bluuebunny/crossref_metadata_2025 huggingface dataset:
Unsupervised Learning Data-Driven Continuous QoE Assessment in Adaptive Streaming-Based Television System
Authors: Andruloniw Paweł , Kowalik Karol , Zwierzykowski Piotr
Published: August 2022

The quality of experience (QoE) assessment of adaptive video streaming may be crucial for detecting degradations impacting customer satisfaction. In a telecommunication environment, eliminating failure points may be the highest priority. This study aims to assess the QoE level of the video played by the STB device connected to the production TV system. The evaluation has been based on the stalling effects, video quality changes, and the time related to the last decreased bitrate change occurrence. The two-phase continuous clustering approach has been studied to assess the QoE level based on the ACR scale. The number of devices with grades 1 or 2 is relatively low, but those devices generate significantly more events than adequately functioning devices. STBs try to play the highest possible bitrate, and there is no possibility of setting the intermediate bitrate level. The STB player does not have the button to set the quality level, usually available in pure over-the-top applications. Hence the bitrate fluctuations that can annoy customers appear for the lowest grades. The boundary cases can be easily assessed. The outcome should be challenged by the customers’ opinions to find the proper QoE threshold. Continuous clustering may allow telecom operators to assess customer satisfaction with their TV service.
Advanced Composite Materials: A Panacea for Improved Electricity Transmission
Authors: Ujah Chika Oliver , Kallon Daramy Vandi Von , Aikhuele Daniel O. , Aigbodion Victor Sunday
Published: August 2022

The demand for electricity has increased drastically due to population explosion globally. Unfortunately, supply does not meet the demand. Consequently, the transmission grid becomes overloaded, culminating in frequent power outages. Worse still, the transmission grid lacks adequate maintenance, and this has led to energy crisis in Africa and some parts of Asia. In this review, studies on the strength and weaknesses of existing transmission conductors were conducted. Further studied were natural and artificial phenomena that attack the overhead transmission networks. It was observed that besides inherent conductor defects, overloading, bush fire, short-circuit, harsh weather, and lightning were the factors that ravage the transmission grid. Hence, there is the need to develop more robust conductor materials that can withstand these challenges. The conventional conductors such as all aluminum conductor (AAC) and aluminum conductor steel reinforced (ACSR) are challenged by low operating temperatures, among others. High-temperature low-sag (HTLS) conductors that were invented to tackle these shortcomings certainly have higher ampacity and better thermal rating than the conventional conductors. However, some challenges still devastate them. So, from the study conducted, it was discovered that developing advanced nano-based Al-composite conductor would help in ameliorating the challenges prevalent in the transmission grid. Such an Al-nanocomposite conductor would possess higher ampacity and better thermal stability and would be more durable and cost effective.
Electrofenton with Reticular Vitreous Carbon and Iron Oxide Nanoparticles for Dye Removal: A Preliminary Study
Authors: Rivera Fernanda L. , Menendez Nieves , Mazarío Eva , Herrasti Pilar
Published: August 2022

In this work, an RVC electrode coated with magnetic iron oxide nanoparticles was used for the degradation of methylene blue as a model dye. The electrofenton process was carried out by the reduction of oxygen dissolved in the electrolyte on the modified RVC electrode to produce hydrogen peroxide. The presence of the magnetite/maghemite nanoparticles in the structure produces the formation of OH∙ radicals that oxidize methylene blue. The RVC/coated was prepared by two different methodologies: Methodology A: by immersion of the electrode in a solution saturated with magnetite nanoparticles; and Methodology B: by electrochemical synthesis. Scanning electron microscopy, X-ray diffraction and Mössbauer spectroscopy shows a uniform coating of the electrode. The Mössbauer spectroscopy determines the only presence of maghemite using methodology A and the presence of 60% of magnetite and a 40% of maghemite when methodology B was used. The dipping methodology is the one that has provided the best results in the electrofenton degradation of methylene blue, obtaining a 100% removal after 35 min, applying a current of 100 mA in a 20 mg L−1 solution of methylene blue, and a concentration of 50 mM sodium sulfate.
On the Resonant Vibrations Control of the Nonlinear Rotor Active Magnetic Bearing Systems
Authors: Saeed Nasser A. , El-Shourbagy Sabry M. , Kamel Magdi , Raslan Kamal R. , Awrejcewicz Jan , Gepreel Khaled A.
Published: August 2022

