bluuebunny/crossref_metadata_2025 huggingface dataset:
Long-term effect of elevated air humidity on seasonal variability in diurnal leaf conductance and gas exchange in silver birch
Authors: Kupper Priit , Rohula-Okunev Gristin , Tullus Arvo , Tulva Ingmar , Merilo Ebe , Sellin Arne
Published: January 2022

Environmental conditions and photoperiod length drive the seasonal variability of gas exchange in plants. Still, little is known about trees’ adaptation to climate change, expressed as a delay in decreasing photosynthetic capacity at the end of the growing season. We investigated the effect of elevated air humidity (RH) and sampling period (from July to September) on the variability of net photosynthesis (An), dark respiration (R), daytime (gl_day) and night-time (gl_night) leaf conductance, an index of leaf chlorophyll content (SPAD), and An:SPAD ratio in cut shoots of silver birch (Betula pendula Roth). Measurements of cut shoots were conducted in a climate chamber to eliminate the direct effect of field conditions. The An, An:SPAD ratio, and gl_day were higher in the humidification treatment (H) than in the control (C) (P < 0.05) in autumn. The R was higher in the control than in the humidification treatment across the study period. The gl_night increased considerably in September in both treatments (P < 0.05) and was significantly correlated with R. Our findings suggest that autumnal leaf conductance and gas exchange in silver birch are considerably influenced by long-term exposure to elevated RH and are probably related to a complex of leaf senescence processes, including nitrogen retranslocation.
Quantitative magnetic resonance imaging of Scots pine seeds and the assessment of germination potential
Authors: Tuomainen Teemu V. , Himanen Katri , Helenius Pekka , Kettunen Mikko I. , Nissi Mikko J.
Published: January 2022

The availability of Scots pine seeds (Pinus sylvestris L.) with high germinability is necessary for artificial forest regeneration. In this work, Scots pine seed orchard seeds were magnetic resonance (MR) imaged to noninvasively investigate the association of the anatomical images and quantitative relaxation times with the structure and germinability of the seeds. Relaxation time differences compared to the germination day were also investigated. The average whole seed relaxation times T1 (two methods), T2, and [Formula: see text] were 430 ± 59, 660 ± 20, 14 ± 1.7, and 0.83 ± 0.33 ms, respectively. It was observed that the seed structures had statistically significant (p < 0.05) differences in relaxation times, while no differences could be observed in relation to the rate of seed germination. Furthermore, the obtained data were compared to radiographs. Empty seeds were observed to provide a minimal MRI signal, whereas intact and mechanically damaged seeds provided a profound signal with distinguishable structures. The mechanically hardest region, i.e., the seed coat, was not visible in MRI as opposed to radiographs. Some seeds determined to be mechanically damaged by radiography were able to germinate, and mechanical faults could be distinguished in MRI. As such, MRI can be seen complementary to the currently used methods to optimize seed sorting and to interpret germination potential.
Dimensional regularization for the particle transition amplitude in curved space
Authors: Corradini Olindo , Crispo Luigi , Muratori Maurizio
Published: January 2022

We compute the perturbative short-time expansion for the transition amplitude of a particle in curved space time, by employing dimensional regularization (DR) to treat the divergences which occur in some Feynman diagrams. The present work generalizes known results where DR was applied to the computation of one-loop effective actions, which in the worldline approach are linked to particle path integrals on the circle, i.e. with periodic boundary conditions. The main motivation of the present work comes from revived interest in particle transition amplitudes in curved space-times, due to their use in the recently proposed worldline quantum field theory (in curved space-time).
Regulating life after death: how mechanical communication mediates the epithelial response to apoptosis
Authors: Bonfim-Melo Alexis , Duszyc Kinga , Gomez Guillermo A. , Yap Alpha S.
Published: January 2022

It is increasingly evident that cells in tissues and organs can communicate with one another using mechanical forces. Such mechanical signalling can serve as a basis for the assembly of cellular communities. For this to occur, there must be local instabilities in tissue mechanics that are the source of the signals, and mechanisms for changes in mechanical force to be transmitted and detected within tissues. In this review, we discuss these principles using the example of cell death by apoptosis, when it occurs in epithelia. This elicits the phenomenon of apical extrusion, which can rapidly eliminate apoptotic cells by expelling them from the epithelium. Apoptotic extrusion requires that epithelial cells detect the presence of nearby apoptotic cells, something which can be elicited by the mechanotransduction of tensile instabilities caused by the apoptotic cell. We discuss the central role that adherens junctions can play in the transmission and detection of mechanical signals from apoptotic cells.

