rough surfaces favour peri-implant bone maintenance and their effect is greater in the first year post implant insertion.
Using Homemade Pressure Device to Improve Plantar Pressure—A Case Study on the Patient with Lower Limb Lymphedema
Authors: Chen Jong-Chen , Wang Yao-Te , Lin Ying-Sheng
Published: October 2021

Feet play a very important and indispensable role in people’s lives. Patients with lymphedema often suffer from collapsed (or even deformed) foot arches as a result of lower extremity edema. This result will change the normal pressure distribution on the soles of their feet, which will affect their mobility and physical health. When the patient does not know that the distribution of pressure on the sole of the foot has changed significantly, the deformation of the sole of the foot will become severe. In response to this problem, this research team hopes to use a set of self-made sensor insoles to help to understand the plantar pressure points in different situations or actions. The subject invited in this study was a patient with lower extremity edema. The entire study was carried out with the consent of the patient, the guidance of the physician and the approval of the Ethics Committee of National Taiwan University Hospital (No: 201805068 RINB, date: 18 June 2018). This study uses this self-made sensor insole to analyze the plantar pressure distribution of the patient before and after the operation of lower extremity edema. The results show that the operation can effectively improve the high foot pressure in the center and rear of the foot area during different sports (standing, walking and biking). This not only increases its stability when standing and walking, but also significantly and effectively improves its walking speed and step distance.
Concept Drift Adaptation with Incremental–Decremental SVM
Authors: Gâlmeanu Honorius , Andonie Răzvan
Published: October 2021

Data classification in streams where the underlying distribution changes over time is known to be difficult. This problem—known as concept drift detection—involves two aspects: (i) detecting the concept drift and (ii) adapting the classifier. Online training only considers the most recent samples; they form the so-called shifting window. Dynamic adaptation to concept drift is performed by varying the width of the window. Defining an online Support Vector Machine (SVM) classifier able to cope with concept drift by dynamically changing the window size and avoiding retraining from scratch is currently an open problem. We introduce the Adaptive Incremental–Decremental SVM (AIDSVM), a model that adjusts the shifting window width using the Hoeffding statistical test. We evaluate AIDSVM performance on both synthetic and real-world drift datasets. Experiments show a significant accuracy improvement when encountering concept drift, compared with similar drift detection models defined in the literature. The AIDSVM is efficient, since it is not retrained from scratch after the shifting window slides.
Arrays of Sub-Terahertz Cryogenic Metamaterial
Authors: Tarasov Mikhail , Gunbina Aleksandra , Chekushkin Artem , Vdovin Vyacheslav , Kalaboukhov Aleksei
Published: October 2021

Integrated quasi-optical cryogenic terahertz receivers contain arrays of detectors, quasi-optical filters, interferometers, and other metamaterials. Matrices of quasi-optical band-pass, low-pass, and high-pass filters, Fabry–Perot grid interferometers, and arrays of half-wave and electrically small antennas with superconductor-insulator-normal metal-insulator-superconductor (SINIS) sub-terahertz wavelength range detectors were fabricated and experimentally studied on the same computational, technological, and experimental platform. For the design of the filters, we used the periodic frequency-selective surfaces (FSS) approach, contrary to detector arrays that can be presented in a model of distributed absorbers. The structures were fabricated using direct electron beam lithography, thermal shadow evaporation, lift-off, alternatively magnetron sputtering, and chemical and plasma etching. The numerical simulation methods of such structures are sufficiently different: for the reactive matrices with low losses, the approximation of an infinite structure with periodic boundary conditions is applicable, and for the arrays of detectors with dissipative elements of absorbers, a complete analysis of the finite structure with hundreds of interacting ports is applicable. The difference is determined by the presence of dissipation in the detector arrays, the phase of the reflected or re-emitted signal turned out to be undefined and the Floquet periodic boundary conditions are correct only for a phased array antenna. The spectral characteristics of the created filters, interferometers, and antenna arrays were measured in the frequency range 50–600 GHz.
A Path Planning Strategy for Multi-Robot Moving with Path-Priority Order Based on a Generalized Voronoi Diagram
Authors: Huang Sheng-Kai , Wang Wen-June , Sun Chung-Hsun
Published: October 2021

