bluuebunny/crossref_metadata_2025 huggingface dataset:
Cellular Prion Protein Is Closely Associated with Early Recurrence and Poor Survival in Patients with Hepatocellular Carcinoma
Authors: Kim Mo-Jong , Cho Yoon-Ah , Kim Eunhye , Choe Ji-Young , Park Ji-Won , Lee Junyong , Lee Jung-Woo , Moon Sung-Hoon , Kim Yong-Sun , Kim Sung-Eun , Choi Eun-Kyoung
Published: July 2022

The cellular prion protein (PrPC) is known to play a role in cancer proliferation and metastasis. However, the role of PrPC expression in hepatocellular carcinoma (HCC) is unknown. This study investigated whether overexpression of PrPC affects recurrence after surgical resection and survival in HCC. A total of 110 HCC patients who underwent hepatic resection were included. They were followed up for a median of 42 months (range 1–213 months) after hepatectomy. The relationships between PrPC expression and the HCC histologic features, recurrence of HCC following surgical resection, and survival of the patients were examined. Seventy-one cases (64.5%) of HCC demonstrated higher expression of PrPC. The expression of PrPC was only correlated with diabetes mellitus. There was no association between PrPC expression and age, sex, hypertension, hepatitis B virus positivity, alcohol consumption, Child–Pugh class, major portal vein invasion, serum alpha-fetoprotein, and HCC size or number. The 1-year recurrence rates in patients with higher PrPC expression were higher than those with lower PrPC expression. The cumulative survival rates of patients with higher PrPC expression were significantly shorter than those of patients with lower PrPC expression. In conclusion, PrPC expression is closely associated with early recurrence and poor survival of HCC patients following surgical resection.
Nodular and Micronodular Basal Cell Carcinoma Subtypes Are Different Tumors Based on Their Morphological Architecture and Their Interaction with the Surrounding Stroma
Authors: Șerbănescu Mircea-Sebastian , Bungărdean Raluca Maria , Georgiu Carmen , Crișan Maria
Published: July 2022

Basal cell carcinoma (BCC) is the most frequent cancer of the skin and comprises low-risk and high-risk subtypes. We selected a low-risk subtype, namely, nodular (N), and a high-risk subtype, namely, micronodular (MN), with the aim to identify differences between them using a classical morphometric approach through a gray-level co-occurrence matrix and histogram analysis, as well as an approach based on deep learning semantic segmentation. From whole-slide images, pathologists selected 216 N and 201 MN BCC images. The two groups were then manually segmented and compared based on four morphological areas: center of the BCC islands (tumor, T), peripheral palisading of the BCC islands (touching tumor, TT), peritumoral cleft (PC) and surrounding stroma (S). We found that the TT pattern varied the least, while the PC pattern varied the most between the two subtypes. The combination of two distinct analysis approaches yielded fresh insights into the characterization of BCC, and thus, we were able to describe two different morphological patterns for the T component of the two subtypes.
The Mesenchymal Niche in Myelodysplastic Syndromes
Authors: Friedrich Chloé , Kosmider Olivier
Published: July 2022

Myelodysplastic syndromes (MDSs) are clonal disorders characterized by ineffective hematopoiesis, resulting in cytopenias and a risk of developing acute myeloid leukemia. In addition to mutations affecting hematopoietic stem cells (HSCs), numerous studies have highlighted the role of the bone marrow microenvironment (BMME) in the development of MDSs. The mesenchymal niche represents a key component of the BMME. In this review, we discuss the role of the mesenchymal niche in the pathophysiology of MDS and provide an overview of currently available in vitro and in vivo models that can be used to study the effects of the mesenchymal niche on HSCs.
Information Geometry in Roegenian Economics
Authors: Udriste Constantin , Tevy Ionel
Published: July 2022

We characterise the geometry of the statistical Roegenian manifold that arises from the equilibrium distribution of an income of noninteracting identical economic actors. The main results for ideal income are included in three subsections: partition function in distribution, scalar curvature, and geodesics. Although this system displays no phase transition, its analysis provides an enlightening contrast with the results of Van der Waals Income in Roegenian Economics, where we shall examine the geometry of the economic Van der Waals income, which does exhibit a “monetary policy as liquidity—income” transition. Here we focus on three subsections: canonical partition function, economic limit, and information geometry of the economic Van der Waals manifold.
Nursing Students’ Perceived Learning Outcomes, Motivation to Learn and Grade Achieved in a Digital Blended Learning Course: A Norwegian Cross-Sectional Study
Authors: Tørris Christine , Meyer Mona Elisabeth , Sandbekken Ida Hellum , Halvorsrud Hedvig , Molin Marianne
Published: July 2022

