bluuebunny/crossref_metadata_2025 huggingface dataset:
Allele‐specific expression and chromatin accessibility contribute to heterosis in tea plants (Camellia sinensis)
Authors: Wang Pengjie , Gu Mengya , Yu Xikai , Shao Shuxian , Du Jiayin , Wang Yibin , Wang Feiquan , Chen Shuai , Liao Zhenyang , Ye Naixing , Zhang Xingtan
Published: October 2022

Heterosis is extensively used to improve crop productivity, yet its allelic and chromatin regulation remains unclear. Based on our resolved genomes of the maternal TGY and paternal HD, we analyzed the contribution of allele‐specific expression (ASE) and chromatin accessibility of JGY and HGY, the artificial hybrids of oolong tea with the largest cultivated area in China. The ASE genes (ASEGs) of tea hybrids with maternal‐biased were mainly related to the energy and terpenoid metabolism pathways, whereas the ASEGs with paternal‐biased tend to be enriched in glutathione metabolism, and these parental bias of hybrids may coordinate and lead to the acquisition of heterosis in more biological pathways. ATAC‐seq results showed that hybrids have significantly higher accessible chromatin regions (ACRs) compared with their parents, which may confer broader and stronger transcriptional activity of genes in hybrids. The number of ACRs with significantly increased accessibility in hybrids was much greater than decreased, and the associated alleles were also affected by differential ACRs across different parents, suggesting enhanced positive chromatin regulation and potential genetic effects in hybrids. Core ASEGs of terpene and purine alkaloid metabolism pathways with significant positive heterosis have greater chromatin accessibility in hybrids, and were potentially regulated by several members of the MYB, DOF and TRB families. The binding motif of CsMYB85 in the promoter ACR of the rate‐limiting enzyme CsDXS was verified by DAP‐seq. These results suggest that higher numbers and more accessible ACRs in hybrids contribute to the regulation of ASEGs, thereby affecting the formation of heterotic metabolites.
Double nested Hilbert schemes and the local stable pairs theory of curves
Authors: Monavari Sergej
Published: October 2022

We propose a variation of the classical Hilbert scheme of points, thedouble nested Hilbert scheme of points, which parametrizes flags of zero-dimensional subschemes whose nesting is dictated by a Young diagram. Over a smooth quasi-projective curve, we compute the generating series of topological Euler characteristic of these spaces, by exploiting the combinatorics of reversed plane partitions. Moreover, we realize this moduli space as the zero locus of a section of a vector bundle over a smooth ambient space, which therefore admits a virtual fundamental class. We apply this construction to the stable pair theory of a local curve, that is the total space of the direct sum of two line bundles over a curve. We show that the invariants localize to virtual intersection numbers on double nested Hilbert scheme of points on the curve, and that the localized contributions to the invariants are controlled by three universal series for every Young diagram, which can be explicitly determined after the anti-diagonal restriction of the equivariant parameters. Under the anti-diagonal restriction, the invariants are matched with the Gromov–Witten invariants of local curves of Bryan–Pandharipande, as predicted by the Maulik–Nekrasov–Okounkov–Pandharipande (MNOP) correspondence. Finally, we discuss$K$-theoretic refinements à la Nekrasov–Okounkov.
Discussion on the Paper “Synchronization Via Fractal–Fractional Differential Operators on Two-Mass Torsional Vibration System Consisting of Motor and Roller, Abro, K. A., and Atangana, A., 2021, ASME J. Comput. Nonlinear Dyn., 16(12), p. 121002”
Authors: Pantokratoras Asterios
Published: October 2022

In the above paper many parameters are unknown.
Mapping the Chaotic Transitions of the Lorenz Equations With Unsupervised Machine Learning
Authors: Tribelhorn Ben , Dillon H. E.
Published: October 2022

Prior work has explored utilizing machine learning for the Lorenz system in the time domain. In this work, we have focused on applications of machine learning for predicting the onset of chaotic transitions in the Lorenz system. Our methods included the development of a robust numerical solution to the Lorenz equations using a fourth order Runge–Kutta method. We solved the Lorenz equations for a large range of Raleigh ratios from 1 to 1000. We calculated the power spectral density, various descriptive statistics, and a cluster analysis using unsupervised machine learning. To identify behaviors and regions in the data, we utilize unsupervised learning as it is designed to assist in recognizing patterns without being told or trained by prior knowledge. We confirmed the performance of the machine learning system's ability to identify chaotic transitions independent of expert selection of Raleigh ratio ranges. The system correctly identifies the transitional behaviors described in prior mathematical work. The results indicate that the power spectral density is very important for the clustering. We also found that examining machine learning clusters by dimension (x, y, and z) was important to understand many of the facets of the chaotic transitions. The results provide a visual mapping of the regions where chaotic transitions may occur based on variations in the Prandtl number and geometry constant. Unsupervised machine learning may be used as a tool to characterize the transition regions for these geometries, providing new lenses for the heat transfer community.
Modeling of Traction Drive in Elastohydrodynamic Lubrication Contact and Traction Coefficient Enhancement Using Surface Texture Under High-Speed Conditions of up to 50,000 rpm
Authors: Yamamoto Takeshi
Published: October 2022

