bluuebunny/crossref_metadata_2025 huggingface dataset:
Age and significance of the Fire Bay assemblage: an Ordovician arc fragment within the Clements Markham belt, northwestern Ellesmere Island, Canada
Authors: Koch Megan M. , Faehnrich Karol , McClelland William C. , Crowley James L. , Melchin Michael J. , Beranek Luke P. , Strauss Justin V.
Published: June 2022

The Fire Bay Formation of Trettin (1998), Clements Markham belt, Ellesmere Island, Canada, includes volcanic rocks described as Silurian in age based on Llandovery graptolites in adjacent clastic rocks. New field observations suggest the Llandovery fossils are from packages of the Silurian Danish River and/or Lands Lokk formations that are fault-bounded rather than stratigraphically tied to Ordovician sections that contain a 470.0 ± 0.2 Ma lithic tuff, volcaniclastic units with maximum depositional ages (MDAs) of 466 ± 2 and 462 ± 2 Ma based on detrital zircon, volcanic clasts with ages of 498 ± 6, 478 ± 4, and 477 ± 8 Ma, and Ordovician conodonts and graptolites of Darriwilian and Sandbian age, respectively. Since the Fire Bay Formation of Trettin (1998) lacks a type section and is fault-bounded with ambiguous age relationships, Ordovician volcanic units and fault-bounded clastic rocks correlated with the Hazen Formation are both included in the Fire Bay assemblage following the original interpretations of Trettin and Nowlan (1990). The Fire Bay assemblage records juvenile Ordovician arc magmatism proximal to the Pearya terrane. The adjacent Lands Lokk Formation yields bimodal age peaks at 440–430 and 465 Ma, MDA of 424 ± 3 Ma, and εHf(t) values of −5 to +10. The signature matches Ordovician Pearya units and Silurian circum-Arctic arc sources but there is no evidence for Silurian arc magmatism between the Pearya terrane and Laurentian margin, compatible with Pearya accretion during oblique Ordovician arc collision and Silurian sinistral translation along the northern Laurentian margin.
Orbitides and free polyamines have similarly limited fungicidal activity against three common pathogens of flax in vitro
Authors: Alves da Costa Ribeiro Quintans Isadora Louise , Alves da Costa Ribeiro Souza Juliana , Deyholos Michael K
Published: June 2022

Fusarium oxysporum f. sp. lini and Septoria linicola are causes of fusarium wilt and pasmo in flax ( Linum usitatissimum). Members of a third fungal genus, Alternaria spp., have also been found in fiber and linseed varieties of flax, and are a source of post-harvest spoilage and mycotoxins in a wide range of crops. We performed a microdilution assay and calculated the median effective concentration (EC50) to compare the potency of cyclolinopeptides (CLPs), two polyamines (spermidine and spermine), and the fungicide carbendazimin in the control of three fungi that have potential pathogenic activity ( F. oxysporum, S. linicola, and Alternaria spp), of which the first two are particulary significant causes of disease in flax. For carbendazim, all EC50 values were <0.6 μg/mL. The observed EC50 ranged from 111 to 340 μg/mL for a mixture of six unique CLPs, 109 to 778 μg/mL for spermine, and 21 to 272 μg/mL for spermidine. Spermidine was most effective against Alternaria sp., with an EC50 of 21 μg/mL. The results presented here showed that polyamines and CLPs possess limited antifungal activities against several fungi, with spermidines the most effective naturally occurring compound tested. Our findings do not support the hypothesis that CLPs act as potent antifungals against the three species of pathogens tested.
The deceleration parameter in ‘tilted’ universes: generalising the Friedmann background
Authors: Tsagas Christos G.
Published: June 2022

Large-scale bulk peculiar motions introduce a characteristic length scale, inside which the local kinematics are dominated by peculiar-velocity perturbations rather than by the background Hubble expansion. Regions smaller than the aforementioned critical length, which typically varies between few hundred and several hundred Mpc, can be heavily “contaminated” by the observers’ relative motion. For example, at the critical length – hereafter referred to as the “transition scale”, the sign of the locally measured deceleration parameter can change from positive to negative, while the surrounding universe is still decelerating globally. Overall, distant observers can assign very different values to their local deceleration parameters, entirely because of their relative motion. In practice, this suggests that information selected from regions inside and close to the transition scale hold only locally and they should not be readily extrapolated to the global universe. We show that this principle applies to essentially all Friedmann backgrounds, irrespective of their equation of state and spatial curvature. Put another way, the transition scale and the related effects are generic to linear peculiar-velocity perturbations. This study generalises previous work applied, primarily for reasons of mathematical simplicity, to a perturbed Einstein–de Sitter universe.
Production of $$Z_{cs}$$ in B and $$B_s$$ decays
Authors: Wu Qi , Chen Dian-Yong , Qin Wen-Hua , Li Gang
Published: June 2022

In the present work, we investigate the productions of $$Z_{cs}^+$$

Z

cs

+

in $$B^+$$

B
+

and $$B_s^0$$

B
s
0

decays, where $$Z_{cs}^+$$

Z

cs

+

is assigned as a $$D_s^{+} {\bar{D}}^{*0} + D_s^{*+}{\bar{D}}^0$$

D
s
+

D

¯

∗
0

+

D
s

∗
+

D

¯

0

molecular state. By using an effective Lagrangian approach, we evaluate the branching fractions of $$B^0_s\rightarrow K^- Z^+_{cs}$$

