bluuebunny/crossref_metadata_2025 huggingface dataset:
Ecosystems of artificial saline lakes. A case of Lake Magic in Wadi El-Rayan depression (Egypt)
Authors: Anufriieva Elena V. , Goher Mohamed E. , Hussian Abd Ellatif M. , El-Sayed Seilem M. , Hegab Mahmoud H. , Tahoun Usama M. , Shadrin Nickolai V.
Published: July 2020

The Wadi El-Rayan is a depression in the Fayoum oasis collecting agricultural drainage water from the Fayoum. Since 1973, this drainage water formed two man-made lakes. Twenty years ago, a third lake, called Lake Magic was formed. Since this newly formed lake was not yet studied, in January of 2019 we conducted research related to its physico-chemical (ion composition, nutrients, heavy metals, etc.) and biological (phyto-, bacterio- and zooplankton) characteristics. The depth of the lake ranged from 1.5 to 9.0 m, water transparency was up to 4.0 m, and the water temperature was 13.6 °C. The average salinity was 29.1 g/l, and the salinity of drainage waters from agricultural fields was 2.9 g/l. A total of 28 phytoplankton species was identified belonging to Bacillariophyceae (eight species), Dinophyceae (three species), Cyanobacteria (seven species), Chlorophyceae (nine species) and Conjugatophyceae (one species). Chlorophyllacontent varied from 14.3 to 24.2 μg/l. In zooplankton, there were three species of Ciliophora, five of Rotifera, and two Copepoda as well as Nematoda and Cirripedia larvae. Salinity in Lake Magic was much higher than in drainage waters coming in the lake. This is a result of a strong salinity increase in Lake Magic after its creation due to climate aridity, and salinity may markedly increase during the next 20 years along with the sharp changes of the lake's ecosystem.
Factors Influencing Postoperative Recovery and Time Off Work of Patients with Benign Indications for Surgery – Results of a Prospective Study
Authors: Strozyk Sophie , Wernecke Klaus-Dieter , Sehouli Jalid , David Matthias
Published: July 2020

Objectives The study aimed to answer a number of questions: Which medical, psychological and sociodemographic factors affect the recovery of women after gynecological surgery for benign indications? Does patientsʼ health-related quality of life improve after surgical intervention? How long are patients signed off work postoperatively? How do patients assess their own capacity to work?

Method Study population: All women between the ages of 18 and 67 years who underwent gynecological surgery for benign indications at the Charité Campus Virchow Clinic over a 7-month period were consecutively enrolled in the study. Four standardized patient surveys (the first survey [T0] was carried out in hospital, T1 at 1 week, T2 at 6 weeks and T3 at 7 – 8 months after discharge by telephone interview) were carried out using evaluated questionnaires to record patientsʼ recovery (Recovery Index), quality of life (RAND-36), satisfaction, complications, sociodemographic information and time off work with a medical sick note. Relevant medical and demographic data were also collected. Statistical analysis was carried out using univariate statistical tests for descriptive analysis and complex multifactorial statistical procedures to record observations over time.

Results A total of 182 patients were included in this study (participation rate: 70%). Relevant prior operations (p = 0.01), in-hospital (p = 0.004) and postoperative complications (p < 0.001), preoperative psychological wellbeing (p = 0.01), physical functioning (p = 0.005) and postoperative anxiety (p = 0,006) had a significant impact on recovery (Recovery Index) and changed significantly over time (p < 0.001). The invasiveness of the surgery or sociodemographic parameters (including migration background) had no significant effect. Health-related quality of life (measured with the RAND-36 questionnaire) also improved postoperatively. More invasive surgical interventions were associated with longer sick leave times and, to a certain extent, with a poorer evaluation of patientsʼ capacity to work.

Conclusion Recovery after gynecological surgery is a multifactorial process. This survey of a patient population identified psychological and physical factors which influence recovery but did not find significant sociodemographic parameters affecting recovery. Irrespective of these findings, gynecological surgery for benign indications resulted in an improvement in health-related quality of life. Prospective studies need to investigate whether psychological interventions could reduce preoperative fear and thereby improve postoperative recovery.
Proptosis in Otorhinolaryngology: An Overview
Authors: Nazeer Novshaba , Ivaturi Phani Bhushan
Published: July 2020

Introduction Ear, nose and throat (ENT)pathologies can present with proptosis as the early manifestation. The majority of ENT pathologies present with ocular manifestations, due to close anatomical relationship.

Objective To study proptosis in ENT disorders in terms of etiology, pathogenesis, and management.

Methods The present article is a prospective study conducted at a tertiary care center, in Telangana, India. Patients presenting with proptosis secondary to ENT disorders were thoroughly evaluated and subjected to surgical exploration after providing a signed informed consent.

Results Sixty cases of proptosis secondary to ENT disorders have been reported. The most common cause was sinonasal squamous cell carcinoma followed by juvenile nasopharyngeal angiofibroma and allergic fungal rhinosinusitis.

