bluuebunny/crossref_metadata_2025 huggingface dataset:
053  Multiple Sclerosis Prevalence: Cardiff and Vale population-based cohort
Authors: Hawken Jonathan , Robertson Neil , Tallantyre Emma , Wynford-Thomas Ray , Anderson Valerie , Loveless Sam
Published: May 2022

As treatment options expand for all disease phases of MS, accurate epidemiological data reflecting contemporary patterns of disease by direct clinical assessment remain key to planning and delivering services. This study describes disease frequency and phenotype in a South Wales population on 01/01/2019 according to McDonald 2017 diagnostic criteria.

831 MS cases were identified in a population of 496,413. Prevalence 167/100,000 (95% CI 156–179); females 236/100,000, males 97/100,000, sex ratio 2.5:1 (F:M), mean age 52.6 (range 17–91). Age specific preva- lence was highest in females aged 50–54 (403/100,000). European population standardised prevalence 189/10,000. Disease course: 55.3% relapsing, 34.8% secondary progressive, and 9.9% primary progressive disease. 76.1% had a disability assessment and 36% an interval MR brain within 12 months of prevalence day. EDSS: <4.0 (45.3%), 4.0–5.5 (11.2%), 6.0–7.5 (31.2%), 8–9.5 (12.3%). MR brain: 73% stable; 22% active

(new T2 ± Gd+); the remainder had features of MS but no relevant comparison scan. 39.6% of patients had prior DMT use of which highly effective treatments 17.3%.

These data sets establish a trend of increasing prevalence but remain less than recent estimates from the MS Society (179/100,000) for Wales, and offer baseline estimates of disease course classification and activity to plan services.

drhawken@outlook.com
058  Serum neurofilament-light concentration and real-world outcome in MS
Authors: Anderson Valerie , Bentley Emily , Loveless Sam , Bianchi Lucia , Harding Katharine E , Thomas Ray Wynford- , Giovannoni Gavin , Robertson Neil P , Marta Monica , Tallantyre Emma C
Published: May 2022

Predicting clinical outcome in multiple sclerosis (MS) remains challenging, and biomarkers capable of providing prognostic information would be valuable in shaping therapeutic decisions. Neurofilament light (NfL) measurements have shown promise in predicting clinical outcomes in MS. We evaluated the relationship between serum NfL (sNfL), measured at diagnosis in 164 people with MS, with contemporary disability, short-term (1-year) and medium-term (5-year) clinical outcomes. Analyses were adjusted for relevant confounders. sNfL concentration at diagnosis was modestly but significantly associated with baseline EDSS score (B=0.264, 95% CI 0.043 to 0.485, p=0.020). However, no significant associations were found between baseline sNfL and the incidence of relapse at 12-months, time to sustained accumulation of disability or 5-year change in EDSS. Dichotomising baseline sNfL according to previously cited cut-offs (</> 14.2pg/ml and </> 90th percentile for age) did not change these results. sNfL appears to be of limited clinical utility in predicting future irreversible neurological disability, in a largely treated population, and remains insufficiently validated to shape treatment decisions at the time of diagnosis. Further studies exploring the value of sequential sNfL measurement and developing valid, universally accepted cut-offs are needed before sNfL can be incorporated as a prognostic marker in the clinic.

tallantyreec@cardiff.ac.uk
060  Profiling cases of impaired immunity in neurology using a novel screening test
Authors: Handley Amy , Jolles Stephen , Tallantyre Emma
Published: May 2022

Previous research has indicated that calculated globulin (CG) derived from routine liver function testing can be used as a screening test for low immunoglobulin (Ig) levels. Disease modifying drugs (DMD) are increasingly used in neurology, with the need for a better understanding of their immunosuppressive impact and an ability to screen for complications. In this retrospective audit we identified 32 cases with low CG levels (<23g/L) in 18 neurology patients, occurring between January 2017 and January 2018. Only 4 out of 18 (22%) had their Ig levels checked within 2 months of the abnormal screening (CG) result, but serum Ig data was available at any subsequent time point in 13 out of 18 patients. Of the 13 patients with low CG, 7 (54%) had low serum Igs and 6 (33%) had low lymphocyte levels. Some cases of low Ig were observed in people receiving DMDs that are not specifically targeted at B-cell depletion. Documented infections were present in 83% of the patients with low Ig levels, most commonly urinary tract and chest infections. Calculated globulin is an inexpensive screening tool that has the potential to provide value in neuroinflammatory clinics by detecting secondary antibody deficiency in people receiving DMDs.

