bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamics of CTCF- and cohesin-mediated chromatin looping revealed by live-cell imaging
Authors: Gabriele Michele , Brandão Hugo B. , Grosse-Holz Simon , Jha Asmita , Dailey Gina M. , Cattoglio Claudia , Hsieh Tsung-Han S. , Mirny Leonid , Zechner Christoph , Hansen Anders S.
Published: April 2022

Animal genomes are folded into loops and topologically associating domains (TADs) by CTCF and loop-extruding cohesins, but the live dynamics of loop formation and stability remain unknown. Here, we directly visualized chromatin looping at the
Fbn2
TAD in mouse embryonic stem cells using super-resolution live-cell imaging and quantified looping dynamics by Bayesian inference. Unexpectedly, the
Fbn2
loop was both rare and dynamic, with a looped fraction of approximately 3 to 6.5% and a median loop lifetime of approximately 10 to 30 minutes. Our results establish that the
Fbn2
TAD is highly dynamic, and about 92% of the time, cohesin-extruded loops exist within the TAD without bridging both CTCF boundaries. This suggests that single CTCF boundaries, rather than the fully CTCF-CTCF looped state, may be the primary regulators of functional interactions.
Strong and fast hydrogel actuators
Authors: Jiang Zhen , Song Pingan
Published: April 2022

Plant cells inspire a hydrogel actuator that achieves ultrastrong and fast actuation
Citizen science for studying earthquakes
Authors: von Hillebrandt-Andrade Christa , Vanacore Elizabeth
Published: April 2022

Seismologist-citizen partnership helped understand the 2021 Haiti earthquake
Pharmacokinetics of Oral Tebipenem Pivoxil Hydrobromide in Subjects with Various Degrees of Renal Impairment
Authors: Patel Gina , Rodvold Keith A. , Gupta Vipul K. , Bruss Jon , Gasink Leanne , Bajraktari Floni , Lei Yang , Jain Akash , Srivastava Praveen , Talley Angela K.
Published: April 2022

Tebipenem pivoxil hydrobromide (TBP-PI-HBr) is an oral carbapenem prodrug antimicrobial agent with broad-spectrum activity that includes multidrug-resistant (MDR)
Enterobacterales
. This study evaluated the safety, tolerability, and pharmacokinetics of TBP-PI-HBr in healthy subjects with normal renal function (cohort 1) and subjects with various degrees of renal impairment (RI [cohorts 2 to 4]) or end-stage renal disease (ESRD) receiving hemodialysis (HD) (cohort 5). Subjects in cohorts 1 to 4 received a single oral dose of TBP-PI-HBr (600 mg).
C6 Hydroxymethyl-Substituted Carbapenem MA-1-206 Inhibits the Major
Acinetobacter baumannii
Carbapenemase OXA-23 by Impeding Deacylation
Authors: Stewart Nichole K. , Toth Marta , Alqurafi Maha A. , Chai Weirui , Nguyen Thu Q. , Quan Pojun , Lee Mijoon , Buynak John D. , Smith Clyde A. , Vakulenko Sergei B.
Published: April 2022

Carbapenem antibiotics are the drugs of choice for treatment of deadly infections caused by Gram-negative bacteria. However, their efficacy is severely compromised by the wide spread of carbapenem-hydrolyzing class D β-lactamases (CHDLs).
Kinetic Tracking of Plasmodium falciparum Antigens on Infected Erythrocytes with a Novel Reporter of Protein Insertion and Surface Exposure
Authors: Shao Jinfeng , Arora Gunjan , Manzella-Lapeira Javier , Brzostowski Joseph A. , Desai Sanjay A.
Published: April 2022

Malaria parasites invade and replicate within red blood cells of their human or animal hosts to avoid immune detection. At the same time, these parasites insert their own proteins into the host membrane to scavenge plasma nutrients, facilitate immune evasion, and perform other essential activities.
Rare Species-Driven Diversity–Ecosystem Multifunctionality Relationships are Promoted by Stochastic Community Assembly
Authors: Zhang Zhengqing , Lu Yahai , Wei Gehong , Jiao Shuo
Published: April 2022

The relative functional importance of rare and abundant species in driving relationships between biodiversity and ecosystem functions remains unknown. Here, we highlighted the importance of rare species for ecosystem multifunctionality.
Temporal Dynamics of Bacterial Communities along a Gradient of Disturbance in a U.S. Southern Plains Agroecosystem
Authors: Cornell Carolyn R. , Zhang Ya , Ning Daliang , Wu Liyou , Wagle Pradeep , Steiner Jean L. , Xiao Xiangming , Zhou Jizhong
Published: April 2022

Agricultural sustainability relies on healthy soils and microbial diversity. Agricultural management alters soil conditions and further influences the temporal dynamics of soil microbial communities essential to ecosystem functions, including organic matter dynamics, nutrient cycling, and plant nutrient availability.
Apparent preservation of primary foraminiferal Mg/Ca ratios and Mg-banding in recrystallized foraminifera
Authors: Staudigel Philip T. , John Eleanor H. , Buse Ben , Pearson Paul N. , Lear Caroline H.
Published: April 2022