Graphical abstract
A Hybrid Model Combining Formulae with Keywords for Mathematical Information Retrieval
Authors: Shen Yuqi , Chen Cheng , Dai Yifan , Cai Jinfang , Chen Liangyu
Published: January 2022

Formula retrieval is an important research topic in Mathematical Information Retrieval (MIR). Most studies have focused on formula comparison to determine the similarity between mathematical documents. However, two similar formulae may appear in entirely different knowledge domains and have different meanings. Based on N-ary Tree-based Formula Embedding Model (NTFEM, our previous work in [Y. Dai, L. Chen, and Z. Zhang, An N-ary tree-based model for similarity evaluation on mathematical formulae, in Proc. 2020 IEEE Int. Conf. Systems, Man, and Cybernetics, 2020, pp. 2578–2584.], we introduce a new hybrid retrieval model, NTFEM-K, which combines formulae with their surrounding keywords for more accurate retrieval. By using keywords extraction technology, we extract keywords from context, which can supplement the semantic information of the formula. Then, we get the vector representations of keywords by FastText N-gram embedding model and the vector representations of formulae by NTFEM. Finally, documents are sorted according to the similarity between keywords, and then the ranking results are optimized by formula similarity. For performance evaluation, NTFEM-K is not only compared with NTFEM but also hybrid retrieval models combining formulae with long text and hybrid retrieval models combining formulae with their keywords using other keyword extraction algorithms. Experimental results show that the accuracy of top-10 results of NTFEM-K is at least 20% higher than that of NTFEM and can be 50% in some specific topics.
INVESTIGATING FRACTAL-FRACTIONAL MATHEMATICAL MODEL OF TUBERCULOSIS (TB) UNDER FRACTAL-FRACTIONAL CAPUTO OPERATOR
Authors: QU HAIDONG , UR RAHMAN MATI , ARFAN MUHAMMAD , LAOUINI GHAYLEN , AHMADIAN ALI , SENU NORAZAK , SALAHSHOUR SOHEIL
Published: January 2022

This paper discussed a new operator known as a fractal-fractional (FF), considered in the Caputo sense. We have investigated the fractional mathematical model of Tuberculosis (TB) disease under FF Caputo derivative. We have provided the existence and uniqueness for the appropriate system by using Banach and Leray–Schauder theorem and for the stability of the model, we have used the Ulam–Hyers approach. Applying the methods of basic theorems of FF calculus (FFC) and the iterative numerical techniques of fractional Adams–Bashforth method for approximate solution. For the simulation of the model, we have considered different values for fractional order [Formula: see text] and fractal dimension [Formula: see text] and compared the results with integer order for real data. The FFC technique is applied as a beneficial technique to know about the real-world problem and also to control the whole world situation of the aforesaid pandemic in the different continents and territories of the world. This new operator, FF in the form of Caputo derivative, gives better results than ordinary integer order. Several results have been discussed by taking the different fractal dimensions and arbitrary order.
QUALITATIVE ANALYSIS OF SEIRS ENDEMIC MODEL BOTH FROM PDEs AND ODEs PERSPECTIVE
Authors: ZHANG LEI , SAEED TAREQ , WANG MIAO-KUN , AAMIR NUDRAT , IBRAHIM MUHAMMAD
Published: January 2022

An age-structured susceptible–exposed–infected–recovered–susceptible (SEIRS) endemic model is proposed in this analysis utilizing the tools of partial differential equations. Because of different outflows and inflows that are lopsided by migration and demographics factors, the population is supposed to be not constant. To demonstrate that the model is well-posed, an abstract Cauchy problem is developed from the proposed system. The simple reproduction number [Formula: see text] is used to analyze the local and global behavior of the disease-free equilibrium. The disease present equilibrium point is shown to exist and be stable locally under appropriate assumptions and conditions. We consider the age-free parameters and the problem is converted into an ordinary differential equations (ODEs) model. The ODEs model is investigated for disease-free and endemic equilibria and the global stability of each equilibrium is presented therein. A few simulations are carried out and discussed at the end of the paper to explain the central theorem of the study.
ANALYSIS OF A FRACTIONAL ORDER SMOKING MODEL WITH RELAPSE AND HARMONIC MEAN TYPE INCIDENCE RATE UNDER 𝒜ℬ𝒞 OPERATOR
Authors: ZHANG LEI , SAEED TAREQ , WANG MIAO-KUN , AAMIR NUDRAT , IBRAHIM MUHAMMAD
Published: January 2022

This paper investigates the newly constructed fractional order (FO) smoking model with relapse and harmonic mean type incidence rate under the fractional operator [Formula: see text]. Furthermore, for the model considered, the existence results and uniqueness of the solution are established with the help of the fixed point theory approach. The stability of the model is proven with the help of Ulam–Hyres approach by considering small perturbation in the problem. The iterative FO Adams–Bashforth technique is considered for obtaining the numerical solution. Moreover, the established scheme is simulated against the available data for some smoking communities where various types of potential, moderate and quit smokers are living. However, different fractional orders are used for simulation and it is evident through the results that FO converges to integer order as order is increased. Moreover, smoking may also be controlled through education, employment and the awareness of its harmfulness by doctors and their dosage of some drugs.
NUMERICAL COMPUTING TO SOLVE THE NONLINEAR CORNEAL SYSTEM OF EYE SURGERY USING THE CAPABILITY OF MORLET WAVELET ARTIFICIAL NEURAL NETWORKS
Authors: WANG BO , GÓMEZ-AGUILAR J. F. , SABIR ZULQURNAIN , RAJA MUHAMMAD ASIF ZAHOOR , XIA WEI-FENG , JAHANSHAHI HADI , ALASSAFI MADINI O. , ALSAADI FAWAZ E.
Published: January 2022

