bluuebunny/crossref_metadata_2025 huggingface dataset:
Casualties of the World War II metaphor: women’s reproductive health fighting for narrative inclusion in COVID-19
Authors: Bailey Yuki , Shankar Megha , Phillips Patrick
Published: June 2021

While the COVID-19 pandemic progresses, politicians and media outlets in the USA have compared the pandemic with World War II (WWII). Though women’s reproductive health has been affected by both COVID-19 and WWII, these specific health needs are not included in either event’s mainstream narrative. This article explores the pandemic’s war metaphor through the lens of women’s reproductive health, arguing for a reframing of the metaphor. Narrative-building determines how health needs are perceived and addressed. A modification of the WWII metaphor can ensure that the narrative formulating around COVID-19 is inclusive of the women’s reproductive health needs that are eminently present.
Opening injection pressure monitoring using an in-line device does not prevent intraneural injection in an isolated nerve model
Authors: Mejia Jorge , Varela Victor , Domenech Javier , Goffin Pierre , Prats-Galino Alberto , Sala-Blanch Xavier
Published: June 2021

Background

Injection pressure monitoring using in-line devices is affordable and easy to implement into a regional anesthesia practice. However, solid evidence regarding their performance is lacking. We aimed to evaluate if opening injection pressure (OIP), measured with a disposable in-line pressure monitor, can prevent intraneural (subepineural) injection using 15 pound per square inch (PSI) as the reference safety threshold.

Methods

An isolated nerve model with six tibial and six common peroneal nerves from three unembalmed fresh cadavers was used for this observational study. A mixture of 0.5% ropivacaine with methylene blue was injected intraneurally at a rate of 10 mL/min, to a maximum of 3 mL. OIP was recorded for each injection as well as evidence of intraneural contrast. Injected volume at 15 and 20 PSI was recorded, and when it leaked out the epineurium, if it occurred.

Results

In all cases, OIP was<15 PSI and intraneural contrast was evident before the safety threshold. The 15–20 PSI mark was attained in 5 of 12 injections (41%), with a median injected volume of 0.9 mL (range 0.4–2.3 mL). Peak pressure of >20 PSI was reached in two injections (at 0.6 mL and 2.7 mL). Contrast leaked out the epineurium in 11 of 12 injections (91%) with a median injected volume of 0.6 mL (range 0.1–1.3 mL).

Conclusions

Our results suggest that in-line pressure monitoring may not prevent intraneural injection using an injection pressure of 15 PSI as reference threshold. Due to the preliminary nature of our study, further evidence is needed to demonstrate clinical relevance.
Impact of lung function on cardiovascular diseases and cardiovascular risk factors: a two sample bidirectional Mendelian randomisation study
Authors: Au Yeung Shiu Lun , Borges Maria Carolina , Lawlor Debbie A , Schooling C Mary
Published: June 2021

Introduction

Observational studies suggested lung function is inversely associated with cardiovascular disease (CVD) although these studies could be confounded. We conducted a two sample Mendelian randomisation study using summary statistics from genome-wide association studies (GWAS) to clarify the role of lung function in CVD and its risk factors, and conversely the role of CVD in lung function.

Methods

We obtained genetic instruments for forced expiratory volume in 1 s (FEV1: 260) and forced vital capacity (FVC: 320) from publicly available UK Biobank summary statistics (n=421 986) and applied to GWAS summary statistics for coronary artery disease (CAD) (n=184 305), stroke (n=446 696), atrial fibrillation (n=1 030 836) and heart failure (n=977 320) and cardiovascular risk factors. Inverse variance weighting was used to assess the impact of lung function on these outcomes, with various sensitivity analyses. Bidirectional Mendelian randomisation was used to assess reverse causation.

Results

FEV1 and FVC were inversely associated with CAD (OR per SD increase, 0.72 (95% CI 0.63 to 0.82) and 0.70 (95%CI 0.62 to 0.78)), overall stroke (0.87 (95%CI 0.77 to 0.97), 0.90 (95% CI 0.82 to 1.00)) and some stroke subtypes. FEV1 and FVC were inversely associated with type 2 diabetes and systolic blood pressure. Sensitivity analyses produced similar findings although the association with CAD was attenuated after adjusting for height (eg, OR for 1SD FEV10.95 (0.75 to 1.19), but not for stroke or type 2 diabetes. There was no strong evidence for reverse causation.