B
s
0

→

K
-

Z

cs

+

and $$B^+\rightarrow \phi Z^{+}_{cs}$$

B
+

→
ϕ

Z

cs

+

via the triangle loop mechanism. The estimated branching fractions of $$B^0_s\rightarrow K^- Z^+_{cs}$$

B
s
0

→

K
-

Z

cs

+

and $$B^+\rightarrow \phi Z^{+}_{cs}$$

B
+

→
ϕ

Z

cs

+

are of the order of $$10^{-4} $$

10

-
4

and $$10^{-5}$$

10

-
5

, respectively. The ratio of these two branching fractions is estimated to be about 4, which indicate that the $$B_s^0 \rightarrow K^\pm Z^\mp _{cs} \rightarrow K^+ K^- J/\psi $$

B
s
0

→

K
±

Z

cs

∓

→

K
+

K
-

J
/
ψ

may be a better process of searching $$Z_{cs}$$

Z

cs

and accessible for further experimental measurements of the Belle II and LHCb Collaborations.
Dunkl–Duffin–Kemmer–Petiau equation in (2 + 1) dimensions: The Dunkl–Bosonic oscillator spinless under Landau levels and Coulomb potential
Authors: Merad A. , Merad M. , Boudjedaa T.
Published: June 2022

In this paper, we consider two fundamental problems in the framework of the Dunkl derivative: the Bosonic oscillator model of spin 0 under magnetic field: Landau levels and the Duffin–Kemmer–Petiau equation with the Coulomb potential. In both cases, we obtain the exact analytical solutions for the bound states in the general case for the different eigenvalues of the reflection operator.
Disease Recognition of Maize Leaf Based on KNN and Feature Extraction
Authors: Li Yawen , Chen Yuexing , Wang Yang
Published: June 2022

Maize is one of the main crops in Shangluo. The maize yield and quality are adversely affected by leaf spot and rust. In order to realize the early prevention of maize leaf spot and rust and avoid problems of environmental pollution induced by the conventional chemical reagents, computer vision technology was proposed for disease detection in this research. The algorithm of [Formula: see text]-means was used to process the image samples obtained from the test field. The healthy area, disease area and background area were separated. Based on the healthy area and disease area, ten parameters were extracted, including four parameters of color characteristic, four parameters of texture feature and two parameters of shape feature, which were taken as the classification criteria in the classification training by KNN algorithm. In total, 200 test image samples (100 samples of leaf spot and 100 samples of maize rust) were sent into the training model for disease identification. The results showed that the algorithm proposed can efficiently and nondestructively identify maize leaf spot and rust based on image segmentation and multi-feature fusion. The method was convenient and environmentally friendly. It can provide technical support for plant protection and can supply research ideas of precise control of crop diseases.
Constraining α-attractor models from reheating
Authors: Germán Gabriel
Published: June 2022

In this paper, we eliminate the parameters originally present in models of inflation of the [Formula: see text]-attractor type in favor of the scalar spectral index [Formula: see text] and the tensor-to-scalar ratio [Formula: see text]. We then write expressions for the number of [Formula: see text]-folds during reheating [Formula: see text]. By imposing reasonable conditions on [Formula: see text], we can restrict [Formula: see text] and [Formula: see text] and in turn, we use these constraints in order to find bounds for cosmological quantities of interest such as the number of [Formula: see text]-folds during inflation and the radiation dominated eras, as well as for the reheating temperature and the running index. The minimum condition that [Formula: see text] must satisfy is [Formula: see text] which we use to constrain the cosmological quantities mentioned above. In particular, we find that the tensor-to-scalar ratio [Formula: see text] (and as a consequence the energy scale of inflation) is bounded from below. We provide figures illustrating the behavior of these quantities as functions of [Formula: see text] for several values of [Formula: see text] and tables containing the bounds so obtained.
The issue of branched Hamiltonian in F(T) teleparallel gravity
Authors: Chakrabortty Manas , Sarkar Kaushik , Sanyal Abhik Kumar
Published: June 2022

As in the case of Lanczos–Lovelock gravity, the main advantage of [Formula: see text] gravity is said to be that it leads to second-order field equations, while [Formula: see text] gravity theory leads to fourth-order equations. We show that it is rather a disadvantage, since it leads to the unresolved issue of ‘Branched Hamiltonian’. The problem is bypassed in [Formula: see text] gravity theory.
APPLICATION OF THE EXTENDED F-EXPANSION METHOD FOR SOLVING THE FRACTIONAL GARDNER EQUATION WITH CONFORMABLE FRACTIONAL DERIVATIVE
Authors: WANG KANG-JIA , SHI FENG , LIU JING-HUA , SI JING
Published: June 2022

In this study, we derive a new fractional Gardner equation with the conformable fractional derivative for the first time. Using the extended F-expansion method, different traveling wave solutions expressed in the form of the hyperbolic solutions such as sech, tanh, csch, coth, sinh and their combination, and the triangular solutions like csc, sec, tan, cot and their combination are obtained. Finally, the solutions are illustrated through the 3D plots. The results strongly prove that the proposed approach is effective and can help us understand the nonlinear problems arising in physics better.
On ergotropic gap of tripartite separable systems
Authors: Wu Ya-Juan , Fei Shao-Ming , Wang Zhi-Xi , Wu Ke
Published: June 2022