Trace element and δ18O values of foraminifera are widely used to reconstruct oceanic temperatures throughout the Cenozoic and beyond. Previous work evaluating the geochemistry of foraminifera with differing degrees of physical preservation have shown that Mg/Ca and δ18O paleothermometers give discrepant values in recrystallized tests, with planktonic oxygen isotopes often yielding significantly lower temperatures than Mg/Ca ratios. To study the mobility of elements during diagenesis, we performed microspatial trace element analyses in Eocene Morozovella. Element maps show that trace element banding is readily identifiable and preserved, to an extent, in texturally recrystallized tests. A reaction-diffusion model was used to test whether the preservation of Mg-banding and the decoupling of δ18O and Mg/Ca values could be the result of diffusively limited “closed-system” recrystallization. Results show that, in a closed system, internal features (such as Mg-banding) will dissipate prior to changes in bulk Mg/Ca composition, while the bulk δ18O value will typically change faster than Mg/Ca. This is observed regardless of what partitioning coefficient is used for Mg and demonstrates that the planktonic Mg/Ca proxy is more diagenetically robust than the δ18O proxy. Thus, this model can explain the observed decoupling of these two proxies. Furthermore, the preservation of intra-test Mg-banding shows potential for use in evaluating the preservation of primary Mg/Ca values and hence the accuracy of paleotemperature reconstructions.
Secretory structure diversity on Astronium leaf
Authors: Carneiro Tainah Eduarda Boian , Martins Aline Redondo
Published: April 2022

Astronium fraxinifolium Schott and Astronium graveolens Jacq. are included in the Anacardiaceae. The secretory structures of Anacardiaceae have been studied several times; however, there is a lack of knowledge related to these structures in Astronium, and there are inconsistencies in the taxonomy of the groups. The present study aimed to describe the internal and external secretory structures of A. fraxinifolium and A. graveolens to refine the genus’ taxonomy and highlight the uniqueness of their differentiation. Plant samples were fixed, dehydrated, and prepared for analysis by light microscopy and scanning electron microscopy using standard anatomical techniques. Non-glandular trichomes are present over the entire surface of the blade of the mature leaves of A. fraxinifolium. In contrast, in A. graveolens, non-glandular trichomes are concentrated only on the midrib region of the leaflets. The glandular trichomes, absent in the mature leaves of A. fraxinifolium, are present in the mature leaves of A. graveolens around the midrib. Astronium fraxinifolium ducts have a schizolysigenous origin, and A. graveolens have a lysigenous origin. Therefore, it was concluded that, in general, secretory structures represent a crucial taxonomic factor distinguishing these species.
Antagonistic effect of copper and zinc in fertilization of spring wheat under low soil phosphorus conditions
Authors: Rahman Noabur , Peak Derek , Schoenau Jeff
Published: April 2022

Sound micronutrient management requires an understanding of nutrient interactions and transformation processes in soil–plant systems which can regulate bioavailability and plant uptake. A series of studies were conducted under controlled environment and field conditions to evaluate wheat response to Cu and Zn fertilization on P-deficient soils from western Canada. The grain and straw yields of wheat were reduced in two (Waskada and Tisdale) of three soils used in the controlled environment study, while yield was not affected at the Echo field site in 2016 when both Cu and Zn sulfate fertilizer were applied at 5 kg·ha–1 rates. Zinc concentration in soil and plant tissues was increased to apparent toxic levels with fertilizer addition in Waskada soils. An imbalance in tissue P:Zn concentration related to micronutrient fertilization was observed in Waskada and Tisdale soils. The availability of Cu and Zn in post-harvest soils was increased with increasing rate of these fertilizers' addition. Chemical and spectroscopic speciation using sequential extraction and X-ray absorption near edge structure, respectively, revealed that Cu and Zn were mostly speciated as carbonate phases, and complexation of these elements with carbonate and phyllosilicate minerals is likely the process controlling bioavailability in the soils.
LNGM: A link prediction algorithm based on local neighbor gravity model
Authors: Xu Yanjie , Ren Tao , Sun Shixiang
Published: April 2022

Link prediction is a fundamental study with a variety of applications in complex network, which has attracted increased attention. Link prediction often can be used to recommend new friends in social networks, as well as recommend new products based on earlier shopping records in recommender systems, which brings considerable benefits for companies. In this work, we propose a new link prediction algorithm Local Neighbor Gravity Model (LNGM) algorithm, which is based on gravity and neighbors (1-hop and 2-hop), to suggest the formation of new links in complex networks. Extensive experiments on nine real-world datasets validate the superiority of LNGM on eight different benchmark algorithms. The results further validate the improved performance of LNGM.
Dynamic Interaction Analysis of High-Speed Maglev Train and Guideway with a Control Loop Failure
Authors: Xiang Huoyue , Tian Xiangfu , Li Yongle , Zeng Min
Published: April 2022

