bluuebunny/crossref_metadata_2025 huggingface dataset:
Stress, Inflammation and Metabolic Biomarkers Are Associated with Body Composition Measures in Lean, Overweight, and Obese Children and Adolescents
Authors: Christaki Eirini V. , Pervanidou Panagiota , Papassotiriou Ioannis , Bastaki Despoina , Valavani Eleni , Mantzou Aimilia , Giannakakis Giorgos , Boschiero Dario , Chrousos George P.
Published: February 2022

The aim of this study was to examine the associations between multiple indices of stress, inflammation and metabolism vs. body composition parameters in 121 (43 boys, 78 girls) children and adolescents, aged 5–15 y. Subjects were divided into two groups: normal weight (N) (N = 40, BMI z-score = −0.1923 ± 0.6), and overweight/obese (OB) (N = 81, BMI z-score = 2.1947 ± 1.4). All subjects completed the State-Trait Anxiety Inventory for Children (STAIC) and Children’s Depression Inventory, and underwent cortisol measurements in hair, diurnal series of saliva, and morning serum. Circulating concentrations of high sensitivity C-reactive protein (hsCRP) and other inflammation biomarkers were also obtained. Body composition analysis was performed with a clinically validated, advanced bioimpedance apparatus (BIA), while heart rate variability (HRV) was measured as a stress biomarker by photoplethysmography (PPG). The OB group had a higher STAIC-state score, waist-to-hip ratio, skeletal muscle mass, and total and abdominal fat mass, and a lower percent fat-free mass (FFM) and bone density than the N group. HRV did not differ between the groups. In the entire population, percent fat mass correlated strongly with circulating hsCRP (r = 0.397, p = 0.001), ferritin, and other inflammatory biomarkers, as well as with indices of insulin resistance. A strong correlation between serum hsCRP and hair cortisol was also observed (r = 0.777, p < 0.001), suggesting interrelation of chronic stress and inflammation. Thus, body fat accumulation in children and adolescents was associated with an elevation in clinical and laboratory biomarkers of stress, inflammation, and insulin resistance. BIA-ACC and PPG can be utilized as a direct screening tool for assessing overweight- and obesity -related health risks in children and adolescents.
Nanomechanical and Electrochemical Properties of ZnO-Nanoparticle-Filled Epoxy Coatings
Authors: Samad Ubair , Alam Mohammad , Anis Arfat , Abdo Hany , Shaikh Hamid , Al-Zahrani Saeed
Published: February 2022

This work focuses on the mechanical, nanomechanical, thermal, and electrochemical properties of epoxy coatings with various percentages of ZnO nanoparticles. The prepared coatings were analyzed after complete curing of 7 days. The dispersion of nanoparticles in the matrix was analyzed by Scanning Electron Microscopy (SEM) followed by Fourier-Transformed Infrared Spectroscopy (FTIR) to evaluate the effect of the nanoparticles on curing and Differential Scanning Calorimetry (DSC) to evaluate its thermal properties. The electrochemical (anticorrosion) properties of the coatings were analyzed by exposing the prepared coatings to a 3.5% NaCl solution. The obtained results indicated that the addition of the nanoparticles was effective at lower loadings; higher loadings of the nanoparticles led to increased agglomeration because of higher particle–particle interaction. At higher nanoparticle loadings, the curing process was adversely affected, which led to lower curing percentage. The lower degree of curing affected the thermal, mechanical, and electrochemical properties. The increase in nanoparticle loading beyond 2% negatively affected the coating properties.
Photocatalytic Treatment of Methyl Orange Dye Wastewater by Porous Floating Ceramsite Loaded with Cuprous Oxide
Authors: Cheng Yue , Cao Ting , Xiao Zhiguo , Zhu Haijie , Yu Miao
Published: February 2022

It is well known that water treatment of printing and dyeing wastewaters is problematic. In order to decompose dyes from dyestuff wastewater and convert them into almost harmless substances for the natural environment, an easily prepared, efficient, practical, and easy-to-regenerate composite material was produced from porous floating ceramsite loaded with cuprous oxide (PFCC). The PFCC samples were prepared and characterized by X-ray diffraction spectroscopy (XRD), scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS). The material was applied for photocatalytic degradation of methyl orange (MO) in water. The results show that the maximal degradation rate of MO was 92.05% when the experimental conditions were as follows: cuprous oxide loading rate of 8%, PFCC dosage of 20 g/L, the reaction time of 2 h, pH value of 8, and solution initial concentration of 30 mg/L. The degradation processes of MO fits well with the Langmuir–Hinshelwood model in reaction kinetics, and the Freundlich model in reaction thermodynamics, respectively. The degradation mechanism of MO was considered from two perspectives—one was the synergetic effect of adsorption and photocatalytic oxidation, and the other was the strong oxidation of hydroxyl radicals produced by photocatalysts.
Experimental Study of Irradiation of Thin Oxide and Mo/Si Multilayers by High Brightness Broadband VUV/UV Radiation and Their Degradation
Authors: Telekh Victor D. , Pavlov Aleksei V. , Kirillov Daniil V. , Vorob’ev Evgeny V. , Turyanskiy Alexander G. , Senkov Viacheslav M. , Tsygankov Petr A. , Parada-Becerra Freddy F. , Vesnin Vladimir R. , Skriabin Andrei S.
Published: February 2022

