bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of collaboratively developed management measures to reduce coral and sponge bycatch in a fully monitored multispecies trawl fishery
Authors: Gale Katie S.P. , Forrest Robyn E. , Rooper Christopher N. , Nephin Jessica , Wallace Scott , Driscoll John , Rubidge Emily
Published: March 2022

To protect cold-water corals and sponges from fishing damage, management changes were made in 2012 to the groundfish bottom trawl fishery British Columbia, Canada. The Groundfish Trawl Habitat Agreement restricted the spatial footprint of the fishery and introduced a cold-water coral and sponge bycatch quota, which was among the world’s first. Using 12 years of catch records from the fishery, we found a 31% decrease in overall frequency of encounters of cold-water coral and sponge, a 76% decrease in mean catch weight, and an 89% decrease in total annual catch. We tracked changes in the relative utilization of fine-scale fishing grounds (“fishing opportunities”) and found evidence of active avoidance of areas with high cold-water coral and sponge density. The habitat agreement appears overall to have been successful at reducing impacts to cold-water coral and sponge, although we identified several areas of potential conservation concern where effort and catch have not decreased. Nonspatial management measures in a complex multispecies fishery can result in spatial changes in fishing behaviour, with positive conservation outcomes for bycatch species.
Crowding competes with trapping to enhance interfacial diffusion
Authors: Cvitković Mislav , Ghanti Dipanwita , Raake Niklas , Smith Ana-Sunčana
Published: March 2022

Diffusion of species on biological membranes or materials interfaces is expected to slow down with an increase in their density, but also due to their intermittent binding to functional moieties or surface-defects. These processes, known as crowding and trapping, respectively, occur simultaneously in a broad range of interfacial systems. However their combined effect on the diffusion coefficients was not studied hitherto. Here, we analytically calculate and numerically validate by Monte Carlo simulations an expression for the diffusion coefficient of a two-dimensional lattice gas in a field of immobilized traps. As expected, trapping and crowding both suppress transport but, surprisingly, the diffusion coefficient is non-monotonous. Namely, increasing gas densities increases trap occupancy while crowding is not overpowering, such that the diffusion reaches a maximum. These results should be relevant to interfacial growth phenomena, as discussed in the context of nascent adhesions in cells.
Dynamical ideals of non-commutative rings
Authors: Nikolaev Igor V.
Published: March 2022

A dynamical analog of the prime ideals for simple non-commutative rings is introduced. We prove a factorization theorem for the dynamical ideals. The result is used to classify the surface knots and links in the smooth four-dimensional manifolds.
ROME: All Overlays Lead to Aggregation, but Some Are Faster than Others
Authors: Blöcher Marcel , Coppa Emilio , Kleber Pascal , Eugster Patrick , Culhane William , Ardekani Masoud Saeida
Published: March 2022

Aggregation is common in data analytics and crucial to distilling information from large datasets, but current data analytics frameworks do not fully exploit the potential for optimization in such phases. The lack of optimization is particularly notable in current “online” approaches that store data in main memory across nodes, shifting the bottleneck away from disk I/O toward network and compute resources, thus increasing the relative performance impact of distributed aggregation phases.

We present ROME, an aggregation system for use within data analytics frameworks or in isolation. ROME uses a set of novel heuristics based primarily on basic knowledge of aggregation functions combined with deployment constraints to efficiently aggregate results from computations performed on individual data subsets across nodes (e.g., merging sorted lists resulting from top-
k
). The user can either provide minimal information that allows our heuristics to be applied directly, or ROME can autodetect the relevant information at little cost. We integrated ROME as a subsystem into the Spark and Flink data analytics frameworks. We use real-world data to experimentally demonstrate speedups up to 3× over single-level aggregation overlays, up to 21% over other multi-level overlays, and 50% for iterative algorithms like gradient descent at 100 iterations.
Category-Stitch Learning for Union Domain Generalization
Authors: Liu Yajing , Xiong Zhiwei , Li Ya , Lu Yuning , Tian Xinmei , Zha Zheng-Jun
Published: March 2022

Domain generalization aims at generalizing the network trained on multiple domains to unknown but related domains. Under the assumption that different domains share the same classes, previous works can build relationships across domains. However, in realistic scenarios, the change of domains is always followed by the change of categories, which raises a difficulty for collecting sufficient aligned categories across domains. Bearing this in mind, this article introduces union domain generalization (UDG) as a new domain generalization scenario, in which the label space varies across domains, and the categories in unknown domains belong to the union of all given domain categories. The absence of categories in given domains is the main obstacle to aligning different domain distributions and obtaining domain-invariant information. To address this problem, we propose category-stitch learning (CSL), which aims at jointly learning the domain-invariant information and completing missing categories in all domains through an improved variational autoencoder and generators. The domain-invariant information extraction and sample generation cross-promote each other to better generalizability. Additionally, we decouple category and domain information and propose explicitly regularizing the semantic information by the classification loss with transferred samples. Thus our method can breakthrough the category limit and generate samples of missing categories in each domain. Extensive experiments and visualizations are conducted on MNIST, VLCS, PACS, Office-Home, and DomainNet datasets to demonstrate the effectiveness of our proposed method.
Investigation of Electromechanical, Piezoelectric and Ferroelectric Properties of Ba(Zr0.05Ti0.95)O3 Ceramic
Authors: Badapanda T. , Parija B. , Barman R. , Chaterjee S.
Published: March 2022