In this study, a novel heuristic computing technique is presented to solve bioinformatics problem for the corneal shape model of eye surgery using Morlet wavelet artificial neural network optimized by the global search schemes, i.e. genetic algorithm (GA), local search technique, i.e. sequential quadratic programming (SQP) and the hybrid of GA-SQP. To measure the performance of the design network configuration, different cases based on nonlinear second-order differential equations governing the corneal model have been solved effectively. The numerical procedure of Adams method is implemented for the comparison purpose of the presented outcomes of the stochastic solver, which shows the worth of the present scheme based on accuracy and convergence with negligible values of absolute error in the range 10[Formula: see text] to 10[Formula: see text]. Furthermore, statistical measures are presented based on “mean absolute error”, “root mean square error” and “coefficient of Theil’s inequality” which additionally endorsed consistently accurate performance of integrated intelligent computing framework for solving the corneal shape model.
COMPUTATIONAL STUDY OF FRACTIONAL-ORDER VECTOR BORNE DISEASES MODEL
Authors: BEDI PALLAVI , KHAN AZIZ , KUMAR ANOOP , ABDELJAWAD THABET
Published: January 2022

In this paper, we solve a nonlinear fractional-order model for analyzing the dynamical behavior of vector-borne diseases within the frame of Caputo-fractional derivative. The proposed mathematical model advances the existing integer-order model on transmission and cure of vector-borne diseases. The existence and uniqueness of the solutions of the fractional-order model are proved using the Banach contraction principle. We investigate the local asymptomatic stability for the obtained disease-free equilibrium point and global stability for the proposed model in the sense of Ulam–Hyers stability criteria, respectively. Besides that, we obtain a numerical solution for the projected model using the Corrector-Predictor algorithm. Finally, to illustrate the obtained theoretical results, we perform numerical simulations for different values of fractional-order derivative and make a comparison with the results of the integer-order derivative.
NUMERICAL ANALYSIS OF NEWLY DEVELOPED FRACTAL-FRACTIONAL MODEL OF CASSON FLUID WITH EXPONENTIAL MEMORY
Authors: MURTAZA SAQIB , KUMAM POOM , AHMAD ZUBAIR , SEANGWATTANA THIDAPORN , ALI IBN E.
Published: January 2022

In the current research community, certain new fractional derivative ideas have been successfully applied to examine several sorts of mathematical models. The fractal fractional derivative is a novel concept that has been proposed in recent years. In the presence of heat generation, however, it is not employed for the free convection Couttee flow of the Casson fluid model. The core interest of the present analysis is to examine the Casson fluid under the influence of heat generation and magnetic field. The flow of the Casson fluid has been considered in between two vertical parallel plates. The distance between the plates is taken as [Formula: see text]. The linear coupled governing equation has been developed in terms of classical PDEs and then generalized by employing the operator of the fractal-fractional derivative with an exponential kernel. The numerical solution of the proposed problem has been found employing the finite-difference technique presented by Crank–Nicolson. The Crank–Nicolson finite difference scheme has the advantage of being unconditionally stable and can be applied directly to the PDEs without any transformation to ODEs. This technique in sense of exponential memory has been revealed to be unreported in the literature for such a proposed problem. For graphical analysis, the graphs of velocity profile and thermal field have been plotted in response to several rooted parameters. For comparative analysis, the graphs for the parameter of fractal-fractional, fractional, and classical order have also been plotted. From the analysis, it has been found that the fractal-fractional order model has a large memory effect than the fractional-order and classical model due to the fractal order parameter.
Hybrid Isolation Strategy for Seismically Isolated Multi-Tower Building with a Large Podium
Authors: Zhang Shangrong , Hu Yuchen , Liu Xinyu , Tan Ping , Guo Xiangjun
Published: January 2022

The Compositive Passive Control method (CPC method) of “interlayer seismic isolation” + “shock absorption between adjacent towers” is applied to Multi-Tower Building (MTB) with a large podium. Taking the total vibration energy of the structure as the optimal control objective, the response expressions of a multi-DOF layer shear model and an equivalent single-DOF layer shear model are derived. The rationality of the equivalent model is demonstrated from the perspective of mode characteristics and time history response. Based on the Kanai–Tajimi spectral seismic motion model, the control effect and the optimal control parameters of the CPC method are studied. Compared with the conventional seismic scheme and the interlayer seismic isolation scheme, the influence of the CPC method on the structure natural vibration characteristics and dynamic response under different parameters of the connecting control device is discussed and analyzed. The numerical analysis proves that the CPC method provides a significant damping effect compared with the interlayer seismic isolation scheme. It maintains the advantages of the interlayer seismic isolation scheme and reduces the defect of the response amplification caused by the interlayer isolation. This analysis constitutes a good reference for the follow-up study of the CPC method of MTB.
Design of Yaw Controller for a Small Unmanned Helicopter Based on Improved ADRC
Authors: Huang Linjie , Pei Hailong
Published: January 2022

Yaw control is significant to the attitude control of small unmanned helicopters (SUHs). Since the existing robust control method cannot be applied to the SUH with unknown dynamics and disturbances, this paper proposes an improved active disturbance rejection control (IADRC) to solve the problem. The IADRC obtains the optimal solution of the actuator gain ([Formula: see text]) by gradient descent. Besides, this paper summarizes some experiences during the tuning process of ADRC, which significantly reduces the difficulty of designing ADRC. Finally, the experimental results show that the proposed method is better than the traditional PID in robust and tracking control performance.
Quantitative prediction of prospectivity for Pb–Zn deposits in Guangxi (China) by back-propagation neural network and fuzzy weights-of-evidence modelling
Authors: Xie Shuyun , Huang Ning , Deng Jun , Wu Songle , Zhan Mingguo , Carranza Emmanuel John M. , Zhang Yuepeng , Meng Fanxing
Published: January 2022