This paper proposes a new path planning strategy called the navigation strategy with path priority (NSPP) for multiple robots moving in a large flat space. In the space, there may be some static or/and dynamic obstacles. Suppose we have the path-priority order for each robot, then this article aims to find an efficient path for each robot from its starting point to its target point without any collision. Here, a generalized Voronoi diagram (GVD) is used to perform the map division based on each robot’s path-priority order, and the proposed NSPP is used to do the path planning for the robots in the space. This NSPP can be applied to any number of robots. At last, there are several simulations with a different number of robots in a circular or rectangular space to be shown that the proposed method can complete the task effectively and has better performance in average trajectory length than those by using the benchmark methods of the shortest distance algorithm (SDA) and reciprocal orientation algorithm (ROA).
A Cross-Correlation-Based Approach to Pattern Distortion and Mutual Coupling for Shared-Aperture Antennas
Authors: Heo Jin Myeong , Yoon Jongwon , Kim Hyun , Kim Youngwan , Byun Gangil
Published: October 2021

This paper proposes a pattern distortion coefficient as a new figure of merit to quantitatively evaluate both mutual coupling and pattern distortions in multi-antenna systems. The proposed coefficient is defined as a cross correlation between unaffected and affected far-field patterns of antennas under test, and the input patterns are weighted using a Gaussian function to consider the target operation angle. The feasibility of the proposed approach is validated using a two-antenna system composed of an inverted-F antenna and a microstrip patch antenna, and the amount of mutual coupling is adjusted by changing the distance between the two antennas. The evaluation is further extended to a single-antenna system with a conducting wall that produces strong platform effects with serious pattern distortions. The results demonstrate that the proposed figure of merit provides quantitative insight into the amplitude and phase distortions of far-field patterns that can be caused by both mutual coupling and platform effects.
BIBC: A Chinese Named Entity Recognition Model for Diabetes Research
Authors: Yang Lei , Fu Yufan , Dai Yu
Published: October 2021

In the medical field, extracting medical entities from text by Named Entity Recognition (NER) has become one of the research hotspots. This thesis takes the chapter-level diabetes literature as the research object and uses a deep learning method to extract medical entities in the literature. Based on the deep and bidirectional transformer network structure, the pre-training language model BERT model can solve the problem of polysemous word representation, and supplement the features by large-scale unlabeled data, combined with BiLSTM-CRF model extracts of the long-distance features of sentences. On this basis, in view of the problem that the model cannot focus on the local information of the sentence, resulting in insufficient feature extraction, and considering the characteristics of Chinese data mainly in words, this thesis proposes a Named Entity Recognition method based on BIBC. This method combines Iterated Dilated CNN to enable the model to take into account global and local features at the same time, and uses the BERT-WWM model based on whole word masking to further extract semantic information from Chinese data. In the experiment of diabetic entity recognition in Ruijin Hospital, the accuracy rate, recall rate, and F1 score are improved to 79.58%, 80.21%, and 79.89%, which are better than the evaluation indexes of existing studies. It indicates that the method can extract the semantic information of diabetic text more accurately and obtain good entity recognition results, which can meet the requirements of practical applications.
A Short S-Equol Exposure Has a Long-Term Inhibitory Effect on Adipogenesis in Mouse 3T3-L1 Cells
Authors: Mandujano-Lázaro Gilberto , Galaviz-Hernández Carlos , Reyes-López César A. , Almanza-Pérez Julio C. , Giacoman-Martínez Abraham , López-Camarillo César , Huang Fengyang , Marchat Laurence A.
Published: October 2021