Extracting work from quantum system is one of the important areas in quantum thermodynamics. As a significant thermodynamic quantity, the ergotropy gap characterizes the difference between the global and local maximum extractable works. We derive an analytical upper bound of the ergotropic gap with respect to [Formula: see text] tripartite separable states. This bound also provides a necessary criterion for the separability of tripartite states. Detailed examples are presented to illustrate the efficiency of this separability criterion.
Squeezing as a probe of the universality hypothesis
Authors: Mourão P. A. L. , Costa H. A. S. , Carvalho P. R. S.
Published: June 2022

We compute analytically the radiative quantum corrections, up to next-to-leading loop order, to the universal critical exponents for both massless and massive O(N) [Formula: see text] scalar squeezed field theories for probing the universality hypothesis. For that, we employ six distinct and independent methods. The outcomes for the universal squeezed critical exponents obtained through these methods are identical among them and reduce to the conventional ones where squeezing is absent. Although the squeezing mechanism modifies the internal properties of the field, the squeezed critical indices are not affected by the squeezing effect, thus implying the validity of the universality hypothesis, at least at the loop level considered. At the end, we present the corresponding physical interpretation for the results in terms of the geometric symmetry properties of the squeezed field.
Intuitionistic Q-Fuzzy PMS-Subalgebras and Their Level Subsets in a PMS-Algebra
Authors: Derseh Beza Lamesgin , Wondifraw Yohannes Gedamu , Alaba Berhanu Assaye
Published: June 2022

In this paper, we introduce the notion of an intuitionistic Q-fuzzy PMS-subalgebra of a PMS-algebra by using the concept of intuitionistic Q-fuzzy subsets in a PMS-algebra and investigate some of their related properties. We define and study the level subsets of an intuitionistic Q-fuzzy PMS-subalgebra of a PMS-algebra and subsequently characterize an intuitionistic Q-fuzzy PMS-subalgebra in terms of its level subsets. In turn, we prove that every PMS-subalgebra of a PMS-algebra is also the level PMS-subalgebra of an intuitionistic Q-fuzzy PMS-subalgebra of a PMS-algebra.
Electrochemical characterization of CuF2/CNTs cathode materials prepared by a coprecipitation method
Authors: Ji Erte , Huang Juan , Yu Zhiyong , Hu Qingxiao , Liu Hanxing , Lai Caiting , Yuan Zhongzhi
Published: June 2022

Carbon nanotubes (CNTs) were proposed to improve the electrochemical performances of copper fluoride (CuF[Formula: see text] via a coprecipitation method. FE-SEM and TEM results proved that the three-dimensional conductive network was constructed by the addition of CNTs in the composites, in which some CuF2 particles attached to the outside of CNTs, and some of them grew inside the tube. According to the charge–discharge tests, with CNTs content increasing from 0 wt.% to 30 wt.%, the initial discharge capacities of CuF2 increased from 461 to 571 mAh/g, which exceeded the theoretical specific capacity of the CuF2. Moreover, the electrodes with CNTs exhibited better reversibility and rate performance than the bare electrode. CV and EIS results confirmed that the enhancements could be attributed to the inhibition of the electrochemical polarization of the electrode and the improvement on the diffusion coefficient of lithium ion in the electrode by the addition of CNTs.
Prediction of strength of rock after thermal treatment through dielectric property
Authors: Dong Zhihao , Sun Qiang , Zhang Weiqiang
Published: June 2022

This study attempts to establish the feasibility of using the dielectric constant to evaluate the strength of sandstone after being subjected to high temperatures. The dielectric constant of red sandstone was determined after thermal treatment at temperatures ranging from 25 to 1200°C was applied to the rock. At the same time, the porosity, tensile strength, mineral composition and microstructure of the sandstone were determined and analysed. The results shows that the dielectric constant for sandstone decreases rapidly between 500 and 1000°C, increases substantially between 1000 and 1100°C, and then decreases slightly between 1100 and 1200°C. The variation trend of the tensile strength is basically consistent with the dielectric constant. Porosity is the main factor affecting the variations in the sandstone dielectric constant and the tensile strength. The volume expansion of minerals and the melting of the sandstone are the two main reasons for the variation in the porosity of the sandstone. There is a significant correlation between dielectric constant, porosity and tensile strength in the temperature range 25–1000°C. The relationship between dielectric constant and tensile strength increases linearly. Therefore, the dielectric constant can be used as a new non-destructive method to evaluate the strength of sandstone after its exposure to high temperatures.
Innovative use of change detection in large numbers of satellite scenes, with geological applications
Authors: Cole P. , Coetzee H.
Published: June 2022

The large number of remote-sensing datasets available necessitates the development of efficient methods when assessing change between such data. A series of techniques, optimizing the analysis of change detection, specifically on large remote-sensing dataset collections, is demonstrated. Iterative (online) statistical measures for mean and standard deviation give the ability to gain a measure of change over potentially hundreds of datasets without excessive computing power being needed. From this, the coefficient of variation can be used to provide further insight. Using such measures, seasonal change can be detected on outcrop (as opposed to vegetation), illustrating that change detection can be used to further extend a spectral signature for rocks. Twelve Sentinel-2 scenes over a 3 year period were used in this study.

