bluuebunny/crossref_metadata_2025 huggingface dataset:
Giuseppe Verdi
Authors: Andries Annelies
Published: August 2022

Liefde, eer, wraak: de passies laaien hoog op in Giuseppe Verdi’s eerste internationale hit, Ernani. Drie rivalen vechten om de hand van Elvira maar hun obsessies en manipulaties leiden enkel tot verbittering en dood. Het onderwerp ontleende Verdi aan Victor Hugo, wiens toneelstuk Hernani in 1830 een heuse esthetische oorlog ontketende over het bestaansrecht van het romantische theater. Op basis van de verhitte debatten in de theater- en operawereld van die tijd toont Annelies Andries hoe esthetische idealen botsten met de praktische vereisten van een operaproductie. De censuur verbood bepaalde politieke onderwerpen, zangers eisten dat hun stemmen zouden schitteren en het operahuis wilde een successtuk. Tenslotte illustreert de luistergids hoe Verdi in Ernani zijn dramaturgische en muzikale visies aanscherpte en zo de voedingsbodem legde voor zijn blijvende populariteit in het operalandschap.
Prokaryotic innate immunity through pattern recognition of conserved viral proteins
Authors: Gao Linyi Alex , Wilkinson Max E. , Strecker Jonathan , Makarova Kira S. , Macrae Rhiannon K. , Koonin Eugene V. , Zhang Feng
Published: August 2022

Many organisms have evolved specialized immune pattern-recognition receptors, including nucleotide-binding oligomerization domain–like receptors (NLRs) of the STAND superfamily that are ubiquitous in plants, animals, and fungi. Although the roles of NLRs in eukaryotic immunity are well established, it is unknown whether prokaryotes use similar defense mechanisms. Here, we show that antiviral STAND (Avs) homologs in bacteria and archaea detect hallmark viral proteins, triggering Avs tetramerization and the activation of diverse N-terminal effector domains, including DNA endonucleases, to abrogate infection. Cryo–electron microscopy reveals that Avs sensor domains recognize conserved folds, active-site residues, and enzyme ligands, allowing a single Avs receptor to detect a wide variety of viruses. These findings extend the paradigm of pattern recognition of pathogen-specific proteins across all three domains of life.
Deep-learning seismology
Authors: Mousavi S. Mostafa , Beroza Gregory C.
Published: August 2022

Seismic waves from earthquakes and other sources are used to infer the structure and properties of Earth’s interior. The availability of large-scale seismic datasets and the suitability of deep-learning techniques for seismic data processing have pushed deep learning to the forefront of fundamental, long-standing research investigations in seismology. However, some aspects of applying deep learning to seismology are likely to prove instructive for the geosciences, and perhaps other research areas more broadly. Deep learning is a powerful approach, but there are subtleties and nuances in its application. We present a systematic overview of trends, challenges, and opportunities in applications of deep-learning methods in seismology.
The evolutionary network of whiptail lizards reveals predictable outcomes of hybridization
Authors: Barley Anthony J. , Nieto-Montes de Oca Adrián , Manríquez-Morán Norma L. , Thomson Robert C.
Published: August 2022

Hybridization between diverging lineages is associated with the generation and loss of species diversity, introgression, adaptation, and changes in reproductive mode, but it is unknown when and why it results in these divergent outcomes. We estimate a comprehensive evolutionary network for the largest group of unisexual vertebrates and use it to understand the evolutionary outcomes of hybridization. Our results show that rates of introgression between species decrease with time since divergence and suggest that species must attain a threshold of evolutionary divergence before hybridization results in transitions to unisexuality. Rates of hybridization also predict genome-wide patterns of genetic diversity in whiptail lizards. These results distinguish among models for hybridization that have not previously been tested and suggest that the evolutionary outcomes can be predictable.
Insurance-sector tools to combat biodiversity loss
Authors: Kousky Carolyn
Published: August 2022

Risk transfer can facilitate nature-positive investments
Our rhythmic existence
Life Time
Russell Foster
Yale University Press, 2022. 480 pp.
Authors: Torres Manon , Kramer Achim
Published: August 2022

A neuroscientist interrogates sleep and circadian clocks
Longevity lessons
Methuselah’s Zoo: What Nature Can Teach Us About Living Longer, Healthier Lives
Steven N. Austad
MIT Press, 2022. 320 pp.
Authors: Brenner Charles
Published: August 2022

Animal aging could hold clues to healthier human life spans
In Science Journals
Authors: Lopez Bianca , Vinson Valda , Suleymanov Yury , Osborne Ian S. , Lavine Marc S. , Foley John F. , Aldenderfer Mark , Jiang Di , Hines Pamela J. , Yeston Jake , Vignieri Sacha , Grocholski Brent , Erkes Dan A. , Norton Melissa
Published: August 2022

Highlights from the
Science
family of journals
Harassment researchers decry proposed reporting rule
Authors: Langin Katie
Published: August 2022

U.S. Title IX law update requiring mandatory reporting of sexual misconduct would cause harm, they say
Metabolic Strategies Shared by Basement Residents of the Lost City Hydrothermal Field
Authors: Brazelton William J. , McGonigle Julia M. , Motamedi Shahrzad , Pendleton H. Lizethe , Twing Katrina I. , Miller Briggs C. , Lowe William J. , Hoffman Alessandrina M. , Prator Cecilia A. , Chadwick Grayson L. , Anderson Rika E. , Thomas Elaina , Butterfield David A. , Aquino Karmina A. , Früh-Green Gretchen L. , Schrenk Matthew O. , Lang Susan Q.
Published: August 2022