The fault of a control loop can occur when a high-speed maglev train is running on guideways, which will affect the dynamic responses of the maglev train and guideway and is one of the controlling cases in the design of guideway functional parts. To study the dynamic response of the vehicle and guideway when a control loop failure occurs, first, a spatial coupling vibration model, which includes the three-dimensional (3D) maglev trains, guideways, piers and electromagnetic force based on the proportional-derivative (PD) controller, is proposed, and the electromagnetic force model for a control loop failure is presented. Second, the effectiveness of the coupling vibration model is verified based on the measured results of the Shanghai maglev line (SML). Finally, the dynamic responses of maglev train and guideway are discussed under a suspension magnet or guidance magnet with a control loop failure, and the influences of the location of the fault, the weight of the vehicle and the preload of the guidance system are analyzed. The most disadvantageous load value acting on the functional parts in case of magnet failure is obtained. The results show that the dynamic responses of the maglev train with a control loop failure will vary due to the location of the fault on trains and guideways, the weight of vehicle and the lateral preload. Although a control loop failure has little influence on the dynamic response of the guideway, the suspension force or guidance force on guideway will increase suddenly, and this sudden force is far larger than the vehicle static load or lateral preload of guidance magnets.
Collaborative Learning to Improve the Non-uniqueness of NMF
Authors: Benlamine Kaoutar , Bennani Younes , Matei Basarab , Grozavu Nistor , Falih Issam
Published: April 2022

Non-negative matrix factorization (NMF) is an unsupervised algorithm for clustering where a non-negative data matrix is factorized into (usually) two matrices with the property that all the matrices have no negative elements. This factorization raises the problem of instability, which means whenever we run NMF for the same dataset, we get different factorization. In order to solve the problem of non-uniqueness and to have a more stable solution, we propose a new approach that consists on collaborating different NMF models followed by a consensus. The proposed approach was validated on several datasets and the experimental results showed the effectiveness of our approach which is based on the reducing of standard reconstruction error in NMF model.
Optimized Feature Selection in Software Product Lines using Discrete Bat Algorithm
Authors: Sadeghi Hajar , Ajoudanian Shohreh
Published: April 2022

Software Product Lines (SPLs) are one of the ways to develop software products by increasing productivity and reducing cost and time in the software development process. In SPLs, each product has many features and it is necessary to consider the optimal and custom features of the products. In fact, selecting key features in SPLs is a challenging process. Feature selection in SPLs is an optimization problem and an NP-Hard problem. One way to select a feature is to use meta-heuristic algorithms modeled on nature, i.e., Bat Algorithm. By modeling bat behavior in prey hunting, a suitable meta-innovative algorithm is considered. This algorithm has important advantages that make it more accurate than conventional methods such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm. In this paper, to select software product features, idol binary algorithm and artificial neural network are used to identify important features of software products that reduce production costs and time. The experiments in MATLAB software and datasets related to software production lines show that the rate of reduction of target performance error or feature selection cost in software production lines in the proposed method has decreased by 64.17% with increasing population.
Directly Using Red Sandstone as a Catalyst to Synthesize Multi-Walled Carbon Nanotubes
Authors: Yuan Xinxin , Huang Hailu , Liang Chen , Chang Yi , Xu Lele , Zhang Hualian , Yong Zhenzhong , Chen Minghai
Published: April 2022

Natural catalysts used in the synthesis of carbon nanotubes have significant cost advantages due to their huge reserves, but natural minerals often require complicated pretreatments to obtain satisfactory products. In this study, red sandstone was directly used as a catalyst for the synthesis of multi-carbon nanotubes by chemical vapor deposition without complicated pretreatment. The SEM, TEM, Raman and TG characterization of the products at different growth temperatures ([Formula: see text]C, [Formula: see text]C and [Formula: see text]C) showed that [Formula: see text]C is the optimal condition for the growth of multi-walled carbon nanotubes (MWCNTs) by red sandstone. High-quality multi-wall carbon nanotubes can be obtained with a relatively high yield, and the [Formula: see text] of the product reaches 1.78, which exceeds that of many commercial multi-wall carbon nanotubes. Compared with other natural materials as catalysts for the synthesis of MWCNTs, red sandstone has a huge cost advantage because it can catalyze the synthesis of high-quality MWCNTs at [Formula: see text]C without complicated pretreatment.
Rapid and efficient characterization of cervical collagen orientation using linearly polarized colposcopic images
Authors: Khuong Cat Phan Ngoc , Quang Dung Nguyen Huu , Thanh Hai Pham , Nguyen Long , Ngoc Quynh Nguyen , Huynh Duc Le , Van Tien Tran , Anh Tu Ly
Published: April 2022

Collagen provides tissue strength and structural integrity. Quantification of the orientated dispersion of collagen fibers is an important factor when studying the mechanical properties of the cervix. In this study, for the first time, a new method for rapid characterization of the collagen fiber orientations of the cervix using linearly polarized light colposcopy is presented. A total of 24 colposcopic images were captured using a cross-polarized imaging system with white LED light sources. In the preprocessing stage, the Red channel of the RGB image was chosen, which contains no information of the blood vessels because of the low-absorption of blood cells in the red region. OrientationJ, which is an ImageJ plug-in, was used to estimate the local orientation of the collagen fibers. The result shows that in the nonpregnant cervix, the middle zone (Zone 2) has circumferentially aligned collagen fibers while the inner zone (Zone 1) has randomly arranged. The collagen fiber dispersion in Zone 2 is much smaller than that in Zone 1 at all four quadrants region (anterior, posterior, left, and right quadrant). This new analysis technique could potentially combine with diagnostic tools to provide a quantitative platform of collagen fibers in the clinic.
Assessing Human-AI Interaction Early through Factorial Surveys: A Study on the Guidelines for Human-AI Interaction
Authors: Li Tianyi , Vorvoreanu Mihaela , Debellis Derek , Amershi Saleema
Published: April 2022