Thematic collection:
This article is part of the Remote sensing for site investigations on Earth and other planets collection available at:
https://www.lyellcollection.org/cc/remote-sensing-for-site-investigations-on-earth-and-other-planets
New information on the Early Devonian acanthodian
Mesacanthus mitchelli
from the Midland Valley of Scotland
Authors: Burrow Carole J. , den Blaauwen Jan L. , Newman Michael J.
Published: June 2022

Mesacanthus mitchelli
is an important taxon in elucidating relationships amongst stem chondrichthyans, being the best known and most abundant of the oldest known acanthodiform acanthodians. Here we note some newly recognized morphological features and describe the histological structure of the endoskeleton and dermal elements. The jaws are preserved as a single layer of irregularly tessellate bone-like mineralizations. A mandibular bone is not present, contrary to previous descriptions. Fin spines have a wide central cavity that is more than half the width at mid-spine level. Prepelvic spines have a very narrow leading edge ridge and a wide open pulp cavity. Head sensory lines are enclosed by a pair of tesserae with a smooth crown, flat base and concave sides, bordering the sensory line canal. The tiny body scales have a relatively large pulp cavity in the embryonic zone. The large size of the eyes relative to the head and body size in
Mesacanthus mitchelli
, the structure and small size of the scales relative to those of other acanthodians of a similar size, and the wide central pulp cavity in the spines, all indicate that the species is likely to have undergone paedomorphism.
The Road to Precision Cosmology
Authors: Turner Michael S.
Published: June 2022

In the past 50 years, cosmology has gone from a field known for the errors being in the exponents to a precision science. The transformation—powered by ideas, technology, a paradigm shift, and culture change—has revolutionized our understanding of the Universe, with the Lambda cold dark matter (ΛCDM) paradigm as its crowning achievement. I chronicle the journey of precision cosmology and finish with thoughts about the next cosmological paradigm.
Dietary Selenium Across Species
Authors: Lei Xin Gen , Combs Gerald F. , Sunde Roger A. , Caton Joel S. , Arthington John D. , Vatamaniuk Marko Z.
Published: June 2022

This review traces the discoveries that led to the recognition of selenium (Se) as an essential nutrient and discusses Se-responsive diseases in animals and humans in the context of current understanding of the molecular mechanisms of their pathogeneses. The article includes a comprehensive analysis of dietary sources, nutritional utilization, metabolic functions, and dietary requirements of Se across various species. We also compare the function and regulation of selenogenomes and selenoproteomes among rodents, food animals, and humans. The review addresses the metabolic impacts of high dietary Se intakes in different species and recent revelations of Se metabolites, means of increasing Se status, and the recycling of Se in food systems and ecosystems. Finally, research needs are identified for supporting basic science and practical applications of dietary Se in food, nutrition, and health across species.
Sex similarities and differences in the reverse and anti-remodeling effect of pressure unloading therapy in a rat model of aortic banding and debanding
Authors: Ruppert Mihály , Barta Bálint András , Korkmaz-Icöz Sevil , Loganathan Sivakkanan , Oláh Attila , Sayour Alex Ali , Benke Kálmán , Nagy Dávid , Bálint Tímea , Karck Matthias , Schilling Oliver , Merkely Béla , Radovits Tamás , Szabó Gábor
Published: June 2022

The present study is the first to assess the role of sex on pressure unloading-induced reverse and anti-remodeling in a rat model of aortic banding and debanding. Our data indicate that female sex is associated with a greater reversibility of fibrosis, fetal gene expression, and proteomic alterations compared with males. Nevertheless, pressure unloading exposes more anti-remodeling effect on the functional level in males, which is attributed to the more rapid functional deterioration in aortic-banded animals.
Mitochondrial DNA Efflux Maintained in Gingival Fibroblasts of Patients with Periodontitis through ROS/mPTP Pathway
Authors: Liu Jia , Wang Yanfeng , Shi Qiao , Wang Xiaoxuan , Zou Peihui , Zheng Ming , Luan Qingxian
Published: June 2022

Mitochondria have their own mitochondrial DNA (mtDNA). Aberrant mtDNA is associated with inflammatory diseases. mtDNA is believed to induce inflammation via the abnormal mtDNA release. Periodontitis is an infectious, oral inflammatory disease. Human gingival fibroblasts (HGFs) from patients with chronic periodontitis (CP) have shown to generate higher reactive oxygen species (ROS) that cause oxidative stress and have decreased mtDNA copy number. Firstly, cell-free mtDNA was identified in plasma from CP mice through qRT-PCR. Next, we investigated whether mtDNA efflux was maintained in primary cultures of HGFs from CP patients and the possible underlying mechanisms using adenovirus-mediated transduction live cell imaging and qRT-PCR analysis. Here, we reported that mtDNA was increased in plasma from the CP mice. Additionally, we confirmed that CP HGFs had significant mtDNA efflux from mitochondria compared with healthy HGFs. Furthermore, lipopolysaccharide (LPS) from Porphyromonas gingivalis can also cause mtDNA release in healthy HGFs. Mechanistically, LPS upregulated ROS levels and mitochondrial permeability transition pore (mPTP) opening by inhibition of pyruvate dehydrogenase kinase (PDK)2 expression, resulting in mtDNA release. Importantly, mtDNA efflux was even persistent in HGFs after LPS was removed and cells were passaged to the next three generations, indicating that mtDNA abnormalities were retained in HGFs in vitro, similar to the primary hosts. Taken together, our results elucidate that mtDNA efflux was maintained in HGFs from periodontitis patients through abnormal ROS/mPTP activity. Therefore, our work indicates that persistent mtDNA efflux may be a possible diagnostic and therapeutic target for patients with periodontitis.
Estimating the Physical Properties of Nanofluids Using a Connectionist Intelligent Model Known as Gaussian Process Regression Approach
Authors: Chen Tzu-Chia , Hammid Ali Thaeer , Akbarov Avzal N. , Shariati Kaveh , Dinari Mina , Ali Mohammed Sardar
Published: June 2022