The COVID-19 pandemic forced educational institutions to move online, and it is important to understand how students perceive learning in a digital learning environment. We aimed to investigate students’ perceived learning outcomes in a digital learning environment and associations between perceived learning outcomes and grades achieved. An anonymous electronic survey was used (n = 230, response rate 34%). A significant linear relationship between overall perceived learning outcome and grade achieved was found (B 0.644, 95% CI 0.52 to 0.77). Of the different learning activities, attending digital seminars were positively associated with grades (B 0.163, 95% CI 0.002 to 0.32). In particular, participating in voluntary colloquium group (B 0.144, 95% CI 0.03 to 0.26) and motivation to learn (B 0.265, 95% CI 0.13 to 0.41) predicted the students’ grades. Intrinsic motivation was positively associated with grades (B 0.285, 95% CI 0.12 to 0.45), and extrinsic motivation was negatively associated with grades (B-0.213, 95% CI-0.35 to -0.07). Nursing students’ perceived learning outcomes and grades were positively associated. Of the different learning activities, attending digital seminars predicted higher grades. Additionally, attending colloquium groups and being motivated to learn predicted higher grades, while high extrinsic motivation was associated with lower grades.
In-Situ Efficiency Estimation of Induction Motors Based on Quantum Particle Swarm Optimization-Trust Region Algorithm (QPSO-TRA)
Authors: Diarra Mahamadou Negue , Yao Yifan , Li Zhaoxuan , Niasse Mouhamed , Li Yonggang , Zhao Haisen
Published: July 2022

The accuracy estimation of induction motors’ efficiency is beneficial and crucial in the industry for energy savings. The requirement for in situ machine efficiency estimation techniques is increasing in importance because it is the precondition to making the energy-saving scheme. Currently, the torque and speed identification method is widely applied in online efficiency estimation for motor systems. However, the higher precision parameters, such as stator resistance Rs and equivalent resistance of iron losses Rfe, which are the key to the efficiency estimation process with the air gap torque method, are of cardinal importance in the estimation process. Moreover, the computation burden is also a severe problem for the real-time data process. To solve these problems, as for the torque and speed-identification-based efficiency estimation method, this paper presents a lower time burden method based on Quantum Particle Swarm Optimization-Trust Region Algorithm (QPSO-TRA). The contribution of the proposed method is to transform the disadvantages of former algorithms to develop a reliable hybrid algorithm to identify the crucial parameters, namely, Rs and Rfe. Sensorless speed identification based on the rotor slot harmonic frequency (RSHF) method is adopted for speed determination. This hybrid algorithm reduces the computation burden by about 1/3 compared to the classical genetic algorithm (GA). The proposed method was validated by testing a 5.5 kW motor in the laboratory and a 10 MW induction motor in the field.
Accelerating Efficient Installation and Optimization of Battery Energy Storage System Operations Onboard Vessels
Authors: He Wei , Mo Olve , Remøy Alfred , Valøen Lars O. , Såtendal Helge , Howie Aaron , Vie Preben J. S.
Published: July 2022

Emerging large battery energy storage systems (BESSs) are key enablers in the electrification of the shipping sector. With huge government investments in BESSs, there are large gaps between the government supported BESS initiatives and actual BESS integration results on vessels. This study aims to close these gaps, allowing BESSs to become the preferred solution for ship owners without needing government support. Firstly, this industry-driven study reviews both the industrial approaches to achieve CO2 emission reductions and the fuel savings and emission reductions from 500 BESS installations on various vessels. Secondly, a 630 kWh BESS retrofitted onto a hybrid-electric vessel is used to quantitively identify the improvement requirements for installations and operations. The installations required many custom designs that were expensive and have high failure risks. The standardization of interfaces’ between BESSs and vessels is thus urgently required. The BESS was intended for spinning reserve capacity and peak shaving but in practice was under-used in terms of energy throughput (shallow cycles and low equivalent full cycles of 80 versus the design specification of 480 yearly). Thirdly, this study develops new, integrated BESS operational models by learning from large operational data, balancing BESS degradation against fuel saving and utilizing onshore/offshore green power supply/charging. The R&D of BESS is required to deal with the increasing safety requirements and further CO2 emission reductions. Finally, four BESS acceleration scenarios were established to facilitate the technical and operational transferability through utilizing digitalization.
Networked Microgrid Energy Management Based on Supervised and Unsupervised Learning Clustering
Authors: Salehi Navid , Martínez-García Herminio , Velasco-Quesada Guillermo
Published: July 2022

Networked microgrid (NMG) is a novel conceptual paradigm that can bring multiple advantages to the distributed system. Increasing renewable energy utilization, reliability and efficiency of system operation and flexibility of energy sharing amongst several microgrids (MGs) are some specific privileges of NMG. In this paper, residential MGs, commercial MGs, and industrial MGs are considered as a community of NMG. The loads’ profiles are split into multiple sections to evaluate the maximum load demand (MLD). Based on the optimal operation of each MG, the operating reserve (OR) of the MGs is calculated for each section. Then, the self-organizing map as a supervised and a k-means algorithm as an unsupervised learning clustering method is utilized to cluster the MGs and effective energy-sharing. The clustering is based on the maximum load demand of MGs and the operating reserve of dispatchable energy sources, and the goal is to provide a more efficient system with high reliability. Eventually, the performance of this energy management and its benefits to the whole system is surveyed effectively. The proposed energy management system offers a more reliable system due to the possibility of reserved energy for MGs in case of power outage variation or shortage of power.
Faulty Section Location Method Based on Dynamic Time Warping Distance in a Resonant Grounding System
Authors: He Yu , Zhang Xinhui , Wang Rui , Cheng Mengzhu , Gao Zhen , Zhang Zheng , Yu Wenxin
Published: July 2022