Conclusion

Higher lung function likely protect against CAD and stroke.
Antifungal mechanisms of lavender essential oil in the inhibition of rot disease caused by Monilinia fructicola in postharvest flat peaches
Authors: Xiong Xiaolin , Zhang Lingling , Li Xingyan , Zeng Qingzhi , Deng Rongrong , Ren Xueyan , Kong Qingjun
Published: June 2021

Lavender essential oil (LEO), a natural antimicrobial agent, is generally recognized as safe and effective in the inhibition of phytopathogenic fungi. Direct contact and fumigation (in vivo and in vitro) were used to study the fungistatic effect of LEO on Monilinia fructicola. Additionally, the effect on the ultrastructure of cells and the degree of destruction of the cell membrane of M. fructicola were revealed. In addition, the effects of LEO on the expression levels of apoptosis-related genes in M. fructicola cells were detected, and GC-MS was used to analyze the main components of LEO. LEO had a good inhibitory efficacy against M. fructicola in flat peaches, with almost complete growth inhibition at 800 μL/L. These effects were associated with the leakage of cytoplasmic contents, hyphal distortion, and spore disruption. Moreover, the expression of apoptosis RTG1 and RLM1 genes increased with LEO treatment. These results demonstrate that LEO can inhibit M. fructicola by inducing cytoplasmic membrane damage and cell apoptosis in fungi, and that the major ingredients of LEO are monoterpenes and sesquiterpenes, which are presumed to contribute to the inhibitory effects.
Preparation of WS2–TiO2–Au using hydrothermal synthesis for photocatalysis under visible light
Authors: Wu Kejun , Koinkar Pankaj , Furube Akihiro
Published: June 2021

In this study, the preparation of ternary photocatalyst using a simple hydrothermal method is shown with high performance. A ternary composite consisting of tungsten sulfide (WS[Formula: see text] nanosheets, titanium oxide (TiO[Formula: see text] and gold (Au) nanoparticles is used to the extend the visible-light absorption region of TiO2. The morphological and spectroscopic natures of the prepared sample were analyzed using scanning electron microscopy (SEM), Raman spectroscopy and ultraviolet–visible (UV–vis) photospectroscopy. The photocatalysis measurement for photodegradation of methylene blue dye was performed under the visible light. The photocatalytic studies suggest that in the ternary composite, consisting of three materials with different energy levels, the electrons excited form a cycle to lower the probability for the recombination of electron–hole pairs enhancing the property of photocatalytic activity of TiO2.
Elastic scattering of α particle at CERN-ISR energy: Three-nucleon force effect
Authors: Hassan Mohamed A. , Awd-Allah Hamed E. A.
Published: June 2021

In the framework of optical limit approximation of Glauber with inclusion of the three-nucleon force effect, we obtained a good agreement with the experimental data of [Formula: see text] elastic scattering differential cross-section at the energies [Formula: see text] and [Formula: see text][Formula: see text]GeV. The relation between the nucleon–nucleon slope parameter and the nucleon–nucleon interaction radius is discussed. In any case, the three-nucleon force is important and must be taken into account for a better agreement with the nucleus–nucleus data.
Tight Upper Bound of the 3-Total-Rainbow Index for 2-(Edge-)Connected Graphs
Authors: Ma Yingbin , Zhu Wenhan
Published: June 2021

Let [Formula: see text] be an edge-colored graph with order [Formula: see text] and [Formula: see text] be a fixed integer satisfying [Formula: see text]. For a vertex set [Formula: see text] of at least two vertices, a tree containing the vertices of [Formula: see text] in [Formula: see text] is called an [Formula: see text]-tree. The [Formula: see text]-tree [Formula: see text] is a total-rainbow [Formula: see text]-tree if the elements of [Formula: see text], except for the vertex set [Formula: see text], have distinct colors. A total-colored graph [Formula: see text] is said to be total-rainbow [Formula: see text]-tree connected if for every set [Formula: see text] of [Formula: see text] vertices in [Formula: see text], there exists a total-rainbow [Formula: see text]-tree in [Formula: see text], while the total-coloring of [Formula: see text] is called a [Formula: see text]-total-rainbow coloring. The [Formula: see text]-total-rainbow index of a nontrivial connected graph [Formula: see text], denoted by [Formula: see text], is the smallest number of colors needed in a [Formula: see text]-total-rainbow coloring of [Formula: see text]. In this paper, we show a sharp upper bound for [Formula: see text], where [Formula: see text] is a [Formula: see text]-connected or [Formula: see text]-edge-connected graph.
Scalable Estimator for Multi-task Gaussian Graphical Models Based in an IoT Network
Authors: Wang Beilun , Zhang Jiaqi , Zhang Yan , Wang Meng , Wang Sen
Published: June 2021

Recently, the Internet of Things (IoT) receives significant interest due to its rapid development. But IoT applications still face two challenges: heterogeneity and large scale of IoT data. Therefore, how to efficiently integrate and process these complicated data becomes an essential problem. In this article, we focus on the problem that analyzing variable dependencies of data collected from different edge devices in the IoT network. Because data from different devices are heterogeneous and the variable dependencies can be characterized into a graphical model, we can focus on the problem that jointly estimating multiple, high-dimensional, and sparse Gaussian Graphical Models for many related tasks (edge devices). This is an important goal in many fields. Many IoT networks have collected massive multi-task data and require the analysis of heterogeneous data in many scenarios. Past works on the joint estimation are non-distributed and involve computationally expensive and complex non-smooth optimizations. To address these problems, we propose a novel approach: Multi-FST. Multi-FST can be efficiently implemented on a cloud-server-based IoT network. The cloud server has a low computational load and IoT devices use asynchronous communication with the server, leading to efficiency. Multi-FST shows significant improvement, over baselines, when tested on various datasets.
Privacy-preserving Data Aggregation against Malicious Data Mining Attack for IoT-enabled Smart Grid
Authors: Wang Jing , Wu Libing , Zeadally Sherali , Khan Muhammad Khurram , He Debiao
Published: June 2021