A high-speed electric motor with a small reducer that has high-power transmission efficiency can be used to realize a high-power-density powertrain system because electric motors can be miniaturized to increase the rotational speed. A traction drive has low vibration noise due to its lack of meshing vibration, making it suitable as a transmission element for high-speed reducers. However, the traction coefficient, which greatly affects transmission performance, decreases with increasing rotational speed. In this study, to increase the traction coefficient using a surface texture, a model that takes into account transient temperature changes under high-speed conditions and the effects of micro-surface geometry was developed. The traction coefficient was measured using a high-speed test machine capable of operating at a maximum speed of 50,000 rpm. The model was able to predict the experimental values with an error of at most 6%. The high-pressure rheological properties of the oil were examined to develop design guidelines for the surface texture and a model was used to optimize the texture parameters. The designed texture was manufactured and evaluated. Experimental results show that the traction coefficient can be improved by up to 19%.
The Dose–Response Relationship Between Training-Load Measures and Changes in Force–Time Components During a Countermovement Jump in Male Academy Soccer Players
Authors: Ellis Matthew , Myers Tony , Taylor Richard , Morris Rhys , Akubat Ibrahim
Published: October 2022

Purpose: To manage physical performance in soccer, practitioners monitor the training load (TL) and the resulting fatigue. A method frequently used to assess performance is the countermovement jump (CMJ). However, the efficacy of CMJ to detect fatigue from soccer matches and training remains uncertain, as does the relationship between TL and change in CMJ performance. The aims of the present study were 2-fold. One was to observe the changes of CMJ force–time components and jump height (JH). The second was to examine dose–response relationships between TL measures and CMJ over a 6-week preseason. Methods: Twelve male academy soccer players (17 [1] y, 71.2 [5.6] kg, and 178 [5.8] cm) were recruited. Daily changes in CMJ were assessed against baseline scores established before preseason training, along with internal and external TL measures. A series of Bayesian random intercept models were fitted to determine probability of change above/below zero and greater than the coefficient of variation established at baseline. Jumps were categorized into match day minus (MD−) categories where the higher number indicated more time from a competitive match. Results: JH was lowest on MD − 3 (28 cm) and highest on MD − 4 (34.6 cm), with the probability of change from baseline coefficient of variation highly uncertain (41% and 61%, respectively). Changes to force–time components were more likely on MD − 3 (21%–99%), which provided less uncertainty than JH. Bayes R2 ranged from .22 to .57 between TL measures and all CMJ parameters. Conclusions: Force–time components were more likely to change than JH. Practitioners should also be cautious when manipulating TL measures to influence CMJ performance.
Influence of Nutrients and the Native Community on E. coli Survival in the Beach Environment
Authors: Meyers Brigid C. , McLellan Sandra L.
Published: October 2022

Current monitoring for fecal pollution does not account for persistent
E. coli
populations in freshwater sand, which can result in higher concentrations in water when no threat to human health is present. This work examined the drivers for persistent
E. coli
populations in sand to aid beach management techniques.
Investigation of the Mechanism and Chemistry Underlying Staphylococcus aureus
'
Ability to Inhibit Pseudomonas aeruginosa Growth
In Vitro
Authors: Kvich Lasse , Crone Stephanie , Christensen Mads H. , Lima Rita , Alhede Morten , Alhede Maria , Staerk Dan , Bjarnsholt Thomas
Published: October 2022

Chronic infections affect a growing part of the population and are associated with high societal and personal costs. Multiple bacterial species are often present in these infections, and multispecies infections are considered more severe than single-species infections.
Staphylococcus aureus
and
Pseudomonas aeruginosa
often coexist in chronic infections.
Serratia marcescens DUF1471-Containing Protein SrfN Is Needed for Adaptation to Acid and Oxidative Stresses
Authors: Elistratova Anna A. , Matrosova Lilia E. , Khilyas Irina V. , Shirshikova Tatiana V. , Danilova Iuliia V. , Laikov Alexander V. , Romanova Yulia D. , Sierra-Bakhshi Cecilia G. , Sharipova Margarita R. , Bogomolnaya Lydia M.
Published: October 2022

Serratia marcescens
is ubiquitous in the environment and can survive in water, soil, plants, insects, and animals, and it can also cause infections in humans. In the face of disturbances such as oxidative or low-pH stress, bacteria adapt, survive, and recover through several mechanisms, including changes in their secretome.
Tree stem volume estimation from terrestrial LiDAR point cloud by unwrapping
Authors: An Zhongming , Froese Robert E.
Published: October 2022