In the search for new drugs against obesity, the chronic disease that threatens human health worldwide, several works have focused on the study of estrogen homologs because of the role of estrogen receptors (ERs) in adipocyte growth. The isoflavone equol, an ERβ agonist, has shown beneficial metabolic effects in in vivo and in vitro assays; however, additional studies are required to better characterize its potential for body weight control. Here, we showed that the treatment of 3T3-L1 cells with 10 μM of S-equol for the first three days of the adipocyte differentiation protocol was able to prevent cells becoming semi-rounded and having a lipid droplet formation until the seventh day of culture; moreover, lipid accumulation was reduced by about 50%. Congruently, S-equol induced a reduction in mRNA expression of the adipogenic markers C/EBPα and PPARγ, and adipokines secretion, mainly Adiponectin, Leptin, Resistin, and MCP-1, while the release of PAI-1 was augmented. Moreover, it also reduced the expression of ERα and attenuated the subexpression of ERβ associated with adipogenesis. Altogether, our data suggested that S-equol binding to ERβ affects the transcriptional program that regulates adipogenesis and alters adipocyte functions. Future efforts will focus on studying the impact of S-equol on ER signaling pathways.
Structural Synthesis of Articulated Manipulators with Non-Fractionated or Fractionated Kinematic Chains without Isomorphism
Authors: Park Ho Sung , Shim Jae Kyung , Kim Woon Ryong , Yun Tae Woong
Published: October 2021

As the kinematic structure of an articulated manipulator affects the characteristics of its motion, rigidity, vibration, and force transmissibility, finding the most suitable kinematic structure for the desired task is important in the conceptual design phase. This paper proposes a systematic method for generating non-isomorphic graphs of articulated manipulators that consist of a fixed base, an end-effector, and a two-degree-of-freedom (DOF) intermediate kinematic chain connecting the two. Based on the analysis of the structural characteristics of articulated manipulators, the conditions that must be satisfied for manipulators to have a desired DOF is identified. Then, isomorphism-free graph generation methods are proposed based on the concepts of the symmetry of a graph, and the number of graphs generated are determined. As a result, 969 graphs of articulated manipulators that have two-DOF non-fractionated intermediate kinematic chains and 33,438 graphs with two-DOF fractionated intermediate kinematic chains are generated, including practical articulated manipulators widely used in industry.
Reducing System Load of Effective Video Using a Network Model
Authors: Cho Soo-Young , Kim Dae-Yeol , Oh Su-Yeong , Sohn Chae-Bong
Published: October 2021

Recently, as non-face-to-face work has become more common, the development of streaming services has become a significant issue. As these services are applied in increasingly diverse fields, various problems are caused by the overloading of systems when users try to transmit high-quality images. In this paper, SRGAN (Super Resolution Generative Adversarial Network) and DAIN (Depth-Aware Video Frame Interpolation) deep learning were used to reduce the overload that occurs during real-time video transmission. Images were divided into a FoV (Field of view) region and a non-FoV (Non-Field of view) region, and SRGAN was applied to the former, DAIN to the latter. Through this process, image quality was improved and system load was reduced.
Characterization of Atypical Pheochromocytomas with Correlative MRI and Planar/Hybrid Radionuclide Imaging: A Preliminary Study
Authors: Galatola Roberta , Attanasio Ludovica , Romeo Valeria , Mainolfi Ciro , Klain Michele , Simeoli Chiara , Modica Roberta , Guadagno Elia , Aprea Giovanni , Basso Luca , Nicolai Emanuele , Salvatore Marco , Maurea Simone
Published: October 2021

Pheochromocytomas may show atypical imaging findings leading to diagnostic pitfalls. We correlated the results of magnetic resonance imaging (MRI) with those of radionuclide studies in patients with pheochromocytomas. T2-weighted (-w), T1-w chemical-shift and T1-w dynamic contrast enhanced (DCE) MRI sequences were evaluated to assess tumor structure. 131Iodine metaiodobenzylguanidine (MIBG) scintigraphy, 18fluoro (F) deoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) or FDG PET/MRI were evaluated for direct comparison. Of a total of 80 adrenal lesions in 73 patients, 20 in 18 patients were pheochromocytomas. More than half (55%) of the pheochromocytomas (n = 11) had the typical increased signal intensity on T2-w and T1-w DCE, while the remaining (n = 9) lesions showed atypical findings; of these nine latter atypical lesions, seven (35%) were cystic (two totally, three predominantly and two partially) and two (10%) were hemorrhagic on MRI. In these atypical lesions, MIBG scintigraphy (n = 5), FDG PET/CT (n = 6) or FDG PET/MRI (n = 2) showed inhomogeneous tracer uptake in the residual viable tissue providing tumor characterization; however, one predominantly cystic pheochromocytoma showed false negative MIBG scan. Our preliminary results show that cystic degeneration may be frequent in pheochromocytoma being so marked that only a thin rim of viable cells may residue to disclose the true nature of the tumor. MRI findings together with those of correlative planar/hybrid radionuclide images are helpful to characterize these atypical pheochromocytomas. In particular, tumor accumulation of MIBG and/or FDG is able to classify these lesions as not simple cysts; in detail, the presence of partial MIBG uptake allows the diagnosis of pheochromocytomas, while the presence of partial FDG uptake generically reflects the presence of viable solid tissue of such cystic tumors.
Current Challenges Supporting School-Aged Children with Vision Problems: A Rapid Review
Authors: Ali Qasim , Heldal Ilona , Helgesen Carsten G. , Krumina Gunta , Costescu Cristina , Kovari Attila , Katona Jozsef , Thill Serge
Published: October 2021