Internet of Things (IoT)-enabled smart grids can achieve more reliable and high-frequency data collection and transmission compared with existing grids. However, this frequent data processing may consume a lot of bandwidth, and even put the user’s privacy at risk. Although many privacy-preserving data aggregation schemes have been proposed to solve the problem, they still suffer from some security weaknesses or performance deficiency, such as lack of satisfactory data confidentiality and resistance to malicious data mining attack. To address these issues, we propose a novel privacy-preserving data aggregation scheme (called PDAM) for IoT-enabled smart grids, which can support efficient data source authentication and integrity checking, secure dynamic user join and exit. Unlike existing schemes, the PDAM is resilient to the malicious data mining attack launched by internal or external attackers and can achieve perfect data confidentiality against not only a malicious aggregator but also a curious control center for an authorized user. The detailed security and performance analysis show that our proposed PDAM can satisfy several well-known security properties and desirable efficiency for a smart grid system. Moreover, the comparative studies and experiments demonstrate that the PDAM is superior to other recently proposed works in terms of both security and performance.
Spatial concepts in the conversation with a computer
Authors: Winter Stephan , Baldwin Timothy , Tomko Martin , Renz Jochen , Kuhn Werner , Vasardani Maria
Published: June 2021

Conversing about places with a computer poses a range of challenges to current AI.
Always-on time-series database
Authors: Schlossnagle Theo , Sheehy Justin , McCubbin Chris
Published: June 2021

A discussion with Theo Schlossnagle, Justin Sheehy, and Chris McCubbin.
Differentiable Compound Optics and Processing Pipeline Optimization for End-to-end Camera Design
Authors: Tseng Ethan , Mosleh Ali , Mannan Fahim , St-Arnaud Karl , Sharma Avinash , Peng Yifan , Braun Alexander , Nowrouzezahrai Derek , Lalonde Jean-François , Heide Felix
Published: June 2021

Most modern commodity imaging systems we use directly for photography—or indirectly rely on for downstream applications—employ optical systems of multiple lenses that must balance deviations from perfect optics, manufacturing constraints, tolerances, cost, and footprint. Although optical designs often have complex interactions with downstream image processing or analysis tasks, today’s compound optics are designed in isolation from these interactions. Existing optical design tools aim to minimize optical aberrations, such as deviations from Gauss’ linear model of optics, instead of application-specific losses, precluding joint optimization with hardware image signal processing (ISP) and highly parameterized neural network processing. In this article, we propose an optimization method for compound optics that lifts these limitations. We optimize
entire
lens systems
jointly
with hardware and software image processing pipelines, downstream neural network processing, and application-specific end-to-end losses. To this end, we propose a learned,
differentiable forward model for compound optics
and an
alternating proximal optimization
method that handles function compositions with highly varying parameter dimensions for optics, hardware ISP, and neural nets. Our method integrates seamlessly atop existing optical design tools, such as
Zemax
. We can thus assess our method across many camera system designs and end-to-end applications. We validate our approach in an automotive camera optics setting—together with hardware ISP post processing and detection—outperforming classical optics designs for automotive object detection and traffic light state detection. For human viewing tasks, we optimize optics and processing pipelines for dynamic outdoor scenarios and dynamic low-light imaging. We outperform existing compartmentalized design or fine-tuning methods qualitatively and quantitatively, across
all
domain-specific applications tested.
Application frameworks
Authors: Nokleberg Chris , Hawkes Brad
Published: June 2021

While powerful, frameworks are not for everyone.
eDeepSave: Saving DNN Inference using Early Exit During Handovers in Mobile Edge Environment
Authors: Ju Weiyu , Yuan Dong , Bao Wei , Ge Liming , Zhou Bing Bing
Published: June 2021

Recent advances in deep neural networks (DNNs) have substantially improved the accuracy of intelligent applications. One effective scheme known as DNN partition further improves the speed of the inference by partitioning the DNN to a mobile device and its connected edge server to jointly process the inference. However, one of the challenges is how to maintain the service during handovers to avoid interruptions. Inspired by the recently developed early exit technique, where the DNN inference can be accelerated by leaving at an earlier exit point, we propose eDeepSave, a promising solution to save a large portion of video frames that cannot be handled during handovers. eDeepSave comprises three subschemes: (1) save the partially completed frames that are affected when the handover begins. (2) determine which frames we should save during a handover to maximize the number of saved frames. (3) repartition the last arriving frame before the end of the handover with a provable performance bound so that the frames after the handover can be processed without experiencing congestion. We build up a real-world prototype for the field experiments and extensive simulations, showing that eDeepSave can save up to 100% of the affected frames during handover.
Semi-supervised Intrusive Appliance Load Monitoring in Smart Energy Monitoring System
Authors: Nguyen Vanh Khuyen , Zhang Wei Emma , Mahmood Adnan
Published: June 2021