Estimating the volume of standing trees is a fundamental concern in forestry and is typically accomplished using one or more measurements of stem diameter along with formulae that assume geometric primitives. In contrast, technologies such as terrestrial Light Detection And Ranging (LiDAR) can record very detailed spatial information on the actual surface of an object, such as a tree bole. We present a method using LiDAR that provides accurate volume estimates of tree stems, as well as 2D rasters that display details of stem surfaces, which we call the “unwrapping method.” This method combines the concepts of cylinder fitting, voxelization, and digital elevation models. The method is illustrated and tested using a sample of standing trees, whereby we are able to generate accurate volume estimates from the point cloud, as well as accurate visualization of the scanned stem sections. When compared to volume estimates derived from Huber's, Smalian's, and Newton's formulae, the differences are consistent with previous studies comparing formula-derived volume estimates and water-displacement-derived volume estimates, suggesting the unwrapping method has comparable accuracy to water displacement.
Is it Feasible to Teach Agent-based Computational Modeling to Elementary and Middle School Students?
Authors: Araya Roberto
Published: October 2022

Many of the computational models in science, engineering, and social studies are agent-based models. However, despite their growing importance and potential attractiveness to students, agent-based models are not taught in elementary, middle or high school. In this paper, the author explores the feasibility of teaching agent-based models to elementary and middle school students, and the extent students can learn modeling using agent-based mathematical and computational models.
Understanding the role of placental pathophysiology in the development of bronchopulmonary dysplasia
Authors: Parsons Andrew , Netsanet Adom , Seedorf Gregory , Abman Steven H. , Taglauer Elizabeth S.
Published: October 2022

The associations between bronchopulmonary dysplasia (BPD) and the gestational pathologies of chorioamnionitis (CA) and hypertensive disorders of pregnancy (HDP) have become increasingly well recognized. However, the mechanisms through which these antenatal conditions cause increased risk of BPD remain less well characterized. The objective of this review is to discuss the role of the placenta in BPD predisposition as a primary driver of intrauterine alterations adversely impacting fetal lung development. We hypothesize that due to similarities in structure and function, placental disorders during pregnancy can uniquely impact the developing fetal lung, creating a unique placental-pulmonary connection. In the current review, we explore this hypothesis through analysis of clinical literature and preclinical model systems evaluating BPD predisposition, discussion of BPD phenotypes, and an overview on strategies to incorporate placental investigation into research on fetal lung development. We also discuss important concepts learned from research on antenatal steroids as a modulator fetal lung development. Finally, we propose that the appropriate selection of animal models and establishment of in vitro lung developmental model systems incorporating primary human placental components are key in continuing to understand and address antenatal predisposition to BPD.
M2c Macrophages Protect Mice from Adriamycin-Induced Nephropathy by Upregulating CD62L in Tregs
Authors: Lu Junyu , Lv Shengqiu , Pang Jielong , Qin Tao , Yang Yegui , Lu Weisheng , Li Zhengzhao , Yang Geng , Zhang Jianfeng
Published: October 2022

Regulatory T cells (Tregs) and M2c macrophages have been shown to exert potentially synergistic therapeutic effects in animals with adriamycin-induced nephropathy (AN), a model chronic proteinuric renal disease. M2c macrophages may protect against renal injury by promoting an increase in the number of Tregs in the renal draining lymph nodes of AN mice, but how they do so is unclear. In this study, we used an AN mouse model to analyze how M2c macrophages induce the migration of Tregs. Using flow cytometry, we found that M2c macrophages promoted the migration of Tregs from the peripheral blood to the spleen, thymus, kidney, and renal draining lymph nodes. At the same time, M2c macrophages significantly upregulated chemokine receptors and adhesion molecule in Tregs, including CCR4, CCR5, CCR7, CXCR5, and CD62L. Treating AN mice with monoclonal anti-CD62L antibody inhibited the migration of M2c macrophages and Tregs to the spleen, thymus, kidney, and renal draining lymph nodes. Taken together, our results suggest that M2c macrophages upregulate CD62L in Tregs and thereby promote their migration to inflammatory sites, where they exert renoprotective effects. These insights may aid the development of treatments against chronic kidney disease.
Consumer Demand Behavior Mining and Product Recommendation Based on Online Product Review Mining and Fuzzy Sets
Authors: Zhuo Jia
Published: October 2022

Consumer demand is the need for product characteristics expressed in their own words, which is the basis for producers to develop product recommendations. The extraction and analysis of consumer demands is the most critical input information in quality function deployment (QFD), which has a significant impact on the final prioritization of product technical features, product optimization, and subsequent configuration decisions in QFD, and is directly related to the success of product development. However, the traditional QFD approach to demand analysis lacks reliability and feasibility, and its application often requires time and labor costs that exceed the company’s actual capabilities. Therefore, this paper uses online reviews as the data source and constructs a latent Dirichlet allocation (LDA) topic model based on fuzzy sets to explore the consumer demand information reflected in user reviews. We also introduce the concept of word vector to improve the LDA topic model and compare it with the traditional topic model to verify the performance of the model, so as to explore the consumer demand behavior more accurately and efficiently.
Analysis of Tire‐Pavement Contact Morphology Characteristics during the Virtual Track Train Maneuvering
Authors: Wang Chengping , Zhang Jimin , Zhou Hechao
Published: October 2022