This paper demonstrates the structural, dielectric, ferroelectric, piezoelectric and electromechanical parameters of the pure-phase Ba(Zr0.05Ti0.95)O3 /BZT composition prepared through conventional solid state technique. The identification of compound and formation were analysed by X-ray diffraction (XRD) technique that demonstrated a pure perovskite phase of the synthesized composition. The sintering temperature- dependent density of the BZT ceramics wasstudied andthe sample with high density was considered for further study. Dense and well-defined grains were observed in the micrograph of the BZT sample studied by SEM analysis. The frequency depended dielectric study at the room temperature shows a very small variation of dielectric constant with frequency. Phase transitions related to orthorhombic symmetry to tetragonal symmetry, and, tetragonal symmetry to cubic symmetry were observed as of temperature variant dielectric study. The ferroelectric and piezoelectric strain behaviours were studied at different amplitudes and frequencies of applied field. The electromechanical parameters were obtained using the resonance and anti-resonance technique as mentioned in the IRE standard. The results obtained from the above studies point out that the BZT ceramic has the potential to be a candidate for environmentally friendly sensor and actuator device with high performance.
Superior Performance in Liquid Crystal Alignment of Polystyrene-Block-Poly(ethylene-ran-butylene)-Block-Polystyrene-Graft-Maleic Anhydride Film Irradiated with Ion Beam
Authors: Kim Dong Hyun , Lee Dong Wook , Oh Jin Young , Won Jonghoon , Seo Dae-Shik
Published: March 2022

We studied the change of the surface and liquid crystal (LC) alignment characteristics of Polystyrene-block-poly(ethylene-ran-butylene)-block-polystyrene-graft-maleic anhydride (SEBS-g-MA) film according to ion beam (IB) irradiation. Atomic force microscopy (AFM) analysis revealed that IB irradiation reduces peaks and creates a wrinkled structure. X-ray photoelectron spectroscopy (XPS) analysis revealed that IB irradiation disintegrates the C–C bonds and makes C–O bonds, creating a dipole-dipole interaction, which improves the LC alignment characteristics. Through polarized optical microscopy (POM) analysis, it was found that the best LC alignment characteristics can be obtained after 120 s of IB irradiation. It was found that the anisotropy caused by the ion beam contributed more to the liquid crystal alignment in homogeneous direction than the one caused by the wrinkle structure.
LINC01535 Attenuates ccRCC Progression through Regulation of the miR-146b-5p/TRIM2 Axis and Inactivation of the PI3K/Akt Pathway
Authors: Zhang Zhiming , Fu Xiaoliang , Gao Yanyao , Nie Zhiyong
Published: March 2022

lncRNAs, a group of eukaryotic cell genome-encoded transcripts, have been demonstrated to exert a notable impact on tumorigenesis. LINC01535, belonging to the lncRNA family, was reported to have an aberrant expression in certain types of cancers and thus affect cancer progression. Nevertheless, the expression pattern and potential roles of LINC01535 in clear cell renal cell carcinoma (ccRCC) remain to be elucidated. Here, LINC01535 expression was detected in ccRCC by RT-qPCR, cell proliferation by CCK-8 assays, and invasion by transwell assays. Besides, effects of LINC01535 on in vivo tumor growth were investigated by xenograft tumor models. The miR-146b-5p/LINC01535/TRIM2 interaction was evaluated via luciferase reporter assays. This study showed downregulation of LINC01535 in ccRCC. Moreover, LINC01535 upregulation attenuated in vitro ccRCC development and hindered in vivo tumor growth. Furthermore, LINC01535 sponged miR-146b-5p which had a negative correlation with LINC01535, and TRIM2 was a direct target of miR-146b-5p and mediated by LINC01535. Mechanically, LINC01535/miR-146b-5p/TRIM2 axis affected ccRCC progression by mediating the PI3K/Akt signaling. All in all, our observations suggest the LINC01535/miR-146b-5p/TRIM2 axis as a crucial role in ccRCC.
A Multiplex Conversion of a Historical Cinema
Authors: Cascardi Alessio , Verre Salvatore , Sportillo Alessandra , Giorgio Gaetano
Published: March 2022

The cultural building Heritage is a valuable trace of the past social life in a city. One peculiar typology of building is the theatre or, more recently, the cinema. Within this indoor space, the community of people actively live an emotional feeling over the time causing memories linked to not only the show itself, but also to the place. Furthermore, cinemas are often located in city centers where buildings are historical‐oriented form the architectural point of view and, for this reason, their added‐value needs to be recognized. Currently, the modernization and the improvement of old cinemas is becoming an interesting topic in the field of civil engineering. In order to empathize this aspect, the structural strengthening for a multiplex conversion of an historical cinema is herein reported. The studied structure required a seismic joint (separating the masonry to the reinforced concrete structural bodies) and a severe strengthening of a very long span beam due to a relevant overloading (in seismic loads combination) caused by the new architectonical project. The numerical simulations demonstrated the validity of two bending strengthening systems (i.e. Fiber Reinforced Polymer‐plate and Beton Plaquè) in terms of both load bearing capacity and maximum deflection. This overview is a part of a larger study in the way of a global structural interventions which will also involve the masonry members.
High-Reliability Business Management Strategy Analysis Based on GPRS Wireless Communication
Authors: Cai Gang , Ni Chunmei
Published: March 2022