Intrusive Load Monitoring (ILM) is a method to measure and collect the energy consumption data of individual appliances via smart plugs or smart sockets. A major challenge of ILM is automatic appliance identification, in which the system is able to determine automatically a label of the active appliance connected to the smart device. Existing ILM techniques depend on labels input by end-users and are usually under the supervised learning scheme. However, in reality, end-users labeling is laboriously rendering insufficient training data to fit the supervised learning models. In this work, we propose a semi-supervised learning (SSL) method that leverages rich signals from the unlabeled dataset and jointly learns the classification loss for the labeled dataset and the consistency training loss for unlabeled dataset. The samples fit into consistency learning are generated by a transformation that is built upon weighted versions of DTW Barycenter Averaging algorithm. The work is inspired by two recent advanced works in SSL in computer vision and combines the advantages of the two. We evaluate our method on the dataset collected from our developed Internet-of-Things based energy monitoring system in a smart home environment. We also examine the method’s performances on 10 benchmark datasets. As a result, the proposed method outperforms other methods on our smart appliance datasets and most of the benchmarks datasets, while it shows competitive results on the rest datasets.
Evidence for Li+/H+ Exchange during Ambient Storage of Ni-Rich Cathode Active Materials
Authors: Hartmann Louis , Pritzl Daniel , Beyer Hans , Gasteiger Hubert A.
Published: June 2021

Layered Ni-rich transition metal oxides like so-called NCMs are one of the most-promising high-energy density cathode active materials (CAMs) for next-generation Li-Ion batteries. However, compared to NCMs with low nickel content, Ni-rich NCMs suffer from a highly reactive surface that leads to an accumulation of surface contaminants and also from a higher soluble base content. Since a detailed understanding of the formation rate of surface contaminants is still lacking, we will investigate the effect of extended storage in high relative humidity air of a Ni-rich NCM851005 (Li1+δ
(Ni0.85Co0.10Mn0.05)1-δ
O2, with δ typically ∼0.005–0.03) and a low nickel content NCM111 (Li1+δ
(Ni1/3Co1/3Mn1/3)1-δ
O2) on the build-up of surface contaminants. The formation rate of the surface contaminants during this accelerated wet-storage test is quantified by TGA-MS under Ar. To elucidate the processes occurring during the TGA-MS experiments, as-received and wet-stored CAMs are introduced into an XPS chamber where they are heated in situ to different temperatures, followed by XPS analysis of the surface compositional changes. Comparative measurements with water-washed NCM851005 reveal the close analogy between the processes that occur during extended storage of NCMs in humid ambient air and during the washing of NCMs, commonly used to lower the soluble base content of Ni-rich NCMs.
Dynamics and Stability Analysis of a Stackelberg Mixed Duopoly Game with Price Competition in Insurance Market
Authors: Wei Longfei , Wang Haiwei , Wang Jing , Hou Jialong
Published: June 2021

This paper investigates the dynamical behaviors of a Stackelberg mixed duopoly game with price competition in the insurance market, involving one state-owned public insurance company and one private insurance company. We study and compare the stability conditions for the Nash equilibrium points of two sequential-move games, public leadership, and private leadership games. Numerical simulations present complicated dynamic behaviors. It is shown that the Nash equilibrium becomes unstable as the price adjustment speed increases, and the system eventually becomes chaotic via flip bifurcation. Moreover, the time-delayed feedback control is used to force the system back to stability.
Kinematic and Static Solutions for Beam Column with Nonlinear Springs Using the Extended Linear Matching Method
Authors: Gao Bin , Wu Jun
Published: June 2021

In this paper, the kinematic and static solutions for solving the static response of the beam column with nonlinear springs are presented by adopting the extended linear matching method (LMM). The extended LMM can be used to predict the displacement response of the beam‐column system consisting of perfectly plastic and strain‐softening materials. It is found that the kinematic solution generated by the extended LMM demonstrates a monotonic decrease for perfect plastic materials with certain restrictions on the yield surface. The potential energy of the system is proved to decrease with iterations for both perfect plastic and strain‐softening materials if the loading multiplier remains constant. The extended LMM method is then applied to analyse the response of the pile system in a 3‐leg offshore platform. An incremental procedure is recommended to determine the peak load for the soil exhibiting strain‐softening. A displacement‐control approach is used with the loading multiplier obtained from the variation of the potential energy. Good convergence of the method is obtained.
Physical Simulation Test on Temperature Field Distribution of Artificial Vertical Straight Multirow Freezing Inclined Shaft
Authors: Sun Jielong , Ren Jianxi
Published: June 2021