This study discusses the main features of the irradiation of prospective multilayer coatings by VUV/UV radiation from compressed plasma flows. Such radiation is characterized by a broadband spectrum and high brightness fluxes. Oxide and Mo/Si bilayers were used as the basis of the reflective multilayers for the visible and UV ranges. A gas-dynamic response from the irradiated surfaces was studied with schlieren photography. The properties of original and irradiated multilayers were described with ultra violet visible infrared spectroscopy (UV-Vis-IR), X-ray diffraction (XRD), X-ray reflectometry, scanning electron microscopy (SEM) and other techniques. Data on the degradation of optical properties and surface morphology were obtained.
Left Anterior Sectorectomy: An Alternative to Left Hepatectomy for Tumors Invading the Distal Part of the Left Portal Vein
Authors: Garancini Mattia , Scotti Mauro Alessandro , Gianotti Luca , Ciulli Cristina , Carissimi Francesca , Uggeri Fabio , Degrate Luca , Braga Marco , Romano Fabrizio
Published: February 2022

Background: Liver tumors invading the distal part of the umbilical portion of the left portal vein usually require left hepatectomy. The recent introduction of the concept of left anterior sector, an independent anatomo-functional unit including the anterior portion of the left liver and supplied by the distal part of the umbilical portion of the left portal vein, could represent the rational for an alternative surgical approach. The aim of this study was to introduce the novel surgical procedure of ultrasound-guided left anterior sectorectomy. Methods: Among 92 consecutive patients who underwent hepatectomy, 3 patients with tumor invading the distal part of the umbilical portion of the left portal (two with colorectal liver metastases and one with neuroendocrine tumor liver metastases) underwent left anterior sectorectomy alone or in association with liver multiple metastasectomies. Results: Mean operation time was 393 min; post-operative morbidity and mortality were not observed. After a mean FU of 23 months (range 19–28), no local recurrence occurred. Conclusions: In presence of tumors invading the distal part of the umbilical portion of the left portal, left anterior sectorectomy could be considered as an anatomic radical surgical option that is safe but more conservative than a left hepatectomy.
Automated Diagnosis of Cervical Intraepithelial Neoplasia in Histology Images via Deep Learning
Authors: Cho Bum-Joo , Kim Jeong-Won , Park Jungkap , Kwon Gui-Young , Hong Mineui , Jang Si-Hyong , Bang Heejin , Kim Gilhyang , Park Sung-Taek
Published: February 2022

Artificial intelligence has enabled the automated diagnosis of several cancer types. We aimed to develop and validate deep learning models that automatically classify cervical intraepithelial neoplasia (CIN) based on histological images. Microscopic images of CIN3, CIN2, CIN1, and non-neoplasm were obtained. The performances of two pre-trained convolutional neural network (CNN) models adopting DenseNet-161 and EfficientNet-B7 architectures were evaluated and compared with those of pathologists. The dataset comprised 1106 images from 588 patients; images of 10% of patients were included in the test dataset. The mean accuracies for the four-class classification were 88.5% (95% confidence interval [CI], 86.3–90.6%) by DenseNet-161 and 89.5% (95% CI, 83.3–95.7%) by EfficientNet-B7, which were similar to human performance (93.2% and 89.7%). The mean per-class area under the receiver operating characteristic curve values by EfficientNet-B7 were 0.996, 0.990, 0.971, and 0.956 in the non-neoplasm, CIN3, CIN1, and CIN2 groups, respectively. The class activation map detected the diagnostic area for CIN lesions. In the three-class classification of CIN2 and CIN3 as one group, the mean accuracies of DenseNet-161 and EfficientNet-B7 increased to 91.4% (95% CI, 88.8–94.0%), and 92.6% (95% CI, 90.4–94.9%), respectively. CNN-based deep learning is a promising tool for diagnosing CIN lesions on digital histological images.
A Review of the Role of Imaging Modalities in the Evaluation of Viral Myocarditis with a Special Focus on COVID-19-Related Myocarditis
Authors: Adeboye Adedayo , Alkhatib Deya , Butt Asra , Yedlapati Neeraja , Garg Nadish
Published: February 2022

Viral myocarditis is inflammation of the myocardium secondary to viral infection. The clinical presentation of viral myocarditis is very heterogeneous and can range from nonspecific symptoms of malaise and fatigue in subclinical disease to a more florid presentation, such as acute cardiogenic shock and sudden cardiac death in severe cases. The accurate and prompt diagnosis of viral myocarditis is very challenging. Endomyocardial biopsy is considered to be the gold standard test to confirm viral myocarditis; however, it is an invasive procedure, and the sensitivity is low when myocardial involvement is focal. Cardiac imaging hence plays an essential role in the noninvasive evaluation of viral myocarditis. The current coronavirus disease 2019 (COVID-19) pandemic has generated considerable interest in the use of imaging in the early detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related myocarditis. This article reviews the role of various cardiac imaging modalities used in the diagnosis and assessment of viral myocarditis, including COVID-19-related myocarditis.
Predictive Factors for Successful Treatment of Deep Incisional Surgical Site Infections following Instrumented Spinal Surgeries: Retrospective Review of 1832 Cases
Authors: Kuroiwa Masahiro , Schol Jordy , Sakai Daisuke , Horikita Natsumi , Hiyama Akihiko , Katoh Hiroyuki , Yamamoto Yukihiro , Sato Masato , Watanabe Masahiko
Published: February 2022