When a single-phase grounding fault occurs in a resonant grounding system, the determination of the fault location remains a significant challenge due to the small fault current and the instability of the grounding arc. In order to solve the problem of low protection sensitivity when a high-resistance grounding fault occurs in a resonant grounding system, this paper proposes a fault location method based on the combination of dynamic time warping (DTW) distance and fuzzy C-means (FCM) clustering. By analyzing the characteristics of the zero-sequence current upstream and downstream of the fault point when a single-phase grounding fault occurs in the resonant grounding system, it is concluded that the waveform similarity on both sides of the fault point is low. DTW distance can be used to measure the similarity of two time series, and has the characteristics of good fault tolerance and synchronization error tolerance. According to the rule that the DTW value of faulty section is much larger than that of nonfaulty sections, FCM clustering is used to classify the DTW value of each section. The membership degree matrix and cluster centers are obtained. In the membership degree matrix, the section corresponding to the data in a class of their own is the faulty section, and all other data correspond to the nonfaulty section; otherwise, it is a fault occurring at the end of the line. The simulation results of MATLAB/Simulink and the field data test show that the method can accurately locate the faulty section.
Structural Systems for Tall Buildings
Authors: Ali Mir M. , Al-Kodmany Kheir
Published: July 2022

Structural systems for tall buildings have gone through an evolutionary process. The rigid frame became popular in the first half of the 20th century but proved to be structurally inefficient beyond a certain height of tall buildings. The invention of the tubular structure in the 1960s allowed buildings to be built taller with low material consumption. Due to the obstructive nature of the closely spaced exterior columns of framed tubes and bracings of braced tubes, the core-outrigger system gained acceptance by the architects as it allowed them to freely articulate the façade design. However, the conventional tubular structures continued to retain their use for tall buildings to a lesser degree and later underwent a resurgence in modified forms. These and other advanced tubular forms in cutting-edge structural systems developed later continue to find application in modern times. This study presents a detailed narrative of different structural systems for tall buildings that is expected to assist structural engineers and architects to collaboratively select appropriate structural systems for tall buildings.
Allometric Equations for the Biomass Estimation of Calophyllum inophyllum L. in Java, Indonesia
Authors: Basuki Tyas Mutiara , Leksono Budi , Baral Himlal , Andini Sarah , Wahyuni Novi Sari , Artati Yustina , Choi Eunho , Shin Seongmin , Kim Raehyun , Yang A-Ram , Samsudin Yusuf B. , Windyarini Eritrina
Published: July 2022

Reliable data on CO2 quantification is increasingly important to quantify the climate benefits of forest landscape restoration and international commitments, such as the Warsaw REDD+ Framework and Nationally Determined Contributions under the Paris Agreement. Calophyllum inophyllum L. (nyamplung as a local name or tamanu tree for the commercial name) is an increasingly popular tree species in forest landscape restoration and bioenergy production for a variety of reasons. In this paper, we present allometric equations for aboveground biomass (AGB), belowground biomass (BGB), and total above- and belowground biomass (TABGB) predictions of C. inophyllum L. Data collection was carried out twice (2017 and 2021) from 40 trees in Java, Indonesia. Allometric equations using the natural logarithm of diameter at breast height (lnDBH) and ln height (lnH) for biomass prediction qualified the model’s fit with statistical significance at 95% of the confidence interval for AGB, BGB, and TABGB predictions. The results showed that the linear models using both lnDBH and lnH were well fit and accurate. However, the model with lnDBH is more precise than the model using lnH. Using lnDBH as a predictor, the R2 values were 0.923, 0.945, and 0.932, and MAPE were 24.7, 37.0, and 25.8 for AGB, BGB, and TABGB, respectively. Using lnH as a predictor, the R2 values were 0.887, 0.918, and 0.898 and MAPE were 37.4, 49.0, and 39.8 for AGB, BGB, and TABGB, respectively. Consequently, the driven allometric equations can help accurate biomass quantification for carbon-trading schemes of C. inophyllum L.
What Motivates Mixed Heritage People to Assert Their Ancestries?
Authors: Song Miri , Liebler Carolyn
Published: July 2022

Research on mixed heritage people has often focused on their reported race(s) and what these self-reports may reveal about their racial leanings. In the U.S., people are also asked: “What is this person’s ancestry or ethnic origin?” as a census fill-in-the-blank question. Existing research has analyzed the census data on race and ancestry and has uncovered meanings about ethnicity among White Americans, but little is known about the importance of ancestry in the case of mixed heritage people. In this paper, we draw on our interviews with 68 American-Indian-White, Black-White, and Asian-White mixed heritage people in the U.S. Given that many mixed heritage people’s connections with their disparate ancestries can be hindered by generational distance, lack of cultural contact and exposure, and social rejection, what motivates mixed heritage people to report their disparate ancestries, and how do their ancestry claims relate to their racial identities? How may the differential histories and racialization of groups in the U.S. shape mixed heritage people’s ability and inclination to assert either their White or minority ancestries? We found that mixed heritage individuals who were motivated to assert their ancestry claims did so for two main reasons: First, by claiming a specific ancestry (or ancestries), participants wished to assert a more individualistic sense of self than was typically allowed, given their racial treatment based upon their racial appearance; this could be especially meaningful if those individuals felt a mismatch between their racial assignment by others and their sense of self. Second, a claim to a specific ancestry was a way for individuals to forge connections with family, relatives, or an ancestry group that had not existed before. Overall, while most of our mixed heritage participants reported details of their European ancestries, it was their Black, American Indian, or Asian ancestries that were deemed to be most salient and/or meaningful to who they were.
Transcriptomic Profile of Genes Regulating the Structural Organization of Porcine Atrial Cardiomyocytes during Primary In Vitro Culture
Authors: Nawrocki Mariusz J. , Jopek Karol , Kaczmarek Mariusz , Zdun Maciej , Mozdziak Paul , Jemielity Marek , Perek Bartłomiej , Bukowska Dorota , Kempisty Bartosz
Published: July 2022