Many children have undetected vision problems or insufficient visual information processing that may be a factor in lower academic outcomes. The aim of this paper is to contribute to a better understanding of the importance of vision screening for school-aged children, and to investigate the possibilities of how eye-tracking (ET) technologies can support this. While there are indications that these technologies can support vision screening, a broad understanding of how to apply them and by whom, and if it is possible to utilize them at schools, is lacking. We review interdisciplinary research on performing vision investigations, and discuss current challenges for technology support. The focus is on exploring the possibilities of ET technologies to better support screening and handling of vision disorders, especially by non-vision experts. The data orginate from a literature survey of peer-reviewed journals and conference articles complemented by secondary sources, following a rapid review methodology. We highlight current trends in supportive technologies for vision screening, and identify the involved stakeholders and the research studies that discuss how to develop more supportive ET technologies for vision screening and training by non-experts.
Dynamic Modeling and Vibration Characteristics for a High-Speed Aero-Engine Rotor with Blade Off
Authors: Wang Longkai , Yin Yijun , Wang Ailun , Heng Xing , Jin Miao
Published: October 2021

Blade off that occurs during operation will generate a sudden imbalance excitation and make the rotor become inertially asymmetric, which leads to large instantaneous impact load and induces more complex rotor dynamic phenomena. In order to study the transient dynamic characteristics for complex rotors suffering from blade off, a mathematical model for solving the response of the gas generator rotor in the aero-turboshaft engine is established based on the FE method and DOF condensation, in which the complex structural characteristics, transient impact load, and inertia asymmetry of the rotor are considered. The complex impeller structure is modeled by piecewise linear fitting with cylindrical beam elements and tapered beam elements. Without loss of generality, the modeling method suitable for complex rotors is verified through a general complex test rotor with modal experiments. Based on this, the responses are solved for carrying out parametric studies and an understanding of the transient dynamic characteristics of the rotor under the extreme working conditions of blade off. The results show that the blade off has a great impact effect on the time-domain waveform, frequency components, and rotor orbits. At the instantaneous stage after blade off, the complex motion is composed of synchronous motion and some lower-order natural modes excited by blade off. Although the transient responses with blade off at different rotational speeds have similar time-varying characteristics, the impact factor is sensitive to the rotating speed. Most important is that the parameter of the blade off location will not only have a significant effect on the impact factor, but also on the frequency spectrum. These dynamic characteristics as well as impact effect provide certain guidance for the fault recognition and dynamic analysis to these complex rotors suffering blade off.
A New Inspiration in Bionic Shock Absorption Midsole Design and Engineering
Authors: Yu Hai-Bin , Zhang Rui , Yu Guo-Long , Wang Hai-Tao , Wang Dao-Chen , Tai Wei-Hsun , Huang Jian-Long
Published: October 2021