One significant geochemical data processing aim is to delineate anomalies associated with mineral deposits. In areas with strong surface weathering, the accumulation centres of surface geochemical anomalies are often not completely matched with locations of mineral deposits. This affects anomaly interpretation and mineral prospectivity prediction. In order to solve this challenging problem, quantitative prediction of mineral prospectivity based on multi-information fusion techniques has been one of the research hotspots in the field of data analysis in recent years. This study first summarized the geological background and metallogenic control factors of each tectonic unit in Guangxi, and then analysed the relationship between Pb–Zn deposits and Pb–Zn geochemical anomalies from 60 767 geochemical stream sediment samples. Based on the re-classified geochemical element contents, gravity, aeromagnetic data and fault, magmatic rock, magmatic rock and fault intersection buffer data as input layers, together with 302 Pb–Zn ore occurrences selected as training data sets, quantitative prediction of prospectivity for Pb–Zn ore deposits in the study area was carried out using back-propagation neural network and fuzzy weights-of-evidence methods. It was found that the Pb–Zn mineral prospectivity prediction areas based on multi-information fusion techniques can eliminate effectively the influence of secondary accumulation of elements during weathering of carbonate rocks on the recognition of deposit-associated stream sediment geochemical anomalies, and identify effectively the mineral resources closely related to rock mass and structure distribution. These analyses reveal the metallogenic regularity of Pb–Zn deposits from the perspective of data mining based on machine learning and geographical information system multi-information fusion for delineation of prospective metallogenic target areas. The purpose here was to provide new ideas for reducing the effects of secondary weathering of extensive carbonate rocks in Guangxi, and in other regions with similar landscapes, on mineral prospectivity prediction.

Thematic collection:
This article is part of the Applications of innovations in geochemical data analysis collection available at:
https://www.lyellcollection.org/cc/applications-of-innovations-in-geochemical-data-analysis
ECCNAS: Efficient Crowd Counting Neural Architecture Search
Authors: Wang Yabin , Ma Zhiheng , Wei Xing , Zheng Shuai , Wang Yaowei , Hong Xiaopeng
Published: January 2022

Recent solutions to crowd counting problems have already achieved promising performance across various benchmarks. However, applying these approaches to real-world applications is still challenging, because they are computation intensive and lack the flexibility to meet various resource budgets. In this article, we propose an efficient crowd counting neural architecture search (ECCNAS) framework to search efficient crowd counting network structures, which can fill this research gap. A novel
search from pre-trained
strategy enables our cross-task NAS to explore the significantly large and flexible search space with less search time and get more proper network structures. Moreover, our well-designed search space can intrinsically provide candidate neural network structures with high performance and efficiency. In order to search network structures according to hardwares with different computational performance, we develop a novel latency cost estimation algorithm in our ECCNAS. Experiments show our searched models get an excellent trade-off between computational complexity and accuracy and have the potential to deploy in practical scenarios with various resource budgets. We reduce the computational cost, in terms of multiply-and-accumulate (MACs), by up to 96% with comparable accuracy. And we further designed experiments to validate the efficiency and the stability improvement of our proposed
search from pre-trained
strategy.
Mask or Non-Mask? Robust Face Mask Detector via Triplet-Consistency Representation Learning
Authors: Yang Chun-Wei , Phung Thanh Hai , Shuai Hong-Han , Cheng Wen-Huang
Published: January 2022

In the absence of vaccines or medicines to stop COVID-19, one of the effective methods to slow the spread of the coronavirus and reduce the overloading of healthcare is to wear a face mask. Nevertheless, to mandate the use of face masks or coverings in public areas, additional human resources are required, which is tedious and attention-intensive. To automate the monitoring process, one of the promising solutions is to leverage existing object detection models to detect the faces with or without masks. As such, security officers do not have to stare at the monitoring devices or crowds, and only have to deal with the alerts triggered by the detection of faces without masks. Existing object detection models usually focus on designing the CNN-based network architectures for extracting discriminative features. However, the size of training datasets of face mask detection is small, while the difference between faces with and without masks is subtle. Therefore, in this article, we propose a face mask detection framework that uses the context attention module to enable the effective attention of the feed-forward convolution neural network by adapting their attention maps’ feature refinement. Moreover, we further propose an anchor-free detector with Triplet-Consistency Representation Learning by integrating the consistency loss and the triplet loss to deal with the small-scale training data and the similarity between masks and occlusions. Extensive experimental results show that our method outperforms the other state-of-the-art methods. The source code is released as a public download to improve public health at
https://github.com/wei-1006/MaskFaceDetection
.
Rectified Meta-learning from Noisy Labels for Robust Image-based Plant Disease Classification
Authors: Zhai Deming , Shi Ruifeng , Jiang Junjun , Liu Xianming
Published: January 2022