Enterprise is an indispensable factor of production in the country’s economic and social development, and the operation of the enterprise is indispensable. The development of strategic operation of the enterprise is facing many problems, and the survival of the enterprise is facing serious threats. The purpose of this article is to study the method of establishing a reliable enterprise strategic management system based on GPRS wireless communication and neural network. Let the company continue to grow in a sustainable and healthy way. This article puts forward the importance of corporate strategic management under GPRS wireless communication. Strategic business management can improve the foresight and initiative of enterprises, overcome short-term behaviour, and provide a clear direction for the development of the enterprise. In the experimental data of this article, it can be seen from 2016 that the demand for talent management by enterprises is lower than that in 2019. By 2019, enterprises will have the demand is as high as 85.3%, so enterprise management development needs should be taken seriously. The error between the actual output of the network and the expected output is controlled within 5%, which shows that the established neural network has a good evaluation effect and can be used to evaluate the talents of business operators. This also shows that the established BP neural network can fully absorb the judgment experience of experts and the actual employment of enterprises. The results show that the evaluation results obtained according to the evaluation network model have certain guiding significance for the selection and assessment of employers and the self-evaluation of management talents.
H

∞

Consensus Design and Online Scheduling for Multiagent Systems with Switching Topologies via Deep Reinforcement Learning
Authors: Cheng Haoyu , Song Ruijia , Xu Linpeng , Zhang Di , Xu Shengli
Published: March 2022

This paper is devoted to

H

∞

consensus design and online scheduling for homogeneous multiagent systems (MASs) with switching topologies via deep reinforcement learning. The model of homogeneous MASs with switching topologies is established based on switched systems theory, in which the switching of topologies is viewed as the switching among subsystems. By employing linear transformation, the closed-loop systems of MASs are converted into reduced-order systems. The problem of

H

∞

consensus design can be transformed to the issue of

H

∞

control. It is supposed that the consensus protocol is composed of two parts: dynamics-based protocol and learning-based protocol, where dynamics-based protocol is provided to guarantee the convergence and weighted attenuation and learning-based protocol is proposed to improve the transient performance. Then, the multiple Lyapunov function (MLF) method and mode-dependent average dwell time (MDADT) method are combined to ensure the stability and weighted

H

∞

disturbance attenuation index of reduced-order systems. The sufficient existing conditions of dynamics-based protocol are given through the feasible solutions of linear matrix inequalities (LMIs). Moreover, the online scheduling is formulated as a Markov decision process, and the deep deterministic policy gradient (DDPG) algorithm in the framework of actor-critic is proposed for the compensation of disturbance to explore optimal control policy. The online scheduling of parameters of MASs is viewed as bounded compensation of dynamics-based protocol, whose stability can be guaranteed by nonfragile control theory. Finally, simulation results are provided to illustrate the effectiveness and superiority of the proposed method.
A Combination Analysis of IVIM‐DWI Biomarkers and T2WI‐Based Texture Features for Tumor Differentiation Grade of Cervical Squamous Cell Carcinoma
Authors: Shi Bin , Dong Jiang-Ning , Zhang Li-Xiang , Li Cui-Ping , Gao Fei , Li Nai-Yu , Wang Chuan-Bin , Fang Xin , Wang Pei-Pei
Published: March 2022

Purpose. To explore the value of intravoxel incoherent motion diffusion‐weighted imaging (IVIM‐DWI) and texture analysis on T2‐weighted imaging (T2WI) for evaluating pathological differentiation of cervical squamous cell carcinoma. Method. This retrospective study included a total of 138 patients with pathologically confirmed poor/moderate/well‐differentiated (71/49/18) who underwent conventional MRI and IVIM‐DWI scans. The values of ADC, D, D∗, and f and 58 T2WI‐based texture features (18 histogram features, 24 gray‐level co‐occurrence matrix features, and 16 gray‐level run length matrix features) were obtained. Multiple comparison, correlation, and regression analyses were used. Results. For IVIM‐DWI, the ADC, D, D∗, and f were significantly different among the three groups (p < 0.05). ADC, D, and D∗ were positively correlated with pathological differentiation (r = 0.262, 0.401, 0.401; p < 0.05), while the correlation was negative for f (r = −0.221; p < 0.05). The comparison of 52 parameters of texture analysis on T2WI reached statistically significant levels (p < 0.05). Multivariate logistic regression analysis incorporated significant IVIM‐DWI, and texture features on T2WI showed good diagnostic performance both in the four differentiation groups (poorly vs. moderately, area under the curve(AUC) = 0.797; moderately vs. well, AUC = 0.954; poorly vs. moderately and well, AUC = 0.795; and well vs. moderately and poorly, AUC = 0.952). The AUCs of each parameters alone were smaller than that of each regression model (0.503∼0.684, 0.547∼0.805, 0.511∼0.712, and 0.636∼0.792, respectively; pairwise comparison of ROC curves between regression model and individual variables, p < 0.05). Conclusions. IVIM‐DWI biomarkers and T2WI‐based texture features had potential to evaluate the pathological differentiation of cervical squamous cell carcinoma. The combination of IVIM‐DWI with texture analysis improved the predictive performance.
Evaluation of Blood-Brain-Barrier Permeability, Neurotoxicity, and Potential Cognitive Impairment by Pseudomonas aeruginosa’s Virulence Factor Pyocyanin
Authors: Rashid Muhammad Ibrahim , Rashid Habiba , Andleeb Saadia , Ali Amjad
Published: March 2022