Conclusion Many ENT disorders can present with proptosis. Proptosis needs to be evaluated completely for proper management and to limit the morbidity associated with it.
Nonsurgical Management of Cartilage Defects of the Knee: Who, When, Why, and How?
Authors: Hanaoka Chad , Fausett Cameron , Jayabalan Prakash
Published: July 2020

The nonoperative practitioner managing individuals with cartilage defects should use a patient-centered, multifaceted approach that aims to individualize treatment to provide optimal benefit. These include addressing modifiable risk factors for disease progression and instituting interventions such as weight loss, nutrition, physical activity, and potentially regenerative medicine strategies. This review will focus on these nonoperative treatment strategies with a focus on when treatments are necessary, who will benefit from these approaches, why they are specifically appropriate, and, finally, how these treatments directly modify the structure of a patient's cartilage and resulting symptoms.
A Revisited Diagnosis of Collagen VI Related Muscular Dystrophy in a Patient with a Novel COL6A2 Variant and 21q22.3 Deletion
Authors: Simsek-Kiper Pelin Ozlem , Oguz Sumeyra , Ergen Fatma Bilge , Utine Gulen Eda , Alikasifoglu Mehmet , Haliloglu Goknur
Published: July 2020

The genetic etiology of collagen VI related muscular dystrophies is heterogenous. Genomic deletions in one allele involving COL6A2 or both COL6A1 and COL6A2 unmasking a pathogenic variant in the second nondeleted allele have been described in the etiology. We aimed to report the clinical and molecular findings of a 13-year-old boy with ring chromosome 21 who presented to our clinic with easy fatigability, muscle weakness, and waddling gait. Phenotypic delineation along with chromosomal microarray analysis and DNA sequencing were performed. Affymetrix CytoScan Optima array platform and DNA sequencing revealed a 2,202 kb de novo deletion at 21q22.3, including COL6A1 and COL6A2, and a novel heterozygous variant at position c.2875G > A;p.(Glu959Lys) in COL6A2, respectively. Before his admission to our center, the patient was evaluated for hypotonia elsewhere when he was 15 months old. He was diagnosed with ring chromosome 21 on peripheral blood karyotype analysis; however, no further assessment was performed at that time. He had normal growth with mild dysmorphic facial features, distal laxity, gastrocnemius hypertrophy, proximal muscle weakness, increased lordotic posture with mild flexion contractures at the knees, and gait disturbance. Although the phenotype does not fit into classical Ullrich congenital muscular dystrophies, muscle magnetic resonance imaging (MRI) revealed a complementary pattern consistent with collagen VI related myopathies. Genetic testing confirmed the clinical diagnosis as well. This patient yet represents another example of the effect of large genomic deletions leading to recessive disorders through unmasking a pathogenic variant in the second nondeleted allele.
Do guide dogs have culture? The case of indirect social learning
Authors: Guillo Dominique , Claidière Nicolas
Published: July 2020

In the study of animal behaviour, culture is often seen as the result of direct social transmission from a model to a conspecific. In this essay, we show that unrecognised cultural phenomena are sustained by a special form of indirect social learning (ISL). ISL occurs when an individual B learns a behaviour from an individual A through something produced by A. A’s behavioural products can be chemicals, artefacts, but also, we argue, behaviours of another group or species that are the consequence of A’s actions. For instance, a behaviour—guiding a blind person—can be transmitted from dog A to dog B, because the fact that dog A learns the behaviour creates in the mind of the trainer representations about the efficacy of the training practice that can be transmitted to another human, who can then train dog B. These dog behaviours have all the properties of standard cultural behaviours and spread in some dog populations through the exploitation of the social learning capacities of another group/species. Following this idea requires a change in perspective on how we see the social transmission of behaviours and brings forward the fact that certain cultural practices can spread among animals through a cultural co-evolutionary dynamic with humans or other animals.
New perspectives on emerging advanced materials for sustainability
Authors: MacManus-Driscoll Judith L. , Seshadri Ram , Cheetham Anthony
Published: July 2020

An introduction to the APL Materials Special Issue on “New Perspectives on Emerging Advanced Materials for Sustainability,” by the Guest Editors.
Fetal public Vγ9Vδ2 T cells expand and gain potent cytotoxic functions early after birth
Authors: Papadopoulou Maria , Dimova Tanya , Shey Muki , Briel Libby , Veldtsman Helen , Khomba Nondumiso , Africa Hadn , Steyn Marcia , Hanekom Willem A. , Scriba Thomas J. , Nemes Elisa , Vermijlen David
Published: July 2020