Background: Surgical site infection (SSI) is a major complication in spinal instrumentation that is often difficult to treat. The purpose of this study was to identify and determine prognostic indicators for successful treatment of spine instrumentation SSI. Methods: Retrospectively, spine surgery cases were examined on SSI diagnosis. Post-instrumentation SSI patients were categorized as “Successful” if SSI subsided after single debridement. Patients in whom SSI did not subsided and/or required removal of instrumentation were classified as “Challenging”. We investigated the relation of treatment outcomes to patients and treatment factors. Results: A total of 1832 spinal instrumentation cases were recognized with 44 (2.40%) SSI cases. White blood cell count, C-reactive protein (CRP) levels, causative bacteria (i.e., S. Aureus or MRSA), trauma injury, and early-stage antimicrobial agent sensitivity correlated with treatment prognosis. Multivariate analysis highlighted CRP levels and applying early-stage sensitive antibiotics as potential impactful predictive factors for successful treatment. Conclusions: Our results demonstrated that early selection of sensitive antimicrobial agents is critical and emphasizes the potential for early-stage classification methods such as Gram staining. Additionally, S. Aureus and MRSA SSI formed significantly more challenging infections to treat, thus requiring consideration when deciding on instrumentation retention. These factors offer promising aspects for further large-scale studies.
Small Renal Masses without Gross Fat: What Is the Role of Contrast-Enhanced MDCT?
Authors: Repeckaite Gerta , Zviniene Kristina , Jankauskiene Justina , Basevicius Algidas , Milonas Daimantas
Published: February 2022

Increased detection of small renal masses (SRMs) has encouraged research for non-invasive diagnostic tools capable of adequately differentiating malignant vs. benign SRMs and the type of the tumour. Multi-detector computed tomography (MDCT) has been suggested as an alternative to intervention, therefore, it is important to determine both the capabilities and limitations of MDCT for SRM evaluation. In our study, two abdominal radiologists retrospectively blindly assessed MDCT scan images of 98 patients with incidentally detected lipid-poor SRMs that did not present as definitely aggressive lesions on CT. Radiological conclusions were compared to histopathological findings of materials obtained during surgery that were assumed as the gold standard. The probability (odds ratio (OR)) in regression analyses, sensitivity (SE), and specificity (SP) of predetermined SRM characteristics were calculated. Correct differentiation between malignant vs. benign SRMs was detected in 70.4% of cases, with more accurate identification of malignant (73%) in comparison to benign (65.7%) lesions. The radiological conclusions of SRM type matched histopathological findings in 56.1%. Central scarring (OR 10.6, p = 0.001), diameter of lesion (OR 2.4, p = 0.003), and homogeneous accumulation of contrast medium (OR 3.4, p = 0.03) significantly influenced the accuracy of malignant diagnosis. SE and SP of these parameters varied from 20.6% to 91.3% and 22.9% to 74.3%, respectively. In conclusion, MDCT is able to correctly differentiate malignant versus uncharacteristic benign SRMs in more than 2/3 of cases. However, frequency of the correct histopathological SRM type MDCT identification remains low.
Clinical Implication of Preoperative C-Reactive Protein/Albumin Ratio in Malignant Transformation of Intraductal Papillary Mucinous Neoplasm: A Propensity Score Analysis
Authors: Maruyama Hirotsugu , Tanoue Kojiro , Ishikawa-Kakiya Yuki , Yamamura Masafumi , Higashimori Akira , Ominami Masaki , Nadatani Yuji , Fukunaga Shusei , Otani Koji , Hosomi Shuhei , Tanaka Fumio , Kamata Noriko , Nagami Yasuaki , Taira Koichi , Ohira Go , Kimura Kenjiro , Amano Ryosuke , Fujiwara Yasuhiro
Published: February 2022

Background: Inflammation-based scoring has been reported to be useful for predicting the recurrence and prognosis of various carcinomas. This study retrospectively investigated the relationship between inflammation-based score and intraductal papillary mucinous neoplasms (IPMNs). Methods: Between January 2013 and October 2018, we enrolled 417 consecutive patients with pancreatic tumors who received surgical resections at our hospital. The main outcome was the association between the preoperative inflammation-based score and their accuracy in predicting malignant transformation of IPMN. Results: Seventy six patients were eligible. Pathological findings indicated that 35 patients had low-grade dysplasia, 18 had high-grade dysplasia, and 23 had invasive carcinomas. As the C-reactive protein albumin ratio (CAR) was higher, malignant transformation of IPMNs also increased (p = 0.007). In comparing CARhigh and CARlow using cutoff value, the results using a propensity score analysis showed that the CARhigh group predicted malignant transformation of IPMNs (odds ratio, 4.18; 95% confidence interval, 1.37–12.8; p = 0.01). In the CARhigh group, disease-free survival (DFS) was significantly shorter (p = 0.04). In the worrisome features, the AUC for the accuracy of malignant transformation with CARhigh was 0.84 when combining with the MPD findings. Conclusions: Preoperative CAR could be a predictive marker of malignant transformation of IPMNs.
Breast Cancer Mammograms Classification Using Deep Neural Network and Entropy-Controlled Whale Optimization Algorithm
Authors: Zahoor Saliha , Shoaib Umar , Lali Ikram Ullah
Published: February 2022