Nonlinear vibration control of the twelve-poles electro-magnetic suspension system was tackled in this study, using a novel control strategy. The introduced control algorithm was a combination of three controllers: the proportional-derivative (PD) controller, the integral resonant controller (IRC), and the positive position feedback (PPF) controller. According to the presented control algorithm, the mathematical model of the controlled twelve-poles rotor was established as a nonlinear four-degree-of-freedom dynamical system coupled to two first-order filters. Then, the derived nonlinear dynamical system was analyzed using perturbation analysis to extract the averaging equations of motion. Based on the extracted averaging equations of motion, the efficiency of different control strategies (i.e., PD, PD+IRC, PD+PPF, and PD+IRC+PPF) for mitigating the rotor’s undesired vibrations and improving its catastrophic bifurcation was investigated. The acquired analytical results demonstrated that both the PD and PD+IRC controllers can force the rotor to respond as a linear system; however, the controlled system may exhibit the maximum oscillation amplitude at the perfect resonance condition. In addition, the obtained results demonstrated that the PD+PPF controller can eliminate the rotor nonlinear oscillation at the perfect resonance, but the system may suffer from high oscillation amplitudes when the resonance condition is lost. Moreover, we report that the combined control algorithm (PD+IRC+PPF) has all the advantages of the individual control algorithms (i.e., PD, PD+IRC, PD+PPF), while avoiding their drawbacks. Finally, the numerical simulations showed that the PD+IRC+PPF controller can eliminate the twelve-poles system vibrations regardless of both the excitation force magnitude and the resonant conditions at a short transient time.
Hybrid VOF–Lagrangian CFD Modeling of Droplet Aerobreakup
Authors: Rossano Viola , De Stefano Giuliano
Published: August 2022

A hybrid VOF–Lagrangian method for simulating the aerodynamic breakup of liquid droplets induced by a traveling shock wave is proposed and tested. The droplet deformation and fragmentation, together with the subsequent mist development, are predicted by using a fully three-dimensional computational fluid dynamics model following the unsteady Reynolds-averaged Navier–Stokes approach. The main characteristics of the aerobreakup process under the shear-induced entrainment regime are effectively reproduced by employing the scale-adaptive simulation method for unsteady turbulent flows. The hybrid two-phase method combines the volume-of-fluid technique for tracking the transient gas–liquid interface on the finite volume grid and the discrete phase model for following the dynamics of the smallest liquid fragments. The proposed computational approach for fluids engineering applications is demonstrated by making a comparison with reference experiments and high-fidelity numerical simulations, achieving acceptably accurate results without being computationally expensive.
Correlation between Bladder Neck Preservation, Positive Surgical Margins, and Biochemical Recurrence in Laparoscopic and Open Radical Prostatectomy: A Prospective Cohort Study
Authors: Kajmakovic Boris M. , Petrovic Milos , Bulat Petar , Bumbasirevic Uros , Milojevic Bogomir , Bukumiric Zoran , Cvijanovic Djordje , Skrijelj Daniel , Jovanovic Aleksandar , Hadzibegovic Adi , Ratkovic Sanja , Dzamic Zoran
Published: August 2022

Background: Bladder neck preservation (BNP) has been adopted in open (ORP), laparoscopic (LRP), and robot-assisted radical prostatectomy (RARP). However, there are concerns that this technique can compromise oncological outcome and increase positive surgical margins (PSM). The aim was to evaluate the outcome of BNP, focusing on surgical and pathological outcomes, as well as biochemical recurrence (BCR). Methods: We prospectively collected demographic and clinical data from 170 consecutive patients who underwent ORP and LRP between 2014 and 2020. ORP was performed in 63 patients, and the rest underwent LRP. BNP was performed in 85 patients. Results: PSM were found in 24.7% of patients. Of patients with BNP, 22.4% had PSM. There was no significant statistical difference between patients with or without BNP in the form of PSM. Base-positive margins were detected in 9.4% of patients with BNP and in 5.9% of patients without BNP with no statistical significance. Bioptic Gleason score, clinical stage, and preoperative PSA were statistically significantly correlated with PSM. BCR was more common in patients without BNP (23.5%) vs. non-BNP (21.2%). The only statistically significant predictor of BCR was PSM. Conclusion: This study suggests that BNP in RP is not associated with an increased level of PSM. Preoperative PSA, bioptic Gleason score, and clinical T stage of disease were identified as predictors of PSM occurrence.
Analysis of the Physiognomy of Unique Sets in the Maximum Number of Repetitions Strategy—The Case of One-Arm Scott Machine Seated Bicep Curls
Authors: Petre Ioana Mdlina , Boscoianu Mircea , Oancea Bogdan , Chicomban Mihaela , Turcu Ioan , Simion Gabriel
Published: August 2022

The aim of this paper is to analyze the physiognomy of unique sets in the maximum number of repetitions (MNR) strategy and different correlations between the maximal forces, duration and volume for a relevant exercise in the case of a small muscle group. The research methodology proposes testing, in two phases, a total of 30 male students, for bicep curl exercises carried out on a bicep Scott machine. The obtained results showed that there were significant differences between the maximum forces (Fmax) developed during the initial and final repetitions of the exercise sets or for different machine loads. There was a large correlation between the load and Fmax and an inverse correlation between the load and MNR or between the MNR and Fmax. The deterioration of the execution mode, represented by the profile of the final repetition of high-duration sets, was also tested and analyzed. We concluded that the study of the physiognomy of cycles and comparisons at the level of relevant repetitions have revealed new perspectives for the design of periodization strategies, for the possibility of manipulating adapted muscular response or compensatory acceleration training for small muscle groups or the MNR strategy.
Hydro Statistical Assessment of TRMM and GPM Precipitation Products against Ground Precipitation over a Mediterranean Mountainous Watershed (in the Moroccan High Atlas)
Authors: Benkirane Myriam , Laftouhi Nour-Eddine , Khabba Saïd , Hera-Portillo África de la
Published: August 2022