Significance

Early-life immune responses have been described as suboptimal, with neonates and infants being susceptible to infections. Vγ9Vδ2 T cells are the first T lymphocytes to be generated in the human fetus. Their T cell receptor-mediated responses to in vitro stimulation and their effector functions at birth are weaker compared with those in adults, possibly reflecting the need for tolerance in utero. However, here we show that upon transition to the prominent microbial exposure early after birth, public fetal-derived Vγ9Vδ2 T cells expand and differentiate into potent cytotoxic effector cells. Thus, they provide newborns with a first line of antimicrobial effector T cells in order to combat infections in early life.
Influencing choices with conversational primes: How a magic trick unconsciously influences card choices
Authors: Pailhès Alice , Kuhn Gustav
Published: July 2020

Significance

This paper shows that naturally embedding primes within a person’s speech and gestures effectively influences people’s decision making. Likewise, our results dovetail findings from choice blindness literature, illustrating that people often do not know the real reason for their choice. Magicians’ forcing techniques may provide a powerful and reliable way of studying these mental processes, and our paper illustrates how this can be done. Moreover, our results raise the possibility that this form of mind control could be used to effectively manipulate other mental processes.
Metabolic characteristics of large and small extracellular vesicles from pleural effusion reveal biomarker candidates for the diagnosis of tuberculosis and malignancy
Authors: Luo Ping , Mao Kaimin , Xu Juanjuan , Wu Feng , Wang Xuan , Wang Sufei , Zhou Mei , Duan Limin , Tan Qi , Ma Guangzhou , Yang Guanghai , Du Ronghui , Huang Hai , Huang Qi , Li Yumei , Guo Mengfei , Jin Yang
Published: July 2020

Pleural effusion is a common respiratory disease worldwide; however, rapid and accurate diagnoses of tuberculosis pleural effusion (TPE) and malignancy pleural effusion (MPE) remain challenging. Although extracellular vesicles (EVs) have been confirmed as promising sources of disease biomarkers, little is known about the metabolite compositions of its subpopulations and their roles in the diagnosis of pleural effusion. Here, we performed metabolomics and lipidomics analysis to investigate the metabolite characteristics of two EV subpopulations derived from pleural effusion by differential ultracentrifugation, namely large EVs (lEVs, pelleted at 20,000 × g) and small EVs (sEVs, pelleted at 110,000 × g), and assessed their metabolite differences between tuberculosis and malignancy. A total of 579 metabolites, including amino acids, acylcarnitines, organic acids, steroids, amides and various lipid species, were detected. The results showed that the metabolic profiles of lEVs and sEVs overlapped with and difference from each other but significantly differed from those of pleural effusion. Additionally, different type of vesicles and pleural effusion showed unique metabolic enrichments. Furthermore, lEVs displayed more significant and larger metabolic alterations between the tuberculosis and malignancy groups, and their differential metabolites were more closely related to clinical parameters than those of sEV. Finally, a panel of four biomarker candidates, including phenylalanine, leucine, phosphatidylcholine 35:0, and sphingomyelin 44:3, in pleural lEVs was defined based on the comprehensive discovery and validation workflow. This panel showed high performance for distinguishing TPE and MPE, particularly in patients with delayed or missed diagnosis, such as the area under the receiver‐operating characteristic curve (AUC) >0.95 in both sets. We conducted comprehensive metabolic profiling analysis of EVs, and further explored the metabolic reprogramming of tuberculosis and malignancy at the level of metabolites in lEVs and sEVs, providing insight into the mechanism of pleural effusion, and identifying novel biomarkers for diagnosing TPE and MPE.
Possible Tricritical Behavior and Anomalous Lattice Softening in van der Waals Itinerant Ferromagnet Fe3GeTe2 under High Pressure
Authors: Xu Jie-Min , Wang Shu-Yang , Wang Wen-Jun , Zhou Yong-Hui , Chen Xu-Liang , Yang Zhao-Rong , Qu Zhe
Published: July 2020

We present a high-pressure study of van der Waals ferromagnetic metal Fe3GeTe2 through electrical transport and Raman scattering measurements in diamond anvil cells at pressures up to 22.4GPa. Upon compression, the ferromagnetic transition temperature T
c manifested by a kink in resistance curve decreases monotonically and becomes undiscernable around P
c = 10GPa, indicative of suppression of the itinerant ferromagnetism. Meanwhile, by fitting the low temperature resistance to the Fermi liquid behavior of R = R
0 + AT
2, we found that R
0 shows a cusp-like anomaly and the coefficient A diverges around P
c. These transport anomalies imply a tricritical point as commonly observed in itinerant ferromagnets under pressure. Unexpectedly, the Raman-active E
2g
and A
1g
modes soften remarkably after an initial weak hardening and the peak widths of both modes broaden evidently on approaching P
c, followed by complete disappearance of both modes above this critical pressure. A possible underlying mechanism for such anomalous lattice softening near P
c is discussed.
Error analysis for filtered back projection reconstructions in Besov spaces
Authors: Beckmann M , Maass P , Nickel J
Published: July 2020