Numerous cardiovascular diseases (CVD) eventually lead to severe myocardial dysfunction, which is the most common cause of death worldwide. A better understanding of underlying molecular mechanisms of cardiovascular pathologies seems to be crucial to develop effective therapeutic options. Therefore, a worthwhile endeavor is a detailed molecular characterization of cells extracted from the myocardium. A transcriptomic profile of atrial cardiomyocytes during long-term primary cell culture revealed the expression patterns depending on the duration of the culture and the heart segment of origin (right atrial appendage and right atrium). Differentially expressed genes (DEGs) were classified as involved in ontological groups such as: “cellular component assembly”, “cellular component organization”, “cellular component biogenesis”, and “cytoskeleton organization”. Transcriptomic profiling allowed us to indicate the increased expression of COL5A2, COL8A1, and COL12A1, encoding different collagen subunits, pivotal in cardiac extracellular matrix (ECM) structure. Conversely, genes important for cellular architecture, such as ABLIM1, TMOD1, XIRP1, and PHACTR1, were downregulated during in vitro culture. The culture conditions may create a favorable environment for reconstruction of the ECM structures, whereas they may be suboptimal for expression of some pivotal transcripts responsible for the formation of intracellular structures.
A Comparative Study on the Influence of Undersampling and Oversampling Techniques for the Classification of Physical Activities Using an Imbalanced Accelerometer Dataset
Authors: Jeong Dong-Hwa , Kim Se-Eun , Choi Woo-Hyeok , Ahn Seong-Ho
Published: July 2022

Accelerometer data collected from wearable devices have recently been used to monitor physical activities (PAs) in daily life. While the intensity of PAs can be distinguished with a cut-off approach, it is important to discriminate different behaviors with similar accelerometry patterns to estimate energy expenditure. We aim to overcome the data imbalance problem that negatively affects machine learning-based PA classification by extracting well-defined features and applying undersampling and oversampling methods. We extracted various temporal, spectral, and nonlinear features from wrist-, hip-, and ankle-worn accelerometer data. Then, the influences of undersampilng and oversampling were compared using various ML and DL approaches. Among various ML and DL models, ensemble methods including random forest (RF) and adaptive boosting (AdaBoost) exhibited great performance in differentiating sedentary behavior (driving) and three walking types (walking on level ground, ascending stairs, and descending stairs) even in a cross-subject paradigm. The undersampling approach, which has a low computational cost, exhibited classification results unbiased to the majority class. In addition, we found that RF could automatically select relevant features for PA classification depending on the sensor location by examining the importance of each node in multiple decision trees (DTs). This study proposes that ensemble learning using well-defined feature sets combined with the undersampling approach is robust for imbalanced datasets in PA classification. This approach will be useful for PA classification in the free-living situation, where data imbalance problems between classes are common.
Classification of Depressive and Schizophrenic Episodes Using Night-Time Motor Activity Signal
Authors: Rodríguez-Ruiz Julieta G. , Galván-Tejada Carlos E. , Luna-García Huizilopoztli , Gamboa-Rosales Hamurabi , Celaya-Padilla José M. , Arceo-Olague José G. , Galván Tejada Jorge I.
Published: July 2022

Major depressive disorder (MDD) is the most recurrent mental illness globally, affecting approximately 5% of adults. Furthermore, according to the National Institute of Mental Health (NIMH) of the U.S., calculating an actual schizophrenia prevalence rate is challenging because of this illness’s underdiagnosis. Still, most current global metrics hover between 0.33% and 0.75%. Machine-learning scientists use data from diverse sources to analyze, classify, or predict to improve the psychiatric attention, diagnosis, and treatment of MDD, schizophrenia, and other psychiatric conditions. Motor activity data are gaining popularity in mental illness diagnosis assistance because they are a cost-effective and noninvasive method. In the knowledge discovery in databases (KDD) framework, a model to classify depressive and schizophrenic patients from healthy controls is constructed using accelerometer data. Taking advantage of the multiple sleep disorders caused by mental disorders, the main objective is to increase the model’s accuracy by employing only data from night-time activity. To compare the classification between the stages of the day and improve the accuracy of the classification, the total activity signal was cut into hourly time lapses and then grouped into subdatasets depending on the phases of the day: morning (06:00–11:59), afternoon (12:00–17:59), evening (18:00–23:59), and night (00:00–05:59). Random forest classifier (RFC) is the algorithm proposed for multiclass classification, and it uses accuracy, recall, precision, the Matthews correlation coefficient, and F1 score to measure its efficiency. The best model was night-featured data and RFC, with 98% accuracy for the classification of three classes. The effectiveness of this experiment leads to less monitoring time for patients, reducing stress and anxiety, producing more efficient models, using wearables, and increasing the amount of data.
Hydrogen Diffusion on, into and in Magnesium Probed by DFT: A Review
Authors: Shelyapina Marina G.
Published: July 2022