This study investigated the temperature field distribution of a freezing inclined shaft. Thus, a three-dimensional physical simulation test system was developed, and the system consists of six parts, which are simulation box and shaft model, loading system, freezing system, external environment simulation system, and data acquisition system. From the results of physical and mechanical property test of artificially frozen sand, in the range of 25°C to -20°C, the heat capacity of sand decreases first, then increases, decreases, and finally tends to be stable; the thermal conductivity of sand gradually increases and finally becomes stable; and the cohesion, internal friction angle, uniaxial compressive strength, and elastic modulus of artificially frozen sand all increase as the freezing temperature decreases. The three-dimensional physical simulation test and field measurement showed that the distance from the freezing pipe is the main factor affecting freezing wall temperature, and the closer to the freezing pipe, the faster the cooling rates. Comparison of theoretical calculation results and field measurement results shows that the calculation formula of freezing wall temperature with time of the inclined shaft can reflect the general law of freezing wall temperature cooling. Therefore, the 3D physical simulation test system is reliable and the test method is feasible.
Antimycobacterial Activity, Synergism, and Mechanism of Action Evaluation of Novel Polycyclic Amines against Mycobacterium tuberculosis
Authors: Kapp Erika , Joubert Jacques , Sampson Samantha L. , Warner Digby F. , Seldon Ronnett , Jordaan Audrey , de Vos Margaretha , Sharma Rajan , Malan Sarel F.
Published: June 2021

Mycobacterium tuberculosis has developed extensive resistance to numerous antimycobacterial agents used in the treatment of tuberculosis. Insufficient intracellular accumulation of active moieties allows for selective survival of mycobacteria with drug resistance mutations and accordingly promotes the development of microbial drug resistance. Discovery of compounds with new mechanisms of action and physicochemical properties that promote intracellular accumulation, or compounds that act synergistically with other antimycobacterial drugs, has the potential to reduce and prevent further drug resistance. To this end, antimycobacterial activity, mechanism of action, and synergism in combination therapy were investigated for a series of polycyclic amine derivatives. Compound selection was based on the presence of moieties with possible antimycobacterial activity, the inclusion of bulky lipophilic carriers to promote intracellular accumulation, and previously demonstrated bioactivity that potentially support inhibition of efflux pump activity. The most potent antimycobacterial demonstrated a minimum inhibitory concentration (MIC99) of 9.6 μM against Mycobacterium tuberculosis H37Rv. Genotoxicity and inhibition of the cytochrome bc1 respiratory complex were excluded as mechanisms of action for all compounds. Inhibition of cell wall synthesis was identified as a likely mechanism of action for the two most active compounds (14 and 15). Compounds 5 and 6 demonstrated synergistic activity with the known Rv1258c efflux pump substrate, spectinomycin, pointing to possible efflux pump inhibition. For this series, the nature of the side chain, rather than the type of polycyclic carrier, seems to play a determining role in the antimycobacterial activity and cytotoxicity of the compounds. Contrariwise, the nature of the polycyclic carrier, particularly the azapentacycloundecane cage, appears to promote synergistic activity. Results point to the possibility of combining an azapentacycloundecane carrier with a side chain that promotes antimycobacterial activity to develop dual acting molecules for the treatment of Mycobacterium tuberculosis.
Analysis of Molecular Mechanism of Erxian Decoction in Treating Osteoporosis Based on Formula Optimization Model
Authors: Yang Lang , Fan Liuyi , Wang Kexin , Chen Yupeng , Liang Lan , Qin Xuemei , Lu Aiping , Cao Peng , Yu Bin , Guan Daogang , Peng Junxiang
Published: June 2021

Osteoporosis (OP) is a highly prevalent orthopedic condition in postmenopausal women and the elderly. Currently, OP treatments mainly include bisphosphonates, receptor activator of nuclear factor kappa‐B ligand (RANKL) antibody therapy, selective estrogen receptor modulators, teriparatide (PTH1‐34), and menopausal hormone therapy. However, increasing evidence has indicated these treatments may exert serious side effects. In recent years, Traditional Chinese Medicine (TCM) has become popular for treating orthopedic disorders. Erxian Decoction (EXD) is widely used for the clinical treatment of OP, but its underlying molecular mechanisms are unclear thanks to its multiple components and multiple target features. In this research, we designed a network pharmacology method, which used a novel node importance calculation model to identify critical response networks (CRNs) and effective proteins. Based on these proteins, a target coverage contribution (TCC) model was designed to infer a core active component group (CACG). This approach decoded the mechanisms underpinning EXD’s role in OP therapy. Our data indicated that the drug response network mediated by the CACG effectively retained information of the component‐target (C‐T) network of pathogenic genes. Functional pathway enrichment analysis showed that EXD exerted therapeutic effects toward OP by targeting PI3K‐Akt signaling (hsa04151), calcium signaling (hsa04020), apoptosis (hsa04210), estrogen signaling (hsa04915), and osteoclast differentiation (hsa04380) via JNK, AKT, and ERK. Our method furnishes a feasible methodological strategy for formula optimization and mechanism analysis and also supplies a reference scheme for the secondary development of the TCM formula.
Realistic Models of Financial Market and Structural Stability
Authors: Smirnov Sergey N.
Published: June 2021

The main aim of this article is to show the role of structural stability in financial modelling; that is, a specific “no-arbitrage” property is unaffected by small perturbations of the model’s dynamics. We prove that under the structural stability assumption, given a convex compact-valued multifunction, there exists a stochastic transition kernel with supports coinciding with this multifunction and one that is strong Feller in the strict sense. We also demonstrate preservation of structural stability for sufficiently small deviations of transition kernels for different probability metrics.
Observed Performance and FEM-Based Parametric Analysis of a Top-Down Deep Excavation in Soil-Rock Composite Stratum
Authors: Lei Gang , Guo Panpan , Hua Fucai , Gong Xiaonan , Luo Lina
Published: June 2021