Filtered back projection (FBP) methods are the most widely used reconstruction algorithms in computerized tomography (CT). The ill-posedness of this inverse problem allows only an approximate reconstruction for given noisy data. Studying the resulting reconstruction error has been a most active field of research in the 1990s and has recently been revived in terms of optimal filter design and estimating the FBP approximation errors in general Sobolev spaces. However, the choice of Sobolev spaces is suboptimal for characterizing typical CT reconstructions. A widely used model are sums of characteristic functions, which are better modelled in terms of Besov spaces

B

q

α
,
p

(

R

2

)

. In particular

B

1

α
,
1

(

R

2

)

with α ≈ 1 is a preferred model in image analysis for describing natural images. In case of noisy Radon data the total FBP reconstruction error

‖
f
−

f

L

δ

‖
⩽
‖
f
−

f

L

‖
+
‖

f

L

−

f

L

δ

‖

splits into an approximation error and a data error, where L serves as regularization parameter. In this paper, we study the approximation error of FBP reconstructions for target functions

f
∈

L

1

(

R

2

)

∩

B

q

α
,
p

(

R

2

)

with positive

α
∉
N

and 1 ⩽ p, q ⩽ ∞. We prove that the L

p
-norm of the inherent FBP approximation error f − f

L
can be bounded above by

‖
f
−

f

L

‖

L

p

(

R

2

)

⩽

c

α
,
q
,
W

L

−
α

|
f

|

B

q

α
,
p

(

R

2

)

under suitable assumptions on the utilized low-pass filter’s window function W. This then extends by classical methods to estimates for the total reconstruction error.
Single-shot phase extraction for fringe projection profilometry using deep convolutional generative adversarial network
Authors: Yang Tao , Zhang Zhongzhi , Li Huanhuan , Li Xiaohan , Zhou Xiang
Published: July 2020

This paper presents a single-shot phase extraction approach based on a deep convolutional generative adversarial network that generates a phase map and a quality mask from an input fringe pattern image. A novel loss function is proposed, and a large-scale (28 800 samples) real fringe pattern dataset is collected to train the network. The experiments demonstrate that the proposed method achieves significantly improved phase extraction accuracy and overcomes the main limitations of Fourier transform profilometry. In addition, the proposed method presents excellent performance for real-time computing, reaching approximately 100 f s−1 with a single GPU. Moreover, the proposed learning-based approach can automatically perform denoising and phase extraction, without any manually set parameters.
Theory of the inverse Faraday effect due to the Rashba spin–oribt interactions: roles of band dispersions and Fermi surfaces
Authors: Tanaka Yasuhiro , Inoue Takashi , Mochizuki Masahito
Published: July 2020

We theoretically study the inverse Faraday effect, i.e., the optical induction of spin polarization with circularly polarized light, by particularly focusing on effects of band dispersions and Fermi surfaces in crystal systems with the spin–orbit interaction (SOI). By numerically solving the time-dependent Schrödinger equation of a tight-binding model with the Rashba-type SOI, we reproduce the light-induced spin polarization proportional to

E

0

2

/

ω

3

where E
0 and ω are the electric-field amplitude and the angular frequency of light, respectively. This optical spin induction is attributed to dynamical magnetoelectric coupling between the light electric field and the electron spins mediated by the SOI. We elucidate that the magnitude and sign of the induced spin polarization sensitively depend on the electron filling. To understand these results, we construct an analytical theory based on the Floquet theorem. The theory successfully explains the dependencies on E
0 and ω and ascribes the electron-filling dependence to a momentum-dependent effective magnetic field governed by the Fermi-surface geometry. Several candidate materials and experimental conditions relevant to our theory and model parameters are also discussed. Our findings will enable us to engineer the magneto-optical responses of matters via tuning the material parameters.
Capacitive effect in ultrafast laser-induced emission from low conductance diamond nanotips
Authors: Torresin Olivier , Mauchain Julien , Borz Mario , Blum Ivan , Vella Angela , Chalopin Benoit
Published: July 2020

Single crystal diamond nanotips reveal a new behavior for ultrafast laser-induced electron emission. Under tightly focused femtosecond laser illumination, electron yield shows a saturation with the laser intensity. When the DC bias is sufficient for dark field emission, large optical intensities can switch off the emission occurring between laser pulses during a few hundred μs, because of the low conductance of the diamond tip. We propose a macroscopic model to combine a capacitive effect with the different conduction and emission mechanisms. This study shows that non-metallic photocathodes offer different perspectives from the conventional metallic ones.
Getting around the cell: physical transport in the intracellular world
Authors: S Mogre Saurabh , Brown Aidan I , Koslover Elena F
Published: July 2020