Breast cancer has affected many women worldwide. To perform detection and classification of breast cancer many computer-aided diagnosis (CAD) systems have been established because the inspection of the mammogram images by the radiologist is a difficult and time taken task. To early diagnose the disease and provide better treatment lot of CAD systems were established. There is still a need to improve existing CAD systems by incorporating new methods and technologies in order to provide more precise results. This paper aims to investigate ways to prevent the disease as well as to provide new methods of classification in order to reduce the risk of breast cancer in women’s lives. The best feature optimization is performed to classify the results accurately. The CAD system’s accuracy improved by reducing the false-positive rates.The Modified Entropy Whale Optimization Algorithm (MEWOA) is proposed based on fusion for deep feature extraction and perform the classification. In the proposed method, the fine-tuned MobilenetV2 and Nasnet Mobile are applied for simulation. The features are extracted, and optimization is performed. The optimized features are fused and optimized by using MEWOA. Finally, by using the optimized deep features, the machine learning classifiers are applied to classify the breast cancer images. To extract the features and perform the classification, three publicly available datasets are used: INbreast, MIAS, and CBIS-DDSM. The maximum accuracy achieved in INbreast dataset is 99.7%, MIAS dataset has 99.8% and CBIS-DDSM has 93.8%. Finally, a comparison with other existing methods is performed, demonstrating that the proposed algorithm outperforms the other approaches.
Linear and Nonlinear Effects in Connectedness Structure: Comparison between European Stock Markets
Authors: Karkowska Renata , Urjasz Szczepan
Published: February 2022

The purpose of this research is to compare the risk transfer structure in Central and Eastern European and Western European stock markets during the 2007–2009 financial crisis and the COVID-19 pandemic. Similar to the global financial crisis (GFC), the spread of coronavirus (COVID-19) created a significant level of risk, causing investors to suffer losses in a very short period of time. We use a variety of methods, including nonstandard like mutual information and transfer entropy. The results that we obtained indicate that there are significant nonlinear correlations in the capital markets that can be practically applied for investment portfolio optimization. From an investor perspective, our findings suggest that in the wake of global crisis and pandemic outbreak, the benefits of diversification will be limited by the transfer of funds between developed and developing country markets. Our study provides an insight into the risk transfer theory in developed and emerging markets as well as a cutting-edge methodology designed for analyzing the connectedness of markets. We contribute to the studies which have examined the different stock markets’ response to different turbulences. The study confirms that specific market effects can still play a significant role because of the interconnection of different sectors of the global economy.
Correlations, Information Backflow, and Objectivity in a Class of Pure Dephasing Models
Authors: Megier Nina , Smirne Andrea , Campbell Steve , Vacchini Bassano
Published: February 2022

We critically examine the role that correlations established between a system and fragments of its environment play in characterising the ensuing dynamics. We employ a dephasing model with different initial conditions, where the state of the initial environment represents a tunable degree of freedom that qualitatively and quantitatively affects the correlation profiles, but nevertheless results in the same reduced dynamics for the system. We apply recently developed tools for the characterisation of non-Markovianity to carefully assess the role that correlations, as quantified by the (quantum) Jensen–Shannon divergence and relative entropy, as well as changes in the environmental state, play in whether the conditions for classical objectivity within the quantum Darwinism paradigm are met. We demonstrate that for precisely the same non-Markovian reduced dynamics of the system arising from different microscopic models, some exhibit quantum Darwinistic features, while others show that no meaningful notion of classical objectivity is present. Furthermore, our results highlight that the non-Markovian nature of an environment does not a priori prevent a system from redundantly proliferating relevant information, but rather it is the system’s ability to establish the requisite correlations that is the crucial factor in the manifestation of classical objectivity.
Optimal UAV Formation Tracking Control with Dynamic Leading Velocity and Network-Induced Delays
Authors: Wang Zhuwei , Xu Mengjiao , Liu Lihan , Fang Chao , Sun Yang , Chen Huamin
Published: February 2022