HandleyAD1@cardiff.ac.uk
Chitin degradation and its effect on natural transformation: a systematic genetic study in Vibrio parahaemolyticus
Authors: Debnath Anusuya , Miyoshi Shin-Ichi
Published: May 2022

The degradation of polymeric chitin by chitinase liberates soluble N-acetyl glucosamine oligosaccharides (GlcNAcn≥2), a source of nutrition that can also induce a state of natural genetic competence in Vibrio parahaemolyticus. This analysis revealed that among seven predicted chitinases, the synergistic action of VPA0055 (ChiA2), VP0619 (ChiB), and VPA0832 (Cdx) were essential for the robust growth and high transformation frequency on chitin. The endochitinase, ChiA2, and periplasmic chitinase, Cdx were indispensable for chitin degradation. ChiB was not essential for growth on chitin but did have an effect on the rate of chitin degradation. Interestingly, the loss of Cdx drastically reduced growth on insoluble chitin, but growth on soluble GlcNAc5/6 remained same. The utilization of GlcNAc5/6 was only inhibited when there was mutation of Cdx with the other periplasmic chitinases VP0755 and VP2486. This suggests that Cdx might also be involved in extracellular degradation of chitin, in addition to its role as a periplasmic chitinase. Moreover, the periplasmic chitin oligosaccharide-binding protein (CBP) was found to be essential for the efficient utilization of chitin. The CBP was specifically needed for the processing of GlcNAc4-6 during growth on chitin. Overall, this study provides detailed analysis of the machinery behind chitin degradation in V. parahaemolyticus.
Parity from gauge symmetry
Authors: Maiezza Alessio , Nesti Fabrizio
Published: May 2022

We argue that Left-Right parity symmetry $${\mathcal {P}}$$
P
can arise as a discrete remnant of a unified gauge symmetry. The high-energy unification necessarily includes the gauging of the Lorentz symmetry, bringing into the game gravitational interactions, and leading to a gravi-GUT scheme. Parity emerges unbroken below the Planck scale, and can be broken spontaneously at lower energies making contact with the Standard Model. This framework motivates the spontaneous origin of parity violation as in Left-Right symmetric theories with $${\mathcal {P}}$$
P
. The possible unifying gauge groups are identified as $$\mathrm{SO}(1,7)$$

SO
(
1
,
7
)

for gravitational and weak interactions, or $$\mathrm{SO}(7,7)$$

SO
(
7
,
7
)

for a complete unification.
Quaternionic scalar field in the real Hilbert space
Authors: Giardino Sergio
Published: May 2022

Using the complex Klein–Gordon field as a model, we quantize the quaternionic scalar field in the real Hilbert space. The Lagrangian formulation has accordingly been obtained, as well as the hamiltonian formulation, and the energy and charge operators. Conversely to the complex case, the quaternionic quantization admits two quantization schemes, concerning either two or four components. Therefore, the quaternionic field permits a richer structure of states, if compared to the complex scalar field case. Moreover, the quaternionic theory admits as a further novel feature a non-associative algebraic structure in their complex components, something not observed in the complex case.
Backward Asymptotics in S-Unimodal Maps
Authors: De Leo Roberto
Published: May 2022

While the forward trajectory of a point in a discrete dynamical system is always unique, in general, a point can have infinitely many backward trajectories. The union of the limit points of all backward trajectories through [Formula: see text] was called by Hero the “special [Formula: see text]-limit” ([Formula: see text]-limit for short) of [Formula: see text]. In this article, we show that there is a hierarchy of [Formula: see text]-limits of points under iterations of a S-unimodal map: the size of the [Formula: see text]-limit of a point increases monotonically as the point gets closer and closer to the attractor. The [Formula: see text]-limit of any point of the attractor is the whole nonwandering set. This hierarchy reflects the structure of the graph of a S-unimodal map recently introduced jointly by Jim Yorke and the present author.
Bifurcation from an Epidemic Model in the Presence of Memory Effects
Authors: Lahrouz A. , El Mahjour H. , Settati A. , Erriani M. , El Jarroudi H.
Published: May 2022

In this paper, we consider a fractional SIS epidemic system with logistic growth demographic and saturated incidence rate for susceptibles. First, we validate our model by proving the global existence, positivity as well as boundedness of solutions. Then, we give necessary and sufficient conditions for the extinction and persistence of the disease from the population. We also study the local asymptotic stability of the unique positive equilibrium point by analyzing the corresponding characteristic equation. We find that combining logistic growth and saturated incidence for susceptibles can lead the system dynamic behavior to exhibit stability switches. By choosing the growth rate and the carrying capacity of the population as the bifurcation parameters, the stability of the positive equilibrium and the existence of Hopf bifurcation are investigated. Finally, numerical simulations are performed to verify the theoretical results, to fit real-time data from 10 June to 25 November of 2020 and also to predict the number of cumulative cases for COVID-19 in Morocco during 2021.
All Possible Bursting Attractors in the Neighborhood of Hopf Bifurcation Point Under Periodic Excitation
Authors: Gou Junting , Zhang Xiaofang , Xia Yibo , Bi Qinsheng
Published: May 2022