The tire‐pavement contact morphology during the virtual track train maneuvering has an essential function in assessing vehicle performance and pavement damage. The longitudinal tread tire and viscoelastic asphalt pavement were developed based on the finite element method. Then, the tire‐pavement contact model was developed according to the Euler–Lagrange algorithm and validated. Contact area and stress distribution under uniform, braking, and cornering conditions are explored with the dynamic tire force of the virtual track train as the external load. Also, the effect factors were analyzed. The results indicate that vertical stress distribution is symmetrical along the length and width directions, and contact area is rectangular under uniform condition. Vertical and longitudinal stresses have similar distributions under braking condition, with a wide front and a narrow back along the length direction. Under cornering condition, the closer to the inside of the cornering, the larger the contact area. Vertical stress is similar to the lateral stress distribution, and the larger stress value is concentrated on the inner side of each tread. Load, tire pressure, slip rate, and slip angle have significant effects on contact morphology, while velocity has little effect. Contact area increases with the increase of load and slip rate and decreases with the increase of tire pressure and slip angle. Vertical stress increases gradually with the increase of load. Higher tire pressure makes stress distribution more concentrated. The increase in slip rate increases vertical and longitudinal stresses and gradually moves in the running direction. Vertical and lateral stresses increase with the slip angle and are mainly distributed on the inside of the turn. This research can be used to evaluate and analyze the response and damage of the virtual track train to asphalt pavement under uniform, braking, and cornering conditions. It can be used as a reference for the design and paving of asphalt pavement.
Comparative Study on Feature Selection in Protein Structure and Function Prediction
Authors: Yi Wenjing , Sun Ao , Liu Manman , Liu Xiaoqing , Zhang Wei , Dai Qi
Published: October 2022

Many effective methods extract and fuse different protein features to study the relationship between protein sequence, structure, and function, but different methods have preferences in solving the research of protein structure and function, which requires selecting valuable and contributing features to design more effective prediction methods. This work mainly focused on the feature selection methods in the study of protein structure and function, and systematically compared and analyzed the efficiency of different feature selection methods in the prediction of protein structures, protein disorders, protein molecular chaperones, and protein solubility. The results show that the feature selection method based on nonlinear SVM performs best in protein structure prediction, protein solubility prediction, protein molecular chaperone prediction, and protein solubility prediction. After selection, the accuracy of features is improved by 13.16% ~71%, especially the Kmer features and PSSM features of proteins.
Prognosis and Prognostic Factors of Serous Borderline Tumor-Micropapillary Variant: Retrospective Study of 200 Patients with Long-Term Follow-Up
Authors: Jia Shuang-Zheng , Yao Hong-Wen , Li Ning , Yang Jun-Jun , Xiang Yang , Zheng Shan , Leng Jin-Hua , Wu Ling-Ying
Published: October 2022

Objective. To determine the oncofertility outcomes and prognostic factors in a large series of serous borderline ovarian tumor-micropapillary variant (SBOT-M) with a long-term follow-up. Methods. Consecutive patients with SBOT-Ms treated from two affiliated hospitals of the Chinese Academy of Medical Sciences were retrospectively reviewed. Prognostic factors on invasive recurrence, disease-free survival (DFS), and overall survival were analyzed, and outcomes of patients treated with conservative and radical surgery were compared. Results. From 2000 to 2020, 200 patients were identified and followed. After a median follow-up of 68 months, 81 patients relapsed. In the multivariate analyses, younger age at diagnosis and conservative surgery that preserved fertility potential were independently associated with worse DFS (

p
=
0.018

and <0.001, respectively). Twenty-three patients experienced invasive recurrence, and seven died of progressive disease. Multivariate analysis showed that nulliparous and advanced FIGO stage were independently adversely associated with lethal recurrence (

p
=
0.022

and 0.029, respectively). Only advanced FIGO stage at diagnosis was associated with worse overall survival at univariate analysis (

p
=
0.02

). Among 61 patients attempting conception, 37 achieved 44 pregnancies and resulted in 32 live births. Conclusions. In this series, patients with SBOT-M have an acceptable oncofertility outcomes. The use of conservative surgery was independently associated with worse DFS, but without an impact on neither invasive relapse nor on overall survival. Patients with advanced FIGO stages had a significantly higher risk of lethal recurrence and worse overall survival, suggesting that adequate staging surgery and intensive postoperative surveillance should be warranted.
Research on the Identification of Internet Critical Nodes Based on Multilayer Network Modeling
Authors: Zhang Yongheng , Lu Yuliang , Yang Guozheng , Luo Zhihao
Published: October 2022