Hydrogen is an energy carrier that can be a sustainable solution for alternative energy with zero greenhouse gas emissions. Hydrogen storage is a key point for hydrogen energy. Metals provide an access for safe, controlled and reversible hydrogen storage and release. Magnesium, due to its outstanding hydrogen storage capacity, high natural abundance, low cost and non-toxicity is one of the most attractive materials for hydrogen storage. The economic efficiency of Mg as a hydrogen accumulator is limited by its sluggish hydrogen sorption kinetics and high stability of its hydride MgH2. Many attempts have been made to overcome these shortcomings. On a microscopic level, hydrogen absorption by metal is a complex multistep process that is impossible to survey experimentally. Theoretical studies help to elucidate this process and focus experimental efforts on the design of new effective Mg-based materials for hydrogen storage. This review reports on the results obtained within a density functional theory approach to studying hydrogen interactions with magnesium surfaces, diffusion on Mg surfaces, into and in bulk Mg, as well as hydrogen induced phase transformations in MgHx and hydrogen desorption from MgH2 surfaces.
Distance to Healthcare Facility and Lady Health Workers’ Visits Reduce Malnutrition in under Five Children: A Case Study of a Disadvantaged Rural District in Pakistan
Authors: Shahid Muhammad , Ameer Waqar , Malik Najma Iqbal , Alam Muhammad Babar , Ahmed Farooq , Qureshi Madeeha Gohar , Zhao Huiping , Yang Juan , Zia Sidra
Published: July 2022

This study accesses the impact of lady health worker (LHWs) visits in the community and distance to a healthcare facility on the nutritional status of under-five children. Additionally, it explores the perceptions and attitudes of the community about the performance of LHWs. A self-administered instrument was applied to gather data on different parameters, such as children’s height, age, weight, and socioeconomic status from 384 rural households in a marginalized district of Punjab province with the help of a purposive random sampling technique. The binary logistic regression model was employed for the computation of the probability of malnutrition. The prevalences of stunting, underweight children, and wasting in the district were 34.8%, 46.1%, and 15.5%, respectively. The logistic results illustrate that those households in which LHW visits occur regularly within 15 days (OR = 0.28 with 95% CI: 0.09–0.82) have a lower probability of malnutrition prevalence among their children. The distance to the health facility shows that the odds of malnutrition were higher from 3–4 Kilometers (Km) (OR = 2.61, 95% CI: 0.85–8.14), and odds were also higher for the ≥5 km category (OR = 2.88, 95% CI: 0.94–8.82). Children from richer families had lower chances of being malnourished (OR = 0.28, 95% CI: 0.07–1.14). Furthermore, the respondents show a positive attitude towards LHWs. They have given the first rank to their performance being beneficial to mothers and childcare, especially on checkups and safe deliveries, while they have shown negative responses and given lower ranks to their performance due to irregular visits (6th rank) and poor community awareness (7th rank). We conclude that LHWs’ regular visits to targeted households and less distance to healthcare facilities reduce the malnutrition risk in under-five children.
A Comprehensive Review on Forward Osmosis Water Treatment: Recent Advances and Prospects of Membranes and Draw Solutes
Authors: Xu Yang , Zhu Yingying , Chen Zhen , Zhu Jinyuan , Chen Geng
Published: July 2022

Forward osmosis (FO) is an evolving membrane separation technology for water treatment and reclamation. However, FO water treatment technology is limited by factors such as concentration polarization, membrane fouling, and reverse solute flux. Therefore, it is of a great importance to prepare an efficient high-density porous membrane and to select an appropriate draw solute to reduce concentration polarization, membrane fouling, and reverse solute flux. This review aims to present a thorough evaluation of the advancement of different draw solutes and membranes with their effects on FO performance. NaCl is still widely used in a large number of studies, and several general draw solutes, such as organic-based and inorganic-based, are selected based on their osmotic pressure and water solubility. The selection criteria for reusable solutes, such as heat-recovered gaseous draw, magnetic field-recovered MNPs, and electrically or thermally-responsive hydrogel are primarily based on their industrial efficiency and energy requirements. CA membranes are resistant to chlorine degradation and are hydrophilic, while TFC/TFN exhibit a high inhibition of bio-adhesion and hydrolysis. AQPs are emerging membranes, due to proteins with complete retention capacity. Moreover, the development of the hybrid system combining FO with other energy or water treatment technologies is crucial to the sustainability of FO.
Modelling and Analyzing the Semantic Evolution of Social Media User Behaviors during Disaster Events: A Case Study of COVID-19
Authors: Han Xuehua , Wang Juanle
Published: July 2022