For a vector field with Hopf bifurcation at the origin, when periodic excitation is introduced in which the frequency of the excitation is far less than the natural frequency, bursting oscillations, characterized by the alternations between the large-amplitude and the small-amplitude oscillations, can often be observed. The paper tries to answer the common question of how many types of bursting attractors may appear in such a vector field. Based on the normal form of Hopf bifurcation up to the third order, by regarding the whole exciting term as a slow-varying bifurcation parameter, all possible equilibrium branches of the generalized autonomous system are derived, the bifurcation sets of which divide the parameter space into regions associated with different types of dynamical behaviors. It is found that, there exist totally four possible combinations of the regions that the trajectory of the full system may visit as the slow-varying parameter varies. Accordingly, four qualitatively different behaviors, i.e. periodic symmetric oscillations, periodic symmetric mixed-mode oscillations, fold/Hopf/Hopf/fold and fold-Hopf/fold-Hopf bursting attractors, are presented, the mechanism of which is obtained by overlapping the transformed phase portrait and the equilibrium branches in the generalized autonomous system. Furthermore, the dynamics of the generalized autonomous system in different regions in the parameter space may influence the structures of the bursting oscillations when the trajectory enters the corresponding regions, while the bifurcations at the boundaries of the regions may lead to changes between the quiescent states and spiking states in the bursting attractors.
Weak Bi-Center and Bifurcation of Critical Periods in a Three-Dimensional Symmetric Quadratic System
Authors: Wu Yusen , Yue Haitao
Published: May 2022

This paper focuses on the weak bi-center and bifurcation of critical periods in a class of three-dimensional quadratic systems with a special type of symmetry. Center manifold theory is applied to prove that the system admits either a rough bi-center or a weak bi-center of infinite order (i.e. isochronous bi-center) rather than a weak bi-center of finite order. As a consequence, no bifurcation of critical periods can be generated from the bi-center.
Complex Dynamics of a Three-Species Food Chain Model with Fear and Allee Effect
Authors: Rana Sourav , Bhattacharya Sabyasachi , Samanta Sudip
Published: May 2022

In ecology, predator–prey interactions are very complex in nature. Apart from direct killing, predator induces fear among their prey which affects the life-history, behavioral changes, and reproduction potential of the prey population. On the other hand, the Allee effect has a great impact on regulating the population size, community structure and population dynamics. In the present investigation, we modify the Hastings–Powell (HP) [1991] model by considering the cost of fear in middle predator and the Allee effect in top predator. The stability conditions for the biologically feasible equilibria are derived using linear stability analysis. Considering the cost of fear and the Allee effect as key parameters, the Hopf bifurcation analysis is carried out around the interior equilibrium. The direction of Hopf bifurcation and the stability of the bifurcating periodic solution are determined by applying the normal form theory and center manifold theorem. Our numerical results suggest that the fear effect can stabilize the system. It is observed that high levels of fear among middle predator decrease the population density of top predator. We also observe that if the Allee parameter is increased, then the system becomes stable from chaotic oscillations. However, further increase in the Allee parameter leads to population extinction. We have also drawn several one- and two-parameter bifurcation diagrams which explore rich dynamical behaviors.
Online Judge System: Requirements, Architecture, and Experiences
Authors: Watanobe Yutaka , Rahman Md. Mostafizer , Matsumoto Taku , Rage Uday Kiran , Ravikumar Penugonda
Published: May 2022

The development and operation of Online Judge System (OJS), which is used to evaluate the correctness of programs, is a nontrivial and difficult task due to the various functional and non-functional requirements. However, although many OJSs have been developed and operated, and their usefulness reported, the theory for constructing OJSs has not been sufficiently discussed. In this paper, we present the functional and nonfunctional requirements oriented to OJS as well as demonstrate the internal components and software architecture of an OJS, which has been in operation for over a decade and has evaluated over six million solutions. We also present real-world experiences and challenges encountered during this long journey of our OJS.
Analysis of space-dependent noise functionals with an application to linearly correlated processes
Authors: Chang Yun-Ching , Shih Hsin-Hung
Published: May 2022

Recently, Hida et al.5, 11 introduced a noise of new type, called the Poisson space noise. It depends only on the space parameter, quite different from the time derivative of a Poisson process. In this paper, without employing the Minlos theorem, we shall construct Poisson space noise from the view of its path behavior, which will be realized by the space derivative of an additive process. Then the existence of the associated Poisson space noise measure and its measurable support are studied, and an orthogonal decomposition of square-integrable Poisson space noise functionals is achieved. Accordingly, we define the Segal–Bargmann transform of Poisson space noise functionals. Through the Segal–Bargmann transform, the test–generalized function setting is established. Then the Poisson space noise will be thought of as generalized Poisson space noise functionals. Finally, as an application, we shall study a linearly correlated process driven by Poisson space noises with a kernel function of Volterra type.
Multiscale Modeling of Metal-Ceramic Spatially Tailored Materials via Gaussian Process Regression and Peridynamics
Authors: El Tuhami Ahmed , Xiao Shaoping
Published: May 2022

In this paper, a micro-to-macro multiscale approach with peridynamics is proposed to study metal-ceramic composites. Since the volume fraction varies in the spatial domain, these composites are called spatially tailored materials (STMs). Microstructure uncertainties, including porosity, are considered at the microscale when conducting peridynamic modeling and simulation. The collected dataset is used to train probabilistic machine learning models via Gaussian process regression, which can stochastically predict material properties. The machine learning models play a role in passing the information from the microscale to the macroscale. Then, at the macroscale, peridynamics is employed to study the mechanics of STM structures with various volume fraction distributions.
Application of Herglotz’s variational principle to electromagnetic systems with dissipation
Authors: Gaset Jordi , Marín-Salvador Adrià
Published: May 2022