With the rapid development of UAV technology, the research of optimal UAV formation tracking has been extensively studied. However, the high maneuverability and dynamic network topology of UAVs make formation tracking control much more difficult. In this paper, considering the highly dynamic features of uncertain time-varying leader velocity and network-induced delays, the optimal formation control algorithms for both near-equilibrium and general dynamic control cases are developed. First, the discrete-time error dynamics of UAV leader–follower models are analyzed. Next, a linear quadratic optimization problem is formulated with the objective of minimizing the errors between the desired and actual states consisting of velocity and position information of the follower. The optimal formation tracking problem of near-equilibrium cases is addressed by using a backward recursion method, and then the results are further extended to the general dynamic case where the leader moves at an uncertain time-varying velocity. Additionally, angle deviations are investigated, and it is proved that the similar state dynamics to the general case can be derived and the principle of control strategy design can be maintained. By using actual real-world data, numerical experiments verify the effectiveness of the proposed optimal UAV formation-tracking algorithm in both near-equilibrium and dynamic control cases in the presence of network-induced delays.
Identification in Parametric Models: The Minimum Hellinger Distance Criterion
Authors: Pacini David
Published: February 2022

This note studies the criterion for identifiability in parametric models based on the minimization of the Hellinger distance and exhibits its relationship to the identifiability criterion based on the Fisher matrix. It shows that the Hellinger distance criterion serves to establish identifiability of parameters of interest, or lack of it, in situations where the criterion based on the Fisher matrix does not apply, like in models where the support of the observed variables depends on the parameter of interest or in models with irregular points of the Fisher matrix. Several examples illustrating this result are provided.
Students’ Performance in Physical Education: The Role of Differential Achievement Goals and Self-Regulated Learning
Authors: Jørgensen Olsen Thomas Mangor , Mehus Ingar
Published: February 2022

The purpose of this study was to examine the relationship between differential achievement goals and self-regulated learning, as well as motivational mechanisms’ consequences for performance in physical education. This was done by using the 2 × 2 achievement goals framework, and the cyclical model for self-regulated learning. The participants (N = 571, 51.7% girls) were physical education students in grades 11–13 from two upper secondary schools in Norway. A cross-sectional questionnaire was conducted, and data were analysed with a multiple-regression-based structural equation model. The modified structural model yielded an adequate fit (X2 = [df = 124] 429.79, p < 0.01; RMSEA = 0.07; CFI = 0.93), and results revealed that achievement goals have consequences for students’ self-regulation in physical education. More specifically, mastery goals have a positive association with self-regulation, whereas performance avoidance is found to have a negative association. Further, the results support claims that self-regulated learning plays a role in students’ performance. Finally, the model showed that self-regulation mediates the relationship between mastery approach goals and performance avoidance goals in relation to performance.
The Bridging Role of Goals between Affective Traits and Positive Creativity
Authors: Wang Hung-Hsiang , Deng Xiaotian
Published: February 2022

Positive creativity training is crucial for 21st century learning, yet the influence of affective traits and goals with different intentions on positive creativity is unclear. We held a creativity training workshop for fifty-four undergraduates to determine its influence. We first assessed participants’ affective traits (risk-taking, curiosity, imagination, and complexity) using the Test of Divergent Feeling from the Creativity Assessment Packet. Then, we provided participants with twenty-seven products as inspiration sources for designing novel staplers. Each participant was asked to define a certain design goal, for which they chose one of the inspiration sources to generate ideas. We assessed the novelty of ideas and classified them according to the goals with different intentions. Results showed a bridging role of the goals between affective traits and creativity. This role was reflected in positive correlations between (1) curiosity and novelty with effort-saving goals; (2) complexity and novelty with orderliness goals. In addition, we found participants with high risk-taking tended to set versatility goals; the orderliness goal led to the highest novelty of ideas. Our findings suggested that teachers should pay attention to students’ affective traits and guide them to set goals in positive creativity education.
Promoting Equity and Assuring Teaching and Learning Quality: Magisterial Lectures in a Philippine University during the COVID-19 Pandemic
Authors: Rodrigo Maria Mercedes T. , Ladrido Estelle Marie Macuja
Published: February 2022

When the COVID-19 pandemic forced universities to shift to online learning, one of the challenges to faculty and administrators was to provide students with high-quality, curriculum-based learning materials that could be accessed despite students’ variable levels of Internet access. Part of the Ateneo de Manila University’s response to this challenge is the production of the Magisterial Lectures, an Open Educational Resource (OER) series of video lectures by some of the University’s most respected faculty members. The goals of this paper are to describe how the production of the lectures was guided by the principles of quality and equity; to discuss the use and reach of the lectures based on YouTube analytics and a survey of Ateneo students and teachers; and to measure the impact of the lectures on students’ learning experience. We enact quality in terms of curricular alignment and high production value. Equity was achieved by making the resource available publicly, free of charge. We found that the videos reached over 350,000 viewers in 37 countries. A survey of Ateneo students and teachers, the primary beneficiaries, shows that these materials were effective educational tools. Their effectiveness is attributable to the grounding of the production in quality and equity; the teachers’ careful integration of the recordings in their lessons; and the students’ engagement with the lectures following their own learning preferences and strategies.
Cost Model Based Incremental Processing in Dynamic Graphs
Authors: Bok Kyoungsoo , Cho Jungkwon , Lee Hyeonbyeong , Choi Dojin , Lim Jongtae , Yoo Jaesoo
Published: February 2022