The tropical Rainfall Measuring Mission TRMM 3B42 V7 product and its successor, the Global Precipitation Measurement Integrated Multi-satellitE Retrievals for GPM IMERG high-resolution product GPM IMERG V5, have been validated against rain gauges precipitation in an arid mountainous basin where ground-based observations of precipitation are sparse, or spatially undistributed. This paper aims to evaluate hydro-statically the performances of the TRMM 3B42 V7 and GPM IMERG V05 satellite precipitations products SPPs, at multiple temporal scales, from 2014 to 2017. SPPs are compared with the gauge station and show good results for both statistical and contingency metrics with notable values R > 0.94. Moreover, the rainfall-runoff events implemented on the hydrological model were performed at 3-hourly time steps and showed satisfactory results based on the obtained Nash–Sutcliffe criteria ranging from 94.50% to 57.50%, and from 89.3% to 51.2%, respectively. The TRMM product tends to underestimate and not capture extreme precipitation events. In contrast, the GPM product can identify the variability of precipitation at small time steps, although a slight underestimation in the detection of extreme events can be corrected during the validation steps. The proposed method is an interesting approach for solving the problem of insufficient observed data in the Mediterranean regions.
Elastic–Plastic Mechanical Behavior Analysis of a Nb3Sn Superconducting Strand with Initial Thermal Damage
Authors: Zhang Zhichao , Shi Lifan
Published: August 2022

It is well known that the parameters of Nb3Sn superconducting strands are strain sensitive, and the internal brittle Nb3Sn filament can easily break under deformations. A temperature difference from the preparation temperature of about 1000 K to the cryogenic working environment of 4.2 K damages brittle Nb3Sn fibers before working. Based on the Curtin–Zhou model, the damage theory for fiber-reinforced composites is utilized to study the influence of filament fractures caused by thermal stress. According to the typical multi-scale geometric of the EAS-Nb3Sn strand (European Advanced Superconductor, EAS), an efficient hierarchical homogenized calculation model considering filament fracture and matrix plasticity was established. In this work, we took the filament fracture caused by both thermal stresses and mechanical loads into consideration using the secant modulus and simultaneously had the impact of the plastic constitutive of the bronze matrix and the copper protective layer. Mechanical parameters, such as the homogenized secant modulus, shear modulus, and Poisson’s ratio in different directions of level scale, were predicted at various temperatures. The elastoplastic mechanical behavior of the strands subjected to axial load was analyzed, and the results were in good agreement with the experiment. The initial thermal fiber fracture has non-negligible effects on the mechanical properties of the EAS-Nb3Sn superconducting strand and play the role in accelerating the increase in fiber breakage.
Current Issues in Combating Chemical, Biological, Radiological, and Nuclear Threats to Empower Sustainability: A Systematic Review
Authors: Gawlik-Kobylińska Małgorzata
Published: August 2022

Combating chemical, biological, radiological, and nuclear (CBRN) threats with novel solutions reduces disasters and accident risks and, at the same time, aids sustainability. This research aims to identify the innovations in combating CBRN threats and verify how they fall within the scope of the Sustainable Development Goals (SDG). The study relies on mixed-method research, including bibliometrics and text-mining used to identify clusters, most frequent words, and codes. The material for the research was 156 publications from the Scopus database from 2017 to April 2022. From the analytical process, textual data served as the indicators of the innovations’ directions driven by SDGs. The research results indicated that innovations for combating CBRN threats support sustainability mainly in health and environmental areas, specifically in: SDG 3: Good Health and Well-being; SDG 6: Clean Water and Sanitation; SDG 14: Life Below Water; SDG 15: Life On Land. The research contributes to the landscape of innovations serving sustainable development. Further studies may focus on narrower perspectives, such as environmental protection and health innovations. There can also be concerns about the dark side of CBRN innovations and technologies of dual use.
Development of Korea Airport Pavement Condition Index for Panel Rating
Authors: Cho Nam-Hyun , Kwon Hong-Joon , Suh Young-Chan , Kim Jangrak
Published: August 2022