This paper investigates the performance of a top-down deep excavation in soil-rock composite stratum. The behavior of the excavation bracing system, consisting of ground anchors and end-suspended piles, has not been well understood due to the lack of relevant research. Based on the observed data of a typical deep excavation case history for the May Fourth Square Station in Tsingtao, China, the characteristics of the horizontal and vertical pile displacements, ground surface settlements, building settlements, axial forces in ground anchors, earth pressure, and pore water pressure during excavation were analysed. Two-dimensional finite element simulations were carried out to further explore the deformation and internal force responses of end-suspended piles and to capture the effects of pile diameter, embedded depth, and rock-socketed depth on the horizontal displacement and bending moment distributions along the pile shaft. It was found that the pattern of the vertical pile displacements could be categorized into three types: rapid settlement, slow settlement, and rapid heave. The magnitudes of the ground and building responses can be well controlled within allowable limits by combining the top-down method with the adopted bracing system. Among the investigated parameters, pile diameter is dominant in affecting the horizontal pile displacement. The primary influence zone for pile bending moment varies, depending on the parameters. It is recommended that a combination of top-down method, ground anchors, and end-suspended piles be adopted for restraining excavation deformation and lowering construction costs of similar deep excavations in soil-rock composite stratum.
A Feature Selection Method by using Chaotic Cuckoo Search Optimization Algorithm with Elitist Preservation and Uniform Mutation for Data Classification
Authors: Wang Le , Gao Yuelin , Li Jiahang , Wang Xiaofeng
Published: June 2021

Feature selection is an essential step in the preprocessing of data in pattern recognition and data mining. Nowadays, the feature selection problem as an optimization problem can be solved with nature-inspired algorithm. In this paper, we propose an efficient feature selection method based on the cuckoo search algorithm called CBCSEM. The proposed method avoids the premature convergence of traditional methods and the tendency to fall into local optima, and this efficient method is attributed to three aspects. Firstly, the chaotic map increases the diversity of the initialization of the algorithm and lays the foundation for its convergence. Then, the proposed two-population elite preservation strategy can find the attractive one of each generation and preserve it. Finally, Lévy flight is developed to update the position of a cuckoo, and the proposed uniform mutation strategy avoids the trouble that the search space is too large for the convergence of the algorithm due to Lévy flight and improves the algorithm exploitation ability. The experimental results on several real UCI datasets show that the proposed method is competitive in comparison with other feature selection algorithms.
A Novel Autophagy‐Related lncRNA Gene Signature to Improve the Prognosis of Patients with Melanoma
Authors: Ding Yi , Li Tian , Li Min , Tayier Tuersong , Zhang MeiLin , Chen Long , Feng ShuMei
Published: June 2021

Objective. Autophagy and long noncoding RNAs (lncRNAs) have been the focus of research on the pathogenesis of melanoma. However, the autophagy network of lncRNAs in melanoma has not been reported. The purpose of this study was to investigate the lncRNA prognostic markers related to melanoma autophagy and predict the prognosis of patients with melanoma. Methods. We downloaded RNA sequencing data and clinical information of melanoma from the Cancer Genome Atlas. The coexpression of autophagy‐related genes (ARGs) and lncRNAs was analyzed. The risk model of autophagy‐related lncRNAs was established by univariate and multivariate Cox regression analyses, and the best prognostic index was evaluated combined with clinical data. Finally, gene set enrichment analysis was performed on patients in the high‐ and low‐risk groups. Results. According to the results of the univariate Cox analysis, only the overexpression of LINC00520 was associated with poor overall survival, unlike HLA‐DQB1‐AS1, USP30‐AS1, AL645929, AL365361, LINC00324, and AC055822. The results of the multivariate Cox analysis showed that the overall survival of patients in the high‐risk group was shorter than that recorded in the low‐risk group (p < 0.001). Moreover, in the receiver operating characteristic curve of the risk model we constructed, the area under the curve (AUC) was 0.734, while the AUC of T and N was 0.707 and 0.658, respectively. The Gene Ontology was mainly enriched with the positive regulation of autophagy and the activation of the immune system. The results of the Kyoto Encyclopedia of Genes and Genomes enrichment were mostly related to autophagy, immunity, and melanin metabolism. Conclusion. The positive regulation of autophagy may slow the transition from low‐risk patients to high‐risk patients in melanoma. Furthermore, compared with clinical information, the autophagy‐related lncRNA risk model may better predict the prognosis of patients with melanoma and provide new treatment ideas.
MicroRNA-34c-5p Inhibition of NUF2 Suppresses Lung Adenocarcinoma Cell Viability and Invasion
Authors: You Xiaoguang , Ren Haiying , Wen Lijun
Published: June 2021