This work applies the contact formalism of classical mechanics and classical field theory, introduced by Herglotz and later developed in the context of contact geometry, to describe electromagnetic systems with dissipation. In particular, we study an electron in a non-perfect conductor and a variation of the cyclotron radiation. In order to apply the contact formalism to a system governed by the Lorentz force, it is necessary to generalize the classical electromagnetic gauge and add a new term in the Lagrangian. We also apply the k-contact theory for classical fields to model the behavior of electromagnetic fields themselves under external damping. In particular, we show how the theory describes the evolution of electromagnetic fields in media under some circumstances. The corresponding Poynting theorem is derived. We discuss its applicability to the Lorentz dipole model and to a highly resistive dielectric.
Non-homogeneous exoplanets in metric-affine gravity
Authors: Kozak Aleksander , Wojnar Aneta
Published: May 2022

The improved description of the planets’ interior is provided. We examine the modified gravity effects on the Earth-like planets composed of the iron core and silicate mantle. We confirm that the mass–radius relations as well as density profiles differ with respect to the commonly adopted Newtonian models.
2-Trees: Structural insights and the study of Hamiltonian paths
Authors: Renjith P. , Sadagopan N.
Published: May 2022

For a connected graph, a path containing all vertices is known as a Hamiltonian path. For general graphs, there is no known necessary and sufficient condition for the existence of Hamiltonian paths and the complexity of finding a Hamiltonian path in general graphs is NP-Complete. We present a necessary and sufficient condition for the existence of Hamiltonian paths in 2-trees. Using our characterization, we also present a linear-time algorithm for the existence of Hamiltonian paths in 2-trees. Our characterization is based on a deep understanding of the structure of 2-trees and the combinatorics presented here may be used in other combinatorial problems restricted to 2-trees.
Digital Fault-based Built-in Self-test and Evaluation of Low Dropout Voltage Regulators
Authors: Ince Mehmet , Bilgic Bora , Ozev Sule
Published: May 2022

With increasing pressure to obtain near-zero defect rates, there is a need to explore built-in self-test and other non-traditional test techniques for embedded mixed-signal components, such as PLLs, power converters, and data converters. This article presents an extremely low-cost built-in self-test technique for LDOs, specifically designed for fault detection. The methodology relies on exciting the LDO loop at the voltage reference input via a pseudo-random signal with white noise characteristics and observing the response from the output of LDO via all-digital circuitry, thereby inducing low area and performance overhead. The BIST circuit along with an LDO as a device under test is designed in 65nm technology. Fault simulations performed at the transistor level show that all resistive open/short defects in circuit components can be detected even if they do not cause a catastrophic failure in the LDO response. The proposed technique is validated with hardware using off-the-shelf components.
Metabolic signatures of pregnancy-induced cardiac growth
Authors: Fulghum Kyle L. , Smith Juliette B. , Chariker Julia , Garrett Lauren F. , Brittian Kenneth R. , Lorkiewicz Pawel K. , McNally Lindsey A. , Uchida Shizuka , Jones Steven P. , Hill Bradford G. , Collins Helen E.
Published: May 2022

Little is known of the underlying molecular and cellular mechanisms that contribute to pregnancy-induced cardiac growth. Several lines of evidence suggest that changes in cardiac metabolism may contribute. Here, we provide a comprehensive metabolic atlas of the metabolomic, proteomic, and transcriptomic changes occurring in the maternal heart. We show that pregnancy-induced cardiac growth is associated with changes in glycerophospholipid, nucleotide, and amino acid metabolism, with reductions in cardiac glucose catabolism. Collectively, these results suggest that substantial metabolic changes occur in the maternal heart during pregnancy and after pregnancy.
Association between Rheumatoid Arthritis Disease Activity and Risk of Ovarian Malignancy in Middle‐Aged and Elderly Women
Authors: Huang Zhaowei , Tan Linlin , Ling Yi , Huang Fangqin , Ma Wukai
Published: May 2022