The Lost City hydrothermal field is an iconic example of a microbial ecosystem fueled by energy and carbon from Earth’s mantle. Uplift of mantle rocks into the seafloor can trigger a process known as serpentinization that releases molecular hydrogen (H
2
) and creates unusual environmental conditions where simple organic carbon molecules are more stable than dissolved inorganic carbon.
The Emergence, Diversification, and Transmission of Subgroup J Avian Leukosis Virus Reveals that the Live Chicken Trade Plays a Critical Role in the Adaption and Endemicity of Viruses to the Yellow-Chickens
Authors: Deng Qiaomu , Li Qiuhong , Li Min , Zhang Shengbin , Wang Peikun , Fu Fumei , Zhu Weiyu , Wei Tianchao , Mo Meilan , Huang Teng , Zhang Huanmin , Wei Ping
Published: August 2022

Although the general epidemiology of ALV-J is well studied, the ongoing evolutionary and transmission dynamics of the virus remain poorly investigated. The phylogenetic differences and relationship of the clades and subclades were characterized, and the epidemics and factors driving the geographical spread and inter-host transmission of different ALV-J clades were explored for the first time.
Highly Variable Expression of Merozoite Surface Protein MSPDBL2 in Diverse Plasmodium falciparum Clinical Isolates and Transcriptome Scans for Correlating Genes
Authors: Hocking Suzanne E. , Stewart Lindsay B. , Freville Aline , Reid Adam J. , Tarr Sarah J. , Tetteh Kevin K. A. , Flueck Christian , Ahouidi Ambroise D. , Amambua-Ngwa Alfred , Diakite Mahamadou , Awandare Gordon A. , Conway David J.
Published: August 2022

These findings contribute to understanding malaria parasite antigenic and developmental variation, focusing on the merozoite surface protein encoded by the single locus under strongest balancing selection. Analyzing the initial
ex vivo
generation of parasites grown from a wide sample of clinical infections, we show a unique and highly skewed pattern of natural expression frequencies of MSPDBL2, distinct from that of any other antigen.
Draft Genome Sequence of the Extremely Haloalkaliphilic and Homoacetic Bacterium Natroniella acetigena Z-7937
T
Authors: Huang Yan , Nobu Masaru K. , Igarashi Kensuke , Kato Souichiro
Published: August 2022

Natroniella acetigena
Z-7937
T
(= DSM 9952
T
) is a heterotrophic homoacetogenic natronophile. The draft genome sequence is 2.6 Mb in 116 contigs, with a G+C content of 34.1%.
The HPV Induced Cancer Resource (THInCR): a Suite of Tools for Investigating HPV-Dependent Human Carcinogenesis
Authors: Salnikov Mikhail , Gameiro Steven F. , Zeng Peter Y. F. , Barrett John W. , Nichols Anthony C. , Mymryk Joe S.
Published: August 2022

The suite of analytical tools of THInCR provides the opportunity to investigate the roles that candidate target genes identified in cell lines or other model systems contribute to in actual HPV-dependent human cancers and is based on large-scale TCGA data sets. Expression of target genes, including both mRNA and microRNA, can be correlated with HPV gene expression, epigenetic changes in DNA methylation, patient survival, and numerous immune features, like leukocyte infiltration, interferon gamma response, T cell response, etc.
Biofilm Formation and Structure in the Filamentous Fungus Fusarium graminearum, a Plant Pathogen
Authors: Shay Rebecca , Wiegand Aaron A. , Trail Frances
Published: August 2022

Fusarium graminearum
is a filamentous fungal pathogen that causes
Fusarium
head blight (FHB) in cereal crops, leading to devastating crop losses. We have demonstrated the ability of this pathogen to form biofilms.
Dynamic Changes in the Gut Microbial Community and Function during Broiler Growth
Authors: Yang Maosen , Shi Lianzhe , Ge Yile , Leng Dong , Zeng Bo , Wang Tao , Jie Hang , Li Diyan
Published: August 2022

The intestinal microbiota has a certain impact on the performance of broilers. However, the change of intestinal microbiota after 4 weeks of age is not clear, and the mechanism of the effect of microorganisms on the weight change of broilers needs more exploration.
Supplemental Material: Don’t judge an orogen by its cover: Kinematics of the Appalachian décollement from seismic anisotropy
Authors: Frothingham Michael , al. et
Published: August 2022

Digitized structural attitudes from the Greenville 1x2° quadrangle (Nelson et al., 1998) and accompanying stereonets, CCP stacks and accompanying A1 trace profiles from SESAME D-W-lines, as well as a table of receiver function A1 arrivals with accompanying worked example and waveform plots.  
Plastics as a carrier of chemical additives to the Arctic: possibilities for strategic monitoring across the circumpolar North
Authors: Hamilton Bonnie M. , Baak Julia E. , Vorkamp Katrin , Hammer Sjúrður , Granberg Maria , Herzke Dorte , Provencher Jennifer F.
Published: August 2022