The research goal of cyberspace security situational awareness analysis is to predict the future security development of the target network by acquiring, understanding, and displaying the security elements in the large-scale network environment. Current cyberspace security situational awareness systems are mostly based on traditional single-layer network topology to analyze the security of the target network's operational posture. However, as the scale of the network continues to expand, the network structure becomes more complex, and the information fusion in multiple fields in practical applications deepens, the single-layer topology model can no longer meet the analysis requirements. In this paper, we construct a multilayer network topology model for cyberspace security situational awareness by integrating multidimensional information in the physical device layer network, business application layer network, and user role layer network. Meanwhile, to eliminate the limitations of traditional node importance indicators, a node importance assessment indicator that integrates topological centrality and node dependency factor is proposed in conjunction with model characteristics: multilayer dependency CRITIC indicator (

MDCI

). On the one hand,

MDCI

fits a variety of evaluation metrics through the CRITIC multi-attribute decision method to comprehensively assess the importance of nodes in network centrality, and on the other hand,

MDCI

better aggregates the important contributions of nodes in each network layer based on node dependency factor to coordinate multilayer network information. The experimental results show that

MDCI

has better ordering monotonicity and generates more stable metric sequences, and can effectively cause large-scale failures in multilayer network while destroying fewer physical device components, which can be better adapted to the critical node identification needs of multilayer network.
Correlation between the Quality of Talent Training and Regional Economic Development Based on Multivariate Statistical Analysis Model
Authors: Yuan Yana
Published: October 2022

Entering the era of knowledge economy, the economic value of talent education is more and more emphasized, and it contributes more and more to the local economy and injects new vitality into local economic development. However, there are still some difficulties in the synergistic development of talent education and local economy, such as the low degree of integration of “industry, profession, and employment” and the lack of synergy between schools and enterprises, which affects the high-quality development of talent education and restricts the long-term development of regional economy. This paper incorporates machine learning algorithms to construct a multivariate statistics analysis model based on the correlation analysis model between talent training quality and regional economic development. Based on the multi-variate statistical analysis theory and method, the qualitative analysis and quantitative analysis are closely combined to scientifically pick up the main indicators affecting the comprehensive quality of talent cultivation and overcome the drawbacks of artificial subjective assignment of values. Through the judicious selection of evaluation indexes, a scientific and fair evaluation model is established, and the targets of talent cultivation are combined with regional economic development, in a comprehensive analysis, which provides a new means for the development of the regional economy.
Seismic Damage Analysis of Large-Span Tied-Arch Bridge with Concrete-Filled Steel Tubes Subjected to Near-Fault Ground Motion
Authors: Xia Yingzhi , Liu Jiawei , Li Hui , Hu Guoping
Published: October 2022

In this study, the damage mechanism due to near-fault ground motions on large-span arch bridges with concrete-filled steel tubes was investigated based on a case study. A tied-arch bridge with concrete-filled steel tubes with a span of 460 m has been examined using the numerical simulation method. The performance of the bridge was analyzed in terms of displacement, overall response, internal force changes, and damage probability considering the various near-fault and non-near-fault ground motions when imposing load onto the bridge. Then, the relationship between the bridge damage and the design parameters of ground motion intensities, near-fault velocity pulse, and excitation angle was obtained. The results indicated that the probability of damage caused by near-fault earthquakes is significantly higher than that by non-near-fault ground motions, and velocity pulses may cause more severe damages to certain components of the bridge during lower-intensity ground motions at certain excitation angles. And the damage furtherly resulted in the weakening of the bridge structure and decrease in its load-carrying capacity. Therefore, the near-fault ground motion should be fully considered in the design of large-span arch bridges with concrete-filled steel tubes in practical engineering.
Research on Application of Intelligent Corpus Annotation of Entity Extraction with Construction of Knowledge Graph
Authors: Liu Xingli , Fan Junjie , Ma Haiqun
Published: October 2022

The purpose of this paper is to solve the problem of big data and small samples caused by the high manual annotation cost of a military corpus. The deep learning algorithm of entity extraction in the military field was organically combined with the method of bootstrapping loop iteration to complete a study on the application of intelligent corpus annotation of military field entities. With the experimental research showing that using a small number of military field entity corpus annotations for RoBERTa pretraining word vectors and BiLSTM-CRF models and based on the bootstrapping algorithm idea to complete 3 rounds of loop iterations and 10 rounds of cross-validation joint-voting model iterations, the best entity extraction model evaluation F value reached up to 91.5%. Finally, the 60M intelligent corpus annotation application testing was completed using the best model of iteration of this round, with a total of 178,177 sentences of military field corpus intelligently labeled, the number of entities that should be labeled reaching 417,734. Therefore, this is an efficient way of construction and evaluation of intelligent corpus annotation model in the military entity extraction field. The findings of this paper provide an effective way of how to complete the labeled corpus. The research serves as a first step for future research, for example, the construction of knowledge graphs and military intelligent Q&A.
Weed Types and Dynamics Associations with Catena Landscape Positions: Smallholder Farmers’ Knowledge and Perception in Zimbabwe
Authors: Chipomho Justin , Tatsvarei Simbarashe , Parwada Cosmas , Mashingaidze Arnold Bray , Rugare Joyful T. , Mabasa Stanford , Chikowo Regis
Published: October 2022