This work aims to develop a robust machine learning model for the prediction of the relative viscosity of nanoparticles (NPs) including Al2O3, TiO2, SiO2, CuO, SiC, and Ag based on the most important input parameters affecting them covering the size, concentration, thickness of the interfacial layer, and intensive properties of NPs. In order to develop a comprehensive artificial intelligence model in this study, sixty-nine data samples were collected. To this end, the Gaussian process regression approach with four basic function kernels (Matern, squared exponential, exponential, and rational quadratic) was exploited. It was found that Matern outperformed other models with R2 = 0.987, MARE (%) = 6.048, RMSE = 0.0577, and STD = 0.0574. This precise yet simple model can be a good alternative to the complex thermodynamic, mathematical-analytical models of the past.
Electroacupuncture Alleviates Neuropathic Pain through Regulating miR-206-3p Targeting BDNF after CCI
Authors: Tu Wenzhan , Yue Jingjing , Li Xuqing , Wu Qiaoyun , Yang Guanhu , Li Shengcun , Sun Qiangsan , Jiang Songhe
Published: June 2022

Background. Electroacupuncture (EA) has benefits for neuropathic pain. However, the underlying mechanisms are still unknown. The current study explores the underlying mechanisms of EA in neuropathic pain of chronic constriction injury (CCI) rats. Material/Methods. Overall, 126 Sprague-Dawley (200-250 g) rats were divided into nine groups randomly: the sham-operated, CCI, CCI+EA, CCI+sham EA, CCI+NS, CCI+AAV-NC, CCI+AAV-miR-206-3p, CCI+EA+NS, and CCI+EA+AAV-miR-206-3p groups. The animals were sacrificed 14 days postsurgery. Mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL) tests were used to determine differences in neurobehavioral manifestations. qPCR, western blotting, and immunofluorescence (IF) were carried out to detect the expression levels of miR-206-3p, BDNF, BAX/Bcl-2, TNF-α, and IL-6. Nissl staining was measured to observe morphological changes in neurons. Transmission electron microscopy (TEM) was employed to evaluate microscopic changes in dorsal horn synapses. Results. Hyperalgesia was reduced markedly by EA in the CCI model. The expression level of miR-206-3p was elevated, whereas the expression levels of BDNF, BAX/Bcl-2, TNF-α, and IL-6 were decreased in EA-treated CCI rats. However, a miR-206-3p inhibitor partially abrogated the analgesic effect of EA and resulted in poor behavioral performance and the BDNF, BAX/Bcl-2, TNF-α, and IL-6 expression was elevated as well. Conclusions. EA can relieve neuropathic pain by regulating the miR-206-3p/BDNF pathway, thus exerting anti-inflammatory and antiapoptotic effect.
Sirtuin 1 Induces Choroidal Neovascularization and Triggers Age-Related Macular Degeneration by Promoting LCN2 through SOX9 Deacetylation
Authors: Zhao Su , Huang Zhi , Jiang Hao , Xiu Jiangfan , Zhang Liying , Long Qiurong , Yang Yuhan , Yu Lu , Lu Lu , Gu Hao
Published: June 2022

Increasing studies have identified the function of sirtuin-1 (SIRT1) in ocular diseases. Hence, this study is aimed at exploring the potential role of SIRT1 in choroidal neovascularization- (CNV-) induced age-related macular degeneration (AMD) development and the associated mechanism. Expression of SIRT1/SOX9/LCN2 in the hypoxic cells was determined, and their interactions were predicted by bioinformatics websites and followed by the verification by luciferase assay and chromatin immunoprecipitation (ChIP). Their in vitro effects on hypoxic cells concerning cell viability, apoptosis, migration, and angiogenesis were detected through gain- and loss-of-function assays. Besides, their in vivo effect was explored using the established CNV mouse models. Highly expressed LCN2, SOX9, and SIRT1 were observed in hypoxic cells. LCN2 was increased by SOX9 and SIRT1 deacetylated SOX9 to promote its nuclear translocation, which further inhibited the viability of human retinal pigment epithelial cells and promoted cell apoptosis and angiogenesis as well as CNV-induced AMD formation. The relieving role of LCN2 inhibition on CNV-induced AMD without toxicity for mice was also demonstrated by in vivo experiments. Overall, SIRT1 promoted the formation of CNV-induced AMD through SOX9 deacetylation-caused LCN2 upregulation, representing a promising target for CNV-induced AMD management.
Certain Analytic Functions Defined by Generalized Mittag-Leffler Function Associated with Conic Domain
Authors: Attiya Adel A. , Seoudy T. M. , Aouf M. K. , Albalahi Abeer M.
Published: June 2022