Plastic pollution (including microplastics) has been reported in a variety of biotic and abiotic compartments across the circumpolar Arctic. Due to their environmental ubiquity, there is a need to understand not only the fate and transport of physical plastic particles, but also the fate and transport of additive chemicals associated with plastic pollution. Further, there is a fundamental research gap in understanding long-range transport of chemical additives to the Arctic via plastics as well as their behavior under environmentally relevant Arctic conditions. Here, we comment on the state of the science of plastic as carriers of chemical additives to the Arctic, and highlight research priorities going forward. We suggest further research on the transport pathways of chemical additives via plastics from both distant and local sources and laboratory experiments to investigate chemical behavior of plastic additives under Arctic conditions, including leaching, uptake, and bioaccumulation. Ultimately, chemical additives need to be included in strategic monitoring efforts to fully understand the contaminant burden of plastic pollution in Arctic ecosystems.
Factors influencing black spruce reproductive potential in the northern boreal forest of Quebec
Authors: Splawinski Tadeusz B. , Boucher Yan , Bouchard Mathieu , Greene David F. , Gauthier Sylvie , Auger Isabelle , Sirois Luc , Valeria Osvaldo , Bergeron Yves
Published: August 2022

The reproductive ecology of the semi-serotinous species black spruce ( Picea mariana (Mill.) BSP) in northern boreal forests remains poorly understood. There is a general lack of data on cone/seed production and viability as a function of biotic tree-level characteristics and abiotic variables. No studies currently exist to quantify these differences over a large gradient in temperature, elevation, and precipitation. Extensive physical, ecological, dendrometric, and reproductive data were collected from young to very old black spruce stands in northern Quebec. ANOVA and general linear mixed models were used to examine interannual cone production, and the relative importance of the biotic and abiotic explanatory factors in determining total cone production; length of the cone-bearing zone; filled seeds per cone; proportion of filled seeds; and seed viability. The results illustrate that the reproductive ecology of black spruce in northern cold forests is mainly explained by biotic variables such as age and diameter at breast height, and by abiotic variables related to temperature such as elevation, length of the growing season, and growing degree-days. Black spruce exhibits a lower reproductive potential in northern cold forests, making it possibly less resilient to increased fire frequency, particularly in unproductive and very young or very old stands.
Six months of unsupervised exercise training lowers blood pressure during moderate, but not vigorous, aerobic exercise in adults with well-healed burn injuries
Authors: Watso Joseph C. , Romero Steven A. , Moralez Gilbert , Huang Mu , Cramer Matthew N. , Johnson Elias , Crandall Craig G.
Published: August 2022

Adults with well-healed burn injuries have greater cardiovascular disease morbidity and all-cause mortality compared with nonburn-injured adults. We found that exercise training reduced blood pressure (BP) during fixed-load cycling at 75 W and during moderate, but not vigorous, intensity cycling exercise in adults with well-healed burn injuries. These data suggest that 6 mo of unsupervised exercise training provides some degree of cardioprotection by reducing BP responses during submaximal exercise in well-healed burn-injured adults.
Age-related performance fatigability: a comprehensive review of dynamic tasks
Authors: Paris Michael T. , McNeil Chris J. , Power Geoffrey A. , Rice Charles L. , Dalton Brian H.
Published: August 2022

Adult aging is associated with a myriad of changes within the neuromuscular system, leading to reductions in contractile function of old adults. One of the consequences of these age-related neuromuscular adaptations is altered performance fatigability, which can limit the ability of old adults to perform activities of daily living. Whereas age-related fatigability during isometric tasks has been well characterized, considerably less is known about fatigability of old adults during dynamic tasks involving movement about a joint, which provides a more functionally relevant task compared with static contractions. This review provides a comprehensive summary of age-related fatigability during dynamic contractions, where the importance of task specificity is highlighted with a brief discussion of the potential mechanisms responsible for differences in fatigability between young and old adults. The angular velocity of the task is critical for evaluating age-related fatigability, as tasks that constrain angular velocity (i.e., isokinetic) produce equivocal age-related differences in fatigability, whereas tasks involving unconstrained velocity (i.e., isotonic-like) consistently induce greater fatigability for old compared with young adults. These unconstrained velocity tasks, which are more closely associated with natural movements, offer an excellent model to uncover the underlying age-related mechanisms of increased fatigability. Future work evaluating the mechanisms of increased age-related fatigability during dynamic tasks should be evaluated using contraction modes that are specific to the task (i.e., dynamic), rather than isometric, particularly for the assessment of spinal and supra spinal components. Advancing our understanding of age-related fatigability is likely to yield novel insights and approaches for improving mobility limitations in old adults.
Physiological predictors of morbidity and mortality in COPD: the relative importance of reduced inspiratory capacity and inspiratory muscle strength
Authors: Phillips Devin B. , James Matthew D. , O’Donnell Conor D. , Vincent Sandra G. , Webb Katherine A. , de-Torres Juan P. , Neder J. Alberto , O’Donnell Denis E.
Published: August 2022

To our knowledge, this study is the first to show an independent association between low resting inspiratory capacity (IC) and, severe exertional dyspnea, exercise limitation, and increased mortality risk, after accounting for the severity of airway obstruction, inspiratory muscle strength, and diffusing capacity. These results support the use of resting IC as an important independent physiological biomarker closely linked to key clinical outcomes in COPD.
The physiological functions of human peroxisomes
Authors: Wanders Ronald J. A. , Baes Myriam , Ribeiro Daniela , Ferdinandusse Sacha , Waterham Hans R.
Published: August 2022