Eukaryotic cells face the challenging task of transporting a variety of particles through the complex intracellular milieu in order to deliver, distribute, and mix the many components that support cell function. In this review, we explore the biological objectives and physical mechanisms of intracellular transport. Our focus is on cytoplasmic and intra-organelle transport at the whole-cell scale. We outline several key biological functions that depend on physically transporting components across the cell, including the delivery of secreted proteins, support of cell growth and repair, propagation of intracellular signals, establishment of organelle contacts, and spatial organization of metabolic gradients. We then review the three primary physical modes of transport in eukaryotic cells: diffusive motion, motor-driven transport, and advection by cytoplasmic flow. For each mechanism, we identify the main factors that determine speed and directionality. We also highlight the efficiency of each transport mode in fulfilling various key objectives of transport, such as particle mixing, directed delivery, and rapid target search. Taken together, the interplay of diffusion, molecular motors, and flows supports the intracellular transport needs that underlie a broad variety of biological phenomena.
Sparse coupled logistic regression to estimate co-activation and modulatory influences of brain regions
Authors: Bolton Thomas A W , Uruñuela Eneko , Tian Ye , Zalesky Andrew , Caballero-Gaudes César , Van De Ville Dimitri
Published: July 2020

Accurate mapping of the functional interactions between remote brain areas with resting-state functional magnetic resonance imaging requires the quantification of their underlying dynamics. In conventional methodological pipelines, a spatial scale of interest is first selected and dynamic analysis then proceeds at this hypothesised level of complexity. If large-scale functional networks or states are studied, more local regional rearrangements are then not described, potentially missing important neurobiological information. Here, we propose a novel mathematical framework that jointly estimates resting-state functional networks and spatially more localised cross-regional modulations. To do so, the changes in activity of each brain region are modelled by a logistic regression including co-activation coefficients (reflective of network assignment, as they highlight simultaneous activations across areas) and causal interplays (denoting finer regional cross-talks, when one region active at time t modulates the t to t + 1 transition likelihood of another area). A two-parameter

ℓ
1

regularisation scheme is used to make these two sets of coefficients sparse: one controls overall sparsity, while the other governs the trade-off between co-activations and causal interplays, enabling to properly fit the data despite the yet unknown balance between both types of couplings. Across a range of simulation settings, we show that the framework successfully retrieves the two types of cross-regional interactions at once. Performance across noise and sample size settings was globally on par with that of other existing methods, with the potential to reveal more precise information missed by alternative approaches. Preliminary application to experimental data revealed that in the resting brain, co-activations and causal modulations co-exist with a varying balance across regions. Our methodological pipeline offers a conceptually elegant alternative for the assessment of functional brain dynamics and can be downloaded at https://c4science.ch/source/Sparse_logistic_regression.git.
Transformable Fingerprinting with Deep Metric Learning Approach for Indoor Localization
Authors: Zeng Xiangsheng , Xiao Limin , Zhao Ming , Xu Xibin , Li Yunzhou
Published: July 2020

Within state-of-the-art indoor localization approaches, fingerprinting based method is more applicable and easier to integrate into most of today’s commodity Wi-Fi devices such as mobile phones and IOT devices which require low cost and computation burden. However, most fingerprinting systems intrinsically depend on fixed channel propagation environment and thus suffers huge reconstruction cost and high localization error when environment changes. In this paper, we propose a novel transformable fingerprinting localization method based on deep metric learning approaches. Our fingerprinting reconstruction method only requires some fresh measurements of CSI (Channel State Information) on a few reference points (RPs) with all the outdated CSI fingerprinting. Extensive system level simulations on Quadriga show that an average of 0.2m error reduction is achieved when our reconstruction method is applied.
Knowledge Service Model of Port Supply Chain Enterprise Based on Ontology
Authors: Yang Bo , Mao Junqing
Published: July 2020

Under the background of the development of port industry and information age, with the help of the knowledge service theory system and ontology technology to build a smart port supply chain knowledge service model to provide a personalized, intelligent, and diversified knowledge-based service system platform solution to port supply chain enterprises, which is of great significance to realization of port supply chain transformation and upgrading and intelligent integrated operation. Based on the analysis of the demand for knowledge service and the research status of knowledge service in port supply chain during the development and operation of port supply chain, this paper uses ontology technology to build domain ontology knowledge base, which is used to dismantle and integrate the massive digital resources in port supply chain, integrate various multi-source heterogeneous data resources, and standardize the form of knowledge sharing organization. On the basis of this, the paper carries on the calculation and reasoning experiment to the port supply chain ontology. The experiment shows that the ontology technology has good effectiveness and superiority in the knowledge representation and knowledge reasoning of constructing the port supply chain knowledge service system model.
Numerical Simulation of Ice Regime Evolution of Pumped Storage Power Station in Cold Area
Authors: Zhao Haijing , Wang Jun , Zhang Yanhong , Chen Pangpang , Cheng Tiejie
Published: July 2020

The formation, development and melt of ice in pumped storage reservoirs in cold climate are studied by numerical simulation. Based on the theory of ice hydrodynamics and the MFC module of Visual C++ 6.0, a mathematical model of ice regime of pumped storage power station in the form of dialog box was established, which includes the hydraulic calculation module, the temperature diffusion module and the ice sheet thermal fluctuation module. The model was applied in Pushihe pumped storage power stations and the results showed that the simulation results were in good agreement with the prototype observation results. The research results can provide effective technical reference for the selection of anti-ice operation mode and the reserve of frozen storage capacity of pumped storage power station in cold area in winter.
Learning Robust Scene Classification Model with Data Augmentation Based on Xception
Authors: Chen Haiyan , Yang Yu , Zhang Suning
Published: July 2020