Public behavior in cyberspace is extremely sensitive to emergency disaster events. Using appropriate methodologies to capture the semantic evolution of social media users’ behaviors and discover how it varies across geographic space and time still presents a significant challenge. This study proposes a novel framework based on complex network, topic model, and GIS to describe the topic change of social media users’ behaviors during disaster events. The framework employs topic modeling to extract topics from social media texts, builds a user semantic evolution model based on a complex network to describe topic dynamics, and analyzes the spatio-temporal characteristics of public semantics evolution. The proposed framework has demonstrated its effectiveness in analyzing the semantic spatial–temporal evolution of Chinese Weibo user behavior during COVID-19. The semantic change in response to COVID-19 was characterized by obvious expansion, frequent change, and gradual stabilization over time. In this case, there were obvious geographical differences in users’ semantic changes, which were mainly concentrated in the capital and economically developed areas. The semantics of users finally focused on specific topics related to positivity, epidemic prevention, and factual comments. Our work provides new insight into the behavioral response to disasters and provides the basis for data-driven public sector decisions. In emergency situations, this model could improve situational assessment, assist decision makers to better comprehend public opinion, and support analysts in allocating resources of disaster relief appropriately.
Metabolites Analysis of Anti-Myocardial Ischemia Active Components of Saussurea involucrata Based on Gut Microbiota—Drug Interaction
Authors: Yu Hang , Fu Jie , Guo Hui-Hui , Pan Li-Bin , Xu Hui , Zhang Zheng-Wei , Hu Jia-Chun , Yang Xin-Yu , Zhang Hao-Jian , Bu Meng-Meng , Lin Yuan , Jiang Jian-Dong , Wang Yan
Published: July 2022

Saussurea involucrata has been reported to have potential therapeutic effects against myocardial ischemia. The pharmacological effects of oral natural medicines may be influenced by the participation of gut microbiota. In this study, we aimed to investigate the bidirectional regulation of gut microbiota and the main components of Saussurea involucrata. We first established a quantitative method for the four main components (chlorogenic acid, syringin, acanthoside B, rutin) which were chosen by fingerprint using liquid chromatography tandem mass spectrometry (LC-MS/MS), and found that gut microbiota has a strong metabolic effect on them. Meanwhile, we identified five major rat gut microbiota metabolites (M1–M5) using liquid chromatography tandem time-of-flight mass spectrometry (LC/MSn-IT-TOF). The metabolic properties of metabolites in vitro were preliminarily elucidated by LC-MS/MS for the first time. These five metabolites of Saussurea involucrata may all have potential contributions to the treatment of myocardial ischemia. Furthermore, the four main components (10 μg/mL) can significantly stimulate intestinal bacteria to produce short chain fatty acids in vitro, respectively, which can further contribute to the effect in myocardial ischemia. In this study, the therapeutic effect against myocardial ischemia of Saussurea involucrata was first reported to be related to the intestinal flora, which can be useful in understanding the effective substances of Saussurea involucrata.
Functions of Breast Cancer Predisposition Genes: Implications for Clinical Management
Authors: Yoshimura Akiyo , Imoto Issei , Iwata Hiroji
Published: July 2022

Approximately 5–10% of all breast cancer (BC) cases are caused by germline pathogenic variants (GPVs) in various cancer predisposition genes (CPGs). The most common contributors to hereditary BC are BRCA1 and BRCA2, which are associated with hereditary breast and ovarian cancer (HBOC). ATM, BARD1, CHEK2, PALB2, RAD51C, and RAD51D have also been recognized as CPGs with a high to moderate risk of BC. Primary and secondary cancer prevention strategies have been established for HBOC patients; however, optimal preventive strategies for most hereditary BCs have not yet been established. Most BC-associated CPGs participate in DNA damage repair pathways and cell cycle checkpoint mechanisms, and function jointly in such cascades; therefore, a fundamental understanding of the disease drivers in such cascades can facilitate the accurate estimation of the genetic risk of developing BC and the selection of appropriate preventive and therapeutic strategies to manage hereditary BCs. Herein, we review the functions of key BC-associated CPGs and strategies for the clinical management in individuals harboring the GPVs of such genes.
Effect of High Myopia on Delayed Absorption of Subretinal Fluid after Scleral Buckling Surgery
Authors: Meng Yongan , Long Kejun , Chen Jing , Luo Jing
Published: July 2022

This study compared the absorption of subretinal fluid (SRF) in patients with rhegmatogenous retinal detachment (RRD) with and without high myopia after scleral buckling (SB) and investigated the effect of high myopia on SRF absorption. This retrospective study included patients with primary macula-off RRD grouped according to myopia and age. The optical coherence tomography (OCT) and OCT angiography indicators included subretinal fluid height (SRFH), subfoveal choroidal thickness (SFCT), and choroidal capillary blood flow density (CCFD) measured regularly. The presence of SRF 3 months after surgery was defined as delayed absorption. Overall, 90 eyes of 89 patients were enrolled, and 46 eyes (51.11%) had high myopia. In 43 eyes (47.78%), SRF absorption was delayed. There was no significant difference in SRF absorption after SB between the high and non-high myopia groups; younger patients (<35 years) had a higher probability of delayed absorption (p < 0.05). The SFCT in high myopia was significantly thinner than that in the non-high myopia group (p < 0.05); SFCT and SRFH were positively correlated (rs = 0.275, p = 0.002), and there was a significant difference between the average CCFD with and without SRF (p < 0.05). High myopia had no significant effect on SRF absorption after SB.
Virtual Reality Hypnosis in the Electrophysiology Lab: When Human Treatments Are Better than Virtual Ones
Authors: Coulibaly Iklo , Cardelli Laura , Duflos Claire , Moulis Lionel , Mandoorah Bara , Nicoleau Jean , Placide Leslie , Massin François , Pasquié Jean-Luc , Granier Mathieu
Published: July 2022