Airports strive to prevent safety issues, such as foreign object debris (FOD), by pavement management using the pavement condition index (PCI). The index is used in decision-making processes for overall pavement maintenance and repair, such as the prevention of additional damage due to cracks and the like. However, considering the current situation in Korea where mostly mid-sized and large commercial airports exist, problems regarding direct applications of the existing PCI deduct value have been consistently pointed out. In addition, as the relationship between the PCI and whether maintenance and repair are required is unrealistic, there have been difficulties in communication between maintenance and repair staff and decision makers. Therefore, to resolve these problems, this study first analyzed the calculation procedure of the existing PCI and then redefined the main distress type of Korean airport pavements. In addition, a deduct value curve (DVC) in terms of the severity level for six main distress factors of asphalt pavements and eight main distress factors of concrete pavements and a corrected deduct value curve (CDVC) for multiple distresses in terms of the pavement form were developed using panel rating, which is an engineering approach, by forming an airport pavement expert panel. Finally, a Korea airport pavement condition index (KPCI) was proposed using the curves, and the field application results were compared against the existing PCI to examine the adequacy of the KPCI. As a result, the developed criteria showed an overall trend lower than existing PCI. Moreover, it was verified that this trend increases with worsening pavement condition. It appears that a more discriminating evaluation may be possible when determining pavement conditions by PCI results of the developed criteria.
Analysis of Technologies for Carbon Dioxide Capture from the Air
Authors: Leonzio Grazia , Fennell Paul S. , Shah Nilay
Published: August 2022

The increase in CO2 concentration in the atmosphere has prompted the research community to find solutions for this environmental problem, which causes climate change and global warming. CO2 removal through the use of negative emissions technologies could lead to global emission levels becoming net negative towards the end of this century. Among these negative emissions technologies, direct air capture (DAC), in which CO2 is captured directly from the atmosphere, could play an important role. The captured CO2 can be removed in the long term and through its storage can be used for chemical processes, allowing closed carbon cycles in the short term. For DAC, different technologies have been suggested in the literature, and an overview of these is proposed in this work. Absorption and adsorption are the most studied and mature technologies, but others are also under investigation. An analysis of the main key performance indicators is also presented here and it is suggested that more efforts should be made to develop DAC at a large scale by reducing costs and improving efficiency. An additional discussion, addressing the social concern, is indicated as well.
Two-Stage Adaptive Large Neighbourhood Search for Team Formation and Worker Assignment Problems in Cellular Manufacturing Systems
Authors: Pasupa Thanatat , Suzuki Sadami
Published: August 2022

We present a novel mathematical programming model to address a team-oriented worker assignment problem, called the team formation and worker assignment problem (TFWAP). The model establishes a multi-skilled team with high group cohesion to meet cell operational requirements. To this end, we developed a two-stage decision methodology based on an adaptive large neighbourhood search (ALNS) method as a solution approach. The first stage was a team formation problem that maximised workers’ skills. The second stage was a worker assignment problem that minimised the total inventory level and variations in the average cell worker’s idle time. The performance of the two-stage ALNS method was assessed on ten cell formation benchmarks selected from the literature. The computational results show that the two-stage ALNS method could provide a solution equivalent to the exact method based on the heuristic-based brute force search (HBBFS) for small instances in the team formation stage. Moreover, the two-stage ALNS method outperformed the non-dominated sorting genetic algorithm-II (NSGA-II)-based single-stage decision methodology on all ten cell formation benchmarks in the worker assignment stage. Finally, the two-way analysis of variance (ANOVA) test highlighted the impact of the cell-cohesion requirement on performance when forming a team in a cell.
A Computer-Aided Diagnostic System for Diabetic Retinopathy Based on Local and Global Extracted Features
Authors: Haggag Sayed , Elnakib Ahmed , Sharafeldeen Ahmed , Elsharkawy Mohamed , Khalifa Fahmi , Farag Rania Kamel , Mohamed Mohamed A. , Sandhu Harpal Singh , Mansoor Wathiq , Sewelam Ashraf , El-Baz Ayman
Published: August 2022

Diabetic retinopathy (DR) is a major public health problem and the leading cause of vision loss in the working age population. This paper presents a novel deep learning system for the detection and diagnosis of DR using optical coherence tomography (OCT) images. The input for this system is three-channel local and global information from OCT images. The local high-level information is represented by the thickness channel and the reflectivity channel. The global low-level information is represented by the grey-level OCT original image. The deep learning system processes the three-channel input to produce the final DR diagnoses. Experimental results on 200 OCT images, augmented to 800 images, which are collected by the University of Louisville, show high system performance related to other competing methods. Moreover, 10-fold and leave-one-subject-out (LOSO) experiments are performed to confirm how significant using the fused images is in improving the performance of the diagnoses, by investigating four different CNN architectures. All of the four architectures achieve acceptable performance and confirm a significant performance improvement using the fused images. Using LOSO, the best network performance has improved from 90.1 ± 2% using only the grey level dataset to 97.7 ± 0.5% using the proposed fused dataset. These results confirm the promise of using the proposed system for the detection of DR using OCT images.
An Experimental Study on the Microstructure Evolution of Soil under Lateral Consolidation Compression
Authors: Zhang Xiao , Ding Zhi , He Shao-Heng , Zhang Gui-Di , Sun Miao-Miao , Xia Tang-Dai
Published: August 2022