Pyocyanin (PCN) is a redox-active secondary metabolite produced by Pseudomonas aeruginosa as its primary virulence factor. Several studies have reported the cytotoxic potential of PCN and its role during infection establishment and progression. Considering its ability to diffuse through biological membranes, it is hypothesized that PCN can gain entry into the brain and induce oxidative stress across the blood-brain barrier (BBB), ultimately contributing towards reactive oxygen species (ROS) mediated neurodegeneration. Potential roles of PCN in the central nervous system (CNS) have never been evaluated, hence the study aimed to evaluate PCN’s probable penetration into CNS through blood-brain barrier (BBB) using both in silico and in vivo (Balb/c mice) approaches and the impact of ROS generation via commonly used tests: Morris water maze test, novel object recognition, elevated plus maze test, and tail suspension test. Furthermore, evidence for ROS generation in the brain was assessed using glutathione S-transferase assay. PCN demonstrated BBB permeability albeit in minute quantities. A significant hike was observed in ROS generation (

P
<
0.0001

) along with changes in behavior indicating PCN permeability across BBB and potentially affecting cognitive functions. This is the first study exploring the potential role of PCN in influencing the cognitive functions of test animals.
Healthcare Big Data Privacy Protection Model Based on Risk-Adaptive Access Control
Authors: Jiang Rong , Han Shanshan , Shi Mingyue , Gao Tilei , Zhao Xusheng
Published: March 2022

Edge computing is playing an increasingly important role in the field of health care. Edge computing provides high-quality personalized services to patients based on user and device data information. However, edge nodes will collect a large amount of sensitive patient information, and patients will also bear the risk of privacy disclosure while enjoying personalized services. How to reduce the risk of privacy disclosure while ensuring that patients enjoy personalized services brought by edge computing is the research content of this paper. In this paper, the work flow and management mode of Hospital Information System (HIS) are investigated on the spot, and the risk-adaptive access control model based on entropy is established. First, we use International Classification of Diseases, Tenth Revision (ICD-10) to mark the information resources accessed by users and use information entropy to measure the correlation “α” between medical information accessed by users and work tasks. Finally, we analyze the relationship between correlation “α” and risk through an example. The results show that users with high correlation α have low risk of access behavior, and users with low risk have high correlation α of access information resources and work goals. This discovery can help managers predict users’ access behavior in the Big Data environment, so as to dynamically formulate access control policies according to the actual access situation of users and then realize the privacy protection of medical big health data.
Order Management and Completion Date Prediction of Manufacturing Job-Shop Based on Deep Learning
Authors: Wang Mei
Published: March 2022

To cope with the volatility of customer order demand, enterprises need to formulate a reasonable production plan based on customer demand for the completion period and their current manufacturing capacity. The existing studies have not fully considered the complex processing procedures, the features of manufacturing attributes, and the repetitive orders of stable consumers. To solve these problems, this paper explores the order management and completion date prediction of manufacturing job-shop based on deep learning. Specifically, the features of manufacturing attributes were extracted and used to predict the activities and completion time of different manufacturing tasks in order management. In addition, a deep learning prediction model was constructed based on a bidirectional long short-term memory network (BiLSTM) and self-attention mechanism, which completes the order management and completion date prediction.
Mobile Performance Intelligent Evaluation of IoT Networks Based on DNN
Authors: Tang Zhen , Fu Xiaobin , Xiao Pingping
Published: March 2022

The rapid development of the sensor equipment has promoted the rapid growth of the Internet of Things (IoT). The IoT has been widely employed in the multidimensional signal processing and gradually formed the IoT networks. Mobile communication promotes the wide application of the IoT networks. In this study, the transmit antenna selection (TAS) scheme is employed to investigate the average symbol error probability (ASEP) performance of mobile IoT networks over the 2-Rayleigh channels. We first employ moment-generating function (MGF) approach to derive the exact ASEP expressions. We also investigate the outage probability (OP) performance and derive OP expressions. Employing the deep neural network (DNN), an OP intelligent prediction algorithm is proposed. Then, the numerical simulations are conducted to confirm the ASEP and OP performance analysis. The effect of different channel parameters is also analyzed. Compared with Nakagami and Rayleigh channel models, the 2-Rayleigh model has 83.6% and 59.1% increase in ASEP values, respectively. Compared with ELM and RBF models, the DNN model has 31.7% and 22.5% increase in OP prediction accuracy, respectively.
A Systematic Review and Meta-Analysis of Tai Chi Training in Cardiorespiratory Fitness of Elderly People
Authors: Tan Tianyang , Meng Yanyan , Lyu Jiaxuan L , Zhang Chaoyang , Wang Chengchao , Liu Meng , Zhao Xirui , Lyu Tianyi , Wei Yulong
Published: March 2022