Peroxisomes are subcellular organelles that play a central role in human physiology by catalyzing a range of unique metabolic functions. The importance of peroxisomes for human health is exemplified by the existence of a group of usually severe diseases caused by an impairment in one or more peroxisomal functions. Among others these include the Zellweger spectrum disorders, X-linked adrenoleukodystrophy, and Refsum disease. To fulfill their role in metabolism, peroxisomes require continued interaction with other subcellular organelles including lipid droplets, lysosomes, the endoplasmic reticulum, and mitochondria. In recent years it has become clear that the metabolic alliance between peroxisomes and other organelles requires the active participation of tethering proteins to bring the organelles physically closer together, thereby achieving efficient transfer of metabolites. This review intends to describe the current state of knowledge about the metabolic role of peroxisomes in humans, with particular emphasis on the metabolic partnership between peroxisomes and other organelles and the consequences of genetic defects in these processes. We also describe the biogenesis of peroxisomes and the consequences of the multiple genetic defects therein. In addition, we discuss the functional role of peroxisomes in different organs and tissues and include relevant information derived from model systems, notably peroxisomal mouse models. Finally, we pay particular attention to a hitherto underrated role of peroxisomes in viral infections.
Reliability Analysis of Sports Training Evaluation Index Based on Random Matrix
Authors: Wei Chen , Jiang Meng
Published: August 2022

This paper presents an in-depth study and analysis of the reliability of indicators for the evaluation of sports training using the algorithm of random matrices. Random matrix theory is used to obtain the degree of randomness of the data and the overall correlation characteristics of the data through statistical analysis of the energy spectrum and eigenstates of complex systems. Using the results of random matrix theory on the eigenvalues of the sample covariance matrix, the energy of each subspace is estimated, and the estimated energy is then used to construct the subspace weighting matrix. The problem of reliable finite-time stability of the model under several types of uncertain time-lagged bounded transfer probability Markov jump parameter compatibility indicators is also explored. The four basic theoretical issues, namely, value orientation, construction basis, construction principles, and conceptual model of the sports training work evaluation index system, are studied. This paper takes the construction of a sports training evaluation index system as the research object and uses the literature method, expert interview method, questionnaire survey method, data analysis method, Delphi method, and hierarchical analysis method as the main research methods to construct a set of sports training evaluation index system as the research task, to enrich the idea of sports training evaluation work, and to provide a reference for the future government to be able to develop a sports training evaluation index system that is in line with the development of the times. The research method was used to collect the opinions of experts. The subjective opinions given by experts were collected using the assignment method, and the weight coefficients of each index were calculated using the AHP hierarchical analysis method. The result is that the index of basic conditions (0.3591) has the largest weight in the whole system. After that, organization and management (0.1911), work effectiveness (0.1376), staffing (0.103), activity development (0.0828), financial and fund management (0.0562), publicity and reporting (0.0382), and material provision (0.032) are in order. The evaluation results of the index system are consistent with the current actual situation of specialization teaching, indicating that the index system for evaluating the effectiveness of high school sports training has good validity.
Improved DV-Hop Algorithm Based on Swarm Intelligence for AI and IoT-Federated Applications in Industry 4.0
Authors: Zhang Lizhi
Published: August 2022

In the Internet of Things (IoT) ecosystem, localization is critical for tracking and monitoring targets via nodes. The distance vector-hop (DV-Hop) technique is a good choice for localizing neighborhood in IoT networks. The conventional DV-Hop algorithm is a distributed localization approach that does not consider the distribution of the nodes into full deliberation when calculating the hop count from the source to destined nodes. The transfer distance and node positions thus do not attain higher efficiency while ascertaining the distance between sources and destined nodes. The study aims to resolve the pitfalls in the traditional algorithm by making enhancements in controlling the original DV-Hop algorithm’s hop count and transfer distance method by utilizing the particle swarm to estimate the node positions. Error rate in the distance between beacon nodes and unseen nodes is effectively reduced with the proposed technique that calculate error factors with corrections in a reversed fashion to revise hop counts. An escape factor is introduced to take control of updating particles’ velocity in the system, and the inertia weight is defined by a piecewise function to enlarge search space. This mechanism increases the diversity of the particle populations and mitigates the tendency of estimations on node positions to be trapped into local optima under stationary state. Also, the improved DV-Hop algorithm described in the paper has a better convergence speed due to the presence of random inertia weight logarithmic method. Finally, the problem of premature convergence is also tackled as a variation factor is adopted in collaboration with a fitness function that affects the particles’ movement range and assists in global convergence. The overall performance of improved DV-Hop is evaluated by statistical metrics and also compared with the traditional DV-Hop algorithm under simulated environment with the data collected from real-world scenarios. Industry 4.0 is fully dependent upon IoT and the count of hops is very important for deciding the routing from the source to destination for speedy transmission of data. The improved DV-hop algorithm can achieve better results and has reduced error rate by more than 30%. The DV-Hop algorithm plays an important role in IoT-enabled environment especially in Industry 4.0.
Irreversible
k
-Threshold Conversion Number of Circulant Graphs
Authors: Shaheen Ramy , Mahfud Suhail , Kassem Ali
Published: August 2022

An irreversible conversion process is a dynamic process on a graph where a one-way change of state (from state 0 to state 1) is applied on the vertices if they satisfy a conversion rule that is determined at the beginning of the study. The irreversible

k

-threshold conversion process on a graph

G
=

V
,
E

is an iterative process which begins by choosing a set

S

0

⊆
V

, and for each step

t

t
=
1
,
2
,
⋯
,

,

S

t

is obtained from

S

t
−
1

by adjoining all vertices that have at least

k

neighbors in

S

t
−
1

.