Aims: Virtual reality hypnosis (VRH) has been used successfully in various clinical settings to decrease anxiety and the sensation of pain. We aimed to investigate the feasibility and safety of VRH in patients undergoing electrophysiology and pacing procedures under conscious sedation. Methods: During a two-month period, VRH support was proposed and accepted by 25 patients undergoing electrophysiological procedures. Data were compared with a control group (n = 61) enrolled during the following three-month period. Both groups underwent the measurement of the duration of intervention, the consumption of analgesics and hypnotics, and their pain and comfort using a validated visual analogue scale (VAS 0−10). Results: The baseline characteristics were comparable in both groups, including age. There were no differences in procedure duration (46 (±29) vs. 56 (±32) min, p = 0.18) or in hypnotic/antalgic consumption (midazolam 1.95 (±1.44) vs. 2.00 (±1.22) mg, p = 0.83; sufentanyl 3.78 (±2.87) vs. 3.58 (±2.48) μg, p = 0.9) between the control and VRH groups. In a multivariate analysis, the use of VRH was independently associated with lower comfort during the procedure assessed by postoperative visual analogue scale (OR 15.00 [95% CI 4.77−47.16], p < 0.01). There was no influence of VRH use on pain or drug consumption. Conclusions: In our experience, compared with VRH, human care is preferable during procedures in electrophysiology lab to improve the comfort of the patient. VRH has no influence on pain or drug consumption.
Examining the Influence of Using First-Person View Drones as Auxiliary Devices in Matte Painting Courses on College Students’ Continuous Learning Intention
Authors: Gu Chao , Sun Jie , Chen Tong , Miao Wei , Yang Yunshuo , Lin Shuyuan , Chen Jiangjie
Published: July 2022

In terms of the teaching process of matte painting, it is essential for students to develop a sound understanding of the relationship between virtual and physical environments. In this study, first-person view (FPV) drones are applied to matte painting courses to evaluate the effectiveness of the teaching, and to propose more effective design suggestions for FPV drones that are more suitable for teaching. This provides students with a better learning environment using a digital education system. The results of the study indicate that the flow experience, learning interest, and continuous learning intention of students who use FPV drones in matte painting are significantly greater than those of students who only utilize traditional teaching methods. Furthermore, the technology incentive model (TIM) was developed in this study after being verified by the structural equation model. The results demonstrate that the second-order construct ‘technology incentive’ comprising perceived interactivity, perceived vividness, and novel experience positively influence students’ learning interest and continuous learning intentions under the mediation of flow experience.
Volatile Compounds of Algal Biomass Pyrolysis
Authors: López-Aguilar Héctor Alfredo , Quiroz-Cardoza David , Pérez-Hernández Antonino
Published: July 2022

The use and transformation of biomass into highly valuable products is a key element in circular economy models. The purpose of this research was to characterise the volatile compounds and the temperature at which they are emitted during the thermal decomposition by pyrolysis of algal biomass while looking at three different types: (A1) endemic microalgae consortium, (A2) photobioreactor microalgae consortium and (A3) Caribbean macroalgae consortium. Furthermore, the ultimate (CHON) and proximate (humidity, volatile solids and ashes) compositions of the algal biomass were determined. Some volatile species were identified as having potential industrial interest for use as precursors and intermediaries, such as commercially used aromatic compounds which if not suitably managed can be harmful to our health and the environment. It is concluded that the pyrolysis of algal biomass shows potential for the generation of valuable products. The information generated is useful, especially the temperature at which volatility occurs, in order to access the valuable compounds offered by the algal biomasses, and under the concept of biorefinery convert the issue of biomass disposal into a sustainable source of raw materials.
Two-Layer Rubber-Based Composite Material and UHMWPE with High Wear Resistance
Authors: Dyakonov Afanasy A. , Vasilev Andrey P. , Danilova Sakhayana N. , Okhlopkova Aitalina A. , Tarasova Praskovia N. , Lazareva Nadezhda N. , Ushkanov Alexander A. , Tuisov Aleksei G. , Kychkin Anatoly K. , Vinokurov Pavel V.
Published: July 2022

The aim of the study is the development of two-layer materials based on ultra-high-molecular-weight polyethylene (UHMWPE) and isoprene rubber (IR) depending on the vulcanization accelerators (2-mercaptobenzothiazole (MBT), diphenylguanidine (DPG), and tetramethylthiuram disulfide (TMTD)). The article presents the study of the influence of these accelerators on the properties and structure of UHMWPE. It is shown that the use of accelerators to modify UHMWPE leads to an increase in tensile strength of 28–53%, a relative elongation at fracture of 7–23%, and wear resistance of three times compared to the original UHMWPE. It has been determined that the introduction of selected vulcanization accelerators into UHMWPE leads to an increase in adhesion between the polymer and rubber. The study of the interfacial boundary of a two-layer material with scanning electron microscopy (SEM) and infrared spectroscopy (FTIR) showed that the structure is characterized by the presence of UHMWPE fibrils localized in the rubber material due to mechanical adhesion.
Dynamic Tensile Behavior of Woven C/SiC Composite: Experiments and Strain-Rate-Dependent Yield Criterion
Authors: Yu Jingwei , Zhang Peiwei , Chen Qiang , Fei Qingguo
Published: July 2022