Inspired by the performance of the ostrich in terms of loading and high-speed moving ability, the purpose of this study was to design a structure and material on the forefoot and heel of the middle soles of sports shoes based on the high cushioning quality of the ostrich toe pad by applying bionic engineering technology. The anatomical dissection method was used to analyze the ostrich foot characteristics. The structure and material of the bionic shock absorption midsole were designed according to the principles of bionic engineering and reverse engineering. F-Scan and numerical simulation were used to evaluate the bionic shock absorption midsole performance. The results showed that the bionic shock absorption midsole decreased the peak pressure (6.04–12.27%), peak force (8.62–16.03%), pressure–time integral (3.06–12.66%), and force–time integral (4.06–10.58%) during walking and brisk walking. In this study, the biomechanical effects to which the bionic shock absorption midsole structure was subjected during walking and brisk walking exercises were analyzed. The bionic midsole has excellent shock resistance. It is beneficial for the comfort of the foot during exercise and might reduce the risk of foot injuries during exercise.
When Intelligent Transportation Systems Sensing Meets Edge Computing: Vision and Challenges
Authors: Zhou Xuan , Ke Ruimin , Yang Hao , Liu Chenxi
Published: October 2021

The widespread use of mobile devices and sensors has motivated data-driven applications that can leverage the power of big data to benefit many aspects of our daily life, such as health, transportation, economy, and environment. Under the context of smart city, intelligent transportation systems (ITS), as a main building block of modern cities, and edge computing (EC), as an emerging computing service that targets addressing the limitations of cloud computing, have attracted increasing attention in the research community in recent years. It is well believed that the application of EC in ITS will have considerable benefits to transportation systems regarding efficiency, safety, and sustainability. Despite the growing trend in ITS and EC research, a big gap in the existing literature is identified: the intersection between these two promising directions has been far from well explored. In this paper, we focus on a critical part of ITS, i.e., sensing, and conducting a review on the recent advances in ITS sensing and EC applications in this field. The key challenges in ITS sensing and future directions with the integration of edge computing are discussed.
Coupled Numerical Method for Modeling Propped Fracture Behavior
Authors: Lengyel Tamás , Varga Attila , Safranyik Ferenc , Jobbik Anita
Published: October 2021

Hydraulic fracturing is a well-known production intensification technique in the petroleum industry that aims to enhance the productivity of a well drilled mostly in less permeable reservoirs. The process’s effectiveness depends on the achieved fracture conductivity, the product of fracture width, and the permeability of the proppant pack placed within the fracture. This article presents an innovative method developed by our research activity that incorporates the benefit of the Discrete—and Finite Element Method to describe the in situ behavior of hydraulic fractures with a particular emphasis on fracture conductivity. DEM (Discrete Element Method) provided the application of random particle generation and non-uniform proppant placement. We also used FEM (Finite Element Method) Static Structural module to simulate the elastic behavior of solid materials: proppant and formation, while CFD (Computational Fluid Dynamics) module was applied to represent fluid dynamics within the propped fracture. The results of our numerical model were compared to data of API RP-19D and API RP-61 laboratory measurements and findings gained by publishers dealing with propped fracture conductivity. The match of the outcomes verified the method and encouraged us to describe proppant deformation and embedment and their effect as precisely as possible. Based on the results, we performed sensitivity analysis which pointed out the impact of several factors affecting proppant embedment, deformation, and fracture conductivity and let one be aware of a reasonable interpretation of propped hydraulic fracture operation. However, DEM–CFD coupled models were introduced regarding fracturing before, to the best of our knowledge, the developed workflow of coupling DEM–FEM–CFD for modeling proppant-supported fracture behavior has not been applied yet, thus arising new perspectives for explorers and engineers.
New Dimensionless Correlations for the Evaluation of the Thermal Resistances of a District Heating Twin Pipe System
Authors: Corcione Massimo , Cretara Luca , Fontana Lucia , Quintino Alessandro
Published: October 2021