Incremental graph processing has been developed to reduce unnecessary redundant calculations in dynamic graphs. In this paper, we propose an incremental dynamic graph-processing scheme using a cost model to selectively perform incremental processing or static processing. The cost model calculates the predicted values of the detection cost and processing cost of the recalculation region based on the past processing history. If there is a benefit of the cost model, incremental query processing is performed. Otherwise, static query processing is performed because the detection cost and processing cost increase due to the graph change. The proposed incremental scheme reduces the amount of computation by processing only the changed region through incremental processing. Further, it reduces the detection and disk I/O costs of the vertex, which are calculated by reusing the subgraphs from the previous results. The processing structure of the proposed scheme stores the data read from the cache and the adjacent vertices and then performs only memory mapping when processing these graph. It is demonstrated through various performance evaluations that the proposed scheme outperforms the existing schemes.
Advanced Control and Estimation Concepts and New Hardware Topologies for Future Mobility
Authors: Assadian Francis F.
Published: February 2022

Current transportation and, in general, mobility have a negative impact on our environment [...]
The Case for Policy in Developing Offshore Wind: Lessons from Norway
Authors: Dahl Iben Ringvej , Tveiten Bård Wathne , Cowan Emily
Published: February 2022

Offshore wind (OSW) has the potential to cut greenhouse gas (GHG) emissions and halt damaging climate change. However, policies to foster an OSW industry in Norway have long been small and scarce. Recent events suggest that this is changing, as the state-owned enterprise Enova decided to grant a record NOK 2.3 bn to build the world’s largest floating offshore wind farm in 2019, the Hywind Tampen project. Based on previous work by the corresponding author, we summarize the political development of OSW in Norway to distil generalisable lessons. The corresponding author employed interviews, document analysis and process tracing, using a theory of policy change to characterise the observed political change. She found that the main obstacle for early OSW deployment has been that environmental and visibility concerns have exacerbated energy–political ones that are created by a longstanding lack of local energy demands. As the green energy demand on a global scale is soaring, the lack of OSW deployment for exports implies that climate–political objectives have been subordinated to energy–political ones, in the formulation of Norwegian OSW policies. This hierarchy of goals was not deemed to have changed, despite the recent political developments in the policy area of Norwegian OSW. Hence, the Norwegian case demonstrates the role of context and national sectoral policies in deciding the pace of sustainable energy transitions. It is suggested that future research considers how policy best practices for renewable energy deployment could be adjusted across varying national contexts to overcome political hurdles to the sustainable transition.
Analysis of Controlled Driving and Spreading Behavior of Molten Pool in Cold Metal Transfer
Authors: Zhang An , Xing Yanfeng , Zhang Xiaobing , Yang Fuyong , Cao Juyong
Published: February 2022

The controlled short-circuit transfer is used to control the heat input of the molten pool and the base metal in the cold metal transfer welding process, including droplet formation, droplet transfer and molten pool flow. Based on the influence of arc pressure on the surface of the molten pool, droplet impact and residual energy on the flow behavior of the molten pool, this research proposes the arc pressure driving model, the droplet impact driving model and the residual energy transfer model on the molten pool surface respectively, and on this basis, a theoretical model of controlled driving and spreading of the cold metal transition bath is proposed. The theoretical relationship between the surface shape of the keyhole and the driving force, and the relationship between the surface shape of the molten pool and the welding current are established. The model accurately predicts the formation width and contact angle of the molten pool in a specific interval, which can better control the welding process and geometry.
Numerical Analysis on the Hydraulic Thrust and Dynamic Response Characteristics of a Turbine Pump
Authors: Kong Linghua , Cao Jingwei , Li Xiangyang , Zhou Xulei , Hu Haihong , Wang Tao , Gui Shuxin , Lai Wenfa , Zhu Zhongfeng , Wang Zhengwei , Liu Yan
Published: February 2022

Pumps as turbines are widely used in the world, wherein the hydraulic thrust of a turbine pump is one of the key factors affecting the safe and stable operation of a unit. There are a lot of difficulties to evaluate the hydraulic thrust by site observation and experiment. These difficulties can be resolved if a numerical simulation is applied. The present work aims to analyze the axial and radial hydraulic thrust of a prototype turbine pump in turbine mode, and then to determine the dynamic response characteristics of the turbine pump shafting. The axial hydraulic thrust in the turbine mode is upward, with a fluctuation range of 155 t to 175 t. The pressure fluctuation in the runner can be 16% of the unit head. The simulation results provide a good reference for understanding the hydraulic performance of the turbine pump and useful guidance for the operation of the unit. The structure analysis shows that the runner has asymmetrical deformation in the axial and radial directions. The amplitude of the dynamic stress on the shafting is about 10 MPa, and the dominant frequency of the dynamic stress on the runner is 20fn. The results could provide guidance for the operating and optimization of the unit, which helps the safe and stable operation of the station.
Experimental Study on Bearing Characteristics of Multi-Strata Anchorage System
Authors: An Yanpei , Zhang Nong , Zhao Yiming , Wang Weiwei , Guo Feng
Published: February 2022