This work contributes a research protocol for evaluating human-AI interaction in the context of specific AI products. The research protocol enables UX and HCI researchers to assess different human-AI interaction solutions and validate design decisions before investing in engineering. We present a detailed account of the research protocol and demonstrate its use by employing it to study an existing set of human-AI interaction guidelines. We used factorial surveys with a 2 × 2 mixed design to compare user perceptions when a guideline is applied versus violated, under conditions of optimal versus sub-optimal AI performance. The results provided both qualitative and quantitative insights into the UX impact of each guideline. These insights can support creators of user-facing AI systems in their nuanced prioritization and application of the guidelines.
Planning Wireless Backhaul Links by Testing Line of Sight and Fresnel Zone Clearance
Authors: Brown Philip E. , Czapiga Krystian , Jotshi Arun , Kanza Yaron , Kounev Velin , Suresh Poornima
Published: April 2022

Microwave backhaul links are often used as wireless connections between telecommunication towers, in places where deploying optical fibers is impossible or too expensive. The relatively high frequency of microwaves increases their ability to transfer information at a high rate, but it also makes them susceptible to spatial obstructions and interference. Hence, when deploying wireless links, there are two conflicting considerations. First, the antennas height, selected from the available slots on each tower, should be as low as possible. Second, there should be a line of sight (LoS) between the antennas, and a buffer around the LoS defined by the first Fresnel zone should be clear of obstacles. To compute antenna heights, a planning system for wireless links has to maintain an elevation model, efficiently discover obstacles between towers, and execute Fresnel-zone clearance tests over a 3D model of the deployment area.

In this article we present a system and algorithms for computing the height of antennas, by testing LoS and clearance of Fresnel zones. The system handles the following requirements: (1) the need to cover large areas, e.g., all of the USA, (2) big distance between towers, e.g., 100 kilometers, and (3) computing batches of thousands of pairs within a few minutes. We introduce three novel algorithms for efficient computation of antenna heights, we show how to effectively model and manage the large-scale geospatial data needed for the planning, and we present the results of tests over real-world settings.
Metrics for Robot Proficiency Self-assessment and Communication of Proficiency in Human-robot Teams
Authors: Norton Adam , Admoni Henny , Crandall Jacob , Fitzgerald Tesca , Gautam Alvika , Goodrich Michael , Saretsky Amy , Scheutz Matthias , Simmons Reid , Steinfeld Aaron , Yanco Holly
Published: April 2022

As development of robots with the ability to self-assess their proficiency for accomplishing tasks continues to grow, metrics are needed to evaluate the characteristics and performance of these robot systems and their interactions with humans. This proficiency-based human-robot interaction (HRI) use case can occur before, during, or after the performance of a task. This article presents a set of metrics for this use case, driven by a four-stage cyclical interaction flow: (1) robot self-assessment of proficiency (RSA), (2) robot communication of proficiency to the human (RCP), (3) human understanding of proficiency (HUP), and (4) robot perception of the human’s intentions, values, and assessments (RPH). This effort leverages work from related fields including explainability, transparency, and introspection, by repurposing metrics under the context of proficiency self-assessment. Considerations for temporal level (a priori, in situ, and post hoc) on the metrics are reviewed, as are the connections between metrics within or across stages in the proficiency-based interaction flow. This article provides a common framework and language for metrics to enhance the development and measurement of HRI in the field of proficiency self-assessment.
Metrics for Human-Robot Team Design: A Teamwork Perspective on Evaluation of Human-Robot Teams
Authors: Ma Lanssie Mingyue , Ijtsma Martijn , Feigh Karen M. , Pritchett Amy R.
Published: April 2022

Metrics for human-robot teaming should extend to teams consisting of multiple human and robotic agents, and to teams working in complex, dynamic work domains. This work proposes that to comprehensively analyze and evaluate multi-human, multi-robot teams, traditional HRI metrics of performance, and efficiency must be expanded upon to incorporate metrics of teamwork. We develop five distinct metrics to capture both ecological and cognitive aspects of teamwork found to be important in human-automation interaction, inspired by research in the cognitive systems engineering (CSE) community. We demonstrate the application of these metrics in a spacecraft maintenance case study comparing multiple human-robot team architectures. The case study demonstrates that the teamwork metrics capture aspects of human-robot interaction (HRI) not apparent when using only traditional performance and efficiency metrics. The article concludes that the proposed teamwork metrics are complementary to existing metrics in HRI and should be included in the evaluation of human-robot teams.
A Framework to Explore Proximate Human-Robot Coordination
Authors: Matsumoto Sachiko , Washburn Auriel , Riek Laurel D.
Published: April 2022