S

0

is called the seed set of the

k

-threshold conversion process, and if

S

t

=
V

G

for some

t
≥
0

, then

S

0

is an irreversible

k

-threshold conversion set (IkCS) of

G

. The

k

-threshold conversion number of

G

(denoted by (

C

k

G

) is the minimum cardinality of all the IkCSs of

G
.

In this paper, we determine

C

2

G

for the circulant graph

C

n

1
,
r

when

r

is arbitrary; we also find

C

3

C

n

1
,
r

when

r
=
2
,
3

. We also introduce an upper bound for

C

3

C

n

1
,
4

. Finally, we suggest an upper bound for

C

3

C

n

1
,
r

if

n
≥
2

r
+
1

and

n
≡
0

mod
 
2

r
+
1

.
Automobile Rear Axle Health Monitoring Technology Based on Deep Learning
Authors: Zhang Quanyu , Zhang Zhenzhong , Ke Fengqin , Gao Yanan , Chen Yi
Published: August 2022

The rear axle is prone to fatigue fracture due to the complicated load impact throughout the vehicle’s service procedure. Real-time suspension health monitoring during operation is an excellent strategy for avoiding such situations. This paper takes the automobile rear axle as the research object and uses the deep learning model to study the rear axle health monitoring technology. A damage prediction model combining multi-Gaussian fitting and long-term and short-term memory neural network is proposed for automobile rear axle health monitoring. The feature extraction method based on multi-Gaussian fitting can obtain comprehensive power spectral density information with fewer feature parameters, which is conducive to improve the calculation efficiency. The LSTM model can accurately identify the fatigue damage value of the rear axle from the extracted characteristic information and ensure the high precision of the damage prediction results. Several deep learning-based comparison models are used to demonstrate that the GAPSD LSTM model has good prediction accuracy and computation efficiency at the same time. It has been proven that the GAPSD LSTM model can efficiently and accurately forecast the fatigue damage of the rear axle by comparing the damage prediction results of all deep learning models.
Multistage Framework for Automatic Face Mask Detection Using Deep Learning
Authors: K. N Sowmya , P. M Rekha , Kumari Trishala , Debtera Baru
Published: August 2022

The whole world is fighting as one against a deadly virus. COVID-19 cases are upon us in waves, with subsequent waves turning out to be worse than the previous one. Scores of human lives are lost while the post-COVID-19 complications are on a rise. Monitoring the behaviour of people in public places and offices is necessary to mitigate the transmission of COVID-19 among humans. In this work, a low-cost, lightweight two-stage face mask detection model is proposed. In the first stage, the model checks if a face mask is worn. In the second stage, it detects if the mask is worn appropriately, by classifying and labelling them. The proposed models are trained to detect faces with and without masks for varied inputs such as images, recorded videos, and live streaming videos where it can efficiently detect multiple faces at once. The efficacy of the proposed approach is tested against conventional datasets as well as our proposed dataset, which includes no masks, surgical masks, and nonsurgical masks. In this work, multiple CNN models like MobileNetV2, ResNet50V2, and InceptionV3 have been considered for training and are evaluated based on transfer learning. We further rely on MobileNetV2 as the backbone model since it has an accuracy of 98.44%.
Recycling of Iron Slag Waste in the Production of Ceramic Roof Tiles
Authors: Ahmed M. M. , El Naggar K. A. M. , Abadir M. F. , Abbas W. , Hamid E. M. Abdel
Published: August 2022

The merit of this study is manufacturing cheaper roof tiles using fluxed waste material such as granulated iron slag, in addition to the environmental benefit of decreasing the cost and negative impact of their disposal and landfilling. Waste water-cooled granulated iron slag was ground and added in proportions ranging from 0 to 30 wt.% to kaolin clay to prepare roof tiles for the economic purpose of decreasing the production cost by incorporating cheap waste and to serve sustainability. The raw materials were characterized by XRD, XRF, and particle size analysis. The specimens were shaped using a rectangular mould with dimensions of 150 × 30 × 30 mm3 under an axial pressure of 10 MPa and then dried in a dryer at 110°C. The firing of the dried specimens was carried out at 900, 1000, and 1100°C. The characteristics of fired specimens were determined by their linear firing shrinkage, water absorption, compressive strength, and freezing-thawing resistance. Results showed that samples containing 20% slag waste and fired at 1000°C displayed a cold water absorption of 12% and a saturation coefficient of 0.82, both values being lower than the maximum value recommended by standards. Also, the recorded breaking strength of 5040 N was much higher than the minimum standard value. These samples were also subjected to 50 freeze-thawing cycles, which they passed without the appearance of any cracks. It was concluded that samples containing 20% slag waste and fired to 1000°C or 1100°C fulfilled the requisites of ASTM C1167 for grade 3 normal duty roof tiles.
Preparation and Performance Analysis of Transformer Aramid Nanopaper-Based Insulating Material Based on Deep Learning
Authors: Liu Bowen , Lv Fangcheng , Fan Xiaozhou , Sui Yueyi , Wang Jiaxue , Yin Shengdong
Published: August 2022