One of the important factors affecting the anchoring force of the end encapsulated bolt is the mechanical properties of the rock formation at the anchoring end. For the fully encapsulated bolt, its bearing performance is closely related to the mechanical properties of the bolt passing through the rock stratum and its permutation mode. In this study, a series of laboratory pull-out tests of multi-strata anchorage systems was carried out based on an actual engineering background. The bearing performances and failure mechanisms of the multi-strata anchorage system under different anchoring methods and combinations of rock stratum were studied. The evolution law of the axial force and shear stress of the Agent-Rock interface was also analyzed. The test results showed that, for end encapsulation, changes in the mechanical properties of the rock strata at the anchoring end caused differences in bearing capacity, while full-length encapsulation markedly reduced the disparities. The position of the stratum with the highest general interface shear strength affected the mechanical response of the anchoring interface. The progressive failure process of multi-strata anchorage systems was discussed, and suggestions for rock bolt support in coal mine roadways were also proposed.
A Novel Feature Identification Method of Pipeline In-Line Inspected Bending Strain Based on Optimized Deep Belief Network Model
Authors: Liu Shucong , Wang Hongjun , Li Rui , Ji Beilei
Published: February 2022

Both long-distance oil and gas pipelines often pass through areas with unstable geological conditions or natural disasters. As a result, they are prone to bending, displacement, and deformation due to the action of an external environmental loading, which poses a threat to the safe operation of pipelines. The in-line inspection method that is based on the implementation of high-precision inertial measurement units (IMU) has become the main means of pipeline bending stress-strain detection technique. However, to address the problems of the inconsistent identification, low identification efficiency, and high misjudgment rate during the application of the traditional manual identification methods, a feature identification approach for the in-line inspected pipeline bending strain based on the employment of an optimized deep belief network (DBN) model is proposed in this work. In addition, our model can automatically learn features from the pipeline bending strain signals and complete classification and identification. On top of that, after the network model was trained and tested by using the actual pipeline bending strain inspection data, the extracted results showed that the model after the implementation of the training process could accurately identify and classify various pipeline features, with an identification accuracy and efficiency of 97.8% and 0.02 min/km, respectively. The high efficiency, elevated accuracy, and strong robustness of our method can effectively improve the in-line inspection procedure of pipelines during the enforcement of a bending strain load.
Accurate Theoretical Models for Frequency Diverse Array Based Wireless Power Transmission
Authors: Ahmad Zeeshan , Wang Zhonghan , Jaffri Zain ul Abidin , Bao Shudi
Published: February 2022

Wireless power transfer (WPT) is a well-known problem, and has received wide attention in the next generation industrial applications and consumer electronics. On the other hand, frequency diverse array (FDA) is a new concept with the ability to generate a range-angle dependent beampattern. Therefore, some researchers are engaged in designing WPT systems based on the FDA framework (FDA-WPT) instead of phased arrays. Unlike phased arrays, the FDA beampattern is time-variant. Therefore, existing beam collection efficiency models based on the phased array are not suitable for the FDA-WPT system. More importantly, the time-variant property of FDAs is usually ignored in the literature, and the system configuration of the target area where the power-harvesting end is located does not conform to the actual WPT scenario. In this paper, we derive and present accurate models of the FDA-WPT system. The power transfer performance of the corrected FDA-WPT system is then compared with the phased array based WPT system. Simulation results demonstrate that time-variant consideration in the FDA-WPT model causes difficulty in controlling the main beam direction to focus the power. The accurate FDA-WPT is theoretically investigated, and numerical simulations are implemented to validate the theoretical analysis.
A Method for Stakeholder Mapping in Connection with the Implementation of a Development Project
Authors: Styk Katarzyna , Bogacz Paweł
Published: February 2022

In the case of the energy sector (including mining companies) and the implementation of their development projects, it is necessary to obtain a social license to operate for a given project, which is associated with the involvement of various groups of stakeholders in the project and should be consistent with the company’s strategy. The basis for obtaining permission to operate is to conduct a stakeholder mapping process. Such an analysis will aid effective dialogue with all stakeholders and guide appropriate relationship building. The aim of this paper is to present the authors’ method of stakeholder mapping, which is an independent methodical idea that can be implemented in any enterprise. This paper comprehensively presents this algorithm, starting with the identification of stakeholder groups, through the determination of their level of interest and influence, ending with the construction of a matrix indicating the necessity of undertaking specific communication activities. Finally, the implementation of the created method in the form of a real business project is presented, the advantages are pointed out, and the possibilities and determinants of further development of this algorithm are presented. This method is proposed to companies from the energy sector, including those mining energy resources, as companies that have a significant impact on their social and environmental environment.
Assessment of Suitable Areas for Smart Grid of Power Generated from Renewable Energy Resources in Western Uganda
Authors: Atwongyeire Jane Rose , Palamanit Arkom , Bennui Adul , Shakeri Mohammad , Techato Kuaanan , Ali Shahid
Published: February 2022