The heat losses from pre-insulated double-pipe district heating (DH) systems buried in a homogeneous soil are studied numerically. The study is conducted using the diameter of the pipes and their distance, the size of the insulation, the thermal conductivity ratio between the insulation and the soil, as well as the burial depth of the double-pipe system, as controlling parameters. A computational code based on a control-volume formulation of the finite-difference method has been developed using the open-source framework OpenFOAM with the purpose to compute the heat transfer rate across adjacent solid regions with different thermophysical properties. The main scopes of the study are: (a) to investigate in what measure the geometry and the relative position of the warm and cold pipes, as well as the temperature imbalance, the burial depth and the physical properties of both the insulation and the soil, affect the heat losses; (b) to analyze the existence of an optimal configuration of the DH system by the thermal resistance enhancement viewpoint; and (c) to develop accurate correlating equations for the evaluation of the thermal resistance existing between each pipe and its surroundings, useful for practical thermal engineering applications.
Evaluating the Checklist for Artificial Intelligence in Medical Imaging (CLAIM)-Based Quality of Reports Using Convolutional Neural Network for Odontogenic Cyst and Tumor Detection
Authors: Le Van Nhat Thang , Kim Jae-Gon , Yang Yeon-Mi , Lee Dae-Woo
Published: October 2021

This review aimed to explore whether studies employing a convolutional neural network (CNN) for odontogenic cyst and tumor detection follow the methodological reporting recommendations, the checklist for artificial intelligence in medical imaging (CLAIM). We retrieved the CNN studies using panoramic and cone-beam-computed tomographic images from inception to April 2021 in PubMed, EMBASE, Scopus, and Web of Science. The included studies were assessed according to the CLAIM. Among the 55 studies yielded, 6 CNN studies for odontogenic cyst and tumor detection were included. Following the CLAIM items, abstract, methods, results, discussion across the included studies were insufficiently described. The problem areas included item 2 in the abstract; items 6–9, 11–18, 20, 21, 23, 24, 26–31 in the methods; items 33, 34, 36, 37 in the results; item 38 in the discussion; and items 40–41 in “other information.” The CNN reports for odontogenic cyst and tumor detection were evaluated as low quality. Inadequate reporting reduces the robustness, comparability, and generalizability of a CNN study for dental radiograph diagnostics. The CLAIM is accepted as a good guideline in the study design to improve the reporting quality on artificial intelligence studies in the dental field.
A Framework to Understand Attitudes towards Immigration through Twitter
Authors: Freire-Vidal Yerka , Graells-Garrido Eduardo , Rowe Francisco
Published: October 2021

Understanding public opinion towards immigrants is key to prevent acts of violence, discrimination and abuse. Traditional data sources, such as surveys, provide rich insights into the formation of such attitudes; yet, they are costly and offer limited temporal granularity, providing only a partial understanding of the dynamics of attitudes towards immigrants. Leveraging Twitter data and natural language processing, we propose a framework to measure attitudes towards immigration in online discussions. Grounded in theories of social psychology, the proposed framework enables the classification of users’ into profile stances of positive and negative attitudes towards immigrants and characterisation of these profiles quantitatively summarising users’ content and temporal stance trends. We use a Twitter sample composed of 36 K users and 160 K tweets discussing the topic in 2017, when the immigrant population in the country recorded an increase by a factor of four from 2010. We found that the negative attitude group of users is smaller than the positive group, and that both attitudes have different distributions of the volume of content. Both types of attitudes show fluctuations over time that seem to be influenced by news events related to immigration. Accounts with negative attitudes use arguments of labour competition and stricter regulation of immigration. In contrast, accounts with positive attitudes reflect arguments in support of immigrants’ human and civil rights. The framework and its application can inform policy makers about how people feel about immigration, with possible implications for policy communication and the design of interventions to improve negative attitudes.
Deep Learning Semantic Segmentation for Water Level Estimation Using Surveillance Camera
Authors: Muhadi Nur Atirah , Abdullah Ahmad Fikri , Bejo Siti Khairunniza , Mahadi Muhammad Razif , Mijic Ana
Published: October 2021