Transformers are an essential part of power production. Insulating paper began to be widely used in transformers in the 1990s. The superior aramid nanofiber as the matrix gives the aramid nano-insulating paper excellent mechanical properties, insulation performance, temperature resistance, and flexibility. At first, the heat resistance and service life of insulating paper should be satisfied for use in electrical equipment. With the continuous development of power equipment, people have put forward higher requirements on the properties of insulating paper, especially heat resistance and electrical properties. Insulation paper made of aramid fibers have better thermal stability and more advantages in electrical and mechanical properties, which can significantly improve the service life and safety of electrical appliances. The purpose of this article is to study the use of aramid nanopaper-based insulating materials in transformers to explore the effect of transformer discharge mechanism on aramid nanopaper-based insulating materials. This paper proposes to design multiple deep learning models to identify the discharge mode of the voltage transformer, find the characteristic signal, and carry out related tests on the discharge signal of different modes, and find the maximum temperature value of the aramid nanopaper-based insulating material for industrial use. The experimental results in this paper show that the aramid nanopaper-based insulating material can be used in transformers discharge detection well, and the safety rate is increased by 20%.
English Teaching Evaluation Model Based on Association Rule Algorithm and Machine Learning
Authors: Yin Liwen , Xu Zhe
Published: August 2022

At present, Chinese colleges and universities have a clear understanding of the importance of teaching quality evaluation. They regard the evaluation of teaching quality as an important part of teaching management. This paper aims to study how to analyze and study English teaching evaluation based on association rule algorithm and machine learning and study the model. This paper raises the question of English teaching evaluation. This question is based on modelling studies. So it expounds the concepts and related algorithms of association rule algorithm and machine learning. This paper designs and analyzes a case study of the English teaching evaluation model. The experimental results show that taking a university as the empirical object for specific analysis, according to the evaluation system established in the research, the final score of the questionnaire is 89.2 points, and the English teaching evaluation result is a good grade.
Analysis of Affective Factors and Optimization Strategies of Emotion in Online Teaching Based on Improved SVM Model
Authors: Wu Hong , Huwan Trip
Published: August 2022

Online teaching has the advantages of not being limited by location and space but it also has some shortcomings. The lack of face-to-face real-time interaction between teachers and students will affect some students’ learning mood. The improved support vector machine (SVM) model is a simple model based on linear algebra, which can convert text data into structured data that can be processed by a computer and then calculate the similarity between two documents into the similarity between two vectors. The facial expression features of learners in the situation collected and extracted by the students of this project group are analyzed and modeled, and the time consumption, occupied space, and classification effect of the feature vectors produced by the improved model are integrated. The original feature dimension can be optimized from 100 dimensions to 60 dimensions, which not only saves the time of training feature vectors but also reduces the size of the final feature vectors. Besides, on the basis of 60-dimensional preliminary features extracted by SVM model, four classification models can also achieve the best results. Therefore, in the optimization part of feature extraction, the dimension of initial features extracted by SVM model is set to 60 dimensions. We can gradually use the improved SVM model to analyze the emotional influencing factors and optimization strategies in online teaching, so as to keep abreast of students’ lectures and let more students participate in online teaching as much as possible.
Efficacy of Risperidone Orally Disintegrating Tablets Combined with Oxazepam in the Treatment of Schizophrenia
Authors: Fang Liang , Xu Ying , Tong Xuefei , Wu Xue , Zhou Xiaomeng
Published: August 2022

Objective. To explore the efficacy of risperidone orally disintegrating tablets combined with oxazepam in the treatment of schizophrenia. Methods. From May 2019 to May 2021, 60 patients with schizophrenia treated in our hospital were recruited and assigned into an observation group (risperidone orally disintegrating tablets combined with oxazepam treatment) and a control group (alprazolam combined with chlorpromazine treatment) according to the random number table method. The positive and negative symptom score (PANSS), quality of life score (QOL-75), ability of daily living score (ADL), clinical efficacy, incidence of adverse reactions, and disease recurrence were compared between the two groups before and after treatment. Results. The PANSS scores were similar in the two groups before treatment (

P
>
0.05

). The two groups presented a declining trend in PANSS score after treatment, whereas a remarkable lower score in the observation group was observed (

P
<
0.05

). The QOL scores of the two groups of patients before treatment was not significantly different (

P
>
0.05

). Both groups witnessed improvements one month and three months after treatment, with considerable improvements being obtained in the observation group (all

P
<
0.05

). The two groups did not differ in ADL scores before treatment (

P
>
0.05

). At 1 month and 3 months after treatment, the ADL scores of the two groups were improved, with a higher score in the observation group (

P
<
0.05

). The observation group had a markedly higher total effective rate as compared to the control group (X2 = 5.455,

P
=
0.020

). Adverse reaction occurred in both groups, with milder results in the observation group. The recurrence rate of the two groups was not statistically different one month after treatment (

P
>
0.05

), while two and three months after treatment, they were lower than those of the control group (all