Objectives. The purpose of this study was to investigate the influence of Tai Chi on cardiorespiratory fitness (CRF) in elderly people using meta-analysis. Methods. This study used seven electronic databases and data retrieved from randomized controlled trials (RCTs) investigating the role of Tai Chi on CRF in the elderly. All these 24 RCTs were screened and selected from 7 literature databases. The Stata 11.2 software (StataCorp, USA) was used for the meta-analysis, subgroup analysis, and bias test, while the Cochrane Collaboration’s tool was used for the assessment of the risk of bias (RoB). 4 researchers independently participated in sample selection, data extraction, and RoB assessment. Results. Following the inclusion criteria, 24 eligible studies were included in our analysis. The meta-analysis indicated that Tai Chi practice significantly increased the maximum rate of oxygen consumption (VO2 max) (weighted mean difference (WMD)  = 3.76, 95% CI: 1.25 to 6.26,

P
<
0.1

), leading to an overall reduction in the heart rate (HR) (WMD  = −1.84, 95% CI: −2.04 to −1.63,

P
 
≤
0.001

) and an increase in the O2 pulse (WMD = 0.94, 95% CI: 0.60 to 1.28,

P
≤
0.001

) in individuals who practiced Tai Chi regularly compared with those who did not. The subgroup analysis suggested that overall in those who practiced Tai Chi, males (WMD = 1.48, 95% CI: 0.85 to 2.12,

P
≤
0.001

) had higher O2 pulse than females (WMD = 0.73, 95% CI: 0.33 to 1.12,

P
≤
0.001

). The subgroup analysis also showed an increase in the vital capacity (VC) (WMD = 316.05, 95% CI: 239.74 to 392.35,

P
≤
0.001

) in individuals practicing Tai Chi. When the samples were further stratified by Tai Chi practicing time, the subgroup analysis suggested that individuals practicing Tai Chi over a period of 24 weeks showed no significant difference in VC (WMD = 82.95, 95% CI: -98.34 to 264.23,

P
=
0.370

), while those practicing Tai Chi over a period of 48 weeks showed a significant increase (WMD = 416.62, 95% CI: 280.68 to 552.56,

P
≤
0.001

). Furthermore, the subgroup analysis demonstrated that the increase in VC is significantly correlated with the Tai Chi practicing time (WMD = 344.97, 95% CI: 227.88 to 442.06,

P
≤
0.001

). Conclusion. Regular Tai Chi practice could improve the CRF in the elderly, as indicated by significant improvement in indicators including VO2max, O2pulse, VC, and HR. However, gender and practice time might influence the overall beneficial outcomes.
K-Means Segmentation of Underwater Image Based on Improved Manta Ray Algorithm
Authors: Zhu Donglin , Xie Linpeng , Zhou Changjun
Published: March 2022

Image segmentation plays an important role in daily life. The traditional K-means image segmentation has the shortcomings of randomness and is easy to fall into local optimum, which greatly reduces the quality of segmentation. To improve these phenomena, a K-means image segmentation method based on improved manta ray foraging optimization (IMRFO) is proposed. IMRFO uses Lévy flight to improve the flexibility of individual manta rays and then puts forward a random walk learning that prevents the algorithm from falling into the local optimal state. Finally, the learning idea of particle swarm optimization is introduced to enhance the convergence accuracy of the algorithm, which effectively improves the global and local optimization ability of the algorithm simultaneously. With the probability that K-means will fall into local optimum reducing, the optimized K-means hold stronger stability. In the 12 standard test functions, 7 basic algorithms and 4 variant algorithms are compared with IMRFO. The results of the optimization index and statistical test show that IMRFO has better optimization ability. Eight underwater images were selected for the experiment and compared with 11 algorithms. The results show that PSNR, SSIM, and FSIM of IMRFO in each image are better. Meanwhile, the optimized K-means image segmentation performance is better.
A Novel Modeling Technique for the Forecasting of Multiple‐Asset Trading Volumes: Innovative Initial‐Value‐Problem Differential Equation Algorithms for Reinforcement Machine Learning
Authors: Al Janabi Mazin A. M.
Published: March 2022

Liquidity risk arises from the inability to unwind or hedge trading positions at the prevailing market prices. The risk of liquidity is a wide and complex topic as it depends on several factors and causes. While much has been written on the subject, there exists no clear‐cut mathematical description of the phenomena and typical market risk modeling methods fail to identify the effect of illiquidity risk. In this paper, we do not propose a definitive one either, but we attempt to derive novel mathematical algorithms for the dynamic modeling of trading volumes during the closeout period from the perspective of multiple‐asset portfolio(s), as well as for financial entities with different subsidiary firms and multiple agents. The robust modeling techniques are based on the application of initial‐value‐problem differential equations technique for portfolio selection and risk management purposes. This paper provides some crucial parameters for the assessment of the trading volumes of multiple‐asset portfolio(s) during the closeout period, where the mathematical proofs for each theorem and corollary are provided. Based on the new developed econophysics theory, this paper presents for the first time a closed‐form solution for key parameters for the estimation of trading volumes and liquidity risk, such as the unwinding constant, half‐life, and mean lifetime and discusses how these novel parameters can be estimated and incorporated into the proposed techniques. The developed modeling algorithms are appealing in terms of theory and are promising for practical econophysics applications, particularly in developing dynamic and robust portfolio management algorithms in light of the 2007–2009 global financial crunch. In addition, they can be applied to artificial intelligence and machine learning for the policymaking process, reinforcement machine learning techniques for the Internet of Things (IoT) data analytics, expert systems in finance, FinTech, and within big data ecosystems.
Analysis of a Kind of Harr Characteristic Big Data Algorithm for College Students’ Safety Education Method
Authors: Wei Li
Published: March 2022