Scene classification technology based on computer vision has been widely applied in many fields. However, with the increasing complexity of images, many computer vision classification models are difficult to meet requirements of current scene classification tasks, as they not only require considering the object, background, spatial layout and other information, but also many relationships in the image. Based on the analysis of existing scene classification algorithms and Xception model, an approach that adds optimization from two aspects of data set processing is proposed to solve complicated scene classification tasks. Combined with the image enhancement technology, the serialized image enhancement method is used to expand the dataset and enhance the image features, and takes advantage of the Xception model to extract the image features to obtain the scene classification model with high robustness. The experimental results showed that Xception model was able to deal with scene classification efficiently by making up for the shortcomings of traditional Convolutional Neural Networks (CNN) models in feature extraction and generalization ability.
On Inequalities for S-Convex Function Based on Katugampola Fractional Integral
Authors: Wu Ying
Published: July 2020

The subject of integral inequalities has been considered and studied by many mathematical scholars. Based on Katugampola fractional integrals in this article, authors discuss s-function and obtain some inequalities.
Research on the Design of Network Ordering System for Distribution Network Operation Order
Authors: Sha Shuming , Luo Liming , Du Zhiqiang
Published: July 2020

The command issuing and executed feedback of dispatching operation order in distribution network is hanging from traditional telephone mode to network mode. Based on the event driven architecture, this paper implements a network ordering system for distribution network operation order, which can be flexibly configured and deployed. It is compatible with intranet site, mobile app, artificial intelligence voice and other command modes, and it supports real-time telemetry data verification of Distribution Automation System. Asynchronous and low coupling design between command channels reduces the overall logic complexity of the system, and improves the adaptability to requirements.
The Design and Implementation of an Augmented Reality Scheme Based on Netty Communication
Authors: Gao Yongping , Wang Jie , Zhang Jingzhong
Published: July 2020

This paper introduces a whole project of augmented reality interaction mode based on netty communication method, determines the main technical difficulties in the implementation process, and finds the solution by means of system architecture design and communication protocol development. In this paper, the netty framework is adopted to deal with network IO and business logic, and the communication between each terminal device, virtual environment and server is established through long connection, This paper adopts the netty framework to deal with network IO and business logic, establishes communication between each terminal device and virtual environment and server through long connection, so as to realize fast and natural real-time interaction between various interactive devices and other augmented reality devices and virtual environments under multiple users. It can also solve the problem of high concurrency of real-time communication between various devices and the virtual environment in augmented reality.
Vehicle and Driver Detection on Highway Based on Cascade R-CNN
Authors: Geng Yifei , Lu Xiaobo
Published: July 2020

Vehicle and driver detection in the highway scene has been a research hotspot in the field of object detection in recent years, and it is still a challenging problem in the research of traffic order and road safety. In this paper, we propose a novel end-to-end vehicle and driver detection method named VDDNet which is based on Cascade R-CNN and SENet. By introducing FPN structure and SENet attention mechanism in the backbone, the ability of the model to learn effective features is enhanced. It can improve the accuracy of detection in difficult scenes such as weak light, partial occlusion, and low picture resolution. The test results based on the database of highway traffic vehicle and drivers constructed by the Jiangsu Provincial Public Security Department. It shows that the detection method has the AP rate of 91.3% and the Recall rate of 92.4%, which demonstrates the effectiveness of the proposed method in complex highway environments.
Design of Employee Comment Sentiment Analysis Platform Based on AE-SVM Algorithm
Authors: Zhang Yongxiong , Wang Liangming
Published: July 2020

In order to solve the high-dimensional data set of employees’ sentiment analysis on enterprise comment, in this paper, we presented three model algorithms: SVM algorithm, PCA-SVM algorithm, and AE-SVM algorithm. And we made a comparative analysis of three index parameters such as the precision, recall and F1 in three different algorithm model scenarios. According to the experimental results, the AE-SVM algorithm is superior to other two algorithms in this kind of Chinese text sentiment analysis. Based on the AE-SVM Algorithm, we also design a solution of sentiment analysis platform of employee comment. This solution has the characteristics of high availability and high concurrency. It can also collect and analyse the sentiment text information of employees’ comment in time.
Comments Prediction Model on Emotional Analysis Based on Bayes Classification
Authors: Chen Xuegang , Duan Sheng , Wang Luda
Published: July 2020

The comments of e-commerce platform are the information feedback of users on the purchase of goods, which shows the concerns and emotional tendencies of the commodity. The research has important research value for enterprises. In this paper, we constructed the analysis model of e-commerce comments. Firstly, reptile obtained data to segment word segmentation, and then use the characteristics of the initial selection model to review data and transfer matrix conversion, using Bayes probability model to prediction work, finally through the prediction error to select the optimal characteristics of the model. Through the empirical study of the commentary data of BOE, the results show the method is effective, and has better performance and higher classification accuracy.
Application of Computer Technology in English Translation
Authors: Yang Ting , Fan Hongbin
Published: July 2020