In the present paper, we investigate and introduce several properties of certain families of analytic functions in the open unit disc, which are defined byq-analogue of Mittag-Leffler function associated with conic domain. A number of coefficient estimates of the functions in these classes have been obtained. Sufficient conditions for the functions belong to these classes are also considered.
Energy Performance Contracting in a Supply Chain under Cap-and-Trade Regulation and Carbon Tax Policy
Authors: Meng Chengzhen , Zhang Rong , Liu Bin
Published: June 2022

Energy performance contracting (EPC) is a new tool for supply chain members to cooperate in emission reduction. This paper investigates a two-tier supply chain composed of a supplier and a capital-constricted manufacturer with carbon reduction demand under different low-carbon policies (Cap-and-Trade Regulation and Carbon Tax Policy, respectively). The manufacturer is motivated to cooperate with the supplier to reduce carbon emissions through EPC services. Different from other research, the emission reduction decision maker of EPC services in this paper could be any supply chain member. The results show that cap-and-trade regulation and carbon tax policy have the same impact on the optimal pricing and emission reduction decisions in the monopoly supply chain, but the manufacturer’s profit is higher under cap-and-trade regulation. And when the cost-sharing coefficient is within a low range, the emission reduction targets decided by the manufacturer are lower. Otherwise, the targets decided by the supplier are lower. Moreover, supply chain members can obtain higher profits when the reduction targets are determined by themselves, and supply chain coordination under different decision models could be realized through revenue sharing contracts. Considering the total profit of the supply chain, when the cost-sharing rate is within a low range, the supply chain can achieve a Pareto improvement if the supplier determines the emission reduction targets. Otherwise, the reduction targets decided by the manufacturer can realize a Pareto improvement.
Construction of College Aesthetic Education Quality Improvement Model under Big Data Network
Authors: Wang XieHong
Published: June 2022

In view of the importance and urgency of college aesthetic education, this paper constructs a quality improvement model of college aesthetic education under the big data network. Firstly, it puts forward the characteristics of planning, step-by-step, scientific, and centralized aesthetic education in colleges and universities and then expounds the importance of aesthetic education in colleges and universities, including the importance of aesthetic education in spiritual education and in the construction of socialist spiritual civilization. Integrating the functions of data mining under the big data network, using the analytic hierarchy process to construct the improvement index, and carrying out the consistency test at the same time, we can get the improvement index system of aesthetic education quality in colleges and universities. The fuzzy judgment matrix is constructed to obtain the final improvement result. The experimental results show that the constructed model verifies the importance and urgency of aesthetic education in colleges and universities, has a high degree of freedom, and reduces the complexity of quality improvement.
Portfolio Optimization Model for Gold and Bitcoin Based on Weighted Unidirectional Dual-Layer LSTM Model and SMA-Slope Strategy
Authors: Xue Qianyi , Ling Yuewei , Tian Bingwei
Published: June 2022

Portfolio optimization is one of the most complex problems in the financial field, and technical analysis is a popular tool to find an optimal solution that maximizes the yields. This paper establishes a portfolio optimization model consisting of a weighted unidirectional dual-layer LSTM model and an SMA-slope strategy. The weighted unidirectional dual-layer LSTM model is developed to predict the daily prices of gold/Bitcoin, which addresses the traditional problem of prediction lag. Based on the predicted prices and comparison of two representative investment strategies, simple moving average (SMA) and Bollinger bands (BB), this paper adopts a new investment strategy, SMA-slope strategy, which introduces the concept of k-slope to measure the daily ups and downs of gold/Bitcoin. As two typical financial products, gold and Bitcoin are opposite in terms of their characteristics, which may represent many existing financial products in investors’ portfolios. With a principle of $1000, this paper conducts a five-year simulation of gold and Bitcoin trading from 11 September 2016 to 10 September 2021. To compensate for the SMA and BB that may miss buying and selling points, 4 different parameters’ values in the k-slope are obtained through particle swarm optimization simulation. Also, the simulation results imply that the proposed portfolio optimization model contributes to helping investors make investment decisions with high profitability.
A Complete Process of Text Classification System Using State-of-the-Art NLP Models
Authors: Dogra Varun , Verma Sahil , Kavita  , Chatterjee Pushpita , Shafi Jana , Choi Jaeyoung , Ijaz Muhammad Fazal
Published: June 2022

With the rapid advancement of information technology, online information has been exponentially growing day by day, especially in the form of text documents such as news events, company reports, reviews on products, stocks-related reports, medical reports, tweets, and so on. Due to this, online monitoring and text mining has become a prominent task. During the past decade, significant efforts have been made on mining text documents using machine and deep learning models such as supervised, semisupervised, and unsupervised. Our area of the discussion covers state-of-the-art learning models for text mining or solving various challenging NLP (natural language processing) problems using the classification of texts. This paper summarizes several machine learning and deep learning algorithms used in text classification with their advantages and shortcomings. This paper would also help the readers understand various subtasks, along with old and recent literature, required during the process of text classification. We believe that readers would be able to find scope for further improvements in the area of text classification or to propose new techniques of text classification applicable in any domain of their interest.
Secure Data Publishing of Private Trajectory in Edge Computing of IoT
Authors: Liu Xinyao , Cui Baojiang , Fu Junsong , Cheng Zishuai , Song Xuyan
Published: June 2022