In order to improve the effectiveness of safety education in colleges and universities and to maintain the long-term effectiveness of college students’ safety awareness, combined with the current safety problems in colleges and universities, by analyzing the relevance of campus safety accidents and safety education, a Harr characteristic big data algorithm for college students is proposed. Safety education methods have constructed a safety education system for college students. The status quo of safety education is analyzed for college students, a safety education system image acquisition module is designed based on Harr characteristic big data algorithm, Harr characteristic big data algorithm and Adaboost algorithm are used to shorten the training time of college students’ safety education image, learning resources are saved, and remote teaching is realized. A set of safety knowledge question banks based on recommendation algorithm has developed a set of practical safety knowledge online learning and testing systems, and targeted solutions to prevent and reduce campus safety accidents are proposed. The experimental results show that the number of student safety incidents in the school within 1 year after the application of this system is significantly reduced to 58, the system’s experimental response time is only 0.05 s on average, and the student’s satisfaction with the system reaches 93%. The application effect of the system is obvious, and it can effectively prevent and reduce the occurrence of campus safety accidents.
A Renovated CNN-Based Model Enhances KGC Task Performance
Authors: Miao Fang , Wang Xueting , Feng Feng , Jin Cong , Jin Libiao
Published: March 2022

Knowledge graph (KG) contains a large number of real-world knowledge and has become an invaluable aid to assist the application of artificial intelligence. Knowledge graph completion (KGC) is the task to complete the missing triple in KG database. Our goal in this study is to enhance the performance of KGC tasks based on CNN model. To do this, we first investigated the effect of adding multiple filters of different shapes into the pioneer model. The obscure improvement leads us to seek other approaches. Our second proposed model, termed DP-ConvKB, which is a deep convolution-neural-network-based model, outperforms state-of-the-art models on several metrics. Our study provides supporting evidence that, by cooperating deep pyramid network structure into models, it can significantly improve the KGC performances.
Cross-Cultural Adaptation and Reliability of the Home Falls and Accidents Screening Tool (HOME FAST) in Assessing Fall-Risk Home Hazards for Stroke Using Technologies over a Conventional Home Visit
Authors: Ahmad Ainuddin Husna , Romli Muhammad Hibatullah , Hamid Tengku Aizan , Salim Mazatulfazura S. F. , Mat Din Hazwan , Mackenzie Lynette
Published: March 2022

Objective. This study is aimed at translating the Home Falls and Accidents Screening Tool (HOME FAST) into the three main languages spoken in Malaysia and investigating its reliability through an alternative technology-based evaluation. Methods. Translation into three languages and cross-cultural adaptation of the HOME FAST was conducted via the five steps adopted from the Mapi Institute. For interrater reliability, occupational therapists who attended a face-to-face home hazard workshop were recruited. Each therapist rated the HOME FAST by using the provided combination of videos and photographs of stroke survivors manoeuvring in their home. For test-retest reliability, the same occupational therapists were invited to rate the same combination of photographs and videos again. Reliability was analysed using Gwet’s

A

C

1

and Bland and Altman’s plot to describe agreement. Results. The translation challenges were minimal and rectifiable. A Bahasa Melayu, Mandarin, and Tamil versions of the HOME FAST were developed. Overall interrater reliability for both video (

A

C

1

=
0.91

) and photograph (

A

C

1

=
0.91

) were good. The test-retest reliability yielded similar outcome (video: overall

A

C

1

=
0.92

and photograph: overall

A

C

1

=
0.93

). Conclusion. Using alternative technology (video and photograph) to do a home hazard assessment was feasible. However, the asynchronous nature of these methods has limitations in clarifying certain aspects in the home. Moving forward, potential investigation on other technologies such as telehealth for synchronous and real-time interaction is warranted.
Circ_0078767 Inhibits the Progression of Non-Small-Cell Lung Cancer by Regulating the GPX3 Expression by Adsorbing miR-665
Authors: Liu Xiting , Chen Ze , Wu Yuqiang , Gu Feng , Yan Dong , Yang Lei , Ma Qin , Fu Caihong
Published: March 2022