Based on the lateral consolidation compression experiment of remolded soil simulating the effects of pile driving and soil squeezing, in this paper, the microstructures of soil with different degrees of lateral consolidation were investigated by a scanning electron microscope. Combined with Image-Pro Plus software to process data, parameters such as the equivalent diameter, porosity, circularity, directional frequency and fractal dimension of the soil microstructure were analyzed. The results demonstrate that the microstructure of the soil sample before consolidation was debris, aggregated particles and irregular flake aggregates. Following consolidation, the microstructure became a closed flake structure, where an obvious agglomeration phenomenon occurred. During the process of lateral consolidation compression, the large pore structure was more likely to be compressed and damaged, resulting in a decrease in the equivalent pore diameter and plane porosity, the approaching of circularity towards unity and an increase in the compaction and homogenization of soil with obvious directionality. Soil particles moved continuously under the action of consolidation compression to adjust the microstructure, and the fractal dimension gradually increased. Then, as consolidation compression continued, it gradually developed to a new equilibrium state, where the fractal dimension began to decrease and approach stability.
Low-Frequency Terahertz Photonic Crystal Waveguide with a Lilac-Shaped Defect Based on Stereolithography 3D Printing
Authors: Shi Jia , Ding Yiyun , Tang Longhuang , Li Xiuyan , Bai Hua , Li Xianguo , Fan Wei , Niu Pingjuan , Fu Weiling , Yang Xiang , Yao Jianquan
Published: August 2022

Terahertz (THz) photonic crystal (PC) waveguides show promise as an efficient and versatile waveguiding platform for communication, sensing, and imaging. However, low-frequency THz PC waveguides with a low-cost and easy fabrication remain challenging. To address this issue, a THz PC waveguide with a lilac-shaped defect has been designed and fabricated by 3D printing based on stereolithography (SLA). The reflection and transmission characteristics of the proposed waveguide have been analyzed using the finite difference frequency domain (FDFD) method. The waveguide spectral response is further optimized by changing the distance of the lilac-shaped resonant cavities. Consistent with the results of numerical modeling, the measured results show that the waveguide performs a resonant reflection in the region of 0.2 to 0.3 THz and low-pass transmission in the 6G mobile communication window. Furthermore, in order to characterize the performance of the proposed waveguide, parameters have been analyzed, including the Q factor, resonant frequency, and bandwidth. This work supplies a novel pathway for the design and fabrication of a low-frequency THz PC waveguide with potential applications in communication, sensing, and imaging.
Phenolic Compounds, Antioxidant Activity, Ascorbic Acid, and Sugars in Honey from Ingenious Hail Province of Saudi Arabia
Authors: Alshammari Ghedeir Muslem , Ahmed Mohammed Asif , Alsulami Tawfiq , Hakeem Mohammed Jamal , Ibraheem Mohamed Abdrabo , Al-Nouri Doha M.
Published: August 2022

Bioactive compounds are responsible for biological activities in honey. The botanical and regional sources of honey contribute to the variable concentration of bioactive compounds. This paper reports the analysis of bioactive compounds such as phenolic compounds, vitamin C, total phenolic contents (TPC), radical scavenging activity (RSA), and sugars of five honey samples (Talh, Athel, Sidr, Spring flower, and Langnese) from the ingenious Hail region (Saudi Arabia) using HPLC-RID and DAD. Talh has the highest TPC level of 26.9 mg GAE/100 g, whereas Spring flower has the lowest level of 8.2 mg GAE/100 g. Quercetin levels in all samples ranged from 0.28 to 2.68 mg GAE/100 g. Gallic acid, a phenolic compound, was found in three samples of honey at concentrations ranging from 0.81–1.08 mg/100 g. DPPH radical scavenging activity (RSA) of Talh and Sidr honey sample are found to be high as compared to other samples. The Sidr honey sample had the highest vitamin C content, 2.59 mg/100 g. Fructose and glucose sugar concentrations ranged from 28.35–37.81 g/100 g and 20.21–32.28 g/100 g, respectively, with a higher fructose ratio. Sucrose was not found in any of the five samples. These findings point to the high quality of honey produced in Saudi Arabia’s ingenious Hail province, and therefore may contribute in therapeutic use of these types of honey, such as in complementary and alternative medicine.
Comparison of Temperature Characteristics of Outer Rotor Low-Speed PM Motors Considering Magnetic Load and Current Density
Authors: Du Guanghui , Zhang Qizheng , Zhou Qixun , Hu Chengshuai , Pu Tao
Published: August 2022