Objective. To investigate the risk of ovarian malignancy in middle‐aged and elderly women with rheumatoid arthritis (RA) and its correlation with disease activity. Methods. 219 middle‐aged and elderly (age ≥ 40) female RA patients who were treated at the Department of Rheumatology and Immunology of the Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine from August 2019 to September 2020 were selected. Their general information such as age and medical history was collected. RA disease activity‐related indicators include rheumatoid factor (RF), anticyclic citrullinated peptide antibody (ACPA), ESR, CRP, and ovarian malignancy risk‐related indicators including alpha fetoprotein (AFP), carcinoembryonic antigen (CEA), CA125, CA199, and human epididymis protein 4 (HE4) were detected. According to Risk of Ovarian Malignancy Algorithm (ROMA), they were divided into a low‐risk group (ROMA‐low, premenopausal: ROMA ≤ 11.4%, postmenopausal: ROMA ≤ 29.9%) and a high‐risk group (ROMA‐high, premenopausal: ROMA > 11.4%, postmenopausal: ROMA > 29.9%) for ovarian malignancy. Meanwhile, according to the DAS28‐ESR, they were divided into the general disease activity group (DAS28‐ESR ≤ 5.1) and the high disease activity group (DAS28‐ESR > 5.1). SPSS 25.0 software was used to compare the differences among groups and to analyze the correlation between ovarian malignancy risk and RA disease activity. Results. Compared with the ROMA‐low group, the levels of RF, ACCP, CDAI, SDAI, DAS28‐ESR, and DAS28‐CRP in the ROMA‐high group were significantly increased (P < 0.05). HE4 and ROMA in the high disease activity group were significantly higher than general disease activity group (P < 0.05). Spearman correlation analysis showed that age (r = 0.472), RF (r = 0.221), ACPA (r = 0.156), CDAI (r = 0.226), SDAI (r = 0.221), DAS28‐ESR (r = 0.254), DAS28‐CRP (r = 0.208), medications (r = 0.189), and CA199 (r = 0.250) were correlated with ROMA (P < 0.05). Multivariate regression analysis showed that ESR (OR = 1.11), SDAI (OR = 1.02), DAS28‐ESR (OR = 1.33), DAS28‐CRP (OR = 1.26), and CA199 (OR = 1.03) were independent risk factors for high risk of ovarian malignancy (P < 0.05). Subgroup analysis showed that CA199 is an effect modification factor for DAS28‐ESR (P < 0.05). Conclusion. The risk of ovarian malignancy is significantly increased in middle‐aged and elderly women with high disease activity with rheumatoid arthritis. In clinical, full attention should be paid to the risk of ovarian malignancy in this population. Screening in time, especially in patients with increased DAS28‐ESR and CA199 at the same time, is needed.
Energy Balance Multihop Clustering Routing Protocol for Large-Scale Water Quality Monitoring
Authors: Gong Yulin , Cao Jiannan , Han Chengfei , Liu Yunqing
Published: May 2022

Due to the influence of the environment on the water quality wireless sensor network, it is difficult to replace the node energy at any time, so it must make the most of the little energy available. This work provides a technique that combines cluster head selection, cluster structure creation, and data transmission into one optimal scheme. Firstly, we optimize the cluster head election probability threshold formula on the basis of LEACH and introduce overlap ratio in the competitive mechanism, to avoid excessive overlap between cluster heads. Subsequently, to alleviate the “hot spot” problem caused by multihop, the competitive mechanism of I-LEACH is optimized, which is based on the nonuniform competitive mechanism in the EEUC algorithm when electing the cluster head. Meanwhile, in the structural planning between cluster heads, the optimal path is searched based on the parallelism of genetic algorithm (variable path coding strategy); the combination of I-LEACH and EEUC-IGA, named Energy Balance Multihop Clustering Routing Protocol (BEBMCR), can avoid the emergence of “hot paths” and reduce running time. The simulation results show that BEBMCR still has a longer stable period and higher energy utilization rate under large-scale networks, and node energy consumption is more balanced.
Computational Analysis of the Related Factors of Deep Vein Thrombosis (DVT) Formation in Patients Undergoing Hip Fracture Surgery
Authors: Zhou Yi , Chen Huali , Zhang Yan , Yang Chao , Yi Xiaohui , Liu Shanshan , Zeng Yao
Published: May 2022

A retrospective study was conducted on 51 patients undergoing hip fracture surgery to investigate the factors associated with the formation of deep venous thrombosis (DVT). The independent sample t-test and correlation analysis were used to sort out and analyze the data. The findings are as follows. (1) Different gender samples showed significant differences in the Caprini score and thrombus location. Most DVTs in females are located in the posterior tibial vein and intermuscular veins. The Caprini score of females was significantly higher than that of males. (2) Age displays a positive correlation with DVT, coronary heart disease, hypertension, and different surgical types, respectively. (3) There is a correlation between age and operation duration. (4) Hyperlipidemia and cerebrovascular disease show a positive correlation with DVT. (5) There was a significant negative correlation between the Caprini score and the quantification of D-dimer. This indicates that in this sample, the higher the patients’ Caprini score is, the lower the quantitation of D-dimer will be. (6) Hyperlipidemia and cardiac insufficiency show a positive correlation with cerebrovascular disease. Patients with hyperlipidemia and cardiac insufficiency may also suffer from cerebrovascular diseases.
The Damage Constitutive Model of Sandstone under Water-Rock Coupling
Authors: Jiang J. , Hou Z. M. , Hou K. P. , Lu Y. F. , Sun H. F. , Niu X. D.
Published: May 2022

A constitutive model based on damage mechanics and statistical strength theory for sandstone under water-rock coupling is proposed and verified by laboratory tests and numerical tests. The damage mechanism of sandstone under the coupling action of water and force is clarified based on the microscopic test of sandstone under the coupling action of water and rock in this paper. The stress state of sandstone is determined by analyzing the results of laboratory tests. Based on the energy theory method, the strength criterion of sandstone under the interaction of water and rock is obtained, which is introduced into the statistical damage constitutive model of sandstone considering the interaction of water and rock; thus, a relatively perfect damage constitutive model of sandstone considering the interaction of water and rock is established. Finally, the influence of the number of cycles on the model parameters was further analyzed by analyzing the model parameters and the water-rock coupling test. Compared with the existing test results, the model established in this paper can perfectly reflect the deterioration characteristics of sandstone under the coupling action of water and rock.
Prospective Five-Year Follow-Up of Patients with Schizophrenia Suspected with Parkinson’s Disease
Authors: Yoritaka Asako , Hayashi Tetsuo , Fusegi Keiko , Inami Rie , Hattori Nobutaka
Published: May 2022