Background. Lung cancer continues to be a burden worldwide with an estimated 2.09 million new cases of lung cancer and 1.76 million deaths in 2018. MicroRNAs (miRs) are key regulators of gene expression and show their oncogenic or antioncogenic role in human cancers including lung cancer. In this study, we test the hypothesis that miR-34c-5p functions as a candidate antioncomiR in lung adenocarcinoma by targeting NUF2. Methods. The expression pattern of miR-34c-5p and NUF2 was evaluated in 202 biopsy specimens from patients with lung adenocarcinoma and 176 biopsy specimens from patients with benign lung diseases. Interaction between miR-34c-5p and NUF2 was verified by the luciferase-based assay. Cell viability and invasion assays were carried out in cultured A549 cells treated with miR-34c-5p mimic, inhibitor, and siRNA against NUF2. Results. NUF2 was highly expressed in lung adenocarcinoma samples and related to the differentiation degree, TNM stage, and presence of lymph node metastasis (LNM). Patients with NUF2 overexpression had reduced overall survival (OS) and disease-free survival (DFS) compared to patients with underexpression. Cox multivariate analysis revealed that high expression of NUF2, advanced TNM stage, well/moderate differentiation, and existence of LNM were unfavorable prognostic factors. siRNA-mediated knockdown of NUF2 inhibits A549 cell viability and invasion. miR-34c-5p was expressed at a poor level in lung adenocarcinoma samples and related to the differentiation degree, TNM stage, and presence of LNM. miR-34c-5p underexpression contributes to reduced OS and DFS, which was demonstrated as an unfavorable prognostic factor by Cox multivariate analysis. siRNA-mediated knockdown of NUF2 could ablate miR-34c-5p inhibition-mediated effects on A549 cells. Conclusion. Our results prove the hypothesis that miR-34c-5p could suppress lung adenocarcinoma progression by binding to the NUF2 gene. The study is a significant step towards extending our understanding of the mode of miRNA regulation in lung adenocarcinoma.
Impulsive Fractional Semilinear Integrodifferential Equations with Nonlocal Conditions
Authors: Wang Xue , Zhu Bo
Published: June 2021

This paper is devoted to a class of impulsive fractional semilinear integrodifferential equations with nonlocal initial conditions. Based on the semigroup theory and some fixed point theorems, the existence theory of PC-mild solutions is established under the condition of compact resolvent operator. Furthermore, the uniqueness of PC-mild solutions is proved in the case of the noncompact resolvent operator.
Perioperative Nursing Care of Vascular Decompression for Trigeminal Neuralgia under AR Medical Technology
Authors: Liu Zhaoyan , Yang Lili , Ding Lin , Wang Longqin
Published: June 2021

AR technology, also known as AR or virtual reality, refers to a technology that combines and allows interaction of the virtual world on the display system with the real world through the position and angle of the camera video and image analysis technology. This technology is different from VR technology, and its characteristics can be easily explained as follows: when using AR technology, the user’s eyes can see not only the real world but also the virtual world derived from the computer through things in the real world. At present, AR has been widely used in education, engineering, entertainment, and medical fields. In order to provide better perioperative care and bring patients a good nursing experience, this article mainly introduces the perioperative care of vascular decompression in the treatment of trigeminal neuralgia by augmented reality medical technology, in order to provide better care for patients with trigeminal neuralgia. This article proposes the perioperative nursing research method of vascular decompression for the treatment of trigeminal neuralgia under AR medical technology, including an overview of trigeminal neuralgia, perioperative related research, and AR medical technology algorithms, and designs related experiments to study whether AR medical technology can bring good news to nursing. Experimental results show that 96% of patients believe that with the enhancement of realistic medical technology, perioperative vascular decompression care for trigeminal neuralgia can help them recover faster and can be gradually popularized.
Convolutional Neural Network‐Based Fish Posture Classification
Authors: Li Xin , Ding Anzi , Mei Shaojie , Wu Wenjin , Hou Wenguang
Published: June 2021

Fish killing machines can effectively relieve the workers from the backbreaking labour. Generally, it is necessary to ensure the fish to be in unified posture before being input into the automatic fish killing machine. As such, how to detect the actual posture of fish in real time is a new and meaningful issue. Considering that in the actual situation, we only need to determine the four postures which are related to the head, tail, back, and belly of the fish, and we transfer this task into a four‐kind classification problem. As such, the convolutional neural network (CNN) is introduced here to do classification and then to detect the fish’s posture. Before training the network, all sample images are preprocessed to make the fish be horizontal on the image according to the principal component analysis. Meanwhile, the histogram equalization is used to make the grey distribution of different images be close. After that, two kinds of strategies are taken to do classification. The first is a paired binary classification CNN and the second is a four‐category CNN. In addition, three kinds of CNN are adopted. By comparison, the four‐kind classification can obtain better results with error less than 1/1000.
Effect of Abutment Geometry and Luting Agents on the Vertical Marginal Discrepancy of Cast Copings on Implant Abutments: An In Vitro Study
Authors: Rosas Jose , Mayta-Tovalino Frank , Malpartida-Carrillo Violeta , Degregori Arnaldo Munive , Mendoza Roman , Guerrero Maria E.
Published: June 2021