Weed infestation is considered as one of the major biotic stresses of dryland crop production. Weed species occurrence, abundance, and densities differ due to spatial soil fertility variability, and management practices by farmers. Weed surveys are therefore vital for tracking such changes and in turn developing appropriate weed management strategies for farmers. A weed survey was carried out in Wedza, eastern Zimbabwe to assess farmer knowledge and perceptions of major weeds in maize fields across catena landscape positions. A multistage sampling procedure was used, involving random sampling of six villages within a 20 km radius, divided according to the catena position and economic status of the farmer. Two hundred and forty-nine (249) households were interviewed using a structured questionnaire. The data were coded and processed using the CSPro software package, and then analysed using the SPSS program. Factors that predicted the spatial distribution of weeds were determined using a binary logistic model. From the survey, 52.8% and 42.3% of farms are on the upper catena and lower catena, respectively, and only 4.8% are on the middle catena. Thirty-one weed species belonging to 15 families were listed by respondents and identified by enumerators in the study area and were categorised into three main groups (broadleaf, grasses, and sedges). Acanthospermum hispidum and Striga asiatica were considered as problem weeds in maize fields on the upper and lower catena, respectively. Xanthium strumarium was perceived as a new invasive weed in low-lying arable fields. The binary logistic model predicted farm location on the landscape and fertiliser use as the main factors affecting weed types, distribution, and abundance. Moreover, farms on lower catena had more Striga infestations compared to upper catena. The results suggested an integrated weed management approach to control A. hispidum, Striga species, and the invasive fast-spreading X. strumarium in the area.
Smart System Design for College Physical Education Class Based on Abnormal Audio Detection Algorithm
Authors: Bai Yonghui
Published: October 2022

Based on dual-core technology and the theory of nontransmission and noninterference of information flow, this paper conducts a detailed system trust environment investigation on key issues such as trust routing design and reliability analysis in the embedded structure. At the same time, we will study the method of extracting features from speech data. When dealing with abnormal audio detection, firstly, the preprocessed valid audio clips are framed and windowed and have stable short-term characteristics; after the feature is stable, the frequency feature and time domain feature of audio data are analyzed and compared. And then combined with specific applications, a detailed demand analysis is carried out, and the development plan and implementation method of the college physical education network auxiliary system are proposed. The teaching system follows a three-tier system structure. In order to expand the existing functions, this paper uses the principle of modularity, starting from the following four aspects: educational resources, online question and answer, coursework, and test-related modules. We choose object-oriented and easy-to-expandable modules, such as the development and implementation of programming language environments and database systems. By applying the abnormal audio detection technology to the embedded system of college P.E. classroom, it can effectively optimize the traditional P.E. teaching mode and promote the teaching efficiency and the new development of P.E. teaching in the information age.
Development of Nanoemulsions for Wound Dressings Containing Cassia alata L. Leaf Extraction
Authors: Sangkaew Surat , Wanmasae Smith , Bunluepeuch Kingkan , Ongtanasup Tassanee , Srisang Siriwan , Manaspon Chawan , Pooprommin Philaslak , Eawsakul Komgrit
Published: October 2022

Natural polymer-based hydrogel films possess considerable potential for use in biomedical applications and are excellent for wound healing. The purpose of this research was to use ionic crosslinking to improve the mechanical characteristics, absorption of fluid in the wound, and drug release behavior of Cassia alata L. (CA) extract loaded niosomes (CANs) that were incorporated in an alginate-pectin film (A/P). Then, chemically crosslinked A/P hydrogels were obtained by immersing them in different concentrations of calcium chloride (CaCl2) (0.5–1% w/v) for 15–120 s. The degree of crosslinking was controlled by both contact time and CaCl2 concentration. The optimal crosslinking conditions were 1% CaCl2 for 15 seconds. In this study, the following features of the hydrogel films were investigated: physical properties, morphological characteristics, drug loading, in vitro drug release, antibacterial activity, wound healing activity, cytocompatibility profiles, and hemocompatibility. The crosslinked hydrogel films maintained their physical integrity during use, with the 1% film attaining the best results in the shortest period (15 sec). Then, in vitro drug release from the films was examined. Crosslinking was observed to prolong the release of the CA extract from the hydrogel film. Finally, a cell viability experiment was conducted to evaluate the cytotoxicity profile. The A/P composite film exhibited excellent wound dressing qualities and good mechanical properties in preformulation testing. The in vitro drug release profile indicated that the A/P created a regulated drug release profile, and the cell viability experiment revealed that the film was nontoxic and hemocompatible. A/P composite films can be produced using CAN extract as a possible wound dressing. However, further studies in animals and humans are required to determine both safety and effectiveness.
Pulmonary Epithelial-Myoepithelial Carcinoma
Authors: Chen Lingru , Fan Ying , Lu Hongyang
Published: October 2022