Non-small-cell lung cancer (NSCLC) is one of the most serious cancers. The circular RNA_0078767 (circ_0078767) expression was decreased in NSCLC tissues. However, the molecular mechanism of circ_0078767 remains unknown. The expression of circ_0078767, microRNA-665 (miR-665), and glutathione peroxidase 3 (GPX3) was detected by quantitative real-time fluorescence polymerase chain reaction (qRT-PCR). Cell proliferation, migration, and invasion were detected by colony formation assay and transwell assay, respectively. The lactate production and glucose consumption were tested by glycolysis. Western blot examined the protein levels of hexokinase-2 (HK2), matrix metalloproteinase-9 (MMP9), and GPX3 cells. Circinteractome predicted the relationship between miR-665 and circ_0078767 or GPX3 and was verified by dual luciferase reporter assays. The xenotransplantation model was established to study the role of circ_0078767 in vivo. The expression of circ_0078767 and GPX3 was decreased in NSCLC tissues, while the expression of miR-665 was increased. Circ_0078767 can sponge miR-665, and GPX3 is the target of miR-665. In vitro complement experiments showed that knockdown of circ_0078767 significantly promoted malignant behavior of NSCLC, while cotransfection of miR-665 inhibitor partially reduced this change. In addition, the GPX3 overexpression decreased the promoting effects of miR-665 upregulation on proliferation, migration, and invasion of NSCLC cells. Mechanically, circ_0078767 regulates the GPX3 expression in NSCLC cells by spongy miR-665. In addition, in vivo studies have shown that downregulation of circ_0078767 promotes tumor growth. Circ_0078767 silencing promotes proliferation, migration, invasion, and glycolysis of NSCLC cells by regulating the miR-665/GPX3 axis, suggesting that circ_0078767/miR-665/GPX3 axis may be a potential regulatory mechanism for the treatment of NSCLC.
The Potential Prognostic Value of Dual-Imaging PET Parameters Based on 18F-FDG and 18F-OC for Neuroendocrine Neoplasms
Authors: Hou Jiale , Long Tingting , Yang Yi , Chen Dengming , Hu Shuo
Published: March 2022

Background. To identify parameters based on dual-imaging 18F-AlF-NOTA-octreotide (18F-OC) and 18-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) for predicting the prognosis of neuroendocrine neoplasms (NENs). Materials and Methods. Sixty-six patients (age: [Formula: see text] (SD): [Formula: see text] years) who underwent both 18F-OC and 18F-FDG PET/CT imaging were enrolled in our retrospective study. The following PET parameters were measured: the maximum standardized uptake value (SUVmax) and the volumetric parameters—18F-OC SSR-derived tumor volume (TV) and somatostatin receptor expression (SRE, TV multiplied by the mean standardized uptake value (SUVmean)) and the 18F-FDG-derived multiple tumor volume (MTV) and tumor lesion glycolysis (TLG). The NETPET grade based on dual-imaging PET images was assessed. Progression-free survival (PFS) was set as an endpoint. Univariate and multivariate survival analyses were performed for PET parameters and clinical tumor data. Results. In the univariate survival analyses of clinical information, PFS was significantly associated with age (>45.5 vs ≤45.5, years, [Formula: see text]) and the presence of bone metastases ([Formula: see text]). Higher values for the 18F-FDG and 18F-OC volumetric parameters and the NETPET grade were adverse factors for PFS according to the dual-imaging PET parameters. In the multivariate survival analysis, the NETPET grade and SRE were predictors of PFS in NEN patients. Conclusion. The NETPET grade is a potential noninvasive prognostic biomarker for NENs.
Estimation Based on Adaptive Progressively Censored under Competing Risks Model with Engineering Applications
Authors: Nassar Mazen , Alotaibi Refah , Dey Sanku
Published: March 2022

This paper has investigated the estimation problem for the competing risks model where the data are adaptive progressively type-II censored and follow the Rayleigh distribution. Maximum likelihood and Bayesian methods are used to estimate the unknown parameters. To generate the interval estimates of the model parameters, approximate confidence intervals and two bootstrap confidence intervals are also considered based on the classical setup. Bayes estimates are obtained using independent gamma priors based on various loss functions including squared error, LINEX, general entropy, weighted SE, and precautionary loss functions. Moreover, Bayes credible intervals and the highest posterior density intervals of the model parameters are obtained. A numerical investigation has been carried out to assess the performance of the classical and Bayes estimates as well as the associated confidence and credible intervals. Finally, one simulated and two real data sets, one for breaking strengths of wire connections and the other for times to failure of small electrical appliances, have been analyzed for illustrative purposes. The results showed that the Bayes estimates using the LINEX loss function provide more reasonable estimates than the classical and Bayes estimates using squared error, general entropy, and precautionary loss functions.
COVID-19 in Emerging Countries and Students’ Intention to Use Cloud Classroom: Evidence from Thailand
Authors: Chaveesuk Singha , Chaiyasoonthorn Wornchanok
Published: March 2022

In many emerging markets, collectivist culture promotes interpersonal relationships which entail sharing both work and personal lives with one other. Nevertheless, the ubiquity of the World Wide Web has provided massive opportunities to teachers and learners around the globe to share knowledge anytime anywhere via online education. It is against this background that this study explores the perceptions of IT students in adopting virtual learning system in higher education institutes in an emerging country context under the COVID-19. We extended Davis’s (1989) Technology Acceptance Model (TAM) and evaluated students’ intention to use cloud classroom. Data were obtained from the five universities IT students in Bangkok, Thailand. Using partial least square structure equation modeling (PLS-SEM), the data of 373 IT students were analyzed. The findings of the research show that all hypotheses were supported, except one that was related to the positive impact of perceived usefulness on students’ intention to use cloud classroom. The extended TAM model explains 51.6% variance to explain students’ intention to use cloud classroom. The result of this study has useful implications for educationists and strategists related to the effectiveness and usability of cloud classroom in higher education institutions.
Association between Serum Trace Elements Levels, Steroid Concentrations, and Reproductive Disorders in Ewes and Does
Authors: Derar Derar , Ali Ahmed , Almundarij Tariq , Abd-Elmoniem Essam , Alhassun Tamim , Zeitoun Moustafa
Published: March 2022