Secure data publishing of private trajectory is a typical application scene in the Internet of Things (IoT). Protecting users’ privacy while publishing data has always been a long-term challenge. In recent years, the mainstream method is to combine the Markov model and differential privacy (DP) mechanism to build a private trajectory generation model and publishes the generated synthetic trajectory data instead of the original data. However, Markov cannot effectively model the long-term trajectory data spatio-temporal correlation, and the DP noise results in the low availability of the synthetic data. To protect users’ privacy and improve the availability of synthetic trajectory data, we propose a trajectory generation model with differential privacy and deep learning (DTG). In DTG, we design a private hierarchical adaptive grid method. It divides the geospatial region into several subregions according to the density of positions to realize the discretization of coordinates of the trajectory data. Second, GRU is used to capture the temporal features of the trajectory sequence for good availability, and we generate synthetic trajectory data by predicting the next position. Third, we adopt the optimizer perturbation method in gradient descent to protect the privacy of model parameters. Finally, we experimentally compare DTG with the state-of-the-art approaches in trajectory generation on actual trajectory data T-Drive, Portotaxi, and Swedishtaxi. The result demonstrates that DTG has a better performance in generating synthetic trajectories under four error metrics.
Path Planning of Multirotor UAV Based on the Improved Ant Colony Algorithm
Authors: Qi Duo , Zhang Zhihao , Zhang Qirui
Published: June 2022

Path planning is an important part of the unmanned aerial vehicle (UAV) to realize its autonomous capabilities. Aiming at the shortcomings of the traditional ant colony algorithm-based trajectory planning method, which has slow convergence speed and easy to fall into the local optimum, a path planning method based on the improved ant colony algorithm is proposed. First, a dynamic adjusting factor is added into the heuristic function to improve the directivity of path selection and search speed. Then, the state transition strategy is improved to solve the problem of slow convergence in the initial stage and easy to fall into local optimum in the later stage. Finally, the path inflection point is smoothly optimized through the cubic B-spline curve. Simulation results show that the improved ant colony algorithm can quickly converge to the optimal path and well adapt to the flight requirements of multirotor UAV.
Metabolic Dysfunction in the Regulation of the NLRP3 Inflammasome Activation: A Potential Target for Diabetic Nephropathy
Authors: Zhao Wenli , Zhou Le , Novák Petr , Shi Xian , Lin Chuang Biao , Zhu Xiao , Yin Kai
Published: June 2022

Metabolic dysfunction plays a key role in the development of diabetic nephropathy (DN). However, the exact effects and mechanisms are still unclear. The pyrin domain-containing protein 3 (NLRP3) inflammasome, a member of the nod-like receptor family, is considered a crucial inflammatory regulator and plays important roles in the progress of DN. A growing body of evidence suggests that high glucose, high fat, or other metabolite disorders can abnormally activate the NLRP3 inflammasome. Thus, in this review, we discuss the potential function of abnormal metabolites such as saturated fatty acids (SFAs), cholesterol crystals, uric acid (UA), and homocysteine in the NLRP3 inflammasome activation and explain the potential function of metabolic dysfunction regulation of NLRP3 activation in the progress of DN via regulation of inflammatory response and renal interstitial fibrosis (RIF). In addition, the potential mechanisms of metabolism-related drugs, such as metformin and sodium glucose cotransporter (SGLT2) inhibitors, which have served as the suppressors of the NLRP3 inflammasomes, in DN, are also discussed. A better understanding of NLRP3 inflammasome activation in abnormal metabolic microenvironment may provide new insights for the prevention and treatment of DN.
Parameter Identification with a New Recursive Framework for Wiener–Hammerstein-Like System and Its Application
Authors: Liang Shujun , Zhang Huanlong , Zhang Jie , Wang Fengxian
Published: June 2022

In the process of actual system modeling, many systems exhibit nonlinear characteristics with memory. Thus, the parameter identification problem of the nonlinear system with memory usually appears in the system modeling. This report focuses on the nonlinear system identification of Wiener–Hammerstein-like model with memory hysteresis, in which a new recursive estimation way is introduced. In this algorithm, the estimation bias problem can be improved by introducing a data filtering technique. On the basis of the filtered data, some auxiliary matrices and vectors are proposed. Following this, the identification error variable is introduced by using auxiliary matrices and vectors with an adaptive forgetting factor. Afterward, the identification error variable is integrated into the design of parameter estimation adaptive law with recursive gain structure. By comparison with the classic estimation methods, the proposed algorithm shows an alternative identification algorithm design angle. In addition, it is strictly proved that the parameter estimation error converges to zero under a general excitation condition. Based on the results of indices

M
S
E

, compared with the existing methods, the performance improvements of the proposed method are 33.9 %, 41.26%, and 53.5%, respectively. In terms of indices

P
E
M

, the augmented performances of the developed scheme are 50%, 56.2%, and 68.4%, respectively, in comparison to the available schemes.
A New Useful Exponential Model with Applications to Quality Control and Actuarial Data
Authors: Fayomi Aisha , Tahir M. H. , Algarni Ali , Imran M. , Jamal Farrukh
Published: June 2022