P
<
0.05

). Conclusion. Risperidone orally disintegrating tablets combined with oxazepam shows potential in the treatment of schizophrenia by relieving patients’ mental symptoms, improving quality of life and activities of daily living, and minimizing the incidence of adverse reactions.
Dendrobium officinale Endophytes May Colonize the Intestinal Tract and Regulate Gut Microbiota in Mice
Authors: Chen Wenhua , Yu Lilong , Zhu Bo , Qin Luping
Published: August 2022

Dendrobium officinale is a traditional Chinese medicine for treating gastrointestinal diseases by nourishing “Yin” and thickening the stomach lining. To study whether D. officinale endophytes can colonize the intestinal tract and regulate gut microbiota in mice, we used autoclave steam sterilizing and 60Co-γ radiation to eliminate D. officinale endophytes from its juice. Then, high-throughput ITS1-ITS2 rDNA and 16S rRNA gene amplicons were sequenced to analyze the microbial community of D. officinale endophytes and fecal samples of mice after administration of fresh D. officinale juice. Sterilization of D. officinale juice by autoclaving for 40 min (ASDO40) could more effectively eliminate the D. officinale endophytes and decrease their interference on the gut microbiota. D. officinale juice could increase beneficial gut microbiota and metabolites including short-chain fatty acids. D. officinale endophytes Pseudomonas mosselii, Trichocladium asperum, Titata maxilliformis, Clonostachys epichloe, and Rhodotorula babjevae could colonize the intestinal tract of mice and modulate gut microbiota after oral administration of the juice for 28 days. Thus, the regulatory effect of D. officinale juice on gut microbiota was observed, which provides a basis for inferring that D. officinale endophytes might colonize the intestinal tract and participate in regulating gut microbiota to treat diseases. Thus, this study further provides a new approach for the treatment of diseases by colonizing plant endophytes in the intestinal tract and regulating gut microbiota.
miR-216b-5p Inhibited the Progression of Experimental Optic Neuritis via Downregulating FAS
Authors: Wang Xiaoke , Ma Chi , Nie Lili
Published: August 2022

Objective. Present study mainly explored the effect of miR-216b-5p on experimental optic neuritis and mechanism. Methods. Female C57BL/6 mice were utilized to establish the EAE model. miR-216b-5p expression was measured by RT-qPCR. Protein expression was evaluated via western blot. Inflammatory infiltration score was analyzed by HE staining. Visual function was assessed by measuring the OKR. Flow cytometry assay was conducted to measure the percentage of IL-17 cells. ELISA was utilized to evaluate the immune factor. Results. The EAE mouse model was successfully established. The EAE score of mice began to increase in EAE group after 11 days of MOG35-55 and CFA immunization. The degree of inflammatory cell infiltration in EAE mice was higher than that in normal mice. Compared with normal mice, the number of microglia and astrocytes was raised in EAE mice. miR-216b-5p expression was obviously declined and FAS expression was obviously raised in EAE. Compared with NC group, demyelination scores and axonal loss were markedly declined in miR-216b-5p mimic group. IL-17A concentration and the percentage of IL-17 cells were obviously declined in miR-216b-5p mimic group. FAS was predicted to be regulated by miR-216b-5p by TargetScan, and luciferase reporter assay confirmed this prediction. In addition, overexpression of FAS exacerbated experimental optic neuritis by promoting the inflammatory response and Th17 cell differentiation, and miR-216b-5p reversed this effect. Conclusions. miR-216b-5p downregulated FAS and inhibited the progression of experimental optic neuritis via promoting the inflammatory response and Th17 cell differentiation.
Application of the R-Tree Clustering Model in Medical Information Retrieval
Authors: Dai Yun , Liu Hao
Published: August 2022

Hospitals produce a large amount of medical information every day. In the face of medical big data, the existing data processing methods cannot meet expectations and need to be continuously optimized. In the database system, when the stored objects are very large, and then the efficiency of data retrieval is a major bottleneck, therefore restricting the application of medical information. For that reason and to improve the efficiency of information retrieval, it is necessary to add an index to the information object and filter the dataset participating in the connection retrieval through the index. In this paper, an information retrieval technique grounded on the R-tree clustering model index is proposed for massive hospital information. The R-tree clustering model is constructed in massive hospital information by using the dynamic determination clustering center (DCC) algorithm. Finally, the superiority of the method is proved by simulations. The experiments and empirical evaluation show that the proposed R-tree clustering model index significantly improves data retrieval efficiency.
Influence of New Energy Materials on Dynamic Interaction between Surrounding Rock and Structure of Heavy‐Duty Railway in Small Clearance Crossing Tunnel
Authors: Hao Xiaotian , Wang Hailong
Published: August 2022