This study aimed to investigate the association of different reproductive disorders with the status of serum trace elements and steroid hormones in ewes and goats. This study included 131 barren and 11 fertile (control) ewes and 94 barren and 9 fertile (control) goats. Animals were examined gynecologically for reproductive soundness. The animals were bled, and their serum was harvested and assayed for manganese (Mn), selenium (Se), iron (Fe), zinc (Zn), estrogen (E2), and progesterone (P4) levels. The results showed that genital affections were associated with significant changes in serum Se (P=0.001), Fe (P=0.008), and Zn (P=0.01) levels in ewes, as well as Mn (P=0.01) levels in goats. Ewes and goats with cystic ovaries had higher serum Se, Fe, and Zn levels (P=0.0001) than ewes with uterine affections, ovarian inactivity, and controls. Ovarian inactivity was linked to low Se levels in ewes and low Se and Zn levels in goats (P=0.05). Ewes and goats with estrogen-dominant reproductive disorders had higher Se (P=0.01), Fe (P=0.03), and Zn (P=0.01) compared with the control group. Se (P=0.02) and Zn (P=0.05) were lower in ewes and goats affected with P4-dominant genital disorders compared with the control group. It can be concluded that the reproductive disorders are associated with changes in the level of trace elements in blood of ewes and goats. There is a reciprocal relationship between the levels of estrogen and progesterone with those of the trace elements in serum of ewes and goats.
Assessing Neonatal Pain with NIPS and COMFORT-B: Evaluation of NICU’s Staff Competences
Authors: Sarkaria Eliza , Gruszfeld Dariusz
Published: March 2022

Background. Pain is considered “the 5th vital sign” that should be regularly assessed in the neonatal intensive care setting. Although over 40 pain assessment tools have been developed for neonates, their implementation in everyday practice is challenging. Epidemiological studies demonstrate that pain is still underassessed and undertreated in European NICUs. Purpose. To evaluate the interrater and intrarater reliability of the NIPS and COMFORT-B scales among the tertiary NICU’s staff members 4 years after their implementation in local pain guidelines with no prior dedicated training. Methods. Physicians and nurses were invited to evaluate 5 video recordings of infants hospitalized in the intensive care settings, using the NIPS and COMFORT-B scales. The assessment took part twice at a 3-month interval. Interrater reliability was calculated for both scales using Kendall’s W coefficient of concordance and Krippendorff’s alpha coefficient. Cohen’s kappa was used to assess intrarater reliability. Results. 17 physicians and 19 nurses took part in the study. Interrater agreement for the COMFORT-B scale was above 0.8 for Kendall’s W coefficient (p < .01) and above 0.667 for Krippendorff’s alpha coefficient. Kendall’s W coefficient for the NIPS scores ranged between 0.7 and 0.8 (p < .01). Krippendorff’s alpha was above 0.667. Intrarater agreement for both the COMFORT-B and NIPS scales was 0.693 and 0.724, respectively. Conclusions. Overall, the agreement between our staff members was moderately good for both scales. This is not enough to avoid inadequate pain assessment. More training is needed to improve NICU’s staff competences in using pain scales.
Application of Fuzzy PID Position Control Algorithm in Motion Control System Design of Palletizing Robot
Authors: Xu Junjie , Xiao Long , Lin Muquan , Tan Xiaojing
Published: March 2022

In view of the low efficiency in traditional palletizing robot problem of poor control precision, this paper introduces fuzzy PID position control algorithm, based on the actual operation situation of palletizing robot; determined as palletizing robot FPGA hardware platform, hardware platform based on this fuzzy PID position control algorithm is applied to implement palletizing robot motion control system design. The simulation model of fuzzy PID motion control was established by MATLAB software for testing to determine that the fuzzy PID position control algorithm reflects the time quickly in the motion control of palletizing robot, and the actual overshooting is small, which is more suitable for the motion control algorithm of palletizing robot. Under this condition, the modular method is adopted to complete the system application design on the FPGA hardware platform.
Telepresence Robots at the Urology and Emergency Department: A Pilot Study Assessing Patients’ and Healthcare Workers’ Satisfaction
Authors: Laigaard Jens , Fredskild Trine Ungermann , Fojecki Grzegorz Lukasz
Published: March 2022

COVID-19 intensified interest in telemedicine, yet no study has evaluated the use of a telepresence robot on unselected urological patients. Therefore, we performed a survey study of patients, bedside caregivers and urologists, investigating the satisfaction and applicability of a telepresence robot (Beam Pro, Suitable Technologies, USA) at the urology ward and emergency department. The primary outcome was the number of patient encounters solved without the urologist’s physical presence. Between March 2021 and May 2021, patients, caregivers, and urologists filled in 42, 35, and 54 questionnaires, respectively. Most patients were male (79%), with a mean age of 64 (

SD
±
17

). Two of the department’s ten urologists participated. The urologists responded that physical examination was required in 7 (13%) encounters. The caregivers would have preferred the urologist physically present in 11 (31%) cases. Most patients (71%) “agreed” or “strongly agreed” that they were willing to be attended by a telepresence robot at future evaluations and generally, patients gave high satisfaction scores. Though implementation among the department’s urologists was a major challenge, participating urologists reported that physical presence could be avoided in 87% of the patient encounters. Studies of patient-reported outcome measures comparing telemedical and physical patient encounters are needed.