Proximate human-robot teaming (pxHRT)
is a complex subspace within human-robot interaction. Studies in this space involve a range of equipment and methods, including the ability to sense people and robots precisely. Research in this area draws from a wide variety of other fields, from human-human interaction to control theory, making the study design complex, particularly for those outside the field of HRI. In this paper, we introduce a framework that helps researchers consider tradeoffs across various task contexts, platforms, sensors, and analysis methods; metrics frequently used in the field; and common challenges researchers may face. We demonstrate the use of the framework via a case study which employs an autonomous mobile manipulator continuously engaging in shared workspace, handover, and co-manipulation tasks with people, and explores the effect of cognitive workload on pxHRT dynamics. We also demonstrate the utility of the framework in a case study with two groups of researchers new to pxHRT. With this framework, we hope to enable researchers, especially those outside HRI, to more thoroughly consider these complex components within their studies, more easily design experiments, and more fully explore research questions within the space of pxHRT.
Mental State Attribution to Robots: A Systematic Review of Conceptions, Methods, and Findings
Authors: Thellman Sam , de Graaf Maartje , Ziemke Tom
Published: April 2022

The topic of mental state attribution to robots has been approached by researchers from a variety of disciplines, including psychology, neuroscience, computer science, and philosophy. As a consequence, the empirical studies that have been conducted so far exhibit considerable diversity in terms of how the phenomenon is described and how it is approached from a theoretical and methodological standpoint. This literature review addresses the need for a shared scientific understanding of mental state attribution to robots by systematically and comprehensively collating conceptions, methods, and findings from 155 empirical studies across multiple disciplines. The findings of the review include that: (1) the terminology used to describe mental state attribution to robots is diverse but largely homogenous in usage; (2) the tendency to attribute mental states to robots is determined by factors such as the age and motivation of the human as well as the behavior, appearance, and identity of the robot; (3) there is acomputer < robot < humanpattern in the tendency to attribute mental states that appears to be moderated by the presence of socially interactive behavior; (4) there are conflicting findings in the empirical literature that stem from different sources of evidence, including self-report and non-verbal behavioral or neurological data. The review contributes toward more cumulative research on the topic and opens up for a transdisciplinary discussion about the nature of the phenomenon and what types of research methods are appropriate for investigation.
Neurophysiological and Behavioral Differences in Human-Multiagent Tasks: An EEG Network Perspective
Authors: Bales Gregory , Kong Zhaodan
Published: April 2022

Effective human-multiagent teams will incorporate the cognitive skills of the human with the autonomous capabilities of the multiagent group to maximize task performance. However, producing a seamless fusion requires a greater understanding of the human’s cognitive state as it reacts to uncertainties in both the task environment and agent dynamics. This study examines external behaviors in concert with neurophysiological measures acquired via electroencephalography (EEG) to probe the interactions between cognitive processes, behaviors, and performance in a human-multiagent team task. We show that changes in the α (8–12 Hz) and θ (4–8 Hz) bands of EEG indicate a higher burden on the cognitive resources associated with visual-spatial reasoning required to estimate a more complex kinematic state of robotic agents. These results are reinforced by complementary behavioral shifts in gaze and pilot inputs. Additionally, higher-performing participants tend to engage more actively in the task by utilizing greater amounts of visual-spatial reasoning. Finally, we show that features based on EEG dynamic-network-metrics provide discriminative information that distinguishes gaze behaviors associated with the attention process.
A novel nonlinear analysis of blood flow dynamics applied to the human lung
Authors: Buxton Richard B. , Prisk G. Kim , Hopkins Susan R.
Published: April 2022

Pulmonary blood flow varies both spatially and temporally. We describe a novel technique to uncover nonlinear interactions in dynamic images of pulmonary blood flow measured using MRI, based on mutual information between the flow fluctuations in different imaging voxels. In a proof-of-principle study, we show that the proposed metric of nonlinear interactions was sufficiently sensitive to detect a difference between small cohorts of subjects susceptible to high-altitude pulmonary edema (HAPE) and subjects resistant to HAPE.
Effects of fentanyl overdose-induced muscle rigidity and dexmedetomidine on respiratory mechanics and pulmonary gas exchange in sedated rats
Authors: Haouzi Philippe , Tubbs Nicole
Published: April 2022

The decrease in respiratory compliance and increased metabolism-induced hypoxemia produced by an overdose of fentanyl, in and of themselves, contribute to fentanyl toxicity.
Coping and Beliefs as Predictors of Functioning and Psychological Adjustment in Fibromyalgia Subgroups
Authors: Rubio Fidel Laura , García-Palacios Azucena , Herrero Rocío , Molinari Guadalupe , Suso-Ribera Carlos
Published: April 2022