With the continuous development of economy, communication is increasing between China and overseas, and business activities are becoming more and more frequent. In this process, foreign trade English plays an important role. Foreign trade English is unique, professional and practical. Under different scenes of foreign trade, English words can express different meanings. In the course of trade, foreign trade English can help both of parties to communicate, and can achieve the translation of language, the interpretation of contract, the understanding of letter and so on. In the process of language communication and reading important documents, we need a solid foundation of English language and profound foreign cultural background, and have a strong ability to deal with the professional knowledge of international trade and the use of English vocabulary. The characteristics of foreign trade English language are analyzed in terms of vocabulary, style and grammar. At the same time, in the process of language understanding and translation, we need to meet the requirements of real-time. With the frequent exchange of foreign trade between our country and other countries, a large number of English documents will be produced, the relevant departments have put forward higher requirements for the accuracy of these documents and real time of these documents, the traditional manual translation can not meet the growing demand for foreign trade translation. With the help of computer aided-translation software memoQ, we help people do auxiliary translation, therefore, it can reduce translator’s burden and improve the accuracy of translation and efficiency of translation. We select a large number of texts and adopt memoQ software to translate, so as to analyze the role of computer-aided translation software in the translation process of English documents.
Rotary Kiln Combustion State Recognition Based on Convolutional Neural Network
Authors: Li Tao , Peng Tao , Chen Hua
Published: July 2020

The accurate recognition of combustion state is an important part of combustion control system. The rotary kiln is nonlinear, large lag, multi-disturbance and multivariable in the combustion process, so it is difficult to realize the intelligent control of the rotary kiln. Moreover, the traditional image recognition method is easily affected by the external environment, and the accuracy of recognition depends on the extraction of artificial features, so the satisfactory results can not be obtained. In order to solve these problems, a method of flame image recognition of combustion state in rotary kiln based on convolution neural network is proposed in this paper. In this method, convolution neural network vgg-16 model is used for feature migration, and the flame images of different combustion states in rotary kiln are trained and tested by network in order to achieve the purpose of automatic recognition of combustion state. The experimental results show that the combustion control system based on convolution neural network image recognition is effective, robust and has high accuracy. Compared with the traditional image recognition method, this method can ahieve more effective accurate and more reliable automatic classification effect.
Design and Implementation of A Website Record Management System Supporting Automatic Verification in IPv6 Transition Phase
Authors: Zhou Jingjing , Deng Gengsheng , Fu Aiying , Lu Zhe
Published: July 2020

Website information registration and filing is the basis of website information security management. In view of the current situation of various websites and increasingly severe network security in Colleges and universities, in order to better manage the websites in Colleges and universities, this paper takes the network environment in the transition stage of IPv6 as an example to design and implement the website filing management system architecture supporting automatic verification. This paper analyzes the methods and shortcomings of the improvement of the traditional website filing management system in the domestic universities, and puts forward the automatic verification mechanism which can actively distinguish the content and status of the website, and actively realize the verification of the filing information by means of scanning detection, page collection, access control, etc., designs and introduces the process of the automatic verification in detail Lists the main code for page collection and reverse proxy services. The actual application shows that the filing management system supporting automatic verification can realize the automatic verification and recording of the information of the completed filing website, detect the website services existing in the managed network, and check out the sites that have not been record, greatly reducing the workload of the management personnel to check the website filing information, and improving the timeliness of the website filing management. Statistics show that IPv6 link access support has become a problem that must be considered by colleges and universities in the transition phase of IPv6. The architecture is based on open source software, and can be used in other universities or similar network environment with only a few configuration and code modification.
Research on Intelligent Tourism Town Based on AI Technology
Authors: Wei Wei , Lin Qian
Published: July 2020

With the understanding of “intelligent Earth”deepening in everyone’s heart, the combination of intelligence and tourism has become the focus of researches. Today, tourism towns are booming in China, which gradually become new growth point of economy and new highlight of urban and rural overall development. This paper discusses tourism town construction with AI technology, analyses problems and shortcomings in tourism town Intelligence construction under present circumstance of smart tourism development and purposes ways and strategies to construct smart towns.
Design of Big Data Platform for Automatic Production Line of Handicraft Structure
Authors: Zhang Yangzhi
Published: July 2020

The automation production line of handicraft structural parts are taken as the research object in this paper, and big data platform is constructed through data modeling, data collection, data analysis and data visualization technologies, including data perception layer, communication layer, storage layer and analysis and display layer. The data acquisition layer obtains the multi-source heterogeneous information source at the bottom of the handicraft processing workshop, transmits it to the big data platform based on the OPC UA protocol for the data analysis of equipment status, production efficiency, product quality and other data, and displays the results through the visualization technology in real time to realize the real-time dynamic control of the handicraft processing process.
Research on Image Visual Information Coordinate Transformation Model Algorithm
Authors: Yuan Liping
Published: July 2020