Objective. It is difficult to distinguish patients with schizophrenia with neuroleptic-induced parkinsonism (NIP) from those with existing idiopathic Parkinson’s disease when their striatal dopamine transporter uptake is reduced. There is a possibility of misdiagnosis of Parkinson’s disease in patients with schizophrenia as schizophrenia with NIP, which leads to inappropriate treatment. This prospective study aimed at determining the underlying pathophysiology using detailed clinical and psychological assessments. Methods. We enrolled six patients with schizophrenia who had parkinsonism and were diagnosed with Parkinson’s disease according to the Movement Disorder Society Clinical Diagnostic Criteria, except for the fifth absolute exclusion criteria. Results. Five patients had been treated with neuroleptics for 20 years. One patient refused treatment for schizophrenia. All patients had impaired cognitive function at enrolment, olfactory dysfunction, and constipation. All patients were treated with dopaminergic therapy, and their parkinsonism substantially improved; one woman in her 40s experienced a wearing-off effect and dyskinesia. The uptake of dopamine transporter in the striatum decreased by 13%/year during the study period. Conclusion. Some patients with schizophrenia and parkinsonism benefit from dopaminergic therapy. Some of these patients may also exhibit Lewy pathology.
Artificial Intelligence-Based CT Imaging on Diagnosis of Patients with Lumbar Disc Herniation by Scalpel Treatment
Authors: Fan Xiaofei , Qiao Xiaoming , Wang Zhisheng , Jiang Luetao , Liu Yue , Sun Qingshan
Published: May 2022

The aim of this study was to explore the application effect of computed tomography (CT) image based on active contour segmentation algorithm in the treatment of lumbar disc herniation (LDH) with scalpel. 78 patients with LDH were selected and divided into a lateral crypt block treatment group (group A) and a scalpel treatment group (group B) randomly. All the patients were examined by lumbar CT images based on artificial intelligence (AI) algorithm. Then, the clinical efficacy and Japanese orthopedic association (JOA) and visual analogue scale (VAS) scores were compared between the two groups. It was found that the total effective rate in group B was higher (92.31% vs. 84.62%) (

P

 < 0.05). After treatment, the disc height (DH) in group A was obviously lower, and the vertebral body slippage was obviously higher (

P

 < 0.05) than before. After treatment, there were more patients with nerve root location changes, edema, or disappearance in group B (

P

 < 0.05). In contrast with JOA and VAS scores before treatment, both the groups showed obvious differences after treatment, especially group B (

P

 < 0.05). Therefore, the CT images based on the AI algorithm can be used to analyze the treatment effect of LDH, and the scalpel treatment was more effective.
Analysis and Prevention and Control System of Domino Accident Risk Data in Chemical Parks Based on Topological Neural Network
Authors: Sun Lanhui , Cheng Feng , Wang Jing
Published: May 2022

A topologically based neural network algorithm is used to conduct an in-depth study and analysis of domino accident risk data in chemical parks, and this is used to construct a prevention and control system applied to the safety prediction of chemical parks. Firstly, the operating model of the flue gas turbine is expanded and analyzed according to the basic theory of topology, and the object element model is constructed to determine the feature vector and potential risk level. Then, the idea of differential evolution is introduced into the topological neural network to solve the problem that the learning rate and weighting coefficients are difficult to determine, and then the complete DE-ENN algorithm is proposed and tested with the UCI standard data set to verify the effectiveness of the algorithm. Finally, the algorithm is applied to the potential risk identification of the smoke machine operation model, and the experimental results show that the method not only has a simple structure, short running time, and high prediction accuracy but also has excellent generalization ability. For the inherent risk and domino effect risk of chemical equipment in chemical fiber enterprises, the accident risk assessment method based on the protection layer analysis method is proposed; combined with the probability of domino accident and personnel vulnerability model based on the comprehensive analysis of the research results of the allowable risk standard, the allowable risk standard applicable to chemical fiber production enterprises in China is proposed. Given the potential accident risk characteristics of chemical fiber production enterprises, the calculation method of firefighting demand and firefighting capacity of firefighting system is given; the index system of firefighting system emergency response capacity assessment is constructed from three aspects of firefighting system integrity, reliability, and effectiveness, and the assessment model and grade classification standard of firefighting emergency response capacity of chemical fiber production enterprises are determined.
Performance Prediction and Action Performance Analysis of Sports Competitive Events Based on Deep Learning
Authors: Zhang Xiaoying , Lou Jianqiang
Published: May 2022