In the electromagnetic design process of the outer rotor of a low-speed permanent magnet motor (LSPMM), due to the different heat dissipation conditions of the stator core and the stator winding, the selection of different magnetic loads and stator current densities will produce different temperature distributions even under the same efficiency. In the existing literature, the effects of magnetic load and current density on temperature distribution are rarely studied, which makes it difficult for designers to select optimal electromagnetic parameters to achieve better temperature performance. Therefore, in this paper, the comparison of temperature characteristics considering magnetic load and current density is conducted based on an outer rotor LSPMM. Firstly, the structure and parameters of an initial scheme of a 200 kW 56 rpm motor is determined, and the electromagnetic and temperature characteristics of the initial scheme are obtained through two-dimensional finite element analysis (2D-FEA) using Ansys Maxwell and Motor-CAD software. Secondly, by comparing the temperature and loss characteristics under different magnetic loads and different current densities, the effect of magnetic load on temperature and the effect of current density on temperature are obtained. Furthermore, four different schemes are proposed, and the loss and temperature characteristics of the four schemes under rated load are also compared to obtain the comprehensive effects of magnetic load and current density on temperature. Next, a final scheme is determined based on the above analysis, and the temperature characteristics of the final scheme and the initial scheme are compared to verify the validity of the conclusions. Finally, a prototype is built and tested to verify the feasibility of the conclusions. For LSPMM design, the results and several measurements provided in this paper can help researchers to choose a better optimization scheme to achieve good temperature performance.
A Critical Review on Obesity: Herbal Approach, Bioactive Compounds, and Their Mechanism
Authors: Kumar Mukul , Kaushik Deepika , Kaur Jasjit , Proestos Charalampos , Oz Fatih , Oz Emel , Gupta Prerna , Kundu Priyanka , Kaur Anmol , Anisha Anisha , Ritika Ritika
Published: August 2022

Obesity is arising as a global pandemic throughout the world. Over the past few decades, obesity has tripled worldwide, creating an alarming situation. The majority of people nowadays are suffering from obesity and overweight. It affects health of people of all age groups, ethnicity, gender, and sex, and is linked to a sedentary lifestyle of people, poor eating habits, and disturbed sleeping patterns. It causes several diseases such as diabetes mellitus type 2, hypertension, cardiovascular diseases, asthma, gallstones, and colon cancer. Many synthetic anti-obesity drugs such as orlistat, lorcaserin, phentermine, bupropion, and liraglutide are already available on the market. However, these drugs have side effects, including dry mouth and sleeping disorders, dizziness, blood pressure, heart rate elevation, constipation, and headache. Humans have a long and ancient history of dependency on traditional medicinal plants and their major bioactive antioxidant components, such as quercetin, anthocyanins, and ellagic acid, for treating such diseases and disorders. This review discusses the herbal approach, bioactive compounds, and their mechanism for treating obesity.
Research on Landscape Perception and Visual Attributes Based on Social Media Data—A Case Study on Wuhan University
Authors: Zhang Xia , Xu Danning , Zhang Ni
Published: August 2022

With the rapid rise of social media, the photo-taking behavior of tourists and their uploaded photos provide a new perspective to explore landscape visual characters. In this study, we provide methodological advancements for assessing landscape visual quality based on content analysis of user-generated photographs. The purpose is to demonstrate an empirical method for evaluating visual indicators reflected in photographs through a case study application. This research takes the core cultural landscape area of Wuhan University as the research scope. The photographs shared on a famous Chinese social media platform Sina Weibo during the Cherry Blossom Festival, together with tourists’ trajectory data, were used as data sources. Based on a fixed-point photography experiment, the spatial relationship between the scenic spot and the observation point was illustrated. Utilizing a semi-automatic photo content analysis founded on computer vision technology, landscape visual attributes of each attraction were studied thoroughly regarding complexity, visual scale, and color. The results indicate that the Old Dormitory is the most popular scenic spot with diverse viewing angles, strikingly vivid colors, and rich color combinations. Complexity and color play key roles in landscape visual quality, while the depth of view has a subtle impact, which suggests the depth-to-height ratio of less than 1 is the best distance for viewers to take photographs. In all, the mapping relationship between landscape visual attributes and viewers’ perception was revealed in the present work.
Development of Deformation Bands and Deformation Induced Weathering in a Forearc Coal-Bearing Paleogene Fold Belt, Northern Japan
Authors: Kaji Hiromi , Takeshita Toru
Published: August 2022

We conducted microstructural and microchemical analyses of deformation bands in a forearc fold belt consisting of the Eocene Urahoro Group located in northern Japan. In the study area, there was one flexure (or monocline) developed where deformation bands pervasively occurred in arkosic sandstone intercalated with mudstone and coal layers. Deformation bands formed at the maximum burial depth of c. 1.5–2.5 km; this was inferred from both the thickness of the overlying strata and vitrinite reflectance values (%RO) of the coal layers (c. 0.5). These bands were inferred to have originated as phyllosilicate bands, which developed into cataclastic bands with increasing strain on sandstones with up to c. 10% volume of phyllosilicate. In the cataclastic bands, the detrital grains in the host parts were crushed into sizes less than one-half to one-fifth of the original ones, and the long axis of the fractured grains tended to align parallel to the deformation bands. It was found that the deformation bands became a site of intense weathering at later stages, where not only detrital biotite grains were altered to vermiculite and kaolinite, but also authigenic clay minerals such as smectite grew in pore spaces created by the fracturing of detrital grains.
Conditional Generative Adversarial Networks for Domain Transfer: A Survey
Authors: Zhou Guoqiang , Fan Yi , Shi Jiachen , Lu Yuyuan , Shen Jun
Published: August 2022