This paper studies the yield behavior of a woven carbon-fiber-reinforced silicon-matrix (C/SiC) composite under dynamic tensile loading. Experiments were carried out to obtain the tensile properties of the C/SiC composite at a strain rate range of 2 × 10−5/s to 99.4/s. A strain-rate-dependent yield criterion based on the distortional strain energy density theory is established to describe the yield behavior. The interval uncertainty is considered for a more reliable yield prediction. Experimental results show that the yield stress, elastic modulus, and yield strain of the C/SiC composite grow with the increasing strain rate. The failure mode transitions from progressive crack extension to uneven fiber bundle breakage. The predicted results by the yield criterion match well with experimental data. Experimental results are enveloped within the uncertainty level of 45% in the critical distortional energy density, corresponding to an uncertainty of 14% and 11% in the yield stress and yield strain, respectively. With the support of the proposed strain-rate-dependent yield criterion, the yield behavior of the C/SiC composite under dynamic loading conditions can be predicted with reasonable accuracy.
3-D Surface Morphological Characterization of CAD/CAM Milled Dental Zirconia: An In Vitro Study of the Effect of Post-Fabrication Processes
Authors: Patil Ashwini , Jebaseelan Davidson
Published: July 2022

Objective: To investigate the effect on zirconia surface of the post-fabrication surface treatments on the morphological characteristics and mechanical properties of CAD/CAM milled dental zirconia specimens as well as to identify the critical parameters in the measurement of oral retention under in vitro circumstances. Method: The zirconia specimens (N = 20, n = 4) were subjected to CAD/CAM milling and divided into five groups. The specifications were: Group G1—sintered; Group G2—sintered followed by a polishing process; Group G3—sintered followed by polishing and sandblasting with alumina particles Al2O3 (110 µm); Group G4—sintered followed by sandblasting; Group G5—sintered followed by sandblasting with polishing as the end process. All the groups were subjected to Fretting wear tests, 3-D surface roughness measurements, and Vickers’s Micro hardness tests. Investigation of the phase transformation using XRD, and surface feature examination using SEM were also carried out. Additionally, one-way ANOVA, Tukey, and Pearson correlations were statistically analysed. Results: The fabrication processes had a significant effect on the performance of zirconia specimens in all the groups (p > 0.05). Specimens that underwent polishing as the last process exhibited lower surface roughness. The monoclinic phase of zirconia was observed in all the specimens before and after wear except for those in the G2 and G5 groups, where polishing was the end process. In G5, the post-wear surface properties revealed lower surface roughness and hardness. Further, the SEM and 3-D topography show grooves as seen by the dale void volume (Vvv) values; shallow valley depth (Svk); micro craters; and wear track. Conclusion: Specimens in G5 that were subjected to multistep post-fabrication process, namely sandblasting followed by polishing, yielded better results when compared to those in the other groups (G1, G2, G3, and G4). G5 with an interlayer of alumina is recommended for clinical applications due to its enhanced surface properties, mechanical properties, and low wear.
Experimental and Numerical Analysis of the Concrete Maturation Process with Additive of Phase Change Materials
Authors: Hsino Mahmoud , Jankowiak Tomasz , Jasiczak Józef
Published: July 2022

The article presents selected types of phase change materials (PCM) and their properties in terms of applications in various fields of science such as construction and concrete technology. The aim of the article is to present a comparative analysis between the results of the laboratory tests and numerical simulations. The analysis contains two types of PCM (powder and in liquid), which were dosed in a hybrid system to the concrete mix. The purpose of using PCM is to allow the technological barrier to be exceeded in hot and dry climate conditions, enabling the construction of non-cracking concrete structures. The paper presents a parametric analysis of the influence of various modeling elements on the obtained results. The procedure of generating and absorbing heat caused by the applied PCM was also implemented using user subroutine into finite element code (Abaqus/Standard). The numerically obtained results are consistent with the experimental results. The presented results demonstrate that the use of PCM improves the conditions of concrete maturation by reducing the average temperature of the mixture in its entire volume.
Experimental Study on Dynamic Compressive Behaviors of Sand under Passive Confining Pressure
Authors: Li Liang , Kou Xinyu , Zhang Gao , Huang Kewei
Published: July 2022

Dynamic compressive tests of sand under passive confining pressure were carried out using a Split Hopkinson Pressure Bar (SHPB) setup. The dynamic response, energy dissipation and particle-breaking behaviors of sand subjected to high-speed impact were investigated. Sand specimens with moisture contents of 0%, 2%, 4%, 8%, 10% and 12% and relative densities of 0.1, 0.5 and 0.9 were prepared. The variation in the strain rate was controlled between 90 s−1 and 500 s−1. The specimens were confined in a designed sleeve to create passive confining pressure. The experimental results show that the sand specimens were extremely sensitive to the strain rate. When the strain rate was less than 400 s−1, the stress and strain of the specimens increased with the increase in the strain rate but decreased when the strain rate exceeded 400 s−1. The peak strain and peak stress increased with the increase in the relative density. Particle breakage was aggravated with the strain-rate increase. Compared with the specimen without water, the relative breakage rate of the specimen with a moisture content of 12% decreased by 30.53% when the strain rate was about 95 s−1 and by 25.44% when the strain rate was about 460 s−1. The analysis of energy dissipation revealed the essential cause of sand destruction. The specific energy absorption rate increased with the increases in the initial relative density and moisture content.