Plant diseases serve as one of main threats to food security and crop production. It is thus valuable to exploit recent advances of artificial intelligence to assist plant disease diagnosis. One popular approach is to transform this problem as a leaf image classification task, which can be then addressed by the powerful convolutional neural networks (CNNs). However, the performance of CNN-based classification approach depends on a large amount of high-quality manually labeled training data, which inevitably introduce noise on labels in practice, leading to model overfitting and performance degradation. To overcome this problem, we propose a novel framework that incorporates rectified meta-learning module into common CNN paradigm to train a noise-robust deep network without using extra supervision information. The proposed method enjoys the following merits: (i) A rectified meta-learning is designed to pay more attention to unbiased samples, leading to accelerated convergence and improved classification accuracy. (ii) Our method is free on assumption of label noise distribution, which works well on various kinds of noise. (iii) Our method serves as a plug-and-play module, which can be embedded into any deep models optimized by gradient descent-based method. Extensive experiments are conducted to demonstrate the superior performance of our algorithm over the state-of-the-arts.
(Invited) Solid-State Chemistry Meets Photoelectrochemistry: New Families of Ternary Oxides and Chalcogenides
Authors: Rajeshwar Krishnan
Published: January 2022

Even after ca. four decades of R&D effort, we still do not have a "magic bullet" inorganic semiconductor to photoelectrochemically generate fuels or chemicals from sunlight in a sustainable, efficient and environment-friendly manner. While it is unlikely that a single semiconductor candidate will emerge that simultaneously satisfies all the optical, electrical, surface chemical, and electrochemical prerequisites for efficient solar conversion, complex oxides or chalcogenides (or derivatives thereof, e.g., oxynitrides) do provide a versatile framework for rational design of the "perfect beast" in a chemical architectural sense. Ultimately two or more such semiconductor compositions can be combined in a composite design much like complementary functionalities are combined in photosynthetic assemblies in Nature. In such designs, the semiconductor(s) and the photoactive junction can even be separated from the electrolyte and the electrocatalyst component in a "buried junction" design. In this vein, the author's laboratory has been engaged in the development of time- and energy-efficient methods for synthesizing new families of photoelectrode or photocatalyst materials. In this particular talk, the author will provide first a context for the key role that solid-state chemistry paradigms and principles can play in photoelectrode designs for driving multi-electron processes typical of solar fuel generation. Two representative ternary semiconductor systems, namely, Cu-V-O and M-Ln-X (M = divalent metal, e.g., Ba, Ln = lanthanide element, e.g., Ce, and X = chalcogen, e.g., S) will be discussed in this talk.
Convex Sets and Subharmonicity of the Inverse Norm Function
Authors: Heydari Mohammad Taghi
Published: January 2022

In this paper, we show that in order for a proper compact subset

K

of plane

ℝ

2

to be convex, it is necessary and sufficient that inverse norm function be subharmonic.
Clinical Study on the Treatment of Benign Prostatic Hyperplasia by Embolization of Prostate Artery Based on Embosphere Microspheres and Gelatin Sponge Granules
Authors: Liu Jinglei , Shi Dianwei , Li Liang , Cao Liming , Liu Jianyu , He Jingliang , Liang Zhihui
Published: January 2022

Prostatic hyperplasia can cause dysuria, such as frequent urination, urgency of urination, increased nocturia, poor urination, and other symptoms, which seriously affect the quality of life of old men. We aim to compare and analyze the safety and clinical effect of embolization of the target blood vessels of ruptured prostatic hyperplasia with gelatin sponge particles and embosphere microspheres. Methods. The transcatheter MRI was performed in 422 patients. Among them, 198 patients were treated with gelfoam particles and 224 patients were treated with embosphere microspheres. The clinical effect and adverse reactions were observed and analyzed by biochemical and imaging examination. Four hundred and twenty two cases were hemostasis. In the gelatin sponge group, 34 patients had recurrent bleeding 24–36 hours after embolization, 122 patients had different degrees of elevation of prostatic hyperplasia transaminase (31 cases increased to more than 1000 U/L), 198 patients had different degrees of elevation of bilirubin; in the microsphere group, there was no significant difference in prostatic hyperplasia function indexes between the two groups. Conclusion. Compared with the gelfoam embolic agent, the embosphere embolic microsphere has a good efficacy and safety in the treatment of prostatic hyperplasia rupture and hemorrhage, with a light adverse reaction, a low probability of recanalization, and little damage to the postoperative prostatic hyperplasia function, which is conducive to the benign recovery of perioperative patients and is worthy of clinical application.
Clinical Efficacy of Adjuvant Treatment of Primary Nephrotic Syndrome in Pediatric Patients with Chinese Medicine
Authors: Wu Hongjie , Zhang Lin , Liu Qing , Ren Baofeng , Li Jun
Published: January 2022

Objective. Current study aimed to investigate the benefits of adjuvant therapy with traditional Chinese medicine on the pediatric primary nephrotic syndrome. Methods. A total of 455 patients with PNS admitted to our hospital from January 2010 to January 2019 were divided into the traditional Chinese medicine group (n = 217) and the control group (n = 238). The control group received conventional Western medical treatment, and the traditional Chinese medicine group was treated with traditional Chinese medicine supplemented with Western medical treatment. The differences in remission rate, recurrence rate, and recurrence-free survival between the two groups were evaluated. Results. The differences in clinical parameters between the two groups were not statistically significant. Compared with the control group, adjuvant treatment with traditional Chinese medicine increased the clinical remission rate (

p
=
0.037

), decreased the relapse rate (

p
=
0.015

), prolonged relapse-free survival (

p
≤
0.01

), and was an independent protective factor for relapse-free survival in children with PNS (HR = 0.55, 95% CI 0.49–0.63,

p
≤
0.01

). In a subgroup analysis of the traditional Chinese medicine formulations, Yuebi Jiazhu Tang, Ganlu Xiaodu Dan, and Yupingfeng granules significantly reduced the risk of recurrence in children (

p
≤
0.01

,

p
≤
0.01

,

p
=
0.003

). Conclusion. Adjuvant treatment of pediatric primary nephrotic syndrome with traditional Chinese medicine could benefit the children.
Lightweight Statistical Approach towards TCP SYN Flood DDoS Attack Detection and Mitigation in SDN Environment
Authors: Batool Sehrish , Zeeshan Khan Farrukh , Qaiser Ali Shah Syed , Ahmed Muneer , Alroobaea Roobaea , Baqasah Abdullah M. , Ali Ihsan , Ahsan Raza Muhammad
Published: January 2022