Generative Adversarial Network (GAN), deemed as a powerful deep-learning-based silver bullet for intelligent data generation, has been widely used in multi-disciplines. Furthermore, conditional GAN (CGAN) introduces artificial control information on the basis of GAN, which is more practical for many specific fields, though it is mostly used in domain transfer. Researchers have proposed numerous methods to tackle diverse tasks by employing CGAN. It is now a timely and also critical point to review these achievements. We first give a brief introduction to the principle of CGAN, then focus on how to improve it to achieve better performance and how to evaluate such performance across the variants. Afterward, the main applications of CGAN in domain transfer are presented. Finally, as another major contribution, we also list the current problems and challenges of CGAN.
Rethinking Academic Conferences in the Age of Pandemic
Authors: Cai Qing , Du Zhanwei , Wu Ye , Xu Xiaoke
Published: August 2022

The year 2020 witnessed the havoc wreaked by the coronavirus disease COVID-19 due to its onset in late 2019. The COVID-19 pandemic is the cruelest public health crisis humankind has ever seen. The COVID-19 pandemic profoundly affected every walk of life, and academic research has been no exception. Academic conferences are an indispensable component of research. Note that the pandemic together with its variants ravaged the globe in 2020, while their recurrences yet have a deep shadow across 2021 and 2022 with uncertainties for the near future. Under the sway of the pandemic, many conferences are conducted in virtual mode to mitigate the propagation of the virus. It is no surprise that academic conferences charge the attendees for registration fees with the amount varying by countries and disciplines. Here, we collect the registration fee information for conferences held in 2019, 2020 and 2021. Note that virtual conferences barely cater to attendees except by providing online platforms. However, we discover that most of the virtual conferences held in 2020 and 2021 still charged high registration fees compared to those in 2019, while the remaining conferences only applied small discounts. In light of the current situation of the pandemic as well as uncertainties in the future, virtual conferences could be a common form of academic activity. Considering the sluggish global economy at well as other potential issues, here, we advocate that going virtual should always be an option for academic conferences in the future. We also suggest that virtual conferences should charge less and the expenditure of the fees should be open to the public.
Otologic Manifestations of IgG4-Related Disease: Literature Review and Report of Two Cases
Authors: Sapir Aviad , Kaplan Daniel M. , Samueli Benzion , Novoa Rosa , Hilly Ohad , El-Saied Sabri
Published: August 2022

Background: IgG4-related disease (IgG4-RD) is an inflammatory process. The literature on IgG4-RD is rather limited, with mastoid involvement being uncommon. In such cases, presentation may mimic other middle ear and mastoid cavity pathologies. Objective: To summarize findings of patients with IgG4-RD involving the mastoid. Methods: Description of two new cases and summary of findings with previous reports. Results: Nineteen cases of IgG4-RD with mastoid bone involvement were reported in the literature, the earliest appearing at the beginning of the previous decade. Most frequent symptoms included hearing deterioration, tinnitus and otalgia. In 58% of the cases, the process was restricted to otologic manifestations. In 7 out of 19 cases, tissue IgG4 levels were elevated. In all histopathologic samples taken from the operative sites, a dense lymphoplasmacytic cell infiltration was observed. Following definitive pathological diagnosis, the most common treatment was corticosteroids. Generally, the time from onset to final diagnosis was usually more than six months. The treatment is corticosteroids, followed by immunosuppressive agents such as rituximab, cyclophosphamide, and methotrexate. Conclusions: IgG4-RD involving the mastoid is a challenging condition, both in diagnosis and treatment. Hence, IgG4-RD should be included in the differential diagnosis of middle ear pathologies and include a multi-disciplinary team for treatment.
An Organizational and Governance Model to Support Mass Collaborative Learning Initiatives
Authors: Zamiri Majid , Sarraipa João , Camarinha-Matos Luis , Jardim-Goncalves Ricardo
Published: August 2022

Mass collaboration can bring about major transformative changes in the way people can work collectively. This emerging paradigm promises significant economic and social benefits and enhanced efficiency across a range of sectors, including learning and education. Accordingly, this article introduces, demonstrates in use, and evaluates an organizational and governance model designed to provide guidance and execution support for the implementation and operation of mass collaborative learning initiatives. The design science research process is adopted to guide the design and development of the proposed model. The model stands on three streams of work, addressing key aspects and elements that have a supporting influence on community learning: (i) identify the positive and negative factors in existing and active examples of mass collaboration; (ii) adopt contributions of collaborative networks in terms of structural and behavioral aspects; and (iii) establish adequate learning assessment indicators and metrics. The model is used for a case study in which vocational education and training meet the needs of collaborative education–enterprise approaches. Initially, the validation of the model is verified by the partners and stakeholders of a particular project in the area of education–enterprises relations to ensure that it is sufficiently appropriate for applications in a digital platform developed by such projects. The three first steps of (the proposed) applicability evaluation (adequacy, feasibility, and effectiveness) are then performed. The positive results gained from model validation and its applicability evaluation in this project indicate that not only is the model fairly adequate, feasible, and effective for applications in the developed digital platform but also that it has a high potential for utilization in supporting and directing the creation, implementation, and operation of mass collaborative learning initiatives. Although the validation was carried out in the context of a single project, in fact, it was based on a large “focus group” of experts involved in this international initiative, which is in accordance with the Design Science Research method. Thus, this article reflects a kind of applied research of a socio-technical nature, aiming to find guidelines and practical solutions to the specific issues, problems, and concerns of mass collaborative learning initiatives.
A GIS Partial Discharge Defect Identification Method Based on YOLOv5
Authors: Lu Yao , Qiu Zhibin , Liao Caibo , Zhou Zhibiao , Li Tonghongfei , Wu Zijian
Published: August 2022