Physical education performance in primary and secondary school classroom education seems mediocre, and many students treat it as a minor subject. With parents and schools paying attention to physical education, physical education performance is very important now, whether in primary and secondary schools or universities. Nowadays, college students have less and less physical exercise, and sports achievements are one of the index achievements for evaluating scholarships. Many teachers also arrange appropriate physical training reasonably in order to improve students’ sports achievements. Forecasting sports achievements is the key to making scientific sports training plans. According to the study of college students’ group sports achievements, we can predict students’ follow-up learning achievements, collect, sort out, and study students’ sports achievements information regularly, so as to better guarantee the quality of college sports teaching. This paper compares and analyzes the sports achievements of various schools from the aspects of strength, endurance, and sensitivity. At the same time, it compares and analyzes the sports achievements of major universities. Finally, from the perspective of physical education, this paper analyzes and studies the situation of individual schools and then finds out the pedagogical factors that make them achieve excellent physical education results and puts forward the teaching strategies to improve physical education results, as well as the positive influence of physical education teachers on teaching, school physical education results, and students’ physical quality. When teaching courses, use big data mining technology to find qualified students to study the actual teaching needs, recommend an efficient learning curriculum system to students with reference to research conclusions, and give rich material resources. Teachers can teach students in accordance with their aptitude with reference to their usual learning situation, instead of “one size fits all.”
Evaluation Model of College Physical Education Based on Random Matrix Simulation Algorithm
Authors: Liu Jie , Li Wei
Published: May 2022

In this study, improved algorithms based on kernel norm minimization are proposed, namely, standard CUR decomposition and fast CUR decomposition. The CUR decomposition algorithm is to decompose the matrix into three parts, namely, C, U, and R. The matrices C and R are sampled by the column selection algorithm, and then, matrix inversion and matrix multiplication are performed to obtain the cross-matrix U. The matrix C ∗ U ∗ R is an approximation of the original matrix. For the improvement of the singular value algorithm, two random algorithms are proposed, namely, the standard random k-SVD algorithm and the fast random k-SVD algorithm. The main idea is to perform dimensionality reduction and random sampling on the original large-scale data matrix, use the random projection algorithm to obtain an approximation of the original data matrix, then, perform corresponding matrix operations on this approximate matrix, and finally obtain a result similar to the original matrix calculation. Based on the empirical investigation of the current situation of physical education teaching evaluation in a university, this research conducts a questionnaire survey on the student group. Combined with the classification of various majors, the relevant factors of the physical education teaching evaluation system are analyzed and studied, and a more reasonable and unique evaluation model is established. We analyze the dimensions and content of the evaluation index system of physical education, and determine the indicators and weights. From the perspective of the combination of physical education curriculum reform and professional characteristics in a university, this study analyzes the current situation of physical education teaching evaluation and builds a sports teaching evaluation system, so as to deepen the reform of physical education teaching in colleges and universities and create a sports education system with higher vocational characteristics. The teaching evaluation model has certain practical significance.
The Informatization of Small and Medium-Sized Enterprises Accounting System Based on Sensor Monitoring and Cloud Computing
Authors: Deng Jingjing
Published: May 2022

Small and medium-sized enterprises (SMEs) are an indispensable part of the development of the market economy, and they occupy a major position in the national economic system. Nowadays, the information construction of SMEs is becoming more and more important. Having an informationized accounting system can speed up the economic development of SMEs. So, this article designs a new type of accounting system, mainly for SMEs. Therefore, this article is based on sensor monitoring and cloud computing to optimize the informatization construction of the accounting system of SMEs. This paper proposes a cloud computing SOA architecture to build a cloud computing-based accounting system, and then combines the wireless sensor network routing protocol in the wireless sensor network system and the method of measuring the distance of the sensor monitoring node, and the wireless sensor network is applied to the cloud computing-based accounting system. Then, designed the enterprise information construction investigation experiment to formulate the rules applicable to SMEs, and then tested the data detection ability of the new accounting system by testing the performance of the sensor network protocol. Finally, the data obtained from the analysis of the weight of the enterprise cloud service is used to optimize the new accounting system, and the performance of the final optimized accounting system is compared with the traditional system. Experiments show that the accuracy of data monitoring by an accounting system based on sensor monitoring and cloud computing has increased by 13.84% compared to traditional accounting systems; compared with the traditional accounting system, the data processing efficiency of the accounting system based on sensor monitoring and cloud computing has increased by 14.63%.
Optimal Emergency Ordering Policy for Inventory with a Random-Ending-Time Supply Disruption
Authors: Hu Man , Guo Libin
Published: May 2022

This paper considers the emergency ordering strategy for the classical economic ordering quantity inventory system with a supply disruption. For situations where the ending time of supply disruption is stochastic and the purchase price increases over time during that period, we develop an emergency ordering optimization model based on maximizing retailer’s profits. Through modeling analysis in various situations, the closed-form solution of the model is obtained, and the optimal emergency ordering strategy is provided for retailers. Numerical experiments verify the effectiveness of the model and the influence of related parameters on the optimal ordering strategy.
LncRNA PVT1 Promotes Cell Proliferation, Invasion, and Migration and Inhibits Cell Apoptosis by Phosphorylating YAP
Authors: Ji Kaiyue , Zhang Qi , Song Wen , Mao Tao , Guo Jing , Min Congcong , Zhang Cuiping , Tian Zibin , Li Xiaoyu
Published: May 2022