Objectives. Research has pointed to two profiles of persons with fibromyalgia according to differences in functionality, thus distinguishing between functional and dysfunctional patients. The role of psychological factors underlying such clusters is unclear. This study aims to explore the contribution of pain beliefs and coping on fibromyalgia clustering. Methods. A cluster analysis was performed to classify 238 women with fibromyalgia using the Fibromyalgia Impact Questionnaire and the Beck Depression Inventory as clustering variables. Cluster differences in physical functioning, depression, pain beliefs, coping, and age were then calculated (Student’s t-test). Finally, a binary logistic regression was conducted to study the unique contribution of age, beliefs, and coping on cluster classification. Results. Two clusters were revealed. Cluster 1 had a poor adaptation to fibromyalgia regarding physical functioning and depression. They generally embraced less adaptive beliefs (i.e., disability, harm, emotion, and requests) and coping strategies (i.e., guarding, resting, and asking for assistance). Cluster 2 showed a better adaptation to fibromyalgia and adopted more favorable beliefs (i.e., control) and coping strategies (i.e., exercise and task persistence). Cluster differences in age were significant but small. The backward binary logistic regression suggested a final model with six predictors (guarding, task persistence, harm, emotion, solicitude, and age) that explained 31% of the variance of group membership. Discussion. These results suggest that only a subset of psychological variables uniquely and independently contribute to functional/dysfunctional group membership. The results support the need to address psychological components in the management of fibromyalgia and point to a subset of preferred target beliefs and coping strategies.
Comparison of Physicochemical Characteristics and Sensory Attributes of Four Different Chicken Breeds from the Genuine and Selected Local Market
Authors: Selamat Jinap , Zaidy Nur A. N. M. , Zakaria Nur S. , Juhari Nurul H. , Murugesu Suganya
Published: April 2022

Village chicken is known as a high-quality product perception and sold at high prices. However, the authenticity of village chicken is doubted because colored chicken has been claimed as village chicken to fraud the consumers and to gain high profit. No stringent strategy has been implemented by the local authority on the authenticity of the claimed village chickens. Thus, the study aimed to determine the meat quality of different chicken breeds including village chicken, broiler chicken (Cobb), colored chicken (Hubbard), and layer chicken from genuine suppliers and chickens sold at different local markets based on the physicochemical characterization, textural properties, and sensory evaluation. Chicken breeds were obtained from genuine suppliers and slaughtered at the slaughtering house Universiti Putra Malaysia. Proximate composition, color, and textural properties were evaluated. Minitab-19 and SIMCA-13 software were used to analyze the results, applying analysis of variance and partial least squares discriminant analysis, respectively. The study revealed that some of the market-supplied chickens were not authentic based on the features studied. About 20% of market village chickens had possessed similar results as the control village chicken. It can be shown that 80% of the claimed village chicken sold in the market was not authentic village chicken. This study showed the differentiation in texture composition such as chewiness, hardness, gumminess, cohesiveness, resilience, and springiness, followed by protein content, ash content, and a

∗

and b

∗

values as an indicator to differentiate the authenticity of different chicken breeds.
Visualization and Analysis of the Mapping Knowledge Domain of Acupuncture and Central Nervous System Cell Apoptosis
Authors: Qi Rongming , Xue Zhe , Liu Yaru
Published: April 2022

Chinese acupuncture therapy has demonstrated good clinical effects on neurological diseases and is widely used internationally. In the past 20 years, an increasing number of researchers around the world have devoted themselves to the study of the effect and mechanism of acupuncture for the treatment of central nervous system cell apoptosis. To discover the current research status of acupuncture-induced antiapoptosis in the central nervous system, we used the method of scientometric research and data visualization software to visually analyse 155 articles. The findings are as follows. First, the antiapoptosis effects of acupuncture in the central nervous system have received increasing attention overseas and domestically. China and the United States have leading positions in this research field. Second, 5 stable and high-yielding research teams have been formed in the field of acupuncture-induced antiapoptosis. The main research directions of these teams are electroacupuncture (EA) pretreatment for the central nervous system cell apoptosis, acupuncture for antineuronal apoptosis in vascular dementia, EA regulation of related signalling pathways, EA regulation of nerve cell apoptosis and autophagy after stroke, and EA regulation of the MAPK signalling pathway. Researchers on teams with more extensive cooperation have more research results and better research continuity. Third, there are diversified research hotspots. The original research hotspots are still receiving attention, and new hotspots have emerged in recent years.
Research on Wastewater Treatment Monitoring Algorithms Based on Deep Convolutional Neural Networks
Authors: Zhang Xun , Gu Yanhui
Published: April 2022

Around the problems of data loss, noise, and different temporal and spatial scale features of urban wastewater treatment process data, a method of monitoring and predicting wastewater treatment process data based on deep convolutional neural networks is proposed in the paper. Firstly, to address the problem that urban wastewater treatment process data has multiple spatial and temporal scale characteristics, which makes it difficult for the data to be used effectively, a spatial and temporal data fusion model based on fuzzy neural network (FNN) is proposed. Fuzzy neural networks have strong generalization ability and robustness. Secondly, to enable accurate and real-time monitoring of the content of the monitored components in the effluent of the urban wastewater treatment process, an intelligent prediction model based on SDF-FNN is established for the effluent. Finally, in order to verify the effectiveness of this intelligent prediction model, the model is tested using data collected from actual municipal wastewater treatment plants. The experimental results show that the wastewater treatment intelligent monitoring model is effective and can predict the content of the effluent monitoring index with high accuracy.
Using Machine Learning to Predict the Requirement for Revascularization in Patients with Chest Pain in the Emergency Department
Authors: Zheng ZhiChang , Guo Ruifeng , Wang Nian , Jiang Bo , Ma Chun Peng , Ai Hui , Wang Xiao , NIE ShaoPing
Published: April 2022