The interest in visual-based surveillance systems, especially in natural disaster applications, such as flood detection and monitoring, has increased due to the blooming of surveillance technology. In this work, semantic segmentation based on convolutional neural networks (CNN) was proposed to identify water regions from the surveillance images. This work presented two well-established deep learning algorithms, DeepLabv3+ and SegNet networks, and evaluated their performances using several evaluation metrics. Overall, both networks attained high accuracy when compared to the measurement data but the DeepLabv3+ network performed better than the SegNet network, achieving over 90% for overall accuracy and IoU metrics, and around 80% for boundary F1 score (BF score), respectively. When predicting new images using both trained networks, the results show that both networks successfully distinguished water regions from the background but the outputs from DeepLabv3+ were more accurate than the results from the SegNet network. Therefore, the DeepLabv3+ network was used for practical application using a set of images captured at five consecutive days in the study area. The segmentation result and water level markers extracted from light detection and ranging (LiDAR) data were overlaid to estimate river water levels and observe the water fluctuation. River water levels were predicted based on the elevation from the predefined markers. The proposed water level framework was evaluated according to Spearman’s rank-order correlation coefficient. The correlation coefficient was 0.91, which indicates a strong relationship between the estimated water level and observed water level. Based on these findings, it can be concluded that the proposed approach has high potential as an alternative monitoring system that offers water region information and water level estimation for flood management and related activities.
Anti-Inflammatory Activity of Cnidoscolus aconitifolius (Mill.) Ethyl Acetate Extract on Croton Oil-Induced Mouse Ear Edema
Authors: Padilla-Camberos Eduardo , Torres-Gonzalez Omar Ricardo , Sanchez-Hernandez Ivan Moises , Diaz-Martinez Nestor Emmanuel , Hernandez-Perez Oscar Rene , Flores-Fernandez Jose Miguel
Published: October 2021

Nowadays, there is a growing interest in the development of medicinal plant-based therapies to diminish the ravages of the inflammatory process related to diseases and tissue damage. Most therapeutic effects of these traditional medicinal plants are owed to their phenolic and antioxidant properties. C. aconitifolius is a traditional medicinal plant in Mexico. Previous characterization reports have stated its high nutritional and antioxidant components. The present study aimed to better understand the biological activity of C. aconitifolius in inflammation response. We developed an ethyl acetate extract of this plant to evaluate its anti-inflammatory capacity and its flavonoid content. The topical anti-inflammatory effect of the ethyl acetate extract of C. aconitifolius was determined by the croton oil-induced mouse ear edema test, while flavonoid detection and concentration were determined by thin layer chromatography and the aluminum chloride colorimetric assay, respectively. Topical application of the extract showed significant inhibition of the induced-ear edema (23.52 and 49.41% for 25 and 50 mg/kg dose, respectively). The extract also exhibited the presence of flavonoids. The finding of the anti-inflammatory activity exerted by the C. aconitifolius and the identification of its active principles may suggest and support its use for inflammation treatment.
Methodology of Functional and Technical Evaluation of Cooperative Intelligent Transport Systems and Its Practical Application
Authors: Lokaj Zdeněk , Šrotýř Martin , Vaniš Miroslav , Mlada Michal
Published: October 2021

In the area of smart cities, great emphasis is placed on many different fields such as energetics, information systems, and transportation. All of these should lead to a simplification of life thanks to smart technologies. If we talk about the transportation field, the main issues related to this area are safety, traffic efficiency, or the environment. Another condition is the successful acceptance of any new technology by its users. Cooperative systems prove to be a suitable solution for these issues, especially in urban areas. Today, pilot implementations of cooperative systems in European countries are being carried out. However, before they are put into full operation, they need to be tested, evaluated, and assessed. This article focuses on the latter two points, i.e., evaluation and assessment of the cooperative systems. For this purpose, a methodology was created, which describes the procedure chosen in the evaluation and assessment of cooperative systems in the Czech Republic and a demonstration of its use by example. The methodology is focused on three main areas, which in this case are functional evaluation, user acceptance, and impact assessment. For the area of user acceptance, the main source was questionnaires, impact assessment relied on measured data while functional evaluation was based on discussions with the drivers, evaluating the cooperative systems, the measured data, and the expert observations. All collected and measured data were then processed and some of the results of the evaluation of the selected service are presented at the end of this article.
A CNN-Based Advertisement Recommendation through Real-Time User Face Recognition
Authors: Kim Gihwi , Choi Ilyoung , Li Qinglong , Kim Jaekyeong
Published: October 2021