Distributed Denial of Service (DDoS) attack is known to be one of the most lethal attacks in traditional network architecture. In this attack, the attacker uses botnets to overwhelm network resources. Botnets can be randomly compromised computers or IoT devices that are used to generate excessive traffic towards the victim, and as a result, legitimate users cannot access the services. In this research, software-defined networking (SDN) has been suggested as a solution to fight DDoS attacks. SDN uses the idea of centralized control and segregation of the data plane from the control plane. SDN is more flexible, and policy implementation on the centralized controller is easy. SDN is now being widely used in modern network paradigms because it has enhanced security. In this work, an entropy-based statistical approach has been suggested to detect and mitigate TCP SYN flood DDoS attacks. The proposed algorithm uses a three-phased detection scheme to minimize the false-positive rate. Entropy, standard deviation, and weighted moving average have been used for intrusion detection. Multiple experiments were performed, and the results show that the suggested approach is more reliable and lightweight and has a minimal false-positive rate.
Prediction of Fatigue Crack Growth Rate and Stress Intensity Factors Using the Finite Element Method
Authors: Ali Fageehi Yahya
Published: January 2022

This study investigates crack growth and stress intensity factors via finite element methods in linear elastic fracture mechanics. The procedure involves estimating stress intensity factors (SIFs), crack trajectory, and fatigue life, using two different softwares in both two and three-dimensional analyses. Crack modeling was done in a variety of ways depending on the software. ANSYS Mechanical R19.2 and FRANC2D/L software were used to prognosticate fatigue crack growth, fatigue life, and associated stress intensity factors under plane stress state. Fatigue analysis was governed by Paris’s law and crack growth direction by the theory of maximum circumferential stress. The results show that the fatigue growth was attracted to the hole and either changes its direction to reach the hole or floats by the hole and grows as the hole is missed. The findings of the study agree with other experimental and numerical crack propagation studies presented in the literature.
The Exosomes Containing LINC00461 Originated from Multiple Myeloma Inhibit the Osteoblast Differentiation of Bone Mesenchymal Stem Cells via Sponging miR-324-3p
Authors: Wu Yang , Zhang Zhemei , Wu Jing , Hou Jinxia , Ding Guosheng
Published: January 2022

Multiple myeloma is one of the hematological malignancies and inhibited osteoblast differentiation of bone marrow mesenchymal stem cells (BM-MSCs) which has been proved as a major complication of the patients with multiple myeloma. However, the pathomechanism of symptom remains unclear. Besides, several studies have indicated that LINC00461 plays an important role in the progression of multiple tumors. Hence, this study attempted to reveal the role of LINC00461 in the osteoblast differentiation of MSCs. In this study, the expression level of LINC00461 in the exosomes of multiple myeloma cells was measured, and BM-MSCs were cultured with the exosomes to observe the change of cellular phenotype. Moreover, downstream target of LINC00461 was searched and verified with dual-luciferase reporter assay, and the activation of the Wnt/β-catenin pathway was also observed by Western blot. The results showed that the isolated BMSCs exhibited special biomarkers of MSCs. LINC00461 was significantly upregulated in the exosomes originated multiple myeloma cells, and increased LINC00461 significantly impeded the osteoblast differentiation of MSCs. Moreover, LINC00461 could significantly suppress the activation of the Wnt/β-catenin pathway in MSCs. In conclusion, this study suggested that LINC00461 in exosomes of multiple myeloma could reduce the activity of the Wnt/β-catenin pathway to inhibit the osteoblast differentiation of BM-MSCs via targeting miR-324-3p.
Macular Edema and Visual Acuity Observation after Cataract Surgery in Patients with Diabetic Retinopathy
Authors: Song Ruiying , Jiang Jing , Wang Hong
Published: January 2022

Objective. The purpose was to explore the effect of cataract surgery on postoperative macular edema and visual acuity in patients with diabetic retinopathy. Methods. 88 patients with diabetic retinopathy treated in our hospital (December 2019–December 2020) were chosen as research subjects and divided into experimental group of 44 patients (52 eyes) and control group of 44 patients (54 eyes) according to the odd and even admission numbers. The control group received laser photocoagulation treatment, while the experimental group underwent cataract surgery. The central macular thickness (CMT) and visual acuity of the two groups after treatment were detected to evaluate the therapeutic effect of different treatment methods on diabetic retinopathy. Results. No obvious differences in sex ratio, average age, average course of disease, average weight, average BMI, average glycosylated hemoglobin, and residence were found between the two groups

P
>
0.05

. The total clinical effective rate in the experimental group was obviously higher compared with the control group