In the rapid development of urban traffic, the small clearance interchange tunnel has always been a difficult problem for heavy‐duty railways, so special requirements are also put forward for materials. Bainite steel with excellent comprehensive mechanical properties is considered to replace traditional high manganese, the best material for steel. This article first improves the process of the material and analyzes the structural dynamics of the material through different isothermal cooling to analyze the different performances of the material on the heavy‐duty railway. Using traditional theoretical data analysis, theoretical data calculation, numerical analysis simulation, and on‐site engineering monitoring technical means is to complement the construction of the soft rock underground tunnel in the subway section at the intersection of the small clear distance line to the existing surrounding rock tunnel wall in the section. The degree of deformation affects the change law, and the related technical issues of engineering control are analyzed. Finally, the control measures of full‐face grouting reinforcement with steel flower pipes and the final construction plan of constructing the left line, right line, and undercut section in sequence are proposed. FLAC numerical simulation software was used to complete the feasibility evaluation of the control measures for the deformation of the ground and lining induced by the construction of the cross tunnel. The results show that the maximum deformation of the ground surface is reduced by 35.4% compared with no control measures, and the longitudinal deformation range of the ground surface and the vault is reduced by 28.9%.
Matching Cybersecurity Ontologies on Internet of Everything through Coevolutionary Multiobjective Evolutionary Algorithm
Authors: Xue Xingsi , Tan Wenbin
Published: August 2022

Since Internet of Everything (IoE) makes all the connections that come online more relevant and valuable, they are subject to numerous security and privacy concerns. Cybersecurity ontology is a shared knowledge model for tackling the security information heterogeneity issue on IoE, which has been widely used in the IoE domain. However, the existing CSOs are developed and maintained independently, yielding the CSO heterogeneity problem. To address this issue, we need to use the similarity measure (SM) to calculate two entities’ similarity value in two CSOs and, on this basis, determine the entity correspondences, i.e., CSO alignment. Usually, it is necessary to integrate various SMs to enhance the result’s correctness, but how to combine and tune these SMs to improve the alignment’s quality is still a challenge. To face this challenge, this work first models CSO matching problem as a Constrained Multiobjective Optimization Problem (CMOOP) and then proposes a Coevolutionary Multiobjective Evolutionary Algorithm (CE-MOEA) to effectively address it. In particular, CE-MOEA uses the multiobjective evolutionary paradigm to avoid the solutions’ bias improvement and introduces the coevolutionary mechanism to trade off Pareto Front’s (PF’s) diversity and convergence. The experiment uses Ontology Alignment Evaluation Initiative’s (OAEI’s) bibliographic track and conference track and five real CSO matching tasks to test CE-MOEA’s performance. Comparisons between OAEI’s participants and EA- and MOEA-based matching techniques show that CE-MOEA is able to effectively address various heterogeneous ontology matching problems and determine high-quality CSO alignments.
Integrated Analysis of Crucial Genes and miRNAs Associated with Osteoporotic Fracture of Type 2 Diabetes
Authors: Mo Liang , Wang Zhangzheng , Huang Haoran , Li Jianxiong , Ma Chao , Zhang Jiahao , Huang Fayi , He Wei , Liu Yuhao , Zhou Chi
Published: August 2022

Purpose. The aim of this study is to explore pathological mechanisms of bone fragility in type 2 diabetes mellitus (T2DM) patients. Methods. Identifying common genes for T2DM and osteoporosis by taking the intersection is shared by the Comparative Toxicogenomics Database (CTD), DISEASES, and GeneCards databases. The differentially expressed genes (DEGs) and the differentially expressed miRNAs (DEMs) were identified by analyzing the Gene Expression Omnibus (GEO) datasets (GSE35958, GSE43950, and GSE70318). FunRich and miRNet were applied to predict potential upstream transcription factors and downstream target genes of candidate DEMs, respectively. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore potential mechanisms using Metascape. Eventually, a miRNA‐gene network was constructed by Cytoscape software. Results. 271 common targets and 35 common DEGs between T2DM and osteoporosis were screened out in the above databases, and a total of ten DEMs were obtained in the GSE70318. SP1 was predicted to potentially regulate most of the DEMs. Enrichment analysis showed the PI3K‐Akt signaling pathway and AGE‐RAGE signaling pathway in diabetic complications may play an important role in diabetic skeletal fragility. Two genes (NAMPT and IGFBP5) were considered as key genes involving in the development of diabetic osteoporosis. Through the construction of the miRNA‐gene network, most of the hub genes were found to be potentially modulated by miR‐96‐5p and miR‐7‐5p. Conclusion. The study uncovered several important genes, miRNAs, and pathological mechanisms involved in diabetic skeletal fragility, among which the PI3K‐Akt signaling pathway and AGE‐RAGE signaling pathway in diabetic complications may play important roles.
Analysis of the Outcome of Treatment of Brain Metastases from Malignant Trophoblastic Tumours and Risk Factors for Prognosis during Pregnancy
Authors: Wang Anbang , Zhang Hua
Published: August 2022

Temozolomide combined with whole‐brain radiotherapy has good near‐term efficacy and safety in the treatment of brain metastases from nonsmall cell lung cancer. In this study, we analyzed the risk factors for treatment and prognosis of brain metastases in gestational trophoblastic neoplasm (GTN) during pregnancy. Thirty‐one patients with brain metastases were included in the study. All patients had a pathological diagnosis of primary lesions, including 23 adenocarcinomas, 7 squamous carcinomas, and 1 adenosquamous carcinoma, and had ≥3 intracranial metastases, controlled primary lesions (including resected primary lesions or unresectable primary lesions in partial remission (PR)/complete remission (CR) for ≥2 months) by cranial enhancement MRI and no extracranial metastases. Presence or control of extracranial metastases was for ≥2 months. The common adverse toxic effects were nausea, vomiting, neutropenia, and thrombocytopenia, but most patients tolerated them with symptomatic management.