Aim. Vertical marginal discrepancy (VMD) influences the success of implant-supported restorations. However, there is little literature that has investigated the influence of geometry and cementing agent on changes in VMD of metal copings on implant abutments. The objective was to evaluate the effect of the geometry of the abutment and cementing agents on VMD. Methods. Cast copings were cemented on implant abutments customized cylindrical (4, 5.5, and 7 mm) and on hexagonal implant abutments (4 mm) cemented or uncemented molded copings were placed (n = 4, totally 64 samples) with different luting agents. The VMD of the copings were measured in the coping-abutment interface at three reference points using a stereomicroscope. The independent Student’s t test was used for comparison between the two different abutment walls. The post hoc statistical analysis was performed by the Tukey test. Results. There was a significant VMD increase between noncemented and cemented cast copings using different luting agents. Abutment geometry and luting agents significantly influenced the VMD

p
≤
0.05

. Cylindrical abutment at 7 mm in height cemented with different luting agent tested showed significantly higher VMD values than cylindrical abutments of 4 mm

p
=
0.019

. Hexagonal abutments with a 4 mm height showed significantly higher VMD values than cylindrical 4 mm abutments using zinc oxide noneugenol and glass ionomer cements

p
=
0.032

. Conclusions. Abutment geometry and luting agents influence the VMD of cast copings cemented on implant abutment. The higher the cylindrical abutment, the greater the VMD, and hexagonal wall abutments promote greater marginal gap.
Remote Care Assistance in Emergency Department Based on Smart Medical
Authors: Zhou Chengli , Hu Juan , Chen Ni
Published: June 2021

Smart medical care is user-centric, medical information is the main line, and big data, Internet of Things, cloud computing, artificial intelligence, and other technologies are used to establish scientific and accurate information, as well as an efficient and reasonable medical service system. Smart medical plays an important role in alleviating doctor-patient conflicts caused by information asymmetry, regional health differences caused by irrational allocation of medical resources, and improving medical service levels. This article mainly introduces the remote care assistance system of emergency department based on smart medical and intends to provide some ideas and directions for the technical research of patients in emergency department receiving remote care. This paper proposes a research method for remote care assistance in emergency departments based on smart medical, including an overview of remote care based on smart medical, remote care sensor real-time monitoring algorithms based on smart medical, signal detection algorithms, and signal clustering algorithms for smart medical. Remote care in the emergency department assisted in research experiments. The experimental results show that 86.0% of patients like the remote care system based on smart medical studied in this paper.
Genome-Wide Association Studies for Striga asiatica Resistance in Tropical Maize
Authors: Pfunye Arthur , Rwafa Rwafa , Mabasa Stanford , Gasura Edmore
Published: June 2021

Striga asiatica L. is a parasitic weed in cereal crops including maize leading to tremendous yield losses up to 100% under severe infestation. The available S. asiatica control methods include cultural control options such as uprooting and burning the Striga plants before they flower, field sanitation, crop rotation, intercropping, organic matter usage, improved fallows, and application of herbicides. Resource limitation among smallholder farmers renders almost all of the control methods impossible. Development and use of Striga resistant genotypes are seen as the most feasible management option. Marker identification formulates tools that are faster, cheaper, and easier to utilise in breeding for S. asiatica resistance which has low heritability. The objective of this study was to identify single nucleotide polymorphism (SNP) markers for Striga resistance using the genome-wide association study (GWAS). Genotyping by sequencing was done on tropical maize inbred lines followed by their evaluation for Striga resistance. Analysis of variance showed significant (

p
<
0.05

) variation among evaluated genotypes for Striga resistance traits such as germination distance, germination percentage, haustoria root attachments, total Striga plants emerged, total biomass, and growth rate. There were also significant differences (

p
<
0.05

) for cobs, leaves, stems, and roots weight. The broad sense heritability was fairly high (up to 61%) for most traits. The means for derived traits on stress tolerance indices were subjected to a

t

-test, and significant differences (

p
<
0.05

) were found for leaves, stem, roots, shoots, and total biomass. The Manhattan plots from GWAS showed the presence of three SNP markers on chromosome numbers 5, 6, and 7 for total Striga plants emerged. The identified markers for resistance to S. asiatica should be validated and utilised to breed for Striga resistance in tropical maize.
A Competition-Based Unequal Clustering Multihop Approach for Wireless Sensor Networks
Authors: Liu Jing , Su Shoubao , Lu Yuhua , Dong Jun
Published: June 2021

The energy efficiency and stability of wireless sensor networks (WSNs) have always been a hot issue in the research. Clustering is a typical architecture for WSNs, and cluster heads (CHs) play a vital role. Unreasonable CH selection causes a lot of energy consumption. In this paper, we propose a competition-based unequal clustering multihop approach (CUCMA). CHs are selected by competition. First, the cluster radius (CR) of a node is calculated according to the distance to base station (BS). Then, CR is resized based on the number of around nodes. Only the nodes with high residual energy and appropriate distances to the selected CHs maybe become CHs, which are usually closer to the surrounding nodes. CUCMA and four related approaches are simulated in different scenarios. The results are analyzed, and it is proved that CUCMA balances the energy consumption of the CHs and reduces the energy consumption of the whole networks, thus leading to prolong the lifetime of WSNs.