P
<
0.05

. The CMT at T1, T2, and T3 in the experimental group was obviously lower compared with the control group

P
<
0.05

. The BCVA in the experimental group at 1 month and 3 months after treatment was obviously higher compared with the control group

P
<
0.05

. The VEGF levels of both groups after treatment were obviously lower

P
<
0.001

, and the VEGF level in the experimental group after treatment was obviously lower compared with the control group

P
<
0.001

. The total incidence of complications in the experimental group was obviously lower compared with the control group

P
<
0.05

. Conclusion. Cataract surgery is a reliable method to improve visual acuity and reduce serum inflammatory indicators in patients with diabetic retinopathy, with better clinical effect than laser photocoagulation, which is recommended for the treatment of diabetic retinopathy.
Improving the Survival Time of Multiagents in Social Dilemmas through Neurotransmitter-Based Deep Q-Learning Model of Emotions
Authors: Hassan Awais , Shahid Maida , Hayat Faisal , Arshad Jehangir , Jaffery Mujtaba Hussain , Rehman Ateeq Ur , Ullah Kalim , Hussen Seada , Hamam Habib
Published: January 2022

In multiagent systems, social dilemmas often arise whenever there is a competition over the limited resources. The major challenge is to establish cooperation among intelligent virtual agents for solving the situations of social dilemmas. In humans, personality and emotions are the primary factors that lead them toward a cooperative environment. To make agents cooperate, they have to become more like humans, that is, believable. Therefore, we hypothesize that emotions according to the personality give birth to believability, and if believability is introduced into agents through emotions, it improves their survival rate in social dilemma situations. The existing researches have introduced different computational models to introduce emotions in virtual agents, but they lack emotions through neurotransmitters. We have proposed a neurotransmitters-based deep Q-learning computational model in multiagents that is a suitable choice for emotion modeling and, hence, believability. The proposed model regulates the agents’ emotions by controlling the virtual neurotransmitters (dopamine and oxytocin) according to the agent’s personality. The personality of the agent is introduced using OCEAN model. To evaluate the proposed system, we simulated a survival scenario with limited food resources in different experiments. These experiments vary the number of selfish agents (higher neuroticism personality trait) and the selfless agents (higher agreeableness personality trait). Experimental results show that by adding the selfless agents in the scenario, the agents develop cooperation, and their collective survival time increases. Thus, to resolve the social dilemma problems in virtual agents, we can make agents believable through the proposed neurotransmitter-based emotional model. This proposed work may help in developing nonplayer characters (NPCs) in games.
Prognostic Lnc-S100B-2 Affects Cell Apoptosis and Microenvironment of Colorectal Cancer through MLLT10 Signaling
Authors: Yi Jianmei , Peng Feng , Zhao Jingli , Gong Xiaosong
Published: January 2022

Long noncoding RNA (LncRNA) is closely associated with the development of colorectal cancer (CRC). The chip data and clinical information of GSE104364 and GSE151021 were downloaded by GEOquery. Limma and Kaplan–Meier analysis were performed. Lnc-S100B-2 was obtained, and high expression of Lnc-S100B-2 was predicted to be associated with a lower survival rate. Online software was adopted to predict downstream regulatory genes, and miR-331-3p and Mixed Lineage Leukemia Translocated to 10 (MLLT10) were screened and verified. After silencing Lnc-S100B-2 and MLLT10, the proliferative activity of CRC cells decreased, and the apoptosis rate increased. At the gene and protein levels, the expressions of PCNA, Ki67, and Bcl-2 were decreased in the sh-Lnc-S100B-2 group, sh-MLLT10 group, and sh-Lnc-S100B-2 + sh-MLLT10 group, while the expressions of cleaved caspase 3, caspase 9, and Bax were increased. In vivo, the volume and mass of the tumor decreased in the sh-Lnc-S100B-2 + sh-MLLT10 group. Proliferation and apoptosis-related index (PCNA, Ki67, cleaved caspase 3, caspase 9, Bax, and Bcl-2) expression level was also altered. Meanwhile, the infiltration of immune cells (CD3 (-), CD16 (+), and CD11b (+) cells) decreased. The expressions of epithelial-mesenchymal transformation (EMT) related indicators (E-cadherin, N-cadherin, Vimentin, β-catenin, Snail, and Slug) were changed. E-cadherin and β-catenin were increased in the sh-Lnc-S100B-2 + sh-MLLT10 group, while N-cadherin, vimentin, snail, and slug were decreased. In conclusion, our study found that the expression of Lnc-S100B-2 was dysregulated in CRC. Lnc-S100B-2 could affect cell apoptosis and the microenvironment of CRC through regulating MLLT10.
The Effect of Preoperative Rehabilitation Training on the Early Recovery of Joint Function after Artificial Total Knee Arthroplasty and Its Effect Evaluation
Authors: Zheng Yuliu , Huang Zida , Dai Liqun , Liu Yu , Chen Yanqin , Zhang Wenming , Lin Rongjin
Published: January 2022