Objective. The study aimed to use machine learning algorithms to predict the need for revascularization in patients presenting with chest pain in the emergency department. Methods. We obtained data from 581 patients with chest pain, 264 who underwent revascularization, and the other 317 were treated with medication alone for 3 months. Using standard algorithms, linear discriminant analysis, and standard algorithms, we analyzed 41 features relevant to coronary artery disease (CAD). Results. We identified seven robust predictive features. The combination of these predictors gave an area under the curve (AUC) of 0.830 to predict the need for revascularization. By contrast, the GRACE score gave an AUC of 0.68. Conclusions. This machine learning-based approach predicts the need for revascularization in patients with chest pain.
College Classroom English Teaching Methods and Practice Based on Big Data Technology
Authors: Tang Yuan , Quan Zhi
Published: April 2022

The quality of classroom English teaching has become a general concern of the society, because the efficiency of students’ classroom learning can reflect the quality of English teaching. Traditional classroom English teaching has deviated from the development of the times, which is not conducive to the training of diversified, practical, and innovative talents. Big data expands the time and space of education and has a great impact on higher education. The combination of traditional education methods and modern education technology is more conducive to improving teaching level and quality. The application advantages of big data in English teaching under the background of big data are particularly prominent. This paper adopts the big data technology of the MOOC online learning platform to analyze the quality of college students’ classroom English teaching so as to help teachers clearly understand the learning effects of students. Meanwhile, it analyzes the learning behaviors of students and teachers’ teaching behaviors so that teachers can understand each student’s learning status. By comparing with the traditional English teaching data of the first semester, the leap of teachers’ life using MOOC English teaching platform has been improved, the participation degree is higher, and the English teaching quality has been improved. Students who use MOOC English teaching platform have 5% higher overall participation in learning than students in traditional English teaching.
Efficacy, Safety, and Prognosis of Sequential Therapy with Tamoxifen and Letrozole versus Letrozole Monotherapy for Breast Carcinoma
Authors: Lu Xinli , Qian Cheng
Published: April 2022

Objective. To explore the efficacy, safety, and patient prognosis of letrozole (LTZ) alone or in sequence with tamoxifen (TAM) for the treatment of breast carcinoma (BC). Methods. In this retrospective study, 150 patients with BC who received treatment in the First People’s Hospital of Ningyang County between January 2012 and January 2017 were selected. According to different treatment methods, 99 cases receiving sequential therapy with TAM and LTZ were included in the research group, and the remaining 51 patients receiving LTZ monotherapy were selected as the control group. The efficacy, safety, survival rate, recurrence rate, and blood lipid indices (total cholesterol, TC; triglyceride, TG; high-density lipoprotein cholesterol, HDL-C; and low-density lipoprotein cholesterol, LDL-C) of the two groups were observed and compared. Results. The overall response rate of the research group was statistically higher than that of the control group, and the incidence of adverse reactions was significantly lower. No evident difference was observed in 1-, 3-, or 5-year survival rates between the two groups, while the 3-5-year recurrence rate was obviously lower, and the improvement of blood lipid indices was significantly better in the research group compared with the control group. Conclusion. LTZ alone or in sequence with TAM is effective and safe for the treatment of BC, which can significantly improve the prognosis and blood lipid indices of BC patients.
Nur77 Deficiency Exacerbates Macrophage NLRP3 Inflammasome-Mediated Inflammation and Accelerates Atherosclerosis
Authors: Yuan Ruosen , Zhang Weifeng , Nie Peng , Lan Keke , Yang Xiaoxiao , Yin Anwen , Xiao Qingqing , Shen Yejiao , Xu Ke , Wang Xia , Pan Xin , Shen Linghong , He Ben
Published: April 2022

Purpose. Activation of NLR (nucleotide-binding and leucine-rich repeat immune receptor) family pyrin domain containing 3 (NLRP3) inflammasome mediating interleukin- (IL-) 1β secretion has emerged as an important component of inflammatory processes in atherogenesis. The nuclear receptor Nur77 is highly expressed in human atherosclerotic lesions; however, its functional role in macrophage NLRP3 inflammasome activation has not yet been clarified. Methods, Materials, and Results. Eight-week-old apolipoprotein E (ApoE)−/− and ApoE−/− Nur77−/− mice that were fed a Western diet underwent partial ligation of the left common carotid artery (LCCA) and left renal artery (LRA) to induce atherogenesis. Four weeks later, severe plaque burden associated with increased lipid deposition, reduced smooth muscle cells, macrophage infiltration, and decreased collagen expression was identified in ApoE−/− Nur77−/− mice compared with those in ApoE−/− mice. ApoE−/− Nur77−/− mice showed increased macrophage inflammatory responses in carotid atherosclerotic lesions. In vitro studies demonstrated that oxidized low-density lipoprotein cholesterol (ox-LDL) increased the release of lactate dehydrogenase (LDH) and upregulated the expressions of cleaved caspase-1, cleaved IL-1β and gasdermin D (GSMD) in WT peritoneal macrophages (PMs) in a NLRP3-dependent manner. Nur77−/− PMs exhibited a further increased level of NLRP3 inflammasome-mediated inflammation under ox-LDL treatment compared with WT PMs. Mechanistically, Nur77 could bind to the promoter of NLRP3 and inhibit its transcriptional activity. Conclusions. This study demonstrated that Nur77 deletion promotes atherogenesis by exacerbating NLRP3 inflammasome-mediated inflammation.
Artificial Neural Network Modeling of Abrasion Loss and Surface Roughness of Crab Carapace Impregnated Coir Vinyl Ester Composites
Authors: Rajamuneeswaran S. , Jayabal S. , Nagaprasad N. , Veerappan G. , Jule Leta Tesfaye , Krishnaraj Ramaswamy
Published: April 2022