Pulmonary epithelial-myoepithelial carcinoma (P-EMC) is an exceptionally rare subtype of salivary gland lung tumor originating from tracheobronchial glands. P-EMC is a biphasic tumor consisting of an inner layer of epithelial cells and an outer layer of spindle-shaped, clear-cell-like myoepithelial cells. Bronchial obstruction symptom is the main clinical characteristic for P-EMC. Because its clinical and imaging characteristics are highly similar to other types of non-small-cell lung cancer (NSCLC), it is easy to cause missed diagnosis and misdiagnosis. The diagnosis is mainly based on the pathology and immunohistochemistry with an inner layer of epithelial cells immunoreactive for cytokeratin and an outside layer of myoepithelial cells immunoreactive for S100 protein (S-100) and smooth muscle actin (SMA). Therefore, positive for cytokeratin, S-100 and SMA can assist in the diagnosis. Although in general, P-EMC is a low-grade malignant neoplasm, it may occasionally recur and metastasize. The optimal method for P-EMC treatment has not been established, and surgical resection is still the main clinical method. Radiotherapy and chemotherapy have been shown not sensitive for P-EMC treatment, whereas targeted therapy and immunotherapy have not evaluated in clinical practice. This review focuses on the pathological characteristics, molecular characteristics, diagnosis, treatment, and prognosis of P-EMC.
Research on Machine Translation Method of English-Chinese Long Sentences Based on Fuzzy Semantic Optimization
Authors: Dong Zhaofeng
Published: October 2022

The machine translation of English-Chinese long sentences is out of order under the constraint of the mixed corpus. In order to improve the accuracy of machine translation of English-Chinese long sentences, a machine translation method based on fuzzy semantic optimization is proposed. By adopting the method of systematic semantic configuration structure fusion, the ontology mapping model of the English-Chinese long sentence subject list under the constraint of the mixed corpus is constructed. In the distribution structure space of English-Chinese long sentences under the constraint of the mixed corpus, the method of extracting the best semantic relevance and analyzing the concept tree of context semantic mapping is adopted to mine the dynamic features of the subject list of English-Chinese long sentence translation under the constraint of the mixed corpus. In the intrinsic distribution sequence of semantic mapping between concepts, the fuzzy semantic combination features of English-Chinese long sentences under the constraint of the mixed corpus are extracted. The distribution results of word knowledge priority selection sequence, the automatic translation of English-Chinese long sentences under the constraint of the mixed corpus is realized by scheduling a grammatical error correction task list. According to the simulation results, machine translation of long English-Chinese sentences under the restriction of mixed corpora is capable of good semantic configuration. The degree of linguistic structural similarity between English and Chinese is great, which enhances the automatic translation capacity of English-Chinese long sentences under the limitation of the mixed corpus.
Dual-Server Identity-Based Encryption with Authorized Equality Test for IoT Data in Clouds
Authors: Zhao Meng , Ding Yong
Published: October 2022

The massive amounts of data collected by Internet of things (IoT) devices can be stored in clouds to solve the problem of the low storage capacity of IoT terminals. However, the privacy and security of outsourced IoT data may be compromised on the cloud side. Traditional cryptographic technologies can protect data privacy but require the user to retrieve the data for decryption and further processing, which would bring vast amounts of bandwidth and computation burden to users. This paper proposes a dual-server identity-based encryption scheme supporting authorized ciphertext equality test (DS-IBE-AET), where two noncolluding servers with authorizations from users can collaboratively carry out an equality test on outsourced IoT ciphertexts without decrypting the data. DS-IBE-AET can resist offline keyword guessing attacks confronted by existing encryption schemes with equality test in the single server model. Security analysis demonstrates that the proposed DS-IBE-AET scheme offers unforgeability for private keys of users and servers and confidentiality protection for outsourced IoT data and authentication tokens. The performance analysis indicates the practicality of our DS-IBE-AET construction for securing outsourced IoT data in clouds.
High-Level Petri Nets-Based Modeling of Network Controlled Systems under Communication Constraints (Network-Induced Delay)
Authors: Farah Khamsa , Chabir Karim , Abdelkrim Mohamed Naceur
Published: October 2022