Objective. To study the effect of preoperative rehabilitation training on the rehabilitation of patients after total knee arthroplasty. Methods. A total of 120 patients diagnosed with knee osteoarthritis and undergoing total knee arthroplasty were selected and divided into experimental group and control group according to a random number table, with 60 cases in each group. The control group only carried out routine clinical nursing before the operation, and the experimental group used the formulated preoperative rehabilitation training method based on the control group for training. By comparing the visual analogue score (VAS), keen society score (KSS), postoperative time to get out of bed for the first time, patient satisfaction, and other related indicators between the two groups of patients, the recovery of keen joint function of patients after surgery was evaluated. Results. The visual analogue scale (VAS) of the experimental group was significantly lower than that of the experimental group at three days after operation. The keen society score (KSS) of the experimental group was significantly better than that of the control group at three days after surgery and one month after surgery. The time to get out of bed for the first time after operation in the experimental group (44.93 ± 13.63) was significantly less than that in the control group (78.33 ± 13.52). The patient satisfaction of the experimental group was significantly higher than that of the control group (88.30 ± 3.61). The above statistical results were all

p
<
0.05

of the two groups, and the differences were statistically significant. Conclusion. Preoperative rehabilitation training can significantly reduce the pain of patients after knee replacement, improve the functional state of knee joints, shorten the time to get out of bed for the first time after surgery, and win the best recovery opportunity, which can better improve patient satisfaction in hospitalization and improve medical care services level.
Evaluation of the Mechanism of Modified Lingguizhugan Decoction in the Treatment of Nonalcoholic Fatty Liver Disease
Authors: Yang Fuyuan , Zhou Jianxiang , Su Bo , Zhang Qiong , Luo Xuezhi , Wang Fei , Huang Jiangrong , Huang Wei
Published: January 2022

Nonalcoholic steatohepatitis (NASH) may develop into cirrhosis and liver cancer, which imposes a great burden to individuals and society. Lingguizhugan decoction is a commonly used dampness dispelling medication in traditional Chinese medicine and is often used to treat those with phlegm and retained fluid from various causes and pathogeneses. The objective of this study was to explore the effect and mechanism of modified Lingguizhugan decoction (MLGZG) on lipid metabolism and the inflammatory response to identify a theoretical basis to promote its clinical application in NASH therapy. After treatment with MLGZG for 8 weeks, the weight of high-fat-diet (HFD)-fed NASH rats was significantly higher than that of rats in the normal group, and the weights in each dose group were significantly lower than those in the model group. The treatment groups (low, medium, and high doses) had different degrees of improvement in the changes in hepatocyte tissue structure, steatosis, and inflammatory infiltration. Compared with that in the normal group, the expression of TNF receptor-associated factor-3 (TRAF-3) and nuclear factor κB (NFκB) in the model group significantly increased to varying degrees. Compared with the NASH group, the treatment groups (low, middle, and high doses) showed modified lipid metabolism gene expression and decreased inflammatory factor expression levels. Modified Lingguizhugan decoction can improve the general condition of rats with nonalcoholic fatty liver disease by reducing the expression levels of TRAF3, NF-κB, the Toll-like receptor 4 (TLR-4) pathway, and related proteins, as well as the expression levels of lipid metabolism genes and cytokines.
Pregnancy Status Is Associated with Lower Hemoglobin A1c among Nondiabetes Women in the United States from NHANES 2005–2016
Authors: Lu Yi , Huo Zhenyu , Ge Fan , Luo Jiachun
Published: January 2022

Background. It has been verified that the incidence rate of diabetes mellitus (DM) is sharply increased in pregnant female adults. However, the relationship between pregnant status and hemoglobin A1c (HbA1c) in nondiabetes women remains unclear. Methods. We conducted a cross-sectional study of 7762 participants in the National Health and Nutrition Examination Survey (NHANES) 2005–2016. Multivariable linear regression models were performed to evaluate the associations between pregnant status with HbA1c and serum glucose in nondiabetes women. Results. HbA1c was significantly lower in the pregnant group than in the nonpregnant group. There was a negative association between urine pregnancy test and HbA1c in all three models (model 1: β = −0.23, 95% CI: (−0.18 to −0.27); model 2: β = −0.20, 95% CI: (−0.15 to −0.24); model 3: β = −0.24, 95% CI: (−0.20 to −0.29)). In the subgroup analysis stratified by age, this negative association existed in all age subgroups (age <20: β = −0.20, 95% CI: (−0.04 to −0.27); age ≥20, <35: β = −0.24, 95% CI: (−0.20 to −0.29); age ≥35: β = −0.28, 95% CI: (−0.17, −0.39)). In the subgroup analysis stratified by race, the negative associations steadily existed in different subgroups (Mexican American:β = −0.20, 95% CI:(-0.11 to -0.29); Other Hispanic:β = -0.31, 95% CI: (-0.16 to -0.46); Non-Hispanic White: β = −0.24, 95% CI: (−0.17 to −0.31); Non-Hispanic Black: β = −0.21, 95% CI: (−0.12 to −0.31); Other races:β = −0.22, 95% CI: (−0.08 to −0.35)). On the other hand, a negative association between self-reported pregnant status and HbA1c was also found (model 1: β = −0.22, 95% CI: (−0.18 to −0.27); model 2: β = −0.19, 95% CI: (−0.15 to −0.2); model 3: β = −0.23, 95% CI: (−0.19 to −0.28)). In the subgroup analysis stratified by age, this negative association also existed in all age subgroups. Conclusions. The study indicated that nondiabetes women with pregnant status had significantly lower HbA1c compared with those nonpregnant. Moreover, the negative associations between pregnant status and HbA1c steadily existed in subgroups stratified by age and gender.