This study assessed suitable smart grid areas for power generation and distribution from solar and small hydro energy resources in Western Uganda by employing the fuzzy analytic hierarchy process (AHP) based on geographic information system (GIS) data. This was performed based on the selected economic, environmental, and technical criteria by the authors guided by the experts’ judgements in the weighing process. The main criteria also included various sub-criteria. The sub-criteria of the economic criterion included distance from transmission lines, topography, and distance to roads. The environmental sub-criteria covered land use, sensitive areas, and protected areas. The technical sub-criteria were on distance from demand centers, available potential energy resources (solar and hydro), and climate (rainfall and sunshine). The weights of the main criteria and the sub-criteria were calculated by using the fuzzy AHP. These weights were then used in the GIS environment to determine both the potential for power generation from the solar energy resource and the smart grid suitable areas. According to the weight results, the economic criteria has the highest weight, followed by environmental and technical criteria. The validation of the experts’ judgements for each criterion by comparing the results from fuzzy AHP with AHP confirmed insignificant differences in weights for all criteria. The obtained suitable smart grid areas in Western Uganda have been classified into three parts, that is, the South, North, and Central. Therefore, this is a one-of-a-kind study that, in the authors’ view, will provide the initial insights to the government, policymakers, renewable energy practitioners, and researchers to investigate, map, and embrace decarbonization strategies for the electricity sector of Uganda.
New Model High Temperature Pasting Analysis of Fermented Cassava Granules
Authors: Nwaiwu Ogueri , Onyeaka Helen
Published: February 2022

Cassava is a starchy food item eaten by millions worldwide in various forms. The product has been subjected to various analysis forms, including the viscosity capacity of different flours made from the product. In this study, cassava granules (Garri) were subjected to scanning electron microscopy (SEM) and laser diffraction particle size analysis to determine microstructure, after which the viscosity behavior was ascertained under high pressure with the new model high-temperature rapid viscosity analyzer (RVA HT 4800), which is capable of reaching a maximum of 140 °C. Viscosity comparisons were then made with the profiles obtained at 95 °C and 140 °C. The microstructure had intact starch cells and was free of extraneous materials or fungal hyphae. The granule size range was found to be 1–1800 µM. It was established that the holding, final, and setback viscosities were most affected and decreased by at least 80% when the samples were subjected to the 140 °C HT profile. The peak time at 95 °C in yellow and white Garri samples of both brands averaged nine minutes, whereas it was 5 min at 140 °C profile. The white Garri samples tolerated the high temperature better based on breakdown viscosity values and may be used for making food products that require tolerance to high temperatures. An opportunity exists to re-evaluate different Garri varieties with the new model RVA to establish behavior at very high temperatures.
CNN for User Activity Detection Using Encrypted In-App Mobile Data
Authors: Pathmaperuma Madushi H. , Rahulamathavan Yogachandran , Dogan Safak , Kondoz Ahmet
Published: February 2022

In this study, a simple yet effective framework is proposed to characterize fine-grained in-app user activities performed on mobile applications using a convolutional neural network (CNN). The proposed framework uses a time window-based approach to split the activity’s encrypted traffic flow into segments, so that in-app activities can be identified just by observing only a part of the activity-related encrypted traffic. In this study, matrices were constructed for each encrypted traffic flow segment. These matrices acted as input into the CNN model, allowing it to learn to differentiate previously trained (known) and previously untrained (unknown) in-app activities as well as the known in-app activity type. The proposed method extracts and selects salient features for encrypted traffic classification. This is the first-known approach proposing to filter unknown traffic with an average accuracy of 88%. Once the unknown traffic is filtered, the classification accuracy of our model would be 92%.
Effect of Dietary Palm Kernel Oil on the Quality, Fatty Acid Profile, and Sensorial Attributes of Young Bull Meat
Authors: dos Santos Neiri J. A. , Bezerra Leilson R. , Castro Daniela P. V. , Marcelino Polyana D. R. , Virgínio Júnior Gercino F. , da Silva Júnior Jarbas M. , Pereira Elzânia S. , de Andrade Ederson A. , Silva Thadeu M. , Barbosa Analívia M. , Oliveira Ronaldo L.
Published: February 2022

Lipid supplementation through vegetable oils in diets for ruminants can be a nutritional strategy to increase energy density, manipulate ruminal fermentation and change the physicochemical composition and sensorial properties of meat. This study evaluated the optimal dietary inclusion of palm kernel oil (PKO) for Nellore bulls on meat quality. The diets consisted of 0.0, 11.5, 23.0, and 34.6 g/kg dry matter (DM) PKO levels. PKO inclusion did not influence the centesimal composition, pH, color indices, water holding capacity, cooking loss, or shear force of the beef. There were linear increases in the concentrations of lauric acid (C12:0) and myristic acid (C14:0) in the bull’s meat. However, palmitic acid (C16:0), oleic acid (C18:0), vaccenic acid (t-11–C18:1) and conjugated linoleic acid (CLA), ∑n − 6, ∑n − 3, ∑n − 6/∑n 3, the hypocholesterolemic: hypercholesterolemic ratio of the fatty acid content, and the thrombogenicity index were not affected. There were linear reductions in the oleic acid meat concentration (c-9–C18:1) and elongated enzymatic activity when PKO was added to the bull diet. The atherogenicity index increased linearly due to PKO inclusion in the bull diet. No effect of the inclusion of PKO on meat flavor, perception of tenderness, juiciness, or global acceptance from the sensorial evaluation was recorded. The inclusion of PKO up to 34.6 g/kg DM can be recommended to supplement young bulls with no effects on meat composition and quality characteristics.