Our work deals with the problems of communication delays, packets dropouts, and quantization errors in the signal transmitted in network-controlled systems (NCS). Although NCS provides a paradigm for adapting to frequent changes in the manufacturing industry, modeling and managing operations are difficult issues due to the complex interactions between system entities and the effect of the network-induced delay on the closed-loop system. Therefore, our paper is about detecting degradations resulting from the insertion of a network in the regulation loop, which can even lead in some cases to the destabilization of the NCS. This paper mainly studies the problem of the graphic modeling, based on the colored Petri nets (CPN), of the NCS under communication constraints. Therefore, models of the communication network (Ethernet) and system entities are presented. Then, the influence of network-induced delay is detected. Finally, as an idea for future work, we propose a solution based on an SDN controller in order to avoid precedent degradations.
Synchronous Colorectal Liver Metastases considering Infectious Complications: Simultaneous or Delayed Surgery?
Authors: Huang Lijun , Tang Xiao , Fang Jiafeng , Zheng Zongheng , Wei Hongbo
Published: October 2022

Background. Simultaneous or delayed surgery for synchronous colorectal liver metastases is performed in the clinic; which method is better is still up for debate. In particular, infectious complications are rarely compared. This study aims to investigate the differences between simultaneous and delayed surgery for synchronous colorectal liver metastases by comparing infectious complications and prognosis. Methods. Firstly, the patients’ information from a single institution’s database was retrospectively analyzed. Then the patients were divided into a simultaneous group and a delayed group according to synchronous colorectal liver metastases. Analyzing the postoperative complications within 30 days, the progression-free survival, and the overall survival in the two groups. Results. The simultaneous group had a higher neo-adjuvant chemotherapy rate (42.0% VS. 16.0% in the delayed group,

P
<
0.05

) and laparoscopic surgery rate (89.8% VS. 72.0% in the delayed group,

P
<
0.05

) than the delayed group. Moreover, the simultaneous group had a higher liver-related infection rate (17.0 VS. 0.0% in the delayed group,

P
<
0.05

). Conclusion. Although there was no difference in survival rate between delayed and simultaneous surgeries, the delayed surgery have fewer liver-related infections compared with the simultaneous surgery in synchronous colorectal liver metastases patients. Delayed surgery could be a better treatment method for synchronous colorectal liver metastases patients.
A Case of an Infantile Lingual Leiomyomatous Hamartoma
Authors: Gao Thomas Z. , Schafer Austin , Althubaiti Abdulrahman , Fung Bonita , Elmaraghy Charles
Published: October 2022

Lingual leiomyomatous hamartomas are rare lesions of the tongue with largely unknown mechanisms of formation. These lesions are often asymptomatic, though they may present with symptoms, particularly relating to swallow function. Workup should include imaging of the head and neck, and diagnosis should be made histologically. Treatment is surgical excision. This case is a report of a 4-week-old female who presented for evaluation of an asymptomatic 1 × 1 cm dorsal midline tongue mass discovered at birth. The patient was monitored until the age of 9 months, at which time the mass was surgically excised. The patient had an uncomplicated postoperative course. Pathological analysis yielded a diagnosis of leiomyomatous hamartoma.
Analysis and Construction of the User Characteristic Model in the Adaptive Learning System for Personalized Learning
Authors: Zhao Xuekong , Long Shirong , Hu Defa
Published: October 2022

Adaptive Learning System (ALS) is a supportive environment, which dynamically provides learners with services that can satisfy their demand for personalized learning in accordance with the differentiation of their individual traits. At present, study on ALS is still in the exploratory stage, and there are still many fields that deserve to be studied thoroughly. User characteristic model is the foundation and core of ALS and the key to the implementation of intelligent and personalized recommendation service. Based on this, this paper intends to analyze learners’ characteristics in ALS through several dimensions, such as basic information, interest, preference, cognitive level and learning style, through which learners’ user characteristic model is established. In the end, ALS, which supports the function of personalized recommendation, is implemented based on this model. It is suggested by the result of the simulation experiment that ALS, which is developed through this model, demonstrates a satisfying effect in recommendation, and it can dynamically recommend appropriate learning resources in accordance with learners’ personalized demands through which learners’ quality and efficiency of learning can be effectively enhanced to a certain extent.
Observer-Based Finite-Time Inverse Optimal Output Regulation for Uncertain Nonlinear Systems
Authors: Meng Guizhi , Lv Yan
Published: October 2022

This paper deals with the finite-time inverse optimal output regulation problem for a class of uncertain nonlinear systems that are subjected to an exosystem. The nonlinear systems not only contain external disturbances in the exosystem but also take the unknown nonlinear functions and unmeasured states into account. The output regulation problem is first converted into a stabilization problem through the internal model. Then, fuzzy logic systems (FLSs) are employed to approximate the unknown nonlinear functions. An auxiliary system is constructed and, based on the auxiliary system, a fuzzy state observer is designed to estimate the unmeasured states. Furthermore, a novel adaptive fuzzy finite-time inverse optimal output feedback controller and adaptive law are designed by combining backstepping technology, adaptive control technology, finite-time stability theory, and the inverse optimal control method. The control algorithm ensures that all the signals of the closed-loop system are semiglobally practical finite-time stable (SGPFS), so the newly well-defined cost function that is connected with the auxiliary system can be minimized. Finally, the validity of the approach is confirmed by virtue of the simulation results.