80% of the information obtained by human beings comes from vision, using pictures and videos as information carriers, and the information obtained from them is called visual intelligence. Visual intelligence analysis refers to extracting the size, distance, speed and other parameter information of the target object from the picture, video. In real life, some measuring tools can be used to get the size, distance and speed of the object Equal parameter information, but only through the picture is not directly available Arbitrary The actual distance between the two points needs to establish a transformation model between the plane coordinate system of the image and the actual coordinate system of the image. The mapping between the actual coordinate system and the phase plane coordinate system is established, the mapping relationship between the pixel plane and the pavement coordinate plane and the imaging model of the monocular camera are established. The vanishing point algorithm is used to calculate the distance from the focus to the center of light and the angle between the optical axis and the ground To achieve Based on the picture Picture actual distance between the target objects to facilitate the intelligence analysis of various picture information.
An Automated Recognition Model for Sensitive Information
Authors: Guo Dongdan , Sun Hao , Zhu Tao , Cai Chang
Published: July 2020

Civil aviation business system carries a lot of passenger information. How to strengthen the management and use of civil aviation passenger information has become an important issue for the civil aviation industry. For the sensitive passenger information with huge data type and quantity, it is extremely inefficient to comb and analyze it manually alone. In this paper, we establish an automatic sensitive information identification model to effectively identify the passenger sensitive information in structured and unstructured files, improve the identification efficiency of sensitive information in civil aviation business system and the ability of data security management.
SINR-Based Time Domain Synthesis Algorithm for Radar
Authors: Li Shumin , Wang Bin , Qu Shihan , Liu Wei , Xin Fengming
Published: July 2020

For optimal radar waveform design and multi-target recognition in cognitive radar, a time-domain synthetic algorithm based on the water-filling algorithm is proposed. We consider the energy spectrum distribution of the synthesized signal based on the signal to interference plus noise ratio (SINR) in the presence of clutter. Simulation results show that after adding phase information, the time-domain synthesis algorithm based on SINR can obtain more target information than the general water-filling algorithm.
Design of Dual-channel HD Audio and Video Recording and Playback Equipment Based on TMS320DM8168
Authors: Zeng Fanchang , Hu Jingying , Zhao Dewei , Zhu Xiaowei
Published: July 2020

In order to meet the needs of dual-channel high-resolution audio and video recording, storage, and playback, as well as important control scenarios such as shipboard, vehicle, and airborne, the need for long-term capture and recording of terminal screen information is convenient for post-event technical analysis, Service quality assessment, exercise deduction, and operation accident responsibility identification. Researched the high-performance DaVinci series chip TMS320DM8168 launched by TI, designed and implemented a record playback device that supports dual-channel high-definition video, using the compression algorithm of the H.264 encoding standard to achieve compression and storage of video data, Use advanced and mature technology, follow the generalized, modular and serial design ideas to ensure better applicability and higher reliability. After the design was completed, the functions of video capture, compression encoding and video playback were verified, and the performance and stability were tested. The delay of video capture and display is within 40ms, The equipment can support high-definition single-channel or dual-channel video input, and realize two channels video information is compressed and stored, while the video decompression is stable, the playback picture is clear, and there is no jitter. The system functions and performance reach the expected goals.
Solving Power System Economic Dispatch Problem Based on Genetic Algorithm
Authors: Ren Yaming
Published: July 2020

With the rapid development of the world economy, the demand for power load is also growing rapidly. The power system economic dispatch problem studied in this paper is to reduce the fuel cost of generator units on the premise of satisfying some series of constraints of power system. In this paper, genetic algorithm is adopted as the solution strategy for power system economic dispatch problem, and the penalty function is used to deal with the equality constraint condition in the power system economic dispatch problem. Finally, we use the genetic algorithm to solve the IEEE-9 notes power system economic dispatch problem and give the corresponding simulation results. The simulation results show that the genetic algorithm can solve the power system economic dispatch problem effectively.
Research on the Development of Smart Rural Tourism in Shandong Province in the Era of Internet
Authors: Wang Ainiao
Published: July 2020

In the era of Internet with the rapid development of modern information technology, the cross-border integration of Internet and industry become a general trend, and smart tourism and smart rural tourism in China are born at the right moment. This paper analyzes the existing problems in the development of smart rural tourism in Shandong Province, puts forward four approaches to accelerate the construction of the basic guarantee system of smart rural tourism, construct the smart rural tourism service system and smart rural tourism marketing system, and strengthen the cultivation of smart rural tourism talents in Shandong Province, carries out the intelligent communication of rural tourism information in Shandong Province, promotes the demand and supply of tourists and rural tourism, and realizes the transformation and upgrading and smart development of rural tourism in Shandong Province.