The advertising market’s use of smartphones and kiosks for non-face-to-face ordering is growing. An advertising video recommender system is needed that continuously shows advertising videos that match a user’s taste and displays other advertising videos quickly for unwanted advertisements. However, it is difficult to make a recommender system to identify users’ dynamic preferences in real time. In this study, we propose an advertising video recommendation procedure based on computer vision and deep learning, which uses changes in users’ facial expressions captured at every moment. Facial expressions represent a user’s emotions toward advertisements. We can utilize facial expressions to find a user’s dynamic preferences. For such a purpose, a CNN-based prediction model was developed to predict ratings, and a SIFT algorithm-based similarity model was developed to search for users with similar preferences in real time. To evaluate the proposed recommendation procedure, we experimented with food advertising videos. The experimental results show that the proposed procedure is superior to benchmark systems such as a random recommendation, an average rating approach, and a typical collaborative filtering approach in recommending advertising videos to both existing users and new users. From these results, we conclude that facial expressions are a critical factor for advertising video recommendations and are helpful in properly addressing the new user problem in existing recommender systems.
Pavement Maintenance Decision Making Based on Optimization Models
Authors: Bao Shitai , Han Keying , Zhang Lan , Luo Xudong , Chen Shunqing
Published: October 2021

Pavement maintenance prioritization considering both quality and cost is an important decision-making problem. In this paper, the actual pavement condition index of city roads was calculated using municipal patrol data. A linear optimization model that maximized maintenance quality with limited maintenance costs and a multi-objective optimization model that maximized maintenance quality while minimizing maintenance costs were developed based on the pavement condition index. These models were subsequently employed in making decisions for actual pavement maintenance using sequential quadratic programming and a genetic algorithm. The results showed that the proposed decision-making models could effectively address actual pavement maintenance issues. Additionally, the results of the single-objective linear optimization model verified that the multiobjective optimization model was accurate. Thus, they could provide optimal pavement maintenance schemes for roads according to actual pavement conditions. The reliability of the models was investigated by analyzing their assumptions and validating their optimization results. Furthermore, their applicability in pavement operation-related decision making and preventive maintenance for roads of different grades was confirmed.
Resolving Gas Bubbles Ascending in Liquid Metal from Low-SNR Neutron Radiography Images
Authors: Birjukovs Mihails , Trtik Pavel , Kaestner Anders , Hovind Jan , Klevs Martins , Gawryluk Dariusz Jakub , Thomsen Knud , Jakovics Andris
Published: October 2021

We demonstrate a new image processing methodology for resolving gas bubbles travelling through liquid metal from dynamic neutron radiography images with an intrinsically low signal-to-noise ratio. Image pre-processing, denoising and bubble segmentation are described in detail, with practical recommendations. Experimental validation is presented—stationary and moving reference bodies with neutron-transparent cavities are radiographed with imaging conditions representative of the cases with bubbles in liquid metal. The new methods are applied to our experimental data from previous and recent imaging campaigns, and the performance of the methods proposed in this paper is compared against our previously achieved results. Significant improvements are observed as well as the capacity to reliably extract physically meaningful information from measurements performed under highly adverse imaging conditions. The showcased image processing solution and separate elements thereof are readily extendable beyond the present application, and have been made open-source.
Cyclostationary Approach to the Analysis of the Power in Electric Circuits under Periodic Excitations
Authors: Shevgunov Timofey , Guschina Oksana , Kuznetsov Yury
Published: October 2021

This paper proposes a cyclostationary based approach to power analysis carried out for electric circuits under arbitrary periodic excitation. Instantaneous power is considered to be a particular case of the two-dimensional cross correlation function (CCF) of the voltage across, and current through, an element in the electric circuit. The cyclostationary notation is used for deriving the frequency domain counterpart of CCF—voltage–current cross spectrum correlation function (CSCF). Not only does the latter exhibit the complete representation of voltage–current interaction in the element, but it can be systematically exploited for evaluating all commonly used power measures, including instantaneous power, in the form of Fourier series expansion. Simulation examples, which are given for the parallel resonant circuit excited by the periodic currents expressed as a finite sum of sinusoids and periodic train of pulses with distorted edges, numerically illustrate the components of voltage–current CSCF and the characteristics derived from it. In addition, the generalization of Tellegen’s theorem, suggested in the paper, leads to the immediate formulation of the power conservation law for each CSCF component separately.