Roughness plays an important role in determining how an object would be related with its environment. In tribology, rough surfaces easily obtain wear more quickly and have higher friction coefficients than smooth surfaces. Roughness is often a good analyzer of the performance of a mechanical component. This investigation is aimed to study the abrasion loss and surface roughness behaviors in crab carapace-filled coir fiber reinforced vinyl ester composites. The development of filler-impregnated fiber-polymer composites in recent years necessitated the evaluation and prediction of tribological behaviors in fiber reinforced composites. The composite fabrication was planned by varying the three fabrication parameters with three levels such as fiber length (10 mm, 30 mm, and 50 mm), fiber diameter (0.1 mm, 0.18 mm, and 0.25 mm), and content of crab carapace fillers (0%, 2%, and 4%) as per Design of Experiments (DOEs) in this current investigation. Low velocity integrated wear loss tests on composite samples were carried out, and also the average surface roughness is measured in the fabricated composites. Nonlinear regression equations were developed to study the correlation between tribological behaviors and fabrication parameters. The interaction effect of fabrication parameters was studied using ANOVA two-tail test and validated using response surface plots. In order to forecast abrasion loss and surface roughness behaviors, artificial neural network (ANN) models were constructed, and it was discovered that the produced ANN models effectively predicted the abrasion loss as well as surface roughness behavior within the given ranges.
[Retracted] Research on the Recommendation Algorithm of Rural Tourism Routes Based on the Fusion Model of Multiple Data Sources
Authors: Li Hong , Qiao Man , Peng Shuai
Published: April 2022

Rural tourism has become an important force in implementing the rural revitalisation strategy and accelerating rural economic development. The hectic pace of life has made more and more city dwellers yearn for rural life, and travelling in the countryside has become their weekend choice. However, the current level of rural tourism informationization is low, the publicity is insufficient, the tourists’ awareness is low, and the source of customers is seriously insufficient. To this end, this paper proposes a relatively novel multidata source fusion tourism recommendation algorithm, which adopts the idea of tensor orthogonal decomposition and fuses multisource data models to predict the target domain’s for rating. The integrated consideration of multiple data sources under the do‐it‐yourself approach assists the target domain to discover the target user neighbourhood users more quickly and to discover the user’s interest degree more accurately. It is worth pointing out that the recommendation algorithm proposed in this paper under the fusion of multiple data sources is not necessarily applicable to data sources with weak correlation, such as travel data sources and music data sources, which are relatively weakly correlated, and the algorithm is slightly weak in making predictions of user preferences.
The Dysregulation of SOX Family Correlates with DNA Methylation and Immune Microenvironment Characteristics to Predict Prognosis in Hepatocellular Carcinoma
Authors: Qin Sha , Liu Gaoming , Jin Haoer , Chen Xue , He Jiang , Xiao Juxiong , Qin Yan , Mao Yitao , Zhao Luqing
Published: April 2022

Background. Due to the molecular heterogeneity of hepatocellular carcinoma (HCC), majority of patients respond poorly among various of therapy. This study is aimed at conducting a comprehensive analysis about roles of SOX family in HCC for obtaining more therapeutic targets and biomarkers which may bring new ideas for the treatment of HCC. Methods. UALCAN, Kaplan Meier plotter, cBioPortal, STRING, WebGestalt, Metascape, TIMER 2.0, DiseaseMeth, MethSurv, HPA, CCLE database, and Cytoscape software were used to comprehensively analyze the bioinformatic data. Results. SOX2, SOX4, SOX8, SOX10, SOX11, SOX12, SOX17, and SOX18 were significantly differentially expressed in HCC and normal tissues and were valuable for the grade and survival of HCC patients. In addition, the gene alterations of SOX family happened frequently, and SOX4 and SOX17 had the highest mutation rate. The function of SOX family on HCC may be closely correlated with the regulation of angiogenesis-related signaling pathways. Moreover, SOX4, SOX8, SOX11, SOX12, SOX17, and SOX18 were correlation with 8 types of immune cells (including CD8+ T cell, CD4+ T cell, B cell, Tregs, neutrophil, macrophage, myeloid DC, and NK cell), and we found that most types of immune cells had a positive correlation with SOX family. Notably, CD4+ T cell and macrophage were positively related with all these SOX family. NK cells were negatively related with most SOX family genes. DNA methylation levels in promoter area of SOX2, SOX4, and SOX10 were lower in HCC than normal tissues, while SOX8, SOX11, SOX17, and SOX18 had higher DNA methylation levels than normal tissues. Moreover, higher DNA methylation level of SOX12 and SOX18 demonstrated worse survival rates in patients with HCC. Conclusion. SOX family genes could predict the prognosis of HCC. In addition, the regulation of angiogenesis-related signaling pathways may participate in the development of HCC. DNA methylation level and immune microenvironment characteristics (especially CD4+ T cell and macrophage immune cell infiltration) could be a novel insight for predicting prognosis in HCC.