Gastric cancer (GC) as a serious global health problem is a threat to human longevity. Plasmacytoma variant translocation 1 (PVT1) participates in the formation and progression of various cancers, including GC. The aim of this study is to investigate the mechanism underlying the functions of PVT1 and explore a novel target for the diagnosis and treatment of GC. Analysis of the TCGA dataset using the R software identified that the lncRNA PVT1 was greatly upregulated in GC tissues. Twenty pairs of GC and adjacent normal tissues were acquired from patients with GC, and the expression of PVT1 was evaluated using RT-qPCR. Furthermore, PVT1 expression was knocked down in GC cells using siRNA, and the GC cells were divided into control, negative control (NC), and siRNA groups. Cell proliferation ability was analyzed using Cell Counting Kit-8 (CCK8) and colony formation assays, whereas cell migration and invasion ability were investigated through wound healing and Transwell assays. Moreover, Western blotting was used to analyze the expression of Yes-associated protein (YAP) and epithelial-to-mesenchymal transition (EMT) proteins. We also found that PVT1 and YAP expressions were upregulated in the GC tissues compared with those in the adjacent nontumor tissues. Knockdown of PVT1 was found to inhibit the proliferation, invasion, and migration and promote apoptosis of GC cells. Furthermore, knockdown of PVT1 downregulated YAP and promoted phosphorylation of YAP, suggesting that PVT1 exerts actions on GC cells by targeting YAP and inhibits cell apoptosis in vitro. The EMT process was also inhibited by the knockdown of PVT1. In summary, lncRNA PVT1 facilitated cell proliferation, invasion, and migration and suppressed cell apoptosis by targeting YAP. This study suggests that the expressions of PVT1 and YAP could be used for the early detection of GC and the occurrence and development of GC could be inhibited by interfering the interaction of PVT1 and YAP, which will provide new insights for the diagnosis, treatment, and prognosis of GC.
Phytochemical, Antioxidant, Anti-Inflammatory, and Thrombolytic Properties of Cleisomeria lanatum (Lindl.) Lindl. ex G. Don
Authors: Rahman Minhajur , Surag Abu Taleb , Begum Roxy , Hossain Tusher Md. Shakhuat , Huda Mohammed Kamrul
Published: May 2022

For the first time, Cleisomeria lanatum (family: Orchidaceae) has been investigated for its phytochemical, antioxidant, anti-inflammatory, and thrombolytic properties. All phytochemicals studied were identified in varying degrees during qualitative screening. In quantitative screening, a maximum of 106.02 ± 0.08 mg/g alkaloids (root), 179.67 ± 8.83 mg/g phenols (stem), 17.34 ± 0.88 mg/g flavonoids (stem), 73.67 ± 1.76 mg/g tannins (stem), and 180.04 ± 0.02 μg/mL proteins (root) were detected. Antioxidant, anti-inflammatory, and thrombolytic properties were investigated using a free-radical scavenging assay, heat-induced albumin denaturation assay, and blood clotting inhibition assay. The root extracts had the most effective antioxidant (IC50 = 67.98 μg/mL) and anti-inflammatory (IC50 = 60.86 μg/mL) properties, whereas the stem extracts had the most effective thrombolytic property (IC50 = 163.8 μg/mL). The bioactivities studied also had a significant positive relationship (r = 0.9;

p
 
<
 
0.05

) with the amount of phenolics and tannins.
Selection of Stationarity Tests for Time Series Forecasting Using Reliability Analysis
Authors: Bawdekar Advait Amol , Prusty B. Rajanarayan
Published: May 2022

Stationarity is an essential concept in time series forecasting. A reliable stationarity test that yields unbiased test outcomes is vital as it is the gateway before a suitable forecasting model development. Renewable generation time series is inherently seasonal, comprising trend components, and often volatile. These characterizing facets alongside time series length tend to bias stationarity tests’ outcomes. A critical comparison study to check the tests’ reliability is carried out in this paper using different synthetic data required for the case-to-case analysis. Based on the tests’ working, reliabilities are analyzed for different time series lengths and group sizes, varying from 200 to 1000 with an increment of 200. This provides information about changes in reliabilities of the tests for various time series lengths or group sizes. This comprehensive comparison report with a necessary set of well-illustrated figures, table, and thorough explanation of the obtained results is expected to help novice readers to select an apt combination of tests for stationarity check for renewable generation applications.
An Empirical Study on the Inequality in Health and Healthcare in China’s Medical Reform
Authors: Li Jing-wei , Jin Feng
Published: May 2022

To make clear what role the Urban and Rural Residents Basic Medical Insurance (URRBMI) plays in the inequality in health and healthcare, this article combines the time‐varying DID method with the concentration index to conduct an empirical study. We find that the URRBMI improves health but expands health inequality among different income groups, with its contribution growing over time. Besides, the URRBMI significantly promotes healthcare utilization, reduces the medical burden, and narrows the gap among different income groups, though this effect is generally downward. These findings help clarify what deserves more attention to enlarge benefits and reduce inequality in this medical reform and provide policy implications for policymakers. Increasing investment in medical resources and constructing the hierarchical medical system and medical treatment combination may make a difference.