The compounding approach is used to introduce a new family of distributions called exponentiated Bell G, analogy to exponentiated G Poisson. Several essential properties of the proposed family are obtained. The special model called exponentiated Bell exponential (EBellE) is presented along with properties. Furthermore, the risk theory related measures including value-at-risk and expected-shortfall are also computed for the special model. Group acceptance sampling plan is designed when a lifetime of a product or item follows an EBellE model taking median as a quality parameter. The parameters of the proposed model are estimated by considering maximum likelihood approach along with simulation analysis. The usefulness of the proposed model is illustrated by practical means which yield better fits as compared to several exponential related extended models.
A Survey of Machine Learning in Friction Stir Welding, including Unresolved Issues and Future Research Directions
Authors: Chadha Utkarsh , Selvaraj Senthil Kumaran , Gunreddy Neha , Sanjay Babu S. , Mishra Swapnil , Padala Deepesh , Shashank M. , Mathew Rhea Mary , Kishore S. Ram , Panigrahi Shraddhanjali , Nagalakshmi R. , Kumar R. Lokesh , Adefris Addisalem
Published: June 2022

Friction stir welding is a method used to weld together materials considered challenging by fusion welding. FSW is primarily a solid phase method that has been proven efficient due to its ability to manufacture low-cost, low-distortion welds. The quality of weld and stresses can be determined by calculating the amount of heat transferred. Recently, many researchers have developed algorithms to optimize manufacturing techniques. These machine learning techniques have been applied to FSW, which allows it to predict the defect before its occurrence. ML methods such as the adaptive neurofuzzy interference system, regression model, support vector machine, and artificial neural networks were studied to predict the error percentage for the friction stir welding technique. This article examines machine learning applications in FSW by utilizing an artificial neural network (ANN) to control fracture failure and a convolutional neural network (CNN) to detect faults. The ultimate tensile strength is predicted using a regression and classification model, a decision tree model, a support vector machine for defecting classification, and Gaussian process regression (UTS). Machine learning implementation mainly promotes uniformity in the process and precision and maximally averts human error and involvement.
Research on the Development Path of Cultural Heritage Information Visualization from the Perspective of Digital Humanities
Authors: Fang Xixi
Published: June 2022

Art and humanities fields can all benefit from the wide range of digital materials, methodologies, and tools available to researchers. It is the merging of conventional humanities fields like archaeology and history with computer-based tools and techniques as well as other conventional fields like linguistics and literature. Increase in digital cultural heritage data from museums, libraries, and so on requires new modes of analysis rather than standard representations of data. Though the field of online humanities was traditionally seen as a text-based one, researchers in fields like cultural heritage are increasingly using digital representations and visual analysis approaches to study their subjects. A country's cultural heritage (CH) preservation and management are important in preserving and enabling history analysis. There is a growing use of digital and visualization technologies in the documentation and preservation of cultural heritage sites. In this paper, we examine the importance of digital humanities methods, such as 3D reconstruction of cultural heritage and using analysis of variance to develop interactive educational platforms. With the help of the digital framework, CH has been examined and an interactive, open-access network for promoting education, heritage preservation, cultural management, and social responsibilities has been established.
Mechanisms for the Invasion and Dissemination of Salmonella
Authors: Li Qiao
Published: June 2022

Salmonella enterica is a gastroenteric Gram-negative bacterium that can infect both humans and animals and causes millions of illnesses per year around the world. Salmonella infections usually occur after the consumption of contaminated food or water. Infections with Salmonella species can cause diseases ranging from enterocolitis to typhoid fever. Salmonella has developed multiple strategies to invade and establish a systemic infection in the host. Different cell types, including epithelial cells, macrophages, dendritic cells, and M cells, are important in the infection process of Salmonella. Dissemination throughout the body and colonization of remote organs are hallmarks of Salmonella infection. There are several routes for the dissemination of Salmonella typhimurium. This review summarizes the current understanding of the infection mechanisms of Salmonella. Additionally, different routes of Salmonella infection will be discussed. In this review, the strategies used by Salmonella enterica to establish persistent infection will be discussed. Understanding both the bacterial and host factors leading to the successful colonization of Salmonella enterica may enable the rational design of effective therapeutic strategies.
The Application of Artificial Intelligence Wireless Network in Music Contextual Teaching under the New Media Art Perspective
Authors: Huang Min , Xia Hailei
Published: June 2022

Technological growth has resulted in simplifying various tasks previously considered tedious jobs by humans. Artificial intelligence technology has increased and is being appointed to reduce the burden of handling charges by assisting humans in their tasks. The artificial intelligence technology integrated with the wireless network systems is designed to teach music with the help of new media art. New media art is referred to as artwork that deploys new media technologies for its production. Some of the new media technologies are as follows: animation, computer graphics, digital art, video games, sound art, and interactive art. New media art is different from the traditional visual arts, such as paintings, sculptures, and architecture. The new media art is gaining popularity and has become an unavoidable technology. In this article, people will research the application of artificial intelligence and wireless networks in the music context of teaching under the vision of new media art. The integration of AI and wireless network technology with new media art in the music teaching field is more advantageous than the traditional methods of music teaching. The integration model Convolutional Neural Network Art Algorithm (CNNAA) is a CNN algorithm to train and test the music teaching in the context of new media art such as technological involvement such as 4G and 5G for faster data transfer in the wireless communication. The proposed model is compared with the existing fuzzy logic, neural network (NN), and K-Nearest Neighbour (KNN) for the training and testing of the model for an accurate teaching process. The results show that the CNNAA has obtained a higher accuracy of 98% and 99% for training and testing.