The correct identification of partial discharge types is of great significance to the stable operation of GIS. In order to improve the recognition accuracy and result of partial discharge, and to meet the requirements of real-time monitoring of GIS equipment, this paper proposes a GIS partial discharge defect recognition model based on YOLOv5. First, the GIS partial discharge simulation experiment is established to create the dataset of partial discharge PRPD map. Then, a YOLOv5-based GIS partial discharge defect recognition model is constructed, and different training methods are used to optimize the parameters of the model. By comparing with target detection models based on other deep learning methods, such as Faster-RCNN and YOLOv4, the YOLOv5 model discussed in the paper has significantly improved the recognition efficiency and recognition accuracy, in which mAP value is 95.89% and FPS is 28.89. In addition, the model can realize the distinction and identification of multiple PD types in a single PRPD map. At last, the YOLOv5-based GIS partial discharge defect identification model is applied to the test in a 500 kV substation. The model accurately determines the type of GIS partial discharge, which verifies the accuracy and validity of the model.
Artificial Intelligence Synergetic Opportunities in Services: Conversational Systems Perspective
Authors: Rozenes Shai , Cohen Yuval
Published: August 2022

The importance of this paper is its discovery of the unused synergetic potential of integration between several AI techniques into an orchestrated effort to improve service. Special emphasis is given to the conversational capabilities of AI systems. The paper shows that the literature related to the use of AI in service is divided into independent knowledge domains (silos) that are either related to the technology under consideration, or to a small group of technologies related to a certain application; it then discusses the reasons for the isolation of these silos, and reveals the barriers and the traps for their integration. Two case studies of service systems are presented to illustrate the importance of synergy. A special focus is given to the conversation part of these service systems: the first case presents an application with high potential for integrating new AI technologies into its AI portfolio, while the second case illustrates the advantages of a mature application that has already integrated many technologies into its AI portfolio. Finally, the paper discusses the two case studies and presents inclusion relationships between AI capabilities to facilitate generating a roadmap for extending AI capabilities with synergetic opportunities.
Generation of Controlled Synthetic Samples and Impact of Hyper-Tuning Parameters to Effectively Classify the Complex Structure of Overlapping Region
Authors: Mahmood Zafar , Butt Naveed Anwer , Rehman Ghani Ur , Zubair Muhammad , Aslam Muhammad , Badshah Afzal , Jilani Syeda Fizzah
Published: August 2022

The classification of imbalanced and overlapping data has provided customary insight over the last decade, as most real-world applications comprise multiple classes with an imbalanced distribution of samples. Samples from different classes overlap near class boundaries, creating a complex structure for the underlying classifier. Due to the imbalanced distribution of samples, the underlying classifier favors samples from the majority class and ignores samples representing the least minority class. The imbalanced nature of the data—resulting in overlapping regions—greatly affects the learning of various machine learning classifiers, as most machine learning classifiers are designed to handle balanced datasets and perform poorly when applied to imbalanced data. To improve learning on multi-class problems, more expertise is required in both traditional classifiers and problem domain datasets. Some experimentation and knowledge of hyper-tuning the parameters and parameters of the classifier under consideration are required. Several techniques for learning from multi-class problems have been reported in the literature, such as sampling techniques, algorithm adaptation methods, transformation methods, hybrid methods, and ensemble techniques. In the current research work, we first analyzed the learning behavior of state-of-the-art ensemble and non-ensemble classifiers on imbalanced and overlapping multi-class data. After analysis, we used grid search techniques to optimize key parameters (by hyper-tuning) of ensemble and non-ensemble classifiers to determine the optimal set of parameters to enhance the learning from a multi-class imbalanced classification problem, performed on 15 public datasets. After hyper-tuning, 20% of the dataset samples are synthetically generated to add to the majority class of each respective dataset to make it more overlapped (complex structure). After the synthetic sample’s addition, the hyper-tuned ensemble and non-ensemble classifiers are tested over that complex structure. This paper also includes a brief description of tuned parameters and their effects on imbalanced data, followed by a detailed comparison of ensemble and non-ensemble classifiers with the default and tuned parameters for both original and synthetically overlapped datasets. We believe that the underlying paper is the first kind of effort in this domain, which will furnish various research aspects to with a greater focus on the parameters of the classifier in the field of learning from imbalanced data problems using machine-learning algorithms.